Self-* and Adaptive Mechanisms for Large Scale Distributed Systems

Science.gov (United States)

Fragopoulou, P.; Mastroianni, C.; Montero, R.; Andrjezak, A.; Kondo, D.

Large-scale distributed computing systems and infrastructure, such as Grids, P2P systems and desktop Grid platforms, are decentralized, pervasive, and composed of a large number of autonomous entities. The complexity of these systems is such that human administration is nearly impossible and centralized or hierarchical control is highly inefficient. These systems need to run on highly dynamic environments, where content, network topologies and workloads are continuously changing. Moreover, they are characterized by the high degree of volatility of their components and the need to provide efficient service management and to handle efficiently large amounts of data. This paper describes some of the areas for which adaptation emerges as a key feature, namely, the management of computational Grids, the self-management of desktop Grid platforms and the monitoring and healing of complex applications. It also elaborates on the use of bio-inspired algorithms to achieve self-management. Related future trends and challenges are described.

Towards more efficient e-learning, intelligence and adapted teaching material

Directory of Open Access Journals (Sweden)

Damir Kalpić

2010-12-01

Full Text Available This article presents results of a research project in which we attempted to determine the relationship between efficient E-learning and teaching materials adapted based on students’ structure of intelligence. The project was conducted on approximately 500 students, 23 classes, nine elementary schools, with ten teachers of history, informatics and several licensed psychologists. E-teaching material was prepared for the subject of History for eight-grade students of elementary school. Students were tested for the structure of intelligence, and based on their most prominent component, they were divided into groups, using teaching materials adapted to their most prominent intelligence component. The results have shown that use of the adapted teaching materials achieved 6-12% better results than E-materials not adapted to students’ structure of intelligence.

Next generation intelligent environments ambient adaptive systems

CERN Document Server

Nothdurft, Florian; Heinroth, Tobias; Minker, Wolfgang

2016-01-01

This book covers key topics in the field of intelligent ambient adaptive systems. It focuses on the results worked out within the framework of the ATRACO (Adaptive and TRusted Ambient eCOlogies) project. The theoretical background, the developed prototypes, and the evaluated results form a fertile ground useful for the broad intelligent environments scientific community as well as for industrial interest groups. The new edition provides: Chapter authors comment on their work on ATRACO with final remarks as viewed in retrospective Each chapter has been updated with follow-up work emerging from ATRACO An extensive introduction to state-of-the-art statistical dialog management for intelligent environments Approaches are introduced on how Trust is reflected during the dialog with the system.

Adaptive Scaling of Cluster Boundaries for Large-Scale Social Media Data Clustering.

Science.gov (United States)

Meng, Lei; Tan, Ah-Hwee; Wunsch, Donald C

2016-12-01

The large scale and complex nature of social media data raises the need to scale clustering techniques to big data and make them capable of automatically identifying data clusters with few empirical settings. In this paper, we present our investigation and three algorithms based on the fuzzy adaptive resonance theory (Fuzzy ART) that have linear computational complexity, use a single parameter, i.e., the vigilance parameter to identify data clusters, and are robust to modest parameter settings. The contribution of this paper lies in two aspects. First, we theoretically demonstrate how complement coding, commonly known as a normalization method, changes the clustering mechanism of Fuzzy ART, and discover the vigilance region (VR) that essentially determines how a cluster in the Fuzzy ART system recognizes similar patterns in the feature space. The VR gives an intrinsic interpretation of the clustering mechanism and limitations of Fuzzy ART. Second, we introduce the idea of allowing different clusters in the Fuzzy ART system to have different vigilance levels in order to meet the diverse nature of the pattern distribution of social media data. To this end, we propose three vigilance adaptation methods, namely, the activation maximization (AM) rule, the confliction minimization (CM) rule, and the hybrid integration (HI) rule. With an initial vigilance value, the resulting clustering algorithms, namely, the AM-ART, CM-ART, and HI-ART, can automatically adapt the vigilance values of all clusters during the learning epochs in order to produce better cluster boundaries. Experiments on four social media data sets show that AM-ART, CM-ART, and HI-ART are more robust than Fuzzy ART to the initial vigilance value, and they usually achieve better or comparable performance and much faster speed than the state-of-the-art clustering algorithms that also do not require a predefined number of clusters.

Iterative learning-based decentralized adaptive tracker for large-scale systems: a digital redesign approach.

Science.gov (United States)

Tsai, Jason Sheng-Hong; Du, Yan-Yi; Huang, Pei-Hsiang; Guo, Shu-Mei; Shieh, Leang-San; Chen, Yuhua

2011-07-01

In this paper, a digital redesign methodology of the iterative learning-based decentralized adaptive tracker is proposed to improve the dynamic performance of sampled-data linear large-scale control systems consisting of N interconnected multi-input multi-output subsystems, so that the system output will follow any trajectory which may not be presented by the analytic reference model initially. To overcome the interference of each sub-system and simplify the controller design, the proposed model reference decentralized adaptive control scheme constructs a decoupled well-designed reference model first. Then, according to the well-designed model, this paper develops a digital decentralized adaptive tracker based on the optimal analog control and prediction-based digital redesign technique for the sampled-data large-scale coupling system. In order to enhance the tracking performance of the digital tracker at specified sampling instants, we apply the iterative learning control (ILC) to train the control input via continual learning. As a result, the proposed iterative learning-based decentralized adaptive tracker not only has robust closed-loop decoupled property but also possesses good tracking performance at both transient and steady state. Besides, evolutionary programming is applied to search for a good learning gain to speed up the learning process of ILC. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

A Decentralized Multivariable Robust Adaptive Voltage and Speed Regulator for Large-Scale Power Systems

Science.gov (United States)

Okou, Francis A.; Akhrif, Ouassima; Dessaint, Louis A.; Bouchard, Derrick

2013-05-01

This papter introduces a decentralized multivariable robust adaptive voltage and frequency regulator to ensure the stability of large-scale interconnnected generators. Interconnection parameters (i.e. load, line and transormer parameters) are assumed to be unknown. The proposed design approach requires the reformulation of conventiaonal power system models into a multivariable model with generator terminal voltages as state variables, and excitation and turbine valve inputs as control signals. This model, while suitable for the application of modern control methods, introduces problems with regards to current design techniques for large-scale systems. Interconnection terms, which are treated as perturbations, do not meet the common matching condition assumption. A new adaptive method for a certain class of large-scale systems is therefore introduces that does not require the matching condition. The proposed controller consists of nonlinear inputs that cancel some nonlinearities of the model. Auxiliary controls with linear and nonlinear components are used to stabilize the system. They compensate unknown parametes of the model by updating both the nonlinear component gains and excitation parameters. The adaptation algorithms involve the sigma-modification approach for auxiliary control gains, and the projection approach for excitation parameters to prevent estimation drift. The computation of the matrix-gain of the controller linear component requires the resolution of an algebraic Riccati equation and helps to solve the perturbation-mismatching problem. A realistic power system is used to assess the proposed controller performance. The results show that both stability and transient performance are considerably improved following a severe contingency.

Using Emotional Intelligence in Personalized Adaptation

NARCIS (Netherlands)

Damjanovic, Violeta; Kravcik, Milos

2008-01-01

Damjanovic, V. & Kravcik, M. (2007). Using Emotional Intelligence in Personalized Adaptation. In M. D. Lytras & A. Naeve (Eds.), Ubiquitous and Pervasive Knowledge and Learning Management (pp. 158-197). IGI Publishing.

Adaptation and hybridization in computational intelligence

CERN Document Server

Jr, Iztok

2015-01-01

  This carefully edited book takes a walk through recent advances in adaptation and hybridization in the Computational Intelligence (CI) domain. It consists of ten chapters that are divided into three parts. The first part illustrates background information and provides some theoretical foundation tackling the CI domain, the second part deals with the adaptation in CI algorithms, while the third part focuses on the hybridization in CI. This book can serve as an ideal reference for researchers and students of computer science, electrical and civil engineering, economy, and natural sciences that are confronted with solving the optimization, modeling and simulation problems. It covers the recent advances in CI that encompass Nature-inspired algorithms, like Artificial Neural networks, Evolutionary Algorithms and Swarm Intelligence –based algorithms.  

Intelligent Optical Systems Using Adaptive Optics

Science.gov (United States)

Clark, Natalie

2012-01-01

Until recently, the phrase adaptive optics generally conjured images of large deformable mirrors being integrated into telescopes to compensate for atmospheric turbulence. However, the development of smaller, cheaper devices has sparked interest for other aerospace and commercial applications. Variable focal length lenses, liquid crystal spatial light modulators, tunable filters, phase compensators, polarization compensation, and deformable mirrors are becoming increasingly useful for other imaging applications including guidance navigation and control (GNC), coronagraphs, foveated imaging, situational awareness, autonomous rendezvous and docking, non-mechanical zoom, phase diversity, and enhanced multi-spectral imaging. The active components presented here allow flexibility in the optical design, increasing performance. In addition, the intelligent optical systems presented offer advantages in size and weight and radiation tolerance.

Emotional intelligence scale for medical students

Directory of Open Access Journals (Sweden)

Kalpana Srivastava

2011-01-01

Full Text Available Background: Emotional Intelligence has been associated with positive outcome process in varied professions. There is paucity of Indian literature on the subject; especially involving medical undergraduates; and presently there is no scale available to measure the same in the Indian scenario. Objective: To develop a scale to measure Emotional Intelligence among medical undergraduates. Materials and Methods: Four domains of Emotional intelligence were selected, viz. Self-Awareness, Self-Management, Social-Awareness & Social-Skills and these were included for the purpose of domains of the scale. On the basis of focused group discussions and in-depth deliberations with experts, undergraduate and postgraduate medical students a pool of 50 items was generated. The items were reduced to 27 based on expert consensus and on the basis of frequency of endorsement by expert reviews. It was followed by a pilot study of 50 undergraduates. This completed the preparation of the preliminary draft based on content analysis. The questionnaire was then administered in 480 students and the data was analyzed by appropriate statistical methods. For the purpose of concurrent validity, emotional intelligence scale developed by Dr. Ekta was used. Results: The Cronbach′s Alpha for Internal Consistency Reliability was 0.68. The EIS had a significant correlation with social awareness domain of Emotional Intelligence Test (EIT establishing Concurrent Validity. Conclusion: Emotional Intelligence Scale for medical undergraduates was constructed. Reliability and concurrent validity were also established for the same.

The Relationship between the Wechsler Intelligence Scale for Children-Revised and the Wechsler Intelligence Scale for Children-III Scales and Subtests for Gifted Children.

Science.gov (United States)

Sabatino, David A.; And Others

1995-01-01

This study determines the comparability of the Wechsler Intelligence Scale for Children-Revised and the Wechsler Intelligence Scale for Children-III in relation to gifted children. Results indicate that both tests produce remarkably similar scale and subtest scores when administered under clinical conditions. (JPS)

Distributed Model Predictive Control over Multiple Groups of Vehicles in Highway Intelligent Space for Large Scale System

Directory of Open Access Journals (Sweden)

Tang Xiaofeng

2014-01-01

Full Text Available The paper presents the three time warning distances for solving the large scale system of multiple groups of vehicles safety driving characteristics towards highway tunnel environment based on distributed model prediction control approach. Generally speaking, the system includes two parts. First, multiple vehicles are divided into multiple groups. Meanwhile, the distributed model predictive control approach is proposed to calculate the information framework of each group. Each group of optimization performance considers the local optimization and the neighboring subgroup of optimization characteristics, which could ensure the global optimization performance. Second, the three time warning distances are studied based on the basic principles used for highway intelligent space (HIS and the information framework concept is proposed according to the multiple groups of vehicles. The math model is built to avoid the chain avoidance of vehicles. The results demonstrate that the proposed highway intelligent space method could effectively ensure driving safety of multiple groups of vehicles under the environment of fog, rain, or snow.

Relationships between the Kaufman Brief Intelligence Test and the Wechsler Adult Intelligence Scale-Third Edition.

Science.gov (United States)

Walters, Steven O; Weaver, Kenneth A

2003-06-01

The Kaufman Brief Intelligence Test detects learning problems of young students and is a screen for whether a more comprehensive test of intelligence is needed. A study to assess whether this test was valid as an adult intelligence test was conducted with 20 undergraduate psychology majors. The correlations between the Kaufman Brief Intelligence Test's Composite, Vocabulary, and Matrices test scores and their corresponding Wechsler Adult Intelligence Scale-Third Edition test scores, the Full Scale (r=.88), Verbal (r=.77), and Performance scores (r=.87), indicated very strong relationships. In addition, no significant differences were obtained between the Composite, Vocabulary, and Matrices means of the Kaufman Brief Intelligence Test and the Full Scale, Verbal, and Performance means of the WAIS-III. The Kaufman Brief Intelligence Test appears to be a valid test of intelligence for adults.

Estimation of the Intelligence Quotient Using Wechsler Intelligence Scales in Children and Adolescents with Asperger Syndrome

Science.gov (United States)

Merchan-Naranjo, Jessica; Mayoral, Maria; Rapado-Castro, Marta; Llorente, Cloe; Boada, Leticia; Arango, Celso; Parellada, Mara

2012-01-01

Asperger syndrome (AS) patients show heterogeneous intelligence profiles and the validity of short forms for estimating intelligence has rarely been studied in this population. We analyzed the validity of Wechsler Intelligence Scale (WIS) short forms for estimating full-scale intelligence quotient (FSIQ) and assessing intelligence profiles in 29…

Large-Scale 3D Printing: The Way Forward

Science.gov (United States)

Jassmi, Hamad Al; Najjar, Fady Al; Ismail Mourad, Abdel-Hamid

2018-03-01

Research on small-scale 3D printing has rapidly evolved, where numerous industrial products have been tested and successfully applied. Nonetheless, research on large-scale 3D printing, directed to large-scale applications such as construction and automotive manufacturing, yet demands a great a great deal of efforts. Large-scale 3D printing is considered an interdisciplinary topic and requires establishing a blended knowledge base from numerous research fields including structural engineering, materials science, mechatronics, software engineering, artificial intelligence and architectural engineering. This review article summarizes key topics of relevance to new research trends on large-scale 3D printing, particularly pertaining (1) technological solutions of additive construction (i.e. the 3D printers themselves), (2) materials science challenges, and (3) new design opportunities.

Reliability and Validity of the New Tanaka B Intelligence Scale Scores: A Group Intelligence Test

OpenAIRE

Uno, Yota; Mizukami, Hitomi; Ando, Masahiko; Yukihiro, Ryoji; Iwasaki, Yoko; Ozaki, Norio

2014-01-01

OBJECTIVE: The present study evaluated the reliability and concurrent validity of the new Tanaka B Intelligence Scale, which is an intelligence test that can be administered on groups within a short period of time. METHODS: The new Tanaka B Intelligence Scale and Wechsler Intelligence Scale for Children-Third Edition were administered to 81 subjects (mean age ± SD 15.2 ± 0.7 years) residing in a juvenile detention home; reliability was assessed using Cronbach's alpha coefficient, and concurre...

Age Effects on Wechsler Adult Intelligence Scale-Revised Tests.

Science.gov (United States)

Sattler, Jerome M.

1982-01-01

Studied age norms for 11 individual Wechsler Adult Intelligence Scale-Revised (WAIS-R) tests. Digit Symbol showed the most decline. Results suggest that fluid intelligence, as measured by the performance scale tests, shows more of a decline with age than crystallized intelligence, as measured by the verbal scale tests. (Author)

External validity of the Indonesian Wechsler Adult Intelligence Scale - Fourth edition (WAIS-IV-ID)

NARCIS (Netherlands)

Suwartono, C.; Hidajat, L.L.; Halim, M.S.; Hendriks, M.P.H.; Kessels, R.P.C.

2016-01-01

The Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV-ID) has been adapted and proved to be valid for its internal structure for Indonesian population. The same structure found as in the American WAIS-IV (WAIS-IV-US; Suwartono, Hendriks, Hidajat, Halim, & Kessels, 2015). Despite its strong

Adaptive Intelligent Ventilation Noise Control, Phase II

Data.gov (United States)

National Aeronautics and Space Administration — To address the NASA need for quiet on-orbit crew quarters (CQ), Physical Optics Corporation (POC) proposes to develop a new Adaptive Intelligent Ventilation Noise...

Adaptive Intelligent Ventilation Noise Control, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — To address NASA needs for quiet crew volumes in a space habitat, Physical Optics Corporation (POC) proposes to develop a new Adaptive Intelligent Ventilation Noise...

Map Matching for Intelligent Speed Adaptation

DEFF Research Database (Denmark)

Tradisauskas, Nerius; Juhl, Jens; Lahrmann, Harry

2007-01-01

The availability of Global Navigation Satellite Systems enables sophisticated vehicle guidance and advisory systems such as Intelligent Speed Adaptation (ISA) systems. In ISA systems, it is essential to be able to position vehicles within a road network. Because digital road networks as well as G...

Normal variability of children's scaled scores on subtests of the Dutch Wechsler Preschool and Primary scale of Intelligence - third edition.

Science.gov (United States)

Hurks, P P M; Hendriksen, J G M; Dek, J E; Kooij, A P

2013-01-01

Intelligence tests are included in millions of assessments of children and adults each year (Watkins, Glutting, & Lei, 2007a , Applied Neuropsychology, 14, 13). Clinicians often interpret large amounts of subtest scatter, or large differences between the highest and lowest scaled subtest scores, on an intelligence test battery as an index for abnormality or cognitive impairment. The purpose of the present study is to characterize "normal" patterns of variability among subtests of the Dutch Wechsler Preschool and Primary Scale of Intelligence - Third Edition (WPPSI-III-NL; Wechsler, 2010 ). Therefore, the frequencies of WPPSI-III-NL scaled subtest scatter were reported for 1039 healthy children aged 4:0-7:11 years. Results indicated that large differences between highest and lowest scaled subtest scores (or subtest scatter) were common in this sample. Furthermore, degree of subtest scatter was related to: (a) the magnitude of the highest scaled subtest score, i.e., more scatter was seen in children with the highest WPPSI-III-NL scaled subtest scores, (b) Full Scale IQ (FSIQ) scores, i.e., higher FSIQ scores were associated with an increase in subtest scatter, and (c) sex differences, with boys showing a tendency to display more scatter than girls. In conclusion, viewing subtest scatter as an index for abnormality in WPPSI-III-NL scores is an oversimplification as this fails to recognize disparate subtest heterogeneity that occurs within a population of healthy children aged 4:0-7:11 years.

The dynamic interplay among EFL learners’ ambiguity tolerance, adaptability, cultural intelligence, learning approach, and language achievement

Directory of Open Access Journals (Sweden)

Shadi Alahdadi

2017-01-01

Full Text Available A key objective of education is to prepare individuals to be fully-functioning learners. This entails developing the cognitive, metacognitive, motivational, cultural, and emotional competencies. The present study aimed to examine the interrelationships among adaptability, tolerance of ambiguity, cultural intelligence, learning approach, and language achievement as manifestations of the above competencies within a single model. The participants comprised one hundred eighty BA and MA Iranian university students studying English language teaching and translation. The instruments used in this study consisted of the translated versions of four questionnaires: second language tolerance of ambiguity scale, adaptability taken from emotional intelligence inventory, cultural intelligence (CQ inventory, and the revised study process questionnaire measuring surface and deep learning. The results estimated via structural equation modeling (SEM revealed that the proposed model containing the variables under study had a good fit with the data. It was found that all the variables except adaptability directly influenced language achievement with deep approach having the highest impact and ambiguity tolerance having the lowest influence. In addition, ambiguity tolerance was a positive and significant predictor of deep approach. CQ was found to be under the influence of both ambiguity tolerance and adaptability. The findings were discussed in the light of the yielded results.

Intelligent Adaptation and Personalization Techniques in Computer-Supported Collaborative Learning

CERN Document Server

Demetriadis, Stavros; Xhafa, Fatos

2012-01-01

Adaptation and personalization have been extensively studied in CSCL research community aiming to design intelligent systems that adaptively support eLearning processes and collaboration. Yet, with the fast development in Internet technologies, especially with the emergence of new data technologies and the mobile technologies, new opportunities and perspectives are opened for advanced adaptive and personalized systems. Adaptation and personalization are posing new research and development challenges to nowadays CSCL systems. In particular, adaptation should be focused in a multi-dimensional way (cognitive, technological, context-aware and personal). Moreover, it should address the particularities of both individual learners and group collaboration. As a consequence, the aim of this book is twofold. On the one hand, it discusses the latest advances and findings in the area of intelligent adaptive and personalized learning systems. On the other hand it analyzes the new implementation perspectives for intelligen...

Envisioning engineering education and practice in the coming intelligence convergence era — a complex adaptive systems approach

Science.gov (United States)

Noor, Ahmed K.

2013-12-01

Some of the recent attempts for improving and transforming engineering education are reviewed. The attempts aim at providing the entry level engineers with the skills needed to address the challenges of future large-scale complex systems and projects. Some of the frontier sectors and future challenges for engineers are outlined. The major characteristics of the coming intelligence convergence era (the post-information age) are identified. These include the prevalence of smart devices and environments, the widespread applications of anticipatory computing and predictive / prescriptive analytics, as well as a symbiotic relationship between humans and machines. Devices and machines will be able to learn from, and with, humans in a natural collaborative way. The recent game changers in learnscapes (learning paradigms, technologies, platforms, spaces, and environments) that can significantly impact engineering education in the coming era are identified. Among these are open educational resources, knowledge-rich classrooms, immersive interactive 3D learning, augmented reality, reverse instruction / flipped classroom, gamification, robots in the classroom, and adaptive personalized learning. Significant transformative changes in, and mass customization of, learning are envisioned to emerge from the synergistic combination of the game changers and other technologies. The realization of the aforementioned vision requires the development of a new multidisciplinary framework of emergent engineering for relating innovation, complexity and cybernetics, within the future learning environments. The framework can be used to treat engineering education as a complex adaptive system, with dynamically interacting and communicating components (instructors, individual, small, and large groups of learners). The emergent behavior resulting from the interactions can produce progressively better, and continuously improving, learning environment. As a first step towards the realization of

Adaptive Fuzzy-Lyapunov Controller Using Biologically Inspired Swarm Intelligence

Directory of Open Access Journals (Sweden)

Alejandro Carrasco Elizalde

2008-01-01

Full Text Available The collective behaviour of swarms produces smarter actions than those achieved by a single individual. Colonies of ants, flocks of birds and fish schools are examples of swarms interacting with their environment to achieve a common goal. This cooperative biological intelligence is the inspiration for an adaptive fuzzy controller developed in this paper. Swarm intelligence is used to adjust the parameters of the membership functions used in the adaptive fuzzy controller. The rules of the controller are designed using a computing-with-words approach called Fuzzy-Lyapunov synthesis to improve the stability and robustness of an adaptive fuzzy controller. Computing-with-words provides a powerful tool to manipulate numbers and symbols, like words in a natural language.

Reliability and validity of the new Tanaka B Intelligence Scale scores: a group intelligence test.

Directory of Open Access Journals (Sweden)

Yota Uno

Full Text Available OBJECTIVE: The present study evaluated the reliability and concurrent validity of the new Tanaka B Intelligence Scale, which is an intelligence test that can be administered on groups within a short period of time. METHODS: The new Tanaka B Intelligence Scale and Wechsler Intelligence Scale for Children-Third Edition were administered to 81 subjects (mean age ± SD 15.2 ± 0.7 years residing in a juvenile detention home; reliability was assessed using Cronbach's alpha coefficient, and concurrent validity was assessed using the one-way analysis of variance intraclass correlation coefficient. Moreover, receiver operating characteristic analysis for screening for individuals who have a deficit in intellectual function (an FIQ<70 was performed. In addition, stratum-specific likelihood ratios for detection of intellectual disability were calculated. RESULTS: The Cronbach's alpha for the new Tanaka B Intelligence Scale IQ (BIQ was 0.86, and the intraclass correlation coefficient with FIQ was 0.83. Receiver operating characteristic analysis demonstrated an area under the curve of 0.89 (95% CI: 0.85-0.96. In addition, the stratum-specific likelihood ratio for the BIQ≤65 stratum was 13.8 (95% CI: 3.9-48.9, and the stratum-specific likelihood ratio for the BIQ≥76 stratum was 0.1 (95% CI: 0.03-0.4. Thus, intellectual disability could be ruled out or determined. CONCLUSION: The present results demonstrated that the new Tanaka B Intelligence Scale score had high reliability and concurrent validity with the Wechsler Intelligence Scale for Children-Third Edition score. Moreover, the post-test probability for the BIQ could be calculated when screening for individuals who have a deficit in intellectual function. The new Tanaka B Intelligence Test is convenient and can be administered within a variety of settings. This enables evaluation of intellectual development even in settings where performing intelligence tests have previously been difficult.

Test Review: Wechsler Abbreviated Scale of Intelligence, Second Edition

Science.gov (United States)

Irby, Sarah M.; Floyd, Randy G.

2013-01-01

The Wechsler Abbreviated Scale of Intelligence, Second Edition (WASI-II; Wechsler, 2011) is a brief intelligence test designed for individuals aged 6 through 90 years. It is a revision of the Wechsler Abbreviated Scale of Intelligence (WASI; Wechsler, 1999). During revision, there were three goals: enhancing the link between the Wechsler…

Reliability and validity of the new Tanaka B Intelligence Scale scores: a group intelligence test.

Science.gov (United States)

Uno, Yota; Mizukami, Hitomi; Ando, Masahiko; Yukihiro, Ryoji; Iwasaki, Yoko; Ozaki, Norio

2014-01-01

The present study evaluated the reliability and concurrent validity of the new Tanaka B Intelligence Scale, which is an intelligence test that can be administered on groups within a short period of time. The new Tanaka B Intelligence Scale and Wechsler Intelligence Scale for Children-Third Edition were administered to 81 subjects (mean age ± SD 15.2 ± 0.7 years) residing in a juvenile detention home; reliability was assessed using Cronbach's alpha coefficient, and concurrent validity was assessed using the one-way analysis of variance intraclass correlation coefficient. Moreover, receiver operating characteristic analysis for screening for individuals who have a deficit in intellectual function (an FIQIntelligence Scale IQ (BIQ) was 0.86, and the intraclass correlation coefficient with FIQ was 0.83. Receiver operating characteristic analysis demonstrated an area under the curve of 0.89 (95% CI: 0.85-0.96). In addition, the stratum-specific likelihood ratio for the BIQ≤65 stratum was 13.8 (95% CI: 3.9-48.9), and the stratum-specific likelihood ratio for the BIQ≥76 stratum was 0.1 (95% CI: 0.03-0.4). Thus, intellectual disability could be ruled out or determined. The present results demonstrated that the new Tanaka B Intelligence Scale score had high reliability and concurrent validity with the Wechsler Intelligence Scale for Children-Third Edition score. Moreover, the post-test probability for the BIQ could be calculated when screening for individuals who have a deficit in intellectual function. The new Tanaka B Intelligence Test is convenient and can be administered within a variety of settings. This enables evaluation of intellectual development even in settings where performing intelligence tests have previously been difficult.

Integrating adaptive behaviour in large-scale flood risk assessments: an Agent-Based Modelling approach

Science.gov (United States)

Haer, Toon; Aerts, Jeroen

2015-04-01

Between 1998 and 2009, Europe suffered over 213 major damaging floods, causing 1126 deaths, displacing around half a million people. In this period, floods caused at least 52 billion euro in insured economic losses making floods the most costly natural hazard faced in Europe. In many low-lying areas, the main strategy to cope with floods is to reduce the risk of the hazard through flood defence structures, like dikes and levees. However, it is suggested that part of the responsibility for flood protection needs to shift to households and businesses in areas at risk, and that governments and insurers can effectively stimulate the implementation of individual protective measures. However, adaptive behaviour towards flood risk reduction and the interaction between the government, insurers, and individuals has hardly been studied in large-scale flood risk assessments. In this study, an European Agent-Based Model is developed including agent representatives for the administrative stakeholders of European Member states, insurers and reinsurers markets, and individuals following complex behaviour models. The Agent-Based Modelling approach allows for an in-depth analysis of the interaction between heterogeneous autonomous agents and the resulting (non-)adaptive behaviour. Existing flood damage models are part of the European Agent-Based Model to allow for a dynamic response of both the agents and the environment to changing flood risk and protective efforts. By following an Agent-Based Modelling approach this study is a first contribution to overcome the limitations of traditional large-scale flood risk models in which the influence of individual adaptive behaviour towards flood risk reduction is often lacking.

Emotional Intelligence and Adaptive Success of Nurses Caring for People with Mental Retardation and Severe Behavior Problems

Science.gov (United States)

Gerits, Linda; Derksen, Jan J. L.; Verbruggen, Antoine B.

2004-01-01

The emotional intelligence profiles, gender differences, and adaptive success of 380 Dutch nurses caring for people with mental retardation and accompanying severe behavior problems are reported. Data were collected with the Bar-On Emotional Quotient Inventory, Utrecht-Coping List, Utrecht-Burnout Scale, MMPI-2, and GAMA. Absence due to illness…

Co-evolution of intelligent socio-technical systems modelling and applications in large scale emergency and transport domains

CERN Document Server

2013-01-01

As the interconnectivity between humans through technical devices is becoming ubiquitous, the next step is already in the making: ambient intelligence, i.e. smart (technical) environments, which will eventually play the same active role in communication as the human players, leading to a co-evolution in all domains where real-time communication is essential. This topical volume, based on the findings of the Socionical European research project, gives equal attention to two highly relevant domains of applications: transport, specifically traffic, dynamics from the viewpoint of a socio-technical interaction and evacuation scenarios for large-scale emergency situations. Care was taken to investigate as much as possible the limits of scalability and to combine the modeling using complex systems science approaches with relevant data analysis.

Wechsler Adult Intelligence Scale-IV Dyads for Estimating Global Intelligence.

Science.gov (United States)

Girard, Todd A; Axelrod, Bradley N; Patel, Ronak; Crawford, John R

2015-08-01

All possible two-subtest combinations of the core Wechsler Adult Intelligence Scale-IV (WAIS-IV) subtests were evaluated as possible viable short forms for estimating full-scale IQ (FSIQ). Validity of the dyads was evaluated relative to FSIQ in a large clinical sample (N = 482) referred for neuropsychological assessment. Sample validity measures included correlations, mean discrepancies, and levels of agreement between dyad estimates and FSIQ scores. In addition, reliability and validity coefficients were derived from WAIS-IV standardization data. The Coding + Information dyad had the strongest combination of reliability and validity data. However, several other dyads yielded comparable psychometric performance, albeit with some variability in their particular strengths. We also observed heterogeneity between validity coefficients from the clinical and standardization-based estimates for several dyads. Thus, readers are encouraged to also consider the individual psychometric attributes, their clinical or research goals, and client or sample characteristics when selecting among the dyadic short forms. © The Author(s) 2014.

8th International Symposium on Intelligent Distributed Computing & Workshop on Cyber Security and Resilience of Large-Scale Systems & 6th International Workshop on Multi-Agent Systems Technology and Semantics

CERN Document Server

Braubach, Lars; Venticinque, Salvatore; Badica, Costin

2015-01-01

This book represents the combined peer-reviewed proceedings of the Eight International Symposium on Intelligent Distributed Computing - IDC'2014, of the Workshop on Cyber Security and Resilience of Large-Scale Systems - WSRL-2014, and of the Sixth International Workshop on Multi-Agent Systems Technology and Semantics- MASTS-2014. All the events were held in Madrid, Spain, during September 3-5, 2014. The 47 contributions published in this book address several topics related to theory and applications of the intelligent distributed computing and multi-agent systems, including: agent-based data processing, ambient intelligence, collaborative systems, cryptography and security, distributed algorithms, grid and cloud computing, information extraction, knowledge management, big data and ontologies, social networks, swarm intelligence or videogames amongst others.

OPUS One: An Intelligent Adaptive Learning Environment Using Artificial Intelligence Support

Science.gov (United States)

Pedrazzoli, Attilio

2010-06-01

AI based Tutoring and Learning Path Adaptation are well known concepts in e-Learning scenarios today and increasingly applied in modern learning environments. In order to gain more flexibility and to enhance existing e-learning platforms, the OPUS One LMS Extension package will enable a generic Intelligent Tutored Adaptive Learning Environment, based on a holistic Multidimensional Instructional Design Model (PENTHA ID Model), allowing AI based tutoring and adaptation functionality to existing Web-based e-learning systems. Relying on "real time" adapted profiles, it allows content- / course authors to apply a dynamic course design, supporting tutored, collaborative sessions and activities, as suggested by modern pedagogy. The concept presented combines a personalized level of surveillance, learning activity- and learning path adaptation suggestions to ensure the students learning motivation and learning success. The OPUS One concept allows to implement an advanced tutoring approach combining "expert based" e-tutoring with the more "personal" human tutoring function. It supplies the "Human Tutor" with precise, extended course activity data and "adaptation" suggestions based on predefined subject matter rules. The concept architecture is modular allowing a personalized platform configuration.

Intelligent and Adaptive Educational-Learning Systems Achievements and Trends

CERN Document Server

2013-01-01

The Smart Innovation, Systems and Technologies book series encompasses the topics of knowledge, intelligence, innovation and sustainability. The aim of the series is to make available a platform for the publication of books on all aspects of single and multi-disciplinary research on these themes in order to make the latest results available in a readily-accessible form.  This book is devoted to the “Intelligent and Adaptive Educational-Learning Systems”. It privileges works that highlight key achievements and outline trends to inspire future research.  After a rigorous revision process twenty manuscripts were accepted and organized into four parts as follows: ·     Modeling: The first part embraces five chapters oriented to: 1) shape the affective behavior; 2) depict the adaptive learning curriculum; 3) predict learning achievements; 4) mine learner models to outcome optimized and adaptive e-learning objects; 5) classify learning preferences of learners. ·     Content: The second part encompas...

Adaptive Fuzzy Output-Constrained Fault-Tolerant Control of Nonlinear Stochastic Large-Scale Systems With Actuator Faults.

Science.gov (United States)

Li, Yongming; Ma, Zhiyao; Tong, Shaocheng

2017-09-01

The problem of adaptive fuzzy output-constrained tracking fault-tolerant control (FTC) is investigated for the large-scale stochastic nonlinear systems of pure-feedback form. The nonlinear systems considered in this paper possess the unstructured uncertainties, unknown interconnected terms and unknown nonaffine nonlinear faults. The fuzzy logic systems are employed to identify the unknown lumped nonlinear functions so that the problems of structured uncertainties can be solved. An adaptive fuzzy state observer is designed to solve the nonmeasurable state problem. By combining the barrier Lyapunov function theory, adaptive decentralized and stochastic control principles, a novel fuzzy adaptive output-constrained FTC approach is constructed. All the signals in the closed-loop system are proved to be bounded in probability and the system outputs are constrained in a given compact set. Finally, the applicability of the proposed controller is well carried out by a simulation example.

Classification of intellectual disability using the Wechsler Intelligence Scale for Children: Full Scale IQ or General Abilities Index?

Science.gov (United States)

Koriakin, Taylor A; McCurdy, Mark D; Papazoglou, Aimilia; Pritchard, Alison E; Zabel, T Andrew; Mahone, E Mark; Jacobson, Lisa A

2013-09-01

We examined the implications of using the Full Scale IQ (FSIQ) versus the General Abilities Index (GAI) for determination of intellectual disability using the Wechsler Intelligence Scales for Children, fourth edition (WISC-IV). Children referred for neuropsychological assessment (543 males, 290 females; mean age 10y 5mo, SD 2y 9mo, range 6-16y) were administered the WISC-IV and the Adaptive Behavior Assessment System, second edition (ABAS-II). GAI and FSIQ were highly correlated; however, fewer children were identified as having intellectual disability using GAI (n=159) than when using FSIQ (n=196). Although the 44 children classified as having intellectual disability based upon FSIQ (but not GAI) had significantly higher adaptive functioning scores than those meeting intellectual disability criteria based upon both FSIQ and GAI, mean adaptive scores still fell within the impaired range. FSIQ and GAI were comparable in predicting impairments in adaptive functioning. Using GAI rather than FSIQ in intellectual disability diagnostic decision-making resulted in fewer individuals being diagnosed with intellectual disability; however, the mean GAI of the disqualified individuals was at the upper end of criteria for intellectual impairment (standard score 75), and these individuals remained adaptively impaired. As GAI and FSIQ were similarly predictive of overall adaptive functioning, the use of GAI for intellectual disability diagnostic decision-making may be of limited value. © 2013 Mac Keith Press.

Adaptive Texture Synthesis for Large Scale City Modeling

Science.gov (United States)

Despine, G.; Colleu, T.

2015-02-01

Large scale city models textured with aerial images are well suited for bird-eye navigation but generally the image resolution does not allow pedestrian navigation. One solution to face this problem is to use high resolution terrestrial photos but it requires huge amount of manual work to remove occlusions. Another solution is to synthesize generic textures with a set of procedural rules and elementary patterns like bricks, roof tiles, doors and windows. This solution may give realistic textures but with no correlation to the ground truth. Instead of using pure procedural modelling we present a method to extract information from aerial images and adapt the texture synthesis to each building. We describe a workflow allowing the user to drive the information extraction and to select the appropriate texture patterns. We also emphasize the importance to organize the knowledge about elementary pattern in a texture catalogue allowing attaching physical information, semantic attributes and to execute selection requests. Roofs are processed according to the detected building material. Façades are first described in terms of principal colours, then opening positions are detected and some window features are computed. These features allow selecting the most appropriate patterns from the texture catalogue. We experimented this workflow on two samples with 20 cm and 5 cm resolution images. The roof texture synthesis and opening detection were successfully conducted on hundreds of buildings. The window characterization is still sensitive to the distortions inherent to the projection of aerial images onto the facades.

A novel adaptive synchronization control of a class of master-slave large-scale systems with unknown channel time-delay

Science.gov (United States)

Shen, Qikun; Zhang, Tianping

2015-05-01

The paper addresses a practical issue for adaptive synchronization in master-slave large-scale systems with constant channel time-delay., and a novel adaptive synchronization control scheme is proposed to guarantee the synchronization errors asymptotically converge to the origin, in which the matching condition as in the related literatures is not necessary. The real value of channel time-delay can be estimated online by a proper adaptation mechanism, which removes the conditions that the channel time-delay should be known exactly as in existing works. Finally, simulation results demonstrate the effectiveness of the approach.

Distributed Problem Solving: Adaptive Networks with a Computer Intermediary Resource. Intelligent Executive Computer Communication

Science.gov (United States)

1991-06-01

Proceedings of The National Conference on Artificial Intelligence , pages 181-184, The American Association for Aritificial Intelligence , Pittsburgh...Intermediary Resource: Intelligent Executive Computer Communication John Lyman and Carla J. Conaway University of California at Los Angeles for Contracting...Include Security Classification) Interim Report: Distributed Problem Solving: Adaptive Networks With a Computer Intermediary Resource: Intelligent

Can enriching emotional intelligence improve medical students' proactivity and adaptability during OB/GYN clerkships?

Science.gov (United States)

Guseh, Stephanie H; Chen, Xiaodong P; Johnson, Natasha R

2015-12-26

The purpose of this pilot study was to examine our hypothesis that enriching workplace emotional intelligence through resident coaches could improve third-year medical students' adaptability and proactivity on the Obstetrics and Gynecology clerkship. An observational pilot study was conducted in a teaching hospital. Fourteen 3rd year medical students from two cohorts of clerkships were randomly divided into two groups, and equally assigned to trained resident coaches and untrained resident coaches. Data was collected through onsite naturalistic observation of students' adaptability and proactivity in clinical settings using a checklist with a 4-point Likert scale (1=poor to 4=excellent). Wilcoxon rank-sum test was used to compare the differences between these two groups. A total of 280 data points were collected through onsite observations conducted by investigators. All (n=14) students' adaptability and proactivity performance significantly improved from an average of 3.04 to 3.45 (p=0.014) over 6-week clerkship. Overall, students with trained resident coaches adapted significantly faster and were more proactive in the obstetrics and gynecology clinical setting than the students with untrained coaches (3.31 vs. 3.24, p=0.019). Findings from our pilot study supported our hypothesis that enriching workplace emotional intelligence knowledge through resident coaches was able to help medical students adapt into obstetrics and gynecology clinical settings faster and become more proactive in learning. Clerkship programs can incorporate the concept of a resident coach in their curriculum to help bridge medical students into clinical settings and to help them engage in self-directed learning throughout the rotation.

Design of Power Cable UAV Intelligent Patrol System Based on Adaptive Kalman Filter Fuzzy PID Control

Directory of Open Access Journals (Sweden)

Chen Siyu

2017-01-01

Full Text Available Patrol UAV has poor aerial posture stability and is largely affected by anthropic factors, which lead to some shortages such as low power cable tracking precision, captured image loss and inconvenient temperature measurement, etc. In order to solve these disadvantages, this article puts forward a power cable intelligent patrol system. The core innovation of the system is a 360° platform. This collects the position information of power cables by using far infrared sensors and carries out real-time all-direction adjustment of UAV lifting platform through the adaptive Kalman filter fuzzy PID control algorithm, so that the precise tracking of power cables is achieved. An intelligent patrol system is established to detect the faults more accurately, so that a high intelligence degree of power cable patrol system is realized.

ADAPTIVE TEXTURE SYNTHESIS FOR LARGE SCALE CITY MODELING

Directory of Open Access Journals (Sweden)

G. Despine

2015-02-01

Full Text Available Large scale city models textured with aerial images are well suited for bird-eye navigation but generally the image resolution does not allow pedestrian navigation. One solution to face this problem is to use high resolution terrestrial photos but it requires huge amount of manual work to remove occlusions. Another solution is to synthesize generic textures with a set of procedural rules and elementary patterns like bricks, roof tiles, doors and windows. This solution may give realistic textures but with no correlation to the ground truth. Instead of using pure procedural modelling we present a method to extract information from aerial images and adapt the texture synthesis to each building. We describe a workflow allowing the user to drive the information extraction and to select the appropriate texture patterns. We also emphasize the importance to organize the knowledge about elementary pattern in a texture catalogue allowing attaching physical information, semantic attributes and to execute selection requests. Roofs are processed according to the detected building material. Façades are first described in terms of principal colours, then opening positions are detected and some window features are computed. These features allow selecting the most appropriate patterns from the texture catalogue. We experimented this workflow on two samples with 20 cm and 5 cm resolution images. The roof texture synthesis and opening detection were successfully conducted on hundreds of buildings. The window characterization is still sensitive to the distortions inherent to the projection of aerial images onto the facades.

Parameter estimation in large-scale systems biology models: a parallel and self-adaptive cooperative strategy.

Science.gov (United States)

Penas, David R; González, Patricia; Egea, Jose A; Doallo, Ramón; Banga, Julio R

2017-01-21

The development of large-scale kinetic models is one of the current key issues in computational systems biology and bioinformatics. Here we consider the problem of parameter estimation in nonlinear dynamic models. Global optimization methods can be used to solve this type of problems but the associated computational cost is very large. Moreover, many of these methods need the tuning of a number of adjustable search parameters, requiring a number of initial exploratory runs and therefore further increasing the computation times. Here we present a novel parallel method, self-adaptive cooperative enhanced scatter search (saCeSS), to accelerate the solution of this class of problems. The method is based on the scatter search optimization metaheuristic and incorporates several key new mechanisms: (i) asynchronous cooperation between parallel processes, (ii) coarse and fine-grained parallelism, and (iii) self-tuning strategies. The performance and robustness of saCeSS is illustrated by solving a set of challenging parameter estimation problems, including medium and large-scale kinetic models of the bacterium E. coli, bakerés yeast S. cerevisiae, the vinegar fly D. melanogaster, Chinese Hamster Ovary cells, and a generic signal transduction network. The results consistently show that saCeSS is a robust and efficient method, allowing very significant reduction of computation times with respect to several previous state of the art methods (from days to minutes, in several cases) even when only a small number of processors is used. The new parallel cooperative method presented here allows the solution of medium and large scale parameter estimation problems in reasonable computation times and with small hardware requirements. Further, the method includes self-tuning mechanisms which facilitate its use by non-experts. We believe that this new method can play a key role in the development of large-scale and even whole-cell dynamic models.

Adaptive intelligent power systems: Active distribution networks

International Nuclear Information System (INIS)

McDonald, Jim

2008-01-01

Electricity networks are extensive and well established. They form a key part of the infrastructure that supports industrialised society. These networks are moving from a period of stability to a time of potentially major transition, driven by a need for old equipment to be replaced, by government policy commitments to cleaner and renewable sources of electricity generation, and by change in the power industry. This paper looks at moves towards active distribution networks. The novel transmission and distribution systems of the future will challenge today's system designs. They will cope with variable voltages and frequencies, and will offer more flexible, sustainable options. Intelligent power networks will need innovation in several key areas of information technology. Active control of flexible, large-scale electrical power systems is required. Protection and control systems will have to react to faults and unusual transient behaviour and ensure recovery after such events. Real-time network simulation and performance analysis will be needed to provide decision support for system operators, and the inputs to energy and distribution management systems. Advanced sensors and measurement will be used to achieve higher degrees of network automation and better system control, while pervasive communications will allow networks to be reconfigured by intelligent systems

Large-uncertainty intelligent states for angular momentum and angle

International Nuclear Information System (INIS)

Goette, Joerg B; Zambrini, Roberta; Franke-Arnold, Sonja; Barnett, Stephen M

2005-01-01

The equality in the uncertainty principle for linear momentum and position is obtained for states which also minimize the uncertainty product. However, in the uncertainty relation for angular momentum and angular position both sides of the inequality are state dependent and therefore the intelligent states, which satisfy the equality, do not necessarily give a minimum for the uncertainty product. In this paper, we highlight the difference between intelligent states and minimum uncertainty states by investigating a class of intelligent states which obey the equality in the angular uncertainty relation while having an arbitrarily large uncertainty product. To develop an understanding for the uncertainties of angle and angular momentum for the large-uncertainty intelligent states we compare exact solutions with analytical approximations in two limiting cases

Reliability, construct and criterion-related validity of the Serbian adaptation of the trait emotional intelligence questionnaire (TEIQue

Directory of Open Access Journals (Sweden)

Jolić-Marjanović Zorana

2014-01-01

Full Text Available This paper presents evidence on the reliability and validity of the Serbian adaptation of the Trait Emotional Intelligence Questionnaire (TEIQue, an instrument designed to comprehensively assess emotional intelligence conceived as a constellation of emotionrelated self-perceptions. Study participants were 254 adults, who completed the Serbian TEIQue, NEO-FFI, MSCEIT, EQ-short, and RSPWB. The results indicate that the adapted TEIQue is a psychometrically sound assessment tool: internal consistencies were mostly acceptable at facet, generally good at factor, and excellent at whole-scale level; the fourfactor structure was confirmed by means of CFA; convergent-discriminant validity was established through meaningful associations with related constructs, indicating that trait EI is closely aligned with affect and self-efficacy related constructs from the realm of personality (i.e., E, N, C, and Empathy, but shows only moderate overlap with ability EI; finally, incremental validity was demonstrated in the prediction of psychological wellbeing, over and above the Big Five. [Projekat Ministarstva nauke Republike Srbije, br. 179018

Concurrent Programming Using Actors: Exploiting Large-Scale Parallelism,

Science.gov (United States)

1985-10-07

ORGANIZATION NAME AND ADDRESS 10. PROGRAM ELEMENT. PROJECT. TASK* Artificial Inteligence Laboratory AREA Is WORK UNIT NUMBERS 545 Technology Square...D-R162 422 CONCURRENT PROGRMMIZNG USING f"OS XL?ITP TEH l’ LARGE-SCALE PARALLELISH(U) NASI AC E Al CAMBRIDGE ARTIFICIAL INTELLIGENCE L. G AGHA ET AL...RESOLUTION TEST CHART N~ATIONAL BUREAU OF STANDA.RDS - -96 A -E. __ _ __ __’ .,*- - -- •. - MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL

Can enriching emotional intelligence improve medical students’ proactivity and adaptability during OB/GYN clerkships?

Science.gov (United States)

Guseh, Stephanie H.; Chen, Xiaodong P.

2015-01-01

Objectives The purpose of this pilot study was to examine our hypothesis that enriching workplace emotional intelligence through resident coaches could improve third-year medical students’ adaptability and proactivity on the Obstetrics and Gynecology clerkship. Methods An observational pilot study was conducted in a teaching hospital. Fourteen 3rd year medical students from two cohorts of clerkships were randomly divided into two groups, and equally assigned to trained resident coaches and untrained resident coaches. Data was collected through onsite naturalistic observation of students’ adaptability and proactivity in clinical settings using a checklist with a 4-point Likert scale (1=poor to 4=excellent). Wilcoxon rank-sum test was used to compare the differences between these two groups. Results A total of 280 data points were collected through onsite observations conducted by investigators. All (n=14) students’ adaptability and proactivity performance significantly improved from an average of 3.04 to 3.45 (p=0.014) over 6-week clerkship. Overall, students with trained resident coaches adapted significantly faster and were more proactive in the obstetrics and gynecology clinical setting than the students with untrained coaches (3.31 vs. 3.24, p=0.019). Conclusions Findings from our pilot study supported our hypothesis that enriching workplace emotional intelligence knowledge through resident coaches was able to help medical students adapt into obstetrics and gynecology clinical settings faster and become more proactive in learning. Clerkship programs can incorporate the concept of a resident coach in their curriculum to help bridge medical students into clinical settings and to help them engage in self-directed learning throughout the rotation. PMID:26708233

Adaptive Neural Networks Decentralized FTC Design for Nonstrict-Feedback Nonlinear Interconnected Large-Scale Systems Against Actuator Faults.

Science.gov (United States)

Li, Yongming; Tong, Shaocheng

The problem of active fault-tolerant control (FTC) is investigated for the large-scale nonlinear systems in nonstrict-feedback form. The nonstrict-feedback nonlinear systems considered in this paper consist of unstructured uncertainties, unmeasured states, unknown interconnected terms, and actuator faults (e.g., bias fault and gain fault). A state observer is designed to solve the unmeasurable state problem. Neural networks (NNs) are used to identify the unknown lumped nonlinear functions so that the problems of unstructured uncertainties and unknown interconnected terms can be solved. By combining the adaptive backstepping design principle with the combination Nussbaum gain function property, a novel NN adaptive output-feedback FTC approach is developed. The proposed FTC controller can guarantee that all signals in all subsystems are bounded, and the tracking errors for each subsystem converge to a small neighborhood of zero. Finally, numerical results of practical examples are presented to further demonstrate the effectiveness of the proposed control strategy.The problem of active fault-tolerant control (FTC) is investigated for the large-scale nonlinear systems in nonstrict-feedback form. The nonstrict-feedback nonlinear systems considered in this paper consist of unstructured uncertainties, unmeasured states, unknown interconnected terms, and actuator faults (e.g., bias fault and gain fault). A state observer is designed to solve the unmeasurable state problem. Neural networks (NNs) are used to identify the unknown lumped nonlinear functions so that the problems of unstructured uncertainties and unknown interconnected terms can be solved. By combining the adaptive backstepping design principle with the combination Nussbaum gain function property, a novel NN adaptive output-feedback FTC approach is developed. The proposed FTC controller can guarantee that all signals in all subsystems are bounded, and the tracking errors for each subsystem converge to a small

A comparison of low IQ scores from the Reynolds Intellectual Assessment Scales and the Wechsler Adult Intelligence Scale-Third Edition.

Science.gov (United States)

Umphress, Thomas B

2008-06-01

Twenty people with suspected intellectual disability took the Reynolds Intellectual Assessment Scales (RIAS; C. R. Reynolds & R. W. Kamphaus, 1998) and the Wechsler Adult Intelligence Scale-3rd Edition (WAIS-III; D. Wechsler, 1997) to see if the 2 IQ tests produced comparable results. A t test showed that the RIAS Composite Intelligence Index scores were significantly higher than WAIS-III Full Scale IQ scores at the alpha level of .01. There was a significant difference between the RIAS Nonverbal Intelligence and WAIS-III Performance Scale, but there was no significant difference between the RIAS Verbal Intelligence Index and the WAIS-III Verbal Scale IQ. The results raise questions concerning test selection for diagnosing intellectual disability and the use of the correlation statistic for comparing intelligence tests.

Data and performance profiles applying an adaptive truncation criterion, within linesearch-based truncated Newton methods, in large scale nonconvex optimization

Directory of Open Access Journals (Sweden)

Andrea Caliciotti

2018-04-01

Full Text Available In this paper, we report data and experiments related to the research article entitled “An adaptive truncation criterion, for linesearch-based truncated Newton methods in large scale nonconvex optimization” by Caliciotti et al. [1]. In particular, in Caliciotti et al. [1], large scale unconstrained optimization problems are considered by applying linesearch-based truncated Newton methods. In this framework, a key point is the reduction of the number of inner iterations needed, at each outer iteration, to approximately solving the Newton equation. A novel adaptive truncation criterion is introduced in Caliciotti et al. [1] to this aim. Here, we report the details concerning numerical experiences over a commonly used test set, namely CUTEst (Gould et al., 2015 [2]. Moreover, comparisons are reported in terms of performance profiles (Dolan and Moré, 2002 [3], adopting different parameters settings. Finally, our linesearch-based scheme is compared with a renowned trust region method, namely TRON (Lin and Moré, 1999 [4].

Robust Optimal Adaptive Control Method with Large Adaptive Gain

Science.gov (United States)

Nguyen, Nhan T.

2009-01-01

In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly. However, a large adaptive gain can lead to high-frequency oscillations which can adversely affect robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient stability robustness. Simulations were conducted for a damaged generic transport aircraft with both standard adaptive control and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model while maintaining a sufficient time delay margin.

CLAss-Specific Subspace Kernel Representations and Adaptive Margin Slack Minimization for Large Scale Classification.

Science.gov (United States)

Yu, Yinan; Diamantaras, Konstantinos I; McKelvey, Tomas; Kung, Sun-Yuan

2018-02-01

In kernel-based classification models, given limited computational power and storage capacity, operations over the full kernel matrix becomes prohibitive. In this paper, we propose a new supervised learning framework using kernel models for sequential data processing. The framework is based on two components that both aim at enhancing the classification capability with a subset selection scheme. The first part is a subspace projection technique in the reproducing kernel Hilbert space using a CLAss-specific Subspace Kernel representation for kernel approximation. In the second part, we propose a novel structural risk minimization algorithm called the adaptive margin slack minimization to iteratively improve the classification accuracy by an adaptive data selection. We motivate each part separately, and then integrate them into learning frameworks for large scale data. We propose two such frameworks: the memory efficient sequential processing for sequential data processing and the parallelized sequential processing for distributed computing with sequential data acquisition. We test our methods on several benchmark data sets and compared with the state-of-the-art techniques to verify the validity of the proposed techniques.

On Event-Triggered Adaptive Architectures for Decentralized and Distributed Control of Large-Scale Modular Systems.

Science.gov (United States)

Albattat, Ali; Gruenwald, Benjamin C; Yucelen, Tansel

2016-08-16

The last decade has witnessed an increased interest in physical systems controlled over wireless networks (networked control systems). These systems allow the computation of control signals via processors that are not attached to the physical systems, and the feedback loops are closed over wireless networks. The contribution of this paper is to design and analyze event-triggered decentralized and distributed adaptive control architectures for uncertain networked large-scale modular systems; that is, systems consist of physically-interconnected modules controlled over wireless networks. Specifically, the proposed adaptive architectures guarantee overall system stability while reducing wireless network utilization and achieving a given system performance in the presence of system uncertainties that can result from modeling and degraded modes of operation of the modules and their interconnections between each other. In addition to the theoretical findings including rigorous system stability and the boundedness analysis of the closed-loop dynamical system, as well as the characterization of the effect of user-defined event-triggering thresholds and the design parameters of the proposed adaptive architectures on the overall system performance, an illustrative numerical example is further provided to demonstrate the efficacy of the proposed decentralized and distributed control approaches.

On Event-Triggered Adaptive Architectures for Decentralized and Distributed Control of Large-Scale Modular Systems

Directory of Open Access Journals (Sweden)

Ali Albattat

2016-08-01

Full Text Available The last decade has witnessed an increased interest in physical systems controlled over wireless networks (networked control systems. These systems allow the computation of control signals via processors that are not attached to the physical systems, and the feedback loops are closed over wireless networks. The contribution of this paper is to design and analyze event-triggered decentralized and distributed adaptive control architectures for uncertain networked large-scale modular systems; that is, systems consist of physically-interconnected modules controlled over wireless networks. Specifically, the proposed adaptive architectures guarantee overall system stability while reducing wireless network utilization and achieving a given system performance in the presence of system uncertainties that can result from modeling and degraded modes of operation of the modules and their interconnections between each other. In addition to the theoretical findings including rigorous system stability and the boundedness analysis of the closed-loop dynamical system, as well as the characterization of the effect of user-defined event-triggering thresholds and the design parameters of the proposed adaptive architectures on the overall system performance, an illustrative numerical example is further provided to demonstrate the efficacy of the proposed decentralized and distributed control approaches.

The Intelligent Control System and Experiments for an Unmanned Wave Glider.

Science.gov (United States)

Liao, Yulei; Wang, Leifeng; Li, Yiming; Li, Ye; Jiang, Quanquan

2016-01-01

The control system designing of Unmanned Wave Glider (UWG) is challenging since the control system is weak maneuvering, large time-lag and large disturbance, which is difficult to establish accurate mathematical model. Meanwhile, to complete marine environment monitoring in long time scale and large spatial scale autonomously, UWG asks high requirements of intelligence and reliability. This paper focuses on the "Ocean Rambler" UWG. First, the intelligent control system architecture is designed based on the cerebrum basic function combination zone theory and hierarchic control method. The hardware and software designing of the embedded motion control system are mainly discussed. A motion control system based on rational behavior model of four layers is proposed. Then, combining with the line-of sight method(LOS), a self-adapting PID guidance law is proposed to compensate the steady state error in path following of UWG caused by marine environment disturbance especially current. Based on S-surface control method, an improved S-surface heading controller is proposed to solve the heading control problem of the weak maneuvering carrier under large disturbance. Finally, the simulation experiments were carried out and the UWG completed autonomous path following and marine environment monitoring in sea trials. The simulation experiments and sea trial results prove that the proposed intelligent control system, guidance law, controller have favorable control performance, and the feasibility and reliability of the designed intelligent control system of UWG are verified.

The Intelligent Control System and Experiments for an Unmanned Wave Glider

Science.gov (United States)

Liao, Yulei; Wang, Leifeng; Li, Yiming; Li, Ye; Jiang, Quanquan

2016-01-01

The control system designing of Unmanned Wave Glider (UWG) is challenging since the control system is weak maneuvering, large time-lag and large disturbance, which is difficult to establish accurate mathematical model. Meanwhile, to complete marine environment monitoring in long time scale and large spatial scale autonomously, UWG asks high requirements of intelligence and reliability. This paper focuses on the “Ocean Rambler” UWG. First, the intelligent control system architecture is designed based on the cerebrum basic function combination zone theory and hierarchic control method. The hardware and software designing of the embedded motion control system are mainly discussed. A motion control system based on rational behavior model of four layers is proposed. Then, combining with the line-of sight method(LOS), a self-adapting PID guidance law is proposed to compensate the steady state error in path following of UWG caused by marine environment disturbance especially current. Based on S-surface control method, an improved S-surface heading controller is proposed to solve the heading control problem of the weak maneuvering carrier under large disturbance. Finally, the simulation experiments were carried out and the UWG completed autonomous path following and marine environment monitoring in sea trials. The simulation experiments and sea trial results prove that the proposed intelligent control system, guidance law, controller have favorable control performance, and the feasibility and reliability of the designed intelligent control system of UWG are verified. PMID:28005956

Large Efficient Intelligent Heating Relay Station System

Science.gov (United States)

Wu, C. Z.; Wei, X. G.; Wu, M. Q.

2017-12-01

The design of large efficient intelligent heating relay station system aims at the improvement of the existing heating system in our country, such as low heating efficiency, waste of energy and serious pollution, and the control still depends on the artificial problem. In this design, we first improve the existing plate heat exchanger. Secondly, the ATM89C51 is used to control the whole system and realize the intelligent control. The detection part is using the PT100 temperature sensor, pressure sensor, turbine flowmeter, heating temperature, detection of user end liquid flow, hydraulic, and real-time feedback, feedback signal to the microcontroller through the heating for users to adjust, realize the whole system more efficient, intelligent and energy-saving.

Wechsler Intelligence Scale for Children-V: Test Review.

Science.gov (United States)

Na, Sabrina D; Burns, Thomas G

2016-01-01

Changes from the fourth edition of the Wechsler Intelligence Scale for Children (WISC) to the fifth edition are discussed, with particular emphasis on how the electronic administration facilitated assessment. The hierarchical organization and conceptualization of primary indices have been adjusted, based on recent theory and research on the construct of intelligence. Changes also include updates to psychometric properties and consideration of cultural bias. The scoring program allows intelligence scores to be linked statistically to achievement measures to aid in diagnoses of learning disabilities. Electronic assessment was clunky at times but overall delivered on its promise of quicker and more accurate administration and scoring.

A Large-Scale Evaluation of an Intelligent Discovery World: Smithtown.

Science.gov (United States)

Shute, Valerie J.; Glaser, Robert

1990-01-01

Presents an evaluation of "Smithtown," an intelligent tutoring system designed to teach inductive inquiry skills and principles of basic microeconomics. Two studies of individual differences in learning are described, including a comparison of knowledge acquisition with traditional instruction; hypotheses tested are discussed; and the…

Beyond adaptive-critic creative learning for intelligent mobile robots

Science.gov (United States)

Liao, Xiaoqun; Cao, Ming; Hall, Ernest L.

2001-10-01

Intelligent industrial and mobile robots may be considered proven technology in structured environments. Teach programming and supervised learning methods permit solutions to a variety of applications. However, we believe that to extend the operation of these machines to more unstructured environments requires a new learning method. Both unsupervised learning and reinforcement learning are potential candidates for these new tasks. The adaptive critic method has been shown to provide useful approximations or even optimal control policies to non-linear systems. The purpose of this paper is to explore the use of new learning methods that goes beyond the adaptive critic method for unstructured environments. The adaptive critic is a form of reinforcement learning. A critic element provides only high level grading corrections to a cognition module that controls the action module. In the proposed system the critic's grades are modeled and forecasted, so that an anticipated set of sub-grades are available to the cognition model. The forecasting grades are interpolated and are available on the time scale needed by the action model. The success of the system is highly dependent on the accuracy of the forecasted grades and adaptability of the action module. Examples from the guidance of a mobile robot are provided to illustrate the method for simple line following and for the more complex navigation and control in an unstructured environment. The theory presented that is beyond the adaptive critic may be called creative theory. Creative theory is a form of learning that models the highest level of human learning - imagination. The application of the creative theory appears to not only be to mobile robots but also to many other forms of human endeavor such as educational learning and business forecasting. Reinforcement learning such as the adaptive critic may be applied to known problems to aid in the discovery of their solutions. The significance of creative theory is that it

Structural and incremental validity of the Wechsler Adult Intelligence Scale-Fourth Edition with a clinical sample.

Science.gov (United States)

Nelson, Jason M; Canivez, Gary L; Watkins, Marley W

2013-06-01

Structural and incremental validity of the Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV; Wechsler, 2008a) was examined with a sample of 300 individuals referred for evaluation at a university-based clinic. Confirmatory factor analysis indicated that the WAIS-IV structure was best represented by 4 first-order factors as well as a general intelligence factor in a direct hierarchical model. The general intelligence factor accounted for the most common and total variance among the subtests. Incremental validity analyses indicated that the Full Scale IQ (FSIQ) generally accounted for medium to large portions of academic achievement variance. For all measures of academic achievement, the first-order factors combined accounted for significant achievement variance beyond that accounted for by the FSIQ, but individual factor index scores contributed trivial amounts of achievement variance. Implications for interpreting WAIS-IV results are discussed. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

Front-End Intelligence for Large-Scale Application-Oriented Internet-of-Things

KAUST Repository

Bader, Ahmed; Ghazzai, Hakim; Kadri, Abdullah; Alouini, Mohamed-Slim

2016-01-01

The Internet-of-things (IoT) refers to the massive integration of electronic devices, vehicles, buildings, and other objects to collect and exchange data. It is the enabling technology for a plethora of applications touching various aspects of our lives such as healthcare, wearables, surveillance, home automation, smart manufacturing, and intelligent automotive systems. Existing IoT architectures are highly centralized and heavily rely on a back-end core network for all decision-making processes. This may lead to inefficiencies in terms of latency, network traffic management, computational processing, and power consumption. In this paper, we advocate the empowerment of front-end IoT devices to support the back-end network in fulfilling end-user applications requirements mainly by means of improved connectivity and efficient network management. A novel conceptual framework is presented for a new generation of IoT devices that will enable multiple new features for both the IoT administrators as well as end users. Exploiting the recent emergence of software-defined architecture, these smart IoT devices will allow fast, reliable, and intelligent management of diverse IoT-based applications. After highlighting relevant shortcomings of the existing IoT architectures, we outline some key design perspectives to enable front-end intelligence while shedding light on promising future research directions.

Front-End Intelligence for Large-Scale Application-Oriented Internet-of-Things

KAUST Repository

Bader, Ahmed

2016-06-14

The Internet-of-things (IoT) refers to the massive integration of electronic devices, vehicles, buildings, and other objects to collect and exchange data. It is the enabling technology for a plethora of applications touching various aspects of our lives such as healthcare, wearables, surveillance, home automation, smart manufacturing, and intelligent automotive systems. Existing IoT architectures are highly centralized and heavily rely on a back-end core network for all decision-making processes. This may lead to inefficiencies in terms of latency, network traffic management, computational processing, and power consumption. In this paper, we advocate the empowerment of front-end IoT devices to support the back-end network in fulfilling end-user applications requirements mainly by means of improved connectivity and efficient network management. A novel conceptual framework is presented for a new generation of IoT devices that will enable multiple new features for both the IoT administrators as well as end users. Exploiting the recent emergence of software-defined architecture, these smart IoT devices will allow fast, reliable, and intelligent management of diverse IoT-based applications. After highlighting relevant shortcomings of the existing IoT architectures, we outline some key design perspectives to enable front-end intelligence while shedding light on promising future research directions.

Study on large scale knowledge base with real time operation for autonomous nuclear power plant. 1. Basic concept and expecting performance

International Nuclear Information System (INIS)

Ozaki, Yoshihiko; Suda, Kazunori; Yoshikawa, Shinji; Ozawa, Kenji

1996-04-01

Since it is desired to enhance availability and safety of nuclear power plants operation and maintenance by removing human factor, there are many researches and developments for intelligent operation or diagnosis using artificial intelligence (AI) technique. We have been developing an autonomous operation and maintenance system for nuclear power plants by substituting AI's and intelligent robots. It is indispensable to use various and large scale knowledge relative to plant design, operation, and maintenance, that is, whole life cycle data of the plant for the autonomous nuclear power plant. These knowledge must be given to AI system or intelligent robots adequately and opportunely. Moreover, it is necessary to insure real time operation using the large scale knowledge base for plant control and diagnosis performance. We have been studying on the large scale and real time knowledge base system for autonomous plant. In the report, we would like to present the basic concept and expecting performance of the knowledge base for autonomous plant, especially, autonomous control and diagnosis system. (author)

The Cylindrical Structure of the Wechsler Intelligence Scale for Children--IV: A Retest of the Guttman Model of Intelligence

Science.gov (United States)

Cohen, Arie; Fiorello, Catherine A.; Farley, Frank H.

2006-01-01

A previous study on the underlying structure of the Wechsler intelligence test (WISC-R; [Wechsler, D. (1974). Manual WISC-R: Wechsler intelligence scale for children-Revised. New York: Psychological Corporation]), using smallest space analysis (SSA) [Guttman, L., and Levy, S. (1991). Two structural laws for intelligence tests.…

Large-scale agent-based social simulation : A study on epidemic prediction and control

NARCIS (Netherlands)

Zhang, M.

2016-01-01

Large-scale agent-based social simulation is gradually proving to be a versatile methodological approach for studying human societies, which could make contributions from policy making in social science, to distributed artificial intelligence and agent technology in computer science, and to theory

Intelligent control of non-linear dynamical system based on the adaptive neurocontroller

Science.gov (United States)

Engel, E.; Kovalev, I. V.; Kobezhicov, V.

2015-10-01

This paper presents an adaptive neuro-controller for intelligent control of non-linear dynamical system. The formed as the fuzzy selective neural net the adaptive neuro-controller on the base of system's state, creates the effective control signal under random perturbations. The validity and advantages of the proposed adaptive neuro-controller are demonstrated by numerical simulations. The simulation results show that the proposed controller scheme achieves real-time control speed and the competitive performance, as compared to PID, fuzzy logic controllers.

Psychometrics of the Emotional Intelligence Scale in Elite, Amateur, and Non-Athletes

Science.gov (United States)

Vaughan, Robert; Laborde, Sylvain

2018-01-01

The purpose of this study was to assess the psychometrics properties of the Emotional Intelligence Scale and assess the measurement invariance across elite (n = 367), amateur (n = 629), and non-athletes (n = 550). In total, 1,546 participants from various sports completed the emotional intelligence scale. Several competing models were compared…

Real-time simulation of large-scale floods

Science.gov (United States)

Liu, Q.; Qin, Y.; Li, G. D.; Liu, Z.; Cheng, D. J.; Zhao, Y. H.

2016-08-01

According to the complex real-time water situation, the real-time simulation of large-scale floods is very important for flood prevention practice. Model robustness and running efficiency are two critical factors in successful real-time flood simulation. This paper proposed a robust, two-dimensional, shallow water model based on the unstructured Godunov- type finite volume method. A robust wet/dry front method is used to enhance the numerical stability. An adaptive method is proposed to improve the running efficiency. The proposed model is used for large-scale flood simulation on real topography. Results compared to those of MIKE21 show the strong performance of the proposed model.

Plants : Adaptive behavior, root-brains, and minimal cognition

NARCIS (Netherlands)

Calvo Garzon, Paco; Keijzer, Fred

Plant intelligence has gone largely unnoticed within the field of animal and human adaptive behavior. In this context, we will introduce current work on plant intelligence as a new set of relevant phenomena that deserves attention and also discuss its potential relevance for the study of adaptive

Adaptive fuzzy PID control of hydraulic servo control system for large axial flow compressor

Science.gov (United States)

Wang, Yannian; Wu, Peizhi; Liu, Chengtao

2017-09-01

To improve the stability of the large axial compressor, an efficient and special intelligent hydraulic servo control system is designed and implemented. The adaptive fuzzy PID control algorithm is used to control the position of the hydraulic servo cylinder steadily, which overcomes the drawback that the PID parameters should be adjusted based on the different applications. The simulation and the test results show that the system has a better dynamic property and a stable state performance.

Intelligent adaptive systems an interaction-centered design perspective

CERN Document Server

Hou, Ming; Burns, Catherine

2014-01-01

A synthesis of recent research and developments on intelligent adaptive systems from the HF (human factors) and HCI (human-computer interaction) domains, this book provides integrated design guidance and recommendations for researchers and system developers. It addresses a recognized lack of integration between the HF and HCI research communities, which has led to inconsistencies between the research approaches adopted, and a lack of exploitation of research from one field by the other. The book establishes design guidance through the review of conceptual frameworks, analytical methodologies,

The Adaptive Multi-scale Simulation Infrastructure

Energy Technology Data Exchange (ETDEWEB)

Tobin, William R. [Rensselaer Polytechnic Inst., Troy, NY (United States)

2015-09-01

The Adaptive Multi-scale Simulation Infrastructure (AMSI) is a set of libraries and tools developed to support the development, implementation, and execution of general multimodel simulations. Using a minimal set of simulation meta-data AMSI allows for minimally intrusive work to adapt existent single-scale simulations for use in multi-scale simulations. Support for dynamic runtime operations such as single- and multi-scale adaptive properties is a key focus of AMSI. Particular focus has been spent on the development on scale-sensitive load balancing operations to allow single-scale simulations incorporated into a multi-scale simulation using AMSI to use standard load-balancing operations without affecting the integrity of the overall multi-scale simulation.

Cognitions as determinants of (mal)adaptive emotions and emotionally intelligent behavior in an organizational context.

Science.gov (United States)

Spörrle, Matthias; Welpe, Isabell M; Försterling, Friedrich

2006-01-01

This study applies the theoretical concepts of Rational Emotive Behavior Therapy (REBT; Ellis, 1962, 1994) to the analysis of functional and dysfunctional behaviour and emotions in the workplace and tests central assumptions of REBT in an organizational setting. We argue that Ellis' appraisal theory of emotion sheds light on some of the cognitive and emotional antecedents of emotional intelligence and emotionally intelligent behaviour. In an extension of REBT, we posit that adaptive emotions resulting from rational cognitions reflect more emotional intelligence than maladaptive emotions which result from irrational cognitions, because the former lead to functional behaviour. We hypothesize that semantically similar emotions (e.g. annoyance and rage) lead to different behavioural reactions and have a different functionality in an organizational context. The results of scenario experiments using organizational vignettes confirm the central assumptions of Ellis' appraisal theory and support our hypotheses of a correspondence between adaptive emotions and emotionally intelligent behaviour. Additionally, we find evidence that irrational job-related attitudes result in reduced work (but not life) satisfaction.

Large scale electrolysers

International Nuclear Information System (INIS)

B Bello; M Junker

2006-01-01

Hydrogen production by water electrolysis represents nearly 4 % of the world hydrogen production. Future development of hydrogen vehicles will require large quantities of hydrogen. Installation of large scale hydrogen production plants will be needed. In this context, development of low cost large scale electrolysers that could use 'clean power' seems necessary. ALPHEA HYDROGEN, an European network and center of expertise on hydrogen and fuel cells, has performed for its members a study in 2005 to evaluate the potential of large scale electrolysers to produce hydrogen in the future. The different electrolysis technologies were compared. Then, a state of art of the electrolysis modules currently available was made. A review of the large scale electrolysis plants that have been installed in the world was also realized. The main projects related to large scale electrolysis were also listed. Economy of large scale electrolysers has been discussed. The influence of energy prices on the hydrogen production cost by large scale electrolysis was evaluated. (authors)

The person who eases your mind "Ibasyo" and emotional intelligence in interpersonal adaptation

Directory of Open Access Journals (Sweden)

Hiroshi Toyota

2009-11-01

Full Text Available The present study was carried out to examine the effect of the "Ibasyo" (the person who eases one's mind and emotional intelligence (EI on self-esteem and loneliness. Five hundred and eight Japanese undergraduates were asked to choose one of the alternatives (e. g., myself, mother, friend to answer the question "Who is the person that eases your mind?" Then, they were asked to rate items from scales corresponding to EI, self-esteem and loneliness. Multiple regression analyses indicated that both Ibasyo and EI explained 25% of loneliness, but only EI explained 25% of self-esteem. The analyses also showed differences of sub-abilities in EI that determined the level of loneliness and self-esteem among Ibasyo groups. These results are interpreted as showing the importance of EI in adaptation.

Architectures of adaptive integration in large collaborative projects

Directory of Open Access Journals (Sweden)

Lois Wright Morton

2015-12-01

Full Text Available Collaborations to address complex societal problems associated with managing human-natural systems often require large teams comprised of scientists from multiple disciplines. For many such problems, large-scale, transdisciplinary projects whose members include scientists, stakeholders, and other professionals are necessary. The success of very large, transdisciplinary projects can be facilitated by attending to the diversity of types of collaboration that inevitably occur within them. As projects progress and evolve, the resulting dynamic collaborative heterogeneity within them constitutes architectures of adaptive integration (AAI. Management that acknowledges this dynamic and fosters and promotes awareness of it within a project can better facilitate the creativity and innovation required to address problems from a systems perspective. In successful large projects, AAI (1 functionally meets objectives and goals, (2 uses disciplinary expertise and concurrently bridges many disciplines, (3 has mechanisms to enable connection, (4 delineates boundaries to keep focus but retain flexibility, (5 continuously monitors and adapts, and (6 encourages project-wide awareness. These principles are illustrated using as case studies three large climate change and agriculture projects funded by the U.S. Department of Agriculture-National Institute of Food and Agriculture.

Intelligence and neuroticism in relation to depression and psychological distress: Evidence from two large population cohorts.

Science.gov (United States)

Navrady, L B; Ritchie, S J; Chan, S W Y; Kerr, D M; Adams, M J; Hawkins, E H; Porteous, D; Deary, I J; Gale, C R; Batty, G D; McIntosh, A M

2017-06-01

Neuroticism is a risk factor for selected mental and physical illnesses and is inversely associated with intelligence. Intelligence appears to interact with neuroticism and mitigate its detrimental effects on physical health and mortality. However, the inter-relationships of neuroticism and intelligence for major depressive disorder (MDD) and psychological distress has not been well examined. Associations and interactions between neuroticism and general intelligence (g) on MDD, self-reported depression, and psychological distress were examined in two population-based cohorts: Generation Scotland: Scottish Family Health Study (GS:SFHS, n=19,200) and UK Biobank (n=90,529). The Eysenck Personality Scale Short Form-Revised measured neuroticism and g was extracted from multiple cognitive ability tests in each cohort. Family structure was adjusted for in GS:SFHS. Neuroticism was strongly associated with increased risk for depression and higher psychological distress in both samples. Although intelligence conferred no consistent independent effects on depression, it did increase the risk for depression across samples once neuroticism was adjusted for. Results suggest that higher intelligence may ameliorate the association between neuroticism and self-reported depression although no significant interaction was found for clinical MDD. Intelligence was inversely associated with psychological distress across cohorts. A small interaction was found across samples such that lower psychological distress associates with higher intelligence and lower neuroticism, although effect sizes were small. From two large cohort studies, our findings suggest intelligence acts a protective factor in mitigating the effects of neuroticism on psychological distress. Intelligence does not confer protection against diagnosis of depression in those high in neuroticism. Copyright © 2017 The Authors. Published by Elsevier Masson SAS.. All rights reserved.

Large-Scale Assessment of a Fully Automatic Co-Adaptive Motor Imagery-Based Brain Computer Interface.

Directory of Open Access Journals (Sweden)

Laura Acqualagna

Full Text Available In the last years Brain Computer Interface (BCI technology has benefited from the development of sophisticated machine leaning methods that let the user operate the BCI after a few trials of calibration. One remarkable example is the recent development of co-adaptive techniques that proved to extend the use of BCIs also to people not able to achieve successful control with the standard BCI procedure. Especially for BCIs based on the modulation of the Sensorimotor Rhythm (SMR these improvements are essential, since a not negligible percentage of users is unable to operate SMR-BCIs efficiently. In this study we evaluated for the first time a fully automatic co-adaptive BCI system on a large scale. A pool of 168 participants naive to BCIs operated the co-adaptive SMR-BCI in one single session. Different psychological interventions were performed prior the BCI session in order to investigate how motor coordination training and relaxation could influence BCI performance. A neurophysiological indicator based on the Power Spectral Density (PSD was extracted by the recording of few minutes of resting state brain activity and tested as predictor of BCI performances. Results show that high accuracies in operating the BCI could be reached by the majority of the participants before the end of the session. BCI performances could be significantly predicted by the neurophysiological indicator, consolidating the validity of the model previously developed. Anyway, we still found about 22% of users with performance significantly lower than the threshold of efficient BCI control at the end of the session. Being the inter-subject variability still the major problem of BCI technology, we pointed out crucial issues for those who did not achieve sufficient control. Finally, we propose valid developments to move a step forward to the applicability of the promising co-adaptive methods.

Behavioral Adaptation and Acceptance

NARCIS (Netherlands)

Martens, M.H.; Jenssen, G.D.

2012-01-01

One purpose of Intelligent Vehicles is to improve road safety, throughput, and emissions. However, the predicted effects are not always as large as aimed for. Part of this is due to indirect behavioral changes of drivers, also called behavioral adaptation. Behavioral adaptation (BA) refers to

Adaptive Large Neighbourhood Search

DEFF Research Database (Denmark)

Røpke, Stefan

Large neighborhood search is a metaheuristic that has gained popularity in recent years. The heuristic repeatedly moves from solution to solution by first partially destroying the solution and then repairing it. The best solution observed during this search is presented as the final solution....... This tutorial introduces the large neighborhood search metaheuristic and the variant adaptive large neighborhood search that dynamically tunes parameters of the heuristic while it is running. Both heuristics belong to a broader class of heuristics that are searching a solution space using very large...... neighborhoods. The tutorial also present applications of the adaptive large neighborhood search, mostly related to vehicle routing problems for which the heuristic has been extremely successful. We discuss how the heuristic can be parallelized and thereby take advantage of modern desktop computers...

Special Issue on Intelligent Robots

Directory of Open Access Journals (Sweden)

Genci Capi

2013-08-01

Full Text Available The research on intelligent robots will produce robots that are able to operate in everyday life environments, to adapt their program according to environment changes, and to cooperate with other team members and humans. Operating in human environments, robots need to process, in real time, a large amount of sensory data—such as vision, laser, microphone—in order to determine the best action. Intelligent algorithms have been successfully applied to link complex sensory data to robot action. This editorial briefly summarizes recent findings in the field of intelligent robots as described in the articles published in this special issue.

A Comparison of Low IQ Scores from the Reynolds Intellectual Assessment Scales and the Wechsler Adult Intelligence Scale--Third Edition

Science.gov (United States)

Umphress, Thomas B.

2008-01-01

Twenty people with suspected intellectual disability took the Reynolds Intellectual Assessment Scales (RIAS; C. R. Reynolds & R. W. Kamphaus, 1998) and the Wechsler Adult Intelligence Scale--3rd Edition (WAIS-III; D. Wechsler, 1997) to see if the 2 IQ tests produced comparable results. A t test showed that the RIAS Composite Intelligence Index…

Development of brief versions of the Wechsler Intelligence Scale for schizophrenia: considerations of the structure and predictability of intelligence.

Science.gov (United States)

Sumiyoshi, Chika; Uetsuki, Miki; Suga, Motomu; Kasai, Kiyoto; Sumiyoshi, Tomiki

2013-12-30

Short forms (SF) of the Wechsler Intelligence Scale have been developed to enhance its practicality. However, only a few studies have addressed the Wechsler Intelligence Scale Revised (WAIS-R) SFs based on data from patients with schizophrenia. The current study was conducted to develop the WAIS-R SFs for these patients based on the intelligence structure and predictability of the Full IQ (FIQ). Relations to demographic and clinical variables were also examined on selecting plausible subtests. The WAIS-R was administered to 90 Japanese patients with schizophrenia. Exploratory factor analysis (EFA) and multiple regression analysis were conducted to find potential subtests. EFA extracted two dominant factors corresponding to Verbal IQ and Performance IQ measures. Subtests with higher factor loadings on those factors were initially nominated. Regression analysis was carried out to reach the model containing all the nominated subtests. The optimality of the potential subtests included in that model was evaluated from the perspectives of the representativeness of intelligence structure, FIQ predictability, and the relation with demographic and clinical variables. Taken together, the dyad of Vocabulary and Block Design was considered to be the most optimal WAIS-R SF for patients with schizophrenia, reflecting both intelligence structure and FIQ predictability. © 2013 Elsevier Ireland Ltd. All rights reserved.

Examining the Role of Emotional Intelligence between Organizational Learning and Adaptive Performance in Indian Manufacturing Industries

Science.gov (United States)

Pradhan, Rabindra Kumar; Jena, Lalatendu Kesari; Singh, Sanjay Kumar

2017-01-01

Purpose: The purpose of this study is to examine the relationship between organisational learning and adaptive performance. Furthermore, the study investigates the moderating role of emotional intelligence in the perspective of organisational learning for addressing adaptive performance of executives employed in manufacturing organisations.…

Failure of Working Memory Training to Enhance Cognition or Intelligence

Science.gov (United States)

Thompson, Todd W.; Waskom, Michael L.; Garel, Keri-Lee A.; Cardenas-Iniguez, Carlos; Reynolds, Gretchen O.; Winter, Rebecca; Chang, Patricia; Pollard, Kiersten; Lala, Nupur; Alvarez, George A.; Gabrieli, John D. E.

2013-01-01

Fluid intelligence is important for successful functioning in the modern world, but much evidence suggests that fluid intelligence is largely immutable after childhood. Recently, however, researchers have reported gains in fluid intelligence after multiple sessions of adaptive working memory training in adults. The current study attempted to replicate and expand those results by administering a broad assessment of cognitive abilities and personality traits to young adults who underwent 20 sessions of an adaptive dual n-back working memory training program and comparing their post-training performance on those tests to a matched set of young adults who underwent 20 sessions of an adaptive attentional tracking program. Pre- and post-training measurements of fluid intelligence, standardized intelligence tests, speed of processing, reading skills, and other tests of working memory were assessed. Both training groups exhibited substantial and specific improvements on the trained tasks that persisted for at least 6 months post-training, but no transfer of improvement was observed to any of the non-trained measurements when compared to a third untrained group serving as a passive control. These findings fail to support the idea that adaptive working memory training in healthy young adults enhances working memory capacity in non-trained tasks, fluid intelligence, or other measures of cognitive abilities. PMID:23717453

Failure of working memory training to enhance cognition or intelligence.

Directory of Open Access Journals (Sweden)

Todd W Thompson

Full Text Available Fluid intelligence is important for successful functioning in the modern world, but much evidence suggests that fluid intelligence is largely immutable after childhood. Recently, however, researchers have reported gains in fluid intelligence after multiple sessions of adaptive working memory training in adults. The current study attempted to replicate and expand those results by administering a broad assessment of cognitive abilities and personality traits to young adults who underwent 20 sessions of an adaptive dual n-back working memory training program and comparing their post-training performance on those tests to a matched set of young adults who underwent 20 sessions of an adaptive attentional tracking program. Pre- and post-training measurements of fluid intelligence, standardized intelligence tests, speed of processing, reading skills, and other tests of working memory were assessed. Both training groups exhibited substantial and specific improvements on the trained tasks that persisted for at least 6 months post-training, but no transfer of improvement was observed to any of the non-trained measurements when compared to a third untrained group serving as a passive control. These findings fail to support the idea that adaptive working memory training in healthy young adults enhances working memory capacity in non-trained tasks, fluid intelligence, or other measures of cognitive abilities.

The adaption study of emotional intelligence inventory in sport

Directory of Open Access Journals (Sweden)

İlhan Adiloğulları

2015-12-01

Full Text Available Aim: The purpose of this study was to test the validity and reliability of the Turkish version of Emotional Intelligence Inventory in Sport (EIIS. Material and Methods: The emotional intelligence inventory in sport which have consists of nineteen items and five subscales, 157 female (age=20,10±1,95 and 247 male (age=21,25±2,18 in total 404 (age=20,80±2,17 participants completed. Respondents of the EIIS indicate the extent to which they agree with each statement on a five-point Likert scale, ranging from 1 (strongly disagree to 5 (strongly agree. Factor structures of the scale were tested by confirmatory factor analysis in AMOS programme. Results: The resulting factor is appropriate for the 19-item inventory value but is below the desired value of the item-total correlation values b4 and paragraphs are seen as loaded with low load factors. However, there was only one item with low factor loadings that was excluded from the inventory. It was obtained acceptable fit index values of inventory that confirming factor structures of Turkish version. Internal consistency coefficients of EIIS were found ranging from 0,69 (Appraisal of others emotions, 0,85 (Appraisal of own emotions, 0,67 (Emotional regulation 0,85 (Use of emotions and 0,61 (Social skills. Conclusion: Turkish version of the Emotional intelligence inventory in Sport is can be used for Turkish athletes.

Dyadic Short Forms of the Wechsler Adult Intelligence Scale-IV.

Science.gov (United States)

Denney, David A; Ringe, Wendy K; Lacritz, Laura H

2015-08-01

Full Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV) administration can be time-consuming and may not be necessary when intelligence quotient estimates will suffice. Estimated Full Scale Intelligence Quotient (FSIQ) and General Ability Index (GAI) scores were derived from nine dyadic short forms using individual regression equations based on data from a clinical sample (n = 113) that was then cross validated in a separate clinical sample (n = 50). Derived scores accounted for 70%-83% of the variance in FSIQ and 77%-88% of the variance in GAI. Predicted FSIQs were strongly associated with actual FSIQ (rs = .73-.88), as were predicted and actual GAIs (rs = .80-.93). Each of the nine dyadic short forms of the WAIS-IV was a good predictor of FSIQ and GAI in the validation sample. These data support the validity of WAIS-IV short forms when time is limited or lengthier batteries cannot be tolerated by patients. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Test Review: Wechsler Preschool and Primary Scale of Intelligence, Fourth Edition: Canadian

Science.gov (United States)

Soares, Melissa A.; McCrimmon, Adam W.

2013-01-01

The Wechsler Preschool and Primary Scale of Intelligence-Fourth Edition: Canadian (WPPSI-IVCDN; Wechsler, 2012), published by NCS Pearson, is a newly updated, individually administered measure of cognitive intelligence for children aged 2:6 through 7:7. Suitable for educational, clinical, and research settings, the purposes of the WPPSI-IVCDN are…

Large Scale Analyses and Visualization of Adaptive Amino Acid Changes Projects.

Science.gov (United States)

Vázquez, Noé; Vieira, Cristina P; Amorim, Bárbara S R; Torres, André; López-Fernández, Hugo; Fdez-Riverola, Florentino; Sousa, José L R; Reboiro-Jato, Miguel; Vieira, Jorge

2018-03-01

When changes at few amino acid sites are the target of selection, adaptive amino acid changes in protein sequences can be identified using maximum-likelihood methods based on models of codon substitution (such as codeml). Although such methods have been employed numerous times using a variety of different organisms, the time needed to collect the data and prepare the input files means that tens or hundreds of coding regions are usually analyzed. Nevertheless, the recent availability of flexible and easy to use computer applications that collect relevant data (such as BDBM) and infer positively selected amino acid sites (such as ADOPS), means that the entire process is easier and quicker than before. However, the lack of a batch option in ADOPS, here reported, still precludes the analysis of hundreds or thousands of sequence files. Given the interest and possibility of running such large-scale projects, we have also developed a database where ADOPS projects can be stored. Therefore, this study also presents the B+ database, which is both a data repository and a convenient interface that looks at the information contained in ADOPS projects without the need to download and unzip the corresponding ADOPS project file. The ADOPS projects available at B+ can also be downloaded, unzipped, and opened using the ADOPS graphical interface. The availability of such a database ensures results repeatability, promotes data reuse with significant savings on the time needed for preparing datasets, and effortlessly allows further exploration of the data contained in ADOPS projects.

Finite element analysis and genetic algorithm optimization design for the actuator placement on a large adaptive structure

Science.gov (United States)

Sheng, Lizeng

The dissertation focuses on one of the major research needs in the area of adaptive/intelligent/smart structures, the development and application of finite element analysis and genetic algorithms for optimal design of large-scale adaptive structures. We first review some basic concepts in finite element method and genetic algorithms, along with the research on smart structures. Then we propose a solution methodology for solving a critical problem in the design of a next generation of large-scale adaptive structures---optimal placements of a large number of actuators to control thermal deformations. After briefly reviewing the three most frequently used general approaches to derive a finite element formulation, the dissertation presents techniques associated with general shell finite element analysis using flat triangular laminated composite elements. The element used here has three nodes and eighteen degrees of freedom and is obtained by combining a triangular membrane element and a triangular plate bending element. The element includes the coupling effect between membrane deformation and bending deformation. The membrane element is derived from the linear strain triangular element using Cook's transformation. The discrete Kirchhoff triangular (DKT) element is used as the plate bending element. For completeness, a complete derivation of the DKT is presented. Geometrically nonlinear finite element formulation is derived for the analysis of adaptive structures under the combined thermal and electrical loads. Next, we solve the optimization problems of placing a large number of piezoelectric actuators to control thermal distortions in a large mirror in the presence of four different thermal loads. We then extend this to a multi-objective optimization problem of determining only one set of piezoelectric actuator locations that can be used to control the deformation in the same mirror under the action of any one of the four thermal loads. A series of genetic algorithms

Cultural Intelligence and Social Adaptability: A Comparison between Iranian and Non-Iranian Dormitory Students of Isfahan University of Medical Sciences.

Science.gov (United States)

Soltani, Batoul; Keyvanara, Mahmoud

2013-01-01

At the modern age, to acquire knowledge and experience, the individuals with their own specific culture have to enter contexts with cultural diversity, adapt to different cultures and have social interactions to be able to have effective inter-cultural relationships.To have such intercultural associations and satisfy individual needs in the society, cultural intelligence and social adaptability are deemed as inevitable requirements, in particular for those who enter a quite different culture. Hence, the present study tries to compare the cultural intelligence and its aspects and social adaptability in Iranian and non-Iranian dormitory students of Isfahan University of Medical Sciences in 2012. The study was of descriptiveanalytical nature. The research population consisted of Iranian and non-Iranian students resided in the dormitories of Isfahan University of Medical Sciences which are 2500, totally. For Iranian students, two-stage sampling method was adopted. At the first stage, classified sampling and at the second stage, systematic random sampling was conducted. In this way, 441 students were selected. To form non-Iranian students' sample, consensus sampling method was applied and a sample of 37 students were obtained. The research data was collected by using Earley & Ang's Cultural Intelligence Questionnaire with the Cronbach's coefficient α of 76% and California Social Adaptability Standard Questionnaire with the Cronbach's coefficient α of over 70%. Then, the data were put into SPSS software to be analyzed. Finally, the results were presented by descriptive and inferential statistics methods. The study findings revealed that there was no statistically significant difference between cultural intelligence and cognitive aspect of cultural intelligence in Iranian and non-Iranian students (P≥0/05). However, Iranian and non-Iranian students statistically differed in terms of the following aspects of cultural intelligence: meta-cognitive aspect (61.8% for

Emotional intelligence and features of social and psychological adaptation in adolescents with deviant behavior

Directory of Open Access Journals (Sweden)

Degtyarev A.V.,

2014-11-01

Full Text Available The problem of social-psychological adaptation of adolescents with deviant behavioral today is of particular relevance in relation to the current process of restructuring of educational institutions - the merging of general and specialized schools for adolescents with behavioral problems in a unified educational complexes. In these circumstances it is necessary to find an efficient tool that will simultaneously accelerate the process of adaptation and have a positive preventive effect. In this article, the author shows that such a tool can become the emotional intelligence as a construct that includes various abilities of the emotional sphere. The main hypothesis of the study was that the socio-psychological adaptation of adolescents with deviant behavior has its own characteristics, different from the norm group, and is interconnected with the components of emotional intelligence. The study was conducted on the basis of general education school № 2077 formed by the merger of five educational institutions: the former school № 738, № 703, № 702, № 7 and № 77. The study involved 222 teenagers from 14 to 16 years (111 girls and 111 boys.

Career Adapt-Abilities Scale-Belgium Form: psychometric characteristics and construct validity

NARCIS (Netherlands)

Dries, N.; van Esbroeck, R.; van Vianen, A.E.M.; de Cooman, R.; Pepermans, R.

2012-01-01

The Dutch version of the Career Adapt-Abilities Scale-Belgium Form (CAAS-Belgium) consists of four scales, each with six items, which measure concern, control, curiosity, and confidence as psychosocial resources for managing occupational transitions, developmental tasks, and work traumas. A pilot

Optical Communication System for Remote Monitoring and Adaptive Control of Distributed Ground Sensors Exhibiting Collective Intelligence

Energy Technology Data Exchange (ETDEWEB)

Cameron, S.M.; Stantz, K.M.; Trahan, M.W.; Wagner, J.S.

1998-11-01

Comprehensive management of the battle-space has created new requirements in information management, communication, and interoperability as they effect surveillance and situational awareness. The objective of this proposal is to expand intelligent controls theory to produce a uniquely powerful implementation of distributed ground-based measurement incorporating both local collective behavior, and interoperative global optimization for sensor fusion and mission oversight. By using a layered hierarchal control architecture to orchestrate adaptive reconfiguration of autonomous robotic agents, we can improve overall robustness and functionality in dynamic tactical environments without information bottlenecks. In this concept, each sensor is equipped with a miniaturized optical reflectance modulator which is interactively monitored as a remote transponder using a covert laser communication protocol from a remote mothership or operative. Robot data-sharing at the ground level can be leveraged with global evaluation criteria, including terrain overlays and remote imaging data. Information sharing and distributed intelli- gence opens up a new class of remote-sensing applications in which small single-function autono- mous observers at the local level can collectively optimize and measure large scale ground-level signals. AS the need for coverage and the number of agents grows to improve spatial resolution, cooperative behavior orchestrated by a global situational awareness umbrella will be an essential ingredient to offset increasing bandwidth requirements within the net. A system of the type described in this proposal will be capable of sensitively detecting, tracking, and mapping spatial distributions of measurement signatures which are non-stationary or obscured by clutter and inter- fering obstacles by virtue of adaptive reconfiguration. This methodology could be used, for example, to field an adaptive ground-penetrating radar for detection of underground structures in

"Annotated Lectures": Student-Instructor Interaction in Large-Scale Global Education

Directory of Open Access Journals (Sweden)

Roger Diehl

2009-10-01

Full Text Available We describe an "Annotated Lectures" system, which will be used in a global virtual teaching and student collaboration event on embodied intelligence presented by the University of Zurich. The lectures will be broadcasted via video-conference to lecture halls of different universities around the globe. Among other collaboration features, an "Annotated Lectures" system will be implemented in a 3D collaborative virtual environment and used by the participating students to make annotations to the video-recorded lectures, which will be sent to and answered by their supervisors, and forwarded to the lecturers in an aggregated way. The "Annotated Lectures" system aims to overcome the issues of limited studentinstructor interaction in large-scale education, and to foster an intercultural and multidisciplinary discourse among students who review the lectures in a group. After presenting the concept of the "Annotated Lectures" system, we discuss a prototype version including a description of the technical components and its expected benefit for large-scale global education.

3D fast adaptive correlation imaging for large-scale gravity data based on GPU computation

Science.gov (United States)

Chen, Z.; Meng, X.; Guo, L.; Liu, G.

2011-12-01

In recent years, large scale gravity data sets have been collected and employed to enhance gravity problem-solving abilities of tectonics studies in China. Aiming at the large scale data and the requirement of rapid interpretation, previous authors have carried out a lot of work, including the fast gradient module inversion and Euler deconvolution depth inversion ,3-D physical property inversion using stochastic subspaces and equivalent storage, fast inversion using wavelet transforms and a logarithmic barrier method. So it can be say that 3-D gravity inversion has been greatly improved in the last decade. Many authors added many different kinds of priori information and constraints to deal with nonuniqueness using models composed of a large number of contiguous cells of unknown property and obtained good results. However, due to long computation time, instability and other shortcomings, 3-D physical property inversion has not been widely applied to large-scale data yet. In order to achieve 3-D interpretation with high efficiency and precision for geological and ore bodies and obtain their subsurface distribution, there is an urgent need to find a fast and efficient inversion method for large scale gravity data. As an entirely new geophysical inversion method, 3D correlation has a rapid development thanks to the advantage of requiring no a priori information and demanding small amount of computer memory. This method was proposed to image the distribution of equivalent excess masses of anomalous geological bodies with high resolution both longitudinally and transversely. In order to tranform the equivalence excess masses into real density contrasts, we adopt the adaptive correlation imaging for gravity data. After each 3D correlation imaging, we change the equivalence into density contrasts according to the linear relationship, and then carry out forward gravity calculation for each rectangle cells. Next, we compare the forward gravity data with real data, and

Relationship of the Kaufman Brief Intelligence Test-Second Edition and the Wechsler Abbreviated Scale of Intelligence in children referred for ADHD.

Science.gov (United States)

Raggio, Donald J; Scattone, Dorothy; May, Warren

2010-04-01

This study examines the relationship between the Wechsler Abbreviated Scale of Intelligence (WASI) and the Kaufman Brief Intelligence Test-Second Edition (KBIT-2). Increasingly, psychologists are using brief measures of intelligence, but scant information exists regarding their clinical utility in various populations. 44 children referred for evaluation of ADHD were administered the KBIT-2 and WASI in counterbalanced order. Results of this study indicated the WASI to be a more stable measure of ADHD children's intelligence, that the KBIT-2 Vocabulary scores were significantly lower than the WASI Verbal score, and that there was significant variability within participants.

Is adaptation of the word accentuation test of premorbid intelligence necessary for use among older, Spanish-speaking immigrants in the United States?

Science.gov (United States)

Schrauf, Robert W; Weintraub, Sandra; Navarro, Ellen

2006-05-01

Adaptations of the National Adult Reading Test (NART) for assessing premorbid intelligence in languages other than English requires (a) generating word-items that are rare and do not follow grapheme-to-phoneme mappings common in that language, and (b) subsequent validation against a cognitive battery normed on the population of interest. Such tests exist for Italy, France, Spain, and Argentina, all normed against national versions of the Wechsler Adult Intelligence Scale. Given the varieties of Spanish spoken in the United States, the adaptation of the Spanish Word Accentuation Test (WAT) requires re-validating the original word list, plus possible new items, against a cognitive battery that has been normed on Spanish-speakers from many countries. This study reports the generation of 55 additional words and revalidation in a sample of 80 older, Spanish-dominant immigrants. The Batería Woodcock-Muñoz Revisada (BWM-R), normed on Spanish speakers from six countries and five U.S. states, was used to establish criterion validity. The original WAT word list accounted for 77% of the variance in the BWM-R and 58% of the variance in Ravens Colored Progressive Matrices, suggesting that the unmodified list possesses adequate predictive validity as an indicator of intelligence. Regression equations are provided for estimating BWM-R and Ravens scores from WAT scores.

Development and Psychometric Properties of the Emotional Intelligence Admission Essay Scale

Directory of Open Access Journals (Sweden)

Sharon A. Gutman

2016-07-01

Full Text Available The purpose was to describe the development and psychometric properties of the Emotional Intelligence Admission Essay scale. The authors developed an admission essay question and rating scale designed to provide information about applicants’ emotional intelligence (EI. Content validity, convergent validity, interrater reliability, and internal consistency were established. The scale was also examined to determine if it could discriminate between students with and without professional behavior problems in the academic and fieldwork settings. Content validity was found to be high by a panel of three experts in EI (content validity index = 1.0. Convergent validity with the Assessing Emotions Scale was moderate (r = .46, p < .02. Interrater reliability between two trained faculty raters was high (ICC = .91, p < .000. Internal consistency of the scale was high with a Cronbach’s alpha of .95. This version of the scale was not able to discriminate between students with and without professional behavior problems. The moderate to strong psychometric properties suggest that the EI Admission Essay Scale has the ability to provide information about applicants’ EI. The wording of the essay question must be modified to better instruct applicants to address interpersonal conflict.

Modelling traffic flows with intelligent cars and intelligent roads

NARCIS (Netherlands)

van Arem, Bart; Tampere, Chris M.J.; Malone, Kerry

2003-01-01

This paper addresses the modeling of traffic flows with intelligent cars and intelligent roads. It will describe the modeling approach MIXIC and review the results for different ADA systems: Adaptive Cruise Control, a special lane for Intelligent Vehicles, cooperative following and external speed

Successful adaptation to climate change across scales

International Nuclear Information System (INIS)

Adger, W.N.; Arnell, N.W.; University of Southampton; Tompkins, E.L.; University of East Anglia, Norwich; University of Southampton

2005-01-01

Climate change impacts and responses are presently observed in physical and ecological systems. Adaptation to these impacts is increasingly being observed in both physical and ecological systems as well as in human adjustments to resource availability and risk at different spatial and societal scales. We review the nature of adaptation and the implications of different spatial scales for these processes. We outline a set of normative evaluative criteria for judging the success of adaptations at different scales. We argue that elements of effectiveness, efficiency, equity and legitimacy are important in judging success in terms of the sustainability of development pathways into an uncertain future. We further argue that each of these elements of decision-making is implicit within presently formulated scenarios of socio-economic futures of both emission trajectories and adaptation, though with different weighting. The process by which adaptations are to be judged at different scales will involve new and challenging institutional processes. (author)

The Application of Intelligent Building Technologies to Space Hotels

Science.gov (United States)

Fawkes, S.

This paper reports that over the last few years Intelligent Building technologies have matured and standardised. It compares the functions of command and control systems in future large space facilities such as space hotels to those commonly found in Intelligent Buildings and looks at how Intelligent Building technologies may be applied to space hotels. Many of the functions required in space hotels are the same as those needed in terrestrial buildings. The adaptation of standardised, low cost, Intelligent Building technologies would reduce capital costs and ease development of future space hotels. Other aspects of Intelligent Buildings may also provide useful models for the development and operation of space hotels.

LEARNING STYLES BASED ADAPTIVE INTELLIGENT TUTORING SYSTEMS: DOCUMENT ANALYSIS OF ARTICLES PUBLISHED BETWEEN 2001. AND 2016.

Directory of Open Access Journals (Sweden)

Amit Kumar

2017-12-01

Full Text Available Actualizing instructional intercessions to suit learner contrasts has gotten extensive consideration. Among these individual contrast factors, the observational confirmation in regards to the academic benefit of learning styles has been addressed, yet the examination on the issue proceeds. Late improvements in web-based executions have driven researchers to re-examine the learning styles in adaptive tutoring frameworks. Adaptivity in intelligent tutoring systems is strongly influenced by the learning style of a learner. This study involved extensive document analysis of adaptive tutoring systems based on learning styles. Seventy-eight studies in literature from 2001 to 2016 were collected and classified under select parameters such as main focus, purpose, research types, methods, types and levels of participants, field/area of application, learner modelling, data gathering tools used and research findings. The current studies reveal that majority of the studies defined a framework or architecture of adaptive intelligent tutoring system (AITS while others focused on impact of AITS on learner satisfaction and academic outcomes. Currents trends, gaps in literature and ications were discussed.

ASDF: A New Adaptable Data Format for Seismology Suitable for Large-Scale Workflows

Science.gov (United States)

Krischer, L.; Smith, J. A.; Spinuso, A.; Tromp, J.

2014-12-01

Increases in the amounts of available data as well as computational power opens the possibility to tackle ever larger and more complex problems. This comes with a slew of new problems, two of which are the need for a more efficient use of available resources and a sensible organization and storage of the data. Both need to be satisfied in order to properly scale a problem and both are frequent bottlenecks in large seismic inversions using ambient noise or more traditional techniques.We present recent developments and ideas regarding a new data format, named ASDF (Adaptable Seismic Data Format), for all branches of seismology aiding with the aforementioned problems. The key idea is to store all information necessary to fully understand a set of data in a single file. This enables the construction of self-explaining and exchangeable data sets facilitating collaboration on large-scale problems. We incorporate the existing metadata standards FDSN StationXML and QuakeML together with waveform and auxiliary data into a common container based on the HDF5 standard. A further critical component of the format is the storage of provenance information as an extension of W3C PROV, meaning information about the history of the data, assisting with the general problem of reproducibility.Applications of the proposed new format are numerous. In the context of seismic tomography it enables the full description and storage of synthetic waveforms including information about the used model, the solver, the parameters, and other variables that influenced the final waveforms. Furthermore, intermediate products like adjoint sources, cross correlations, and receiver functions can be described and most importantly exchanged with others.Usability and tool support is crucial for any new format to gain acceptance and we additionally present a fully functional implementation of this format based on Python and ObsPy. It offers a convenient way to discover and analyze data sets as well as making

Cognitive Proficiency Index for the Canadian Edition of the Wechsler Intelligence Scale for Children-Fourth Edition

Science.gov (United States)

Saklofske, Donald H.; Zhu, Jianjun; Coalson, Diane L.; Raiford, Susan E.; Weiss, Lawrence G.

2010-01-01

The Cognitive Proficiency Index (CPI) developed for the most recent Wechsler intelligence scales comprises the working memory and processing speed subtests. It reflects the proficiency and efficiency of cognitive processing and provides another lens for analyzing children's abilities assessed by the Wechsler Intelligence Scale for Children--Fourth…

Factor analysis of Wechsler Adult Intelligence Scale-Revised in developmentally disabled persons.

Science.gov (United States)

Di Nuovo, Santo F; Buono, Serafino

2006-12-01

The results of previous studies on the factorial structure of Wechsler Intelligence Scales are somewhat inconsistent across normal and pathological samples. To study specific clinical groups, such as developmentally disabled persons, it is useful to examine the factor structure in appropriate samples. A factor analysis was carried out using the principal component method and the Varimax orthogonal rotation on the Wechsler Adult Intelligence Scale (WAIS-R) in a sample of 203 developmentally disabled persons, with a mean age of 25 years 4 months. Developmental disability ranged from mild to moderate. Partially contrasting with previous studies on normal samples, results found a two-factor solution. Wechsler's traditional Verbal and Performance scales seems to be more appropriate for this sample than the alternative three-factor solution.

Towards Brain-inspired Web Intelligence

Science.gov (United States)

Zhong, Ning

Artificial Intelligence (AI) has been mainly studied within the realm of computer based technologies. Various computational models and knowledge based systems have been developed for automated reasoning, learning, and problem-solving. However, there still exist several grand challenges. The AI research has not produced major breakthrough recently due to a lack of understanding of human brains and natural intelligence. In addition, most of the AI models and systems will not work well when dealing with large-scale, dynamically changing, open and distributed information sources at a Web scale.

Reimagining large-scale open-water fisheries governance through adaptive comanagement in hilsa shad sanctuaries

Directory of Open Access Journals (Sweden)

Martin L. van Brakel

2018-03-01

Full Text Available Almost a half million fishers in Bangladesh are predominantly reliant on the hilsa shad (Tenualosa ilisha fishery in the Meghna River and estuarine ecosystem. This paper adopts a broadened concept of social-ecological traps to frame the complex dynamics that emerge from social and ecological interactions in this highly natural resource-dependent social-ecological system (SES. We analyze how endogenous self-reinforcing processes in the system and poor initial conditions, particularly debt and lack of livelihood options outside fisheries, keep fishing households in poverty. We identify a policy decision in favor of incentive-based fisheries management as a critical juncture that influenced a trajectory of recovery in hilsa shad stocks in this complex adaptive system. Normative assessment of stakeholder perceptions indicates that fishers perceive a nominal improvement in well-being as a result of this policy. Compensation in return for compliance with a seasonal fishing ban in sanctuary areas does not, however, disrupt trap dynamics perpetuating the cycle of poverty, social exclusion, and political disempowerment in which fishing households are entrenched. Poverty and lack of alternative livelihood opportunities remain significant reasons for noncompliance with the ban as long as fishers do not have any meaningful representation in resource management and decision making. A secured tenure system through adaptive comanagement involving fishers in monitoring and enforcement of compliance with fishing bans, supported by sustainable finance for livelihood improvements outside of natural resource exploitation and predicated on responsive and accountable institutions for and by people who depend on the fishery, can form the foundation for local stewardship in a unique demonstration of contemporary large-scale open-water fisheries governance in this complex SES.

Development and reliability of the Indonesian Wechsler Adult Intelligence Scale - Fourth edition (WAIS-IV)

NARCIS (Netherlands)

Suwartono, C.; Halim, M.S.; Hidajat, L.L.; Hendriks, M.P.H.; Kessels, R.P.C.

2014-01-01

Through the years, several translated versions of Wechsler's intelligence test have been used in Indonesia, in clinical, educational or industrial settings. However, instruments such as Wechsler-Bellevue Intelligence Scale are outdated, have not been validated and lack proper normative data,

The Development of the Wechsler Scales and Their Influence on Contemporary Intelligence Testing

Science.gov (United States)

Benisz, Mark

2014-01-01

The history of intelligence testing merits study as standardized intelligence tests have been administered for only a little over a century. The most popular tests in use today are the Wechsler scales, despite the availability of other test batteries that are better grounded in contemporary theory. To understand why contemporary revisions of…

Embedded intelligent adaptive PI controller for an electromechanical system.

Science.gov (United States)

El-Nagar, Ahmad M

2016-09-01

In this study, an intelligent adaptive controller approach using the interval type-2 fuzzy neural network (IT2FNN) is presented. The proposed controller consists of a lower level proportional - integral (PI) controller, which is the main controller and an upper level IT2FNN which tuning on-line the parameters of a PI controller. The proposed adaptive PI controller based on IT2FNN (API-IT2FNN) is implemented practically using the Arduino DUE kit for controlling the speed of a nonlinear DC motor-generator system. The parameters of the IT2FNN are tuned on-line using back-propagation algorithm. The Lyapunov theorem is used to derive the stability and convergence of the IT2FNN. The obtained experimental results, which are compared with other controllers, demonstrate that the proposed API-IT2FNN is able to improve the system response over a wide range of system uncertainties. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

"Intelligent Ensemble" Projections of Precipitation and Surface Radiation in Support of Agricultural Climate Change Adaptation

Science.gov (United States)

Taylor, Patrick C.; Baker, Noel C.

2015-01-01

Earth's climate is changing and will continue to change into the foreseeable future. Expected changes in the climatological distribution of precipitation, surface temperature, and surface solar radiation will significantly impact agriculture. Adaptation strategies are, therefore, required to reduce the agricultural impacts of climate change. Climate change projections of precipitation, surface temperature, and surface solar radiation distributions are necessary input for adaption planning studies. These projections are conventionally constructed from an ensemble of climate model simulations (e.g., the Coupled Model Intercomparison Project 5 (CMIP5)) as an equal weighted average, one model one vote. Each climate model, however, represents the array of climate-relevant physical processes with varying degrees of fidelity influencing the projection of individual climate variables differently. Presented here is a new approach, termed the "Intelligent Ensemble, that constructs climate variable projections by weighting each model according to its ability to represent key physical processes, e.g., precipitation probability distribution. This approach provides added value over the equal weighted average method. Physical process metrics applied in the "Intelligent Ensemble" method are created using a combination of NASA and NOAA satellite and surface-based cloud, radiation, temperature, and precipitation data sets. The "Intelligent Ensemble" method is applied to the RCP4.5 and RCP8.5 anthropogenic climate forcing simulations within the CMIP5 archive to develop a set of climate change scenarios for precipitation, temperature, and surface solar radiation in each USDA Farm Resource Region for use in climate change adaptation studies.

Large-Scale Topic Detection and Language Model Adaptation

National Research Council Canada - National Science Library

Seymore, Kristie

1997-01-01

.... We have developed a language model adaptation scheme that takes apiece of text, chooses the most similar topic clusters from a set of over 5000 elemental topics, and uses topic specific language...

Joint U.S./Japan Conference on Adaptive Structures, 1st, Maui, HI, Nov. 13-15, 1990, Proceedings

Science.gov (United States)

Wada, Ben K.; Fanson, James L.; Miura, Koryo

1991-11-01

The present volume of adaptive structures discusses the development of control laws for an orbiting tethered antenna/reflector system test scale model, the sizing of active piezoelectric struts for vibration suppression on a space-based interferometer, the control design of a space station mobile transporter with multiple constraints, and optimum configuration control of an intelligent truss structure. Attention is given to the formulation of full state feedback for infinite order structural systems, robustness issues in the design of smart structures, passive piezoelectric vibration damping, shape control experiments with a functional model for large optical reflectors, and a mathematical basis for the design optimization of adaptive trusses in precision control. Topics addressed include approaches to the optimal adaptive geometries of intelligent truss structures, the design of an automated manufacturing system for tubular smart structures, the Sandia structural control experiments, and the zero-gravity dynamics of space structures in parabolic aircraft flight.

An innovative approach for Predicting Farmers' Adaptive Behavior at the Large Watershed Scale: Implications for Water Quality and Crop Yields

Science.gov (United States)

Valcu-Lisman, A. M.; Gassman, P. W.; Arritt, R. W.; Kling, C.; Arbuckle, J. G.; Roesch-McNally, G. E.; Panagopoulos, Y.

2017-12-01

Projected changes in the climatic patterns (higher temperatures, changes in extreme precipitation events, and higher levels of humidity) will affect agricultural cropping and management systems in major agricultural production areas. The concept of adaption to new climatic or economic conditions is an important aspect of the agricultural decision-making process. Adopting cover crops, reduced tillage, extending the drainage systems and adjusting crop management are only a few examples of adaptive actions. These actions can be easily implemented as long as they have private benefits (increased profits, reduced risk). However, each adaptive action has a different impact on water quality. Cover crops and no till usually have a positive impact on water quality, but increased tile drainage typically results in more degraded water quality due primarily to increased export of soluble nitrogen and phosphorus. The goal of this research is to determine the changes in water quality as well in crop yields as farmers undertake these adaptive measures. To answer this research question, we need to estimate the likelihood that these actions will occur, identify the agricultural areas where these actions are most likely to be implemented, and simulate the water quality impacts associated with each of these scenarios. We apply our modeling efforts to the whole Upper-Mississippi River Basin Basin (UMRB) and the Ohio-Tennessee River Basin (OTRB). These two areas are critical source regions for the re-occurring hypoxic zone in the gulf of Mexico. The likelihood of each adaptive agricultural action is estimated using data from a survey conducted in 2012. A large, representative sample of farmers in the Corn Belt was used in the survey to elicit behavioral intentions regarding three of the most important agricultural adaptation strategies (no-till, cover crops and tile drainage). We use these data to study the relationship between intent to adapt, farmer characteristics, farm

Test Review: Wechsler Preschool and Primary Scale of Intelligence-

Science.gov (United States)

Syeda, Maisha M.; Climie, Emma A.

2014-01-01

The "Wechsler Preschool and Primary Scale of Intelligence-Fourth Edition" (WPPSI-IV; Wechsler, 2012a, 2012b) is a comprehensive clinical tool, intended for assessing cognitive functioning among children aged 2 years 6 months through 7 years 7 months. Published by Pearson, the WPPSI-IV is an individually administered tool, to be used by…

Adaptive Profiles in Autism and Other Neurodevelopmental Disorders

Science.gov (United States)

Mouga, Susana; Almeida, Joana; Café, Cátia; Duque, Frederico; Oliveira, Guiomar

2015-01-01

We investigated the influence of specific autism spectrum disorder (ASD) deficits in learning adaptive behaviour, besides intelligence quotient (IQ). Participated 217 school-aged: ASD (N = 115), and other neurodevelopmental disorders (OND) groups (N = 102) matched by Full-Scale IQ. We compared standard scores of Vineland Adaptive Behaviour Scale…

Referred Students' Performance on the Reynolds Intellectual Assessment Scales and the Wechsler Intelligence Scale for Children--Fourth Edition

Science.gov (United States)

Edwards, Oliver W.; Paulin, Rachel V.

2007-01-01

This study investigates the convergent relations of the Reynolds Intellectual Assessment Scales (RIAS) and the Wechsler Intelligence Scale for Children--Fourth Edition (WISC-IV). Data from counterbalanced administrations of each instrument to 48 elementary school students referred for psychoeducational testing were examined. Analysis of the 96…

Evolutionary Hierarchical Multi-Criteria Metaheuristics for Scheduling in Large-Scale Grid Systems

CERN Document Server

Kołodziej, Joanna

2012-01-01

One of the most challenging issues in modelling today's large-scale computational systems is to effectively manage highly parametrised distributed environments such as computational grids, clouds, ad hoc networks and P2P networks. Next-generation computational grids must provide a wide range of services and high performance computing infrastructures. Various types of information and data processed in the large-scale dynamic grid environment may be incomplete, imprecise, and fragmented, which complicates the specification of proper evaluation criteria and which affects both the availability of resources and the final collective decisions of users. The complexity of grid architectures and grid management may also contribute towards higher energy consumption. All of these issues necessitate the development of intelligent resource management techniques, which are capable of capturing all of this complexity and optimising meaningful metrics for a wide range of grid applications.   This book covers hot topics in t...

Hierarchical hybrid control of manipulators: Artificial intelligence in large scale integrated circuits

Science.gov (United States)

Greene, P. H.

1972-01-01

Both in practical engineering and in control of muscular systems, low level subsystems automatically provide crude approximations to the proper response. Through low level tuning of these approximations, the proper response variant can emerge from standardized high level commands. Such systems are expressly suited to emerging large scale integrated circuit technology. A computer, using symbolic descriptions of subsystem responses, can select and shape responses of low level digital or analog microcircuits. A mathematical theory that reveals significant informational units in this style of control and software for realizing such information structures are formulated.

Relation of intelligence to ego functioning in an adult psychiatric population.

Science.gov (United States)

Allen, J G; Coyne, L; David, E

1986-01-01

Wechsler Adult Intelligence Scale-Revised (WAIS-R) IQs and clinical ratings of 10 ego functions in a diagnostically heterogeneous sample of 60 adult psychiatric inpatients were correlated. With severity of pathology statistically controlled, higher intelligence was associated with more adequate ego functioning in several spheres: primary autonomous functions, thought processes, object relations, and mastery-competence. There were also some clinically meaningful differences between the Verbal and Performance IQs in the pattern of correlations. Extending Hartmann's original views, the authors employ an ethological framework to conceptualize intelligence in relation to the ego's role in adaptation, emphasizing that intelligence is an important-albeit neglected-aspect of ego functioning.

Developing a fluid intelligence scale through a combination of Rasch modeling and cognitive psychology.

Science.gov (United States)

Primi, Ricardo

2014-09-01

Ability testing has been criticized because understanding of the construct being assessed is incomplete and because the testing has not yet been satisfactorily improved in accordance with new knowledge from cognitive psychology. This article contributes to the solution of this problem through the application of item response theory and Susan Embretson's cognitive design system for test development in the development of a fluid intelligence scale. This study is based on findings from cognitive psychology; instead of focusing on the development of a test, it focuses on the definition of a variable for the creation of a criterion-referenced measure for fluid intelligence. A geometric matrix item bank with 26 items was analyzed with data from 2,797 undergraduate students. The main result was a criterion-referenced scale that was based on information from item features that were linked to cognitive components, such as storage capacity, goal management, and abstraction; this information was used to create the descriptions of selected levels of a fluid intelligence scale. The scale proposed that the levels of fluid intelligence range from the ability to solve problems containing a limited number of bits of information with obvious relationships through the ability to solve problems that involve abstract relationships under conditions that are confounded with an information overload and distraction by mixed noise. This scale can be employed in future research to provide interpretations for the measurements of the cognitive processes mastered and the types of difficulty experienced by examinees. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Test Review: Review of the Wechsler Abbreviated Scale of Intelligence, Second Edition (WASI-II)

Science.gov (United States)

McCrimmon, Adam W.; Smith, Amanda D.

2013-01-01

The Wechsler Abbreviated Scale of Intelligence, Second Edition (WASI-II; Wechsler, 2011), published by Pearson, is a newly updated abbreviated measure of cognitive intelligence designed for individuals 6 to 90 years of age. Primarily used in clinical, psychoeducational, and research settings, the WASI-II was developed to quickly and accurately…

Exhaustion and Emotional Demands in China:A Large-Scale Investigation across Occupations

Institute of Scientific and Technical Information of China (English)

Kelly Z.Peng

2017-01-01

As the Chinese economy moves toward a market-based model,employees are likely to face more emotional demands and exhaustion at work.However,there are some unique aspects to the emotional demands of work in the Chinese cultural context.We investigate emotional demands and exhaustion in China with a large-scale sample across the six major occupations identified by the Holland classification system.Results show that incumbents of social and enterprising jobs face higher emotional demands.Unexpectedly,exhaustion differs significantly between conventional and other types of jobs.Building on the Job Demand-Resources (JD-R) model,job crafting and the cultural context,we propose that the nonlinear relationship of emotional demands and exhaustion exists only when emotional intelligence is low.Our study may inform practitioners and policy makers in Chinese enterprises about emotional demands and exhaustion for various occupations and the importance of selection and training programs in emotional intelligence.

A generic architecture for an adaptive, interoperable and intelligent type 2 diabetes mellitus care system.

Science.gov (United States)

Uribe, Gustavo A; Blobel, Bernd; López, Diego M; Schulz, Stefan

2015-01-01

Chronic diseases such as Type 2 Diabetes Mellitus (T2DM) constitute a big burden to the global health economy. T2DM Care Management requires a multi-disciplinary and multi-organizational approach. Because of different languages and terminologies, education, experiences, skills, etc., such an approach establishes a special interoperability challenge. The solution is a flexible, scalable, business-controlled, adaptive, knowledge-based, intelligent system following a systems-oriented, architecture-centric, ontology-based and policy-driven approach. The architecture of real systems is described, using the basics and principles of the Generic Component Model (GCM). For representing the functional aspects of a system the Business Process Modeling Notation (BPMN) is used. The system architecture obtained is presented using a GCM graphical notation, class diagrams and BPMN diagrams. The architecture-centric approach considers the compositional nature of the real world system and its functionalities, guarantees coherence, and provides right inferences. The level of generality provided in this paper facilitates use case specific adaptations of the system. By that way, intelligent, adaptive and interoperable T2DM care systems can be derived from the presented model as presented in another publication.

Large-scale solar purchasing

International Nuclear Information System (INIS)

1999-01-01

The principal objective of the project was to participate in the definition of a new IEA task concerning solar procurement (''the Task'') and to assess whether involvement in the task would be in the interest of the UK active solar heating industry. The project also aimed to assess the importance of large scale solar purchasing to UK active solar heating market development and to evaluate the level of interest in large scale solar purchasing amongst potential large scale purchasers (in particular housing associations and housing developers). A further aim of the project was to consider means of stimulating large scale active solar heating purchasing activity within the UK. (author)

Fast and accurate solution for the SCUC problem in large-scale power systems using adapted binary programming and enhanced dual neural network

International Nuclear Information System (INIS)

Shafie-khah, M.; Moghaddam, M.P.; Sheikh-El-Eslami, M.K.; Catalão, J.P.S.

2014-01-01

Highlights: • A novel hybrid method based on decomposition of SCUC into QP and BP problems is proposed. • An adapted binary programming and an enhanced dual neural network model are applied. • The proposed EDNN is exactly convergent to the global optimal solution of QP. • An AC power flow procedure is developed for including contingency/security issues. • It is suited for large-scale systems, providing both accurate and fast solutions. - Abstract: This paper presents a novel hybrid method for solving the security constrained unit commitment (SCUC) problem. The proposed formulation requires much less computation time in comparison with other methods while assuring the accuracy of the results. Furthermore, the framework provided here allows including an accurate description of warmth-dependent startup costs, valve point effects, multiple fuel costs, forbidden zones of operation, and AC load flow bounds. To solve the nonconvex problem, an adapted binary programming method and enhanced dual neural network model are utilized as optimization tools, and a procedure for AC power flow modeling is developed for including contingency/security issues, as new contributions to earlier studies. Unlike classical SCUC methods, the proposed method allows to simultaneously solve the unit commitment problem and comply with the network limits. In addition to conventional test systems, a real-world large-scale power system with 493 units has been used to fully validate the effectiveness of the novel hybrid method proposed

Concurrent validity of the Snijders-Oomen Nonverbal Intelligence Test 2 1/2-7-Revised with the Wechsler Preschool and Primary Scale of Intelligence - Revised

NARCIS (Netherlands)

Moore, C; O'Keefe, SL; Lawhon, D; Tellegen, P

This study examined the concurrent validity of the Snijders-Oomen Nonverbal Intelligence Test-Revised compared to the Wechsler Preschool and Primary Scale of Intelligence-Revised Subjects were 25 4-yr.-olds of lower, lower-middle, and middle socioeconomic status from both urban and rural areas of

A Self-Organizing Spatial Clustering Approach to Support Large-Scale Network RTK Systems.

Science.gov (United States)

Shen, Lili; Guo, Jiming; Wang, Lei

2018-06-06

The network real-time kinematic (RTK) technique can provide centimeter-level real time positioning solutions and play a key role in geo-spatial infrastructure. With ever-increasing popularity, network RTK systems will face issues in the support of large numbers of concurrent users. In the past, high-precision positioning services were oriented towards professionals and only supported a few concurrent users. Currently, precise positioning provides a spatial foundation for artificial intelligence (AI), and countless smart devices (autonomous cars, unmanned aerial-vehicles (UAVs), robotic equipment, etc.) require precise positioning services. Therefore, the development of approaches to support large-scale network RTK systems is urgent. In this study, we proposed a self-organizing spatial clustering (SOSC) approach which automatically clusters online users to reduce the computational load on the network RTK system server side. The experimental results indicate that both the SOSC algorithm and the grid algorithm can reduce the computational load efficiently, while the SOSC algorithm gives a more elastic and adaptive clustering solution with different datasets. The SOSC algorithm determines the cluster number and the mean distance to cluster center (MDTCC) according to the data set, while the grid approaches are all predefined. The side-effects of clustering algorithms on the user side are analyzed with real global navigation satellite system (GNSS) data sets. The experimental results indicate that 10 km can be safely used as the cluster radius threshold for the SOSC algorithm without significantly reducing the positioning precision and reliability on the user side.

9th International Symposium on Intelligent Distributed Computing

CERN Document Server

Camacho, David; Analide, Cesar; Seghrouchni, Amal; Badica, Costin

2016-01-01

This book represents the combined peer-reviewed proceedings of the ninth International Symposium on Intelligent Distributed Computing – IDC’2015, of the Workshop on Cyber Security and Resilience of Large-Scale Systems – WSRL’2015, and of the International Workshop on Future Internet and Smart Networks – FI&SN’2015. All the events were held in Guimarães, Portugal during October 7th-9th, 2015. The 46 contributions published in this book address many topics related to theory and applications of intelligent distributed computing, including: Intelligent Distributed Agent-Based Systems, Ambient Intelligence and Social Networks, Computational Sustainability, Intelligent Distributed Knowledge Representation and Processing, Smart Networks, Networked Intelligence and Intelligent Distributed Applications, amongst others.

Perceived emotional intelligence in nursing: psychometric properties of the Trait Meta-Mood Scale.

Science.gov (United States)

Aradilla-Herrero, Amor; Tomás-Sábado, Joaquín; Gómez-Benito, Juana

2014-04-01

To examine the psychometric properties of the Trait Meta-Mood Scale in the nursing context and to determine the relationships between emotional intelligence, self-esteem, alexithymia and death anxiety. The Trait Meta-Mood Scale is one of the most widely used self-report measures for assessing perceived emotional intelligence. However, in the nursing context, no extensive analysis has been conducted to examine its psychometric properties. Cross-sectional and observational study. A total of 1417 subjects participated in the study (1208 nursing students and 209 hospital nurses). The Trait Meta-Mood Scale, the Toronto Alexithymia Scale, the Rosenberg Self-Esteem Scale and the Death Anxiety Inventory were all applied to half of the sample (n = 707). A confirmatory factor analysis was carried out, and statistical analyses examined the internal consistency and test-retest reliability of the Trait Meta-Mood Scale, as well as its relationship with relevant variables. Confirmatory factor analysis confirmed the three dimensions of the original scale (Attention, Clarity and Repair). The instrument showed adequate internal consistency and temporal stability. Correlational results indicated that nurses with high scores on emotional Attention experience more death anxiety, report greater difficulties identifying feelings and have less self-esteem. By contrast, nurses with high levels of emotional Clarity and Repair showed less death anxiety and higher levels of self-esteem. The Trait Meta-Mood Scale is an effective, valid and reliable tool for measuring perceived emotional intelligence in the nursing context. Training programmes should seek to promote emotional abilities among nurses. Use of the Trait Meta-Mood Scale in the nursing context would provide information about nurses' perceived abilities to interpret and manage emotions when interacting with patients. © 2013 John Wiley & Sons Ltd.

Brazilian Portuguese transcultural adaptation of Barkley Deficits in Executive Functioning Scale (BDEFS

Directory of Open Access Journals (Sweden)

Victor Polignano Godoy

2015-12-01

Full Text Available Abstract Background Considering the importance of Executive Functions to clinical and nonclinical situations, Barkley proposed a new theory of executive functioning based on an evolutionary neuropsychological perspective and clinical research using large samples of clinical and community identified adults and children as well as children with ADHD followed to adulthood. Objective The present study aims to adapt the Barkley Deficits in Executive Functions Scales (BDEFS to Brazilian Portuguese and also assess its construct validity in a sample of normal Brazilian adults. Methods The original version of scale was adapted to Brazilian Portuguese according to the guideline from the ISPOR Task Force. To assess the semantic equivalence between the original and adapted version, both of them were applied into a sample of 25 Brazilian bilingual adults. Finally, 60 Brazilian adults completed the BDEFS and the Brazilian versions of Barratt Impulsiveness Scale (BIS-11 and Adult Self-Report Scale (ASRS-18 to assess convergent validity. Results The BDEFS Brazilian Portuguese version has semantic correspondence with the original version indicating that the adaptation procedure was successful. The BDEFS correlated significantly with the impulsivity and attention scores from the BIS-11 and ASRS-18 supporting its construct validity. Cronbach’s alpha (α = 0.961 indicated that the BDEFS translated version has satisfactory internal consistency. Discussion Together, these findings indicate the successful adaptation of the BDEFS to Brazilian Portuguese and support its utility in that population.

Intelligent structural optimization: Concept, Model and Methods

International Nuclear Information System (INIS)

Lu, Dagang; Wang, Guangyuan; Peng, Zhang

2002-01-01

Structural optimization has many characteristics of Soft Design, and so, it is necessary to apply the experience of human experts to solving the uncertain and multidisciplinary optimization problems in large-scale and complex engineering systems. With the development of artificial intelligence (AI) and computational intelligence (CI), the theory of structural optimization is now developing into the direction of intelligent optimization. In this paper, a concept of Intelligent Structural Optimization (ISO) is proposed. And then, a design process model of ISO is put forward in which each design sub-process model are discussed. Finally, the design methods of ISO are presented

Adaptive Moving Object Tracking Integrating Neural Networks And Intelligent Processing

Science.gov (United States)

Lee, James S. J.; Nguyen, Dziem D.; Lin, C.

1989-03-01

A real-time adaptive scheme is introduced to detect and track moving objects under noisy, dynamic conditions including moving sensors. This approach integrates the adaptiveness and incremental learning characteristics of neural networks with intelligent reasoning and process control. Spatiotemporal filtering is used to detect and analyze motion, exploiting the speed and accuracy of multiresolution processing. A neural network algorithm constitutes the basic computational structure for classification. A recognition and learning controller guides the on-line training of the network, and invokes pattern recognition to determine processing parameters dynamically and to verify detection results. A tracking controller acts as the central control unit, so that tracking goals direct the over-all system. Performance is benchmarked against the Widrow-Hoff algorithm, for target detection scenarios presented in diverse FLIR image sequences. Efficient algorithm design ensures that this recognition and control scheme, implemented in software and commercially available image processing hardware, meets the real-time requirements of tracking applications.

Collaborative mining and interpretation of large-scale data for biomedical research insights.

Directory of Open Access Journals (Sweden)

Georgia Tsiliki

Full Text Available Biomedical research becomes increasingly interdisciplinary and collaborative in nature. Researchers need to efficiently and effectively collaborate and make decisions by meaningfully assembling, mining and analyzing available large-scale volumes of complex multi-faceted data residing in different sources. In line with related research directives revealing that, in spite of the recent advances in data mining and computational analysis, humans can easily detect patterns which computer algorithms may have difficulty in finding, this paper reports on the practical use of an innovative web-based collaboration support platform in a biomedical research context. Arguing that dealing with data-intensive and cognitively complex settings is not a technical problem alone, the proposed platform adopts a hybrid approach that builds on the synergy between machine and human intelligence to facilitate the underlying sense-making and decision making processes. User experience shows that the platform enables more informed and quicker decisions, by displaying the aggregated information according to their needs, while also exploiting the associated human intelligence.

The Dynamic Interplay among EFL Learners' Ambiguity Tolerance, Adaptability, Cultural Intelligence, Learning Approach, and Language Achievement

Science.gov (United States)

Alahdadi, Shadi; Ghanizadeh, Afsaneh

2017-01-01

A key objective of education is to prepare individuals to be fully-functioning learners. This entails developing the cognitive, metacognitive, motivational, cultural, and emotional competencies. The present study aimed to examine the interrelationships among adaptability, tolerance of ambiguity, cultural intelligence, learning approach, and…

Large scale applicability of a Fully Adaptive Non-Intrusive Spectral Projection technique: Sensitivity and uncertainty analysis of a transient

International Nuclear Information System (INIS)

Perkó, Zoltán; Lathouwers, Danny; Kloosterman, Jan Leen; Hagen, Tim van der

2014-01-01

Highlights: • Grid and basis adaptive Polynomial Chaos techniques are presented for S and U analysis. • Dimensionality reduction and incremental polynomial order reduce computational costs. • An unprotected loss of flow transient is investigated in a Gas Cooled Fast Reactor. • S and U analysis is performed with MC and adaptive PC methods, for 42 input parameters. • PC accurately estimates means, variances, PDFs, sensitivities and uncertainties. - Abstract: Since the early years of reactor physics the most prominent sensitivity and uncertainty (S and U) analysis methods in the nuclear community have been adjoint based techniques. While these are very effective for pure neutronics problems due to the linearity of the transport equation, they become complicated when coupled non-linear systems are involved. With the continuous increase in computational power such complicated multi-physics problems are becoming progressively tractable, hence affordable and easily applicable S and U analysis tools also have to be developed in parallel. For reactor physics problems for which adjoint methods are prohibitive Polynomial Chaos (PC) techniques offer an attractive alternative to traditional random sampling based approaches. At TU Delft such PC methods have been studied for a number of years and this paper presents a large scale application of our Fully Adaptive Non-Intrusive Spectral Projection (FANISP) algorithm for performing the sensitivity and uncertainty analysis of a Gas Cooled Fast Reactor (GFR) Unprotected Loss Of Flow (ULOF) transient. The transient was simulated using the Cathare 2 code system and a fully detailed model of the GFR2400 reactor design that was investigated in the European FP7 GoFastR project. Several sources of uncertainty were taken into account amounting to an unusually high number of stochastic input parameters (42) and numerous output quantities were investigated. The results show consistently good performance of the applied adaptive PC

Intelligent systems engineering methodology

Science.gov (United States)

Fouse, Scott

1990-01-01

An added challenge for the designers of large scale systems such as Space Station Freedom is the appropriate incorporation of intelligent system technology (artificial intelligence, expert systems, knowledge-based systems, etc.) into their requirements and design. This presentation will describe a view of systems engineering which successfully addresses several aspects of this complex problem: design of large scale systems, design with requirements that are so complex they only completely unfold during the development of a baseline system and even then continue to evolve throughout the system's life cycle, design that involves the incorporation of new technologies, and design and development that takes place with many players in a distributed manner yet can be easily integrated to meet a single view of the requirements. The first generation of this methodology was developed and evolved jointly by ISX and the Lockheed Aeronautical Systems Company over the past five years on the Defense Advanced Research Projects Agency/Air Force Pilot's Associate Program, one of the largest, most complex, and most successful intelligent systems constructed to date. As the methodology has evolved it has also been applied successfully to a number of other projects. Some of the lessons learned from this experience may be applicable to Freedom.

Intelligent Electric Power Systems with Active-Adaptive Electric Networks: Challenges for Simulation Tools

Directory of Open Access Journals (Sweden)

Ufa Ruslan A.

2015-01-01

Full Text Available The motivation of the presented research is based on the needs for development of new methods and tools for adequate simulation of intelligent electric power systems with active-adaptive electric networks (IES including Flexible Alternating Current Transmission System (FACTS devices. The key requirements for the simulation were formed. The presented analysis of simulation results of IES confirms the need to use a hybrid modelling approach.

Intelligent Speed Assistance (ISA).

NARCIS (Netherlands)

2015-01-01

Intelligent Speed Assistance (ISA) has been a promising type of advanced driver support system for some decades. From a technical point of view, large scale ISA implementation is possible in the short term. The different types of ISA are expected to have different effects on behaviour and traffic

How Large Asexual Populations Adapt

Science.gov (United States)

Desai, Michael

2007-03-01

We often think of beneficial mutations as being rare, and of adaptation as a sequence of selected substitutions: a beneficial mutation occurs, spreads through a population in a selective sweep, then later another beneficial mutation occurs, and so on. This simple picture is the basis for much of our intuition about adaptive evolution, and underlies a number of practical techniques for analyzing sequence data. Yet many large and mostly asexual populations -- including a wide variety of unicellular organisms and viruses -- live in a very different world. In these populations, beneficial mutations are common, and frequently interfere or cooperate with one another as they all attempt to sweep simultaneously. This radically changes the way these populations adapt: rather than an orderly sequence of selective sweeps, evolution is a constant swarm of competing and interfering mutations. I will describe some aspects of these dynamics, including why large asexual populations cannot evolve very quickly and the character of the diversity they maintain. I will explain how this changes our expectations of sequence data, how sex can help a population adapt, and the potential role of ``mutator'' phenotypes with abnormally high mutation rates. Finally, I will discuss comparisons of these predictions with evolution experiments in laboratory yeast populations.

A Holistic Management Architecture for Large-Scale Adaptive Networks

National Research Council Canada - National Science Library

Clement, Michael R

2007-01-01

This thesis extends the traditional notion of network management as an indicator of resource availability and utilization into a systemic model of resource requirements, capabilities, and adaptable...

Multigrid preconditioned conjugate-gradient method for large-scale wave-front reconstruction.

Science.gov (United States)

Gilles, Luc; Vogel, Curtis R; Ellerbroek, Brent L

2002-09-01

We introduce a multigrid preconditioned conjugate-gradient (MGCG) iterative scheme for computing open-loop wave-front reconstructors for extreme adaptive optics systems. We present numerical simulations for a 17-m class telescope with n = 48756 sensor measurement grid points within the aperture, which indicate that our MGCG method has a rapid convergence rate for a wide range of subaperture average slope measurement signal-to-noise ratios. The total computational cost is of order n log n. Hence our scheme provides for fast wave-front simulation and control in large-scale adaptive optics systems.

Challenges in introduction of artificial intelligence in medical practice – a review of clinical trials concerning adaptation of artificial intelligence in medicine

OpenAIRE

Mielnik, Pawel Franciszek; Fojcik, Marcin; Kulbacki, Marek; Segen, Jakub

2016-01-01

An interest in Artificial Intelligence [AI] as science is growing in the last years. It has become gradually more used in the medicine. Methodology of development and testing of AI algorithms is generally well established. Use of AI in medicine requires elaboration of standards of its validation in clinical settings. This paper is a review of literature concerning clinical trials on AI adaptation in medicine

[Advances in the research of application of artificial intelligence in burn field].

Science.gov (United States)

Li, H H; Bao, Z X; Liu, X B; Zhu, S H

2018-04-20

Artificial intelligence has been able to automatically learn and judge large-scale data to some extent. Based on database of a large amount of burn data and in-depth learning, artificial intelligence can assist burn surgeons to evaluate burn surface, diagnose burn depth, guide fluid supply during shock stage, and predict prognosis, with high accuracy. With the development of technology, artificial intelligence can provide more accurate information for burn surgeons to make clinical diagnosis and treatment strategies.

Energy transfers in large-scale and small-scale dynamos

Science.gov (United States)

Samtaney, Ravi; Kumar, Rohit; Verma, Mahendra

2015-11-01

We present the energy transfers, mainly energy fluxes and shell-to-shell energy transfers in small-scale dynamo (SSD) and large-scale dynamo (LSD) using numerical simulations of MHD turbulence for Pm = 20 (SSD) and for Pm = 0.2 on 10243 grid. For SSD, we demonstrate that the magnetic energy growth is caused by nonlocal energy transfers from the large-scale or forcing-scale velocity field to small-scale magnetic field. The peak of these energy transfers move towards lower wavenumbers as dynamo evolves, which is the reason for the growth of the magnetic fields at the large scales. The energy transfers U2U (velocity to velocity) and B2B (magnetic to magnetic) are forward and local. For LSD, we show that the magnetic energy growth takes place via energy transfers from large-scale velocity field to large-scale magnetic field. We observe forward U2U and B2B energy flux, similar to SSD.

Complexity and Pilot Workload Metrics for the Evaluation of Adaptive Flight Controls on a Full Scale Piloted Aircraft

Science.gov (United States)

Hanson, Curt; Schaefer, Jacob; Burken, John J.; Larson, David; Johnson, Marcus

2014-01-01

Flight research has shown the effectiveness of adaptive flight controls for improving aircraft safety and performance in the presence of uncertainties. The National Aeronautics and Space Administration's (NASA)'s Integrated Resilient Aircraft Control (IRAC) project designed and conducted a series of flight experiments to study the impact of variations in adaptive controller design complexity on performance and handling qualities. A novel complexity metric was devised to compare the degrees of simplicity achieved in three variations of a model reference adaptive controller (MRAC) for NASA's F-18 (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) Full-Scale Advanced Systems Testbed (Gen-2A) aircraft. The complexity measures of these controllers are also compared to that of an earlier MRAC design for NASA's Intelligent Flight Control System (IFCS) project and flown on a highly modified F-15 aircraft (McDonnell Douglas, now The Boeing Company, Chicago, Illinois). Pilot comments during the IRAC research flights pointed to the importance of workload on handling qualities ratings for failure and damage scenarios. Modifications to existing pilot aggressiveness and duty cycle metrics are presented and applied to the IRAC controllers. Finally, while adaptive controllers may alleviate the effects of failures or damage on an aircraft's handling qualities, they also have the potential to introduce annoying changes to the flight dynamics or to the operation of aircraft systems. A nuisance rating scale is presented for the categorization of nuisance side-effects of adaptive controllers.

The persuasiveness of ambient intelligence

NARCIS (Netherlands)

Aarts, E.H.L.; Markopoulos, P.; Ruyter, de B.E.R.; Petkovic, M.; Jonker, W.

2007-01-01

Ambient intelligence (AmI) is a novel concept for embedded computing that builds on the large-scale integration of electronic devices into peoples’ surroundings and the ubiquitous availability of digital information to the users of such environments. The concept however is not only concerned with

Challenges and opportunities for large landscape-scale management in a shifting climate: The importance of nested adaptation responses across geospatial and temporal scales

Science.gov (United States)

Gary M. Tabor; Anne Carlson; Travis Belote

2014-01-01

The Yellowstone to Yukon Conservation Initiative (Y2Y) was established over 20 years ago as an experiment in large landscape conservation. Initially, Y2Y emerged as a response to large scale habitat fragmentation by advancing ecological connectivity. It also laid the foundation for large scale multi-stakeholder conservation collaboration with almost 200 non-...

Forecasting the natural gas demand in China using a self-adapting intelligent grey model

International Nuclear Information System (INIS)

Zeng, Bo; Li, Chuan

2016-01-01

Reasonably forecasting demands of natural gas in China is of significance as it could aid Chinese government in formulating energy policies and adjusting industrial structures. To this end, a self-adapting intelligent grey prediction model is proposed in this paper. Compared with conventional grey models which have the inherent drawbacks of fixed structure and poor adaptability, the proposed new model can automatically optimize model parameters according to the real data characteristics of modeling sequence. In this study, the proposed new model, discrete grey model, even difference grey model and classical grey model were employed, respectively, to simulate China's natural gas demands during 2002–2010 and forecast demands during 2011–2014. The results show the new model has the best simulative and predictive precision. Finally, the new model is used to forecast China's natural gas demand during 2015–2020. The forecast shows the demand will grow rapidly over the next six years. Therefore, in order to maintain the balance between the supplies and the demands for the natural gas in the future, Chinese government needs to take some measures, such as importing huge amounts of natural gas from abroad, increasing the domestic yield, using more alternative energy, and reducing the industrial reliance on natural gas. - Highlights: • A self-adapting intelligent grey prediction model (SIGM) is proposed in this paper. • The SIGM has the advantage of working with exponential functions and linear functions. • The SIGM solves the drawbacks of fixed structure and poor adaptability of grey models. • The demand of natural gas in China is successfully forecasted using the SIGM model. • The study findings can help Chinese government reasonably formulate energy policies.

A Self-Organizing Spatial Clustering Approach to Support Large-Scale Network RTK Systems

Directory of Open Access Journals (Sweden)

Lili Shen

2018-06-01

Full Text Available The network real-time kinematic (RTK technique can provide centimeter-level real time positioning solutions and play a key role in geo-spatial infrastructure. With ever-increasing popularity, network RTK systems will face issues in the support of large numbers of concurrent users. In the past, high-precision positioning services were oriented towards professionals and only supported a few concurrent users. Currently, precise positioning provides a spatial foundation for artificial intelligence (AI, and countless smart devices (autonomous cars, unmanned aerial-vehicles (UAVs, robotic equipment, etc. require precise positioning services. Therefore, the development of approaches to support large-scale network RTK systems is urgent. In this study, we proposed a self-organizing spatial clustering (SOSC approach which automatically clusters online users to reduce the computational load on the network RTK system server side. The experimental results indicate that both the SOSC algorithm and the grid algorithm can reduce the computational load efficiently, while the SOSC algorithm gives a more elastic and adaptive clustering solution with different datasets. The SOSC algorithm determines the cluster number and the mean distance to cluster center (MDTCC according to the data set, while the grid approaches are all predefined. The side-effects of clustering algorithms on the user side are analyzed with real global navigation satellite system (GNSS data sets. The experimental results indicate that 10 km can be safely used as the cluster radius threshold for the SOSC algorithm without significantly reducing the positioning precision and reliability on the user side.

Adding intelligence to scientific data management

Science.gov (United States)

Campbell, William J.; Short, Nicholas M., Jr.; Treinish, Lloyd A.

1989-01-01

NASA plans to solve some of the problems of handling large-scale scientific data bases by turning to artificial intelligence (AI) are discussed. The growth of the information glut and the ways that AI can help alleviate the resulting problems are reviewed. The employment of the Intelligent User Interface prototype, where the user will generate his own natural language query with the assistance of the system, is examined. Spatial data management, scientific data visualization, and data fusion are discussed.

Cross-cultural adaptation of the Posttraumatic Stress Disorder Checklist 5 (PCL-5 and Life Events Checklist 5 (LEC-5 for the Brazilian context

Directory of Open Access Journals (Sweden)

Eduardo de Paula Lima

Full Text Available Abstract Objective: To describe the process of cross-cultural adaptation of the Posttraumatic Stress Disorder Checklist 5 (PCL-5 and the Life Events Checklist 5 (LEC-5 for the Brazilian sociolinguistic context. Method: The adaptation process sought to establish conceptual, semantic, and operational equivalence between the original items of the questionnaire and their translated versions, following standardized protocols. Initially, two researchers translated the original version of the scale into Brazilian Portuguese. Next, a native English speaker performed the back-translation. Quantitative and qualitative criteria were used to evaluate the intelligibility of items. Five specialists compared the original and translated versions and assessed the degree of equivalence between them in terms of semantic, idiomatic, cultural and conceptual aspects. The degree of agreement between the specialists was measured using the content validity coefficient (CVC. Finally, 28 volunteers from the target population were interviewed in order to assess their level of comprehension of the items. Results: CVCs for items from both scales were satisfactory for all criteria. The mean comprehension scores were above the cutoff point established. Overall, the results showed that the adapted versions' items had adequate rates of equivalence in terms of concepts and semantics. Conclusions: The translation and adaptation processes were successful for both scales, resulting in versions that are not only equivalent to the originals, but are also intelligible for the population at large.

Beyond fluid intelligence and personality traits in social support: the role of ability based emotional intelligence.

Science.gov (United States)

Fabio, Annamaria Di

2015-01-01

Social support represents an important individual resource that has been associated with multiple indices of adaptive functioning and resiliency. Existing research has also identified an association between emotional intelligence (EI) and social support. The present study builds on prior research by investigating the contributions of ability based EI to social support, beyond the effects of fluid intelligence and personality traits. The Advanced Progressive Matrices, the Big Five Questionnaire, the Mayer Salovey Caruso EI test (MSCEIT), and the Multidimensional Scale of Perceived Social Support were administered to 149 Italian high school students. The results showed that ability based EI added significant incremental variance in explaining perceived social support, beyond the variance due to fluid intelligence and personality traits. The results underline the role of ability based EI in relation to perceived social support. Since ability based EI can be increased through specific training, the results of the present study highlight new possibilities for research and intervention in a preventive framework.

[Children's intelligence quotient following general anesthesia for dental care: a clinical observation by Chinese Wechsler young children scale of intelligence].

Science.gov (United States)

Xia, B; Wang, J H; Xiao, Y M; Liu, K Y; Yang, X D; Ge, L H

2016-04-18

It has been demonstrated that anesthetics exposure may lead to neurocognitive impairment in developing brain of animal models. However, for the limitation that the animal models cannot fully mimic the dose and duration in clinical settings especially for dental general anesthesia, the clinical significance of anesthetics exposure on developing central nervous system remains undetermined. Therefore, we conducted the current study in order to observe the fluctuation of intelligence quotient (IQ) after the administration of dental general anesthesia comparing to that before surgery. We conducted the current study in order to observe the fluctuation of intelligence quotient (IQ) after the administration of dental general anesthesia compared with that before surgery. Thirty two patients, ASA I, who were exposed to dental general anesthesia in Department of Pediatric Dentistry Peking University School and Hospital of Stomatology, aged 4 to 6.5 years, were enrolled in this prospective study. Patients with severe learning difficulties or communication disorders were excluded. Written and informed consent was obtained from each patients' family which was fully explained of the purpose and method of study. Their intelligence quotients were evaluated with the Chinese Wechsler young children scale of intelligence (Urban version) before and 2 weeks after dental anesthesia. They were treated by experienced pediatric dentists and the sevoflurane, propofol and nitrous oxide were used for general anesthesia by anesthetist. Articaine hydrochloride and epinephrine tartrate injections were used for their pulp treatment or extraction. The examiners and scorers for IQ had technical training in the test administration. All the patients were tested by the same examiner and with standardized guide language. Each subtest was scored according to the tool review. Verbal IQ and performance IQ consisted of relevant 5 subtests and full scale IQ. Statistical analyses were performed by SPSS 18

Hypersingular integral equations, waveguiding effects in Cantorian Universe and genesis of large scale structures

International Nuclear Information System (INIS)

Iovane, G.; Giordano, P.

2005-01-01

In this work we introduce the hypersingular integral equations and analyze a realistic model of gravitational waveguides on a cantorian space-time. A waveguiding effect is considered with respect to the large scale structure of the Universe, where the structure formation appears as if it were a classically self-similar random process at all astrophysical scales. The result is that it seems we live in an El Naschie's o (∞) Cantorian space-time, where gravitational lensing and waveguiding effects can explain the appearing Universe. In particular, we consider filamentary and planar large scale structures as possible refraction channels for electromagnetic radiation coming from cosmological structures. From this vision the Universe appears like a large self-similar adaptive mirrors set, thanks to three numerical simulations. Consequently, an infinite Universe is just an optical illusion that is produced by mirroring effects connected with the large scale structure of a finite and not a large Universe

Colloquium paper: adaptive specializations, social exchange, and the evolution of human intelligence.

Science.gov (United States)

Cosmides, Leda; Barrett, H Clark; Tooby, John

2010-05-11

Blank-slate theories of human intelligence propose that reasoning is carried out by general-purpose operations applied uniformly across contents. An evolutionary approach implies a radically different model of human intelligence. The task demands of different adaptive problems select for functionally specialized problem-solving strategies, unleashing massive increases in problem-solving power for ancestrally recurrent adaptive problems. Because exchange can evolve only if cooperators can detect cheaters, we hypothesized that the human mind would be equipped with a neurocognitive system specialized for reasoning about social exchange. Whereas humans perform poorly when asked to detect violations of most conditional rules, we predicted and found a dramatic spike in performance when the rule specifies an exchange and violations correspond to cheating. According to critics, people's uncanny accuracy at detecting violations of social exchange rules does not reflect a cheater detection mechanism, but extends instead to all rules regulating when actions are permitted (deontic conditionals). Here we report experimental tests that falsify these theories by demonstrating that deontic rules as a class do not elicit the search for violations. We show that the cheater detection system functions with pinpoint accuracy, searching for violations of social exchange rules only when these are likely to reveal the presence of someone who intends to cheat. It does not search for violations of social exchange rules when these are accidental, when they do not benefit the violator, or when the situation would make cheating difficult.

Large-scale data analytics

CERN Document Server

Gkoulalas-Divanis, Aris

2014-01-01

Provides cutting-edge research in large-scale data analytics from diverse scientific areas Surveys varied subject areas and reports on individual results of research in the field Shares many tips and insights into large-scale data analytics from authors and editors with long-term experience and specialization in the field

WAMS Based Intelligent Operation and Control of Modern Power System with large Scale Renewable Energy Penetration

DEFF Research Database (Denmark)

Rather, Zakir Hussain

security limits. Under such scenario, progressive displacement of conventional generation by wind generation is expected to eventually lead a complex power system with least presence of central power plants. Consequently the support from conventional power plants is expected to reach its all-time low...... system voltage control responsibility from conventional power plants to wind turbines. With increased wind penetration and displaced conventional central power plants, dynamic voltage security has been identified as one of the challenging issue for large scale wind integration. To address the dynamic...... security issue, a WAMS based systematic voltage control scheme for large scale wind integrated power system has been proposed. Along with the optimal reactive power compensation, the proposed scheme considers voltage support from wind farms (equipped with voltage support functionality) and refurbished...

Various approaches to the modelling of large scale 3-dimensional circulation in the Ocean

Digital Repository Service at National Institute of Oceanography (India)

Shaji, C.; Bahulayan, N.; Rao, A.D.; Dube, S.K.

In this paper, the three different approaches to the modelling of large scale 3-dimensional flow in the ocean such as the diagnostic, semi-diagnostic (adaptation) and the prognostic are discussed in detail. Three-dimensional solutions are obtained...

Can enriching emotional intelligence improve medical students? proactivity and adaptability during OB/GYN clerkships?

OpenAIRE

Guseh, Stephanie H.; Chen, Xiaodong P.; Johnson, Natasha R.

2015-01-01

Objectives: The purpose of this pilot study was to examine our hypothesis that enriching workplace emotional intelligence through resident coaches could improve third-year medical students’ adaptability and proactivity on the Obstetrics and Gynecology clerkship. Methods: An observational pilot study was conducted in a teaching hospital. Fourteen 3rd year medical students from two cohorts of clerkships were randomly divided into two groups, and equally assigned to trained resident coaches and ...

Validación estructural del Wong-Law Emotional Intelligence Scale (WLEIS: estudio preliminar en adultos / Structural validation of the Wong-Law Emotional Intelligence Scale (WLEIS: preliminary study in adults

Directory of Open Access Journals (Sweden)

César Merino Soto

2016-06-01

Full Text Available RESUMEN: La medición de la inteligencia emocional ha tenido muchas propuestas en formato de autorreporte. Una de estas es el Wong-Law Emotional Intelligence Scale (WLEIS, creada para el contexto laboral y que evalúa valoración y expresión de las emociones propias, valoración y reconocimiento de las emociones en otros, regulación de las propias emociones y uso de la emoción para facilitar el desempeño. Hay poca evidencia psicométrica sobre el Wong-Law Emotional Intelligence Scale en habla hispana, lo que posiblemente conduce a que sea también poco utilizado en la investigación y práctica profesional. El objetivo del presente estudio es presentar los primeros resultados de la validez de la estructura interna del WLEIS en adultos peruanos. Fueron 120 participantes (72 mujeres entre 17 y 59 años, quienes respondieron al cuestionario mediados por internet. Se analizó la estructura interna mediante metodología de ecuaciones estructurales. Se halló una satisfactoria estructura de 4 factores y elevadas cargas factoriales de los ítems; las correlaciones interfactores fueron altas o moderadamente altas; y la consistencia interna fue buena. Se concluye que los primeros resultados son aceptables para asumir que el modelo de Wong-Law también es aparentemente generalizable. ABSTRACT: The measurement of emotional intelligence has had many proposals in the form of self-report. One of these is the Wong-Law Emotional Intelligence Scale (WLEIS, created for the job context and which evaluates valuation and the expression of self-emotions; valuation and recognition of emotions in others; regulation of one’s own emotions and the use of emotion to facilitate performance. There is little psychometric evidence regarding the Wong-Law Emotional Intelligence Scale in the Spanish speaking world, which could lead to it also being little used in research and professional practice. The objective of this study is to present the first results of the internal

Large-scale grid management

International Nuclear Information System (INIS)

Langdal, Bjoern Inge; Eggen, Arnt Ove

2003-01-01

The network companies in the Norwegian electricity industry now have to establish a large-scale network management, a concept essentially characterized by (1) broader focus (Broad Band, Multi Utility,...) and (2) bigger units with large networks and more customers. Research done by SINTEF Energy Research shows so far that the approaches within large-scale network management may be structured according to three main challenges: centralization, decentralization and out sourcing. The article is part of a planned series

The added value of a gaming context and intelligent adaptation for a mobile application for vocabulary learning

NARCIS (Netherlands)

Sandberg, J.; Maris, M.; Hoogendoorn, P.

2014-01-01

Two groups participated in a study on the added value of a gaming context and intelligent adaptation for a mobile learning application. The control group worked at home for a fortnight with the original Mobile English Learning application (MEL-original) developed in a previous project. The

Fatigue distribution optimization for offshore wind farms using intelligent agent control

DEFF Research Database (Denmark)

Zhao, Rongyong; Shen, Wen Zhong; Knudsen, Torben

2012-01-01

with its neighbouring downwind turbines and organizes them adaptively into a wind delivery group along the wind direction. The agent attributes and the event structure are designed on the basis of the intelligent agent theory by using the unified modelling language. The control strategy of the intelligent......A novel control approach is proposed to optimize the fatigue distribution of wind turbines in a large‐scale offshore wind farm on the basis of an intelligent agent theory. In this approach, each wind turbine is considered to be an intelligent agent. The turbine at the farm boundary communicates...... coefficient for every wind turbine. The optimization is constrained such that the average fatigue for every turbine is smaller than what would be achieved by conventional dispatch and such that the total power loss of the wind farm is restricted to a few percent of the total power. This intelligent agent...

Intelligence.

Science.gov (United States)

Sternberg, Robert J

2012-03-01

Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain-especially with regard to the functioning in the prefrontal cortex-and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret.

Intelligence

Science.gov (United States)

Sternberg, Robert J.

2012-01-01

Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain—especially with regard to the functioning in the prefrontal cortex—and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret. PMID:22577301

Large-scale transportation network congestion evolution prediction using deep learning theory.

Science.gov (United States)

Ma, Xiaolei; Yu, Haiyang; Wang, Yunpeng; Wang, Yinhai

2015-01-01

Understanding how congestion at one location can cause ripples throughout large-scale transportation network is vital for transportation researchers and practitioners to pinpoint traffic bottlenecks for congestion mitigation. Traditional studies rely on either mathematical equations or simulation techniques to model traffic congestion dynamics. However, most of the approaches have limitations, largely due to unrealistic assumptions and cumbersome parameter calibration process. With the development of Intelligent Transportation Systems (ITS) and Internet of Things (IoT), transportation data become more and more ubiquitous. This triggers a series of data-driven research to investigate transportation phenomena. Among them, deep learning theory is considered one of the most promising techniques to tackle tremendous high-dimensional data. This study attempts to extend deep learning theory into large-scale transportation network analysis. A deep Restricted Boltzmann Machine and Recurrent Neural Network architecture is utilized to model and predict traffic congestion evolution based on Global Positioning System (GPS) data from taxi. A numerical study in Ningbo, China is conducted to validate the effectiveness and efficiency of the proposed method. Results show that the prediction accuracy can achieve as high as 88% within less than 6 minutes when the model is implemented in a Graphic Processing Unit (GPU)-based parallel computing environment. The predicted congestion evolution patterns can be visualized temporally and spatially through a map-based platform to identify the vulnerable links for proactive congestion mitigation.

Ethics of large-scale change

OpenAIRE

Arler, Finn

2006-01-01

  The subject of this paper is long-term large-scale changes in human society. Some very significant examples of large-scale change are presented: human population growth, human appropriation of land and primary production, the human use of fossil fuels, and climate change. The question is posed, which kind of attitude is appropriate when dealing with large-scale changes like these from an ethical point of view. Three kinds of approaches are discussed: Aldo Leopold's mountain thinking, th...

The relationship of the Reynolds Intellectual Assessment Scales and the Wechsler Adult Intelligence Scale-Third Edition.

Science.gov (United States)

Smith, Billy L; McChristian, Chrystal L; Smith, Teresa D; Meaux, Julie

2009-08-01

The purpose of this study was to compare scores on the Reynolds Intellectual Assessment Scales (RIAS) with scores on the Wechsler Adult Intelligence Scale-Third Edition (WAIS-III) in a group of college students diagnosed with a Learning Disability, Attention-Deficit Hyperactivity Disorder (ADHD), or a combination of the two. The RIAS Composite Index score was significantly higher than the WAIS-III Full Scale IQ, although scores on both tests were in the average range. Correlations between the two tests were significant on all measures. Male students were significantly higher than female students on both the RIAS Composite Index and on the WAIS-III Full Scale IQ. Although the ADHD group was higher on IQ than the Learning Disabled and combined disorder groups on all IQ measures, no significant differences were found.

Adaptive user interfaces

CERN Document Server

1990-01-01

This book describes techniques for designing and building adaptive user interfaces developed in the large AID project undertaken by the contributors.Key Features* Describes one of the few large-scale adaptive interface projects in the world* Outlines the principles of adaptivity in human-computer interaction

Composite Reliability and Standard Errors of Measurement for a Seven-Subtest Short Form of the Wechsler Adult Intelligence Scale-Revised.

Science.gov (United States)

Schretlen, David; And Others

1994-01-01

Composite reliability and standard errors of measurement were computed for prorated Verbal, Performance, and Full-Scale intelligence quotient (IQ) scores from a seven-subtest short form of the Wechsler Adult Intelligence Scale-Revised. Results with 1,880 adults (standardization sample) indicate that this form is as reliable as the complete test.…

Validation of the Child Premorbid Intelligence Estimate method to predict premorbid Wechsler Intelligence Scale for Children-Fourth Edition Full Scale IQ among children with brain injury.

Science.gov (United States)

Schoenberg, Mike R; Lange, Rael T; Saklofske, Donald H; Suarez, Mariann; Brickell, Tracey A

2008-12-01

Determination of neuropsychological impairment involves contrasting obtained performances with a comparison standard, which is often an estimate of premorbid IQ. M. R. Schoenberg, R. T. Lange, T. A. Brickell, and D. H. Saklofske (2007) proposed the Child Premorbid Intelligence Estimate (CPIE) to predict premorbid Full Scale IQ (FSIQ) using the Wechsler Intelligence Scale for Children-4th Edition (WISC-IV; Wechsler, 2003). The CPIE includes 12 algorithms to predict FSIQ, 1 using demographic variables and 11 algorithms combining WISC-IV subtest raw scores with demographic variables. The CPIE was applied to a sample of children with acquired traumatic brain injury (TBI sample; n = 40) and a healthy demographically matched sample (n = 40). Paired-samples t tests found estimated premorbid FSIQ differed from obtained FSIQ when applied to the TBI sample (ps .02). The demographic only algorithm performed well at a group level, but estimates were restricted in range. Algorithms combining single subtest scores with demographics performed adequately. Results support the clinical application of the CPIE algorithms. However, limitations to estimating individual premorbid ability, including statistical and developmental factors, must be considered. (c) 2008 APA, all rights reserved.

DEVELOPMENT AND ADAPTATION OF VORTEX REALIZABLE MEASUREMENT SYSTEM FOR BENCHMARK TEST WITH LARGE SCALE MODEL OF NUCLEAR REACTOR

Directory of Open Access Journals (Sweden)

S. M. Dmitriev

2017-01-01

Full Text Available The last decades development of applied calculation methods of nuclear reactor thermal and hydraulic processes are marked by the rapid growth of the High Performance Computing (HPC, which contribute to the active introduction of Computational Fluid Dynamics (CFD. The use of such programs to justify technical and economic parameters and especially the safety of nuclear reactors requires comprehensive verification of mathematical models and CFD programs. The aim of the work was the development and adaptation of a measuring system having the characteristics necessary for its application in the verification test (experimental facility. It’s main objective is to study the processes of coolant flow mixing with different physical properties (for example, the concentration of dissolved impurities inside a large-scale reactor model. The basic method used for registration of the spatial concentration field in the mixing area is the method of spatial conductometry. In the course of the work, a measurement complex, including spatial conductometric sensors, a system of secondary converters and software, was created. Methods of calibration and normalization of measurement results are developed. Averaged concentration fields, nonstationary realizations of the measured local conductivity were obtained during the first experimental series, spectral and statistical analysis of the realizations were carried out.The acquired data are compared with pretest CFD-calculations performed in the ANSYS CFX program. A joint analysis of the obtained results made it possible to identify the main regularities of the process under study, and to demonstrate the capabilities of the designed measuring system to receive the experimental data of the «CFD-quality» required for verification.The carried out adaptation of spatial sensors allows to conduct a more extensive program of experimental tests, on the basis of which a databank and necessary generalizations will be created

Adapting to large-scale changes in Advanced Placement Biology, Chemistry, and Physics: the impact of online teacher communities

Science.gov (United States)

Frumin, Kim; Dede, Chris; Fischer, Christian; Foster, Brandon; Lawrenz, Frances; Eisenkraft, Arthur; Fishman, Barry; Jurist Levy, Abigail; McCoy, Ayana

2018-03-01

Over the past decade, the field of teacher professional learning has coalesced around core characteristics of high quality professional development experiences (e.g. Borko, Jacobs, & Koellner, 2010. Contemporary approaches to teacher professional development. In P. L. Peterson, E. Baker, & B. McGaw (Eds.), International encyclopedia of education (Vol. 7, pp. 548-556). Oxford: Elsevier.; Darling-Hammond, Hyler, & Gardner, 2017. Effective teacher professional development. Palo Alto, CA: Learning Policy Institute). Many countries have found these advances of great interest because of a desire to build teacher capacity in science education and across the full curriculum. This paper continues this progress by examining the role and impact of an online professional development community within the top-down, large-scale curriculum and assessment revision of Advanced Placement (AP) Biology, Chemistry, and Physics. This paper is part of a five-year, longitudinal, U.S. National Science Foundation-funded project to study the relative effectiveness of various types of professional development in enabling teachers to adapt to the revised AP course goals and exams. Of the many forms of professional development our research has examined, preliminary analyses indicated that participation in the College Board's online AP Teacher Community (APTC) - where teachers can discuss teaching strategies, share resources, and connect with each other - had positive, direct, and statistically significant association with teacher self-reported shifts in practice and with gains in student AP scores (Fishman et al., 2014). This study explored how usage of the online APTC might be useful to teachers and examined a more robust estimate of these effects. Findings from the experience of AP teachers may be valuable in supporting other large-scale curriculum changes, such as the U.S. Next Generation Science Standards or Common Core Standards, as well as parallel curricular shifts in other countries.

Wechsler Intelligence Scale for Children-Third and -Fourth Edition: Predictors of Academic Achievement in Children with Attention-Deficit/Hyperactivity Disorder

Science.gov (United States)

Mayes, Susan Dickerson; Calhoun, Susan L.

2007-01-01

IQ and achievement scores were analyzed for 678 children with attention-deficit/hyperactivity disorder (ADHD; 6-16 years of age, IQ=80) administered the Wechsler Intelligence Scale for Children-Third Edition (WISC-III; n=586) and Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV, n=92). Approximately 76% of children in both samples…

Exploration of malingering indices in the Wechsler Adult Intelligence Scale-Fourth Edition Digit Span subtest.

Science.gov (United States)

Reese, Caitlin S; Suhr, Julie A; Riddle, Tara L

2012-03-01

Prior research shows that Digit Span is a useful embedded measure of malingering. However, the Wechsler Adult Intelligence Scale-IV (Wechsler, 2008) altered Digit Span in meaningful ways, necessitating another look at Digit Span as an embedded measure of malingering. Using a simulated malingerer design, we examined the predictive accuracy of existing Digit Span validity indices and explored whether patterns of performance utilizing the new version would provide additional evidence for malingering. Undergraduates with a history of mild head injury performed with best effort or simulated impaired cognition and were also compared with a large sample of non-head-injured controls. Previously established cutoffs for the age-corrected scaled score and Reliable Digit Span (RDS) performed similarly in the present samples. Patterns of RDS length using all three subscales of the new scale were different in malingerers when compared with both head-injured and non-head-injured controls. Two potential alternative RDS scores were introduced, which showed better sensitivity than the traditional RDS, while retaining specificity to malingering.

ENGINEERING OF UNIVERSITY INTELLIGENT LEARNING SYSTEMS

Directory of Open Access Journals (Sweden)

Vasiliy M. Trembach

2016-01-01

Full Text Available In the article issues of engineering intelligent tutoring systems of University with adaptation are considered. The article also dwells on some modern approaches to engineering of information systems. It shows the role of engineering e-learning devices (systems in system engineering. The article describes the basic principles of system engineering and these principles are expanded regarding to intelligent information systems. The structure of intelligent learning systems with adaptation of the individual learning environments based on services is represented in the article.

Prospective EFL Teachers' Emotional Intelligence and Tablet Computer Use and Literacy

Science.gov (United States)

Herguner, Sinem

2017-01-01

The aim of this study was to investigate whether there is a relationship between tablet computer use and literacy, and emotional intelligence of prospective English language teachers. The study used a survey approach. In the study, "Prospective Teachers Tablet Computer Use and Literacy Scale" and an adapted and translated version into…

Scale-adaptive Local Patches for Robust Visual Object Tracking

Directory of Open Access Journals (Sweden)

Kang Sun

2014-04-01

Full Text Available This paper discusses the problem of robustly tracking objects which undergo rapid and dramatic scale changes. To remove the weakness of global appearance models, we present a novel scheme that combines object’s global and local appearance features. The local feature is a set of local patches that geometrically constrain the changes in the target’s appearance. In order to adapt to the object’s geometric deformation, the local patches could be removed and added online. The addition of these patches is constrained by the global features such as color, texture and motion. The global visual features are updated via the stable local patches during tracking. To deal with scale changes, we adapt the scale of patches in addition to adapting the object bound box. We evaluate our method by comparing it to several state-of-the-art trackers on publicly available datasets. The experimental results on challenging sequences confirm that, by using this scale-adaptive local patches and global properties, our tracker outperforms the related trackers in many cases by having smaller failure rate as well as better accuracy.

Self-adapted sliding scale spectroscopy ADC

International Nuclear Information System (INIS)

Xu Qichun; Wang Jingjin

1992-01-01

The traditional sliding scale technique causes a disabled range that is equal to the sliding length, thus reduces the analysis range of a MCA. A method for reduce ADC's DNL, which is called self-adapted sliding scale method, has been designed and tested. With this method, the disabled range caused by a traditional sliding scale method can be eliminated by a random trial scale and there is no need of an additional amplitude discriminator with swing threshold. A special trial-and-correct logic is presented. The tested DNL of the spectroscopy ADC described here is less than 0.5%

Enhancement of large fluctuations to extinction in adaptive networks

Science.gov (United States)

Hindes, Jason; Schwartz, Ira B.; Shaw, Leah B.

2018-01-01

During an epidemic, individual nodes in a network may adapt their connections to reduce the chance of infection. A common form of adaption is avoidance rewiring, where a noninfected node breaks a connection to an infected neighbor and forms a new connection to another noninfected node. Here we explore the effects of such adaptivity on stochastic fluctuations in the susceptible-infected-susceptible model, focusing on the largest fluctuations that result in extinction of infection. Using techniques from large-deviation theory, combined with a measurement of heterogeneity in the susceptible degree distribution at the endemic state, we are able to predict and analyze large fluctuations and extinction in adaptive networks. We find that in the limit of small rewiring there is a sharp exponential reduction in mean extinction times compared to the case of zero adaption. Furthermore, we find an exponential enhancement in the probability of large fluctuations with increased rewiring rate, even when holding the average number of infected nodes constant.

Bio-inspired wooden actuators for large scale applications.

Science.gov (United States)

Rüggeberg, Markus; Burgert, Ingo

2015-01-01

Implementing programmable actuation into materials and structures is a major topic in the field of smart materials. In particular the bilayer principle has been employed to develop actuators that respond to various kinds of stimuli. A multitude of small scale applications down to micrometer size have been developed, but up-scaling remains challenging due to either limitations in mechanical stiffness of the material or in the manufacturing processes. Here, we demonstrate the actuation of wooden bilayers in response to changes in relative humidity, making use of the high material stiffness and a good machinability to reach large scale actuation and application. Amplitude and response time of the actuation were measured and can be predicted and controlled by adapting the geometry and the constitution of the bilayers. Field tests in full weathering conditions revealed long-term stability of the actuation. The potential of the concept is shown by a first demonstrator. With the sensor and actuator intrinsically incorporated in the wooden bilayers, the daily change in relative humidity is exploited for an autonomous and solar powered movement of a tracker for solar modules.

Development and Psychometric Evaluation of the Adaptive Functions of Music Listening Scale.

Science.gov (United States)

Groarke, Jenny M; Hogan, Michael J

2018-01-01

Music listening may serve many adaptive functions in everyday life. However, studies examining the relationship between the functions of music listening (FML) and wellbeing outcomes have produced mixed findings. The purpose of this study is to develop a new measure to assess music listening functions that is psychometrically robust, and suitable for outcomes-based research on music listening and wellbeing. Scale items were developed based on a literature review and a prior qualitative enquiry. The items were reviewed by four content experts in music psychology and scale development. Scale structure was investigated by EFA and CFA in two large samples of participants ( N = 1,191, 17-66 years, M = 22.04, SD = 6.23, 326 males). Tests of dimensionality revealed a 46-item scale with 11 factors for the Adaptive Functions of Music Listening (AFML) scale. Namely, Stress Regulation, Anxiety Regulation, Anger Regulation, Loneliness Regulation, Rumination, Reminiscence, Strong Emotional Experiences, Awe and Appreciation, Cognitive Regulation, Identity , and Sleep FML. The scale and its subscales possess good internal consistency and construct validity. In line with theory and research on gender differences in FML, scores on factors representing affect regulation FML were significantly higher among female respondents. Supporting the concurrent validity of the AFML scale, factors were positively correlated with an existing measure of the FML-the Music USE questionnaire. Further evidence of construct validity derives from positive associations between affect regulation factor scores and level of reappraisal, and lack of association with suppression, as measured by the Emotion Regulation Questionnaire. Consistent with the view that adaptive FML are positively related to wellbeing, a number of factors, affect regulation factors in particular, were significantly positively correlated with subjective, psychological, and social wellbeing measures across two cross-sectional studies.

Development and Psychometric Evaluation of the Adaptive Functions of Music Listening Scale

Directory of Open Access Journals (Sweden)

Jenny M. Groarke

2018-04-01

Full Text Available Music listening may serve many adaptive functions in everyday life. However, studies examining the relationship between the functions of music listening (FML and wellbeing outcomes have produced mixed findings. The purpose of this study is to develop a new measure to assess music listening functions that is psychometrically robust, and suitable for outcomes-based research on music listening and wellbeing. Scale items were developed based on a literature review and a prior qualitative enquiry. The items were reviewed by four content experts in music psychology and scale development. Scale structure was investigated by EFA and CFA in two large samples of participants (N = 1,191, 17–66 years, M = 22.04, SD = 6.23, 326 males. Tests of dimensionality revealed a 46-item scale with 11 factors for the Adaptive Functions of Music Listening (AFML scale. Namely, Stress Regulation, Anxiety Regulation, Anger Regulation, Loneliness Regulation, Rumination, Reminiscence, Strong Emotional Experiences, Awe and Appreciation, Cognitive Regulation, Identity, and Sleep FML. The scale and its subscales possess good internal consistency and construct validity. In line with theory and research on gender differences in FML, scores on factors representing affect regulation FML were significantly higher among female respondents. Supporting the concurrent validity of the AFML scale, factors were positively correlated with an existing measure of the FML—the Music USE questionnaire. Further evidence of construct validity derives from positive associations between affect regulation factor scores and level of reappraisal, and lack of association with suppression, as measured by the Emotion Regulation Questionnaire. Consistent with the view that adaptive FML are positively related to wellbeing, a number of factors, affect regulation factors in particular, were significantly positively correlated with subjective, psychological, and social wellbeing measures across two cross

Transcultural adaptation and validation of Hindi version of Quebec Back Pain Disability Scale.

Science.gov (United States)

Zaidi, Sahar; Verma, Shalini; Moiz, Jamal Ali; Hussain, Mohammed E

2017-08-07

To transculturally adapt the Quebec Back Pain Disability Scale for Hindi-speaking population and examine its psychometric properties in patients with low back pain. The Quebec Back Pain Disability Scale was translated and cross-culturally adapted into Hindi following international guidelines. Hindi version of the scale was completed by 120 patients with low back pain and 60 healthy controls. Patients with low back pain were also administered the Hindi-Roland Morris Disability Questionnaire and Visual Analog Scale. Psychometric evaluation included test-retest reliability, convergent and discriminative validity. Exploratory factor analysis was carried out to determine the factor structure. The factorial analysis revealed a four-factor solution (bending/carrying, ambulation/reach, prolonged postures and rest). Convergent validity was confirmed by high correlation of Hindi Quebec Back Pain Disability Scale to the Hindi version of Roland Morris Disability Questionnaire (r = 0.77 and p Visual Analog Scale (r = 0.682 and p Disability Scale has good test-retest reliability, discriminative and convergent validity and is appropriate for clinical and research use in Hindi-speaking low back pain patients. Implications for rehabilitation Linguistically and culturally adapted questionnaires help researchers make adequate inferences about instruments measuring health and quality of life. The translated version would serve as a valid research tool allowing comparability of data across cultures thus, providing opportunities for large multicenter, multicountry trials. A Hindi Quebec Back Pain Disability Scale version will help to improve the quality and efficacy of assessment of low back pain by developing in patients, a better understanding of the items which can be easily correlated with the activities of daily living.

Improved decomposition–coordination and discrete differential dynamic programming for optimization of large-scale hydropower system

International Nuclear Information System (INIS)

Li, Chunlong; Zhou, Jianzhong; Ouyang, Shuo; Ding, Xiaoling; Chen, Lu

2014-01-01

Highlights: • Optimization of large-scale hydropower system in the Yangtze River basin. • Improved decomposition–coordination and discrete differential dynamic programming. • Generating initial solution randomly to reduce generation time. • Proposing relative coefficient for more power generation. • Proposing adaptive bias corridor technology to enhance convergence speed. - Abstract: With the construction of major hydro plants, more and more large-scale hydropower systems are taking shape gradually, which brings up a challenge to optimize these systems. Optimization of large-scale hydropower system (OLHS), which is to determine water discharges or water levels of overall hydro plants for maximizing total power generation when subjecting to lots of constrains, is a high dimensional, nonlinear and coupling complex problem. In order to solve the OLHS problem effectively, an improved decomposition–coordination and discrete differential dynamic programming (IDC–DDDP) method is proposed in this paper. A strategy that initial solution is generated randomly is adopted to reduce generation time. Meanwhile, a relative coefficient based on maximum output capacity is proposed for more power generation. Moreover, an adaptive bias corridor technology is proposed to enhance convergence speed. The proposed method is applied to long-term optimal dispatches of large-scale hydropower system (LHS) in the Yangtze River basin. Compared to other methods, IDC–DDDP has competitive performances in not only total power generation but also convergence speed, which provides a new method to solve the OLHS problem

Reproducing the Wechsler Intelligence Scale for Children-Fifth Edition: Factor Model Results

Science.gov (United States)

Beaujean, A. Alexander

2016-01-01

One of the ways to increase the reproducibility of research is for authors to provide a sufficient description of the data analytic procedures so that others can replicate the results. The publishers of the Wechsler Intelligence Scale for Children-Fifth Edition (WISC-V) do not follow these guidelines when reporting their confirmatory factor…

Political consultation and large-scale research

International Nuclear Information System (INIS)

Bechmann, G.; Folkers, H.

1977-01-01

Large-scale research and policy consulting have an intermediary position between sociological sub-systems. While large-scale research coordinates science, policy, and production, policy consulting coordinates science, policy and political spheres. In this very position, large-scale research and policy consulting lack of institutional guarantees and rational back-ground guarantee which are characteristic for their sociological environment. This large-scale research can neither deal with the production of innovative goods under consideration of rentability, nor can it hope for full recognition by the basis-oriented scientific community. Policy consulting knows neither the competence assignment of the political system to make decisions nor can it judge succesfully by the critical standards of the established social science, at least as far as the present situation is concerned. This intermediary position of large-scale research and policy consulting has, in three points, a consequence supporting the thesis which states that this is a new form of institutionalization of science: These are: 1) external control, 2) the organization form, 3) the theoretical conception of large-scale research and policy consulting. (orig.) [de

Career Adapt-Abilities Scale--Netherlands Form: Psychometric Properties and Relationships to Ability, Personality, and Regulatory Focus

Science.gov (United States)

van Vianen, Annelies E. M.; Klehe, Ute-Christine; Koen, Jessie; Dries, Nicky

2012-01-01

The Career Adapt-Abilities Scale (CAAS)--Netherlands Form consists of four scales, each with six items, which measure concern, control, curiosity, and confidence as psychosocial resources for managing occupational transitions, developmental tasks, and work traumas. Internal consistency estimates for the subscale and total scores ranged from…

Large-scale multimedia modeling applications

International Nuclear Information System (INIS)

Droppo, J.G. Jr.; Buck, J.W.; Whelan, G.; Strenge, D.L.; Castleton, K.J.; Gelston, G.M.

1995-08-01

Over the past decade, the US Department of Energy (DOE) and other agencies have faced increasing scrutiny for a wide range of environmental issues related to past and current practices. A number of large-scale applications have been undertaken that required analysis of large numbers of potential environmental issues over a wide range of environmental conditions and contaminants. Several of these applications, referred to here as large-scale applications, have addressed long-term public health risks using a holistic approach for assessing impacts from potential waterborne and airborne transport pathways. Multimedia models such as the Multimedia Environmental Pollutant Assessment System (MEPAS) were designed for use in such applications. MEPAS integrates radioactive and hazardous contaminants impact computations for major exposure routes via air, surface water, ground water, and overland flow transport. A number of large-scale applications of MEPAS have been conducted to assess various endpoints for environmental and human health impacts. These applications are described in terms of lessons learned in the development of an effective approach for large-scale applications

Validation of an Adapted French Form of the Career Adapt-Abilities Scale in Four Francophone Countries

Science.gov (United States)

Johnston, Claire S.; Broonen, Jean-Paul; Stauffer, Sarah D.; Hamtiaux, Armanda; Pouyaud, Jacques; Zecca, Gregory; Houssemand, Claude; Rossier, Jerome

2013-01-01

This study presents the validation of a French version of the Career Adapt-Abilities Scale in four Francophone countries. The aim was to re-analyze the item selection and then compare this newly developed French-language form with the international form 2.0. Exploratory factor analysis was used as a tool for item selection, and confirmatory factor…

Cultural adaptation and validation of Stroke Impact Scale 3.0 version in Uganda: A small-scale study.

Science.gov (United States)

Kamwesiga, Julius T; von Koch, Lena; Kottorp, Anders; Guidetti, Susanne

2016-01-01

Knowledge is scarce about the impact of stroke in Uganda, and culturally adapted, psychometrically tested patient-reported outcome measures are lacking. The Stroke Impact Scale 3.0 is recommended, but it has not been culturally adapted and validated in Uganda. To culturally adapt and determine the psychometric properties of the Stroke Impact Scale 3.0 in the Ugandan context on a small scale. The Stroke Impact Scale 3.0 was culturally adapted to form Stroke Impact Scale 3.0 Uganda ( in English ) by involving 25 participants in three different expert committees. Subsequently, Stroke Impact Scale 3.0 Uganda from English to Luganda language was done in accordance with guidelines. The first language in Uganda is English and Luganda is the main spoken language in Kampala city and its surroundings. Translation of Stroke Impact Scale 3.0 Uganda ( both in English and Luganda ) was then tested psychometrically by applying a Rasch model on data collected from 95 participants with stroke. Overall, 10 of 59 (17%) items in the eight domains of the Stroke Impact Scale 3.0 were culturally adapted. The majority were 6 of 10 items in the domain Activities of Daily Living, 2 of 9 items in the domain Mobility, and 2 of 5 items in the domain Hand function. Only in two domains, all items demonstrated acceptable goodness of fit to the Rasch model. There were also more than 5% person misfits in the domains Participation and Emotion, while the Communication, Mobility, and Hand function domains had the lowest proportions of person misfits. The reliability coefficient was equal or larger than 0.90 in all domains except the Emotion domain, which was below the set criterion of 0.80 (0.75). The cultural adaptation and translation of Stroke Impact Scale 3.0 Uganda provides initial evidence of validity of the Stroke Impact Scale 3.0 when used in this context. The results provide support for several aspects of validity and precision but also point out issues for further adaptation and improvement

The influence of gender on personality variables conditioning learning: Emotional intelligence and academic procrastination

Directory of Open Access Journals (Sweden)

Mercè Clariana,

2011-10-01

Full Text Available This research analyses the relationship between academic procrastination and emotional intelligence taking also into account the gender and age influence. Psychology undergraduates from the UAB (Universitat Autónoma de Barcelona, Spain and the UIB (Universitat de les Illes Balears, Spain, 45 males and 147 females constituted the sample of the study. Academic procrastination was assessed by means of the D scale (CLARIANA & MARTÍN, 2008 and emotional intelligence by means of the EQ–i (BAR–ON, 1997. The results show that academic procrastination has a significant negative relationship with intrapersonal intelligence, emotional quotient and mood. Moreover, female students scored significantly higher than males both in intrapersonal and interpersonal Intelligence while males obtained higher scores in both stress management and adaptability.

Integration and segregation of large-scale brain networks during short-term task automatization.

Science.gov (United States)

Mohr, Holger; Wolfensteller, Uta; Betzel, Richard F; Mišić, Bratislav; Sporns, Olaf; Richiardi, Jonas; Ruge, Hannes

2016-11-03

The human brain is organized into large-scale functional networks that can flexibly reconfigure their connectivity patterns, supporting both rapid adaptive control and long-term learning processes. However, it has remained unclear how short-term network dynamics support the rapid transformation of instructions into fluent behaviour. Comparing fMRI data of a learning sample (N=70) with a control sample (N=67), we find that increasingly efficient task processing during short-term practice is associated with a reorganization of large-scale network interactions. Practice-related efficiency gains are facilitated by enhanced coupling between the cingulo-opercular network and the dorsal attention network. Simultaneously, short-term task automatization is accompanied by decreasing activation of the fronto-parietal network, indicating a release of high-level cognitive control, and a segregation of the default mode network from task-related networks. These findings suggest that short-term task automatization is enabled by the brain's ability to rapidly reconfigure its large-scale network organization involving complementary integration and segregation processes.

Validation of the Intelligibility in Context Scale for school students in Fiji.

Science.gov (United States)

Hopf, Suzanne C; McLeod, Sharynne; McDonagh, Sarah H

2017-01-01

Fiji is a multilingual nation with few assessment tools addressing children's communication. This article describes the validation of the Intelligibility in Context Scale for Fiji English, Standard Fijian, and Fiji Hindi. Informants were caregivers of 65 typically developing multilingual children (aged 5;3-10;5) attending a Fiji primary school. The students spoke an average of 2.9 languages (range = 1-5). Their main language was Standard Fijian (41.5%), Fiji Hindi (23.1%), Fiji English (20.0%), or Fijian dialect (15.4%). An ICS mean score of 4.6 was obtained for main language (ICS-ML) and 4.4 for Fiji English (ICS-FE) indicating that students were usually to always intelligible. There were no significant differences between main language, number of languages spoken, gender, age, or socio-economic status. Both scales had good internal consistency, but were not correlated with speech accuracy measures possibly due to ceiling effects. Further validation with younger children is recommended. The ICS may be a useful tool for Fiji with comparative results to other international studies.

An Adaptive Critic Approach to Reference Model Adaptation

Science.gov (United States)

Krishnakumar, K.; Limes, G.; Gundy-Burlet, K.; Bryant, D.

2003-01-01

Neural networks have been successfully used for implementing control architectures for different applications. In this work, we examine a neural network augmented adaptive critic as a Level 2 intelligent controller for a C- 17 aircraft. This intelligent control architecture utilizes an adaptive critic to tune the parameters of a reference model, which is then used to define the angular rate command for a Level 1 intelligent controller. The present architecture is implemented on a high-fidelity non-linear model of a C-17 aircraft. The goal of this research is to improve the performance of the C-17 under degraded conditions such as control failures and battle damage. Pilot ratings using a motion based simulation facility are included in this paper. The benefits of using an adaptive critic are documented using time response comparisons for severe damage situations.

How to Improve Artificial Intelligence through Web

OpenAIRE

Adrian Lupasc

2005-01-01

Intelligent agents, intelligent software applications and artificial intelligent applications from artificial intelligence service providers may make their way onto the Web in greater number as adaptive software, dynamic programming languages and Learning Algorithms are introduced into Web Services. The evolution of Web architecture may allow intelligent applications to run directly on the Web by introducing XML, RDF and logic layer. The Intelligent Wireless Web’s significant potential for ra...

Large-scale transportation network congestion evolution prediction using deep learning theory.

Directory of Open Access Journals (Sweden)

Xiaolei Ma

Full Text Available Understanding how congestion at one location can cause ripples throughout large-scale transportation network is vital for transportation researchers and practitioners to pinpoint traffic bottlenecks for congestion mitigation. Traditional studies rely on either mathematical equations or simulation techniques to model traffic congestion dynamics. However, most of the approaches have limitations, largely due to unrealistic assumptions and cumbersome parameter calibration process. With the development of Intelligent Transportation Systems (ITS and Internet of Things (IoT, transportation data become more and more ubiquitous. This triggers a series of data-driven research to investigate transportation phenomena. Among them, deep learning theory is considered one of the most promising techniques to tackle tremendous high-dimensional data. This study attempts to extend deep learning theory into large-scale transportation network analysis. A deep Restricted Boltzmann Machine and Recurrent Neural Network architecture is utilized to model and predict traffic congestion evolution based on Global Positioning System (GPS data from taxi. A numerical study in Ningbo, China is conducted to validate the effectiveness and efficiency of the proposed method. Results show that the prediction accuracy can achieve as high as 88% within less than 6 minutes when the model is implemented in a Graphic Processing Unit (GPU-based parallel computing environment. The predicted congestion evolution patterns can be visualized temporally and spatially through a map-based platform to identify the vulnerable links for proactive congestion mitigation.

Gaussian process based intelligent sampling for measuring nano-structure surfaces

Science.gov (United States)

Sun, L. J.; Ren, M. J.; Yin, Y. H.

2016-09-01

Nanotechnology is the science and engineering that manipulate matters at nano scale, which can be used to create many new materials and devices with a vast range of applications. As the nanotech product increasingly enters the commercial marketplace, nanometrology becomes a stringent and enabling technology for the manipulation and the quality control of the nanotechnology. However, many measuring instruments, for instance scanning probe microscopy, are limited to relatively small area of hundreds of micrometers with very low efficiency. Therefore some intelligent sampling strategies should be required to improve the scanning efficiency for measuring large area. This paper presents a Gaussian process based intelligent sampling method to address this problem. The method makes use of Gaussian process based Bayesian regression as a mathematical foundation to represent the surface geometry, and the posterior estimation of Gaussian process is computed by combining the prior probability distribution with the maximum likelihood function. Then each sampling point is adaptively selected by determining the position which is the most likely outside of the required tolerance zone among the candidates and then inserted to update the model iteratively. Both simulationson the nominal surface and manufactured surface have been conducted on nano-structure surfaces to verify the validity of the proposed method. The results imply that the proposed method significantly improves the measurement efficiency in measuring large area structured surfaces.

Brazilian Portuguese transcultural adaptation of Barkley Deficits in Executive Functioning Scale (BDEFS)

OpenAIRE

Godoy, Victor Polignano; Mata, Fernanda Gomes Da; Conde, Bárbara Romaneli; Souza, Caroline Antunes de Oliveira e; Martins, Ana Luiza Guimarães; Mattos, Paulo; Miranda, Débora Marques de; Malloy-Diniz, Leandro Fernandes

2015-01-01

Abstract Background Considering the importance of Executive Functions to clinical and nonclinical situations, Barkley proposed a new theory of executive functioning based on an evolutionary neuropsychological perspective and clinical research using large samples of clinical and community identified adults and children as well as children with ADHD followed to adulthood. Objective The present study aims to adapt the Barkley Deficits in Executive Functions Scales (BDEFS) to Brazilian Portug...

Decentralized Large-Scale Power Balancing

DEFF Research Database (Denmark)

Halvgaard, Rasmus; Jørgensen, John Bagterp; Poulsen, Niels Kjølstad

2013-01-01

problem is formulated as a centralized large-scale optimization problem but is then decomposed into smaller subproblems that are solved locally by each unit connected to an aggregator. For large-scale systems the method is faster than solving the full problem and can be distributed to include an arbitrary...

Preschooler Sleep Patterns Related to Cognitive and Adaptive Functioning

Science.gov (United States)

Keefe-Cooperman, Kathleen; Brady-Amoon, Peggy

2014-01-01

Research Findings: Preschoolers' sleep patterns were examined related to cognitive and adaptive functioning. The sample consisted of 874 typically developing preschool children with a mean age of 40.01 months. Parent/caregiver reports of children's sleep pattern factors, Stanford-Binet 5 intelligence scale scores, and Behavior Assessment System…

Next generation sensing platforms for extended deployments in large-scale, multidisciplinary, adaptive sampling and observational networks

Science.gov (United States)

Cross, J. N.; Meinig, C.; Mordy, C. W.; Lawrence-Slavas, N.; Cokelet, E. D.; Jenkins, R.; Tabisola, H. M.; Stabeno, P. J.

2016-12-01

New autonomous sensors have dramatically increased the resolution and accuracy of oceanographic data collection, enabling rapid sampling over extremely fine scales. Innovative new autonomous platofrms like floats, gliders, drones, and crawling moorings leverage the full potential of these new sensors by extending spatiotemporal reach across varied environments. During 2015 and 2016, The Innovative Technology for Arctic Exploration Program at the Pacific Marine Environmental Laboratory tested several new types of fully autonomous platforms with increased speed, durability, and power and payload capacity designed to deliver cutting-edge ecosystem assessment sensors to remote or inaccessible environments. The Expendable Ice-Tracking (EXIT) gloat developed by the NOAA Pacific Marine Environmental Laboratory (PMEL) is moored near bottom during the ice-free season and released on an autonomous timer beneath the ice during the following winter. The float collects a rapid profile during ascent, and continues to collect critical, poorly-accessible under-ice data until melt, when data is transmitted via satellite. The autonomous Oculus sub-surface glider developed by the University of Washington and PMEL has a large power and payload capacity and an enhanced buoyancy engine. This 'coastal truck' is designed for the rapid water column ascent required by optical imaging systems. The Saildrone is a solar and wind powered ocean unmanned surface vessel (USV) developed by Saildrone, Inc. in partnership with PMEL. This large-payload (200 lbs), fast (1-7 kts), durable (46 kts winds) platform was equipped with 15 sensors designed for ecosystem assessment during 2016, including passive and active acoustic systems specially redesigned for autonomous vehicle deployments. The senors deployed on these platforms achieved rigorous accuracy and precision standards. These innovative platforms provide new sampling capabilities and cost efficiencies in high-resolution sensor deployment

The Cultural Historical Complexity of Human Personality Adaptation

Directory of Open Access Journals (Sweden)

Melissa E. Wynn

2012-10-01

Full Text Available Research on implicit intelligence has conceptualized students’ beliefs about the nature of intelligence as either fixed or malleable. This research has largely not included African American adolescents, a group for whom beliefs about intelligence have a cultural historical complexity related to both scientific racism and master narratives of race and intelligence. The purpose of this study was to investigate the nature of implicit theories of intelligence for 63 African American adolescents who are seventh and eighth graders in a public charter school. The two-way ANOVA revealed that these adolescents held a malleable view of intelligence, which did not vary by gender or grade. Exploratory correlation analysis showed some consistent relationships with achievement motivation variables found in other studies. These findings may be explained by African American cultural values and the personality characteristic adaptations that they make living within a racialized society.

Large-scale Meteorological Patterns Associated with Extreme Precipitation Events over Portland, OR

Science.gov (United States)

Aragon, C.; Loikith, P. C.; Lintner, B. R.; Pike, M.

2017-12-01

Extreme precipitation events can have profound impacts on human life and infrastructure, with broad implications across a range of stakeholders. Changes to extreme precipitation events are a projected outcome of climate change that warrants further study, especially at regional- to local-scales. While global climate models are generally capable of simulating mean climate at global-to-regional scales with reasonable skill, resiliency and adaptation decisions are made at local-scales where most state-of-the-art climate models are limited by coarse resolution. Characterization of large-scale meteorological patterns associated with extreme precipitation events at local-scales can provide climatic information without this scale limitation, thus facilitating stakeholder decision-making. This research will use synoptic climatology as a tool by which to characterize the key large-scale meteorological patterns associated with extreme precipitation events in the Portland, Oregon metro region. Composite analysis of meteorological patterns associated with extreme precipitation days, and associated watershed-specific flooding, is employed to enhance understanding of the climatic drivers behind such events. The self-organizing maps approach is then used to characterize the within-composite variability of the large-scale meteorological patterns associated with extreme precipitation events, allowing us to better understand the different types of meteorological conditions that lead to high-impact precipitation events and associated hydrologic impacts. A more comprehensive understanding of the meteorological drivers of extremes will aid in evaluation of the ability of climate models to capture key patterns associated with extreme precipitation over Portland and to better interpret projections of future climate at impact-relevant scales.

Adaptive Oceanographic Sampling in a Coastal Environment Using Autonomous Gliding Vehicles

National Research Council Canada - National Science Library

Fratantoni, David

2003-01-01

... and modular sensor payload. Particular emphasis is placed on the development of adaptive sampling strategies and the intelligent control of large glider fleets operating within the framework of an autonomous oceanographic sampling network...

Orthogonal Higher Order Structure and Confirmatory Factor Analysis of the French Wechsler Adult Intelligence Scale (WAIS-III)

Science.gov (United States)

Golay, Philippe; Lecerf, Thierry

2011-01-01

According to the most widely accepted Cattell-Horn-Carroll (CHC) model of intelligence measurement, each subtest score of the Wechsler Intelligence Scale for Adults (3rd ed.; WAIS-III) should reflect both 1st- and 2nd-order factors (i.e., 4 or 5 broad abilities and 1 general factor). To disentangle the contribution of each factor, we applied a…

Targeted business intelligence pays off.

Science.gov (United States)

Hennen, James

2009-03-01

Application business intelligence can accomplish much of what large-scale, enterprisewide efforts can accomplish: Focus on a variety of data that are interrelated in a meaningful way, Support decision making at multiple levels within a given organization, Leverage data that are already captured but not fully used, Provide actionable information and support quick response via a dashboard or control panel.

Cultural adaptation and validation of Stroke Impact Scale 3.0 version in Uganda: A small-scale study

Directory of Open Access Journals (Sweden)

Julius T Kamwesiga

2016-09-01

Full Text Available Background: Knowledge is scarce about the impact of stroke in Uganda, and culturally adapted, psychometrically tested patient-reported outcome measures are lacking. The Stroke Impact Scale 3.0 is recommended, but it has not been culturally adapted and validated in Uganda. Objective: To culturally adapt and determine the psychometric properties of the Stroke Impact Scale 3.0 in the Ugandan context on a small scale. Method: The Stroke Impact Scale 3.0 was culturally adapted to form Stroke Impact Scale 3.0 Uganda (in English by involving 25 participants in three different expert committees. Subsequently, Stroke Impact Scale 3.0 Uganda from English to Luganda language was done in accordance with guidelines. The first language in Uganda is English and Luganda is the main spoken language in Kampala city and its surroundings. Translation of Stroke Impact Scale 3.0 Uganda (both in English and Luganda was then tested psychometrically by applying a Rasch model on data collected from 95 participants with stroke. Results: Overall, 10 of 59 (17% items in the eight domains of the Stroke Impact Scale 3.0 were culturally adapted. The majority were 6 of 10 items in the domain Activities of Daily Living, 2 of 9 items in the domain Mobility, and 2 of 5 items in the domain Hand function. Only in two domains, all items demonstrated acceptable goodness of fit to the Rasch model. There were also more than 5% person misfits in the domains Participation and Emotion, while the Communication, Mobility, and Hand function domains had the lowest proportions of person misfits. The reliability coefficient was equal or larger than 0.90 in all domains except the Emotion domain, which was below the set criterion of 0.80 (0.75. Conclusion: The cultural adaptation and translation of Stroke Impact Scale 3.0 Uganda provides initial evidence of validity of the Stroke Impact Scale 3.0 when used in this context. The results provide support for several aspects of validity and precision

Cultural adaptation and validation of Stroke Impact Scale 3.0 version in Uganda: A small-scale study

Science.gov (United States)

Kamwesiga, Julius T; von Koch, Lena; Kottorp, Anders; Guidetti, Susanne

2016-01-01

Background: Knowledge is scarce about the impact of stroke in Uganda, and culturally adapted, psychometrically tested patient-reported outcome measures are lacking. The Stroke Impact Scale 3.0 is recommended, but it has not been culturally adapted and validated in Uganda. Objective: To culturally adapt and determine the psychometric properties of the Stroke Impact Scale 3.0 in the Ugandan context on a small scale. Method: The Stroke Impact Scale 3.0 was culturally adapted to form Stroke Impact Scale 3.0 Uganda (in English) by involving 25 participants in three different expert committees. Subsequently, Stroke Impact Scale 3.0 Uganda from English to Luganda language was done in accordance with guidelines. The first language in Uganda is English and Luganda is the main spoken language in Kampala city and its surroundings. Translation of Stroke Impact Scale 3.0 Uganda (both in English and Luganda) was then tested psychometrically by applying a Rasch model on data collected from 95 participants with stroke. Results: Overall, 10 of 59 (17%) items in the eight domains of the Stroke Impact Scale 3.0 were culturally adapted. The majority were 6 of 10 items in the domain Activities of Daily Living, 2 of 9 items in the domain Mobility, and 2 of 5 items in the domain Hand function. Only in two domains, all items demonstrated acceptable goodness of fit to the Rasch model. There were also more than 5% person misfits in the domains Participation and Emotion, while the Communication, Mobility, and Hand function domains had the lowest proportions of person misfits. The reliability coefficient was equal or larger than 0.90 in all domains except the Emotion domain, which was below the set criterion of 0.80 (0.75). Conclusion: The cultural adaptation and translation of Stroke Impact Scale 3.0 Uganda provides initial evidence of validity of the Stroke Impact Scale 3.0 when used in this context. The results provide support for several aspects of validity and precision but also point

Validation of the Intelligibility in Context Scale for Jamaican Creole-Speaking Preschoolers.

Science.gov (United States)

Washington, Karla N; McDonald, Megan M; McLeod, Sharynne; Crowe, Kathryn; Devonish, Hubert

2017-08-15

To describe validation of the Intelligibility in Context Scale (ICS; McLeod, Harrison, & McCormack, 2012a) and ICS-Jamaican Creole (ICS-JC; McLeod, Harrison, & McCormack, 2012b) in a sample of typically developing 3- to 6-year-old Jamaicans. One-hundred and forty-five preschooler-parent dyads participated in the study. Parents completed the 7-item ICS (n = 145) and ICS-JC (n = 98) to rate children's speech intelligibility (5-point scale) across communication partners (parents, immediate family, extended family, friends, acquaintances, strangers). Preschoolers completed the Diagnostic Evaluation of Articulation and Phonology (DEAP; Dodd, Hua, Crosbie, Holm, & Ozanne, 2006) in English and Jamaican Creole to establish speech-sound competency. For this sample, we examined validity and reliability (interrater, test-rest, internal consistency) evidence using measures of speech-sound production: (a) percentage of consonants correct, (b) percentage of vowels correct, and (c) percentage of phonemes correct. ICS and ICS-JC ratings showed preschoolers were always (5) to usually (4) understood across communication partners (ICS, M = 4.43; ICS-JC, M = 4.50). Both tools demonstrated excellent internal consistency (α = .91), high interrater, and test-retest reliability. Significant correlations between the two tools and between each measure and language-specific percentage of consonants correct, percentage of vowels correct, and percentage of phonemes correct provided criterion-validity evidence. A positive correlation between the ICS and age further strengthened validity evidence for that measure. Both tools show promising evidence of reliability and validity in describing functional speech intelligibility for this group of typically developing Jamaican preschoolers.

Intelligent Optics Laboratory

Data.gov (United States)

Federal Laboratory Consortium — The Intelligent Optics Laboratory supports sophisticated investigations on adaptive and nonlinear optics; advancedimaging and image processing; ground-to-ground and...

Bifactor Structure of the Wechsler Preschool and Primary Scale of Intelligence-Fourth Edition

Science.gov (United States)

Watkins, Marley W.; Beaujean, A. Alexander

2014-01-01

The Wechsler Preschool and Primary Scale of Intelligence-Fourth Edition (WPPSI-IV; Wechsler, 2012) represents a substantial departure from its predecessor, including omission of 4 subtests, addition of 5 new subtests, and modification of the contents of the 5 retained subtests. Wechsler (2012) explicitly assumed a higher-order structure with…

The Software Reliability of Large Scale Integration Circuit and Very Large Scale Integration Circuit

OpenAIRE

Artem Ganiyev; Jan Vitasek

2010-01-01

This article describes evaluation method of faultless function of large scale integration circuits (LSI) and very large scale integration circuits (VLSI). In the article there is a comparative analysis of factors which determine faultless of integrated circuits, analysis of already existing methods and model of faultless function evaluation of LSI and VLSI. The main part describes a proposed algorithm and program for analysis of fault rate in LSI and VLSI circuits.

A new type of intelligent wireless sensing network for health monitoring of large-size structures

Science.gov (United States)

Lei, Ying; Liu, Ch.; Wu, D. T.; Tang, Y. L.; Wang, J. X.; Wu, L. J.; Jiang, X. D.

2009-07-01

In recent years, some innovative wireless sensing systems have been proposed. However, more exploration and research on wireless sensing systems are required before wireless systems can substitute for the traditional wire-based systems. In this paper, a new type of intelligent wireless sensing network is proposed for the heath monitoring of large-size structures. Hardware design of the new wireless sensing units is first studied. The wireless sensing unit mainly consists of functional modules of: sensing interface, signal conditioning, signal digitization, computational core, wireless communication and battery management. Then, software architecture of the unit is introduced. The sensing network has a two-level cluster-tree architecture with Zigbee communication protocol. Important issues such as power saving and fault tolerance are considered in the designs of the new wireless sensing units and sensing network. Each cluster head in the network is characterized by its computational capabilities that can be used to implement the computational methodologies of structural health monitoring; making the wireless sensing units and sensing network have "intelligent" characteristics. Primary tests on the measurement data collected by the wireless system are performed. The distributed computational capacity of the intelligent sensing network is also demonstrated. It is shown that the new type of intelligent wireless sensing network provides an efficient tool for structural health monitoring of large-size structures.

Relationship between application scale and maximum time latency in intelligent transport solutions

NARCIS (Netherlands)

Knoop, V.; Lint, J. van; Vries, J.; Kester, L.J.H.M.; Passchier, I.

2013-01-01

Congestion is a major problem in large, urbanized areas. Intelligent transport solutions aim to reduce this problem. In general, traffic is monitored with the use of sensors, the resulting data are processed, a traffic state is estimated, and a control measure is computed and implemented. The

Bio-inspired wooden actuators for large scale applications.

Directory of Open Access Journals (Sweden)

Markus Rüggeberg

Full Text Available Implementing programmable actuation into materials and structures is a major topic in the field of smart materials. In particular the bilayer principle has been employed to develop actuators that respond to various kinds of stimuli. A multitude of small scale applications down to micrometer size have been developed, but up-scaling remains challenging due to either limitations in mechanical stiffness of the material or in the manufacturing processes. Here, we demonstrate the actuation of wooden bilayers in response to changes in relative humidity, making use of the high material stiffness and a good machinability to reach large scale actuation and application. Amplitude and response time of the actuation were measured and can be predicted and controlled by adapting the geometry and the constitution of the bilayers. Field tests in full weathering conditions revealed long-term stability of the actuation. The potential of the concept is shown by a first demonstrator. With the sensor and actuator intrinsically incorporated in the wooden bilayers, the daily change in relative humidity is exploited for an autonomous and solar powered movement of a tracker for solar modules.

The role of intelligence and feedback in children's strategy competence.

Science.gov (United States)

Luwel, Koen; Foustana, Ageliki; Papadatos, Yiannis; Verschaffel, Lieven

2011-01-01

A test-intervention-test study was conducted investigating the role of intelligence on four parameters of strategy competence in the context of a numerosity judgment task. Moreover, the effectiveness of two feedback types on these four parameters was tested. In the two test sessions, the choice/no-choice method was used to assess the strategy repertoire, frequency, efficiency, and adaptivity of a group of low-, average-, and high-intelligence children. During the intervention, half of the participants from each intelligence group were given outcome feedback (OFB), whereas the other half received strategy feedback (SFB). The pretest data showed large differences among the three intelligence groups on all four strategy parameters. These differences had disappeared at the posttest due to a particularly strong improvement on all strategy parameters in the low-intelligence group. Furthermore, it was found that SFB was more beneficial than OFB for all parameters involving strategy selection. These results indicate that intelligence plays an important role in children's strategy use and suggest that strategy feedback can be a powerful instructional tool, especially for low-intelligence children. Copyright © 2010 Elsevier Inc. All rights reserved.

A Large-Scale Multi-Hop Localization Algorithm Based on Regularized Extreme Learning for Wireless Networks.

Science.gov (United States)

Zheng, Wei; Yan, Xiaoyong; Zhao, Wei; Qian, Chengshan

2017-12-20

A novel large-scale multi-hop localization algorithm based on regularized extreme learning is proposed in this paper. The large-scale multi-hop localization problem is formulated as a learning problem. Unlike other similar localization algorithms, the proposed algorithm overcomes the shortcoming of the traditional algorithms which are only applicable to an isotropic network, therefore has a strong adaptability to the complex deployment environment. The proposed algorithm is composed of three stages: data acquisition, modeling and location estimation. In data acquisition stage, the training information between nodes of the given network is collected. In modeling stage, the model among the hop-counts and the physical distances between nodes is constructed using regularized extreme learning. In location estimation stage, each node finds its specific location in a distributed manner. Theoretical analysis and several experiments show that the proposed algorithm can adapt to the different topological environments with low computational cost. Furthermore, high accuracy can be achieved by this method without setting complex parameters.

Insufficiency of avoided crossings for witnessing large-scale quantum coherence in flux qubits

Science.gov (United States)

Fröwis, Florian; Yadin, Benjamin; Gisin, Nicolas

2018-04-01

Do experiments based on superconducting loops segmented with Josephson junctions (e.g., flux qubits) show macroscopic quantum behavior in the sense of Schrödinger's cat example? Various arguments based on microscopic and phenomenological models were recently adduced in this debate. We approach this problem by adapting (to flux qubits) the framework of large-scale quantum coherence, which was already successfully applied to spin ensembles and photonic systems. We show that contemporary experiments might show quantum coherence more than 100 times larger than experiments in the classical regime. However, we argue that the often-used demonstration of an avoided crossing in the energy spectrum is not sufficient to make a conclusion about the presence of large-scale quantum coherence. Alternative, rigorous witnesses are proposed.

Reconfigurable, Intelligently-Adaptive, Communication System, an SDR Platform

Science.gov (United States)

Roche, Rigoberto J.; Shalkhauser, Mary Jo; Hickey, Joseph P.; Briones, Janette C.

2016-01-01

The Space Telecommunications Radio System (STRS) provides a common, consistent framework to abstract the application software from the radio platform hardware. STRS aims to reduce the cost and risk of using complex, configurable and reprogrammable radio systems across NASA missions. The NASA Glenn Research Center (GRC) team made a software defined radio (SDR) platform STRS compliant by adding an STRS operating environment and a field programmable gate array (FPGA) wrapper, capable of implementing each of the platforms interfaces, as well as a test waveform to exercise those interfaces. This effort serves to provide a framework toward waveform development onto an STRS compliant platform to support future space communication systems for advanced exploration missions. The use of validated STRS compliant applications provides tested code with extensive documentation to potentially reduce risk, cost and e ort in development of space-deployable SDRs. This paper discusses the advantages of STRS, the integration of STRS onto a Reconfigurable, Intelligently-Adaptive, Communication System (RIACS) SDR platform, and the test waveform and wrapper development e orts. The paper emphasizes the infusion of the STRS Architecture onto the RIACS platform for potential use in next generation flight system SDRs for advanced exploration missions.

Phylogenetic distribution of large-scale genome patchiness

Directory of Open Access Journals (Sweden)

Hackenberg Michael

2008-04-01

Full Text Available Abstract Background The phylogenetic distribution of large-scale genome structure (i.e. mosaic compositional patchiness has been explored mainly by analytical ultracentrifugation of bulk DNA. However, with the availability of large, good-quality chromosome sequences, and the recently developed computational methods to directly analyze patchiness on the genome sequence, an evolutionary comparative analysis can be carried out at the sequence level. Results The local variations in the scaling exponent of the Detrended Fluctuation Analysis are used here to analyze large-scale genome structure and directly uncover the characteristic scales present in genome sequences. Furthermore, through shuffling experiments of selected genome regions, computationally-identified, isochore-like regions were identified as the biological source for the uncovered large-scale genome structure. The phylogenetic distribution of short- and large-scale patchiness was determined in the best-sequenced genome assemblies from eleven eukaryotic genomes: mammals (Homo sapiens, Pan troglodytes, Mus musculus, Rattus norvegicus, and Canis familiaris, birds (Gallus gallus, fishes (Danio rerio, invertebrates (Drosophila melanogaster and Caenorhabditis elegans, plants (Arabidopsis thaliana and yeasts (Saccharomyces cerevisiae. We found large-scale patchiness of genome structure, associated with in silico determined, isochore-like regions, throughout this wide phylogenetic range. Conclusion Large-scale genome structure is detected by directly analyzing DNA sequences in a wide range of eukaryotic chromosome sequences, from human to yeast. In all these genomes, large-scale patchiness can be associated with the isochore-like regions, as directly detected in silico at the sequence level.

Managing large-scale models: DBS

International Nuclear Information System (INIS)

1981-05-01

A set of fundamental management tools for developing and operating a large scale model and data base system is presented. Based on experience in operating and developing a large scale computerized system, the only reasonable way to gain strong management control of such a system is to implement appropriate controls and procedures. Chapter I discusses the purpose of the book. Chapter II classifies a broad range of generic management problems into three groups: documentation, operations, and maintenance. First, system problems are identified then solutions for gaining management control are disucssed. Chapters III, IV, and V present practical methods for dealing with these problems. These methods were developed for managing SEAS but have general application for large scale models and data bases

Human Brain inspired Artificial Intelligence & Developmental Robotics: A Review

Directory of Open Access Journals (Sweden)

Suresh Kumar

2017-06-01

Full Text Available Along with the developments in the field of the robotics, fascinating contributions and developments can be seen in the field of Artificial intelligence (AI. In this paper we will discuss about the developments is the field of artificial intelligence focusing learning algorithms inspired from the field of Biology, particularly large scale brain simulations, and developmental Psychology. We will focus on the emergence of the Developmental robotics and its significance in the field of AI.

Validation of the Schutte Self-Report Emotional Intelligence Scale with American College Students

Science.gov (United States)

Gong, Xiaopeng; Paulson, Sharon E.

2018-01-01

The current study examined the factor structure of the Schutte Self-Report Emotional Intelligence (SSREI) scale with an American college sample (n = 404, 322 females, 88.9% Whites). Data were collected through an online survey, and confirmatory factor analyses were conducted to test several proposed factor models from previous studies. The results…

Large Scale Self-Organizing Information Distribution System

National Research Council Canada - National Science Library

Low, Steven

2005-01-01

This project investigates issues in "large-scale" networks. Here "large-scale" refers to networks with large number of high capacity nodes and transmission links, and shared by a large number of users...

Large scale structure and baryogenesis

International Nuclear Information System (INIS)

Kirilova, D.P.; Chizhov, M.V.

2001-08-01

We discuss a possible connection between the large scale structure formation and the baryogenesis in the universe. An update review of the observational indications for the presence of a very large scale 120h -1 Mpc in the distribution of the visible matter of the universe is provided. The possibility to generate a periodic distribution with the characteristic scale 120h -1 Mpc through a mechanism producing quasi-periodic baryon density perturbations during inflationary stage, is discussed. The evolution of the baryon charge density distribution is explored in the framework of a low temperature boson condensate baryogenesis scenario. Both the observed very large scale of a the visible matter distribution in the universe and the observed baryon asymmetry value could naturally appear as a result of the evolution of a complex scalar field condensate, formed at the inflationary stage. Moreover, for some model's parameters a natural separation of matter superclusters from antimatter ones can be achieved. (author)

Evolutionary Developmental Soft Robotics As a Framework to Study Intelligence and Adaptive Behavior in Animals and Plants

Directory of Open Access Journals (Sweden)

Francesco Corucci

2017-07-01

Full Text Available In this paper, a comprehensive methodology and simulation framework will be reviewed, designed in order to study the emergence of adaptive and intelligent behavior in generic soft-bodied creatures. By incorporating artificial evolutionary and developmental processes, the system allows to evolve complete creatures (brain, body, developmental properties, sensory, control system, etc. for different task environments. Whether the evolved creatures will resemble animals or plants is in general not known a priori, and depends on the specific task environment set up by the experimenter. In this regard, the system may offer a unique opportunity to explore differences and similarities between these two worlds. Different material properties can be simulated and optimized, from a continuum of soft/stiff materials, to the interconnection of heterogeneous structures, both found in animals and plants alike. The adopted genetic encoding and simulation environment are particularly suitable in order to evolve distributed sensory and control systems, which play a particularly important role in plants. After a general description of the system some case studies will be presented, focusing on the emergent properties of the evolved creatures. Particular emphasis will be on some unifying concepts that are thought to play an important role in the emergence of intelligent and adaptive behavior across both the animal and plant kingdoms, such as morphological computation and morphological developmental plasticity. Overall, with this paper, we hope to draw attention on set of tools, methodologies, ideas and results, which may be relevant to researchers interested in plant-inspired robotics and intelligence.

Automatic management software for large-scale cluster system

International Nuclear Information System (INIS)

Weng Yunjian; Chinese Academy of Sciences, Beijing; Sun Gongxing

2007-01-01

At present, the large-scale cluster system faces to the difficult management. For example the manager has large work load. It needs to cost much time on the management and the maintenance of large-scale cluster system. The nodes in large-scale cluster system are very easy to be chaotic. Thousands of nodes are put in big rooms so that some managers are very easy to make the confusion with machines. How do effectively carry on accurate management under the large-scale cluster system? The article introduces ELFms in the large-scale cluster system. Furthermore, it is proposed to realize the large-scale cluster system automatic management. (authors)

Large-scale gene expression reveals different adaptations of Hyalopterus persikonus to winter and summer host plants.

Science.gov (United States)

Cui, Na; Yang, Peng-Cheng; Guo, Kun; Kang, Le; Cui, Feng

2017-06-01

Host alternation, an obligatory seasonal shifting between host plants of distant genetic relationship, has had significant consequences for the diversification and success of the superfamily of aphids. However, the underlying molecular mechanism remains unclear. In this study, the molecular mechanism of host alternation was explored through a large-scale gene expression analysis of the mealy aphid Hyalopterus persikonus on winter and summer host plants. More than four times as many unigenes of the mealy aphid were significantly upregulated on summer host Phragmites australis than on winter host Rosaceae plants. In order to identify gene candidates related to host alternation, the differentially expressed unigenes of H. persikonus were compared to salivary gland expressed genes and secretome of Acyrthosiphon pisum. Genes involved in ribosome and oxidative phosphorylation and with molecular functions of heme-copper terminal oxidase activity, hydrolase activity and ribosome binding were potentially upregulated in salivary glands of H. persikonus on the summer host. Putative secretory proteins, such as detoxification enzymes (carboxylesterases and cytochrome P450s), antioxidant enzymes (peroxidase and superoxide dismutase), glutathione peroxidase, glucose dehydrogenase, angiotensin-converting enzyme, cadherin, and calreticulin, were highly expressed in H. persikonus on the summer host, while a SCP GAPR-1-like family protein and a salivary sheath protein were highly expressed in the aphids on winter hosts. These results shed light on phenotypic plasticity in host utilization and seasonal adaptation of aphids. © 2016 Institute of Zoology, Chinese Academy of Sciences.

Autism As a Disorder of High Intelligence

Science.gov (United States)

Crespi, Bernard J.

2016-01-01

A suite of recent studies has reported positive genetic correlations between autism risk and measures of mental ability. These findings indicate that alleles for autism overlap broadly with alleles for high intelligence, which appears paradoxical given that autism is characterized, overall, by below-average IQ. This paradox can be resolved under the hypothesis that autism etiology commonly involves enhanced, but imbalanced, components of intelligence. This hypothesis is supported by convergent evidence showing that autism and high IQ share a diverse set of convergent correlates, including large brain size, fast brain growth, increased sensory and visual-spatial abilities, enhanced synaptic functions, increased attentional focus, high socioeconomic status, more deliberative decision-making, profession and occupational interests in engineering and physical sciences, and high levels of positive assortative mating. These findings help to provide an evolutionary basis to understanding autism risk as underlain in part by dysregulation of intelligence, a core human-specific adaptation. In turn, integration of studies on intelligence with studies of autism should provide novel insights into the neurological and genetic causes of high mental abilities, with important implications for cognitive enhancement, artificial intelligence, the relationship of autism with schizophrenia, and the treatment of both autism and intellectual disability. PMID:27445671

Cognitive Profile of Intellectually Gifted Adults: Analyzing the Wechsler Adult Intelligence Scale.

Science.gov (United States)

Lang, Margherita; Matta, Michael; Parolin, Laura; Morrone, Cristina; Pezzuti, Lina

2017-09-01

The Wechsler Adult Intelligence Scale (WAIS) has been used extensively to study intellectual abilities of special groups. Here, we report the results of an intellectually gifted group on the WAIS-IV. Gifted individuals are people who obtained scores equal to or greater than 2 standard deviations above the mean on an intelligence test. Hence, the current study aims first, to examine mean group performance data of gifted individuals on the WAIS-IV; second, to revalidate the pattern of performance identified in this special group in previous studies (i.e., verbal skills higher than all other abilities); third, to compare scatter measures across intellectual domains with a matched comparison group. A total of 130 gifted individuals (79 males) were administered the full battery and their performance was compared with a matched comparison group. Analyses revealed that gifted group displayed higher scores in all intellectual domains. Contrary to expectations, they showed the highest scores in perceptual reasoning tasks. A multivariate approach revealed that this ability was statistically different from all other domains within the gifted group. Moreover, gifted individuals showed higher discrepancies across intellectual domains than average-intelligence people. Findings have important practical implications to detect intellectual giftedness in adulthood.

Evolutionary Psychology and Intelligence Research

Science.gov (United States)

Kanazawa, Satoshi

2010-01-01

This article seeks to unify two subfields of psychology that have hitherto stood separately: evolutionary psychology and intelligence research/differential psychology. I suggest that general intelligence may simultaneously be an evolved adaptation and an individual-difference variable. Tooby and Cosmides's (1990a) notion of random quantitative…

Long-Term Stability of Scores on the Wechsler Intelligence Scale for Children-Fourth Edition in Children with Learning Disabilities

Science.gov (United States)

Lander, Jenny

2010-01-01

The present investigation explored the stability of scores on the Wechsler Intelligence Scale for Children-IV (WISC-IV) over approximately a three-year period. Previous research has suggested that some children with Learning Disabilities (LD) do not demonstrate long-term stability of intelligence. Legally, school districts are no longer required…

Spanish adaptation of the Participatory Behaviors Scale (PBS

Directory of Open Access Journals (Sweden)

Alejandro Magallares

2016-04-01

Full Text Available The aim of this study was to adapt the Participatory Behaviors Scale (PBS and validate the results for use among the Spanish population. Using snowball sampling methodology, 501 individuals from all areas of Spain were selected to participate in the study. The Participatory Behaviors Scale (PBS and questionnaires that measure a sense of community, belief in a just world and Machiavellianism were used to analyze the criterion validity of the adapted scale. A confirmatory factor analysis indicated that the items on the questionnaire fit a second-order model with four factors, which corresponded to the four dimensions proposed by the original authors, namely, disengagement, civil participation, formal political participation and activism. Additionally, it has been found that the scale is related to a sense of community, belief in a just world and Machiavellianism. In light of these results, we concluded that the questionnaire is methodologically valid and can be used by the scientific community to measure participatory behavior.

Mutual intelligibility between closely related language in Europe.

NARCIS (Netherlands)

Gooskens, Charlotte; van Heuven, Vincent; Golubovic, Jelena; Schüppert, Anja; Swarte, Femke; Voigt, Stefanie

2018-01-01

By means of a large-scale web-based investigation, we established the degree of mutual intelligibility of 16 closely related spoken languages within the Germanic, Slavic and Romance language families in Europe. We first present the results of a selection of 1833 listeners representing the mutual

Large scale network-centric distributed systems

CERN Document Server

Sarbazi-Azad, Hamid

2014-01-01

A highly accessible reference offering a broad range of topics and insights on large scale network-centric distributed systems Evolving from the fields of high-performance computing and networking, large scale network-centric distributed systems continues to grow as one of the most important topics in computing and communication and many interdisciplinary areas. Dealing with both wired and wireless networks, this book focuses on the design and performance issues of such systems. Large Scale Network-Centric Distributed Systems provides in-depth coverage ranging from ground-level hardware issu

Large-Scale Outflows in Seyfert Galaxies

Science.gov (United States)

Colbert, E. J. M.; Baum, S. A.

1995-12-01

\\catcode`\\@=11 \\ialign{m @th#1hfil ##hfil \\crcr#2\\crcr\\sim\\crcr}}} \\catcode`\\@=12 Highly collimated outflows extend out to Mpc scales in many radio-loud active galaxies. In Seyfert galaxies, which are radio-quiet, the outflows extend out to kpc scales and do not appear to be as highly collimated. In order to study the nature of large-scale (>~1 kpc) outflows in Seyferts, we have conducted optical, radio and X-ray surveys of a distance-limited sample of 22 edge-on Seyfert galaxies. Results of the optical emission-line imaging and spectroscopic survey imply that large-scale outflows are present in >~{{1} /{4}} of all Seyferts. The radio (VLA) and X-ray (ROSAT) surveys show that large-scale radio and X-ray emission is present at about the same frequency. Kinetic luminosities of the outflows in Seyferts are comparable to those in starburst-driven superwinds. Large-scale radio sources in Seyferts appear diffuse, but do not resemble radio halos found in some edge-on starburst galaxies (e.g. M82). We discuss the feasibility of the outflows being powered by the active nucleus (e.g. a jet) or a circumnuclear starburst.

Adaptive nonparametric Bayesian inference using location-scale mixture priors

NARCIS (Netherlands)

Jonge, de R.; Zanten, van J.H.

2010-01-01

We study location-scale mixture priors for nonparametric statistical problems, including multivariate regression, density estimation and classification. We show that a rate-adaptive procedure can be obtained if the prior is properly constructed. In particular, we show that adaptation is achieved if

Intelligent speed adaptation as an assistive device for drivers with acquired brain injury

DEFF Research Database (Denmark)

Klarborg, Brith; Lahrmann, Harry Spaabæk; Agerholm, Niels

2012-01-01

Intelligent speed adaptation (ISA) was tested as an assistive device for drivers with an acquired brain injury (ABI). The study was part of the “Pay as You Speed” project (PAYS) and used the same equipment and technology as the main study (Lahrmann et al., in press-a, in press-b). Two drivers......, and in general they described driving with ISA as relaxed. ISA reduced the percentage of the total distance that was driven with a speed above the speed limit (PDA), but the subjects relapsed to their previous PDA level in Baseline 2. This suggests that ISA is more suited as a permanent assistive device (i...

A User-Centric View of Intelligent Environments: User Expectations, User Experience and User Role in Building Intelligent Environments

Directory of Open Access Journals (Sweden)

Eija Kaasinen

2012-12-01

Full Text Available Our everyday environments are gradually becoming intelligent, facilitated both by technological development and user activities. Although large-scale intelligent environments are still rare in actual everyday use, they have been studied for quite a long time, and several user studies have been carried out. In this paper, we present a user-centric view of intelligent environments based on published research results and our own experiences from user studies with concepts and prototypes. We analyze user acceptance and users’ expectations that affect users’ willingness to start using intelligent environments and to continue using them. We discuss user experience of interacting with intelligent environments where physical and virtual elements are intertwined. Finally, we touch on the role of users in shaping their own intelligent environments instead of just using ready-made environments. People are not merely “using” the intelligent environments but they live in them, and they experience the environments via embedded services and new interaction tools as well as the physical and social environment. Intelligent environments should provide emotional as well as instrumental value to the people who live in them, and the environments should be trustworthy and controllable both by regular users and occasional visitors. Understanding user expectations and user experience in intelligent environments, and providing users with tools to influence the environments can help to shape the vision of intelligent environments into meaningful, acceptable and appealing service entities for all those who live and act in them.

2015 Chinese Intelligent Automation Conference

CERN Document Server

Li, Hongbo

2015-01-01

Proceedings of the 2015 Chinese Intelligent Automation Conference presents selected research papers from the CIAC’15, held in Fuzhou, China. The topics include adaptive control, fuzzy control, neural network based control, knowledge based control, hybrid intelligent control, learning control, evolutionary mechanism based control, multi-sensor integration, failure diagnosis, reconfigurable control, etc. Engineers and researchers from academia, industry and the government can gain valuable insights into interdisciplinary solutions in the field of intelligent automation.

Risk and Disaster Management: From Planning and Expertise to Smart, Intelligent, and Adaptive Systems.

Science.gov (United States)

Benis, Arriel; Notea, Amos; Barkan, Refael

2018-01-01

"Disaster" means some surprising and misfortunate event. Its definition is broad and relates to complex environments. Medical Informatics approaches, methodologies and systems are used as a part of Disaster and Emergency Management systems. At the Holon Institute of Technology - HIT, Israel, in 2016 a National R&D Center: AFRAN was established to study the disaster's reduction aspects. The Center's designation is to investigate and produce new approaches, methodologies and to offer recommendations in the fields of disaster mitigation, preparedness, response and recovery and to disseminate disaster's knowledge. Adjoint to the Center a "Smart, Intelligent, and Adaptive Systems" laboratory (SIAS) was established with the goal to study the applications of Information and Communication Technologies (ICT) and Artificial Intelligence (AI) to Risk and Disaster Management (RDM). In this paper, we are redefining the concept of Disaster, pointing-out how ICT, AI, in the Big Data era, are central players in the RDM game. In addition we show the merit of the Center and lab combination to the benefit of the performed research projects.

A generic library for large scale solution of PDEs on modern heterogeneous architectures

DEFF Research Database (Denmark)

Glimberg, Stefan Lemvig; Engsig-Karup, Allan Peter

2012-01-01

Adapting to new programming models for modern multi- and many-core architectures requires code-rewriting and changing algorithms and data structures, in order to achieve good efficiency and scalability. We present a generic library for solving large scale partial differential equations (PDEs......), capable of utilizing heterogeneous CPU/GPU environments. The library can be used for fast proto-typing of PDE solvers, based on finite difference approximations of spatial derivatives in one, two, or three dimensions. In order to efficiently solve large scale problems, we keep memory consumption...... and memory access low, using a low-storage implementation of flexible-order finite difference operators. We will illustrate the use of library components by assembling such matrix-free operators to be used with one of the supported iterative solvers, such as GMRES, CG, Multigrid or Defect Correction...

SCALE INTERACTION IN A MIXING LAYER. THE ROLE OF THE LARGE-SCALE GRADIENTS

KAUST Repository

Fiscaletti, Daniele

2015-08-23

The interaction between scales is investigated in a turbulent mixing layer. The large-scale amplitude modulation of the small scales already observed in other works depends on the crosswise location. Large-scale positive fluctuations correlate with a stronger activity of the small scales on the low speed-side of the mixing layer, and a reduced activity on the high speed-side. However, from physical considerations we would expect the scales to interact in a qualitatively similar way within the flow and across different turbulent flows. Therefore, instead of the large-scale fluctuations, the large-scale gradients modulation of the small scales has been additionally investigated.

Investigation of the factor structure of the Wechsler Adult Intelligence Scale--Fourth Edition (WAIS-IV): exploratory and higher order factor analyses.

Science.gov (United States)

Canivez, Gary L; Watkins, Marley W

2010-12-01

The present study examined the factor structure of the Wechsler Adult Intelligence Scale--Fourth Edition (WAIS-IV; D. Wechsler, 2008a) standardization sample using exploratory factor analysis, multiple factor extraction criteria, and higher order exploratory factor analysis (J. Schmid & J. M. Leiman, 1957) not included in the WAIS-IV Technical and Interpretation Manual (D. Wechsler, 2008b). Results indicated that the WAIS-IV subtests were properly associated with the theoretically proposed first-order factors, but all but one factor-extraction criterion recommended extraction of one or two factors. Hierarchical exploratory analyses with the Schmid and Leiman procedure found that the second-order g factor accounted for large portions of total and common variance, whereas the four first-order factors accounted for small portions of total and common variance. It was concluded that the WAIS-IV provides strong measurement of general intelligence, and clinical interpretation should be primarily at that level.

Psychological variables and Wechsler Adult Intelligence Scale-IV performance.

Science.gov (United States)

Gass, Carlton S; Gutierrez, Laura

2017-01-01

The MMPI-2 and WAIS-IV are commonly used together in neuropsychological evaluations yet little is known about their interrelationships. This study explored the potential influence of psychological factors on WAIS-IV performance in a sample of 180 predominantly male veteran referrals that underwent a comprehensive neuropsychological examination in a VA Medical Center. Exclusionary criteria included failed performance validity testing and self-report distortion on the MMPI-2. A Principal Components Analysis was performed on the 15 MMPI-2 content scales, yielding three broader higher-order psychological dimensions: Internalized Emotional Dysfunction (IED), Externalized Emotional Dysfunction (EED), and Fear. Level of IED was not related to performance on the WAIS-IV Full Scale IQ or its four indexes: (Verbal Comprehension, Perceptual Reasoning, Working Memory, and Processing Speed). EED was not related to WAIS-IV performance. Level of Fear, which encompasses health preoccupations (HEA) and distorted perceptions (BIZ), was significantly related to WAIS-IV Full Scale IQ and Verbal Comprehension. These results challenge the common use of high scores on the MMPI-2 IED measures (chiefly depression and anxiety) to explain deficient WAIS-IV performance. In addition, they provide impetus for further investigation of the relation between verbal intelligence and Fear.

A spatial picture of the synthetic large-scale motion from dynamic roughness

Science.gov (United States)

Huynh, David; McKeon, Beverley

2017-11-01

Jacobi and McKeon (2011) set up a dynamic roughness apparatus to excite a synthetic, travelling wave-like disturbance in a wind tunnel, boundary layer study. In the present work, this dynamic roughness has been adapted for a flat-plate, turbulent boundary layer experiment in a water tunnel. A key advantage of operating in water as opposed to air is the longer flow timescales. This makes accessible higher non-dimensional actuation frequencies and correspondingly shorter synthetic length scales, and is thus more amenable to particle image velocimetry. As a result, this experiment provides a novel spatial picture of the synthetic mode, the coupled small scales, and their streamwise development. It is demonstrated that varying the roughness actuation frequency allows for significant tuning of the streamwise wavelength of the synthetic mode, with a range of 3 δ-13 δ being achieved. Employing a phase-locked decomposition, spatial snapshots are constructed of the synthetic large scale and used to analyze its streamwise behavior. Direct spatial filtering is used to separate the synthetic large scale and the related small scales, and the results are compared to those obtained by temporal filtering that invokes Taylor's hypothesis. The support of AFOSR (Grant # FA9550-16-1-0361) is gratefully acknowledged.

Deep Adaptive Log-Demons: Diffeomorphic Image Registration with Very Large Deformations

Directory of Open Access Journals (Sweden)

Liya Zhao

2015-01-01

Full Text Available This paper proposes a new framework for capturing large and complex deformation in image registration. Traditionally, this challenging problem relies firstly on a preregistration, usually an affine matrix containing rotation, scale, and translation and afterwards on a nonrigid transformation. According to preregistration, the directly calculated affine matrix, which is obtained by limited pixel information, may misregistrate when large biases exist, thus misleading following registration subversively. To address this problem, for two-dimensional (2D images, the two-layer deep adaptive registration framework proposed in this paper firstly accurately classifies the rotation parameter through multilayer convolutional neural networks (CNNs and then identifies scale and translation parameters separately. For three-dimensional (3D images, affine matrix is located through feature correspondences by a triplanar 2D CNNs. Then deformation removal is done iteratively through preregistration and demons registration. By comparison with the state-of-the-art registration framework, our method gains more accurate registration results on both synthetic and real datasets. Besides, principal component analysis (PCA is combined with correlation like Pearson and Spearman to form new similarity standards in 2D and 3D registration. Experiment results also show faster convergence speed.

BUSINESS INTELLIGENCE ADOPTION IN LARGE ROMANIAN COMPANIES

Directory of Open Access Journals (Sweden)

Flavia CAIA

2014-11-01

Full Text Available The economic conditions and market competition create pressures on companies to adopt new technologies that can provide more efficient information and can support decision-making better. The purpose of the research is to investigate the decision support information systems in order to apprise and enhance the capacity of the entities to apply the new knowledge that BI produces for organizational success and competitiveness. The importance of the conducted research consists in identifying solutions to improve reporting and stimulate the entities to start using business intelligence (BI technologies, which facilitate obtaining new information, in order to ensure flexibility, resilience and provide answers to questions that go beyond what the pre-defined reports can do to support decision-making. The estimated result is a technical and operational overview of the large companies in Romania, drawing future directions for an improved competitive behaviour and strategic awareness, and identifying the significant factors for optimizing the decision-making process.

Emotional intelligence, performance, and retention in clinical staff nurses.

Science.gov (United States)

Codier, Estelle; Kamikawa, Cindy; Kooker, Barbara M; Shoultz, Jan

2009-01-01

Emotional intelligence has been correlated with performance, retention, and organizational commitment in professions other than nursing. A 2006 pilot study provided the first evidence of a correlation between emotional intelligence and performance in clinical staff nurses. A follow-up study was completed, the purpose of which was to explore emotional intelligence, performance level, organizational commitment, and retention. A convenience sample of 350 nurses in a large medical center in urban Hawaii participated in this study. This article reports the findings pertaining to the subset of 193 clinical staff nurses who responded. The Mayer-Salovey-Caruso Emotional Intelligence Test instrument was used to measure emotional intelligence abilities. Performance was defined as ranking on a clinical ladder. Commitment was scored on a Likert scale. The following variables measured retention: total years in nursing, years in current job, total years anticipated in current job, and total anticipated career length. Emotional intelligence scores in clinical staff nurses correlated positively with both performance level and retention variables. Clinical staff nurses with higher emotional intelligence scores demonstrated higher performance, had longer careers, and greater job retention.

Dissecting the large-scale galactic conformity

Science.gov (United States)

Seo, Seongu

2018-01-01

Galactic conformity is an observed phenomenon that galaxies located in the same region have similar properties such as star formation rate, color, gas fraction, and so on. The conformity was first observed among galaxies within in the same halos (“one-halo conformity”). The one-halo conformity can be readily explained by mutual interactions among galaxies within a halo. Recent observations however further witnessed a puzzling connection among galaxies with no direct interaction. In particular, galaxies located within a sphere of ~5 Mpc radius tend to show similarities, even though the galaxies do not share common halos with each other ("two-halo conformity" or “large-scale conformity”). Using a cosmological hydrodynamic simulation, Illustris, we investigate the physical origin of the two-halo conformity and put forward two scenarios. First, back-splash galaxies are likely responsible for the large-scale conformity. They have evolved into red galaxies due to ram-pressure stripping in a given galaxy cluster and happen to reside now within a ~5 Mpc sphere. Second, galaxies in strong tidal field induced by large-scale structure also seem to give rise to the large-scale conformity. The strong tides suppress star formation in the galaxies. We discuss the importance of the large-scale conformity in the context of galaxy evolution.

Analyzing extreme sea levels for broad-scale impact and adaptation studies

Science.gov (United States)

Wahl, T.; Haigh, I. D.; Nicholls, R. J.; Arns, A.; Dangendorf, S.; Hinkel, J.; Slangen, A.

2017-12-01

Coastal impact and adaptation assessments require detailed knowledge on extreme sea levels (ESL), because increasing damage due to extreme events is one of the major consequences of sea-level rise (SLR) and climate change. Over the last few decades, substantial research efforts have been directed towards improved understanding of past and future SLR; different scenarios were developed with process-based or semi-empirical models and used for coastal impact studies at various temporal and spatial scales to guide coastal management and adaptation efforts. Uncertainties in future SLR are typically accounted for by analyzing the impacts associated with a range of scenarios and model ensembles. ESL distributions are then displaced vertically according to the SLR scenarios under the inherent assumption that we have perfect knowledge on the statistics of extremes. However, there is still a limited understanding of present-day ESL which is largely ignored in most impact and adaptation analyses. The two key uncertainties stem from: (1) numerical models that are used to generate long time series of storm surge water levels, and (2) statistical models used for determining present-day ESL exceedance probabilities. There is no universally accepted approach to obtain such values for broad-scale flood risk assessments and while substantial research has explored SLR uncertainties, we quantify, for the first time globally, key uncertainties in ESL estimates. We find that contemporary ESL uncertainties exceed those from SLR projections and, assuming that we meet the Paris agreement, the projected SLR itself by the end of the century. Our results highlight the necessity to further improve our understanding of uncertainties in ESL estimates through (1) continued improvement of numerical and statistical models to simulate and analyze coastal water levels and (2) exploit the rich observational database and continue data archeology to obtain longer time series and remove model bias

Self-adapted and tunable graphene strain sensors for detecting both subtle and large human motions.

Science.gov (United States)

Tao, Lu-Qi; Wang, Dan-Yang; Tian, He; Ju, Zhen-Yi; Liu, Ying; Pang, Yu; Chen, Yuan-Quan; Yang, Yi; Ren, Tian-Ling

2017-06-22

Conventional strain sensors rarely have both a high gauge factor and a large strain range simultaneously, so they can only be used in specific situations where only a high sensitivity or a large strain range is required. However, for detecting human motions that include both subtle and large motions, these strain sensors can't meet the diverse demands simultaneously. Here, we come up with laser patterned graphene strain sensors with self-adapted and tunable performance for the first time. A series of strain sensors with either an ultrahigh gauge factor or a preferable strain range can be fabricated simultaneously via one-step laser patterning, and are suitable for detecting all human motions. The strain sensors have a GF of up to 457 with a strain range of 35%, or have a strain range of up to 100% with a GF of 268. Most importantly, the performance of the strain sensors can be easily tuned by adjusting the patterns of the graphene, so that the sensors can meet diverse demands in both subtle and large motion situations. The graphene strain sensors show significant potential in applications such as wearable electronics, health monitoring and intelligent robots. Furthermore, the facile, fast and low-cost fabrication method will make them possible and practical to be used for commercial applications in the future.

The power of event-driven analytics in Large Scale Data Processing

CERN Multimedia

CERN. Geneva; Marques, Paulo

2011-01-01

FeedZai is a software company specialized in creating high-­‐throughput low-­‐latency data processing solutions. FeedZai develops a product called "FeedZai Pulse" for continuous event-­‐driven analytics that makes application development easier for end users. It automatically calculates key performance indicators and baselines, showing how current performance differ from previous history, creating timely business intelligence updated to the second. The tool does predictive analytics and trend analysis, displaying data on real-­‐time web-­‐based graphics. In 2010 FeedZai won the European EBN Smart Entrepreneurship Competition, in the Digital Models category, being considered one of the "top-­‐20 smart companies in Europe". The main objective of this seminar/workshop is to explore the topic for large-­‐scale data processing using Complex Event Processing and, in particular, the possible uses of Pulse in...

REIONIZATION ON LARGE SCALES. I. A PARAMETRIC MODEL CONSTRUCTED FROM RADIATION-HYDRODYNAMIC SIMULATIONS

International Nuclear Information System (INIS)

Battaglia, N.; Trac, H.; Cen, R.; Loeb, A.

2013-01-01

We present a new method for modeling inhomogeneous cosmic reionization on large scales. Utilizing high-resolution radiation-hydrodynamic simulations with 2048 3 dark matter particles, 2048 3 gas cells, and 17 billion adaptive rays in a L = 100 Mpc h –1 box, we show that the density and reionization redshift fields are highly correlated on large scales (∼> 1 Mpc h –1 ). This correlation can be statistically represented by a scale-dependent linear bias. We construct a parametric function for the bias, which is then used to filter any large-scale density field to derive the corresponding spatially varying reionization redshift field. The parametric model has three free parameters that can be reduced to one free parameter when we fit the two bias parameters to simulation results. We can differentiate degenerate combinations of the bias parameters by combining results for the global ionization histories and correlation length between ionized regions. Unlike previous semi-analytic models, the evolution of the reionization redshift field in our model is directly compared cell by cell against simulations and performs well in all tests. Our model maps the high-resolution, intermediate-volume radiation-hydrodynamic simulations onto lower-resolution, larger-volume N-body simulations (∼> 2 Gpc h –1 ) in order to make mock observations and theoretical predictions

Overview of Intelligent Systems and Operations Development

Science.gov (United States)

Pallix, Joan; Dorais, Greg; Penix, John

2004-01-01

To achieve NASA's ambitious mission objectives for the future, aircraft and spacecraft will need intelligence to take the correct action in a variety of circumstances. Vehicle intelligence can be defined as the ability to "do the right thing" when faced with a complex decision-making situation. It will be necessary to implement integrated autonomous operations and low-level adaptive flight control technologies to direct actions that enhance the safety and success of complex missions despite component failures, degraded performance, operator errors, and environment uncertainty. This paper will describe the array of technologies required to meet these complex objectives. This includes the integration of high-level reasoning and autonomous capabilities with multiple subsystem controllers for robust performance. Future intelligent systems will use models of the system, its environment, and other intelligent agents with which it interacts. They will also require planners, reasoning engines, and adaptive controllers that can recommend or execute commands enabling the system to respond intelligently. The presentation will also address the development of highly dependable software, which is a key component to ensure the reliability of intelligent systems.

Multi-approaches analysis reveals local adaptation in the emmer wheat (Triticum dicoccoides) at macro- but not micro-geographical scale.

Science.gov (United States)

Volis, Sergei; Ormanbekova, Danara; Yermekbayev, Kanat; Song, Minshu; Shulgina, Irina

2015-01-01

Detecting local adaptation and its spatial scale is one of the most important questions of evolutionary biology. However, recognition of the effect of local selection can be challenging when there is considerable environmental variation across the distance at the whole species range. We analyzed patterns of local adaptation in emmer wheat, Triticum dicoccoides, at two spatial scales, small (inter-population distance less than one km) and large (inter-population distance more than 50 km) using several approaches. Plants originating from four distinct habitats at two geographic scales (cold edge, arid edge and two topographically dissimilar core locations) were reciprocally transplanted and their success over time was measured as 1) lifetime fitness in a year of planting, and 2) population growth four years after planting. In addition, we analyzed molecular (SSR) and quantitative trait variation and calculated the QST/FST ratio. No home advantage was detected at the small spatial scale. At the large spatial scale, home advantage was detected for the core population and the cold edge population in the year of introduction via measuring life-time plant performance. However, superior performance of the arid edge population in its own environment was evident only after several generations via measuring experimental population growth rate through genotyping with SSRs allowing counting the number of plants and seeds per introduced genotype per site. These results highlight the importance of multi-generation surveys of population growth rate in local adaptation testing. Despite predominant self-fertilization of T. dicoccoides and the associated high degree of structuring of genetic variation, the results of the QST - FST comparison were in general agreement with the pattern of local adaptation at the two spatial scales detected by reciprocal transplanting.

Perceived emotional intelligence, general intelligence and early professional success: predictive and incremental validity

Directory of Open Access Journals (Sweden)

José-Manuel de Haro

2014-05-01

Full Text Available Although the study of factors affecting career success has shown connections between biographical and other aspects related to ability, knowledge and personality, few studies have examined the relationship between emotional intelligence and professional success at the initial career stage. When these studies were carried out, the results showed significant relationships between the dimensions of emotional intelligence (emotional self-awareness, self-regulation, social awareness or social skills and the level of professional competence. In this paper, we analyze the relationship between perceived emotional intelligence, measured by the Trait Meta-Mood Scale (TMMS-24 questionnaire, general intelligence assessed by the Cattell factor "g" test, scale 3, and extrinsic indicators of career success, in a sample of 130 graduates at the beginning of their careers. Results from hierarchical regression analysis indicate that emotional intelligence makes a specific contribution to the prediction of salary, after controlling the general intelligence effect. The perceived emotional intelligence dimensions of TMMS repair, TMMS attention and sex show a higher correlation and make a greater contribution to professional success than general intelligence. The implications of these results for the development of socio-emotional skills among University graduates are discussed.

Talking About The Smokes: a large-scale, community-based participatory research project.

Science.gov (United States)

Couzos, Sophia; Nicholson, Anna K; Hunt, Jennifer M; Davey, Maureen E; May, Josephine K; Bennet, Pele T; Westphal, Darren W; Thomas, David P

2015-06-01

To describe the Talking About The Smokes (TATS) project according to the World Health Organization guiding principles for conducting community-based participatory research (PR) involving indigenous peoples, to assist others planning large-scale PR projects. The TATS project was initiated in Australia in 2010 as part of the International Tobacco Control Policy Evaluation Project, and surveyed a representative sample of 2522 Aboriginal and Torres Strait Islander adults to assess the impact of tobacco control policies. The PR process of the TATS project, which aimed to build partnerships to create equitable conditions for knowledge production, was mapped and summarised onto a framework adapted from the WHO principles. Processes describing consultation and approval, partnerships and research agreements, communication, funding, ethics and consent, data and benefits of the research. The TATS project involved baseline and follow-up surveys conducted in 34 Aboriginal community-controlled health services and one Torres Strait community. Consistent with the WHO PR principles, the TATS project built on community priorities and strengths through strategic partnerships from project inception, and demonstrated the value of research agreements and trusting relationships to foster shared decision making, capacity building and a commitment to Indigenous data ownership. Community-based PR methodology, by definition, needs adaptation to local settings and priorities. The TATS project demonstrates that large-scale research can be participatory, with strong Indigenous community engagement and benefits.

Large-scale perspective as a challenge

NARCIS (Netherlands)

Plomp, M.G.A.

2012-01-01

1. Scale forms a challenge for chain researchers: when exactly is something ‘large-scale’? What are the underlying factors (e.g. number of parties, data, objects in the chain, complexity) that determine this? It appears to be a continuum between small- and large-scale, where positioning on that

Mutual intelligibility between closely related languages in Europe

NARCIS (Netherlands)

Gooskens, C.; Heuven, van V.J.J.P.; Golubović, J.; Schüppert, A.; Swarte, F.; Voigt, S.

2017-01-01

By means of a large-scale web-based investigation, we established the degree of mutual intelligibility of 16 closely related spoken languages within the Germanic, Slavic and Romance language families in Europe. We first present the results of a selection of 1833 listeners representing the mutual

Algorithm 896: LSA: Algorithms for Large-Scale Optimization

Czech Academy of Sciences Publication Activity Database

Lukšan, Ladislav; Matonoha, Ctirad; Vlček, Jan

2009-01-01

Roč. 36, č. 3 (2009), 16-1-16-29 ISSN 0098-3500 R&D Pro jects: GA AV ČR IAA1030405; GA ČR GP201/06/P397 Institutional research plan: CEZ:AV0Z10300504 Keywords : algorithms * design * large-scale optimization * large-scale nonsmooth optimization * large-scale nonlinear least squares * large-scale nonlinear minimax * large-scale systems of nonlinear equations * sparse pro blems * partially separable pro blems * limited-memory methods * discrete Newton methods * quasi-Newton methods * primal interior-point methods Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.904, year: 2009

Cloud Computing Boosts Business Intelligence of Telecommunication Industry

Science.gov (United States)

Xu, Meng; Gao, Dan; Deng, Chao; Luo, Zhiguo; Sun, Shaoling

Business Intelligence becomes an attracting topic in today's data intensive applications, especially in telecommunication industry. Meanwhile, Cloud Computing providing IT supporting Infrastructure with excellent scalability, large scale storage, and high performance becomes an effective way to implement parallel data processing and data mining algorithms. BC-PDM (Big Cloud based Parallel Data Miner) is a new MapReduce based parallel data mining platform developed by CMRI (China Mobile Research Institute) to fit the urgent requirements of business intelligence in telecommunication industry. In this paper, the architecture, functionality and performance of BC-PDM are presented, together with the experimental evaluation and case studies of its applications. The evaluation result demonstrates both the usability and the cost-effectiveness of Cloud Computing based Business Intelligence system in applications of telecommunication industry.

Scale interactions in a mixing layer – the role of the large-scale gradients

KAUST Repository

Fiscaletti, D.

2016-02-15

© 2016 Cambridge University Press. The interaction between the large and the small scales of turbulence is investigated in a mixing layer, at a Reynolds number based on the Taylor microscale of , via direct numerical simulations. The analysis is performed in physical space, and the local vorticity root-mean-square (r.m.s.) is taken as a measure of the small-scale activity. It is found that positive large-scale velocity fluctuations correspond to large vorticity r.m.s. on the low-speed side of the mixing layer, whereas, they correspond to low vorticity r.m.s. on the high-speed side. The relationship between large and small scales thus depends on position if the vorticity r.m.s. is correlated with the large-scale velocity fluctuations. On the contrary, the correlation coefficient is nearly constant throughout the mixing layer and close to unity if the vorticity r.m.s. is correlated with the large-scale velocity gradients. Therefore, the small-scale activity appears closely related to large-scale gradients, while the correlation between the small-scale activity and the large-scale velocity fluctuations is shown to reflect a property of the large scales. Furthermore, the vorticity from unfiltered (small scales) and from low pass filtered (large scales) velocity fields tend to be aligned when examined within vortical tubes. These results provide evidence for the so-called \\'scale invariance\\' (Meneveau & Katz, Annu. Rev. Fluid Mech., vol. 32, 2000, pp. 1-32), and suggest that some of the large-scale characteristics are not lost at the small scales, at least at the Reynolds number achieved in the present simulation.

The Development of a Motor-Free Short-Form of the Wechsler Intelligence Scale for Children-Fifth Edition.

Science.gov (United States)

Piovesana, Adina M; Harrison, Jessica L; Ducat, Jacob J

2017-12-01

This study aimed to develop a motor-free short-form of the Wechsler Intelligence Scale for Children-Fifth Edition (WISC-V) that allows clinicians to estimate the Full Scale Intelligence Quotients of youths with motor impairments. Using the reliabilities and intercorrelations of six WISC-V motor-free subtests, psychometric methodologies were applied to develop look-up tables for four Motor-free Short-form indices: Verbal Comprehension Short-form, Perceptual Reasoning Short-form, Working Memory Short-form, and a Motor-free Intelligence Quotient. Index-level discrepancy tables were developed using the same methods to allow clinicians to statistically compare visual, verbal, and working memory abilities. The short-form indices had excellent reliabilities ( r = .92-.97) comparable to the original WISC-V. This motor-free short-form of the WISC-V is a reliable alternative for the assessment of intellectual functioning in youths with motor impairments. Clinicians are provided with user-friendly look-up tables, index level discrepancy tables, and base rates, displayed similar to those in the WISC-V manuals to enable interpretation of assessment results.

A new hybrid optimization method inspired from swarm intelligence: Fuzzy adaptive swallow swarm optimization algorithm (FASSO

Directory of Open Access Journals (Sweden)

Mehdi Neshat

2015-11-01

Full Text Available In this article, the objective was to present effective and optimal strategies aimed at improving the Swallow Swarm Optimization (SSO method. The SSO is one of the best optimization methods based on swarm intelligence which is inspired by the intelligent behaviors of swallows. It has been able to offer a relatively strong method for solving optimization problems. However, despite its many advantages, the SSO suffers from two shortcomings. Firstly, particles movement speed is not controlled satisfactorily during the search due to the lack of an inertia weight. Secondly, the variables of the acceleration coefficient are not able to strike a balance between the local and the global searches because they are not sufficiently flexible in complex environments. Therefore, the SSO algorithm does not provide adequate results when it searches in functions such as the Step or Quadric function. Hence, the fuzzy adaptive Swallow Swarm Optimization (FASSO method was introduced to deal with these problems. Meanwhile, results enjoy high accuracy which are obtained by using an adaptive inertia weight and through combining two fuzzy logic systems to accurately calculate the acceleration coefficients. High speed of convergence, avoidance from falling into local extremum, and high level of error tolerance are the advantages of proposed method. The FASSO was compared with eleven of the best PSO methods and SSO in 18 benchmark functions. Finally, significant results were obtained.

Large-scale matrix-handling subroutines 'ATLAS'

International Nuclear Information System (INIS)

Tsunematsu, Toshihide; Takeda, Tatsuoki; Fujita, Keiichi; Matsuura, Toshihiko; Tahara, Nobuo

1978-03-01

Subroutine package ''ATLAS'' has been developed for handling large-scale matrices. The package is composed of four kinds of subroutines, i.e., basic arithmetic routines, routines for solving linear simultaneous equations and for solving general eigenvalue problems and utility routines. The subroutines are useful in large scale plasma-fluid simulations. (auth.)

Large-scale solar heat

Energy Technology Data Exchange (ETDEWEB)

Tolonen, J.; Konttinen, P.; Lund, P. [Helsinki Univ. of Technology, Otaniemi (Finland). Dept. of Engineering Physics and Mathematics

1998-12-31

In this project a large domestic solar heating system was built and a solar district heating system was modelled and simulated. Objectives were to improve the performance and reduce costs of a large-scale solar heating system. As a result of the project the benefit/cost ratio can be increased by 40 % through dimensioning and optimising the system at the designing stage. (orig.)

Adaptation at Scale in Semi-arid Regions (ASSAR)

International Development Research Centre (IDRC) Digital Library (Canada)

Microsoft Office User

Long-term climate projections in Africa & suggest necessity of far reaching adaptation actions. • Large potential impacts on food production & security, water resources, from both heat and changes in moisture. • Often many social, political, economic and governance barriers to adaptation. • Robust knowledge systems and ...

Fixed Point Learning Based Intelligent Traffic Control System

Science.gov (United States)

Zongyao, Wang; Cong, Sui; Cheng, Shao

2017-10-01

Fixed point learning has become an important tool to analyse large scale distributed system such as urban traffic network. This paper presents a fixed point learning based intelligence traffic network control system. The system applies convergence property of fixed point theorem to optimize the traffic flow density. The intelligence traffic control system achieves maximum road resources usage by averaging traffic flow density among the traffic network. The intelligence traffic network control system is built based on decentralized structure and intelligence cooperation. No central control is needed to manage the system. The proposed system is simple, effective and feasible for practical use. The performance of the system is tested via theoretical proof and simulations. The results demonstrate that the system can effectively solve the traffic congestion problem and increase the vehicles average speed. It also proves that the system is flexible, reliable and feasible for practical use.

Accident of Large-scale Wind Turbines Disconnecting from Power Grid and Its Protection

Institute of Scientific and Technical Information of China (English)

2012-01-01

There were many accidents of large-scale wind turbines disconnecting from power grid in 2011. As single- phase-to-ground fault cannot be correctly detected, single-phase-to-ground fault evolved to phase-to-phase fault. Phase-to-phase fault was isolated slowly, thus leading to low voltage. And wind turbines without enough low voltage ride-through capacity had to be disconnected from the grid. After some wind turbines being disconnected from the grid, overvoltage caused by reactive power surplus made more wind turbines disconnect from the grid. Based on the accident analysis, this paper presents solutions to above problems, including travelling waves based single-phase-to-ground protection, adaptive low voltage protection, integrated protection and control, and high impedance fault detection. The solutions lay foundations in theory and technology to prevent large-scale wind turbines disconnecting from the operating power grid.

Probes of large-scale structure in the Universe

International Nuclear Information System (INIS)

Suto, Yasushi; Gorski, K.; Juszkiewicz, R.; Silk, J.

1988-01-01

Recent progress in observational techniques has made it possible to confront quantitatively various models for the large-scale structure of the Universe with detailed observational data. We develop a general formalism to show that the gravitational instability theory for the origin of large-scale structure is now capable of critically confronting observational results on cosmic microwave background radiation angular anisotropies, large-scale bulk motions and large-scale clumpiness in the galaxy counts. (author)

A Distributed Snapshot Protocol for Efficient Artificial Intelligence Computation in Cloud Computing Environments

Directory of Open Access Journals (Sweden)

JongBeom Lim

2018-01-01

Full Text Available Many artificial intelligence applications often require a huge amount of computing resources. As a result, cloud computing adoption rates are increasing in the artificial intelligence field. To support the demand for artificial intelligence applications and guarantee the service level agreement, cloud computing should provide not only computing resources but also fundamental mechanisms for efficient computing. In this regard, a snapshot protocol has been used to create a consistent snapshot of the global state in cloud computing environments. However, the existing snapshot protocols are not optimized in the context of artificial intelligence applications, where large-scale iterative computation is the norm. In this paper, we present a distributed snapshot protocol for efficient artificial intelligence computation in cloud computing environments. The proposed snapshot protocol is based on a distributed algorithm to run interconnected multiple nodes in a scalable fashion. Our snapshot protocol is able to deal with artificial intelligence applications, in which a large number of computing nodes are running. We reveal that our distributed snapshot protocol guarantees the correctness, safety, and liveness conditions.

Segmentation by Large Scale Hypothesis Testing - Segmentation as Outlier Detection

DEFF Research Database (Denmark)

Darkner, Sune; Dahl, Anders Lindbjerg; Larsen, Rasmus

2010-01-01

a microscope and we show how the method can handle transparent particles with significant glare point. The method generalizes to other problems. THis is illustrated by applying the method to camera calibration images and MRI of the midsagittal plane for gray and white matter separation and segmentation......We propose a novel and efficient way of performing local image segmentation. For many applications a threshold of pixel intensities is sufficient but determine the appropriate threshold value can be difficult. In cases with large global intensity variation the threshold value has to be adapted...... locally. We propose a method based on large scale hypothesis testing with a consistent method for selecting an appropriate threshold for the given data. By estimating the background distribution we characterize the segment of interest as a set of outliers with a certain probability based on the estimated...

Trait emotional intelligence in initial teacher training

Directory of Open Access Journals (Sweden)

David Molero

2017-02-01

Full Text Available This study analyzes the emotional intelligence (EI in teachers during their initial training following the trait EI model, namely the wellness model Bar-On (2002; 2006. 460 students participated (age in years M=22.57, SD=±3.39 of the University of Jaen (Spain who responded to the scale EQ-i Short Form Spanish version (López-Zafra, Pulido-Martos, & Berrios-Martos, 2014, that includes 4 factors (Interpersonal, Adaptability, Stress management and Intrapersonal. There are significant differences (p<.05 on various factors based on gender, age, degree of participants and the educational level of the same. The variables considered in the regression analysis that most predict global IE are Stress Management, Adaptability followed, Intrapersonal and Interpersonal. The results are consistent with those obtained in other studies in similar contexts.

Multiple time scales of adaptation in auditory cortex neurons.

Science.gov (United States)

Ulanovsky, Nachum; Las, Liora; Farkas, Dina; Nelken, Israel

2004-11-17

Neurons in primary auditory cortex (A1) of cats show strong stimulus-specific adaptation (SSA). In probabilistic settings, in which one stimulus is common and another is rare, responses to common sounds adapt more strongly than responses to rare sounds. This SSA could be a correlate of auditory sensory memory at the level of single A1 neurons. Here we studied adaptation in A1 neurons, using three different probabilistic designs. We showed that SSA has several time scales concurrently, spanning many orders of magnitude, from hundreds of milliseconds to tens of seconds. Similar time scales are known for the auditory memory span of humans, as measured both psychophysically and using evoked potentials. A simple model, with linear dependence on both short-term and long-term stimulus history, provided a good fit to A1 responses. Auditory thalamus neurons did not show SSA, and their responses were poorly fitted by the same model. In addition, SSA increased the proportion of failures in the responses of A1 neurons to the adapting stimulus. Finally, SSA caused a bias in the neuronal responses to unbiased stimuli, enhancing the responses to eccentric stimuli. Therefore, we propose that a major function of SSA in A1 neurons is to encode auditory sensory memory on multiple time scales. This SSA might play a role in stream segregation and in binding of auditory objects over many time scales, a property that is crucial for processing of natural auditory scenes in cats and of speech and music in humans.

Crowd counting via scale-adaptive convolutional neural network

OpenAIRE

Zhang, Lu; Shi, Miaojing; Chen, Qiaobo

2017-01-01

The task of crowd counting is to automatically estimate the pedestrian number in crowd images. To cope with the scale and perspective changes that commonly exist in crowd images, state-of-the-art approaches employ multi-column CNN architectures to regress density maps of crowd images. Multiple columns have different receptive fields corresponding to pedestrians (heads) of different scales. We instead propose a scale-adaptive CNN (SaCNN) architecture with a backbone of fixed small receptive fi...

Large-scale grid management; Storskala Nettforvaltning

Energy Technology Data Exchange (ETDEWEB)

Langdal, Bjoern Inge; Eggen, Arnt Ove

2003-07-01

The network companies in the Norwegian electricity industry now have to establish a large-scale network management, a concept essentially characterized by (1) broader focus (Broad Band, Multi Utility,...) and (2) bigger units with large networks and more customers. Research done by SINTEF Energy Research shows so far that the approaches within large-scale network management may be structured according to three main challenges: centralization, decentralization and out sourcing. The article is part of a planned series.

Emotional intelligence, happiness, hope and marital satisfaction ...

African Journals Online (AJOL)

Emotional Intelligence Scale, Subjective-happiness Scale, Adult Trait-hope Scale and the Marital Satisfaction Scale were used to collect data from the participants. Statistical analysis involved the use of Simple Linear and Standard Multiple regression. Findings indicated that, emotional intelligence did not have a significant ...

Life as an emergent phenomenon: studies from a large-scale boid simulation and web data

Science.gov (United States)

Ikegami, Takashi; Mototake, Yoh-ichi; Kobori, Shintaro; Oka, Mizuki; Hashimoto, Yasuhiro

2017-11-01

A large group with a special structure can become the mother of emergence. We discuss this hypothesis in relation to large-scale boid simulations and web data. In the boid swarm simulations, the nucleation, organization and collapse dynamics were found to be more diverse in larger flocks than in smaller flocks. In the second analysis, large web data, consisting of shared photos with descriptive tags, tended to group together users with similar tendencies, allowing the network to develop a core-periphery structure. We show that the generation rate of novel tags and their usage frequencies are high in the higher-order cliques. In this case, novelty is not considered to arise randomly; rather, it is generated as a result of a large and structured network. We contextualize these results in terms of adjacent possible theory and as a new way to understand collective intelligence. We argue that excessive information and material flow can become a source of innovation. This article is part of the themed issue 'Reconceptualizing the origins of life'.

Japanese large-scale interferometers

CERN Document Server

Kuroda, K; Miyoki, S; Ishizuka, H; Taylor, C T; Yamamoto, K; Miyakawa, O; Fujimoto, M K; Kawamura, S; Takahashi, R; Yamazaki, T; Arai, K; Tatsumi, D; Ueda, A; Fukushima, M; Sato, S; Shintomi, T; Yamamoto, A; Suzuki, T; Saitô, Y; Haruyama, T; Sato, N; Higashi, Y; Uchiyama, T; Tomaru, T; Tsubono, K; Ando, M; Takamori, A; Numata, K; Ueda, K I; Yoneda, H; Nakagawa, K; Musha, M; Mio, N; Moriwaki, S; Somiya, K; Araya, A; Kanda, N; Telada, S; Sasaki, M; Tagoshi, H; Nakamura, T; Tanaka, T; Ohara, K

2002-01-01

The objective of the TAMA 300 interferometer was to develop advanced technologies for kilometre scale interferometers and to observe gravitational wave events in nearby galaxies. It was designed as a power-recycled Fabry-Perot-Michelson interferometer and was intended as a step towards a final interferometer in Japan. The present successful status of TAMA is presented. TAMA forms a basis for LCGT (large-scale cryogenic gravitational wave telescope), a 3 km scale cryogenic interferometer to be built in the Kamioka mine in Japan, implementing cryogenic mirror techniques. The plan of LCGT is schematically described along with its associated R and D.

The influence of active vision on the exoskeleton of intelligent agents

Science.gov (United States)

Smith, Patrice; Terry, Theodore B.

2016-04-01

Chameleonization occurs when a self-learning autonomous mobile system's (SLAMR) active vision scans the surface of which it is perched causing the exoskeleton to changes colors exhibiting a chameleon effect. Intelligent agents having the ability to adapt to their environment and exhibit key survivability characteristics of its environments would largely be due in part to the use of active vision. Active vision would allow the intelligent agent to scan its environment and adapt as needed in order to avoid detection. The SLAMR system would have an exoskeleton, which would change, based on the surface it was perched on; this is known as the "chameleon effect." Not in the common sense of the term, but from the techno-bio inspired meaning as addressed in our previous paper. Active vision, utilizing stereoscopic color sensing functionality would enable the intelligent agent to scan an object within its close proximity, determine the color scheme, and match it; allowing the agent to blend with its environment. Through the use of its' optical capabilities, the SLAMR system would be able to further determine its position, taking into account spatial and temporal correlation and spatial frequency content of neighboring structures further ensuring successful background blending. The complex visual tasks of identifying objects, using edge detection, image filtering, and feature extraction are essential for an intelligent agent to gain additional knowledge about its environmental surroundings.

Isolating relativistic effects in large-scale structure

Science.gov (United States)

Bonvin, Camille

2014-12-01

We present a fully relativistic calculation of the observed galaxy number counts in the linear regime. We show that besides the density fluctuations and redshift-space distortions, various relativistic effects contribute to observations at large scales. These effects all have the same physical origin: they result from the fact that our coordinate system, namely the galaxy redshift and the incoming photons’ direction, is distorted by inhomogeneities in our Universe. We then discuss the impact of the relativistic effects on the angular power spectrum and on the two-point correlation function in configuration space. We show that the latter is very well adapted to isolate the relativistic effects since it naturally makes use of the symmetries of the different contributions. In particular, we discuss how the Doppler effect and the gravitational redshift distortions can be isolated by looking for a dipole in the cross-correlation function between a bright and a faint population of galaxies.

Applications of Adaptive Learning Controller to Synthetic Aperture Radar.

Science.gov (United States)

1985-02-01

TERMS (Continue on retuerse if necessary and identify by block num ber) FIELD YGROUP SUB. GR. Adaptive control, aritificial intelligence , synthetic aetr1...application of Artificial Intelligence methods to Synthetic Aperture Radars (SARs) is investigated. It was shown that the neuron-like Adaptive Learning...wavelength Al SE!RI M RADAR DIVISION REFERENCES 1. Barto, A.G. and R.S. Sutton, Goal Seeking Components for Adaptive Intelligence : An Initial Assessment

Intelligent Lighting Control System

OpenAIRE

García, Elena; Rodríguez González, Sara; de Paz Santana, Juan F.; Bajo Pérez, Javier

2014-01-01

This paper presents an adaptive architecture that allows centralized control of public lighting and intelligent management, in order to economise on lighting and maintain maximum comfort status of the illuminated areas. To carry out this management, architecture merges various techniques of artificial intelligence (AI) and statistics such as artificial neural networks (ANN), multi-agent systems (MAS), EM algorithm, methods based on ANOVA and a Service Oriented Aproach (SOA). It performs optim...

Efficient large-scale graph data optimization for intelligent video surveillance

Science.gov (United States)

Shang, Quanhong; Zhang, Shujun; Wang, Yanbo; Sun, Chen; Wang, Zepeng; Zhang, Luming

2017-08-01

Society is rapidly accepting the use of a wide variety of cameras Location and applications: site traffic monitoring, parking Lot surveillance, car and smart space. These ones here the camera provides data every day in an analysis Effective way. Recent advances in sensor technology Manufacturing, communications and computing are stimulating.The development of new applications that can change the traditional Vision system incorporating universal smart camera network. This Analysis of visual cues in multi camera networks makes wide Applications ranging from smart home and office automation to large area surveillance and traffic surveillance. In addition, dense Camera networks, most of which have large overlapping areas of cameras. In the view of good research, we focus on sparse camera networks. One Sparse camera network using large area surveillance. As few cameras as possible, most cameras do not overlap Each other’s field of vision. This task is challenging Lack of knowledge of topology Network, the specific changes in appearance and movement Track different opinions of the target, as well as difficulties Understanding complex events in a network. In this review in this paper, we present a comprehensive survey of recent studies Results to solve the problem of topology learning, Object appearance modeling and global activity understanding sparse camera network. In addition, some of the current open Research issues are discussed.

A Brazilian Portuguese cross-cultural adaptation of the modified JOA scale for myelopathy.

Science.gov (United States)

Pratali, Raphael R; Smith, Justin S; Motta, Rodrigo L N; Martins, Samuel M; Motta, Marcel M; Rocha, Ricardo D; Herrero, Carlos Fernando P S

2017-02-01

To develop a version of the modified Japanese Orthopaedic Association (mJOA) scale that had been translated into Portuguese and cross-culturally adapted for the Brazilian population. The well-established process of forward-backward translation was employed along with cross-cultural adaptation. Three bilingual translators (English and native Portuguese) performed the forward translation of the mJOA scale from English to Portuguese based on iterative discussions used to reach a consensus translation. The translated version of the mJOA scale was then back-translated into English by a native English-speaking translator unaware of the concepts involved with the mJOA scale. The original mJOA scale and the back-translated version were compared by a native North American neurosurgeon, and as they were considered equivalent, the final version of the mJOA scale that had been translated into Portuguese and cross-culturally adapted was defined. To facilitate global and cross-cultural comparisons of the severity of cervical myelopathy, this study presents a version of the mJOA scale that was translated into Portuguese and cross-culturally adapted for the Brazilian population.

Large scale model testing

International Nuclear Information System (INIS)

Brumovsky, M.; Filip, R.; Polachova, H.; Stepanek, S.

1989-01-01

Fracture mechanics and fatigue calculations for WWER reactor pressure vessels were checked by large scale model testing performed using large testing machine ZZ 8000 (with a maximum load of 80 MN) at the SKODA WORKS. The results are described from testing the material resistance to fracture (non-ductile). The testing included the base materials and welded joints. The rated specimen thickness was 150 mm with defects of a depth between 15 and 100 mm. The results are also presented of nozzles of 850 mm inner diameter in a scale of 1:3; static, cyclic, and dynamic tests were performed without and with surface defects (15, 30 and 45 mm deep). During cyclic tests the crack growth rate in the elastic-plastic region was also determined. (author). 6 figs., 2 tabs., 5 refs

Why small-scale cannabis growers stay small: five mechanisms that prevent small-scale growers from going large scale.

Science.gov (United States)

Hammersvik, Eirik; Sandberg, Sveinung; Pedersen, Willy

2012-11-01

Over the past 15-20 years, domestic cultivation of cannabis has been established in a number of European countries. New techniques have made such cultivation easier; however, the bulk of growers remain small-scale. In this study, we explore the factors that prevent small-scale growers from increasing their production. The study is based on 1 year of ethnographic fieldwork and qualitative interviews conducted with 45 Norwegian cannabis growers, 10 of whom were growing on a large-scale and 35 on a small-scale. The study identifies five mechanisms that prevent small-scale indoor growers from going large-scale. First, large-scale operations involve a number of people, large sums of money, a high work-load and a high risk of detection, and thus demand a higher level of organizational skills than for small growing operations. Second, financial assets are needed to start a large 'grow-site'. Housing rent, electricity, equipment and nutrients are expensive. Third, to be able to sell large quantities of cannabis, growers need access to an illegal distribution network and knowledge of how to act according to black market norms and structures. Fourth, large-scale operations require advanced horticultural skills to maximize yield and quality, which demands greater skills and knowledge than does small-scale cultivation. Fifth, small-scale growers are often embedded in the 'cannabis culture', which emphasizes anti-commercialism, anti-violence and ecological and community values. Hence, starting up large-scale production will imply having to renegotiate or abandon these values. Going from small- to large-scale cannabis production is a demanding task-ideologically, technically, economically and personally. The many obstacles that small-scale growers face and the lack of interest and motivation for going large-scale suggest that the risk of a 'slippery slope' from small-scale to large-scale growing is limited. Possible political implications of the findings are discussed. Copyright

Distributed large-scale dimensional metrology new insights

CERN Document Server

Franceschini, Fiorenzo; Maisano, Domenico

2011-01-01

Focuses on the latest insights into and challenges of distributed large scale dimensional metrology Enables practitioners to study distributed large scale dimensional metrology independently Includes specific examples of the development of new system prototypes

Learning for intelligent mobile robots

Science.gov (United States)

Hall, Ernest L.; Liao, Xiaoqun; Alhaj Ali, Souma M.

2003-10-01

Unlike intelligent industrial robots which often work in a structured factory setting, intelligent mobile robots must often operate in an unstructured environment cluttered with obstacles and with many possible action paths. However, such machines have many potential applications in medicine, defense, industry and even the home that make their study important. Sensors such as vision are needed. However, in many applications some form of learning is also required. The purpose of this paper is to present a discussion of recent technical advances in learning for intelligent mobile robots. During the past 20 years, the use of intelligent industrial robots that are equipped not only with motion control systems but also with sensors such as cameras, laser scanners, or tactile sensors that permit adaptation to a changing environment has increased dramatically. However, relatively little has been done concerning learning. Adaptive and robust control permits one to achieve point to point and controlled path operation in a changing environment. This problem can be solved with a learning control. In the unstructured environment, the terrain and consequently the load on the robot"s motors are constantly changing. Learning the parameters of a proportional, integral and derivative controller (PID) and artificial neural network provides an adaptive and robust control. Learning may also be used for path following. Simulations that include learning may be conducted to see if a robot can learn its way through a cluttered array of obstacles. If a situation is performed repetitively, then learning can also be used in the actual application. To reach an even higher degree of autonomous operation, a new level of learning is required. Recently learning theories such as the adaptive critic have been proposed. In this type of learning a critic provides a grade to the controller of an action module such as a robot. The creative control process is used that is "beyond the adaptive critic." A

Intelligent Systems For Aerospace Engineering: An Overview

Science.gov (United States)

KrishnaKumar, K.

2003-01-01

Intelligent systems are nature-inspired, mathematically sound, computationally intensive problem solving tools and methodologies that have become extremely important for advancing the current trends in information technology. Artificially intelligent systems currently utilize computers to emulate various faculties of human intelligence and biological metaphors. They use a combination of symbolic and sub-symbolic systems capable of evolving human cognitive skills and intelligence, not just systems capable of doing things humans do not do well. Intelligent systems are ideally suited for tasks such as search and optimization, pattern recognition and matching, planning, uncertainty management, control, and adaptation. In this paper, the intelligent system technologies and their application potential are highlighted via several examples.

A Proactive Complex Event Processing Method for Large-Scale Transportation Internet of Things

OpenAIRE

Wang, Yongheng; Cao, Kening

2014-01-01

The Internet of Things (IoT) provides a new way to improve the transportation system. The key issue is how to process the numerous events generated by IoT. In this paper, a proactive complex event processing method is proposed for large-scale transportation IoT. Based on a multilayered adaptive dynamic Bayesian model, a Bayesian network structure learning algorithm using search-and-score is proposed to support accurate predictive analytics. A parallel Markov decision processes model is design...

Measuring Components of Intelligence: Mission Impossible?

Science.gov (United States)

Gregoire, Jacques

2013-01-01

The two studies conducted by Weiss, Keith, Zhu, and Chen in 2013 on the Wechsler Adult Intelligence Scale (WAIS-IV) and the Wechsler Intelligence Scale for Children (WISC-IV), respectively, provide strong evidence for the validity of a four-factor solution corresponding to the current hierarchical model of both scales. These analyses support the…

Prognostic Role of Spiritual Intelligence Components in Pregnant Women’s Depression, Anxiety, and Stress

Directory of Open Access Journals (Sweden)

Batul Khodakarami

2016-06-01

Full Text Available Background and Objectives: Physiological changes and psychological adaptations during pregnancy period expose pregnant mothers to increased risk of depression, anxiety, and stress. Presently, spiritual intelligence is addressed as one of the most influential issues in mental and emotional health of individuals. This study was conducted aimed at examination of the relationship between spiritual intelligence, on the one hand, and depression, anxiety, and stress, on the other, among pregnant women. Methods: This descriptive-correlative study was performed on 182 pregnant women using Stratified Random Sampling method. Depression, Anxiety, and Stress Scale (DASS-21 and King Spiritual Intelligence Self-Report Inventory were used to evaluate and compare research’s variables. SPSS, version 16, and descriptive-analytical statistical methods were employed to analyze data. Results: Results indicated that there was a negative, significant relationship between all scales of spiritual intelligence components and subscales of depression and stress during pregnancy period (P<0.05. There was a negative, significant relationship between critical existential thinking and personal meaning production, on the one hand, and stress, on the other, in pregnancy period (P<0.05. Multiple regressions analysis indicated that predictor variables explain criterion variables in a significant way. Conclusion: Pregnant women with higher degrees of spiritual intelligence tend to have lower degrees of depression, anxiety, and stress during their pregnancy period.

SCALE INTERACTION IN A MIXING LAYER. THE ROLE OF THE LARGE-SCALE GRADIENTS

KAUST Repository

Fiscaletti, Daniele; Attili, Antonio; Bisetti, Fabrizio; Elsinga, Gerrit E.

2015-01-01

from physical considerations we would expect the scales to interact in a qualitatively similar way within the flow and across different turbulent flows. Therefore, instead of the large-scale fluctuations, the large-scale gradients modulation of the small scales has been additionally investigated.

Longitudinal Invariance of the Wechsler Intelligence Scale for Children--Fourth Edition in a Referral Sample

Science.gov (United States)

Richerson, Lindsay P.; Watkins, Marley W.; Beaujean, A. Alexander

2014-01-01

Measurement invariance of the Wechsler Intelligence Scale for Children--Fourth Edition (WISC-IV) was investigated with a group of 352 students eligible for psychoeducational evaluations tested, on average, 2.8 years apart. Configural, metric, and scalar invariance were found. However, the error variance of the Coding subtest was not constant…

Designing an Adaptive Nuero-Fuzzy Inference System for Evaluating the Business Intelligence System Implementation in Software Industry

Directory of Open Access Journals (Sweden)

Iman Raeesi Vanani

2015-03-01

Full Text Available The main goal of research is designing an adaptive nuero-fuzzy inference system for evaluating the implementation of business intelligence systems in software industry. Iranian software development organizations have been facing a lot of problems in case of implementing business intelligence systems. This system would be helpful in recognizing the conditions and prerequisites of success or failure. Organizations can recalculate the neuro-fuzzy system outputs with some considerations on various inputs to figure out which inputs have the most effect on the implementation outputs. By resolving the problems on inputs, organizations can achieve a better level of implementation success. The designed system has been trained by a data set and afterwards, it has been evaluated. The trained system has reached the error value of 0.08. Eventually, some recommendations have been provided for software development firms on the areas that might need more considerations and improvements.

A Research on the Structure of Intelligence and Creativity, and Creativity Style

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Feyzullah Şahin

2015-06-01

Full Text Available The relationship between intelligence and creativity may be linked to the difficulties in defining and measuring methodology. Threshold theory is one of the theories which is used to explain the relationship between them. The aim of this study is to investigate the structures which the creative thinking ability of the gifted students and their intellectual structure is grouped and the structure which their creative thinking ability are alone. Data was gathered using Wechsler Intelligence Scale for Children-R and Torrance Thinking Creativity Test (TTCT. Confirmatory factor analyses were conducted with data from 278 gifted primary school students which contained the grade range of 1 to 3. The results indicate that the TTCT subscores consist of 2 factors called adaptive and innovative rather than a single factor. Besides, the results of the analyses provide support that creativity and intelligence are independent from each other.

Gender, "g", and Fixed versus Growth Intelligence Mindsets as Predictors of Self-Estimated Domain Masculine Intelligence (DMIQ)

Science.gov (United States)

Storek, Josephine; Furnham, Adrian

2013-01-01

Over 120 participants completed three timed intelligence tests, a self-estimated Domain Masculine (DMIQ) Intelligence scale, and a mindset "beliefs about intelligence" measure (Dweck, 2012) to examine correlates of the Hubris-Humility Effect (HHE) which shows males believe they are more intelligent than females. As predicted males gave…

Trends in large-scale testing of reactor structures

International Nuclear Information System (INIS)

Blejwas, T.E.

2003-01-01

Large-scale tests of reactor structures have been conducted at Sandia National Laboratories since the late 1970s. This paper describes a number of different large-scale impact tests, pressurization tests of models of containment structures, and thermal-pressure tests of models of reactor pressure vessels. The advantages of large-scale testing are evident, but cost, in particular limits its use. As computer models have grown in size, such as number of degrees of freedom, the advent of computer graphics has made possible very realistic representation of results - results that may not accurately represent reality. A necessary condition to avoiding this pitfall is the validation of the analytical methods and underlying physical representations. Ironically, the immensely larger computer models sometimes increase the need for large-scale testing, because the modeling is applied to increasing more complex structural systems and/or more complex physical phenomena. Unfortunately, the cost of large-scale tests is a disadvantage that will likely severely limit similar testing in the future. International collaborations may provide the best mechanism for funding future programs with large-scale tests. (author)

Optimization of large-scale industrial systems : an emerging method

Energy Technology Data Exchange (ETDEWEB)

Hammache, A.; Aube, F.; Benali, M.; Cantave, R. [Natural Resources Canada, Varennes, PQ (Canada). CANMET Energy Technology Centre

2006-07-01

This paper reviewed optimization methods of large-scale industrial production systems and presented a novel systematic multi-objective and multi-scale optimization methodology. The methodology was based on a combined local optimality search with global optimality determination, and advanced system decomposition and constraint handling. The proposed method focused on the simultaneous optimization of the energy, economy and ecology aspects of industrial systems (E{sup 3}-ISO). The aim of the methodology was to provide guidelines for decision-making strategies. The approach was based on evolutionary algorithms (EA) with specifications including hybridization of global optimality determination with a local optimality search; a self-adaptive algorithm to account for the dynamic changes of operating parameters and design variables occurring during the optimization process; interactive optimization; advanced constraint handling and decomposition strategy; and object-oriented programming and parallelization techniques. Flowcharts of the working principles of the basic EA were presented. It was concluded that the EA uses a novel decomposition and constraint handling technique to enhance the Pareto solution search procedure for multi-objective problems. 6 refs., 9 figs.

The TRIDEC System-of-Systems; Choreography of large-scale concurrent tasks in Natural Crisis Management

Science.gov (United States)

Häner, R.; Wächter, J.

2012-04-01

The project Collaborative, Complex, and Critical Decision-Support in Evolving Crises (TRIDEC), co-funded by the European Commission in its Seventh Framework Programme aims at establishing a network of dedicated, autonomous legacy systems for large-scale concurrent management of natural crises utilising heterogeneous information resources. TRIDEC's architecture reflects the System-of- Systems (SoS) approach which is based on task-oriented systems, cooperatively interacting as a collective in a common environment. The design of the TRIDEC-SoS follows the principles of service-oriented and event-driven architectures (SOA & EDA) exceedingly focusing on a loose coupling of the systems. The SoS approach in combination with SOA and EDA has the distinction of being able to provide novel and coherent behaviours and features resulting from a process of dynamic self-organisation. Self-organisation is a process without the need for a central or external coordinator controlling it through orchestration. It is the result of enacted concurrent tasks in a collaborative environment of geographically distributed systems. Although the individual systems act completely autonomously, their interactions expose emergent structures of evolving nature. Particularly, the fact is important that SoS are inherently able to evolve on all facets of intelligent information management. This includes adaptive properties, e.g. seamless integration of new resource types or the adoption of new fields in natural crisis management. In the case of TRIDEC with various heterogeneous participants involved, concurrent information processing is of fundamental importance because of the achievable improvements regarding cooperative decision making. Collaboration within TRIDEC will be implemented with choreographies and conversations. Choreographies specify the expected behaviour between two or more participants; conversations describe the message exchange between all participants emphasising their logical

Using FML and fuzzy technology in adaptive ambient intelligent environments

NARCIS (Netherlands)

Acampora, G.; Loia, V.

2005-01-01

Ambient Intelligence (AmI, shortly) gathers best re-sults from three key technologies, Ubiquitous Computing, Ubiq-uitous Communication, and Intelligent User Friendly Inter-faces. The functional and spatial distribution of tasks is a natu-ral thrust to employ multi-agent paradigm to design and

Accuracy of Short Forms of the Dutch Wechsler Preschool and Primary Scale of Intelligence: Third Edition.

Science.gov (United States)

Hurks, Petra; Hendriksen, Jos; Dek, Joelle; Kooij, Andress

2016-04-01

This article investigated the accuracy of six short forms of the Dutch Wechsler Preschool and Primary Scale of Intelligence-Third edition (WPPSI-III-NL) in estimating intelligent quotient (IQ) scores in healthy children aged 4 to 7 years (N = 1,037). Overall, accuracy for each short form was studied, comparing IQ equivalences based on the short forms with the original WPPSI-III-NL Full Scale IQ (FSIQ) scores. Next, our sample was divided into three groups: children performing below average, average, or above average, based on the WPPSI-III-NL FSIQ estimates of the original long form, to study the accuracy of WPPSI-III-NL short forms at the tails of the FSIQ distribution. While studying the entire sample, all IQ estimates of the WPPSI-III-NL short forms correlated highly with the FSIQ estimates of the original long form (all rs ≥ .83). Correlations decreased significantly while studying only the tails of the IQ distribution (rs varied between .55 and .83). Furthermore, IQ estimates of the short forms deviated significantly from the FSIQ score of the original long form, when the IQ estimates were based on short forms containing only two subtests. In contrast, unlike the short forms that contained two to four subtests, the Wechsler Abbreviated Scale of Intelligence short form (containing the subtests Vocabulary, Similarities, Block Design, and Matrix Reasoning) and the General Ability Index short form (containing the subtests Vocabulary, Similarities, Comprehension, Block Design, Matrix Reasoning, and Picture Concepts) produced less variations when compared with the original FSIQ score. © The Author(s) 2015.

Construct Validity of the Wechsler Intelligence Scale for Children-Fourth UK Edition with a Referred Irish Sample: Wechsler and Cattell-Horn-Carroll Model Comparisons with 15 Subtests

Science.gov (United States)

Canivez, Gary L.; Watkins, Marley W.; Good, Rebecca; James, Kate; James, Trevor

2017-01-01

Background: Irish educational psychologists frequently use the Wechsler Intelligence Scale for Children-Fourth UK Edition (WISC-IV[superscript UK]; Wechsler, 2004, Wechsler Intelligence Scale for Children-Fourth UK Edition, London, UK, Harcourt Assessment) in clinical assessments of children with learning difficulties. Unfortunately, reliability…

SPATIALLY RESOLVED SPECTROSCOPY OF EUROPA’S LARGE-SCALE COMPOSITIONAL UNITS AT 3–4 μ m WITH KECK NIRSPEC

Energy Technology Data Exchange (ETDEWEB)

Fischer, P. D.; Brown, M. E.; Trumbo, S. K. [Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125 (United States); Hand, K. P., E-mail: pfischer@caltech.edu [Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109 (United States)

2017-01-01

We present spatially resolved spectroscopic observations of Europa’s surface at 3–4 μ m obtained with the near-infrared spectrograph and adaptive optics system on the Keck II telescope. These are the highest quality spatially resolved reflectance spectra of Europa’s surface at 3–4 μ m. The observations spatially resolve Europa’s large-scale compositional units at a resolution of several hundred kilometers. The spectra show distinct features and geographic variations associated with known compositional units; in particular, large-scale leading hemisphere chaos shows a characteristic longward shift in peak reflectance near 3.7 μ m compared to icy regions. These observations complement previous spectra of large-scale chaos, and can aid efforts to identify the endogenous non-ice species.

A Temporal Domain Decomposition Algorithmic Scheme for Large-Scale Dynamic Traffic Assignment

Directory of Open Access Journals (Sweden)

Eric J. Nava

2012-03-01

This paper presents a temporal decomposition scheme for large spatial- and temporal-scale dynamic traffic assignment, in which the entire analysis period is divided into Epochs. Vehicle assignment is performed sequentially in each Epoch, thus improving the model scalability and confining the peak run-time memory requirement regardless of the total analysis period. A proposed self-turning scheme adaptively searches for the run-time-optimal Epoch setting during iterations regardless of the characteristics of the modeled network. Extensive numerical experiments confirm the promising performance of the proposed algorithmic schemes.

A Brazilian Portuguese cross-cultural adaptation of the modified JOA scale for myelopathy

Directory of Open Access Journals (Sweden)

Raphael R. Pratali

Full Text Available OBJECTIVES: To develop a version of the modified Japanese Orthopaedic Association (mJOA scale that had been translated into Portuguese and cross-culturally adapted for the Brazilian population. METHODS: The well-established process of forward-backward translation was employed along with cross-cultural adaptation. RESULTS: Three bilingual translators (English and native Portuguese performed the forward translation of the mJOA scale from English to Portuguese based on iterative discussions used to reach a consensus translation. The translated version of the mJOA scale was then back-translated into English by a native English-speaking translator unaware of the concepts involved with the mJOA scale. The original mJOA scale and the back-translated version were compared by a native North American neurosurgeon, and as they were considered equivalent, the final version of the mJOA scale that had been translated into Portuguese and cross-culturally adapted was defined. CONCLUSION: To facilitate global and cross-cultural comparisons of the severity of cervical myelopathy, this study presents a version of the mJOA scale that was translated into Portuguese and cross-culturally adapted for the Brazilian population.

E-learning environment as intelligent tutoring system

Science.gov (United States)

Nagyová, Ingrid

2017-07-01

The development of computers and artificial intelligence theory allow their application in the field of education. Intelligent tutoring systems reflect student learning styles and adapt the curriculum according to their individual needs. The building of intelligent tutoring systems requires not only the creation of suitable software, but especially the search and application of the rules enabling ICT to individually adapt the curriculum. The main idea of this paper is to attempt to specify the rules for dividing the students to systematically working students and more practically or pragmatically inclined students. The paper shows that monitoring the work of students in e-learning environment, analysis of various approaches to educational materials and correspondence assignments show different results for the defined groups of students.

Development and validation of the Psychological Adaptation Scale (PAS): use in six studies of adaptation to a health condition or risk.

Science.gov (United States)

Biesecker, Barbara B; Erby, Lori H; Woolford, Samuel; Adcock, Jessica Young; Cohen, Julie S; Lamb, Amanda; Lewis, Katie V; Truitt, Megan; Turriff, Amy; Reeve, Bryce B

2013-11-01

We introduce The Psychological Adaptation Scale (PAS) for assessing adaptation to a chronic condition or risk and present validity data from six studies of genetic conditions. Informed by theory, we identified four domains of adaptation: effective coping, self-esteem, social integration, and spiritual/existential meaning. Items were selected from the PROMIS "positive illness impact" item bank and adapted from the Rosenberg self-esteem scale to create a 20-item scale. Each domain included five items, with four sub-scale scores. Data from studies of six populations: adults affected with or at risk for genetic conditions (N=3) and caregivers of children with genetic conditions (N=3) were analyzed using confirmatory factor analyses (CFA). CFA suggested that all but five posited items converge on the domains as designed. Invariance of the PAS amongst the studies further suggested it is a valid and reliable tool to facilitate comparisons of adaptation across conditions. Use of the PAS will standardize assessments of adaptation and foster understanding of the relationships among related health outcomes, such as quality of life and psychological well-being. Clinical interventions can be designed based on PAS data to enhance dimensions of psychological adaptation to a chronic health condition or risk. Published by Elsevier Ireland Ltd.

Large Scale Computations in Air Pollution Modelling

DEFF Research Database (Denmark)

Zlatev, Z.; Brandt, J.; Builtjes, P. J. H.

Proceedings of the NATO Advanced Research Workshop on Large Scale Computations in Air Pollution Modelling, Sofia, Bulgaria, 6-10 July 1998......Proceedings of the NATO Advanced Research Workshop on Large Scale Computations in Air Pollution Modelling, Sofia, Bulgaria, 6-10 July 1998...

Intelligent Distributed Computing VI : Proceedings of the 6th International Symposium on Intelligent Distributed Computing

CERN Document Server

Badica, Costin; Malgeri, Michele; Unland, Rainer

2013-01-01

This book represents the combined peer-reviewed proceedings of the Sixth International Symposium on Intelligent Distributed Computing -- IDC~2012, of the International Workshop on Agents for Cloud -- A4C~2012 and of the Fourth International Workshop on Multi-Agent Systems Technology and Semantics -- MASTS~2012. All the events were held in Calabria, Italy during September 24-26, 2012. The 37 contributions published in this book address many topics related to theory and applications of intelligent distributed computing and multi-agent systems, including: adaptive and autonomous distributed systems, agent programming, ambient assisted living systems, business process modeling and verification, cloud computing, coalition formation, decision support systems, distributed optimization and constraint satisfaction, gesture recognition, intelligent energy management in WSNs, intelligent logistics, machine learning, mobile agents, parallel and distributed computational intelligence, parallel evolutionary computing, trus...

Investigating Validity Evidence of the Satisfaction with Life Scale Adapted for Children

Science.gov (United States)

Gadermann, Anne M.; Schonert-Reichl, Kimberly A.; Zumbo, Bruno D.

2010-01-01

This study introduces the Satisfaction with Life Scale adapted for Children (SWLS-C) and presents psychometric findings regarding its validation. The SWLS-C was adapted from the Satisfaction with Life Scale (SWLS; Diener et al. 1985), which is one of the most commonly used measures to assess satisfaction with life in adults. Three subject matter…

Flood AI: An Intelligent Systems for Discovery and Communication of Disaster Knowledge

Science.gov (United States)

Demir, I.; Sermet, M. Y.

2017-12-01

Communities are not immune from extreme events or natural disasters that can lead to large-scale consequences for the nation and public. Improving resilience to better prepare, plan, recover, and adapt to disasters is critical to reduce the impacts of extreme events. The National Research Council (NRC) report discusses the topic of how to increase resilience to extreme events through a vision of resilient nation in the year 2030. The report highlights the importance of data, information, gaps and knowledge challenges that needs to be addressed, and suggests every individual to access the risk and vulnerability information to make their communities more resilient. This project presents an intelligent system, Flood AI, for flooding to improve societal preparedness by providing a knowledge engine using voice recognition, artificial intelligence, and natural language processing based on a generalized ontology for disasters with a primary focus on flooding. The knowledge engine utilizes the flood ontology and concepts to connect user input to relevant knowledge discovery channels on flooding by developing a data acquisition and processing framework utilizing environmental observations, forecast models, and knowledge bases. Communication channels of the framework includes web-based systems, agent-based chat bots, smartphone applications, automated web workflows, and smart home devices, opening the knowledge discovery for flooding to many unique use cases.

SEX DIFFERENCES ON THE WECHSLER INTELLIGENCE SCALE FOR CHILDREN-III IN BAHRAIN AND THE UNITED STATES.

Science.gov (United States)

Bakhiet, Salaheldin Farah Attallah; Lynn, Richard

2015-12-01

Sex differences on the Wechsler Intelligence Scale for Children-III (WISC-III) are reported for children in Bahrain and the United States. The results for the two samples were consistent in showing no significant differences in Verbal, Performance, and Full Scale IQs, higher average scores by boys on the Block design and Mazes subtests of spatial ability, and higher average scores by girls on Coding. There was also greater variability in boys than in girls.

A NDVI assisted remote sensing image adaptive scale segmentation method

Science.gov (United States)

Zhang, Hong; Shen, Jinxiang; Ma, Yanmei

2018-03-01

Multiscale segmentation of images can effectively form boundaries of different objects with different scales. However, for the remote sensing image which widely coverage with complicated ground objects, the number of suitable segmentation scales, and each of the scale size is still difficult to be accurately determined, which severely restricts the rapid information extraction of the remote sensing image. A great deal of experiments showed that the normalized difference vegetation index (NDVI) can effectively express the spectral characteristics of a variety of ground objects in remote sensing images. This paper presents a method using NDVI assisted adaptive segmentation of remote sensing images, which segment the local area by using NDVI similarity threshold to iteratively select segmentation scales. According to the different regions which consist of different targets, different segmentation scale boundaries could be created. The experimental results showed that the adaptive segmentation method based on NDVI can effectively create the objects boundaries for different ground objects of remote sensing images.

Veiligheidsaspecten bij een grootschalige proef met Intelligente Snelheidsaanpassing (ISA) : opzet van een evaluatiekader aan de hand van open interviews.

NARCIS (Netherlands)

Jagtman, H.M.

2004-01-01

Safety aspects in a large-scale experiment with Intelligent Speed Adaptation; The design of an evaluation framework using open interviews. All sorts of in-vehicle Intelligent Transport Systems are being designed and, in the meantime, a number of `simple' systems have already been introduced. Until

Growth Limits in Large Scale Networks

DEFF Research Database (Denmark)

Knudsen, Thomas Phillip

limitations. The rising complexity of network management with the convergence of communications platforms is shown as problematic for both automatic management feasibility and for manpower resource management. In the fourth step the scope is extended to include the present society with the DDN project as its......The Subject of large scale networks is approached from the perspective of the network planner. An analysis of the long term planning problems is presented with the main focus on the changing requirements for large scale networks and the potential problems in meeting these requirements. The problems...... the fundamental technological resources in network technologies are analysed for scalability. Here several technological limits to continued growth are presented. The third step involves a survey of major problems in managing large scale networks given the growth of user requirements and the technological...

Accelerating sustainability in large-scale facilities

CERN Multimedia

Marina Giampietro

2011-01-01

Scientific research centres and large-scale facilities are intrinsically energy intensive, but how can big science improve its energy management and eventually contribute to the environmental cause with new cleantech? CERN’s commitment to providing tangible answers to these questions was sealed in the first workshop on energy management for large scale scientific infrastructures held in Lund, Sweden, on the 13-14 October.   Participants at the energy management for large scale scientific infrastructures workshop. The workshop, co-organised with the European Spallation Source (ESS) and  the European Association of National Research Facilities (ERF), tackled a recognised need for addressing energy issues in relation with science and technology policies. It brought together more than 150 representatives of Research Infrastrutures (RIs) and energy experts from Europe and North America. “Without compromising our scientific projects, we can ...

Vision Guided Intelligent Robot Design And Experiments

Science.gov (United States)

Slutzky, G. D.; Hall, E. L.

1988-02-01

The concept of an intelligent robot is an important topic combining sensors, manipulators, and artificial intelligence to design a useful machine. Vision systems, tactile sensors, proximity switches and other sensors provide the elements necessary for simple game playing as well as industrial applications. These sensors permit adaption to a changing environment. The AI techniques permit advanced forms of decision making, adaptive responses, and learning while the manipulator provides the ability to perform various tasks. Computer languages such as LISP and OPS5, have been utilized to achieve expert systems approaches in solving real world problems. The purpose of this paper is to describe several examples of visually guided intelligent robots including both stationary and mobile robots. Demonstrations will be presented of a system for constructing and solving a popular peg game, a robot lawn mower, and a box stacking robot. The experience gained from these and other systems provide insight into what may be realistically expected from the next generation of intelligent machines.

Large scale reflood test

International Nuclear Information System (INIS)

Hirano, Kemmei; Murao, Yoshio

1980-01-01

The large-scale reflood test with a view to ensuring the safety of light water reactors was started in fiscal 1976 based on the special account act for power source development promotion measures by the entrustment from the Science and Technology Agency. Thereafter, to establish the safety of PWRs in loss-of-coolant accidents by joint international efforts, the Japan-West Germany-U.S. research cooperation program was started in April, 1980. Thereupon, the large-scale reflood test is now included in this program. It consists of two tests using a cylindrical core testing apparatus for examining the overall system effect and a plate core testing apparatus for testing individual effects. Each apparatus is composed of the mock-ups of pressure vessel, primary loop, containment vessel and ECCS. The testing method, the test results and the research cooperation program are described. (J.P.N.)

Validation of the Serbian adaptation of the Trait Emotional Intelligence Questionnaire-Child Form (TEIQue-CF

Directory of Open Access Journals (Sweden)

Banjac Sonja

2016-01-01

Full Text Available This study investigated trait EI in childhood in a Serbian population by validating a Serbian adaptation of the Trait Emotional Intelligence Questionnaire - Child Form (TEIQue-CF. All 606 participants (Mage = 10.33, SD = 1.55 completed the TEIQue-CF, the Reading the Mind in the Eyes Test (revised version, and the Guess Who peer assessment. Data on academic achievement and truancy were also obtained. The Serbian TEIQue-CF demonstrated robust psychometric properties with satisfactory internal consistencies and extensive evidence of validity in relation to criteria such as emotion recognition, academic grades, truancy rates, and peer ratings. Factor analyses suggested a two-factor solution for the total sample, but a unifactorial structure for the two groups of younger children aged 8 to 9 and 10 to 11. Overall, the results corroborate the validity of the Serbian adaptation and the theoretical and practical importance of the construct of trait EI in children. [Projekat Ministarstva nauke Republike Srbije, br. 179018

Adaptation of the multidimensional scale of perceived social support ...

African Journals Online (AJOL)

Background: The Multidimensional Scale of Perceived Social Support (MSPSS) was developed in the USA. The adequacy of its use in Uganda to guarantee its reliability and validity has not been ascertained. Aim: Thus the aim of the present study was to adapt the MSPSS scale by testing the validity and reliability of the ...

Career Adapt-Abilities Scale--Italian Form: Psychometric Properties and Relationships to Breadth of Interests, Quality of Life, and Perceived Barriers

Science.gov (United States)

Soresi, Salvatore; Nota, Laura; Ferrari, Lea

2012-01-01

The Career Adapt-Abilities Scale (CAAS)-Italian Form consists of four 6-item scales, which measure concern, control, curiosity, and confidence as psychosocial resources for managing occupational transitions, developmental tasks, and work traumas. The 24-item CAAS-Italian Form is identical to the International Form 2.0. The factor structure was…

Understanding the Gap between Cognitive Abilities and Daily Living Skills in Adolescents with Autism Spectrum Disorders with Average Intelligence

Science.gov (United States)

Duncan, Amie W.; Bishop, Somer L.

2015-01-01

Daily living skills standard scores on the Vineland Adaptive Behavior Scales-2nd edition were examined in 417 adolescents from the Simons Simplex Collection. All participants had at least average intelligence and a diagnosis of autism spectrum disorder. Descriptive statistics and binary logistic regressions were used to examine the prevalence and…

Large-scale recovery of an endangered amphibian despite ongoing exposure to multiple stressors

Science.gov (United States)

Knapp, Roland A.; Fellers, Gary M.; Kleeman, Patrick M.; Miller, David A. W.; Vrendenburg, Vance T.; Rosenblum, Erica Bree; Briggs, Cheryl J.

2016-01-01

Amphibians are one of the most threatened animal groups, with 32% of species at risk for extinction. Given this imperiled status, is the disappearance of a large fraction of the Earth’s amphibians inevitable, or are some declining species more resilient than is generally assumed? We address this question in a species that is emblematic of many declining amphibians, the endangered Sierra Nevada yellow-legged frog (Rana sierrae). Based on >7,000 frog surveys conducted across Yosemite National Park over a 20-y period, we show that, after decades of decline and despite ongoing exposure to multiple stressors, including introduced fish, the recently emerged disease chytridiomycosis, and pesticides, R. sierrae abundance increased sevenfold during the study and at a rate of 11% per year. These increases occurred in hundreds of populations throughout Yosemite, providing a rare example of amphibian recovery at an ecologically relevant spatial scale. Results from a laboratory experiment indicate that these increases may be in part because of reduced frog susceptibility to chytridiomycosis. The disappearance of nonnative fish from numerous water bodies after cessation of stocking also contributed to the recovery. The large-scale increases in R. sierrae abundance that we document suggest that, when habitats are relatively intact and stressors are reduced in their importance by active management or species’ adaptive responses, declines of some amphibians may be partially reversible, at least at a regional scale. Other studies conducted over similarly large temporal and spatial scales are critically needed to provide insight and generality about the reversibility of amphibian declines at a global scale.

Large Scale Cosmological Anomalies and Inhomogeneous Dark Energy

Directory of Open Access Journals (Sweden)

Leandros Perivolaropoulos

2014-01-01

Full Text Available A wide range of large scale observations hint towards possible modifications on the standard cosmological model which is based on a homogeneous and isotropic universe with a small cosmological constant and matter. These observations, also known as “cosmic anomalies” include unexpected Cosmic Microwave Background perturbations on large angular scales, large dipolar peculiar velocity flows of galaxies (“bulk flows”, the measurement of inhomogenous values of the fine structure constant on cosmological scales (“alpha dipole” and other effects. The presence of the observational anomalies could either be a large statistical fluctuation in the context of ΛCDM or it could indicate a non-trivial departure from the cosmological principle on Hubble scales. Such a departure is very much constrained by cosmological observations for matter. For dark energy however there are no significant observational constraints for Hubble scale inhomogeneities. In this brief review I discuss some of the theoretical models that can naturally lead to inhomogeneous dark energy, their observational constraints and their potential to explain the large scale cosmic anomalies.

Large-scale patterns in Rayleigh-Benard convection

International Nuclear Information System (INIS)

Hardenberg, J. von; Parodi, A.; Passoni, G.; Provenzale, A.; Spiegel, E.A.

2008-01-01

Rayleigh-Benard convection at large Rayleigh number is characterized by the presence of intense, vertically moving plumes. Both laboratory and numerical experiments reveal that the rising and descending plumes aggregate into separate clusters so as to produce large-scale updrafts and downdrafts. The horizontal scales of the aggregates reported so far have been comparable to the horizontal extent of the containers, but it has not been clear whether that represents a limitation imposed by domain size. In this work, we present numerical simulations of convection at sufficiently large aspect ratio to ascertain whether there is an intrinsic saturation scale for the clustering process when that ratio is large enough. From a series of simulations of Rayleigh-Benard convection with Rayleigh numbers between 10 5 and 10 8 and with aspect ratios up to 12π, we conclude that the clustering process has a finite horizontal saturation scale with at most a weak dependence on Rayleigh number in the range studied

Swarm intelligence. A whole new way to think about business.

Science.gov (United States)

Bonabeau, E; Meyer, C

2001-05-01

What do ants and bees have to do with business? A great deal, it turns out. Individually, social insects are only minimally intelligent, and their work together is largely self-organized and unsupervised. Yet collectively they're capable of finding highly efficient solutions to difficult problems and can adapt automatically to changing environments. Over the past 20 years, the authors and other researchers have developed rigorous mathematical models to describe this phenomenon, which has been dubbed "swarm intelligence," and they are now applying them to business. Their research has already helped several companies develop more efficient ways to schedule factory equipment, divide tasks among workers, organize people, and even plot strategy. Emulating the way ants find the shortest path to a new food supply, for example, has led researchers at Hewlett-Packard to develop software programs that can find the most efficient way to route phone traffic over a telecommunications network. South-west Airlines has used a similar model to efficiently route cargo. To allocate labor, honeybees appear to follow one simple but powerful rule--they seem to specialize in a particular activity unless they perceive an important need to perform another function. Using that model, researchers at Northwestern University have devised a system for painting trucks that can automatically adapt to changing conditions. In the future, the authors speculate, a company might structure its entire business using the principles of swarm intelligence. The result, they believe, would be the ultimate self-organizing enterprise--one that could adapt quickly and instinctively to fast-changing markets.

Revisiting the Psychology of Intelligence Analysis: From Rational Actors to Adaptive Thinkers

Science.gov (United States)

Puvathingal, Bess J.; Hantula, Donald A.

2012-01-01

Intelligence analysis is a decision-making process rife with ambiguous, conflicting, irrelevant, important, and excessive information. The U.S. Intelligence Community is primed for psychology to lend its voice to the "analytic transformation" movement aimed at improving the quality of intelligence analysis. Traditional judgment and decision making…

Factor Structure of the Wechsler Intelligence Scales for Children-Fourth Edition among Referred Native American Students

Science.gov (United States)

Nakano, Selena; Watkins, Marley W.

2013-01-01

The Native American population is severely underrepresented in empirical test validity research despite being overrepresented in special education programs and at increased risk for psychoeducational evaluation. The structural validity of the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) was investigated with a sample of 176,…

2013 Chinese Intelligent Automation Conference

CERN Document Server

Deng, Zhidong

2013-01-01

Proceedings of the 2013 Chinese Intelligent Automation Conference presents selected research papers from the CIAC’13, held in Yangzhou, China. The topics include e.g. adaptive control, fuzzy control, neural network based control, knowledge based control, hybrid intelligent control, learning control, evolutionary mechanism based control, multi-sensor integration, failure diagnosis, and reconfigurable control. Engineers and researchers from academia, industry, and government can gain an inside view of new solutions combining ideas from multiple disciplines in the field of intelligent automation.   Zengqi Sun and Zhidong Deng are professors at the Department of Computer Science, Tsinghua University, China.

2013 Chinese Intelligent Automation Conference

CERN Document Server

Deng, Zhidong

2013-01-01

Proceedings of the 2013 Chinese Intelligent Automation Conference presents selected research papers from the CIAC’13, held in Yangzhou, China. The topics include e.g. adaptive control, fuzzy control, neural network based control, knowledge based control, hybrid intelligent control, learning control, evolutionary mechanism based control, multi-sensor integration, failure diagnosis, and reconfigurable control. Engineers and researchers from academia, industry, and government can gain an inside view of new solutions combining ideas from multiple disciplines in the field of intelligent automation. Zengqi Sun and Zhidong Deng are professors at the Department of Computer Science, Tsinghua University, China.

From dinosaurs to modern bird diversity: extending the time scale of adaptive radiation.

Directory of Open Access Journals (Sweden)

Daniel Moen

2014-05-01

Full Text Available What explains why some groups of organisms, like birds, are so species rich? And what explains their extraordinary ecological diversity, ranging from large, flightless birds to small migratory species that fly thousand of kilometers every year? These and similar questions have spurred great interest in adaptive radiation, the diversification of ecological traits in a rapidly speciating group of organisms. Although the initial formulation of modern concepts of adaptive radiation arose from consideration of the fossil record, rigorous attempts to identify adaptive radiation in the fossil record are still uncommon. Moreover, most studies of adaptive radiation concern groups that are less than 50 million years old. Thus, it is unclear how important adaptive radiation is over temporal scales that span much larger portions of the history of life. In this issue, Benson et al. test the idea of a "deep-time" adaptive radiation in dinosaurs, compiling and using one of the most comprehensive phylogenetic and body-size datasets for fossils. Using recent phylogenetic statistical methods, they find that in most clades of dinosaurs there is a strong signal of an "early burst" in body-size evolution, a predicted pattern of adaptive radiation in which rapid trait evolution happens early in a group's history and then slows down. They also find that body-size evolution did not slow down in the lineage leading to birds, hinting at why birds survived to the present day and diversified. This paper represents one of the most convincing attempts at understanding deep-time adaptive radiations.

From dinosaurs to modern bird diversity: extending the time scale of adaptive radiation.

Science.gov (United States)

Moen, Daniel; Morlon, Hélène

2014-05-01

What explains why some groups of organisms, like birds, are so species rich? And what explains their extraordinary ecological diversity, ranging from large, flightless birds to small migratory species that fly thousand of kilometers every year? These and similar questions have spurred great interest in adaptive radiation, the diversification of ecological traits in a rapidly speciating group of organisms. Although the initial formulation of modern concepts of adaptive radiation arose from consideration of the fossil record, rigorous attempts to identify adaptive radiation in the fossil record are still uncommon. Moreover, most studies of adaptive radiation concern groups that are less than 50 million years old. Thus, it is unclear how important adaptive radiation is over temporal scales that span much larger portions of the history of life. In this issue, Benson et al. test the idea of a "deep-time" adaptive radiation in dinosaurs, compiling and using one of the most comprehensive phylogenetic and body-size datasets for fossils. Using recent phylogenetic statistical methods, they find that in most clades of dinosaurs there is a strong signal of an "early burst" in body-size evolution, a predicted pattern of adaptive radiation in which rapid trait evolution happens early in a group's history and then slows down. They also find that body-size evolution did not slow down in the lineage leading to birds, hinting at why birds survived to the present day and diversified. This paper represents one of the most convincing attempts at understanding deep-time adaptive radiations.

Intelligent Membranes: Dream or Reality?

Directory of Open Access Journals (Sweden)

Annarosa Gugliuzza

2013-07-01

Full Text Available Intelligent materials are claimed to overcome current drawbacks associated with the attainment of high standards of life, health, security and defense. Membrane-based sensors represent a category of smart systems capable of providing a large number of benefits to different markets of textiles, biomedicine, environment, chemistry, agriculture, architecture, transport and energy. Intelligent membranes can be characterized by superior sensitivity, broader dynamic range and highly sophisticated mechanisms of autorecovery. These prerogatives are regarded as the result of multi-compartment arrays, where complementary functions can be accommodated and well-integrated. Based on the mechanism of “sense to act”, stimuli-responsive membranes adapt themselves to surrounding environments, producing desired effects such as smart regulation of transport, wetting, transcription, hydrodynamics, separation, and chemical or energy conversion. Hopefully, the design of new smart devices easier to manufacture and assemble can be realized through the integration of sensing membranes with wireless networks, looking at the ambitious challenge to establish long-distance communications. Thus, the transfer of signals to collecting systems could allow continuous and real-time monitoring of data, events and/or processes.

A Factor-Analytic Study of Adaptive Behavior and Intellectual Functioning in Learning Disabled Children.

Science.gov (United States)

Yeargan, Dollye R.

The factorial structure of intellectual functioning and adaptive behavior was examined in 160 learning disabled students (6 to 16 years old). Ss were administered the Wechsler Intelligence Scale for Children-Revised (WISC-R) and the Coping Inventory (CI). Factor analysis of WISC-R scores revealed three factors: verbal comprehenson, perceptual…

Structure of the Wechsler Intelligence Scale for Children--Fourth Edition among a national sample of referred students.

Science.gov (United States)

Watkins, Marley W

2010-12-01

The structure of the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV; D. Wechsler, 2003a) was analyzed via confirmatory factor analysis among a national sample of 355 students referred for psychoeducational evaluation by 93 school psychologists from 35 states. The structure of the WISC-IV core battery was best represented by four first-order factors as per D. Wechsler (2003b), plus a general intelligence factor in a direct hierarchical model. The general factor was the predominate source of variation among WISC-IV subtests, accounting for 48% of the total variance and 75% of the common variance. The largest 1st-order factor, Processing Speed, only accounted for 6.1% total and 9.5% common variance. Given these explanatory contributions, recommendations favoring interpretation of the 1st-order factor scores over the general intelligence score appear to be misguided.

Intelligibility in Context Scale: Normative and Validation Data for English-Speaking Preschoolers.

Science.gov (United States)

McLeod, Sharynne; Crowe, Kathryn; Shahaeian, Ameneh

2015-07-01

The purpose of this study was to describe normative and validation data on the Intelligibility in Context Scale (ICS; McLeod, Harrison, & McCormack, 2012c) for English-speaking children. The ICS is a 7-item, parent-report measure of children's speech intelligibility with a range of communicative partners. Data were collected from the parents of 803 Australian English-speaking children ranging in age from 4;0 (years;months) to 5;5 (37.0% were multilingual). The mean ICS score was 4.4 (SD = 0.7) out of a possible total score of 5. Children's speech was reported to be most intelligible to their parents, followed by their immediate family, friends, and teachers; children's speech was least intelligible to strangers. The ICS had high internal consistency (α = .94). Significant differences in scores were identified on the basis of sex and age but not on the basis of socioeconomic status or the number of languages spoken. There were significant differences in scores between children whose parents had concerns about their child's speech (M = 3.9) and those who did not (M = 4.6). A sensitivity of .82 and a specificity of .58 were established as the optimal cutoff. Test-retest reliability and criterion validity were established for 184 children with a speech sound disorder. There was a significant low correlation between the ICS mean score and percentage of phonemes correct (r = .30), percentage of consonants correct (r = .24), and percentage of vowels correct (r = .30) on the Diagnostic Evaluation of Articulation and Phonology (Dodd, Hua, Crosbie, Holm, & Ozanne, 2002). Thirty-one parents completed the ICS related to English and another language spoken by their child with a speech sound disorder. The significant correlations between the scores suggest that the ICS may be robust between languages. This article provides normative ICS data for English-speaking children and additional validation of the psychometric properties of the ICS. The robustness of the ICS was suggested

Factor structure of the Wechsler Intelligence Scale for Children-Fifth Edition: Exploratory factor analyses with the 16 primary and secondary subtests.

Science.gov (United States)

Canivez, Gary L; Watkins, Marley W; Dombrowski, Stefan C

2016-08-01

The factor structure of the 16 Primary and Secondary subtests of the Wechsler Intelligence Scale for Children-Fifth Edition (WISC-V; Wechsler, 2014a) standardization sample was examined with exploratory factor analytic methods (EFA) not included in the WISC-V Technical and Interpretive Manual (Wechsler, 2014b). Factor extraction criteria suggested 1 to 4 factors and results favored 4 first-order factors. When this structure was transformed with the Schmid and Leiman (1957) orthogonalization procedure, the hierarchical g-factor accounted for large portions of total and common variance while the 4 first-order factors accounted for small portions of total and common variance; rendering interpretation at the factor index level less appropriate. Although the publisher favored a 5-factor model where the Perceptual Reasoning factor was split into separate Visual Spatial and Fluid Reasoning dimensions, no evidence for 5 factors was found. It was concluded that the WISC-V provides strong measurement of general intelligence and clinical interpretation should be primarily, if not exclusively, at that level. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Manufacturing test of large scale hollow capsule and long length cladding in the large scale oxide dispersion strengthened (ODS) martensitic steel

International Nuclear Information System (INIS)

Narita, Takeshi; Ukai, Shigeharu; Kaito, Takeji; Ohtsuka, Satoshi; Fujiwara, Masayuki

2004-04-01

Mass production capability of oxide dispersion strengthened (ODS) martensitic steel cladding (9Cr) has being evaluated in the Phase II of the Feasibility Studies on Commercialized Fast Reactor Cycle System. The cost for manufacturing mother tube (raw materials powder production, mechanical alloying (MA) by ball mill, canning, hot extrusion, and machining) is a dominant factor in the total cost for manufacturing ODS ferritic steel cladding. In this study, the large-sale 9Cr-ODS martensitic steel mother tube which is made with a large-scale hollow capsule, and long length claddings were manufactured, and the applicability of these processes was evaluated. Following results were obtained in this study. (1) Manufacturing the large scale mother tube in the dimension of 32 mm OD, 21 mm ID, and 2 m length has been successfully carried out using large scale hollow capsule. This mother tube has a high degree of accuracy in size. (2) The chemical composition and the micro structure of the manufactured mother tube are similar to the existing mother tube manufactured by a small scale can. And the remarkable difference between the bottom and top sides in the manufactured mother tube has not been observed. (3) The long length cladding has been successfully manufactured from the large scale mother tube which was made using a large scale hollow capsule. (4) For reducing the manufacturing cost of the ODS steel claddings, manufacturing process of the mother tubes using a large scale hollow capsules is promising. (author)

Using Score Equating and Measurement Invariance to Examine the Flynn Effect in the Wechsler Adult Intelligence Scale.

Science.gov (United States)

Benson, Nicholas; Beaujean, A Alexander; Taub, Gordon E

2015-01-01

The Flynn effect (FE; i.e., increase in mean IQ scores over time) is commonly viewed as reflecting population shifts in intelligence, despite the fact that most FE studies have not investigated the assumption of score comparability. Consequently, the extent to which these mean differences in IQ scores reflect population shifts in cognitive abilities versus changes in the instruments used to measure these abilities is unclear. In this study, we used modern psychometric tools to examine the FE. First, we equated raw scores for each common subtest to be on the same scale across instruments. This enabled the combination of scores from all three instruments into one of 13 age groups before converting raw scores into Z scores. Second, using age-based standardized scores for standardization samples, we examined measurement invariance across the second (revised), third, and fourth editions of the Wechsler Adult Intelligence Scale. Results indicate that while scores were equivalent across the third and fourth editions, they were not equivalent across the second and third editions. Results suggest that there is some evidence for an increase in intelligence, but also call into question many published FE findings as presuming the instruments' scores are invariant when this assumption is not warranted.

Intelligence of programs

Energy Technology Data Exchange (ETDEWEB)

Novak, D

1982-01-01

A general discussion about the level of artificial intelligence in computer programs is presented. The suitability of various languages for the development of complex, intelligent programs is discussed, considering fourth-generation language as well as the well established structured COBOL language. It is concluded that the success of automation in many administrative fields depends to a large extent on the development of intelligent programs.

A simple transferable adaptive potential to study phase separation in large-scale xMgO-(1-x)SiO2 binary glasses.

Science.gov (United States)

Bidault, Xavier; Chaussedent, Stéphane; Blanc, Wilfried

2015-10-21

A simple transferable adaptive model is developed and it allows for the first time to simulate by molecular dynamics the separation of large phases in the MgO-SiO2 binary system, as experimentally observed and as predicted by the phase diagram, meaning that separated phases have various compositions. This is a real improvement over fixed-charge models, which are often limited to an interpretation involving the formation of pure clusters, or involving the modified random network model. Our adaptive model, efficient to reproduce known crystalline and glassy structures, allows us to track the formation of large amorphous Mg-rich Si-poor nanoparticles in an Mg-poor Si-rich matrix from a 0.1MgO-0.9SiO2 melt.

Amplification of large-scale magnetic field in nonhelical magnetohydrodynamics

KAUST Repository

Kumar, Rohit

2017-08-11

It is typically assumed that the kinetic and magnetic helicities play a crucial role in the growth of large-scale dynamo. In this paper, we demonstrate that helicity is not essential for the amplification of large-scale magnetic field. For this purpose, we perform nonhelical magnetohydrodynamic (MHD) simulation, and show that the large-scale magnetic field can grow in nonhelical MHD when random external forcing is employed at scale 1/10 the box size. The energy fluxes and shell-to-shell transfer rates computed using the numerical data show that the large-scale magnetic energy grows due to the energy transfers from the velocity field at the forcing scales.

Intelligent Control Systems with an Introduction to System of Systems Engineering

CERN Document Server

Nanayakkara, Thrishantha

2009-01-01

From aeronautics and manufacturing to healthcare and disaster management, systems engineering (SE) focuses on designing applications that ensure performance optimization. This title integrates the fundamentals of artificial intelligence and systems control in a framework applicable to both simple dynamic systems and large-scale system of systems

The highly intelligent virtual agents for modeling financial markets

Science.gov (United States)

Yang, G.; Chen, Y.; Huang, J. P.

2016-02-01

Researchers have borrowed many theories from statistical physics, like ensemble, Ising model, etc., to study complex adaptive systems through agent-based modeling. However, one fundamental difference between entities (such as spins) in physics and micro-units in complex adaptive systems is that the latter are usually with high intelligence, such as investors in financial markets. Although highly intelligent virtual agents are essential for agent-based modeling to play a full role in the study of complex adaptive systems, how to create such agents is still an open question. Hence, we propose three principles for designing high artificial intelligence in financial markets and then build a specific class of agents called iAgents based on these three principles. Finally, we evaluate the intelligence of iAgents through virtual index trading in two different stock markets. For comparison, we also include three other types of agents in this contest, namely, random traders, agents from the wealth game (modified on the famous minority game), and agents from an upgraded wealth game. As a result, iAgents perform the best, which gives a well support for the three principles. This work offers a general framework for the further development of agent-based modeling for various kinds of complex adaptive systems.

A proposed method to estimate premorbid full scale intelligence quotient (FSIQ) for the Canadian Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) using demographic and combined estimation procedures.

Science.gov (United States)

Schoenberg, Mike R; Lange, Rael T; Saklofske, Donald H

2007-11-01

Establishing a comparison standard in neuropsychological assessment is crucial to determining change in function. There is no available method to estimate premorbid intellectual functioning for the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV). The WISC-IV provided normative data for both American and Canadian children aged 6 to 16 years old. This study developed regression algorithms as a proposed method to estimate full-scale intelligence quotient (FSIQ) for the Canadian WISC-IV. Participants were the Canadian WISC-IV standardization sample (n = 1,100). The sample was randomly divided into two groups (development and validation groups). The development group was used to generate regression algorithms; 1 algorithm only included demographics, and 11 combined demographic variables with WISC-IV subtest raw scores. The algorithms accounted for 18% to 70% of the variance in FSIQ (standard error of estimate, SEE = 8.6 to 14.2). Estimated FSIQ significantly correlated with actual FSIQ (r = .30 to .80), and the majority of individual FSIQ estimates were within +/-10 points of actual FSIQ. The demographic-only algorithm was less accurate than algorithms combining demographic variables with subtest raw scores. The current algorithms yielded accurate estimates of current FSIQ for Canadian individuals aged 6-16 years old. The potential application of the algorithms to estimate premorbid FSIQ is reviewed. While promising, clinical validation of the algorithms in a sample of children and/or adolescents with known neurological dysfunction is needed to establish these algorithms as a premorbid estimation procedure.

Intelligent Augmented Reality Training for Motherboard Assembly

Science.gov (United States)

Westerfield, Giles; Mitrovic, Antonija; Billinghurst, Mark

2015-01-01

We investigate the combination of Augmented Reality (AR) with Intelligent Tutoring Systems (ITS) to assist with training for manual assembly tasks. Our approach combines AR graphics with adaptive guidance from the ITS to provide a more effective learning experience. We have developed a modular software framework for intelligent AR training…

Unraveling The Connectome: Visualizing and Abstracting Large-Scale Connectomics Data

KAUST Repository

Al-Awami, Ali K.

2017-04-30

volumes interactively. We focus on two aspects: (1) Segmented objects are often toggled on and off by an interactive query, which makes it unfeasible to pre-compute a well-adapted space subdivision. (2) To scale to large data, culling and empty-space skipping must scale with the output size instead of the input volume. Our approach combines the advantages of object- and image-order stages of the empty-space skipping process.

Sensitivity technologies for large scale simulation

International Nuclear Information System (INIS)

Collis, Samuel Scott; Bartlett, Roscoe Ainsworth; Smith, Thomas Michael; Heinkenschloss, Matthias; Wilcox, Lucas C.; Hill, Judith C.; Ghattas, Omar; Berggren, Martin Olof; Akcelik, Volkan; Ober, Curtis Curry; van Bloemen Waanders, Bart Gustaaf; Keiter, Eric Richard

2005-01-01

Sensitivity analysis is critically important to numerous analysis algorithms, including large scale optimization, uncertainty quantification,reduced order modeling, and error estimation. Our research focused on developing tools, algorithms and standard interfaces to facilitate the implementation of sensitivity type analysis into existing code and equally important, the work was focused on ways to increase the visibility of sensitivity analysis. We attempt to accomplish the first objective through the development of hybrid automatic differentiation tools, standard linear algebra interfaces for numerical algorithms, time domain decomposition algorithms and two level Newton methods. We attempt to accomplish the second goal by presenting the results of several case studies in which direct sensitivities and adjoint methods have been effectively applied, in addition to an investigation of h-p adaptivity using adjoint based a posteriori error estimation. A mathematical overview is provided of direct sensitivities and adjoint methods for both steady state and transient simulations. Two case studies are presented to demonstrate the utility of these methods. A direct sensitivity method is implemented to solve a source inversion problem for steady state internal flows subject to convection diffusion. Real time performance is achieved using novel decomposition into offline and online calculations. Adjoint methods are used to reconstruct initial conditions of a contamination event in an external flow. We demonstrate an adjoint based transient solution. In addition, we investigated time domain decomposition algorithms in an attempt to improve the efficiency of transient simulations. Because derivative calculations are at the root of sensitivity calculations, we have developed hybrid automatic differentiation methods and implemented this approach for shape optimization for gas dynamics using the Euler equations. The hybrid automatic differentiation method was applied to a first

Hydrometeorological variability on a large french catchment and its relation to large-scale circulation across temporal scales

Science.gov (United States)

Massei, Nicolas; Dieppois, Bastien; Fritier, Nicolas; Laignel, Benoit; Debret, Maxime; Lavers, David; Hannah, David

2015-04-01

In the present context of global changes, considerable efforts have been deployed by the hydrological scientific community to improve our understanding of the impacts of climate fluctuations on water resources. Both observational and modeling studies have been extensively employed to characterize hydrological changes and trends, assess the impact of climate variability or provide future scenarios of water resources. In the aim of a better understanding of hydrological changes, it is of crucial importance to determine how and to what extent trends and long-term oscillations detectable in hydrological variables are linked to global climate oscillations. In this work, we develop an approach associating large-scale/local-scale correlation, enmpirical statistical downscaling and wavelet multiresolution decomposition of monthly precipitation and streamflow over the Seine river watershed, and the North Atlantic sea level pressure (SLP) in order to gain additional insights on the atmospheric patterns associated with the regional hydrology. We hypothesized that: i) atmospheric patterns may change according to the different temporal wavelengths defining the variability of the signals; and ii) definition of those hydrological/circulation relationships for each temporal wavelength may improve the determination of large-scale predictors of local variations. The results showed that the large-scale/local-scale links were not necessarily constant according to time-scale (i.e. for the different frequencies characterizing the signals), resulting in changing spatial patterns across scales. This was then taken into account by developing an empirical statistical downscaling (ESD) modeling approach which integrated discrete wavelet multiresolution analysis for reconstructing local hydrometeorological processes (predictand : precipitation and streamflow on the Seine river catchment) based on a large-scale predictor (SLP over the Euro-Atlantic sector) on a monthly time-step. This approach

Superconducting materials for large scale applications

International Nuclear Information System (INIS)

Dew-Hughes, D.

1975-01-01

Applications of superconductors capable of carrying large current densities in large-scale electrical devices are examined. Discussions are included on critical current density, superconducting materials available, and future prospects for improved superconducting materials. (JRD)

Brain entropy and human intelligence: A resting-state fMRI study

Science.gov (United States)

Calderone, Daniel; Morales, Leah J.

2018-01-01

Human intelligence comprises comprehension of and reasoning about an infinitely variable external environment. A brain capable of large variability in neural configurations, or states, will more easily understand and predict variable external events. Entropy measures the variety of configurations possible within a system, and recently the concept of brain entropy has been defined as the number of neural states a given brain can access. This study investigates the relationship between human intelligence and brain entropy, to determine whether neural variability as reflected in neuroimaging signals carries information about intellectual ability. We hypothesize that intelligence will be positively associated with entropy in a sample of 892 healthy adults, using resting-state fMRI. Intelligence is measured with the Shipley Vocabulary and WASI Matrix Reasoning tests. Brain entropy was positively associated with intelligence. This relation was most strongly observed in the prefrontal cortex, inferior temporal lobes, and cerebellum. This relationship between high brain entropy and high intelligence indicates an essential role for entropy in brain functioning. It demonstrates that access to variable neural states predicts complex behavioral performance, and specifically shows that entropy derived from neuroimaging signals at rest carries information about intellectual capacity. Future work in this area may elucidate the links between brain entropy in both resting and active states and various forms of intelligence. This insight has the potential to provide predictive information about adaptive behavior and to delineate the subdivisions and nature of intelligence based on entropic patterns. PMID:29432427

Brain entropy and human intelligence: A resting-state fMRI study.

Science.gov (United States)

Saxe, Glenn N; Calderone, Daniel; Morales, Leah J

2018-01-01

Human intelligence comprises comprehension of and reasoning about an infinitely variable external environment. A brain capable of large variability in neural configurations, or states, will more easily understand and predict variable external events. Entropy measures the variety of configurations possible within a system, and recently the concept of brain entropy has been defined as the number of neural states a given brain can access. This study investigates the relationship between human intelligence and brain entropy, to determine whether neural variability as reflected in neuroimaging signals carries information about intellectual ability. We hypothesize that intelligence will be positively associated with entropy in a sample of 892 healthy adults, using resting-state fMRI. Intelligence is measured with the Shipley Vocabulary and WASI Matrix Reasoning tests. Brain entropy was positively associated with intelligence. This relation was most strongly observed in the prefrontal cortex, inferior temporal lobes, and cerebellum. This relationship between high brain entropy and high intelligence indicates an essential role for entropy in brain functioning. It demonstrates that access to variable neural states predicts complex behavioral performance, and specifically shows that entropy derived from neuroimaging signals at rest carries information about intellectual capacity. Future work in this area may elucidate the links between brain entropy in both resting and active states and various forms of intelligence. This insight has the potential to provide predictive information about adaptive behavior and to delineate the subdivisions and nature of intelligence based on entropic patterns.

Test Review: Wechsler, D. (2014),"Wechsler Intelligence Scale for Children, Fifth Edition: Canadian 322 (WISC-V[superscript CDN])." Toronto, Ontario: Pearson Canada Assessment.

Science.gov (United States)

Cormier, Damien C.; Kennedy, Kathleen E.; Aquilina, Alexandra M.

2016-01-01

The Wechsler Intelligence Scale for Children, Fifth Edition: Canadian (WISC-V[superscript CDN]; Wechsler, 2014) is published by Pearson Canada Assessment. The WISC-V[superscript CDN] is a norm-referenced, individually administered intelligence battery that provides a comprehensive diagnostic profile of the cognitive strengths and weaknesses of…

Large-scale influences in near-wall turbulence.

Science.gov (United States)

Hutchins, Nicholas; Marusic, Ivan

2007-03-15

Hot-wire data acquired in a high Reynolds number facility are used to illustrate the need for adequate scale separation when considering the coherent structure in wall-bounded turbulence. It is found that a large-scale motion in the log region becomes increasingly comparable in energy to the near-wall cycle as the Reynolds number increases. Through decomposition of fluctuating velocity signals, it is shown that this large-scale motion has a distinct modulating influence on the small-scale energy (akin to amplitude modulation). Reassessment of DNS data, in light of these results, shows similar trends, with the rate and intensity of production due to the near-wall cycle subject to a modulating influence from the largest-scale motions.

Traditional Enterprise Business Intelligence Software Compared to Software as a Service Business Intelligence

Directory of Open Access Journals (Sweden)

Marian Pompiliu CRISTESCU

2016-01-01

Full Text Available The focus of this paper is on the one hand on the importance of business intelligence in large and medium-sized businesses and on the other side on the evaluation and implementation of Business Intelligence. It shows how companies make better and faster decisions regarding their customers, partners and operations by converting data into valuable business information. The paper describes how to bring business intelligence information, people and technology together to help to create a successful business strategy. The conclusion of the paper is the assessment of the possibility of business intelligence to develop projects in large and medium-sized companies and the discussion of the possible alternatives with respect to the different functions.

Validation and norming of the Intelligibility in Context Scale in Northern Viet Nam.

Science.gov (United States)

Phạm, Ben; McLeod, Sharynne; Harrison, Linda J

2017-01-01

Vietnamese is one of the 20 most commonly spoken languages in the world; however, there are no standardised tools to assess Vietnamese children's speech. This study aimed to validate and norm the Vietnamese version of the Intelligibility in Context Scale (ICS-VN). Data were collected from parents of 181 children (aged 2;0-5;11) living in Ha Noi, Northern Viet Nam. The mean ICS-VN score was 4.43 (out of a maximum of 5), indicating that children were 'usually' to 'always' intelligible; however, item-level scores demonstrated significant differences between communication partners. Children with parental concerns about speech and language had significantly lower mean scores than children without parental concerns. Scores also differed by children's age, parents' occupation and mothers' education level but not by sex of child or fathers' education level. The ICS-VN had good psychometric properties indicating it to be a valid tool for use with Vietnamese-speaking children in Northern Viet Nam.

Artificial intelligence in conceptual design of intelligent manufacturing systems: A state of the art review

OpenAIRE

Petrović, Milica M.; Miljković, Zoran Đ.; Babić, Bojan R.

2013-01-01

Intelligent manufacturing systems (IMS), as the highest class of flexible manufacturing systems, are able to adapt to market changes applying methods of artificial intelligence. This paper presents a detailed review of the following IMS functions: (i) process planning optimization, (ii) scheduling optimization, (iii) integrated process planning and scheduling, and (iv) mobile robot scheduling for internal material transport tasks. The research presented in this paper shows that improved perfo...

The Validity, Reliability and Factorial Structure of the Turkish Version of the Tromso Social Intelligence Scale

Science.gov (United States)

Dogan, Tayfun; Cetin, Bayram

2009-01-01

The purpose of the present study was to investigate the reliability and validity of the Turkish version of the Tromso Social Intelligence Scale (TSIS) developed by Silvera, Martinussen, and Dahl (2001). 719 students from Sakarya University participated in the study. Construct validity and criterion related validity and reliability were assessed.…

Large Scale Monte Carlo Simulation of Neutrino Interactions Using the Open Science Grid and Commercial Clouds

International Nuclear Information System (INIS)

Norman, A.; Boyd, J.; Davies, G.; Flumerfelt, E.; Herner, K.; Mayer, N.; Mhashilhar, P.; Tamsett, M.; Timm, S.

2015-01-01

Modern long baseline neutrino experiments like the NOvA experiment at Fermilab, require large scale, compute intensive simulations of their neutrino beam fluxes and backgrounds induced by cosmic rays. The amount of simulation required to keep the systematic uncertainties in the simulation from dominating the final physics results is often 10x to 100x that of the actual detector exposure. For the first physics results from NOvA this has meant the simulation of more than 2 billion cosmic ray events in the far detector and more than 200 million NuMI beam spill simulations. Performing these high statistics levels of simulation have been made possible for NOvA through the use of the Open Science Grid and through large scale runs on commercial clouds like Amazon EC2. We details the challenges in performing large scale simulation in these environments and how the computing infrastructure for the NOvA experiment has been adapted to seamlessly support the running of different simulation and data processing tasks on these resources. (paper)

PKI security in large-scale healthcare networks.

Science.gov (United States)

Mantas, Georgios; Lymberopoulos, Dimitrios; Komninos, Nikos

2012-06-01

During the past few years a lot of PKI (Public Key Infrastructures) infrastructures have been proposed for healthcare networks in order to ensure secure communication services and exchange of data among healthcare professionals. However, there is a plethora of challenges in these healthcare PKI infrastructures. Especially, there are a lot of challenges for PKI infrastructures deployed over large-scale healthcare networks. In this paper, we propose a PKI infrastructure to ensure security in a large-scale Internet-based healthcare network connecting a wide spectrum of healthcare units geographically distributed within a wide region. Furthermore, the proposed PKI infrastructure facilitates the trust issues that arise in a large-scale healthcare network including multi-domain PKI infrastructures.

SOCIO-PSYCHOLOGICAL ADAPTATION TO PROFESSIONAL ACTIVITY

Directory of Open Access Journals (Sweden)

V. Ivanov

2016-01-01

Full Text Available The article analyzes the factors of successful adaptation of employees to professional work in the new environment. Under the new conditions of professional development and employee having professional experience and young professional may encounter, with the presentation not only new professional requirements and tasks, but also new working conditions, the system of building relationships in the team, discovering with some discrepancies between obtained them in the learning process theoretical knowledge and skills available to the real practice of professional activities. At the level of interpersonal relations of the process of social cognition, is account of the special knowledge of the process of social facilities and construction of social reality, such an important parameter defi nes as "emotional intelligence" – construct is proposed for study in 1990 by American psychologists Peter Salovey and John Mayer. Initially, the concept of "emotional intelligence" was linked to the notion of social intelligence. The effectiveness of social and psychological adaptation to the professional activity can be enhanced through the development of emotional intelligence. Implementation of the basic functions of emotional intelligence improves communication efficiency, optimization of interpersonal relationships, social and psychological adaptation of personality.

Emotional intelligence and coronary atherosclerosis: exploratory study using the Trait Meta-Mood Scale

Directory of Open Access Journals (Sweden)

Mariana Suárez-Bagnasco

2013-12-01

Full Text Available Introduction There are no prior studies that assess emotional intelligence in asymptomatic adults with coronary atherosclerosis. Aim The purpose of this study is to explore associations between emotional intelligence in asymptomatic adults with and without coronary atherosclerotic lesions. Design and method Cross-sectional design. The sample consisted of 100 asymptomatic 30 to 80 year-old adults that met the inclusion and exclusion criteria and who underwent coronary multislice computed tomography. Coronary atherosclerosis was shown by 64-channel multislice computed tomography. Emotional intelligence was assessed by applying the Trait Meta-Mood Scale. Results The sample was composed of 73% men and 27% women. Fifty-one percent had coronary atherosclerotic lesions, 78% had scores below the reference values for both Clarity and Repair. Seventy-nine percent had scores above the reference values for Attention. Statistically significant associations were found between the presence of coronary atherosclerotic lesion and: a emotional attention, chi-square: 0.302, p=0.043, b emotional clarity, chi-square: -0.312, p=0.040, b emotional regulation, chi-square: -0.313, p=0.040. Conclusions: People with coronary atherosclerotic lesions showed an excessive tendency to focus on their own feelings and higher levels of rumination, together with lower ability to identify, distinguish and describe their emotions. Likewise, they have lower ability to reduce or eliminate negative emotions and to increase or maintain the intensity of positive emotions.

Emerging large-scale solar heating applications

International Nuclear Information System (INIS)

Wong, W.P.; McClung, J.L.

2009-01-01

Currently the market for solar heating applications in Canada is dominated by outdoor swimming pool heating, make-up air pre-heating and domestic water heating in homes, commercial and institutional buildings. All of these involve relatively small systems, except for a few air pre-heating systems on very large buildings. Together these applications make up well over 90% of the solar thermal collectors installed in Canada during 2007. These three applications, along with the recent re-emergence of large-scale concentrated solar thermal for generating electricity, also dominate the world markets. This paper examines some emerging markets for large scale solar heating applications, with a focus on the Canadian climate and market. (author)

Emerging large-scale solar heating applications

Energy Technology Data Exchange (ETDEWEB)

Wong, W.P.; McClung, J.L. [Science Applications International Corporation (SAIC Canada), Ottawa, Ontario (Canada)

2009-07-01

Currently the market for solar heating applications in Canada is dominated by outdoor swimming pool heating, make-up air pre-heating and domestic water heating in homes, commercial and institutional buildings. All of these involve relatively small systems, except for a few air pre-heating systems on very large buildings. Together these applications make up well over 90% of the solar thermal collectors installed in Canada during 2007. These three applications, along with the recent re-emergence of large-scale concentrated solar thermal for generating electricity, also dominate the world markets. This paper examines some emerging markets for large scale solar heating applications, with a focus on the Canadian climate and market. (author)

Efficacy of the SU(3) scheme for ab initio large-scale calculations beyond the lightest nuclei

Energy Technology Data Exchange (ETDEWEB)

Dytrych, T. [Academy of Sciences of the Czech Republic (ASCR), Prague (Czech Republic); Louisiana State Univ., Baton Rouge, LA (United States); Maris, Pieter [Iowa State Univ., Ames, IA (United States); Launey, K. D. [Louisiana State Univ., Baton Rouge, LA (United States); Draayer, J. P. [Louisiana State Univ., Baton Rouge, LA (United States); Vary, James [Iowa State Univ., Ames, IA (United States); Langr, D. [Czech Technical Univ., Prague (Czech Republic); Aerospace Research and Test Establishment, Prague (Czech Republic); Saule, E. [Univ. of North Carolina, Charlotte, NC (United States); Caprio, M. A. [Univ. of Notre Dame, IN (United States); Catalyurek, U. [The Ohio State Univ., Columbus, OH (United States). Dept. of Electrical and Computer Engineering; Sosonkina, M. [Old Dominion Univ., Norfolk, VA (United States)

2016-06-09

We report on the computational characteristics of ab initio nuclear structure calculations in a symmetry-adapted no-core shell model (SA-NCSM) framework. We examine the computational complexity of the current implementation of the SA-NCSM approach, dubbed LSU3shell, by analyzing ab initio results for ⁶Li and ¹²C in large harmonic oscillator model spaces and SU(3)-selected subspaces. We demonstrate LSU3shell's strong-scaling properties achieved with highly-parallel methods for computing the many-body matrix elements. Results compare favorably with complete model space calculations and signi cant memory savings are achieved in physically important applications. In particular, a well-chosen symmetry-adapted basis a ords memory savings in calculations of states with a fixed total angular momentum in large model spaces while exactly preserving translational invariance.

Advanced intelligent computational technologies and decision support systems

CERN Document Server

Kountchev, Roumen

2014-01-01

This book offers a state of the art collection covering themes related to Advanced Intelligent Computational Technologies and Decision Support Systems which can be applied to fields like healthcare assisting the humans in solving problems. The book brings forward a wealth of ideas, algorithms and case studies in themes like: intelligent predictive diagnosis; intelligent analyzing of medical images; new format for coding of single and sequences of medical images; Medical Decision Support Systems; diagnosis of Down’s syndrome; computational perspectives for electronic fetal monitoring; efficient compression of CT Images; adaptive interpolation and halftoning for medical images; applications of artificial neural networks for real-life problems solving; present and perspectives for Electronic Healthcare Record Systems; adaptive approaches for noise reduction in sequences of CT images etc.

Increased Specificity of Wechsler Adult Intelligence Scale-Third Edition Matrix Reasoning Test Instructions and Time Limits

Science.gov (United States)

Callens, Andy M.; Atchison, Timothy B.; Engler, Rachel R.

2009-01-01

Instructions for the Matrix Reasoning Test (MRT) of the Wechsler Adult Intelligence Scale-Third Edition were modified by explicitly stating that the subtest was untimed or that a per-item time limit would be imposed. The MRT was administered within one of four conditions: with (a) standard administration instructions, (b) explicit instructions…

Prediction of monthly rainfall on homogeneous monsoon regions of India based on large scale circulation patterns using Genetic Programming

Science.gov (United States)

Kashid, Satishkumar S.; Maity, Rajib

2012-08-01

SummaryPrediction of Indian Summer Monsoon Rainfall (ISMR) is of vital importance for Indian economy, and it has been remained a great challenge for hydro-meteorologists due to inherent complexities in the climatic systems. The Large-scale atmospheric circulation patterns from tropical Pacific Ocean (ENSO) and those from tropical Indian Ocean (EQUINOO) are established to influence the Indian Summer Monsoon Rainfall. The information of these two large scale atmospheric circulation patterns in terms of their indices is used to model the complex relationship between Indian Summer Monsoon Rainfall and the ENSO as well as EQUINOO indices. However, extracting the signal from such large-scale indices for modeling such complex systems is significantly difficult. Rainfall predictions have been done for 'All India' as one unit, as well as for five 'homogeneous monsoon regions of India', defined by Indian Institute of Tropical Meteorology. Recent 'Artificial Intelligence' tool 'Genetic Programming' (GP) has been employed for modeling such problem. The Genetic Programming approach is found to capture the complex relationship between the monthly Indian Summer Monsoon Rainfall and large scale atmospheric circulation pattern indices - ENSO and EQUINOO. Research findings of this study indicate that GP-derived monthly rainfall forecasting models, that use large-scale atmospheric circulation information are successful in prediction of All India Summer Monsoon Rainfall with correlation coefficient as good as 0.866, which may appears attractive for such a complex system. A separate analysis is carried out for All India Summer Monsoon rainfall for India as one unit, and five homogeneous monsoon regions, based on ENSO and EQUINOO indices of months of March, April and May only, performed at end of month of May. In this case, All India Summer Monsoon Rainfall could be predicted with 0.70 as correlation coefficient with somewhat lesser Correlation Coefficient (C.C.) values for different

Artificial intelligence in diagnosis of obstructive lung disease: current status and future potential.

Science.gov (United States)

Das, Nilakash; Topalovic, Marko; Janssens, Wim

2018-03-01

The application of artificial intelligence in the diagnosis of obstructive lung diseases is an exciting phenomenon. Artificial intelligence algorithms work by finding patterns in data obtained from diagnostic tests, which can be used to predict clinical outcomes or to detect obstructive phenotypes. The purpose of this review is to describe the latest trends and to discuss the future potential of artificial intelligence in the diagnosis of obstructive lung diseases. Machine learning has been successfully used in automated interpretation of pulmonary function tests for differential diagnosis of obstructive lung diseases. Deep learning models such as convolutional neural network are state-of-the art for obstructive pattern recognition in computed tomography. Machine learning has also been applied in other diagnostic approaches such as forced oscillation test, breath analysis, lung sound analysis and telemedicine with promising results in small-scale studies. Overall, the application of artificial intelligence has produced encouraging results in the diagnosis of obstructive lung diseases. However, large-scale studies are still required to validate current findings and to boost its adoption by the medical community.

Large-scale regions of antimatter

International Nuclear Information System (INIS)

Grobov, A. V.; Rubin, S. G.

2015-01-01

Amodified mechanism of the formation of large-scale antimatter regions is proposed. Antimatter appears owing to fluctuations of a complex scalar field that carries a baryon charge in the inflation era

Large-scale regions of antimatter

Energy Technology Data Exchange (ETDEWEB)

Grobov, A. V., E-mail: alexey.grobov@gmail.com; Rubin, S. G., E-mail: sgrubin@mephi.ru [National Research Nuclear University MEPhI (Russian Federation)

2015-07-15

Amodified mechanism of the formation of large-scale antimatter regions is proposed. Antimatter appears owing to fluctuations of a complex scalar field that carries a baryon charge in the inflation era.

The National Adult Reading Test: restandardisation against the Wechsler Adult Intelligence Scale-Fourth edition.

Science.gov (United States)

Bright, Peter; Hale, Emily; Gooch, Vikki Jayne; Myhill, Thomas; van der Linde, Ian

2018-09-01

Since publication in 1982, the 50-item National Adult Reading Test (NART; Nelson, 1982; NART-R; Nelson & Willison, 1991) has remained a widely adopted method for estimating premorbid intelligence both for clinical and research purposes. However, the NART has not been standardised against the most recent revisions of the Wechsler Adult Intelligence Scale (WAIS-III; Wechsler, 1997, and WAIS-IV; Wechsler, 2008). Our objective, therefore, was to produce reliable standardised estimates of WAIS-IV IQ from the NART. Ninety-two neurologically healthy British adults were assessed and regression equations calculated to produce population estimates of WAIS-IV full-scale IQ (FSIQ) and constituent index scores. Results showed strong NART/WAIS-IV FSIQ correlations with more moderate correlations observed between NART error and constituent index scores. FSIQ estimates were closely similar to the published WAIS and WAIS-R estimates at the high end of the distribution, but at the lower end were approximately equidistant from the highly discrepant WAIS (low) and WAIS-R (high) values. We conclude that the NART is likely to remain an important tool for estimating the impact of neurological damage on general cognitive ability. We advise caution in the use of older published WAIS and/or WAIS-R estimates for estimating premorbid WAIS-IV FSIQ, particularly for those with low NART scores.

Estimating premorbid general cognitive functioning for children and adolescents using the American Wechsler Intelligence Scale for Children-Fourth Edition: demographic and current performance approaches.

Science.gov (United States)

Schoenberg, Mike R; Lange, Rael T; Brickell, Tracey A; Saklofske, Donald H

2007-04-01

Neuropsychologic evaluation requires current test performance be contrasted against a comparison standard to determine if change has occurred. An estimate of premorbid intelligence quotient (IQ) is often used as a comparison standard. The Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) is a commonly used intelligence test. However, there is no method to estimate premorbid IQ for the WISC-IV, limiting the test's utility for neuropsychologic assessment. This study develops algorithms to estimate premorbid Full Scale IQ scores. Participants were the American WISC-IV standardization sample (N = 2172). The sample was randomly divided into 2 groups (development and validation). The development group was used to generate 12 algorithms. These algorithms were accurate predictors of WISC-IV Full Scale IQ scores in healthy children and adolescents. These algorithms hold promise as a method to predict premorbid IQ for patients with known or suspected neurologic dysfunction; however, clinical validation is required.

[Comparing Two Editions of Wechsler Intelligence Scales and Assessing Reading Skills in Children with Attention Deficit and Hyperactivity Disorder].

Science.gov (United States)

Çelik, Cihat; Erden, Gülsen; Özmen, Sevim; Tural Hesapçıoğlu, Selma

2017-01-01

This study aimed to examine the cognitive profiles of children with Attention Deficit and Hyperactivity Disorder (ADHD) with the Wechsler Intelligence Scales for Children-Revised (WISC-R) and the Wechsler Intelligence Scales for Children-Fourth Edition (WISC-IV), the latter of which was recently standardized in Turkey. In addition, the reading abilities and intelligence scores of these children were also investigated. A total of 48 children with ADHD between the ages of 6 and 16 years who were outpatients in Muş State Hospital were included in this study. The children were administered the WISC-R, the WISC-IV, and the Oral Reading Skills and Reading Comprehension Test (ORCT). There were no significant differences between the WISC-R IQ scores and WISC-IV index scores. Moreover, reading comprehension skills (derived from ORCT scores) were predicted with significant accuracy by both the WISC-R Verbal IQ and the WISC-IV WMI (Working Memory Index). Results of this study suggest that the WISC-R and the WISC-IV scale are not sufficient for obtaining a specific cognitive profile for ADHD - there is no significant difference between them. However, the four-factor structure of the WISC-IV is believed to provide more specific information. In addition, results of this study related to reading skills indicate that the importance of reading skills should not be overlooked when assessing children with ADHD.

Large-Scale Analysis of Art Proportions

DEFF Research Database (Denmark)

Jensen, Karl Kristoffer

2014-01-01

While literature often tries to impute mathematical constants into art, this large-scale study (11 databases of paintings and photos, around 200.000 items) shows a different truth. The analysis, consisting of the width/height proportions, shows a value of rarely if ever one (square) and with majo......While literature often tries to impute mathematical constants into art, this large-scale study (11 databases of paintings and photos, around 200.000 items) shows a different truth. The analysis, consisting of the width/height proportions, shows a value of rarely if ever one (square...

The Expanded Large Scale Gap Test

Science.gov (United States)

1987-03-01

NSWC TR 86-32 DTIC THE EXPANDED LARGE SCALE GAP TEST BY T. P. LIDDIARD D. PRICE RESEARCH AND TECHNOLOGY DEPARTMENT ’ ~MARCH 1987 Ap~proved for public...arises, to reduce the spread in the LSGT 50% gap value.) The worst charges, such as those with the highest or lowest densities, the largest re-pressed...Arlington, VA 22217 PE 62314N INS3A 1 RJ14E31 7R4TBK 11 TITLE (Include Security CIlmsilficatiorn The Expanded Large Scale Gap Test . 12. PEIRSONAL AUTHOR() T

Intelligence for embedded systems a methodological approach

CERN Document Server

Alippi, Cesare

2014-01-01

Addressing current issues of which any engineer or computer scientist should be aware, this monograph is a response to the need to adopt a new computational paradigm as the methodological basis for designing pervasive embedded systems with sensor capabilities. The requirements of this paradigm are to control complexity, to limit cost and energy consumption, and to provide adaptation and cognition abilities allowing the embedded system to interact proactively with the real world. The quest for such intelligence requires the formalization of a new generation of intelligent systems able to exploit advances in digital architectures and in sensing technologies. The book sheds light on the theory behind intelligence for embedded systems with specific focus on: ·        robustness (the robustness of a computational flow and its evaluation); ·        intelligence (how to mimic the adaptation and cognition abilities of the human brain), ·        the capacity to learn in non-stationary and evolv...

Advances in Intelligent Modelling and Simulation Artificial Intelligence-Based Models and Techniques in Scalable Computing

CERN Document Server

Khan, Samee; Burczy´nski, Tadeusz

2012-01-01

One of the most challenging issues in today’s large-scale computational modeling and design is to effectively manage the complex distributed environments, such as computational clouds, grids, ad hoc, and P2P networks operating under  various  types of users with evolving relationships fraught with  uncertainties. In this context, the IT resources and services usually belong to different owners (institutions, enterprises, or individuals) and are managed by different administrators. Moreover, uncertainties are presented to the system at hand in various forms of information that are incomplete, imprecise, fragmentary, or overloading, which hinders in the full and precise resolve of the evaluation criteria, subsequencing and selection, and the assignment scores. Intelligent scalable systems enable the flexible routing and charging, advanced user interactions and the aggregation and sharing of geographically-distributed resources in modern large-scale systems.   This book presents new ideas, theories, models...

Large scale and big data processing and management

CERN Document Server

Sakr, Sherif

2014-01-01

Large Scale and Big Data: Processing and Management provides readers with a central source of reference on the data management techniques currently available for large-scale data processing. Presenting chapters written by leading researchers, academics, and practitioners, it addresses the fundamental challenges associated with Big Data processing tools and techniques across a range of computing environments.The book begins by discussing the basic concepts and tools of large-scale Big Data processing and cloud computing. It also provides an overview of different programming models and cloud-bas

Crowd-Sourced Intelligence Agency: Prototyping counterveillance

Directory of Open Access Journals (Sweden)

Jennifer Gradecki

2017-02-01

Full Text Available This paper discusses how an interactive artwork, the Crowd-Sourced Intelligence Agency (CSIA, can contribute to discussions of Big Data intelligence analytics. The CSIA is a publicly accessible Open Source Intelligence (OSINT system that was constructed using information gathered from technical manuals, research reports, academic papers, leaked documents, and Freedom of Information Act files. Using a visceral heuristic, the CSIA demonstrates how the statistical correlations made by automated classification systems are different from human judgment and can produce false-positives, as well as how the display of information through an interface can affect the judgment of an intelligence agent. The public has the right to ask questions about how a computer program determines if they are a threat to national security and to question the practicality of using statistical pattern recognition algorithms in place of human judgment. Currently, the public’s lack of access to both Big Data and the actual datasets intelligence agencies use to train their classification algorithms keeps the possibility of performing effective sous-dataveillance out of reach. Without this data, the results returned by the CSIA will not be identical to those of intelligence agencies. Because we have replicated how OSINT is processed, however, our results will resemble the type of results and mistakes made by OSINT systems. The CSIA takes some initial steps toward contributing to an informed public debate about large-scale monitoring of open source, social media data and provides a prototype for counterveillance and sousveillance tools for citizens.

Large scale cluster computing workshop

International Nuclear Information System (INIS)

Dane Skow; Alan Silverman

2002-01-01

Recent revolutions in computer hardware and software technologies have paved the way for the large-scale deployment of clusters of commodity computers to address problems heretofore the domain of tightly coupled SMP processors. Near term projects within High Energy Physics and other computing communities will deploy clusters of scale 1000s of processors and be used by 100s to 1000s of independent users. This will expand the reach in both dimensions by an order of magnitude from the current successful production facilities. The goals of this workshop were: (1) to determine what tools exist which can scale up to the cluster sizes foreseen for the next generation of HENP experiments (several thousand nodes) and by implication to identify areas where some investment of money or effort is likely to be needed. (2) To compare and record experimences gained with such tools. (3) To produce a practical guide to all stages of planning, installing, building and operating a large computing cluster in HENP. (4) To identify and connect groups with similar interest within HENP and the larger clustering community

Towards a Scalable and Adaptive Application Support Platform for Large-Scale Distributed E-Sciences in High-Performance Network Environments

Energy Technology Data Exchange (ETDEWEB)

Wu, Chase Qishi [New Jersey Inst. of Technology, Newark, NJ (United States); Univ. of Memphis, TN (United States); Zhu, Michelle Mengxia [Southern Illinois Univ., Carbondale, IL (United States)

2016-06-06

The advent of large-scale collaborative scientific applications has demonstrated the potential for broad scientific communities to pool globally distributed resources to produce unprecedented data acquisition, movement, and analysis. System resources including supercomputers, data repositories, computing facilities, network infrastructures, storage systems, and display devices have been increasingly deployed at national laboratories and academic institutes. These resources are typically shared by large communities of users over Internet or dedicated networks and hence exhibit an inherent dynamic nature in their availability, accessibility, capacity, and stability. Scientific applications using either experimental facilities or computation-based simulations with various physical, chemical, climatic, and biological models feature diverse scientific workflows as simple as linear pipelines or as complex as a directed acyclic graphs, which must be executed and supported over wide-area networks with massively distributed resources. Application users oftentimes need to manually configure their computing tasks over networks in an ad hoc manner, hence significantly limiting the productivity of scientists and constraining the utilization of resources. The success of these large-scale distributed applications requires a highly adaptive and massively scalable workflow platform that provides automated and optimized computing and networking services. This project is to design and develop a generic Scientific Workflow Automation and Management Platform (SWAMP), which contains a web-based user interface specially tailored for a target application, a set of user libraries, and several easy-to-use computing and networking toolkits for application scientists to conveniently assemble, execute, monitor, and control complex computing workflows in heterogeneous high-performance network environments. SWAMP will enable the automation and management of the entire process of scientific

Flight Test Results from the NF-15B Intelligent Flight Control System (IFCS) Project with Adaptation to a Simulated Stabilator Failure

Science.gov (United States)

Bosworth, John T.; Williams-Hayes, Peggy S.

2010-01-01

Adaptive flight control systems have the potential to be more resilient to extreme changes in airplane behavior. Extreme changes could be a result of a system failure or of damage to the airplane. A direct adaptive neural-network-based flight control system was developed for the National Aeronautics and Space Administration NF-15B Intelligent Flight Control System airplane and subjected to an inflight simulation of a failed (frozen) (unmovable) stabilator. Formation flight handling qualities evaluations were performed with and without neural network adaptation. The results of these flight tests are presented. Comparison with simulation predictions and analysis of the performance of the adaptation system are discussed. The performance of the adaptation system is assessed in terms of its ability to decouple the roll and pitch response and reestablish good onboard model tracking. Flight evaluation with the simulated stabilator failure and adaptation engaged showed that there was generally improvement in the pitch response; however, a tendency for roll pilot-induced oscillation was experienced. A detailed discussion of the cause of the mixed results is presented.

Large-Scale Agriculture and Outgrower Schemes in Ethiopia

DEFF Research Database (Denmark)

Wendimu, Mengistu Assefa

, the impact of large-scale agriculture and outgrower schemes on productivity, household welfare and wages in developing countries is highly contentious. Chapter 1 of this thesis provides an introduction to the study, while also reviewing the key debate in the contemporary land ‘grabbing’ and historical large...... sugarcane outgrower scheme on household income and asset stocks. Chapter 5 examines the wages and working conditions in ‘formal’ large-scale and ‘informal’ small-scale irrigated agriculture. The results in Chapter 2 show that moisture stress, the use of untested planting materials, and conflict over land...... commands a higher wage than ‘formal’ large-scale agriculture, while rather different wage determination mechanisms exist in the two sectors. Human capital characteristics (education and experience) partly explain the differences in wages within the formal sector, but play no significant role...

Adaptation of Vanderbilt Attention Deficit Hyperactivity Disorder Diagnostic Parent Scale in Turkish

Directory of Open Access Journals (Sweden)

Tüba KÜÇÜK DOĞAROĞLU

2013-12-01

Full Text Available The purpose of this study is to adaptation of Vanderbilt Attention Deficit and Hyperactivity Disorder Diagnostic Parent Rating Scale (Vanderbilt ADHD PRS to Turkish. This study was done 343 mother whose children with DEHB and 7 – 9 years old. Gender of mothers’ children is 132 girls and 211 boys. Age of children is that 82 children are 7 years old, 141 children are 8 years old and 120 children are 9 years old. Datas are gathering by Vanderbilt ADHD PRS and data form. Validity and reliability of scale was examined exploratory factor analysis and Cronbach Alpha. Results reveal that adaptation of Vanderbilt ADHD PRS to Turkish included 45 items which had 4 factors (inattention / hyperactivity / oppositional and conduct disorder / depression – anxiety. Results indicated that adaptation of Vanderbilt ADHD PRS to Turkish is valid and reliable scale

Diagnosis of Short-Circuit Fault in Large-Scale Permanent-Magnet Wind Power Generator Based on CMAC

Directory of Open Access Journals (Sweden)

Chin-Tsung Hsieh

2013-01-01

Full Text Available This study proposes a method based on the cerebellar model arithmetic controller (CMAC for fault diagnosis of large-scale permanent-magnet wind power generators and compares the results with Error Back Propagation (EBP. The diagnosis is based on the short-circuit faults in permanent-magnet wind power generators, magnetic field change, and temperature change. Since CMAC is characterized by inductive ability, associative ability, quick response, and similar input signals exciting similar memories, it has an excellent effect as an intelligent fault diagnosis implement. The experimental results suggest that faults can be diagnosed effectively after only training CMAC 10 times. In comparison to training 151 times for EBP, CMAC is better than EBP in terms of training speed.

Efficient Computation of Sparse Matrix Functions for Large-Scale Electronic Structure Calculations: The CheSS Library.

Science.gov (United States)

Mohr, Stephan; Dawson, William; Wagner, Michael; Caliste, Damien; Nakajima, Takahito; Genovese, Luigi

2017-10-10

We present CheSS, the "Chebyshev Sparse Solvers" library, which has been designed to solve typical problems arising in large-scale electronic structure calculations using localized basis sets. The library is based on a flexible and efficient expansion in terms of Chebyshev polynomials and presently features the calculation of the density matrix, the calculation of matrix powers for arbitrary powers, and the extraction of eigenvalues in a selected interval. CheSS is able to exploit the sparsity of the matrices and scales linearly with respect to the number of nonzero entries, making it well-suited for large-scale calculations. The approach is particularly adapted for setups leading to small spectral widths of the involved matrices and outperforms alternative methods in this regime. By coupling CheSS to the DFT code BigDFT, we show that such a favorable setup is indeed possible in practice. In addition, the approach based on Chebyshev polynomials can be massively parallelized, and CheSS exhibits excellent scaling up to thousands of cores even for relatively small matrix sizes.

Associations between emotional intelligence, depression and suicide risk in nursing students.

Science.gov (United States)

Aradilla-Herrero, Amor; Tomás-Sábado, Joaquín; Gómez-Benito, Juana

2014-04-01

The most important factor which predisposes young people to suicide is depression, although protective factors such as self-esteem, emotional adaptation and social support may reduce the probability of suicidal ideation and suicide attempts. Several studies have indicated an elevated risk of suicide for health-related professions. Little is known, however, about the relationship between perceived emotional intelligence and suicide risk among nursing students. The main goals were to determine the prevalence of suicide risk in a sample of nursing students, to examine the relationship between suicide risk and perceived emotional intelligence, depression, trait anxiety and self-esteem, and to identify any gender differences in relation to these variables. Cross-sectional study of nursing students (n=93) who completed self-report measures of perceived emotional intelligence (Trait Meta-Mood Scale, which evaluates three dimensions: emotional attention, clarity and repair), suicide risk (Plutchik Suicide Risk Scale), self-esteem (Rosenberg Self-esteem Scale), depression (Zung Self-Rating Depression Scale) and anxiety (Trait scale of the State-Trait Anxiety Inventory). Linear regression analysis confirmed that depression and emotional attention are significant predictors of suicidal ideation. Moreover, suicide risk showed a significant negative association with self-esteem and with emotional clarity and repair. Gender differences were only observed in relation to depression, on which women scored significantly higher. Overall, 14% of the students were considered to present a substantial suicide risk. The findings suggest that interventions to prevent suicidal ideation among nursing students should include strategies to detect mood disorders (especially depression) and to improve emotional coping skills. In line with previous research the results indicate that high scores on emotional attention are linked to heightened emotional susceptibility and an increased risk of

Climate change adaptation strategies by small-scale farmers in ...

African Journals Online (AJOL)

Mburu

SPSS) ... were financial constraints (93.4%), lack of relevant skills (74.5%) and lack of ... Key words: Climate change, small-scale farmers, adaptation strategies. ... investment in irrigation infrastructure, high post-harvest ..... 72.0 School drop out.

Economically viable large-scale hydrogen liquefaction

Science.gov (United States)

Cardella, U.; Decker, L.; Klein, H.

2017-02-01

The liquid hydrogen demand, particularly driven by clean energy applications, will rise in the near future. As industrial large scale liquefiers will play a major role within the hydrogen supply chain, production capacity will have to increase by a multiple of today’s typical sizes. The main goal is to reduce the total cost of ownership for these plants by increasing energy efficiency with innovative and simple process designs, optimized in capital expenditure. New concepts must ensure a manageable plant complexity and flexible operability. In the phase of process development and selection, a dimensioning of key equipment for large scale liquefiers, such as turbines and compressors as well as heat exchangers, must be performed iteratively to ensure technological feasibility and maturity. Further critical aspects related to hydrogen liquefaction, e.g. fluid properties, ortho-para hydrogen conversion, and coldbox configuration, must be analysed in detail. This paper provides an overview on the approach, challenges and preliminary results in the development of efficient as well as economically viable concepts for large-scale hydrogen liquefaction.

Diversification and intensification of agricultural adaptation from global to local scales.

Directory of Open Access Journals (Sweden)

Minjie Chen

Full Text Available Smallholder farming systems are vulnerable to a number of challenges, including continued population growth, urbanization, income disparities, land degradation, decreasing farm size and productivity, all of which are compounded by uncertainty of climatic patterns. Understanding determinants of smallholder farming practices is critical for designing and implementing successful interventions, including climate change adaptation programs. We examine two dimensions wherein smallholder farmers may adapt agricultural practices; through intensification (i.e., adopt more practices or diversification (i.e. adopt different practices. We use data on 5314 randomly sampled households located in 38 sites in 15 countries across four regions (East and West Africa, South Asia, and Central America. We estimate empirical models designed to assess determinants of both intensification and diversification of adaptation activities at global scales. Aspects of adaptive capacity that are found to increase intensification of adaptation globally include variables associated with access to information and human capital, financial considerations, assets, household infrastructure and experience. In contrast, there are few global drivers of adaptive diversification, with a notable exception being access to weather information, which also increases adaptive intensification. Investigating reasons for adaptation indicate that conditions present in underdeveloped markets provide the primary impetus for adaptation, even in the context of climate change. We also compare determinants across spatial scales, which reveals a variety of local avenues through which policy interventions can relax economic constraints and boost agricultural adaptation for both intensification and diversification. For example, access to weather information does not affect intensification adaptation in Africa, but is significant at several sites in Bangladesh and India. Moreover, this information leads to

Diversification and intensification of agricultural adaptation from global to local scales

Science.gov (United States)

Chen, Minjie; Wichmann, Bruno; Luckert, Marty; Winowiecki, Leigh; Förch, Wiebke

2018-01-01

Smallholder farming systems are vulnerable to a number of challenges, including continued population growth, urbanization, income disparities, land degradation, decreasing farm size and productivity, all of which are compounded by uncertainty of climatic patterns. Understanding determinants of smallholder farming practices is critical for designing and implementing successful interventions, including climate change adaptation programs. We examine two dimensions wherein smallholder farmers may adapt agricultural practices; through intensification (i.e., adopt more practices) or diversification (i.e. adopt different practices). We use data on 5314 randomly sampled households located in 38 sites in 15 countries across four regions (East and West Africa, South Asia, and Central America). We estimate empirical models designed to assess determinants of both intensification and diversification of adaptation activities at global scales. Aspects of adaptive capacity that are found to increase intensification of adaptation globally include variables associated with access to information and human capital, financial considerations, assets, household infrastructure and experience. In contrast, there are few global drivers of adaptive diversification, with a notable exception being access to weather information, which also increases adaptive intensification. Investigating reasons for adaptation indicate that conditions present in underdeveloped markets provide the primary impetus for adaptation, even in the context of climate change. We also compare determinants across spatial scales, which reveals a variety of local avenues through which policy interventions can relax economic constraints and boost agricultural adaptation for both intensification and diversification. For example, access to weather information does not affect intensification adaptation in Africa, but is significant at several sites in Bangladesh and India. Moreover, this information leads to diversification of

Large scale chromatographic separations using continuous displacement chromatography (CDC)

International Nuclear Information System (INIS)

Taniguchi, V.T.; Doty, A.W.; Byers, C.H.

1988-01-01

A process for large scale chromatographic separations using a continuous chromatography technique is described. The process combines the advantages of large scale batch fixed column displacement chromatography with conventional analytical or elution continuous annular chromatography (CAC) to enable large scale displacement chromatography to be performed on a continuous basis (CDC). Such large scale, continuous displacement chromatography separations have not been reported in the literature. The process is demonstrated with the ion exchange separation of a binary lanthanide (Nd/Pr) mixture. The process is, however, applicable to any displacement chromatography separation that can be performed using conventional batch, fixed column chromatography

Advanced Artificial Intelligence Technology Testbed

Science.gov (United States)

Anken, Craig S.

1993-01-01

The Advanced Artificial Intelligence Technology Testbed (AAITT) is a laboratory testbed for the design, analysis, integration, evaluation, and exercising of large-scale, complex, software systems, composed of both knowledge-based and conventional components. The AAITT assists its users in the following ways: configuring various problem-solving application suites; observing and measuring the behavior of these applications and the interactions between their constituent modules; gathering and analyzing statistics about the occurrence of key events; and flexibly and quickly altering the interaction of modules within the applications for further study.

Large Scale Processes and Extreme Floods in Brazil

Science.gov (United States)

Ribeiro Lima, C. H.; AghaKouchak, A.; Lall, U.

2016-12-01

Persistent large scale anomalies in the atmospheric circulation and ocean state have been associated with heavy rainfall and extreme floods in water basins of different sizes across the world. Such studies have emerged in the last years as a new tool to improve the traditional, stationary based approach in flood frequency analysis and flood prediction. Here we seek to advance previous studies by evaluating the dominance of large scale processes (e.g. atmospheric rivers/moisture transport) over local processes (e.g. local convection) in producing floods. We consider flood-prone regions in Brazil as case studies and the role of large scale climate processes in generating extreme floods in such regions is explored by means of observed streamflow, reanalysis data and machine learning methods. The dynamics of the large scale atmospheric circulation in the days prior to the flood events are evaluated based on the vertically integrated moisture flux and its divergence field, which are interpreted in a low-dimensional space as obtained by machine learning techniques, particularly supervised kernel principal component analysis. In such reduced dimensional space, clusters are obtained in order to better understand the role of regional moisture recycling or teleconnected moisture in producing floods of a given magnitude. The convective available potential energy (CAPE) is also used as a measure of local convection activities. We investigate for individual sites the exceedance probability in which large scale atmospheric fluxes dominate the flood process. Finally, we analyze regional patterns of floods and how the scaling law of floods with drainage area responds to changes in the climate forcing mechanisms (e.g. local vs large scale).

HD-MTL: Hierarchical Deep Multi-Task Learning for Large-Scale Visual Recognition.

Science.gov (United States)

Fan, Jianping; Zhao, Tianyi; Kuang, Zhenzhong; Zheng, Yu; Zhang, Ji; Yu, Jun; Peng, Jinye

2017-02-09

In this paper, a hierarchical deep multi-task learning (HD-MTL) algorithm is developed to support large-scale visual recognition (e.g., recognizing thousands or even tens of thousands of atomic object classes automatically). First, multiple sets of multi-level deep features are extracted from different layers of deep convolutional neural networks (deep CNNs), and they are used to achieve more effective accomplishment of the coarseto- fine tasks for hierarchical visual recognition. A visual tree is then learned by assigning the visually-similar atomic object classes with similar learning complexities into the same group, which can provide a good environment for determining the interrelated learning tasks automatically. By leveraging the inter-task relatedness (inter-class similarities) to learn more discriminative group-specific deep representations, our deep multi-task learning algorithm can train more discriminative node classifiers for distinguishing the visually-similar atomic object classes effectively. Our hierarchical deep multi-task learning (HD-MTL) algorithm can integrate two discriminative regularization terms to control the inter-level error propagation effectively, and it can provide an end-to-end approach for jointly learning more representative deep CNNs (for image representation) and more discriminative tree classifier (for large-scale visual recognition) and updating them simultaneously. Our incremental deep learning algorithms can effectively adapt both the deep CNNs and the tree classifier to the new training images and the new object classes. Our experimental results have demonstrated that our HD-MTL algorithm can achieve very competitive results on improving the accuracy rates for large-scale visual recognition.

Computing in Large-Scale Dynamic Systems

NARCIS (Netherlands)

Pruteanu, A.S.

2013-01-01

Software applications developed for large-scale systems have always been difficult to de- velop due to problems caused by the large number of computing devices involved. Above a certain network size (roughly one hundred), necessary services such as code updating, topol- ogy discovery and data

Fires in large scale ventilation systems

International Nuclear Information System (INIS)

Gregory, W.S.; Martin, R.A.; White, B.W.; Nichols, B.D.; Smith, P.R.; Leslie, I.H.; Fenton, D.L.; Gunaji, M.V.; Blythe, J.P.

1991-01-01

This paper summarizes the experience gained simulating fires in large scale ventilation systems patterned after ventilation systems found in nuclear fuel cycle facilities. The series of experiments discussed included: (1) combustion aerosol loading of 0.61x0.61 m HEPA filters with the combustion products of two organic fuels, polystyrene and polymethylemethacrylate; (2) gas dynamic and heat transport through a large scale ventilation system consisting of a 0.61x0.61 m duct 90 m in length, with dampers, HEPA filters, blowers, etc.; (3) gas dynamic and simultaneous transport of heat and solid particulate (consisting of glass beads with a mean aerodynamic diameter of 10μ) through the large scale ventilation system; and (4) the transport of heat and soot, generated by kerosene pool fires, through the large scale ventilation system. The FIRAC computer code, designed to predict fire-induced transients in nuclear fuel cycle facility ventilation systems, was used to predict the results of experiments (2) through (4). In general, the results of the predictions were satisfactory. The code predictions for the gas dynamics, heat transport, and particulate transport and deposition were within 10% of the experimentally measured values. However, the code was less successful in predicting the amount of soot generation from kerosene pool fires, probably due to the fire module of the code being a one-dimensional zone model. The experiments revealed a complicated three-dimensional combustion pattern within the fire room of the ventilation system. Further refinement of the fire module within FIRAC is needed. (orig.)

Energetic benefits and adaptations in mammalian limbs: Scale effects and selective pressures.

Science.gov (United States)

Kilbourne, Brandon M; Hoffman, Louwrens C

2015-06-01

Differences in limb size and shape are fundamental to mammalian morphological diversity; however, their relevance to locomotor costs has long been subject to debate. In particular, it remains unknown if scale effects in whole limb morphology could partially underlie decreasing mass-specific locomotor costs with increasing limb length. Whole fore- and hindlimb inertial properties reflecting limb size and shape-moment of inertia (MOI), mass, mass distribution, and natural frequency-were regressed against limb length for 44 species of quadrupedal mammals. Limb mass, MOI, and center of mass position are negatively allometric, having a strong potential for lowering mass-specific locomotor costs in large terrestrial mammals. Negative allometry of limb MOI results in a 40% reduction in MOI relative to isometry's prediction for our largest sampled taxa. However, fitting regression residuals to adaptive diversification models reveals that codiversification of limb mass, limb length, and body mass likely results from selection for differing locomotor modes of running, climbing, digging, and swimming. The observed allometric scaling does not result from selection for energetically beneficial whole limb morphology with increasing size. Instead, our data suggest that it is a consequence of differing morphological adaptations and body size distributions among quadrupedal mammals, highlighting the role of differing limb functions in mammalian evolution. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

Leader emotional intelligence, transformational leadership, trust and team commitment: Testing a model within a team context

Directory of Open Access Journals (Sweden)

Anton F. Schlechter

2008-06-01

Full Text Available This exploratory study tested a model within a team context consisting of transformational-leadership behaviour, team-leader emotional intelligence, trust (both in the team leader and in the team members and team commitment. It was conducted within six manufacturing plants, with 25 teams participating. Of the 320 surveys distributed to these teams, 178 were received (which equals a 56% response rate. The surveys consisted of the multi-factor leadership questionnaire (MLQ, the Swinburne University emotional intelligence test (SUEIT, the organisational-commitment scale (OCS (adapted for team commitment and the workplace trust survey (WTS. The validity of these scales was established using exploratory factor analysis (EFA and confrmatory factor analysis (CFA. The Cronbach alpha was used to assess the reliability of the scales. The model was tested using structural equation modelling (SEM; an acceptable level of model ft was found. Signifcant positive relationships were further found among all the constructs. Such an integrated model has not been tested in a team context before and the positive fndings therefore add to existing teamwork literature. The fnding that transformational leadership and leader emotional intelligence are positively related to team commitment and trust further emphasises the importance of effective leadership behaviour in team dynamics and performance.

SAP Business Intelligence: Migración de COGNOS a SAP

OpenAIRE

Legorburu Cladera, Iñigo

2013-01-01

El objetivo del proyecto consiste en la migración de la herramienta de Business Intelligence de COGNOS a una nueva solución de Business Intelligence, que reduzca los costes y se adapte a las necesidades de la empresa. Este objetivo incluye la migración de todos los informes y cubos al nuevo Business Intelligence.

Data adaptive control parameter estimation for scaling laws

Energy Technology Data Exchange (ETDEWEB)

Dinklage, Andreas [Max-Planck-Institut fuer Plasmaphysik, Teilinstitut Greifswald, Wendelsteinstrasse 1, D-17491 Greifswald (Germany); Dose, Volker [Max-Planck- Institut fuer Plasmaphysik, Boltzmannstrasse 2, D-85748 Garching (Germany)

2007-07-01

Bayesian experimental design quantifies the utility of data expressed by the information gain. Data adaptive exploration determines the expected utility of a single new measurement using existing data and a data descriptive model. In other words, the method can be used for experimental planning. As an example for a multivariate linear case, we apply this method for constituting scaling laws of fusion devices. In detail, the scaling of the stellarator W7-AS is examined for a subset of {iota}=1/3 data. The impact of the existing data on the scaling exponents is presented. Furthermore, in control parameter space regions of high utility are identified which improve the accuracy of the scaling law. This approach is not restricted to the presented example only, but can also be extended to non-linear models.

The Properties of Intelligent Human-Machine Interface

Directory of Open Access Journals (Sweden)

Alexander Alfimtsev

2012-04-01

Full Text Available Intelligent human-machine interfaces based on multimodal interaction are developed separately in different application areas. No unified opinion exists about the issue of what properties should these interfaces have to provide an intuitive and natural interaction. Having carried out an analytical survey of the papers that deal with intelligent interfaces a set of properties are presented, which are necessary for intelligent interface between an information system and a human: absolute response, justification, training, personification, adaptiveness, collectivity, security, hidden persistence, portability, filtering.

Large-scale Complex IT Systems

OpenAIRE

Sommerville, Ian; Cliff, Dave; Calinescu, Radu; Keen, Justin; Kelly, Tim; Kwiatkowska, Marta; McDermid, John; Paige, Richard

2011-01-01

This paper explores the issues around the construction of large-scale complex systems which are built as 'systems of systems' and suggests that there are fundamental reasons, derived from the inherent complexity in these systems, why our current software engineering methods and techniques cannot be scaled up to cope with the engineering challenges of constructing such systems. It then goes on to propose a research and education agenda for software engineering that identifies the major challen...

Large-scale complex IT systems

OpenAIRE

Sommerville, Ian; Cliff, Dave; Calinescu, Radu; Keen, Justin; Kelly, Tim; Kwiatkowska, Marta; McDermid, John; Paige, Richard

2012-01-01

12 pages, 2 figures This paper explores the issues around the construction of large-scale complex systems which are built as 'systems of systems' and suggests that there are fundamental reasons, derived from the inherent complexity in these systems, why our current software engineering methods and techniques cannot be scaled up to cope with the engineering challenges of constructing such systems. It then goes on to propose a research and education agenda for software engineering that ident...

Exploring the moderating effect of social intelligence on the relationship between entrepreneurial decision-making strategy and SME sustainable performance

Directory of Open Access Journals (Sweden)

Muhd Yusuf Dayang Hasliza

2018-01-01

Full Text Available The study reveals that causation, rather than effectuation, decision-making strategy is a more significant predictor of sustainable performance of SMEs. However, social intelligence was not found to be a significant moderator of entrepreneurial decision-making-sustainable performance relationship. The study uses data from a survey among 91 technology-based SMEs (TBS in Malaysia and employs structural equation modelling techniques for data analysis. A new instrument to measure all three variables of entrepreneurial decision-making strategy, social intelligence, and venture performance is proposed based on adoption and adaptation of existing validated scales available in literature.

Leadership Institute: Building Leadership Capacity through Emotional Intelligence

Science.gov (United States)

Argabright, Karen J.; King, Jeff; Cochran, Graham R.; Chen, Claire Yueh-Ti

2013-01-01

Given the changing dynamics of society and the pressures on Extension organizations to adapt, leadership effectiveness has become a crucial element of success. The program presented here is designed to enhance individual emotional intelligence. Through in-depth engagement of the participants, they learn to apply dynamics of emotional intelligence,…

Mathematical Intelligence and Mathematical Creativity: A Causal Relationship

Science.gov (United States)

Tyagi, Tarun Kumar

2017-01-01

This study investigated the causal relationship between mathematical creativity and mathematical intelligence. Four hundred thirty-nine 8th-grade students, age ranged from 11 to 14 years, were included in the sample of this study by random cluster technique on which mathematical creativity and Hindi adaptation of mathematical intelligence test…

First Mile Challenges for Large-Scale IoT

KAUST Repository

Bader, Ahmed; Elsawy, Hesham; Gharbieh, Mohammad; Alouini, Mohamed-Slim; Adinoyi, Abdulkareem; Alshaalan, Furaih

2017-01-01

The Internet of Things is large-scale by nature. This is not only manifested by the large number of connected devices, but also by the sheer scale of spatial traffic intensity that must be accommodated, primarily in the uplink direction. To that end

Adaptive local routing strategy on a scale-free network

International Nuclear Information System (INIS)

Feng, Liu; Han, Zhao; Ming, Li; Yan-Bo, Zhu; Feng-Yuan, Ren

2010-01-01

Due to the heterogeneity of the structure on a scale-free network, making the betweennesses of all nodes become homogeneous by reassigning the weights of nodes or edges is very difficult. In order to take advantage of the important effect of high degree nodes on the shortest path communication and preferentially deliver packets by them to increase the probability to destination, an adaptive local routing strategy on a scale-free network is proposed, in which the node adjusts the forwarding probability with the dynamical traffic load (packet queue length) and the degree distribution of neighbouring nodes. The critical queue length of a node is set to be proportional to its degree, and the node with high degree has a larger critical queue length to store and forward more packets. When the queue length of a high degree node is shorter than its critical queue length, it has a higher probability to forward packets. After higher degree nodes are saturated (whose queue lengths are longer than their critical queue lengths), more packets will be delivered by the lower degree nodes around them. The adaptive local routing strategy increases the probability of a packet finding its destination quickly, and improves the transmission capacity on the scale-free network by reducing routing hops. The simulation results show that the transmission capacity of the adaptive local routing strategy is larger than that of three previous local routing strategies. (general)

Emotional Intelligence and Transformational Leadership in Physical Education Managers

Directory of Open Access Journals (Sweden)

Nooshin Esfahani,

2013-03-01

Full Text Available The aim of the present research was to investigate the relationship between emotional intelligence and transformational leadership in managers of physical education of Golestan province. The managers and deputies of Golestan physical education departments participated in this research and 47 subjects were selected as the statistical sample of this study. Emotional Intelligence questionnaire that assessed five micro scales of self-awareness, self-management, self-motivation, empathy and social skills, Multifactor Leadership questionnaire (MLQ by Bass and Avolio (1996 that measured five micro scales related to transformational leadership, three micro scales of transactional leadership, and laissez-faire leadership were used to collect the data. In order to analyze the data, ANOVA test, multiple regression test, and Pearson correlation coefficient were applied. The results showed a significant relationship between emotional intelligence and transformational leadership method. Also, the results of multiple regression test indicated that among transformational leadership micro scales, personal considerations was the strongest predictive variable in transformational leadership method and among emotional intelligence micro scales, empathy had a great influence on emotional intelligence of physical education managers.