WorldWideScience

Sample records for learning based heterogeneous

  1. Force Sensor Based Tool Condition Monitoring Using a Heterogeneous Ensemble Learning Model

    Directory of Open Access Journals (Sweden)

    Guofeng Wang

    2014-11-01

    Full Text Available Tool condition monitoring (TCM plays an important role in improving machining efficiency and guaranteeing workpiece quality. In order to realize reliable recognition of the tool condition, a robust classifier needs to be constructed to depict the relationship between tool wear states and sensory information. However, because of the complexity of the machining process and the uncertainty of the tool wear evolution, it is hard for a single classifier to fit all the collected samples without sacrificing generalization ability. In this paper, heterogeneous ensemble learning is proposed to realize tool condition monitoring in which the support vector machine (SVM, hidden Markov model (HMM and radius basis function (RBF are selected as base classifiers and a stacking ensemble strategy is further used to reflect the relationship between the outputs of these base classifiers and tool wear states. Based on the heterogeneous ensemble learning classifier, an online monitoring system is constructed in which the harmonic features are extracted from force signals and a minimal redundancy and maximal relevance (mRMR algorithm is utilized to select the most prominent features. To verify the effectiveness of the proposed method, a titanium alloy milling experiment was carried out and samples with different tool wear states were collected to build the proposed heterogeneous ensemble learning classifier. Moreover, the homogeneous ensemble learning model and majority voting strategy are also adopted to make a comparison. The analysis and comparison results show that the proposed heterogeneous ensemble learning classifier performs better in both classification accuracy and stability.

  2. Heterogeneous inflation expectations, learning, and market outcomes

    OpenAIRE

    Madeira, Carlos; Zafar, Basit

    2012-01-01

    Using the panel component of the Michigan Survey of Consumers, we show that individuals, in particular women and ethnic minorities, are highly heterogeneous in their expectations of inflation. We estimate a model of inflation expectations based on learning from experience that also allows for heterogeneity in both private information and updating. Our model vastly outperforms existing models of inflation expectations in explaining the heterogeneity in the data. We find that women, ethnic mino...

  3. A DDoS Attack Detection Method Based on Hybrid Heterogeneous Multiclassifier Ensemble Learning

    Directory of Open Access Journals (Sweden)

    Bin Jia

    2017-01-01

    Full Text Available The explosive growth of network traffic and its multitype on Internet have brought new and severe challenges to DDoS attack detection. To get the higher True Negative Rate (TNR, accuracy, and precision and to guarantee the robustness, stability, and universality of detection system, in this paper, we propose a DDoS attack detection method based on hybrid heterogeneous multiclassifier ensemble learning and design a heuristic detection algorithm based on Singular Value Decomposition (SVD to construct our detection system. Experimental results show that our detection method is excellent in TNR, accuracy, and precision. Therefore, our algorithm has good detective performance for DDoS attack. Through the comparisons with Random Forest, k-Nearest Neighbor (k-NN, and Bagging comprising the component classifiers when the three algorithms are used alone by SVD and by un-SVD, it is shown that our model is superior to the state-of-the-art attack detection techniques in system generalization ability, detection stability, and overall detection performance.

  4. Grouped to Achieve: Are There Benefits to Assigning Students to Heterogeneous Cooperative Learning Groups Based on Pre-Test Scores?

    Science.gov (United States)

    Werth, Arman Karl

    Cooperative learning has been one of the most widely used instructional practices around the world since the early 1980's. Small learning groups have been in existence since the beginning of the human race. These groups have grown in their variance and complexity overtime. Classrooms are getting more diverse every year and instructors need a way to take advantage of this diversity to improve learning. The purpose of this study was to see if heterogeneous cooperative learning groups based on student achievement can be used as a differentiated instructional strategy to increase students' ability to demonstrate knowledge of science concepts and ability to do engineering design. This study includes two different groups made up of two different middle school science classrooms of 25-30 students. These students were given an engineering design problem to solve within cooperative learning groups. One class was put into heterogeneous cooperative learning groups based on student's pre-test scores. The other class was grouped based on random assignment. The study measured the difference between each class's pre-post gains, student's responses to a group interaction form and interview questions addressing their perceptions of the makeup of their groups. The findings of the study were that there was no significant difference between learning gains for the treatment and comparison groups. There was a significant difference between the treatment and comparison groups in student perceptions of their group's ability to stay on task and manage their time efficiently. Both the comparison and treatment groups had a positive perception of the composition of their cooperative learning groups.

  5. Heterogeneous inflation expectations and learning

    OpenAIRE

    Madeira, Carlos; Zafar, Basit

    2012-01-01

    Using the panel component of the Michigan Survey of Consumers, we estimate a learning model of inflation expectations, allowing for heterogeneous use of both private information and lifetime inflation experience. “Life-experience inflation” has a significant impact on individual expectations, but only for one-year-ahead inflation. Public information is substantially more relevant for longer-horizon expectations. Even controlling for life-experience inflation and public information, idiosyncra...

  6. A Coral Reef Algorithm Based on Learning Automata for the Coverage Control Problem of Heterogeneous Directional Sensor Networks.

    Science.gov (United States)

    Li, Ming; Miao, Chunyan; Leung, Cyril

    2015-12-04

    Coverage control is one of the most fundamental issues in directional sensor networks. In this paper, the coverage optimization problem in a directional sensor network is formulated as a multi-objective optimization problem. It takes into account the coverage rate of the network, the number of working sensor nodes and the connectivity of the network. The coverage problem considered in this paper is characterized by the geographical irregularity of the sensed events and heterogeneity of the sensor nodes in terms of sensing radius, field of angle and communication radius. To solve this multi-objective problem, we introduce a learning automata-based coral reef algorithm for adaptive parameter selection and use a novel Tchebycheff decomposition method to decompose the multi-objective problem into a single-objective problem. Simulation results show the consistent superiority of the proposed algorithm over alternative approaches.

  7. When high achievers and low achievers work in the same group: the roles of group heterogeneity and processes in project-based learning.

    Science.gov (United States)

    Cheng, Rebecca Wing-yi; Lam, Shui-fong; Chan, Joanne Chung-yan

    2008-06-01

    There has been an ongoing debate about the inconsistent effects of heterogeneous ability grouping on students in small group work such as project-based learning. The present research investigated the roles of group heterogeneity and processes in project-based learning. At the student level, we examined the interaction effect between students' within-group achievement and group processes on their self- and collective efficacy. At the group level, we examined how group heterogeneity was associated with the average self- and collective efficacy reported by the groups. The participants were 1,921 Hong Kong secondary students in 367 project-based learning groups. Student achievement was determined by school examination marks. Group processes, self-efficacy and collective efficacy were measured by a student-report questionnaire. Hierarchical linear modelling was used to analyse the nested data. When individual students in each group were taken as the unit of analysis, results indicated an interaction effect of group processes and students' within-group achievement on the discrepancy between collective- and self-efficacy. When compared with low achievers, high achievers reported lower collective efficacy than self-efficacy when group processes were of low quality. However, both low and high achievers reported higher collective efficacy than self-efficacy when group processes were of high quality. With 367 groups taken as the unit of analysis, the results showed that group heterogeneity, group gender composition and group size were not related to the discrepancy between collective- and self-efficacy reported by the students. Group heterogeneity was not a determinant factor in students' learning efficacy. Instead, the quality of group processes played a pivotal role because both high and low achievers were able to benefit when group processes were of high quality.

  8. Annual sums of carbon dioxide exchange over a heterogeneous urban landscape through machine learning based gap-filling

    Science.gov (United States)

    Menzer, Olaf; Meiring, Wendy; Kyriakidis, Phaedon C.; McFadden, Joseph P.

    2015-01-01

    A small, but growing, number of flux towers in urban environments measure surface-atmospheric exchanges of carbon dioxide by the eddy covariance method. As in all eddy covariance studies, obtaining annual sums of urban CO2 exchange requires imputation of data gaps due to low turbulence and non-stationary conditions, adverse weather, and instrument failures. Gap-filling approaches that are widely used for measurements from towers in natural vegetation are based on light and temperature response models. However, they do not account for key features of the urban environment including tower footprint heterogeneity and localized CO2 sources. Here, we present a novel gap-filling modeling framework that uses machine learning to select explanatory variables, such as continuous traffic counts and temporal variables, and then constrains models separately for spatially classified subsets of the data. We applied the modeling framework to a three year time series of measurements from a tall broadcast tower in a suburban neighborhood of Minneapolis-Saint Paul, Minnesota, USA. The gap-filling performance was similar to that reported for natural measurement sites, explaining 64% to 88% of the variability in the fluxes. Simulated carbon budgets were in good agreement with an ecophysiological bottom-up study at the same site. Total annual carbon dioxide flux sums for the tower site ranged from 1064 to 1382 g C m-2 yr-1, across different years and different gap-filling methods. Bias errors of annual sums resulting from gap-filling did not exceed 18 g C m-2 yr-1 and random uncertainties did not exceed ±44 g C m-2 yr-1 (or ±3.8% of the annual flux). Regardless of the gap-filling method used, the year-to-year differences in carbon exchange at this site were small. In contrast, the modeled annual sums of CO2 exchange differed by a factor of two depending on wind direction. This indicated that the modeled time series captured the spatial variability in both the biogenic and

  9. Heterogeneous iris image hallucination using sparse representation on a learned heterogeneous patch dictionary

    Science.gov (United States)

    Li, Yung-Hui; Zheng, Bo-Ren; Ji, Dai-Yan; Tien, Chung-Hao; Liu, Po-Tsun

    2014-09-01

    Cross sensor iris matching may seriously degrade the recognition performance because of the sensor mis-match problem of iris images between the enrollment and test stage. In this paper, we propose two novel patch-based heterogeneous dictionary learning method to attack this problem. The first method applies the latest sparse representation theory while the second method tries to learn the correspondence relationship through PCA in heterogeneous patch space. Both methods learn the basic atoms in iris textures across different image sensors and build connections between them. After such connections are built, at test stage, it is possible to hallucinate (synthesize) iris images across different sensors. By matching training images with hallucinated images, the recognition rate can be successfully enhanced. The experimental results showed the satisfied results both visually and in terms of recognition rate. Experimenting with an iris database consisting of 3015 images, we show that the EER is decreased 39.4% relatively by the proposed method.

  10. A heterogeneous graph-based recommendation simulator

    Energy Technology Data Exchange (ETDEWEB)

    Yeonchan, Ahn [Seoul National University; Sungchan, Park [Seoul National University; Lee, Matt Sangkeun [ORNL; Sang-goo, Lee [Seoul National University

    2013-01-01

    Heterogeneous graph-based recommendation frameworks have flexibility in that they can incorporate various recommendation algorithms and various kinds of information to produce better results. In this demonstration, we present a heterogeneous graph-based recommendation simulator which enables participants to experience the flexibility of a heterogeneous graph-based recommendation method. With our system, participants can simulate various recommendation semantics by expressing the semantics via meaningful paths like User Movie User Movie. The simulator then returns the recommendation results on the fly based on the user-customized semantics using a fast Monte Carlo algorithm.

  11. A Multianalyzer Machine Learning Model for Marine Heterogeneous Data Schema Mapping

    Directory of Open Access Journals (Sweden)

    Wang Yan

    2014-01-01

    Full Text Available The main challenges that marine heterogeneous data integration faces are the problem of accurate schema mapping between heterogeneous data sources. In order to improve the schema mapping efficiency and get more accurate learning results, this paper proposes a heterogeneous data schema mapping method basing on multianalyzer machine learning model. The multianalyzer analysis the learning results comprehensively, and a fuzzy comprehensive evaluation system is introduced for output results’ evaluation and multi factor quantitative judging. Finally, the data mapping comparison experiment on the East China Sea observing data confirms the effectiveness of the model and shows multianalyzer’s obvious improvement of mapping error rate.

  12. A Multianalyzer Machine Learning Model for Marine Heterogeneous Data Schema Mapping

    Science.gov (United States)

    Yan, Wang; Jiajin, Le; Yun, Zhang

    2014-01-01

    The main challenges that marine heterogeneous data integration faces are the problem of accurate schema mapping between heterogeneous data sources. In order to improve the schema mapping efficiency and get more accurate learning results, this paper proposes a heterogeneous data schema mapping method basing on multianalyzer machine learning model. The multianalyzer analysis the learning results comprehensively, and a fuzzy comprehensive evaluation system is introduced for output results' evaluation and multi factor quantitative judging. Finally, the data mapping comparison experiment on the East China Sea observing data confirms the effectiveness of the model and shows multianalyzer's obvious improvement of mapping error rate. PMID:25250372

  13. Heterogeneity, learning and information stickiness in inflation expectations

    DEFF Research Database (Denmark)

    Pfajfar, Damjan; Santoro, Emiliano

    2010-01-01

    In this paper we propose novel techniques for the empirical analysis of adaptive learning and sticky information in inflation expectations. These methodologies are applied to the distribution of households’ inflation expectations collected by the University of Michigan Survey Research Center....... To account for the evolution of the cross-section of inflation forecasts over time and measure the degree of heterogeneity in private agents’ forecasts, we explore time series of percentiles from the empirical distribution. Our results show that heterogeneity is pervasive in the process of inflation...... hand side of the median formed in accordance with adaptive learning and sticky information....

  14. Micromechanics Based Failure Analysis of Heterogeneous Materials

    Science.gov (United States)

    Sertse, Hamsasew M.

    In recent decades, heterogeneous materials are extensively used in various industries such as aerospace, defense, automotive and others due to their desirable specific properties and excellent capability of accumulating damage. Despite their wide use, there are numerous challenges associated with the application of these materials. One of the main challenges is lack of accurate tools to predict the initiation, progression and final failure of these materials under various thermomechanical loading conditions. Although failure is usually treated at the macro and meso-scale level, the initiation and growth of failure is a complex phenomena across multiple scales. The objective of this work is to enable the mechanics of structure genome (MSG) and its companion code SwiftComp to analyze the initial failure (also called static failure), progressive failure, and fatigue failure of heterogeneous materials using micromechanics approach. The initial failure is evaluated at each numerical integration point using pointwise and nonlocal approach for each constituent of the heterogeneous materials. The effects of imperfect interfaces among constituents of heterogeneous materials are also investigated using a linear traction-displacement model. Moreover, the progressive and fatigue damage analyses are conducted using continuum damage mechanics (CDM) approach. The various failure criteria are also applied at a material point to analyze progressive damage in each constituent. The constitutive equation of a damaged material is formulated based on a consistent irreversible thermodynamics approach. The overall tangent modulus of uncoupled elastoplastic damage for negligible back stress effect is derived. The initiation of plasticity and damage in each constituent is evaluated at each numerical integration point using a nonlocal approach. The accumulated plastic strain and anisotropic damage evolution variables are iteratively solved using an incremental algorithm. The damage analyses

  15. Emergence of heterogeneity in an agent-based model

    OpenAIRE

    Abdullah, Wan Ahmad Tajuddin Wan

    2002-01-01

    We study an interacting agent model of a game-theoretical economy. The agents play a minority-subsequently-majority game and they learn, using backpropagation networks, to obtain higher payoffs. We study the relevance of heterogeneity to performance, and how heterogeneity emerges.

  16. Representation Learning from Time Labelled Heterogeneous Data for Mobile Crowdsensing

    Directory of Open Access Journals (Sweden)

    Chunmei Ma

    2016-01-01

    Full Text Available Mobile crowdsensing is a new paradigm that can utilize pervasive smartphones to collect and analyze data to benefit users. However, sensory data gathered by smartphone usually involves different data types because of different granularity and multiple sensor sources. Besides, the data are also time labelled. The heterogeneous and time sequential data raise new challenges for data analyzing. Some existing solutions try to learn each type of data one by one and analyze them separately without considering time information. In addition, the traditional methods also have to determine phone orientation because some sensors equipped in smartphone are orientation related. In this paper, we think that a combination of multiple sensors can represent an invariant feature for a crowdsensing context. Therefore, we propose a new representation learning method of heterogeneous data with time labels to extract typical features using deep learning. We evaluate that our proposed method can adapt data generated by different orientations effectively. Furthermore, we test the performance of the proposed method by recognizing two group mobile activities, walking/cycling and driving/bus with smartphone sensors. It achieves precisions of 98.6% and 93.7% in distinguishing cycling from walking and bus from driving, respectively.

  17. Mobile Inquiry Based Learning

    NARCIS (Netherlands)

    Specht, Marcus

    2012-01-01

    Specht, M. (2012, 8 November). Mobile Inquiry Based Learning. Presentation given at the Workshop "Mobile inquiry-based learning" at the Mobile Learning Day 2012 at the Fernuniversität Hagen, Hagen, Germany.

  18. Heterogeneous Users in MOOC and their Adaptive Learning Needs

    Directory of Open Access Journals (Sweden)

    María Luisa SEIN-ECHALUCE LACLETA

    2017-02-01

    Full Text Available Many research works point out the overcrowding and the heterogeneity of participant’s profiles in Massive Open Online Courses (MOOC as the main causes of their low completion rate. On the other hand, the methodologies of personalization of the learning, along next to the technologies of the information, that allows to realize techniques of adaptativity, appear in international reports as an effective way to improve the learning. This paper explores the participante’ perception of their adaptive needs in this tupe of course, as well as their relationship with different aspects of the participants, such as: profiles (gender, age, geographical location and academic level, previous experience and knowledge about the topic of the MOOC and motivation to enroll the MOOC. The study is carried out through a survey completes by the participants in the MOOC Campus of Educational Innovation. We conclude that the age or gender of the participants does not significantly influence their need for adaptive techniques in a MOOC. However, living in a Latin American country, working as a manager or enrolling in a MOOC with a specific motivation, are some of the factors that influence in the desire for adaptive techniques in a MOOC. The obtained results will contribute to improve the adaptive designs of the MOOC and will be easily transferable to any online training course, in blended or virtual learning.

  19. Learning to Learn: A Case for the Heterogeneous Expectations Hypothesis in Industrialized Markets

    Directory of Open Access Journals (Sweden)

    Desmond W. Ng

    2016-07-01

    Full Text Available A cobweb model is developed where the heterogeneous expectation hypothesis is examined. An agent’s heterogeneous expectation involves the development of a “higher ordered learning” process in which agents over time develop expectations that are consistent with rational expectations. In addition, as cob web models are production based systems, an agents’ heterogeneous expectations are influenced by a specialization of activities. The case of the industrialization of the U.S. hog-pork industry is used to illustrate the influence of these features on the equilibrium and non-equilibrium properties of a modified cob-web model.

  20. Application-specific mesh-based heterogeneous FPGA architectures

    CERN Document Server

    Parvez, Husain

    2011-01-01

    This volume presents a new exploration environment for mesh-based, heterogeneous FPGA architectures. Readers will find a description of state-of-the-art techniques for reducing area requirements, which both increase performance and enable power reduction.

  1. Unsupervised multiple kernel learning for heterogeneous data integration.

    Science.gov (United States)

    Mariette, Jérôme; Villa-Vialaneix, Nathalie

    2018-03-15

    Recent high-throughput sequencing advances have expanded the breadth of available omics datasets and the integrated analysis of multiple datasets obtained on the same samples has allowed to gain important insights in a wide range of applications. However, the integration of various sources of information remains a challenge for systems biology since produced datasets are often of heterogeneous types, with the need of developing generic methods to take their different specificities into account. We propose a multiple kernel framework that allows to integrate multiple datasets of various types into a single exploratory analysis. Several solutions are provided to learn either a consensus meta-kernel or a meta-kernel that preserves the original topology of the datasets. We applied our framework to analyse two public multi-omics datasets. First, the multiple metagenomic datasets, collected during the TARA Oceans expedition, was explored to demonstrate that our method is able to retrieve previous findings in a single kernel PCA as well as to provide a new image of the sample structures when a larger number of datasets are included in the analysis. To perform this analysis, a generic procedure is also proposed to improve the interpretability of the kernel PCA in regards with the original data. Second, the multi-omics breast cancer datasets, provided by The Cancer Genome Atlas, is analysed using a kernel Self-Organizing Maps with both single and multi-omics strategies. The comparison of these two approaches demonstrates the benefit of our integration method to improve the representation of the studied biological system. Proposed methods are available in the R package mixKernel, released on CRAN. It is fully compatible with the mixOmics package and a tutorial describing the approach can be found on mixOmics web site http://mixomics.org/mixkernel/. jerome.mariette@inra.fr or nathalie.villa-vialaneix@inra.fr. Supplementary data are available at Bioinformatics online.

  2. Strengths-based Learning

    DEFF Research Database (Denmark)

    Ledertoug, Mette Marie

    -being. The Ph.D.-project in Strength-based learning took place in a Danish school with 750 pupils age 6-16 and a similar school was functioning as a control group. The presentation will focus on both the aware-explore-apply processes and the practical implications for the schools involved, and on measurable......Strength-based learning - Children͛s Character Strengths as Means to their Learning Potential͛ is a Ph.D.-project aiming to create a strength-based mindset in school settings and at the same time introducing strength-based interventions as specific tools to improve both learning and well...

  3. Web-Based Learning Support System

    Science.gov (United States)

    Fan, Lisa

    Web-based learning support system offers many benefits over traditional learning environments and has become very popular. The Web is a powerful environment for distributing information and delivering knowledge to an increasingly wide and diverse audience. Typical Web-based learning environments, such as Web-CT, Blackboard, include course content delivery tools, quiz modules, grade reporting systems, assignment submission components, etc. They are powerful integrated learning management systems (LMS) that support a number of activities performed by teachers and students during the learning process [1]. However, students who study a course on the Internet tend to be more heterogeneously distributed than those found in a traditional classroom situation. In order to achieve optimal efficiency in a learning process, an individual learner needs his or her own personalized assistance. For a web-based open and dynamic learning environment, personalized support for learners becomes more important. This chapter demonstrates how to realize personalized learning support in dynamic and heterogeneous learning environments by utilizing Adaptive Web technologies. It focuses on course personalization in terms of contents and teaching materials that is according to each student's needs and capabilities. An example of using Rough Set to analyze student personal information to assist students with effective learning and predict student performance is presented.

  4. How Teaching Science Using Project-Based Learning Strategies Affects the Classroom Learning Environment

    Science.gov (United States)

    Hugerat, Muhamad

    2016-01-01

    This study involved 458 ninth-grade students from two different Arab middle schools in Israel. Half of the students learned science using project-based learning strategies and the other half learned using traditional methods (non-project-based). The classes were heterogeneous regarding their achievements in the sciences. The adapted questionnaire…

  5. Problem Based Learning

    DEFF Research Database (Denmark)

    de Graaff, Erik; Guerra, Aida

    , the key principles remain the same everywhere. Graaff & Kolmos (2003) identify the main PBL principles as follows: 1. Problem orientation 2. Project organization through teams or group work 3. Participant-directed 4. Experiental learning 5. Activity-based learning 6. Interdisciplinary learning and 7...... model and in general problem based and project based learning. We apply the principle of teach as you preach. The poster aims to outline the visitors’ workshop programme showing the results of some recent evaluations.......Problem-Based Learning (PBL) is an innovative method to organize the learning process in such a way that the students actively engage in finding answers by themselves. During the past 40 years PBL has evolved and diversified resulting in a multitude in variations in models and practices. However...

  6. Heterogeneous Community-based mobility model for human opportunistic network

    DEFF Research Database (Denmark)

    Hu, Liang; Dittmann, Lars

    2009-01-01

    a heterogeneous community-based random way-point (HC-RWP) mobility model that captures the four important properties of real human mobility. These properties are based on both intuitive observations of daily human mobility and analysis of empirical mobility traces. By discrete event simulation, we show HC...

  7. Sophisticated Online Learning Scheme for Green Resource Allocation in 5G Heterogeneous Cloud Radio Access Networks

    KAUST Repository

    Alqerm, Ismail

    2018-01-23

    5G is the upcoming evolution for the current cellular networks that aims at satisfying the future demand for data services. Heterogeneous cloud radio access networks (H-CRANs) are envisioned as a new trend of 5G that exploits the advantages of heterogeneous and cloud radio access networks to enhance spectral and energy efficiency. Remote radio heads (RRHs) are small cells utilized to provide high data rates for users with high quality of service (QoS) requirements, while high power macro base station (BS) is deployed for coverage maintenance and low QoS users service. Inter-tier interference between macro BSs and RRHs and energy efficiency are critical challenges that accompany resource allocation in H-CRANs. Therefore, we propose an efficient resource allocation scheme using online learning, which mitigates interference and maximizes energy efficiency while maintaining QoS requirements for all users. The resource allocation includes resource blocks (RBs) and power. The proposed scheme is implemented using two approaches: centralized, where the resource allocation is processed at a controller integrated with the baseband processing unit and decentralized, where macro BSs cooperate to achieve optimal resource allocation strategy. To foster the performance of such sophisticated scheme with a model free learning, we consider users\\' priority in RB allocation and compact state representation learning methodology to improve the speed of convergence and account for the curse of dimensionality during the learning process. The proposed scheme including both approaches is implemented using software defined radios testbed. The obtained results and simulation results confirm that the proposed resource allocation solution in H-CRANs increases the energy efficiency significantly and maintains users\\' QoS.

  8. A Deep Convolutional Coupling Network for Change Detection Based on Heterogeneous Optical and Radar Images.

    Science.gov (United States)

    Liu, Jia; Gong, Maoguo; Qin, Kai; Zhang, Puzhao

    2018-03-01

    We propose an unsupervised deep convolutional coupling network for change detection based on two heterogeneous images acquired by optical sensors and radars on different dates. Most existing change detection methods are based on homogeneous images. Due to the complementary properties of optical and radar sensors, there is an increasing interest in change detection based on heterogeneous images. The proposed network is symmetric with each side consisting of one convolutional layer and several coupling layers. The two input images connected with the two sides of the network, respectively, are transformed into a feature space where their feature representations become more consistent. In this feature space, the different map is calculated, which then leads to the ultimate detection map by applying a thresholding algorithm. The network parameters are learned by optimizing a coupling function. The learning process is unsupervised, which is different from most existing change detection methods based on heterogeneous images. Experimental results on both homogenous and heterogeneous images demonstrate the promising performance of the proposed network compared with several existing approaches.

  9. Problem-based learning

    NARCIS (Netherlands)

    Loyens, Sofie; Kirschner, Paul A.; Paas, Fred

    2010-01-01

    Loyens, S. M. M., Kirschner, P. A., & Paas, F. (2011). Problem-based learning. In S. Graham (Editor-in-Chief), A. Bus, S. Major, & L. Swanson (Associate Editors), APA educational psychology handbook: Vol. 3. Application to learning and teaching (pp. 403-425). Washington, DC: American Psychological

  10. Research on Heterogeneous Data Exchange based on XML

    Science.gov (United States)

    Li, Huanqin; Liu, Jinfeng

    Integration of multiple data sources is becoming increasingly important for enterprises that cooperate closely with their partners for e-commerce. OLAP enables analysts and decision makers fast access to various materialized views from data warehouses. However, many corporations have internal business applications deployed on different platforms. This paper introduces a model for heterogeneous data exchange based on XML. The system can exchange and share the data among the different sources. The method used to realize the heterogeneous data exchange is given in this paper.

  11. Addressing data heterogeneity: Lessons learned from a multimedia risk assessment

    International Nuclear Information System (INIS)

    Oezkaynak, H.; Xue, Jianping; Butler, D.A.; Haroun, L.A.; MacDonell, M.M.; Fingleton, D.J.

    1991-01-01

    Cleanup activities are currently being conducted by the US Department of Energy (DOE) at a former chemical plant site that has been inactive for more than 20 years. The Army produced nitroaromatic explosives at the 220-acre site during the 1940s, and radioactive materials of the uranium and thorium series were processed there by DOE's predecessor agency during the 1950s and 1960s. Chemical and radioactive contaminants are present in soil, surface water, sediment, and groundwater at the site as a result of both past releases and disposal activities and subsequent contaminant migration. Samples have been collected from these media over a number of years under both DOE's environmental monitoring program and the site characterization program of the Superfund process. Results of samples analyses have been compiled in a computerized data base. These data are being evaluated in the context of potential exposure pathways that are currently present at the site or that may be present in the future, in order to estimate possible adverse impacts to human health and the environment in the absence of cleanup. This paper discusses the methodology used to address associated tasks and the lessons learned during the assessment process. Statistical issues and recommended future directions for dealing with technical aspects of this project and with similar multimedia risk assessment projects are addressed in the final discussion. 10 refs., 9 figs., 1 tab

  12. An FPGA-based heterogeneous image fusion system design method

    Science.gov (United States)

    Song, Le; Lin, Yu-chi; Chen, Yan-hua; Zhao, Mei-rong

    2011-08-01

    Taking the advantages of FPGA's low cost and compact structure, an FPGA-based heterogeneous image fusion platform is established in this study. Altera's Cyclone IV series FPGA is adopted as the core processor of the platform, and the visible light CCD camera and infrared thermal imager are used as the image-capturing device in order to obtain dualchannel heterogeneous video images. Tailor-made image fusion algorithms such as gray-scale weighted averaging, maximum selection and minimum selection methods are analyzed and compared. VHDL language and the synchronous design method are utilized to perform a reliable RTL-level description. Altera's Quartus II 9.0 software is applied to simulate and implement the algorithm modules. The contrast experiments of various fusion algorithms show that, preferably image quality of the heterogeneous image fusion can be obtained on top of the proposed system. The applied range of the different fusion algorithms is also discussed.

  13. How Design of Online Learning Materials can Accommodate the Heterogeneity in Student Abilities, Aptitudes and Aspirations

    OpenAIRE

    Bates, Simon; Hardy, Judy; Hill, Jon; McKain, David; University of Gloucestershire

    2008-01-01

    We describe the challenges facing higher education in terms of the heterogeneity of the cohort of students that arrive at university. The reasons why such diversity exists are many: students differ widely in terms of their preparedness for study at university, their degree choice aspirations and the issue of motivation for study of a particular subject. We illustrate how well-designed e-learning course materials can support many of the particular facets of heterogeneity by offering an inheren...

  14. Synchronous message-based communication for distributed heterogeneous systems

    International Nuclear Information System (INIS)

    Wilkinson, N.; Dohan, D.

    1992-01-01

    The use of a synchronous, message-based real-time operating system (Unison) as the basis of transparent interprocess and inter-processor communication over VME-bus is described. The implementation of a synchronous, message-based protocol for network communication between heterogeneous systems is discussed. In particular, the design and implementation of a message-based session layer over a virtual circuit transport layer protocol using UDP/IP is described. Inter-process communication is achieved via a message-based semantic which is portable by virtue of its ease of implementation in other operating system environments. Protocol performance for network communication among heterogeneous architecture is presented, including VMS, Unix, Mach and Unison. (author)

  15. Heterogeneous Face Attribute Estimation: A Deep Multi-Task Learning Approach.

    Science.gov (United States)

    Han, Hu; K Jain, Anil; Shan, Shiguang; Chen, Xilin

    2017-08-10

    Face attribute estimation has many potential applications in video surveillance, face retrieval, and social media. While a number of methods have been proposed for face attribute estimation, most of them did not explicitly consider the attribute correlation and heterogeneity (e.g., ordinal vs. nominal and holistic vs. local) during feature representation learning. In this paper, we present a Deep Multi-Task Learning (DMTL) approach to jointly estimate multiple heterogeneous attributes from a single face image. In DMTL, we tackle attribute correlation and heterogeneity with convolutional neural networks (CNNs) consisting of shared feature learning for all the attributes, and category-specific feature learning for heterogeneous attributes. We also introduce an unconstrained face database (LFW+), an extension of public-domain LFW, with heterogeneous demographic attributes (age, gender, and race) obtained via crowdsourcing. Experimental results on benchmarks with multiple face attributes (MORPH II, LFW+, CelebA, LFWA, and FotW) show that the proposed approach has superior performance compared to state of the art. Finally, evaluations on a public-domain face database (LAP) with a single attribute show that the proposed approach has excellent generalization ability.

  16. Heterogeneous Multi-Metric Learning for Multi-Sensor Fusion

    Science.gov (United States)

    2011-07-01

    Neural Information Processing Systems, 2010. [18] C.-C. Shen and W.-H. Tsai. Multisensor fusion in smartphones for lifestyle monitoring. In Int. Conf. on...Ministry of Education (708085) of China. REFERENCES [1] C. M. Bishop. Pattern Recognition and Machine Learning. Springer, 2006. [2] S. Boughhorbel, J

  17. Neuroanatomical heterogeneity of schizophrenia revealed by semi-supervised machine learning methods.

    Science.gov (United States)

    Honnorat, Nicolas; Dong, Aoyan; Meisenzahl-Lechner, Eva; Koutsouleris, Nikolaos; Davatzikos, Christos

    2017-12-20

    Schizophrenia is associated with heterogeneous clinical symptoms and neuroanatomical alterations. In this work, we aim to disentangle the patterns of neuroanatomical alterations underlying a heterogeneous population of patients using a semi-supervised clustering method. We apply this strategy to a cohort of patients with schizophrenia of varying extends of disease duration, and we describe the neuroanatomical, demographic and clinical characteristics of the subtypes discovered. We analyze the neuroanatomical heterogeneity of 157 patients diagnosed with Schizophrenia, relative to a control population of 169 subjects, using a machine learning method called CHIMERA. CHIMERA clusters the differences between patients and a demographically-matched population of healthy subjects, rather than clustering patients themselves, thereby specifically assessing disease-related neuroanatomical alterations. Voxel-Based Morphometry was conducted to visualize the neuroanatomical patterns associated with each group. The clinical presentation and the demographics of the groups were then investigated. Three subgroups were identified. The first two differed substantially, in that one involved predominantly temporal-thalamic-peri-Sylvian regions, whereas the other involved predominantly frontal regions and the thalamus. Both subtypes included primarily male patients. The third pattern was a mix of these two and presented milder neuroanatomic alterations and comprised a comparable number of men and women. VBM and statistical analyses suggest that these groups could correspond to different neuroanatomical dimensions of schizophrenia. Our analysis suggests that schizophrenia presents distinct neuroanatomical variants. This variability points to the need for a dimensional neuroanatomical approach using data-driven, mathematically principled multivariate pattern analysis methods, and should be taken into account in clinical studies. Copyright © 2017 Elsevier B.V. All rights reserved.

  18. Heterogeneous agent model and numerical analysis of learning

    Czech Academy of Sciences Publication Activity Database

    Vošvrda, Miloslav; Vácha, Lukáš

    2002-01-01

    Roč. 9, č. 17 (2002), s. 15-22 ISSN 1212-074X R&D Projects: GA ČR GA402/01/0034; GA ČR GA402/01/0539; GA AV ČR IAA7075202 Institutional research plan: CEZ:AV0Z1075907 Keywords : efficient markets hypothesis * technical trading rules * numerical analysis of learning Subject RIV: AH - Economics

  19. Constrained Active Learning for Anchor Link Prediction Across Multiple Heterogeneous Social Networks.

    Science.gov (United States)

    Zhu, Junxing; Zhang, Jiawei; Wu, Quanyuan; Jia, Yan; Zhou, Bin; Wei, Xiaokai; Yu, Philip S

    2017-08-03

    Nowadays, people are usually involved in multiple heterogeneous social networks simultaneously. Discovering the anchor links between the accounts owned by the same users across different social networks is crucial for many important inter-network applications, e.g., cross-network link transfer and cross-network recommendation. Many different supervised models have been proposed to predict anchor links so far, but they are effective only when the labeled anchor links are abundant. However, in real scenarios, such a requirement can hardly be met and most anchor links are unlabeled, since manually labeling the inter-network anchor links is quite costly and tedious. To overcome such a problem and utilize the numerous unlabeled anchor links in model building, in this paper, we introduce the active learning based anchor link prediction problem. Different from the traditional active learning problems, due to the one-to-one constraint on anchor links, if an unlabeled anchor link a = ( u , v ) is identified as positive (i.e., existing), all the other unlabeled anchor links incident to account u or account v will be negative (i.e., non-existing) automatically. Viewed in such a perspective, asking for the labels of potential positive anchor links in the unlabeled set will be rewarding in the active anchor link prediction problem. Various novel anchor link information gain measures are defined in this paper, based on which several constraint active anchor link prediction methods are introduced. Extensive experiments have been done on real-world social network datasets to compare the performance of these methods with state-of-art anchor link prediction methods. The experimental results show that the proposed Mean-entropy-based Constrained Active Learning (MC) method can outperform other methods with significant advantages.

  20. "The Coat Traps All Your Body Heat": Heterogeneity as Fundamental to Learning

    Science.gov (United States)

    Rosebery, Ann S.; Ogonowski, Mark; DiSchino, Mary; Warren, Beth

    2010-01-01

    This article explores heterogeneity as fundamental to learning. Inspired by Bakhtin's notion of heteroglossia, a design team consisting of an experienced classroom teacher and 2 researchers investigated how a class of 3rd and 4th graders came to understand disciplinary points of view on heat, heat transfer, and the particulate nature of matter.…

  1. Boundedly rational learning and heterogeneous trading strategies with hybrid neuro-fuzzy models

    NARCIS (Netherlands)

    Bekiros, S.D.

    2009-01-01

    The present study deals with heterogeneous learning rules in speculative markets where heuristic strategies reflect the rules-of-thumb of boundedly rational investors. The major challenge for "chartists" is the development of new models that would enhance forecasting ability particularly for time

  2. Associations Between Academic and Motor Performance in a Heterogeneous Sample of Children With Learning Disabilities

    NARCIS (Netherlands)

    Vuijk, Pieter Jelle; Hartman, Esther; Mombarg, Remo; Scherder, Erik; Visscher, Chris

    2011-01-01

    A heterogeneous sample of 137 school-aged children with learning disabilities (IQ > 80) attending special needs schools was examined on the Movement Assessment Battery for Children (MABC). The results show that compared to the available norm scores, 52.6% of the children tested performed below the

  3. Group Composition of Cooperative Learning: Does Heterogeneous Grouping Work in Asian Classrooms?

    Science.gov (United States)

    Thanh, Pham Thi Hong; Gillies, Robyn

    2010-01-01

    Constructing an appropriate group is important to teamwork success. Although, heterogeneous grouping is widely recommended in Western countries, this method of grouping is questioned in Asian classrooms because Asian and Western students have different cultures of learning. Unfortunately, this issue has not been addressed in any research to date.…

  4. Ontology based heterogeneous materials database integration and semantic query

    Science.gov (United States)

    Zhao, Shuai; Qian, Quan

    2017-10-01

    Materials digital data, high throughput experiments and high throughput computations are regarded as three key pillars of materials genome initiatives. With the fast growth of materials data, the integration and sharing of data is very urgent, that has gradually become a hot topic of materials informatics. Due to the lack of semantic description, it is difficult to integrate data deeply in semantic level when adopting the conventional heterogeneous database integration approaches such as federal database or data warehouse. In this paper, a semantic integration method is proposed to create the semantic ontology by extracting the database schema semi-automatically. Other heterogeneous databases are integrated to the ontology by means of relational algebra and the rooted graph. Based on integrated ontology, semantic query can be done using SPARQL. During the experiments, two world famous First Principle Computational databases, OQMD and Materials Project are used as the integration targets, which show the availability and effectiveness of our method.

  5. Projection specificity in heterogeneous locus coeruleus cell populations: implications for learning and memory

    Science.gov (United States)

    Uematsu, Akira; Tan, Bao Zhen

    2015-01-01

    Noradrenergic neurons in the locus coeruleus (LC) play a critical role in many functions including learning and memory. This relatively small population of cells sends widespread projections throughout the brain including to a number of regions such as the amygdala which is involved in emotional associative learning and the medial prefrontal cortex which is important for facilitating flexibility when learning rules change. LC noradrenergic cells participate in both of these functions, but it is not clear how this small population of neurons modulates these partially distinct processes. Here we review anatomical, behavioral, and electrophysiological studies to assess how LC noradrenergic neurons regulate these different aspects of learning and memory. Previous work has demonstrated that subpopulations of LC noradrenergic cells innervate specific brain regions suggesting heterogeneity of function in LC neurons. Furthermore, noradrenaline in mPFC and amygdala has distinct effects on emotional learning and cognitive flexibility. Finally, neural recording data show that LC neurons respond during associative learning and when previously learned task contingencies change. Together, these studies suggest a working model in which distinct and potentially opposing subsets of LC neurons modulate particular learning functions through restricted efferent connectivity with amygdala or mPFC. This type of model may provide a general framework for understanding other neuromodulatory systems, which also exhibit cell type heterogeneity and projection specificity. PMID:26330494

  6. Enhanced machine learning scheme for energy efficient resource allocation in 5G heterogeneous cloud radio access networks

    KAUST Repository

    Alqerm, Ismail

    2018-02-15

    Heterogeneous cloud radio access networks (H-CRAN) is a new trend of 5G that aims to leverage the heterogeneous and cloud radio access networks advantages. Low power remote radio heads (RRHs) are exploited to provide high data rates for users with high quality of service requirements (QoS), while high power macro base stations (BSs) are deployed for coverage maintenance and low QoS users support. However, the inter-tier interference between the macro BS and RRHs and energy efficiency are critical challenges that accompany resource allocation in H-CRAN. Therefore, we propose a centralized resource allocation scheme using online learning, which guarantees interference mitigation and maximizes energy efficiency while maintaining QoS requirements for all users. To foster the performance of such scheme with a model-free learning, we consider users\\' priority in resource blocks (RBs) allocation and compact state representation based learning methodology to enhance the learning process. Simulation results confirm that the proposed resource allocation solution can mitigate interference, increase energy and spectral efficiencies significantly, and maintain users\\' QoS requirements.

  7. A Parallel Strategy for Convolutional Neural Network Based on Heterogeneous Cluster for Mobile Information System

    Directory of Open Access Journals (Sweden)

    Jilin Zhang

    2017-01-01

    Full Text Available With the development of the mobile systems, we gain a lot of benefits and convenience by leveraging mobile devices; at the same time, the information gathered by smartphones, such as location and environment, is also valuable for business to provide more intelligent services for customers. More and more machine learning methods have been used in the field of mobile information systems to study user behavior and classify usage patterns, especially convolutional neural network. With the increasing of model training parameters and data scale, the traditional single machine training method cannot meet the requirements of time complexity in practical application scenarios. The current training framework often uses simple data parallel or model parallel method to speed up the training process, which is why heterogeneous computing resources have not been fully utilized. To solve these problems, our paper proposes a delay synchronization convolutional neural network parallel strategy, which leverages the heterogeneous system. The strategy is based on both synchronous parallel and asynchronous parallel approaches; the model training process can reduce the dependence on the heterogeneous architecture in the premise of ensuring the model convergence, so the convolution neural network framework is more adaptive to different heterogeneous system environments. The experimental results show that the proposed delay synchronization strategy can achieve at least three times the speedup compared to the traditional data parallelism.

  8. DIGITAL ONCOLOGY PATIENT RECORD - HETEROGENEOUS FILE BASED APPROACH

    Directory of Open Access Journals (Sweden)

    Nikolay Sapundzhiev

    2010-12-01

    Full Text Available Introduction: Oncology patients need extensive follow-up and meticulous documentation. The aim of this study was to introduce a simple, platform independent file based system for documentation of diagnostic and therapeutic procedures in oncology patients and test its function.Material and methods: A file-name based system of the type M1M2M3.F2 was introduced, where M1 is a unique identifier for the patient, M2 is the date of the clinical intervention/event, M3 is an identifier for the author of the medical record and F2 is the specific software generated file-name extension.Results: This system is in use at 5 institutions, where a total of 11 persons on 14 different workstations inputted 16591 entries (files for 2370. The merge process was tested on 2 operating systems - when copied together all files sort up as expected by patient, and for each patient in a chronological order, providing a digital cumulative patient record, which contains heterogeneous file formats.Conclusion: The file based approach for storing heterogeneous digital patient related information is an reliable system, which can handle open-source, proprietary, general and custom file formats and seems to be easily scalable. Further development of software for automatic checks of the integrity and searching and indexing of the files is expected to produce a more user-friendly environment

  9. Formation Learning Control of Multiple Autonomous Underwater Vehicles With Heterogeneous Nonlinear Uncertain Dynamics.

    Science.gov (United States)

    Yuan, Chengzhi; Licht, Stephen; He, Haibo

    2017-09-26

    In this paper, a new concept of formation learning control is introduced to the field of formation control of multiple autonomous underwater vehicles (AUVs), which specifies a joint objective of distributed formation tracking control and learning/identification of nonlinear uncertain AUV dynamics. A novel two-layer distributed formation learning control scheme is proposed, which consists of an upper-layer distributed adaptive observer and a lower-layer decentralized deterministic learning controller. This new formation learning control scheme advances existing techniques in three important ways: 1) the multi-AUV system under consideration has heterogeneous nonlinear uncertain dynamics; 2) the formation learning control protocol can be designed and implemented by each local AUV agent in a fully distributed fashion without using any global information; and 3) in addition to the formation control performance, the distributed control protocol is also capable of accurately identifying the AUVs' heterogeneous nonlinear uncertain dynamics and utilizing experiences to improve formation control performance. Extensive simulations have been conducted to demonstrate the effectiveness of the proposed results.

  10. Coordinated SLNR based Precoding in Large-Scale Heterogeneous Networks

    KAUST Repository

    Boukhedimi, Ikram; Kammoun, Abla; Alouini, Mohamed-Slim

    2017-01-01

    This work focuses on the downlink of large-scale two-tier heterogeneous networks composed of a macro-cell overlaid by micro-cell networks. Our interest is on the design of coordinated beamforming techniques that allow to mitigate the inter-cell interference. Particularly, we consider the case in which the coordinating base stations (BSs) have imperfect knowledge of the channel state information. Under this setting, we propose a regularized SLNR based precoding design in which the regularization factor is used to allow better resilience with respect to the channel estimation errors. Based on tools from random matrix theory, we provide an analytical analysis of the SINR and SLNR performances. These results are then exploited to propose a proper setting of the regularization factor. Simulation results are finally provided in order to validate our findings and to confirm the performance of the proposed precoding scheme.

  11. Coordinated SLNR based Precoding in Large-Scale Heterogeneous Networks

    KAUST Repository

    Boukhedimi, Ikram

    2017-03-06

    This work focuses on the downlink of large-scale two-tier heterogeneous networks composed of a macro-cell overlaid by micro-cell networks. Our interest is on the design of coordinated beamforming techniques that allow to mitigate the inter-cell interference. Particularly, we consider the case in which the coordinating base stations (BSs) have imperfect knowledge of the channel state information. Under this setting, we propose a regularized SLNR based precoding design in which the regularization factor is used to allow better resilience with respect to the channel estimation errors. Based on tools from random matrix theory, we provide an analytical analysis of the SINR and SLNR performances. These results are then exploited to propose a proper setting of the regularization factor. Simulation results are finally provided in order to validate our findings and to confirm the performance of the proposed precoding scheme.

  12. Meta-path based heterogeneous combat network link prediction

    Science.gov (United States)

    Li, Jichao; Ge, Bingfeng; Yang, Kewei; Chen, Yingwu; Tan, Yuejin

    2017-09-01

    The combat system-of-systems in high-tech informative warfare, composed of many interconnected combat systems of different types, can be regarded as a type of complex heterogeneous network. Link prediction for heterogeneous combat networks (HCNs) is of significant military value, as it facilitates reconfiguring combat networks to represent the complex real-world network topology as appropriate with observed information. This paper proposes a novel integrated methodology framework called HCNMP (HCN link prediction based on meta-path) to predict multiple types of links simultaneously for an HCN. More specifically, the concept of HCN meta-paths is introduced, through which the HCNMP can accumulate information by extracting different features of HCN links for all the six defined types. Next, an HCN link prediction model, based on meta-path features, is built to predict all types of links of the HCN simultaneously. Then, the solution algorithm for the HCN link prediction model is proposed, in which the prediction results are obtained by iteratively updating with the newly predicted results until the results in the HCN converge or reach a certain maximum iteration number. Finally, numerical experiments on the dataset of a real HCN are conducted to demonstrate the feasibility and effectiveness of the proposed HCNMP, in comparison with 30 baseline methods. The results show that the performance of the HCNMP is superior to those of the baseline methods.

  13. Experimental oligopolies modeling: A dynamic approach based on heterogeneous behaviors

    Science.gov (United States)

    Cerboni Baiardi, Lorenzo; Naimzada, Ahmad K.

    2018-05-01

    In the rank of behavioral rules, imitation-based heuristics has received special attention in economics (see [14] and [12]). In particular, imitative behavior is considered in order to understand the evidences arising in experimental oligopolies which reveal that the Cournot-Nash equilibrium does not emerge as unique outcome and show that an important component of the production at the competitive level is observed (see e.g.[1,3,9] or [7,10]). By considering the pioneering groundbreaking approach of [2], we build a dynamical model of linear oligopolies where heterogeneous decision mechanisms of players are made explicit. In particular, we consider two different types of quantity setting players characterized by different decision mechanisms that coexist and operate simultaneously: agents that adaptively adjust their choices towards the direction that increases their profit are embedded with imitator agents. The latter ones use a particular form of proportional imitation rule that considers the awareness about the presence of strategic interactions. It is noteworthy that the Cournot-Nash outcome is a stationary state of our models. Our thesis is that the chaotic dynamics arousing from a dynamical model, where heterogeneous players are considered, are capable to qualitatively reproduce the outcomes of experimental oligopolies.

  14. Arrester Resistive Current Measuring System Based on Heterogeneous Network

    Science.gov (United States)

    Zhang, Yun Hua; Li, Zai Lin; Yuan, Feng; Hou Pan, Feng; Guo, Zhan Nan; Han, Yue

    2018-03-01

    Metal Oxide Arrester (MOA) suffers from aging and poor insulation due to long-term impulse voltage and environmental impact, and the value and variation tendency of resistive current can reflect the health conditions of MOA. The common wired MOA detection need to use long cables, which is complicated to operate, and that wireless measurement methods are facing the problems of poor data synchronization and instability. Therefore a novel synchronous measurement system of arrester current resistive based on heterogeneous network is proposed, which simplifies the calculation process and improves synchronization, accuracy and stability and of the measuring system. This system combines LoRa wireless network, high speed wireless personal area network and the process layer communication, and realizes the detection of arrester working condition. Field test data shows that the system has the characteristics of high accuracy, strong anti-interference ability and good synchronization, which plays an important role in ensuring the stable operation of the power grid.

  15. Motion Learning Based on Bayesian Program Learning

    Directory of Open Access Journals (Sweden)

    Cheng Meng-Zhen

    2017-01-01

    Full Text Available The concept of virtual human has been highly anticipated since the 1980s. By using computer technology, Human motion simulation could generate authentic visual effect, which could cheat human eyes visually. Bayesian Program Learning train one or few motion data, generate new motion data by decomposing and combining. And the generated motion will be more realistic and natural than the traditional one.In this paper, Motion learning based on Bayesian program learning allows us to quickly generate new motion data, reduce workload, improve work efficiency, reduce the cost of motion capture, and improve the reusability of data.

  16. Spatial Heterogeneity of the Forest Canopy Scales with the Heterogeneity of an Understory Shrub Based on Fractal Analysis

    Directory of Open Access Journals (Sweden)

    Catherine K. Denny

    2017-04-01

    Full Text Available Spatial heterogeneity of vegetation is an important landscape characteristic, but is difficult to assess due to scale-dependence. Here we examine how spatial patterns in the forest canopy affect those of understory plants, using the shrub Canada buffaloberry (Shepherdia canadensis (L. Nutt. as a focal species. Evergreen and deciduous forest canopy and buffaloberry shrub presence were measured with line-intercept sampling along ten 2-km transects in the Rocky Mountain foothills of west-central Alberta, Canada. Relationships between overstory canopy and understory buffaloberry presence were assessed for scales ranging from 2 m to 502 m. Fractal dimensions of both canopy and buffaloberry were estimated and then related using box-counting methods to evaluate spatial heterogeneity based on patch distribution and abundance. Effects of canopy presence on buffaloberry were scale-dependent, with shrub presence negatively related to evergreen canopy cover and positively related to deciduous cover. The effect of evergreen canopy was significant at a local scale between 2 m and 42 m, while that of deciduous canopy was significant at a meso-scale between 150 m and 358 m. Fractal analysis indicated that buffaloberry heterogeneity positively scaled with evergreen canopy heterogeneity, but was unrelated to that of deciduous canopy. This study demonstrates that evergreen canopy cover is a determinant of buffaloberry heterogeneity, highlighting the importance of spatial scale and canopy composition in understanding canopy-understory relationships.

  17. Adaptive Load Balancing of Parallel Applications with Multi-Agent Reinforcement Learning on Heterogeneous Systems

    Directory of Open Access Journals (Sweden)

    Johan Parent

    2004-01-01

    Full Text Available We report on the improvements that can be achieved by applying machine learning techniques, in particular reinforcement learning, for the dynamic load balancing of parallel applications. The applications being considered in this paper are coarse grain data intensive applications. Such applications put high pressure on the interconnect of the hardware. Synchronization and load balancing in complex, heterogeneous networks need fast, flexible, adaptive load balancing algorithms. Viewing a parallel application as a one-state coordination game in the framework of multi-agent reinforcement learning, and by using a recently introduced multi-agent exploration technique, we are able to improve upon the classic job farming approach. The improvements are achieved with limited computation and communication overhead.

  18. Teaching Problem Based Learning as Blended Learning

    DEFF Research Database (Denmark)

    Kolbæk, Ditte; Nortvig, Anne-Mette

    2018-01-01

    Problem-based and project organized learning (PBL) was originally developed for collaboration between physically present students, but political decisions at many universities require that collaboration, dialogues, and other PBL activities take place online as well. With a theoretical point...... of departure in Dewey and a methodological point of departure in netnography, this study focuses on an online module at Aalborg University where teaching is based on PBL. With the research question ‘How can teachers design for PBL online,’ this study explores the teacher’s role in a six weeks’ blended learning...... program, and we present suggestions for designs for blended learning PBL based on case studies from two PBL courses...

  19. A resilient and efficient CFD framework: Statistical learning tools for multi-fidelity and heterogeneous information fusion

    Science.gov (United States)

    Lee, Seungjoon; Kevrekidis, Ioannis G.; Karniadakis, George Em

    2017-09-01

    Exascale-level simulations require fault-resilient algorithms that are robust against repeated and expected software and/or hardware failures during computations, which may render the simulation results unsatisfactory. If each processor can share some global information about the simulation from a coarse, limited accuracy but relatively costless auxiliary simulator we can effectively fill-in the missing spatial data at the required times by a statistical learning technique - multi-level Gaussian process regression, on the fly; this has been demonstrated in previous work [1]. Based on the previous work, we also employ another (nonlinear) statistical learning technique, Diffusion Maps, that detects computational redundancy in time and hence accelerate the simulation by projective time integration, giving the overall computation a "patch dynamics" flavor. Furthermore, we are now able to perform information fusion with multi-fidelity and heterogeneous data (including stochastic data). Finally, we set the foundations of a new framework in CFD, called patch simulation, that combines information fusion techniques from, in principle, multiple fidelity and resolution simulations (and even experiments) with a new adaptive timestep refinement technique. We present two benchmark problems (the heat equation and the Navier-Stokes equations) to demonstrate the new capability that statistical learning tools can bring to traditional scientific computing algorithms. For each problem, we rely on heterogeneous and multi-fidelity data, either from a coarse simulation of the same equation or from a stochastic, particle-based, more "microscopic" simulation. We consider, as such "auxiliary" models, a Monte Carlo random walk for the heat equation and a dissipative particle dynamics (DPD) model for the Navier-Stokes equations. More broadly, in this paper we demonstrate the symbiotic and synergistic combination of statistical learning, domain decomposition, and scientific computing in

  20. Cloud-Based Mobile Learning

    Directory of Open Access Journals (Sweden)

    Alexandru BUTOI

    2013-01-01

    Full Text Available As the cloud technologies are largely studied and mobile technologies are evolving, new di-rections for development of mobile learning tools deployed on cloud are proposed.. M-Learning is treated as part of the ubiquitous learning paradigm and is a pervasive extension of E-Learning technologies. Development of such learning tools requires specific development strategies for an effective abstracting of pedagogical principles at the software design and implementation level. Current paper explores an interdisciplinary approach for designing and development of cloud based M-Learning tools by mapping a specific development strategy used for educational programs to software prototyping strategy. In order for such instruments to be user effective from the learning outcome point of view, the evaluation process must be rigorous as we propose a metric model for expressing the trainee’s overall learning experience with evaluated levels of interactivity, content presentation and graphical user interface usability.

  1. TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

    OpenAIRE

    Abadi, Martín; Agarwal, Ashish; Barham, Paul; Brevdo, Eugene; Chen, Zhifeng; Citro, Craig; Corrado, Greg S.; Davis, Andy; Dean, Jeffrey; Devin, Matthieu; Ghemawat, Sanjay; Goodfellow, Ian; Harp, Andrew; Irving, Geoffrey; Isard, Michael

    2016-01-01

    TensorFlow is an interface for expressing machine learning algorithms, and an implementation for executing such algorithms. A computation expressed using TensorFlow can be executed with little or no change on a wide variety of heterogeneous systems, ranging from mobile devices such as phones and tablets up to large-scale distributed systems of hundreds of machines and thousands of computational devices such as GPU cards. The system is flexible and can be used to express a wide variety of algo...

  2. Research on distributed heterogeneous data PCA algorithm based on cloud platform

    Science.gov (United States)

    Zhang, Jin; Huang, Gang

    2018-05-01

    Principal component analysis (PCA) of heterogeneous data sets can solve the problem that centralized data scalability is limited. In order to reduce the generation of intermediate data and error components of distributed heterogeneous data sets, a principal component analysis algorithm based on heterogeneous data sets under cloud platform is proposed. The algorithm performs eigenvalue processing by using Householder tridiagonalization and QR factorization to calculate the error component of the heterogeneous database associated with the public key to obtain the intermediate data set and the lost information. Experiments on distributed DBM heterogeneous datasets show that the model method has the feasibility and reliability in terms of execution time and accuracy.

  3. Digital Microdroplet Ejection Technology-Based Heterogeneous Objects Prototyping

    OpenAIRE

    Li, Na; Yang, Jiquan; Feng, Chunmei; Yang, Jianfei; Zhu, Liya; Guo, Aiqing

    2016-01-01

    An integrate fabrication framework is presented to build heterogeneous objects (HEO) using digital microdroplets injecting technology and rapid prototyping. The heterogeneous materials part design and manufacturing method in structure and material was used to change the traditional process. The net node method was used for digital modeling that can configure multimaterials in time. The relationship of material, color, and jetting nozzle was built. The main important contributions are to combi...

  4. Problem Based Learning Online

    DEFF Research Database (Denmark)

    Kolbæk, Ditte

    2018-01-01

    “How do two online learning designs affect student engagement in the PBL online modules?” The empirical data were collected and analyzed using a netnographic approach. The study finds that concepts such as self-directed learning and active involvement may be perceived very differently from the students...

  5. Dimensions of problem based learning

    DEFF Research Database (Denmark)

    Nielsen, Jørgen Lerche; Andreasen, Lars Birch

    2013-01-01

    The article contributes to the literature on problem based learning and problem-oriented project work, building on and reflecting the experiences of the authors through decades of work with problem-oriented project pedagogy. The article explores different dimensions of problem based learning such...... and Learning (MIL). We discuss changes in the roles of the teachers as supervisors within this learning environment, and we explore the involvement of students as active participants and co-designers of how course and project activities unfold....

  6. Interfacial mechanisms of heterogeneous Fenton reactions catalyzed by iron-based materials: A review.

    Science.gov (United States)

    He, Jie; Yang, Xiaofang; Men, Bin; Wang, Dongsheng

    2016-01-01

    The heterogeneous Fenton reaction can generate highly reactive hydroxyl radicals (OH) from reactions between recyclable solid catalysts and H2O2 at acidic or even circumneutral pH. Hence, it can effectively oxidize refractory organics in water or soils and has become a promising environmentally friendly treatment technology. Due to the complex reaction system, the mechanism behind heterogeneous Fenton reactions remains unresolved but fascinating, and is crucial for understanding Fenton chemistry and the development and application of efficient heterogeneous Fenton technologies. Iron-based materials usually possess high catalytic activity, low cost, negligible toxicity and easy recovery, and are a superior type of heterogeneous Fenton catalysts. Therefore, this article reviews the fundamental but important interfacial mechanisms of heterogeneous Fenton reactions catalyzed by iron-based materials. OH, hydroperoxyl radicals/superoxide anions (HO2/O2(-)) and high-valent iron are the three main types of reactive oxygen species (ROS), with different oxidation reactivity and selectivity. Based on the mechanisms of ROS generation, the interfacial mechanisms of heterogeneous Fenton systems can be classified as the homogeneous Fenton mechanism induced by surface-leached iron, the heterogeneous catalysis mechanism, and the heterogeneous reaction-induced homogeneous mechanism. Different heterogeneous Fenton systems catalyzed by characteristic iron-based materials are comprehensively reviewed. Finally, related future research directions are also suggested. Copyright © 2015. Published by Elsevier B.V.

  7. Thesaurus-based search in large heterogeneous collections

    NARCIS (Netherlands)

    Wielemaker, J.; Hildebrand, M.; van Ossenbruggen, J.; Schreiber, G.

    2008-01-01

    In cultural heritage, large virtual collections are coming into existence. Such collections contain heterogeneous sets of metadata and vocabulary concepts, originating from multiple sources. In the context of the E-Culture demonstrator we have shown earlier that such virtual collections can be

  8. Thesaurus-based search in large heterogeneous collections

    NARCIS (Netherlands)

    J. Wielemaker (Jan); M. Hildebrand (Michiel); J.R. van Ossenbruggen (Jacco); G. Schreiber (Guus); A. Sheth; not CWI et al

    2008-01-01

    htmlabstractIn cultural heritage, large virtual collections are coming into existence. Such collections contain heterogeneous sets of metadata and vocabulary concepts, originating from multiple sources. In the context of the E-Culture demonstrator we have shown earlier that such virtual

  9. Conceptualizing a tool to optimize therapy based on dynamic heterogeneity

    International Nuclear Information System (INIS)

    Liao, David; Estévez-Salmerón, Luis; Tlsty, Thea D

    2012-01-01

    Complex biological systems often display a randomness paralleled in processes studied in fundamental physics. This simple stochasticity emerges owing to the complexity of the system and underlies a fundamental aspect of biology called phenotypic stochasticity. Ongoing stochastic fluctuations in phenotype at the single-unit level can contribute to two emergent population phenotypes. Phenotypic stochasticity not only generates heterogeneity within a cell population, but also allows reversible transitions back and forth between multiple states. This phenotypic interconversion tends to restore a population to a previous composition after that population has been depleted of specific members. We call this tendency homeostatic heterogeneity. These concepts of dynamic heterogeneity can be applied to populations composed of molecules, cells, individuals, etc. Here we discuss the concept that phenotypic stochasticity both underlies the generation of heterogeneity within a cell population and can be used to control population composition, contributing, in particular, to both the ongoing emergence of drug resistance and an opportunity for depleting drug-resistant cells. Using notions of both ‘large’ and ‘small’ numbers of biomolecular components, we rationalize our use of Markov processes to model the generation and eradication of drug-resistant cells. Using these insights, we have developed a graphical tool, called a metronomogram, that we propose will allow us to optimize dosing frequencies and total course durations for clinical benefit. (paper)

  10. Cluster-based service discovery for heterogeneous wireless sensor networks

    NARCIS (Netherlands)

    Marin Perianu, Raluca; Scholten, Johan; Havinga, Paul J.M.; Hartel, Pieter H.

    2007-01-01

    We propose an energy-efficient service discovery protocol for heterogeneous wireless sensor networks. Our solution exploits a cluster overlay, where the clusterhead nodes form a distributed service registry. A service lookup results in visiting only the clusterhead nodes. We aim for minimizing the

  11. Heterogeneity in Perceptual Category Learning by High Functioning Children with Autism Spectrum Disorder

    Directory of Open Access Journals (Sweden)

    Eduardo eMercado

    2015-06-01

    Full Text Available Previous research suggests that high functioning children with Autism Spectrum Disorder (ASD sometimes have problems learning categories, but often appear to perform normally in categorization tasks. The deficits that individuals with ASD show when learning categories have been attributed to executive dysfunction, general deficits in implicit learning, atypical cognitive strategies, or abnormal perceptual biases and abilities. Several of these psychological explanations for category learning deficits have been associated with neural abnormalities such as cortical underconnectivity. The present study evaluated how well existing neurally-based theories account for atypical perceptual category learning shown by high functioning children with ASD across multiple category learning tasks involving novel, abstract shapes. Consistent with earlier results, children’s performances revealed two distinct patterns of learning and generalization associated with ASD: one was indistinguishable from performance in typically developing children; the other revealed dramatic impairments. These two patterns were evident regardless of training regimen or stimulus set. Surprisingly, some children with ASD showed both patterns. Simulations of perceptual category learning could account for the two observed patterns in terms of differences in neural plasticity. However, no current psychological or neural theory adequately explains why a child with ASD might show such large fluctuations in category learning ability across training conditions or stimulus sets.

  12. Heterogeneity in perceptual category learning by high functioning children with autism spectrum disorder.

    Science.gov (United States)

    Mercado, Eduardo; Church, Barbara A; Coutinho, Mariana V C; Dovgopoly, Alexander; Lopata, Christopher J; Toomey, Jennifer A; Thomeer, Marcus L

    2015-01-01

    Previous research suggests that high functioning (HF) children with autism spectrum disorder (ASD) sometimes have problems learning categories, but often appear to perform normally in categorization tasks. The deficits that individuals with ASD show when learning categories have been attributed to executive dysfunction, general deficits in implicit learning, atypical cognitive strategies, or abnormal perceptual biases and abilities. Several of these psychological explanations for category learning deficits have been associated with neural abnormalities such as cortical underconnectivity. The present study evaluated how well existing neurally based theories account for atypical perceptual category learning shown by HF children with ASD across multiple category learning tasks involving novel, abstract shapes. Consistent with earlier results, children's performances revealed two distinct patterns of learning and generalization associated with ASD: one was indistinguishable from performance in typically developing children; the other revealed dramatic impairments. These two patterns were evident regardless of training regimen or stimulus set. Surprisingly, some children with ASD showed both patterns. Simulations of perceptual category learning could account for the two observed patterns in terms of differences in neural plasticity. However, no current psychological or neural theory adequately explains why a child with ASD might show such large fluctuations in category learning ability across training conditions or stimulus sets.

  13. Learning second language vocabulary: neural dissociation of situation-based learning and text-based learning.

    Science.gov (United States)

    Jeong, Hyeonjeong; Sugiura, Motoaki; Sassa, Yuko; Wakusawa, Keisuke; Horie, Kaoru; Sato, Shigeru; Kawashima, Ryuta

    2010-04-01

    Second language (L2) acquisition necessitates learning and retrieving new words in different modes. In this study, we attempted to investigate the cortical representation of an L2 vocabulary acquired in different learning modes and in cross-modal transfer between learning and retrieval. Healthy participants learned new L2 words either by written translations (text-based learning) or in real-life situations (situation-based learning). Brain activity was then measured during subsequent retrieval of these words. The right supramarginal gyrus and left middle frontal gyrus were involved in situation-based learning and text-based learning, respectively, whereas the left inferior frontal gyrus was activated when learners used L2 knowledge in a mode different from the learning mode. Our findings indicate that the brain regions that mediate L2 memory differ according to how L2 words are learned and used. Copyright 2009 Elsevier Inc. All rights reserved.

  14. CLASS-PAIR-GUIDED MULTIPLE KERNEL LEARNING OF INTEGRATING HETEROGENEOUS FEATURES FOR CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    Q. Wang

    2017-10-01

    Full Text Available In recent years, many studies on remote sensing image classification have shown that using multiple features from different data sources can effectively improve the classification accuracy. As a very powerful means of learning, multiple kernel learning (MKL can conveniently be embedded in a variety of characteristics. The conventional combined kernel learned by MKL can be regarded as the compromise of all basic kernels for all classes in classification. It is the best of the whole, but not optimal for each specific class. For this problem, this paper proposes a class-pair-guided MKL method to integrate the heterogeneous features (HFs from multispectral image (MSI and light detection and ranging (LiDAR data. In particular, the one-against-one strategy is adopted, which converts multiclass classification problem to a plurality of two-class classification problem. Then, we select the best kernel from pre-constructed basic kernels set for each class-pair by kernel alignment (KA in the process of classification. The advantage of the proposed method is that only the best kernel for the classification of any two classes can be retained, which leads to greatly enhanced discriminability. Experiments are conducted on two real data sets, and the experimental results show that the proposed method achieves the best performance in terms of classification accuracies in integrating the HFs for classification when compared with several state-of-the-art algorithms.

  15. Heterogeneous Catalysis of Polyoxometalate Based Organic–Inorganic Hybrids

    Directory of Open Access Journals (Sweden)

    Yuanhang Ren

    2015-03-01

    Full Text Available Organic–inorganic hybrid polyoxometalate (POM compounds are a subset of materials with unique structures and physical/chemical properties. The combination of metal-organic coordination complexes with classical POMs not only provides a powerful way to gain multifarious new compounds but also affords a new method to modify and functionalize POMs. In parallel with the many reports on the synthesis and structure of new hybrid POM compounds, the application of these compounds for heterogeneous catalysis has also attracted considerable attention. The hybrid POM compounds show noteworthy catalytic performance in acid, oxidation, and even in asymmetric catalytic reactions. This review summarizes the design and synthesis of organic–inorganic hybrid POM compounds and particularly highlights their recent progress in heterogeneous catalysis.

  16. Digital Microdroplet Ejection Technology-Based Heterogeneous Objects Prototyping

    Science.gov (United States)

    Yang, Jiquan; Feng, Chunmei; Yang, Jianfei; Zhu, Liya; Guo, Aiqing

    2016-01-01

    An integrate fabrication framework is presented to build heterogeneous objects (HEO) using digital microdroplets injecting technology and rapid prototyping. The heterogeneous materials part design and manufacturing method in structure and material was used to change the traditional process. The net node method was used for digital modeling that can configure multimaterials in time. The relationship of material, color, and jetting nozzle was built. The main important contributions are to combine the structure, material, and visualization in one process and give the digital model for manufacture. From the given model, it is concluded that the method is effective for HEO. Using microdroplet rapid prototyping and the model given in the paper HEO could be gotten basically. The model could be used in 3D biomanufacturing. PMID:26981110

  17. Digital Microdroplet Ejection Technology-Based Heterogeneous Objects Prototyping.

    Science.gov (United States)

    Li, Na; Yang, Jiquan; Feng, Chunmei; Yang, Jianfei; Zhu, Liya; Guo, Aiqing

    2016-01-01

    An integrate fabrication framework is presented to build heterogeneous objects (HEO) using digital microdroplets injecting technology and rapid prototyping. The heterogeneous materials part design and manufacturing method in structure and material was used to change the traditional process. The net node method was used for digital modeling that can configure multimaterials in time. The relationship of material, color, and jetting nozzle was built. The main important contributions are to combine the structure, material, and visualization in one process and give the digital model for manufacture. From the given model, it is concluded that the method is effective for HEO. Using microdroplet rapid prototyping and the model given in the paper HEO could be gotten basically. The model could be used in 3D biomanufacturing.

  18. Digital Microdroplet Ejection Technology-Based Heterogeneous Objects Prototyping

    Directory of Open Access Journals (Sweden)

    Na Li

    2016-01-01

    Full Text Available An integrate fabrication framework is presented to build heterogeneous objects (HEO using digital microdroplets injecting technology and rapid prototyping. The heterogeneous materials part design and manufacturing method in structure and material was used to change the traditional process. The net node method was used for digital modeling that can configure multimaterials in time. The relationship of material, color, and jetting nozzle was built. The main important contributions are to combine the structure, material, and visualization in one process and give the digital model for manufacture. From the given model, it is concluded that the method is effective for HEO. Using microdroplet rapid prototyping and the model given in the paper HEO could be gotten basically. The model could be used in 3D biomanufacturing.

  19. Heterogeneity Measurement Based on Distance Measure for Polarimetric SAR Data

    Science.gov (United States)

    Xing, Xiaoli; Chen, Qihao; Liu, Xiuguo

    2018-04-01

    To effectively test the scene heterogeneity for polarimetric synthetic aperture radar (PolSAR) data, in this paper, the distance measure is introduced by utilizing the similarity between the sample and pixels. Moreover, given the influence of the distribution and modeling texture, the K distance measure is deduced according to the Wishart distance measure. Specifically, the average of the pixels in the local window replaces the class center coherency or covariance matrix. The Wishart and K distance measure are calculated between the average matrix and the pixels. Then, the ratio of the standard deviation to the mean is established for the Wishart and K distance measure, and the two features are defined and applied to reflect the complexity of the scene. The proposed heterogeneity measure is proceeded by integrating the two features using the Pauli basis. The experiments conducted on the single-look and multilook PolSAR data demonstrate the effectiveness of the proposed method for the detection of the scene heterogeneity.

  20. Model-based machine learning.

    Science.gov (United States)

    Bishop, Christopher M

    2013-02-13

    Several decades of research in the field of machine learning have resulted in a multitude of different algorithms for solving a broad range of problems. To tackle a new application, a researcher typically tries to map their problem onto one of these existing methods, often influenced by their familiarity with specific algorithms and by the availability of corresponding software implementations. In this study, we describe an alternative methodology for applying machine learning, in which a bespoke solution is formulated for each new application. The solution is expressed through a compact modelling language, and the corresponding custom machine learning code is then generated automatically. This model-based approach offers several major advantages, including the opportunity to create highly tailored models for specific scenarios, as well as rapid prototyping and comparison of a range of alternative models. Furthermore, newcomers to the field of machine learning do not have to learn about the huge range of traditional methods, but instead can focus their attention on understanding a single modelling environment. In this study, we show how probabilistic graphical models, coupled with efficient inference algorithms, provide a very flexible foundation for model-based machine learning, and we outline a large-scale commercial application of this framework involving tens of millions of users. We also describe the concept of probabilistic programming as a powerful software environment for model-based machine learning, and we discuss a specific probabilistic programming language called Infer.NET, which has been widely used in practical applications.

  1. Policy-Based mobility Management for Heterogeneous Networks

    DEFF Research Database (Denmark)

    Mihovska, Albena D.

    2007-01-01

    Next generation communications will be composed of flexible, scalable and context-aware, secure and resilient architectures and technologies that allow full mobility of the user and enable dynamic management policies that ensure end-to-end secure transmission of data and services across heterogen......Next generation communications will be composed of flexible, scalable and context-aware, secure and resilient architectures and technologies that allow full mobility of the user and enable dynamic management policies that ensure end-to-end secure transmission of data and services across...... access technology (RAT) association, user and flow context transfer, handover decision, and deployment priority. Index Terms— distributed RRM, centralized...

  2. Distribution of model-based multipoint heterogeneity lod scores.

    Science.gov (United States)

    Xing, Chao; Morris, Nathan; Xing, Guan

    2010-12-01

    The distribution of two-point heterogeneity lod scores (HLOD) has been intensively investigated because the conventional χ(2) approximation to the likelihood ratio test is not directly applicable. However, there was no study investigating th e distribution of the multipoint HLOD despite its wide application. Here we want to point out that, compared with the two-point HLOD, the multipoint HLOD essentially tests for homogeneity given linkage and follows a relatively simple limiting distribution ½χ²₀+ ½χ²₁, which can be obtained by established statistical theory. We further examine the theoretical result by simulation studies. © 2010 Wiley-Liss, Inc.

  3. Heterogeneity, histological features and DNA ploidy in oral carcinoma by image-based analysis.

    Science.gov (United States)

    Diwakar, N; Sperandio, M; Sherriff, M; Brown, A; Odell, E W

    2005-04-01

    Oral squamous carcinomas appear heterogeneous on DNA ploidy analysis. However, this may be partly a result of sample dilution or the detection limit of techniques. The aim of this study was to determine whether oral squamous carcinomas are heterogeneous for ploidy status using image-based ploidy analysis and to determine whether ploidy status correlates with histological parameters. Multiple samples from 42 oral squamous carcinomas were analysed for DNA ploidy using an image-based system and scored for histological parameters. 22 were uniformly aneuploid, 1 uniformly tetraploid and 3 uniformly diploid. 16 appeared heterogeneous but only 8 appeared to be genuinely heterogeneous when minor ploidy histogram peaks were taken into account. Ploidy was closely related to nuclear pleomorphism but not differentiation. Sample variation, detection limits and diagnostic criteria account for much of the ploidy heterogeneity observed. Confident diagnosis of diploid status in an oral squamous cell carcinoma requires a minimum of 5 samples.

  4. Group Formation Based on Learning Styles: Can It Improve Students' Teamwork?

    Science.gov (United States)

    Kyprianidou, Maria; Demetriadis, Stavros; Tsiatsos, Thrasyvoulos; Pombortsis, Andreas

    2012-01-01

    This work explores the impact of teacher-led heterogeneous group formation on students' teamwork, based on students' learning styles. Fifty senior university students participated in a project-based course with two key organizational features: first, a web system (PEGASUS) was developed to help students identify their learning styles and…

  5. SDN Based User-Centric Framework for Heterogeneous Wireless Networks

    Directory of Open Access Journals (Sweden)

    Zhaoming Lu

    2016-01-01

    Full Text Available Due to the rapid growth of mobile data traffic, more and more basestations and access points (APs have been densely deployed to provide users with ubiquitous network access, which make current wireless network a complex heterogeneous network (HetNet. However, traditional wireless networks are designed with network-centric approaches where different networks have different quality of service (QoS strategies and cannot easily cooperate with each other to serve network users. Massive network infrastructures could not assure users perceived network and service quality, which is an indisputable fact. To address this issue, we design a new framework for heterogeneous wireless networks with the principle of user-centricity, refactoring the network from users’ perspective to suffice their requirements and preferences. Different from network-centric approaches, the proposed framework takes advantage of Software Defined Networking (SDN and virtualization technology, which will bring better perceived services quality for wireless network users. In the proposed user-centric framework, control plane and data plane are decoupled to manage the HetNets in a flexible and coadjutant way, and resource virtualization technology is introduced to abstract physical resources of HetNets into unified virtualized resources. Hence, ubiquitous and undifferentiated network connectivity and QoE (quality of experience driven fine-grained resource management could be achieved for wireless network users.

  6. Connexin-based intercellular communication and astrocyte heterogeneity.

    Science.gov (United States)

    Theis, Martin; Giaume, Christian

    2012-12-03

    This review gives an overview of the current knowledge on connexin-mediated communication in astrocytes, covering gap junction and hemichannel functions mediated by connexins. Astroglia is the main brain cell type that expresses the largest amount of connexin and exhibits high level of gap junctional communication compared to neurons and oligodendrocytes. However, in certain developmental and regional situations, astrocytes are also coupled with oligodendrocytes and neurons. This heterotypic coupling is infrequent and minor in terms of extent of the coupling area, which does not mean that it is not important in terms of cell interaction. Here, we present an update on heterogeneity of connexin expression and function at the molecular, subcellular, cellular and networking levels. Interestingly, while astrocytes were initially considered as a homogenous population, there is now increasing evidence for morphological, developmental, molecular and physiological heterogeneity of astrocytes. Consequently, the specificity of gap junction channel- and hemichannel-mediated communication, which tends to synchronize cell populations, is also a parameter to take into account when neuroglial interactions are investigated. This article is part of a Special Issue entitled Electrical Synapses. Copyright © 2012 Elsevier B.V. All rights reserved.

  7. An Erbium-Based Bifuctional Heterogeneous Catalyst: A Cooperative Route Towards C-C Bond Formation

    Directory of Open Access Journals (Sweden)

    Manuela Oliverio

    2014-07-01

    Full Text Available Heterogeneous bifuctional catalysts are multifunctional synthetic catalysts enabling efficient organic transformations by exploiting two opposite functionalities without mutual destruction. In this paper we report the first Er(III-based metallorganic heterogeneous catalyst, synthesized by post-calcination MW-assisted grafting and modification of the natural aminoacid L-cysteine. The natural acid–base distance between sites was maintained to assure the cooperation. The applicability of this new bifunctional heterogeneous catalyst to C-C bond formation and the supposed mechanisms of action are discussed as well.

  8. Consensus of heterogeneous multi-agent systems based on sampled data with a small sampling delay

    International Nuclear Information System (INIS)

    Wang Na; Wu Zhi-Hai; Peng Li

    2014-01-01

    In this paper, consensus problems of heterogeneous multi-agent systems based on sampled data with a small sampling delay are considered. First, a consensus protocol based on sampled data with a small sampling delay for heterogeneous multi-agent systems is proposed. Then, the algebra graph theory, the matrix method, the stability theory of linear systems, and some other techniques are employed to derive the necessary and sufficient conditions guaranteeing heterogeneous multi-agent systems to asymptotically achieve the stationary consensus. Finally, simulations are performed to demonstrate the correctness of the theoretical results. (interdisciplinary physics and related areas of science and technology)

  9. Modified silica-based heterogeneous catalysts for etherification of glycerol

    Energy Technology Data Exchange (ETDEWEB)

    Gholami, Zahra, E-mail: zahra.gholami@petronas.com.my [Centralized Analytical Laboratory, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 31750 Tronoh, Perak (Malaysia); Abdullah, Ahmad Zuhairi, E-mail: chzuhairi@usm.my; Gholami, Fatemeh, E-mail: fgholami59@gmail.com [School of Chemical Engineering, Universiti Sains Malaysia, Engineering Campus,14300 Nibong Tebal, Penang (Malaysia); Vakili, Mohammadtaghi, E-mail: farshid3601@gmail.com [School of Industrial Technology, Universiti Sains Malaysia, 11800 Penang (Malaysia)

    2015-07-22

    The advent of mesoporous silicas such as MCM-41 has provided new opportunities for research into supported metal catalysis. The loading of metals into framework structures and particularly into the pores of porous molecular sieves, has long been of interest because of their potential catalytic activity. Stable heterogeneous mesoporous basic catalysts were synthesized by wet impregnation of MCM-41 with calcium nitrate and lanthanum nitrate. The surface and structural properties of the prepared catalysts were characterized using BET surface analysis, SEM and TEM. MCM-41 and modified MCM-41 were used in the solventless etherification of glycerol to produce diglycerol as the desired product. The reaction was performed at 250 °C for 8 h, and catalyst activity was evaluated. Catalytic etherification over the 20%Ca{sub 1.6}La{sub 0.6}/MCM-41 catalyst resulted in the highest glycerol conversion of 91% and diglycerol yield of 43%.

  10. Stylized facts from a threshold-based heterogeneous agent model

    Science.gov (United States)

    Cross, R.; Grinfeld, M.; Lamba, H.; Seaman, T.

    2007-05-01

    A class of heterogeneous agent models is investigated where investors switch trading position whenever their motivation to do so exceeds some critical threshold. These motivations can be psychological in nature or reflect behaviour suggested by the efficient market hypothesis (EMH). By introducing different propensities into a baseline model that displays EMH behaviour, one can attempt to isolate their effects upon the market dynamics. The simulation results indicate that the introduction of a herding propensity results in excess kurtosis and power-law decay consistent with those observed in actual return distributions, but not in significant long-term volatility correlations. Possible alternatives for introducing such long-term volatility correlations are then identified and discussed.

  11. Modified silica-based heterogeneous catalysts for etherification of glycerol

    International Nuclear Information System (INIS)

    Gholami, Zahra; Abdullah, Ahmad Zuhairi; Gholami, Fatemeh; Vakili, Mohammadtaghi

    2015-01-01

    The advent of mesoporous silicas such as MCM-41 has provided new opportunities for research into supported metal catalysis. The loading of metals into framework structures and particularly into the pores of porous molecular sieves, has long been of interest because of their potential catalytic activity. Stable heterogeneous mesoporous basic catalysts were synthesized by wet impregnation of MCM-41 with calcium nitrate and lanthanum nitrate. The surface and structural properties of the prepared catalysts were characterized using BET surface analysis, SEM and TEM. MCM-41 and modified MCM-41 were used in the solventless etherification of glycerol to produce diglycerol as the desired product. The reaction was performed at 250 °C for 8 h, and catalyst activity was evaluated. Catalytic etherification over the 20%Ca 1.6 La 0.6 /MCM-41 catalyst resulted in the highest glycerol conversion of 91% and diglycerol yield of 43%

  12. Heterogeneity wavelet kinetics from DCE-MRI for classifying gene expression based breast cancer recurrence risk.

    Science.gov (United States)

    Mahrooghy, Majid; Ashraf, Ahmed B; Daye, Dania; Mies, Carolyn; Feldman, Michael; Rosen, Mark; Kontos, Despina

    2013-01-01

    Breast tumors are heterogeneous lesions. Intra-tumor heterogeneity presents a major challenge for cancer diagnosis and treatment. Few studies have worked on capturing tumor heterogeneity from imaging. Most studies to date consider aggregate measures for tumor characterization. In this work we capture tumor heterogeneity by partitioning tumor pixels into subregions and extracting heterogeneity wavelet kinetic (HetWave) features from breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to obtain the spatiotemporal patterns of the wavelet coefficients and contrast agent uptake from each partition. Using a genetic algorithm for feature selection, and a logistic regression classifier with leave one-out cross validation, we tested our proposed HetWave features for the task of classifying breast cancer recurrence risk. The classifier based on our features gave an ROC AUC of 0.78, outperforming previously proposed kinetic, texture, and spatial enhancement variance features which give AUCs of 0.69, 0.64, and 0.65, respectively.

  13. Image-based computational quantification and visualization of genetic alterations and tumour heterogeneity.

    Science.gov (United States)

    Zhong, Qing; Rüschoff, Jan H; Guo, Tiannan; Gabrani, Maria; Schüffler, Peter J; Rechsteiner, Markus; Liu, Yansheng; Fuchs, Thomas J; Rupp, Niels J; Fankhauser, Christian; Buhmann, Joachim M; Perner, Sven; Poyet, Cédric; Blattner, Miriam; Soldini, Davide; Moch, Holger; Rubin, Mark A; Noske, Aurelia; Rüschoff, Josef; Haffner, Michael C; Jochum, Wolfram; Wild, Peter J

    2016-04-07

    Recent large-scale genome analyses of human tissue samples have uncovered a high degree of genetic alterations and tumour heterogeneity in most tumour entities, independent of morphological phenotypes and histopathological characteristics. Assessment of genetic copy-number variation (CNV) and tumour heterogeneity by fluorescence in situ hybridization (ISH) provides additional tissue morphology at single-cell resolution, but it is labour intensive with limited throughput and high inter-observer variability. We present an integrative method combining bright-field dual-colour chromogenic and silver ISH assays with an image-based computational workflow (ISHProfiler), for accurate detection of molecular signals, high-throughput evaluation of CNV, expressive visualization of multi-level heterogeneity (cellular, inter- and intra-tumour heterogeneity), and objective quantification of heterogeneous genetic deletions (PTEN) and amplifications (19q12, HER2) in diverse human tumours (prostate, endometrial, ovarian and gastric), using various tissue sizes and different scanners, with unprecedented throughput and reproducibility.

  14. Characteristics of Problem-Based Learning

    DEFF Research Database (Denmark)

    Kolmos, Anette

    2003-01-01

    Problem BAsed LEarning (PBL) is widely regarded as a successful and innovative method for engineering education. The article highlights the Dutch approach of directing the learning process throuogh problem analysis and the Danish model of project-organised learning...

  15. Activities of Heterogeneous Acid-Base Catalysts for Fragrances Synthesis: A Review

    Directory of Open Access Journals (Sweden)

    Hartati Hartati

    2013-06-01

    Full Text Available This paper reviews various types of heterogeneous acid-base catalysts for fragrances preparation. Catalytic activities of various types of heterogeneous acid and base catalysts in fragrances preparation, i.e. non-zeolitic, zeolitic, and mesoporous molecular sieves have been reported. Generally, heterogeneous acid catalysts are commonly used in fragrance synthesis as compared to heterogeneous base catalysts. Heteropoly acids and hydrotalcites type catalysts are widely used as heterogeneous acid and base catalysts, respectively. © 2013 BCREC UNDIP. All rights reservedReceived: 20th January 2013; Revised: 31st March 2013; Accepted: 1st April 2013[How to Cite: Hartati, H., Santoso, M., Triwahyono, S., Prasetyoko, D. (2013. Activities of Heterogeneous Acid-Base Catalysts for Fragrances Synthesis: A Review. Bulletin of Chemical Reaction Engineering & Catalysis, 8 (1: 14-33. (doi:10.9767/bcrec.8.1.4394.14-33][Permalink/DOI: http://dx.doi.org/10.9767/bcrec.8.1.4394.14-33] | View in  |

  16. DEMARCATE: Density-based magnetic resonance image clustering for assessing tumor heterogeneity in cancer.

    Science.gov (United States)

    Saha, Abhijoy; Banerjee, Sayantan; Kurtek, Sebastian; Narang, Shivali; Lee, Joonsang; Rao, Ganesh; Martinez, Juan; Bharath, Karthik; Rao, Arvind U K; Baladandayuthapani, Veerabhadran

    2016-01-01

    Tumor heterogeneity is a crucial area of cancer research wherein inter- and intra-tumor differences are investigated to assess and monitor disease development and progression, especially in cancer. The proliferation of imaging and linked genomic data has enabled us to evaluate tumor heterogeneity on multiple levels. In this work, we examine magnetic resonance imaging (MRI) in patients with brain cancer to assess image-based tumor heterogeneity. Standard approaches to this problem use scalar summary measures (e.g., intensity-based histogram statistics) that do not adequately capture the complete and finer scale information in the voxel-level data. In this paper, we introduce a novel technique, DEMARCATE (DEnsity-based MAgnetic Resonance image Clustering for Assessing Tumor hEterogeneity) to explore the entire tumor heterogeneity density profiles (THDPs) obtained from the full tumor voxel space. THDPs are smoothed representations of the probability density function of the tumor images. We develop tools for analyzing such objects under the Fisher-Rao Riemannian framework that allows us to construct metrics for THDP comparisons across patients, which can be used in conjunction with standard clustering approaches. Our analyses of The Cancer Genome Atlas (TCGA) based Glioblastoma dataset reveal two significant clusters of patients with marked differences in tumor morphology, genomic characteristics and prognostic clinical outcomes. In addition, we see enrichment of image-based clusters with known molecular subtypes of glioblastoma multiforme, which further validates our representation of tumor heterogeneity and subsequent clustering techniques.

  17. Friendship-based partner switching promotes cooperation in heterogeneous populations

    Science.gov (United States)

    Chen, Wei; Wu, Te; Li, Zhiwu; Wang, Long

    2016-02-01

    The forming of human social ties tends to be with similar individuals. This study concentrates on the emergence of cooperation among heterogeneous populations. A simple model is proposed by considering the impact of interplay between the evolution of strategies and that of social partnerships on cooperation dynamics. Whenever two individuals acquire the rewards by playing prisoner's dilemma game with each other, the friendship (friendship is quantified as the weight of a link) between the two individuals deepens. Individuals can switch off the social ties with the partners who are unfriendly and rewire to similar new ones. Under this partner switching mechanism, population structure is divided into several groups and cooperation can prevail. It is observed that the frequent tendency of partner switching can lead to the enhancement of cooperative behavior under the enormous temptation to defect. Moreover, the influence of discounting the relationship between different individuals is also investigated. Meanwhile, the cooperation prevails when the adjustment of friendships mainly depends on the incomes of selected individuals rather than that of their partners. Finally, it is found that too similar population fail to maximize the cooperation and there exists a moderate similarity that can optimize cooperation.

  18. Collaborative Inquiry-based Learning

    NARCIS (Netherlands)

    Suarez, Angel

    2017-01-01

    This thesis presents the results of the conducted research and development of applications to support collaborative inquiry-based learning, with a special focus on leveraging learners’ agency. The reported results are structured into three parts: the theoretical foundations, the design and

  19. Web-Based Instruction, Learning Effectiveness and Learning Behavior: The Impact of Relatedness

    Science.gov (United States)

    Shieh, Chich-Jen; Liao, Ying; Hu, Ridong

    2013-01-01

    This study aims to discuss the effects of Web-based Instruction and Learning Behavior on Learning Effectiveness. Web-based Instruction contains the dimensions of Active Learning, Simulation-based Learning, Interactive Learning, and Accumulative Learning; and, Learning Behavior covers Learning Approach, Learning Habit, and Learning Attitude. The…

  20. Learning Object Retrieval and Aggregation Based on Learning Styles

    Science.gov (United States)

    Ramirez-Arellano, Aldo; Bory-Reyes, Juan; Hernández-Simón, Luis Manuel

    2017-01-01

    The main goal of this article is to develop a Management System for Merging Learning Objects (msMLO), which offers an approach that retrieves learning objects (LOs) based on students' learning styles and term-based queries, which produces a new outcome with a better score. The msMLO faces the task of retrieving LOs via two steps: The first step…

  1. Consumer Product Perceptions and Salmon Consumption Frequency: The Role of Heterogeneity Based on Food Lifestyle Segments

    OpenAIRE

    Yuko Onozaka; Håvard Hansen; Arne Sørvig

    2014-01-01

    Seafood consumers are vastly heterogeneous in terms of their knowledge, confidence, and perceptions about seafood. This article examines the relationship between consumer perceptions (healthiness, value for money, and convenience) and salmon consumption frequencies while modeling unobserved consumer heterogeneity by segmenting consumers based on their food-related lifestyle. We employ latent class analysis (LCA) that embeds the structural equation modeling (SEM) to ensure the latent nature of...

  2. Improving Collaborative Learning in the Classroom: Text Mining Based Grouping and Representing

    Science.gov (United States)

    Erkens, Melanie; Bodemer, Daniel; Hoppe, H. Ulrich

    2016-01-01

    Orchestrating collaborative learning in the classroom involves tasks such as forming learning groups with heterogeneous knowledge and making learners aware of the knowledge differences. However, gathering information on which the formation of appropriate groups and the creation of graphical knowledge representations can be based is very effortful…

  3. Agent-based land markets: Heterogeneous agents, land proces and urban land use change

    NARCIS (Netherlands)

    Filatova, Tatiana; Parker, Dawn C.; van der Veen, A.; Amblard, F.

    2007-01-01

    We construct a spatially explicit agent-based model of a bilateral land market. Heterogeneous agents form their bid and ask prices for land based on the utility that they obtain from a certain location (houte/land) and base on the state of the market (an excess of demand or supply). We underline the

  4. Combining heterogeneous features for colonic polyp detection in CTC based on semi-definite programming

    Science.gov (United States)

    Wang, Shijun; Yao, Jianhua; Petrick, Nicholas A.; Summers, Ronald M.

    2009-02-01

    Colon cancer is the second leading cause of cancer-related deaths in the United States. Computed tomographic colonography (CTC) combined with a computer aided detection system provides a feasible combination for improving colonic polyps detection and increasing the use of CTC for colon cancer screening. To distinguish true polyps from false positives, various features extracted from polyp candidates have been proposed. Most of these features try to capture the shape information of polyp candidates or neighborhood knowledge about the surrounding structures (fold, colon wall, etc.). In this paper, we propose a new set of shape descriptors for polyp candidates based on statistical curvature information. These features, called histogram of curvature features, are rotation, translation and scale invariant and can be treated as complementing our existing feature set. Then in order to make full use of the traditional features (defined as group A) and the new features (group B) which are highly heterogeneous, we employed a multiple kernel learning method based on semi-definite programming to identify an optimized classification kernel based on the combined set of features. We did leave-one-patient-out test on a CTC dataset which contained scans from 50 patients (with 90 6-9mm polyp detections). Experimental results show that a support vector machine (SVM) based on the combined feature set and the semi-definite optimization kernel achieved higher FROC performance compared to SVMs using the two groups of features separately. At a false positive per patient rate of 7, the sensitivity on 6-9mm polyps using the combined features improved from 0.78 (Group A) and 0.73 (Group B) to 0.82 (p<=0.01).

  5. Constructivism Based Blended Learning in Higher Education

    OpenAIRE

    Al-Huneidi, Ahmad

    2011-01-01

    Blended Learning, which is a mix of online and face-to-face learning, can combine the benefits of both, traditional classroom learning and e-learning environments.3 The aim of this thesis is to explore how to design and implement Blended Learning environment based on Constructivism theory, which focuses on students’ experience to construct the knowledge, in order to increase learning outcomes, performance, and quality in academic institutions. An affective and successful learni...

  6. [Verification of Learning Effects by Team-based Learning].

    Science.gov (United States)

    Ono, Shin-Ichi; Ito, Yoshihisa; Ishige, Kumiko; Inokuchi, Norio; Kosuge, Yasuhiro; Asami, Satoru; Izumisawa, Megumi; Kobayashi, Hiroko; Hayashi, Hiroyuki; Suzuki, Takashi; Kishikawa, Yukinaga; Hata, Harumi; Kose, Eiji; Tabata, Kei-Ichi

    2017-11-01

     It has been recommended that active learning methods, such as team-based learning (TBL) and problem-based learning (PBL), be introduced into university classes by the Central Council for Education. As such, for the past 3 years, we have implemented TBL in a medical therapeutics course for 4-year students. Based upon our experience, TBL is characterized as follows: TBL needs fewer teachers than PBL to conduct a TBL module. TBL enables both students and teachers to recognize and confirm the learning results from preparation and reviewing. TBL grows students' responsibility for themselves and their teams, and likely facilitates learning activities through peer assessment.

  7. Graph Regularized Meta-path Based Transductive Regression in Heterogeneous Information Network.

    Science.gov (United States)

    Wan, Mengting; Ouyang, Yunbo; Kaplan, Lance; Han, Jiawei

    2015-01-01

    A number of real-world networks are heterogeneous information networks, which are composed of different types of nodes and links. Numerical prediction in heterogeneous information networks is a challenging but significant area because network based information for unlabeled objects is usually limited to make precise estimations. In this paper, we consider a graph regularized meta-path based transductive regression model ( Grempt ), which combines the principal philosophies of typical graph-based transductive classification methods and transductive regression models designed for homogeneous networks. The computation of our method is time and space efficient and the precision of our model can be verified by numerical experiments.

  8. Cloudification of mmwave-based and packet-based fronthaul for future heterogeneous mobile networks

    DEFF Research Database (Denmark)

    Artuso, Matteo; Marcano, Andrea; Christiansen, Henrik Lehrmann

    2015-01-01

    is seen as an enabler for next-generation heterogeneous mobile networks. This allows for simpler base stations and savings in deployment costs, but introduces challenges in the fronthaul network connecting the sites to the processing pool. The fronthaul needs to have very low latency and high capacity......, but the traditional architecture of this network uses point-to-point links between each site and the pool, thus making it impossible to share capacity as the demands change. To address these challenges, a flexible network architecture for the fronthaul is presented that is based on Ethernet to carry the baseband......Current deployments of mobile networks are seriously challenged by increasing capacity demands, and traditional solutions are no longer practical. The use of small cells is considered as a viable technique to meet these demands. In this context, the use of centralized signal processing in a pool...

  9. Learning Object Metadata in a Web-Based Learning Environment

    NARCIS (Netherlands)

    Avgeriou, Paris; Koutoumanos, Anastasios; Retalis, Symeon; Papaspyrou, Nikolaos

    2000-01-01

    The plethora and variance of learning resources embedded in modern web-based learning environments require a mechanism to enable their structured administration. This goal can be achieved by defining metadata on them and constructing a system that manages the metadata in the context of the learning

  10. Generative Adversarial Networks Based Heterogeneous Data Integration and Its Application for Intelligent Power Distribution and Utilization

    Directory of Open Access Journals (Sweden)

    Yuanpeng Tan

    2018-01-01

    Full Text Available Heterogeneous characteristics of a big data system for intelligent power distribution and utilization have already become more and more prominent, which brings new challenges for the traditional data analysis technologies and restricts the comprehensive management of distribution network assets. In order to solve the problem that heterogeneous data resources of power distribution systems are difficult to be effectively utilized, a novel generative adversarial networks (GANs based heterogeneous data integration method for intelligent power distribution and utilization is proposed. In the proposed method, GANs theory is introduced to expand the distribution of completed data samples. Then, a so-called peak clustering algorithm is proposed to realize the finite open coverage of the expanded sample space, and repair those incomplete samples to eliminate the heterogeneous characteristics. Finally, in order to realize the integration of the heterogeneous data for intelligent power distribution and utilization, the well-trained discriminator model of GANs is employed to check the restored data samples. The simulation experiments verified the validity and stability of the proposed heterogeneous data integration method, which provides a novel perspective for the further data quality management of power distribution systems.

  11. Lessons learned from IOR steamflooding in a bitumen-light oil heterogeneous reservoir

    NARCIS (Netherlands)

    Al Mudhafar, W.J.M.; Hosseini Nasab, S.M.

    2015-01-01

    The Steamflooding was considered in this research to extract the discontinuous bitumen layers that are located at the oil-water contact for the heterogeneous light oil sandstone reservoir of South Rumaila Field. The reservoir heterogeneity and the bitumen layers impede water aquifer approaching into

  12. Features and Characteristics of Problem Based Learning

    Science.gov (United States)

    Ceker, Eser; Ozdamli, Fezile

    2016-01-01

    Throughout the years, there appears to be an increase in Problem Based Learning applications in education; and Problem Based Learning related research areas. The main aim of this research is to underline the fundamentals (basic elements) of Problem Based Learning, investigate the dimensions of research approached to PBL oriented areas (with a look…

  13. The Credentials of Brain-Based Learning

    Science.gov (United States)

    Davis, Andrew

    2004-01-01

    This paper discusses the current fashion for brain-based learning, in which value-laden claims about learning are grounded in neurophysiology. It argues that brain science cannot have the authority about learning that some seek to give it. It goes on to discuss whether the claim that brain science is relevant to learning involves a category…

  14. Foundations of Game-Based Learning

    Science.gov (United States)

    Plass, Jan L.; Homer, Bruce D.; Kinzer, Charles K.

    2015-01-01

    In this article we argue that to study or apply games as learning environments, multiple perspectives have to be taken into account. We first define game-based learning and gamification, and then discuss theoretical models that describe learning with games, arguing that playfulness is orthogonal to learning theory. We then review design elements…

  15. Java problem-based learning

    Directory of Open Access Journals (Sweden)

    Goran P, Šimić

    2012-01-01

    Full Text Available The paper describes the self-directed problem-based learning system (PBL named Java PBL. The expert module is the kernel of Java PBL. It involves a specific domain model, a problem generator and a solution generator. The overall system architecture is represented in the paper. Java PBL can act as the stand-alone system, but it is also designed to provide support to learning management systems (LMSs. This is provided by a modular design of the system. An LMS can offer the declarative knowledge only. Java PBL offers the procedural knowledge and the progress of the learner programming skills. The free navigation, unlimited numbers of problems and recommendations represent the main pedagogical strategies and tactics implemented into the system.

  16. Heterogeneous classifier fusion for ligand-based virtual screening: or, how decision making by committee can be a good thing.

    Science.gov (United States)

    Riniker, Sereina; Fechner, Nikolas; Landrum, Gregory A

    2013-11-25

    The concept of data fusion - the combination of information from different sources describing the same object with the expectation to generate a more accurate representation - has found application in a very broad range of disciplines. In the context of ligand-based virtual screening (VS), data fusion has been applied to combine knowledge from either different active molecules or different fingerprints to improve similarity search performance. Machine-learning (ML) methods based on fusion of multiple homogeneous classifiers, in particular random forests, have also been widely applied in the ML literature. The heterogeneous version of classifier fusion - fusing the predictions from different model types - has been less explored. Here, we investigate heterogeneous classifier fusion for ligand-based VS using three different ML methods, RF, naïve Bayes (NB), and logistic regression (LR), with four 2D fingerprints, atom pairs, topological torsions, RDKit fingerprint, and circular fingerprint. The methods are compared using a previously developed benchmarking platform for 2D fingerprints which is extended to ML methods in this article. The original data sets are filtered for difficulty, and a new set of challenging data sets from ChEMBL is added. Data sets were also generated for a second use case: starting from a small set of related actives instead of diverse actives. The final fused model consistently outperforms the other approaches across the broad variety of targets studied, indicating that heterogeneous classifier fusion is a very promising approach for ligand-based VS. The new data sets together with the adapted source code for ML methods are provided in the Supporting Information .

  17. Integration of Heterogeneous Information Sources into a Knowledge Resource Management System for Lifelong Learning

    NARCIS (Netherlands)

    Demidova, Elena; Ternier, Stefaan; Olmedilla, Daniel; Duval, Erik; Dicerto, Michele; Stefanov, Krassen; Sacristán, Naiara

    2007-01-01

    Demidova, E., Ternier, S., Olmedilla, D., Duval, E., Dicerto, M., Stefanov, K., et al. (2007). Integration of Heterogeneous Information Sources into a Knowledge Resource Management System for Lifelong. TENCompetence Workshop on Service Oriented Approaches and Lifelong Competence Development

  18. Heterogeneous base-catalyzed methanolysis of vegetable oils: State of art

    Directory of Open Access Journals (Sweden)

    Miladinović Marija R.

    2010-01-01

    Full Text Available Today, homogeneous base-catalyzed methanolysis is most frequently used method for industrial biodiesel production. High requirements for the quality of feedstocks and the problems related to a huge amount of wastewaters have led to the development of novel biodiesel production technologies. Among them, the most important is heterogeneous base-catalyzed methanolysis, which has been intensively investigated in the last decade in order to develop new catalytic systems, to optimize the reaction conditions and to recycle catalysts. These studies are a base for developing continuous biodiesel production on industrial scale in near future. The present work summarizes up-to-date studies on biodiesel production by heterogeneous base-catalyzed methanolysis. The main goals were to point out the application of different base compounds as catalysts, the methods of catalyst preparation, impregnation on carriers and recycling as well as the possibilities to improve existing base-catalyzed biodiesel production processes and to develop novel ones.

  19. Design And Planning Of E- Learning EnvironmentE-Education System On Heterogeneous Wireless Network Control System

    Directory of Open Access Journals (Sweden)

    ThandarOo

    2015-06-01

    Full Text Available Abstract The purpose of this research is to provide a more efficient and effective communication method between teacher and student with the use of heterogeneous network. Moreover the effective use of heterogeneous network can be emphasized. The system of e-education can develop utilizing wireless network.The e-Education system can help students to communicate with their teacher more easily and effectively using a heterogeneous wireless network system. In this wireless network system students who are blind or dumb will also be able to communicate and learn from the teacher as normal students can do. All the devices or laptops will be connected on wireless LAN. Even when the teacher is not around he will be able to help his students with their study or give instructions easily by using the mobile phone to send text or voice signal. When the teacher sends information to the dumb student it will be converted into sign language for the student to be able to understand. When the dumb student sends the information to the teacher it will be converted into text for the teacher to understand. For the blind student text instructions from the teacher will be converted into audio signal using text-to-speech conversion.Thus the performance of heterogeneous wireless network model can evaluate by using Robust Optimization Method. Therefore the e-Education systems performance improves by evaluating Robust Optimization Method.

  20. A model-based approach to studying changes in compositional heterogeneity

    NARCIS (Netherlands)

    Baeten, L.; Warton, D.; Calster, van H.; Frenne, De P.; Verstraeten, G.; Bonte, D.; Bernhardt-Romermann, M.; Cornelis, R.; Decocq, G.; Eriksson, O.; Hommel, P.W.F.M.

    2014-01-01

    1. Non-random species loss and gain in local communities change the compositional heterogeneity between communities over time, which is traditionally quantified with dissimilarity-based approaches. Yet, dissimilarities summarize the multivariate species data into a univariate index and obscure the

  1. Performance Evaluation of a Cluster-Based Service Discovery Protocol for Heterogeneous Wireless Sensor Networks

    NARCIS (Netherlands)

    Marin Perianu, Raluca; Scholten, Johan; Havinga, Paul J.M.; Hartel, Pieter H.

    2006-01-01

    Abstract—This paper evaluates the performance in terms of resource consumption of a service discovery protocol proposed for heterogeneous Wireless Sensor Networks (WSNs). The protocol is based on a clustering structure, which facilitates the construction of a distributed directory. Nodes with higher

  2. A simple network agreement-based approach for combining evidences in a heterogeneous sensor network

    Directory of Open Access Journals (Sweden)

    Raúl Eusebio-Grande

    2015-12-01

    Full Text Available In this research we investigate how the evidences provided by both static and mobile nodes that are part of a heterogenous sensor network can be combined to have trustworthy results. A solution relying on a network agreement-based approach was implemented and tested.

  3. Effects of Heterogeneity in Residential Preferences on an Agent-Based Model of Urban Sprawl

    Directory of Open Access Journals (Sweden)

    Daniel G. Brown

    2006-06-01

    Full Text Available The ability of agent-based models (ABMs to represent heterogeneity in the characteristics and behaviors of actors enables analyses about the implications of this heterogeneity for system behavior. The importance of heterogeneity in the specification of ABMs, however, creates new demands for empirical support. An earlier analysis of a survey of residential preferences within southeastern Michigan revealed seven groups of residents with similar preferences on similar characteristics of location. In this paper, we present an ABM that represents the process of residential development within an urban system and run it for a hypothetical pattern of environmental variation. Residential locations are selected by residential agents, who evaluate locations on the basis of preference for nearness to urban services, including jobs, aesthetic quality of the landscape, and their similarity to their neighbors. We populate our ABM with a population of residential preferences drawn from the survey results in five different ways: (1 preferences drawn at random; (2 equal preferences based on the mean from the entire survey sample; (3 preferences drawn from a single distribution, whose mean and standard deviation are derived from the survey sample; (4 equal preferences within each of seven groups, based on the group means; and (5 preferences drawn from distributions for each of seven groups, defined by group means and standard deviations. Model sensitivity analysis, based on multiple runs of our model under each case, revealed that adding heterogeneity to agents has a significant effect on model outcomes, measured by aggregate patterns of development sprawl and clustering.

  4. A CFD Heterogeneous Parallel Solver Based on Collaborating CPU and GPU

    Science.gov (United States)

    Lai, Jianqi; Tian, Zhengyu; Li, Hua; Pan, Sha

    2018-03-01

    Since Graphic Processing Unit (GPU) has a strong ability of floating-point computation and memory bandwidth for data parallelism, it has been widely used in the areas of common computing such as molecular dynamics (MD), computational fluid dynamics (CFD) and so on. The emergence of compute unified device architecture (CUDA), which reduces the complexity of compiling program, brings the great opportunities to CFD. There are three different modes for parallel solution of NS equations: parallel solver based on CPU, parallel solver based on GPU and heterogeneous parallel solver based on collaborating CPU and GPU. As we can see, GPUs are relatively rich in compute capacity but poor in memory capacity and the CPUs do the opposite. We need to make full use of the GPUs and CPUs, so a CFD heterogeneous parallel solver based on collaborating CPU and GPU has been established. Three cases are presented to analyse the solver’s computational accuracy and heterogeneous parallel efficiency. The numerical results agree well with experiment results, which demonstrate that the heterogeneous parallel solver has high computational precision. The speedup on a single GPU is more than 40 for laminar flow, it decreases for turbulent flow, but it still can reach more than 20. What’s more, the speedup increases as the grid size becomes larger.

  5. Polymer-based 2D/3D wafer level heterogeneous integration for SSL module

    NARCIS (Netherlands)

    Yuan, C.; Wei, J.; Ye, H.; Koh, S.; Harianto, S.; Nieuwenhof, M.A. van den; Zhang, G.Q.

    2012-01-01

    This paper demonstrates a heterogeneous integration of solid state lighting (SSL) module, including light source (LED) and driver/control components. Such integration has been realized by the polymer-based reconfigured wafer level package technologies and such structure has been prototyped and

  6. An operational framework for object-based land use classification of heterogeneous rural landscapes

    DEFF Research Database (Denmark)

    Watmough, Gary Richard; Palm, Cheryl; Sullivan, Clare

    2017-01-01

    The characteristics of very high resolution (VHR) satellite data are encouraging development agencies to investigate its use in monitoring and evaluation programmes. VHR data pose challenges for land use classification of heterogeneous rural landscapes as it is not possible to develop generalised...... and transferable land use classification definitions and algorithms. We present an operational framework for classifying VHR satellite data in heterogeneous rural landscapes using an object-based and random forest classifier. The framework overcomes the challenges of classifying VHR data in anthropogenic...

  7. A Distributed Dynamic Super Peer Selection Method Based on Evolutionary Game for Heterogeneous P2P Streaming Systems

    Directory of Open Access Journals (Sweden)

    Jing Chen

    2013-01-01

    Full Text Available Due to high efficiency and good scalability, hierarchical hybrid P2P architecture has drawn more and more attention in P2P streaming research and application fields recently. The problem about super peer selection, which is the key problem in hybrid heterogeneous P2P architecture, is becoming highly challenging because super peers must be selected from a huge and dynamically changing network. A distributed super peer selection (SPS algorithm for hybrid heterogeneous P2P streaming system based on evolutionary game is proposed in this paper. The super peer selection procedure is modeled based on evolutionary game framework firstly, and its evolutionarily stable strategies are analyzed. Then a distributed Q-learning algorithm (ESS-SPS according to the mixed strategies by analysis is proposed for the peers to converge to the ESSs based on its own payoff history. Compared to the traditional randomly super peer selection scheme, experiments results show that the proposed ESS-SPS algorithm achieves better performance in terms of social welfare and average upload rate of super peers and keeps the upload capacity of the P2P streaming system increasing steadily with the number of peers increasing.

  8. Quantum-dot-based immunofluorescent imaging of HER2 and ER provides new insights into breast cancer heterogeneity

    International Nuclear Information System (INIS)

    Chen Chuang; Li Yan; Peng Jun; Xu Hao; Tang Hongwu; Zhang Zhiling; Pang Daiwen; Xia Heshun; Wu Qiongshui; Zeng Libo; Zhu Xiaobo

    2010-01-01

    Breast cancer (BC) is a heterogeneous tumor, and better understanding of its heterogeneity is essential to improving treatment effect. Quantum dot (QD)-based immunofluorescent nanotechnology (QD-IHC) for molecular pathology has potential advantages in delineating tumor heterogeneity. This potential is explored in this paper by QD-IHC imaging of HER2 and ER. BC heterogeneity can be displayed more clearly and sensitively by QD-IHC than conventional IHC in BC tissue microarrays. Furthermore, the simultaneous imaging of ER and HER2 might help understand their interactions during the process of evolution of heterogeneous BC.

  9. A numerical homogenization method for heterogeneous, anisotropic elastic media based on multiscale theory

    KAUST Repository

    Gao, Kai

    2015-06-05

    The development of reliable methods for upscaling fine-scale models of elastic media has long been an important topic for rock physics and applied seismology. Several effective medium theories have been developed to provide elastic parameters for materials such as finely layered media or randomly oriented or aligned fractures. In such cases, the analytic solutions for upscaled properties can be used for accurate prediction of wave propagation. However, such theories cannot be applied directly to homogenize elastic media with more complex, arbitrary spatial heterogeneity. Therefore, we have proposed a numerical homogenization algorithm based on multiscale finite-element methods for simulating elastic wave propagation in heterogeneous, anisotropic elastic media. Specifically, our method used multiscale basis functions obtained from a local linear elasticity problem with appropriately defined boundary conditions. Homogenized, effective medium parameters were then computed using these basis functions, and the approach applied a numerical discretization that was similar to the rotated staggered-grid finite-difference scheme. Comparisons of the results from our method and from conventional, analytical approaches for finely layered media showed that the homogenization reliably estimated elastic parameters for this simple geometry. Additional tests examined anisotropic models with arbitrary spatial heterogeneity in which the average size of the heterogeneities ranged from several centimeters to several meters, and the ratio between the dominant wavelength and the average size of the arbitrary heterogeneities ranged from 10 to 100. Comparisons to finite-difference simulations proved that the numerical homogenization was equally accurate for these complex cases.

  10. XML-based approaches for the integration of heterogeneous bio-molecular data.

    Science.gov (United States)

    Mesiti, Marco; Jiménez-Ruiz, Ernesto; Sanz, Ismael; Berlanga-Llavori, Rafael; Perlasca, Paolo; Valentini, Giorgio; Manset, David

    2009-10-15

    The today's public database infrastructure spans a very large collection of heterogeneous biological data, opening new opportunities for molecular biology, bio-medical and bioinformatics research, but raising also new problems for their integration and computational processing. In this paper we survey the most interesting and novel approaches for the representation, integration and management of different kinds of biological data by exploiting XML and the related recommendations and approaches. Moreover, we present new and interesting cutting edge approaches for the appropriate management of heterogeneous biological data represented through XML. XML has succeeded in the integration of heterogeneous biomolecular information, and has established itself as the syntactic glue for biological data sources. Nevertheless, a large variety of XML-based data formats have been proposed, thus resulting in a difficult effective integration of bioinformatics data schemes. The adoption of a few semantic-rich standard formats is urgent to achieve a seamless integration of the current biological resources.

  11. Conformity-based cooperation in online social networks: The effect of heterogeneous social influence

    International Nuclear Information System (INIS)

    Xu, Bo; Wang, Jianwei; Zhang, Xuejun

    2015-01-01

    This paper extends the conformity model by introducing heterogeneous social influence into the analysis. We associate the influence of a player in the network with its degree centrality assuming that players of higher degree exhibit more social influence on its neighbors. The results show that the equilibrium level of cooperators can be dramatically enhanced if the conformity-driven players are preferentially influenced by neighbors of higher degree. We attribute this finding to two elementary mechanisms in the evolutionary process: (1) degree-based social influence facilitates the formation of strategic clusters around hubs; and (2) payoff-heterogeneity between cooperative clusters and defective clusters contributes to the promotion of cooperation. This research reveals the important role of heterogeneous social influence on the emergence of cooperation in social networks.

  12. Music Learning Based on Computer Software

    Directory of Open Access Journals (Sweden)

    Baihui Yan

    2017-12-01

    Full Text Available In order to better develop and improve students’ music learning, the authors proposed the method of music learning based on computer software. It is still a new field to use computer music software to assist teaching. Hereby, we conducted an in-depth analysis on the computer-enabled music learning and the music learning status in secondary schools, obtaining the specific analytical data. Survey data shows that students have many cognitive problems in the current music classroom, and yet teachers have not found a reasonable countermeasure to them. Against this background, the introduction of computer music software to music learning is a new trial that can not only cultivate the students’ initiatives of music learning, but also enhance their abilities to learn music. Therefore, it is concluded that the computer software based music learning is of great significance to improving the current music learning modes and means.

  13. How has problem based learning fared in Pakistan?

    Science.gov (United States)

    Mahmud, Waqas; Hyder, Omar

    2012-10-01

    To conduct a systematic review of primary research in undergraduate medical education in Pakistan in order to evaluate PBL programs, examine outcomes and competencies influenced by PBL, and compare them with conventional learning (lecture based learning, LBL). Qualitative content analysis. Rawalpindi Medical College, Rawalpindi, from June 2010 - February 2011. Literature was searched using online resources. Studies evaluating outcomes influenced by PBL, or comparing PBL with lecture based learning (LBL) were selected. Due to heterogeneity, a qualitative content analysis was performed in which studies were classified according to the methods of assessment; results were then summarized by outcome and frequencies were calculated. Eleven studies were included. Apart from knowledge acquisition, students gave high ratings to PBL in selected outcomes, alone, and in comparison with LBL. There was a disagreement among results of studies that evaluated knowledge acquisition alone. Based on student perceptions, PBL has many advantages. However, the results of this review are limited due to heterogeneity and methodological weakness of studies, specially the studies that compared exam scores to assess knowledge acquisition.

  14. Classifying spatially heterogeneous wetland communities using machine learning algorithms and spectral and textural features.

    Science.gov (United States)

    Szantoi, Zoltan; Escobedo, Francisco J; Abd-Elrahman, Amr; Pearlstine, Leonard; Dewitt, Bon; Smith, Scot

    2015-05-01

    Mapping of wetlands (marsh vs. swamp vs. upland) is a common remote sensing application.Yet, discriminating between similar freshwater communities such as graminoid/sedge fromremotely sensed imagery is more difficult. Most of this activity has been performed using medium to low resolution imagery. There are only a few studies using highspatial resolutionimagery and machine learning image classification algorithms for mapping heterogeneouswetland plantcommunities. This study addresses this void by analyzing whether machine learning classifierssuch as decisiontrees (DT) and artificial neural networks (ANN) can accurately classify graminoid/sedgecommunities usinghigh resolution aerial imagery and image texture data in the Everglades National Park, Florida.In addition tospectral bands, the normalized difference vegetation index, and first- and second-order texturefeatures derivedfrom the near-infrared band were analyzed. Classifier accuracies were assessed using confusiontablesand the calculated kappa coefficients of the resulting maps. The results indicated that an ANN(multilayerperceptron based on backpropagation) algorithm produced a statistically significantly higheraccuracy(82.04%) than the DT (QUEST) algorithm (80.48%) or the maximum likelihood (80.56%)classifier (αtexture features.

  15. Human disease MiRNA inference by combining target information based on heterogeneous manifolds.

    Science.gov (United States)

    Ding, Pingjian; Luo, Jiawei; Liang, Cheng; Xiao, Qiu; Cao, Buwen

    2018-04-01

    The emergence of network medicine has provided great insight into the identification of disease-related molecules, which could help with the development of personalized medicine. However, the state-of-the-art methods could neither simultaneously consider target information and the known miRNA-disease associations nor effectively explore novel gene-disease associations as a by-product during the process of inferring disease-related miRNAs. Computational methods incorporating multiple sources of information offer more opportunities to infer disease-related molecules, including miRNAs and genes in heterogeneous networks at a system level. In this study, we developed a novel algorithm, named inference of Disease-related MiRNAs based on Heterogeneous Manifold (DMHM), to accurately and efficiently identify miRNA-disease associations by integrating multi-omics data. Graph-based regularization was utilized to obtain a smooth function on the data manifold, which constitutes the main principle of DMHM. The novelty of this framework lies in the relatedness between diseases and miRNAs, which are measured via heterogeneous manifolds on heterogeneous networks integrating target information. To demonstrate the effectiveness of DMHM, we conducted comprehensive experiments based on HMDD datasets and compared DMHM with six state-of-the-art methods. Experimental results indicated that DMHM significantly outperformed the other six methods under fivefold cross validation and de novo prediction tests. Case studies have further confirmed the practical usefulness of DMHM. Copyright © 2018 Elsevier Inc. All rights reserved.

  16. Learning Theory Foundations of Simulation-Based Mastery Learning.

    Science.gov (United States)

    McGaghie, William C; Harris, Ilene B

    2018-06-01

    Simulation-based mastery learning (SBML), like all education interventions, has learning theory foundations. Recognition and comprehension of SBML learning theory foundations are essential for thoughtful education program development, research, and scholarship. We begin with a description of SBML followed by a section on the importance of learning theory foundations to shape and direct SBML education and research. We then discuss three principal learning theory conceptual frameworks that are associated with SBML-behavioral, constructivist, social cognitive-and their contributions to SBML thought and practice. We then discuss how the three learning theory frameworks converge in the course of planning, conducting, and evaluating SBML education programs in the health professions. Convergence of these learning theory frameworks is illustrated by a description of an SBML education and research program in advanced cardiac life support. We conclude with a brief coda.

  17. Learning for Entrepreneurship in Heterogeneous Groups: Experiences From an International, Interdisciplinary Higher Education Student Program

    NARCIS (Netherlands)

    Lans, T.; Popov, V.; Oganisjana, K.; Täks, M.

    2013-01-01

    Although entrepreneurship education (EE) has gained popularity internationally, empirical work is scarce on the factors which influence the underlying learning process. This article presents the experiences of a European summer school where factors which contribute to entrepreneurial learning in

  18. Electrophysiological Evidence of Heterogeneity in Visual Statistical Learning in Young Children with ASD

    Science.gov (United States)

    Jeste, Shafali S.; Kirkham, Natasha; Senturk, Damla; Hasenstab, Kyle; Sugar, Catherine; Kupelian, Chloe; Baker, Elizabeth; Sanders, Andrew J.; Shimizu, Christina; Norona, Amanda; Paparella, Tanya; Freeman, Stephanny F. N.; Johnson, Scott P.

    2015-01-01

    Statistical learning is characterized by detection of regularities in one's environment without an awareness or intention to learn, and it may play a critical role in language and social behavior. Accordingly, in this study we investigated the electrophysiological correlates of visual statistical learning in young children with autism…

  19. Bioinformatics Methods for Learning Radiation-Induced Lung Inflammation from Heterogeneous Retrospective and Prospective Data

    Science.gov (United States)

    Spencer, Sarah J.; Almiron Bonnin, Damian; Deasy, Joseph O.; Bradley, Jeffrey D.; El Naqa, Issam

    2009-01-01

    Radiotherapy outcomes are determined by complex interactions between physical and biological factors, reflecting both treatment conditions and underlying genetics. Recent advances in radiotherapy and biotechnology provide new opportunities and challenges for predicting radiation-induced toxicities, particularly radiation pneumonitis (RP), in lung cancer patients. In this work, we utilize datamining methods based on machine learning to build a predictive model of lung injury by retrospective analysis of treatment planning archives. In addition, biomarkers for this model are extracted from a prospective clinical trial that collects blood serum samples at multiple time points. We utilize a 3-way proteomics methodology to screen for differentially expressed proteins that are related to RP. Our preliminary results demonstrate that kernel methods can capture nonlinear dose-volume interactions, but fail to address missing biological factors. Our proteomics strategy yielded promising protein candidates, but their role in RP as well as their interactions with dose-volume metrics remain to be determined. PMID:19704920

  20. Inference of Cell Mechanics in Heterogeneous Epithelial Tissue Based on Multivariate Clone Shape Quantification

    Science.gov (United States)

    Tsuboi, Alice; Umetsu, Daiki; Kuranaga, Erina; Fujimoto, Koichi

    2017-01-01

    Cell populations in multicellular organisms show genetic and non-genetic heterogeneity, even in undifferentiated tissues of multipotent cells during development and tumorigenesis. The heterogeneity causes difference of mechanical properties, such as, cell bond tension or adhesion, at the cell–cell interface, which determine the shape of clonal population boundaries via cell sorting or mixing. The boundary shape could alter the degree of cell–cell contacts and thus influence the physiological consequences of sorting or mixing at the boundary (e.g., tumor suppression or progression), suggesting that the cell mechanics could help clarify the physiology of heterogeneous tissues. While precise inference of mechanical tension loaded at each cell–cell contacts has been extensively developed, there has been little progress on how to distinguish the population-boundary geometry and identify the cause of geometry in heterogeneous tissues. We developed a pipeline by combining multivariate analysis of clone shape with tissue mechanical simulations. We examined clones with four different genotypes within Drosophila wing imaginal discs: wild-type, tartan (trn) overexpression, hibris (hbs) overexpression, and Eph RNAi. Although the clones were previously known to exhibit smoothed or convoluted morphologies, their mechanical properties were unknown. By applying a multivariate analysis to multiple criteria used to quantify the clone shapes based on individual cell shapes, we found the optimal criteria to distinguish not only among the four genotypes, but also non-genetic heterogeneity from genetic one. The efficient segregation of clone shape enabled us to quantitatively compare experimental data with tissue mechanical simulations. As a result, we identified the mechanical basis contributed to clone shape of distinct genotypes. The present pipeline will promote the understanding of the functions of mechanical interactions in heterogeneous tissue in a non-invasive manner. PMID

  1. Heterogeneity within autism spectrum disorders: what have we learned from neuroimaging studies?

    Directory of Open Access Journals (Sweden)

    Rhoshel Krystyna Lenroot

    2013-10-01

    Full Text Available Autism spectrum disorders (ASD display significant heterogeneity. Although most neuroimaging studies in ASD have been designed to identify commonalities among affected individuals, rather than differences, some studies have explored variation within ASD. There have been two general types of approaches used for this in the neuroimaging literature to date: comparison of subgroups within ASD, and analyses using dimensional measures to link clinical variation to brain differences. This review focuses on structural and functional magnetic resonance imaging studies that have used these approaches to begin to explore heterogeneity between individuals with ASD. Although this type of data is yet sparse, recognition is growing of the limitations of behaviourally defined categorical diagnoses for understanding neurobiology. Study designs that are more informative regarding the sources of heterogeneity in ASD have the potential to improve our understanding of the neurobiological processes underlying ASD.

  2. Study on distributed generation algorithm of variable precision concept lattice based on ontology heterogeneous database

    Science.gov (United States)

    WANG, Qingrong; ZHU, Changfeng

    2017-06-01

    Integration of distributed heterogeneous data sources is the key issues under the big data applications. In this paper the strategy of variable precision is introduced to the concept lattice, and the one-to-one mapping mode of variable precision concept lattice and ontology concept lattice is constructed to produce the local ontology by constructing the variable precision concept lattice for each subsystem, and the distributed generation algorithm of variable precision concept lattice based on ontology heterogeneous database is proposed to draw support from the special relationship between concept lattice and ontology construction. Finally, based on the standard of main concept lattice of the existing heterogeneous database generated, a case study has been carried out in order to testify the feasibility and validity of this algorithm, and the differences between the main concept lattice and the standard concept lattice are compared. Analysis results show that this algorithm above-mentioned can automatically process the construction process of distributed concept lattice under the heterogeneous data sources.

  3. A link prediction method for heterogeneous networks based on BP neural network

    Science.gov (United States)

    Li, Ji-chao; Zhao, Dan-ling; Ge, Bing-Feng; Yang, Ke-Wei; Chen, Ying-Wu

    2018-04-01

    Most real-world systems, composed of different types of objects connected via many interconnections, can be abstracted as various complex heterogeneous networks. Link prediction for heterogeneous networks is of great significance for mining missing links and reconfiguring networks according to observed information, with considerable applications in, for example, friend and location recommendations and disease-gene candidate detection. In this paper, we put forward a novel integrated framework, called MPBP (Meta-Path feature-based BP neural network model), to predict multiple types of links for heterogeneous networks. More specifically, the concept of meta-path is introduced, followed by the extraction of meta-path features for heterogeneous networks. Next, based on the extracted meta-path features, a supervised link prediction model is built with a three-layer BP neural network. Then, the solution algorithm of the proposed link prediction model is put forward to obtain predicted results by iteratively training the network. Last, numerical experiments on the dataset of examples of a gene-disease network and a combat network are conducted to verify the effectiveness and feasibility of the proposed MPBP. It shows that the MPBP with very good performance is superior to the baseline methods.

  4. Learning-based diagnosis and repair

    NARCIS (Netherlands)

    Roos, Nico

    2017-01-01

    This paper proposes a new form of diagnosis and repair based on reinforcement learning. Self-interested agents learn locally which agents may provide a low quality of service for a task. The correctness of learned assessments of other agents is proved under conditions on exploration versus

  5. Features and characteristics of problem based learning

    Directory of Open Access Journals (Sweden)

    Eser Ceker

    2016-12-01

    Full Text Available Throughout the years, there appears to be an increase in Problem Based Learning applications in education; and Problem Based Learning related research areas. The main aim of this research is to underline the fundamentals (basic elements of Problem Based Learning, investigate the dimensions of research approached to PBL oriented areas (with a look for the latest technology supported tools of Problem Based Learning. This research showed that the most researched characteristics of PBL are; teacher and student assessments on Problem Based Learning, Variety of disciplines in which Problem Based Learning strategies were tried and success evaluated, Using Problem Based Learning alone or with other strategies (Hybrid or Mix methods, Comparing Problem Based Learning with other strategies, and new trends and tendencies in Problem Based Learning related research. Our research may help us to identify the latest trends and tendencies referred to in the published studies related to “problem based learning” areas. In this research, Science Direct and Ulakbim were used as our main database resources. The sample of this study consists of 150 articles.

  6. Inquiry based learning as didactic model in distant learning

    NARCIS (Netherlands)

    Rothkrantz, L.J.M.

    2015-01-01

    Recent years many universities are involved in development of Massive Open Online Courses (MOOCs). Unfortunately an appropriate didactic model for cooperated network learning is lacking. In this paper we introduce inquiry based learning as didactic model. Students are assumed to ask themselves

  7. Problem Based Learning for engineering.

    Science.gov (United States)

    Kumar, Dinesh; Radcliffe, Pj

    2017-07-01

    the role of Problem Based Learning (PBL) is relative clear in domains such as medicine but its efficacy in engineering is as yet less certain. To clarify the role of PBL in engineering, a 3 day workshop was conducted for senior Brazilian engineering academics where they were given the theory and then an immersive PBL experience. One major purpose for running this workshop was for them to identify suitable courses where PBL could be considered. During this workshop, they were split in teams and given a diverse range of problems. At the conclusion of the workshop, a quantifiable survey was conducted and the results show that PBL can deliver superior educational outcomes providing the student group is drawn from the top 5% of the year 12 students, and that significantly higher resources are made available. Thus, any proposed PBL program in engineering must be able to demonstrate that it can meet these requirements before it can move forward to implementation.

  8. Music Learning Based on Computer Software

    OpenAIRE

    Baihui Yan; Qiao Zhou

    2017-01-01

    In order to better develop and improve students’ music learning, the authors proposed the method of music learning based on computer software. It is still a new field to use computer music software to assist teaching. Hereby, we conducted an in-depth analysis on the computer-enabled music learning and the music learning status in secondary schools, obtaining the specific analytical data. Survey data shows that students have many cognitive problems in the current music classroom, and yet teach...

  9. Students' learning processes during school-based learning and workplace learning in vocational education : a review

    NARCIS (Netherlands)

    Dr. Harmen Schaap; Dr. Liesbeth Baartman; Prof.Dr. Elly de Bruijn

    2012-01-01

    This article reviews 24 articles in order to get a structured view on student's learning processes when dealing with a combination of school-based learning and workplace learning in vocational education. It focuses on six main themes: students' expertise development, students' learning styles,

  10. Problem-based learning and radiology

    International Nuclear Information System (INIS)

    Thurley, P.; Dennick, R.

    2008-01-01

    The Royal College of Radiologists recently published documents setting out guidelines to improve the teaching of radiology to medical students. These included recommendations that clinicians who teach radiology should be aware of newer educational techniques, such as problem-based learning, and should be involved in the development of curricula and assessment in medical schools. This review aims to introduce the educational theories behind problem-based learning and describe how a problem-based learning tutorial is run. The relevance of problem-based learning to radiology and the potential advantages and disadvantages are discussed

  11. Multiple Kernel Learning for Heterogeneous Anomaly Detection: Algorithm and Aviation Safety Case Study

    Science.gov (United States)

    Das, Santanu; Srivastava, Ashok N.; Matthews, Bryan L.; Oza, Nikunj C.

    2010-01-01

    The world-wide aviation system is one of the most complex dynamical systems ever developed and is generating data at an extremely rapid rate. Most modern commercial aircraft record several hundred flight parameters including information from the guidance, navigation, and control systems, the avionics and propulsion systems, and the pilot inputs into the aircraft. These parameters may be continuous measurements or binary or categorical measurements recorded in one second intervals for the duration of the flight. Currently, most approaches to aviation safety are reactive, meaning that they are designed to react to an aviation safety incident or accident. In this paper, we discuss a novel approach based on the theory of multiple kernel learning to detect potential safety anomalies in very large data bases of discrete and continuous data from world-wide operations of commercial fleets. We pose a general anomaly detection problem which includes both discrete and continuous data streams, where we assume that the discrete streams have a causal influence on the continuous streams. We also assume that atypical sequence of events in the discrete streams can lead to off-nominal system performance. We discuss the application domain, novel algorithms, and also discuss results on real-world data sets. Our algorithm uncovers operationally significant events in high dimensional data streams in the aviation industry which are not detectable using state of the art methods

  12. FEATURE SELECTION METHODS BASED ON MUTUAL INFORMATION FOR CLASSIFYING HETEROGENEOUS FEATURES

    Directory of Open Access Journals (Sweden)

    Ratri Enggar Pawening

    2016-06-01

    Full Text Available Datasets with heterogeneous features can affect feature selection results that are not appropriate because it is difficult to evaluate heterogeneous features concurrently. Feature transformation (FT is another way to handle heterogeneous features subset selection. The results of transformation from non-numerical into numerical features may produce redundancy to the original numerical features. In this paper, we propose a method to select feature subset based on mutual information (MI for classifying heterogeneous features. We use unsupervised feature transformation (UFT methods and joint mutual information maximation (JMIM methods. UFT methods is used to transform non-numerical features into numerical features. JMIM methods is used to select feature subset with a consideration of the class label. The transformed and the original features are combined entirely, then determine features subset by using JMIM methods, and classify them using support vector machine (SVM algorithm. The classification accuracy are measured for any number of selected feature subset and compared between UFT-JMIM methods and Dummy-JMIM methods. The average classification accuracy for all experiments in this study that can be achieved by UFT-JMIM methods is about 84.47% and Dummy-JMIM methods is about 84.24%. This result shows that UFT-JMIM methods can minimize information loss between transformed and original features, and select feature subset to avoid redundant and irrelevant features.

  13. Distance learning, problem based learning and dynamic knowledge networks.

    Science.gov (United States)

    Giani, U; Martone, P

    1998-06-01

    This paper is an attempt to develop a distance learning model grounded upon a strict integration of problem based learning (PBL), dynamic knowledge networks (DKN) and web tools, such as hypermedia documents, synchronous and asynchronous communication facilities, etc. The main objective is to develop a theory of distance learning based upon the idea that learning is a highly dynamic cognitive process aimed at connecting different concepts in a network of mutually supporting concepts. Moreover, this process is supposed to be the result of a social interaction that has to be facilitated by the web. The model was tested by creating a virtual classroom of medical and nursing students and activating a learning session on the concept of knowledge representation in health sciences.

  14. Lifelong Transfer Learning for Heterogeneous Teams of Agents in Sequential Decision Processes

    Science.gov (United States)

    2016-06-01

    computational complexity and exhibits sublinear regret , thus providing strong theoretical guarantees [Bou Ammar et al., 2015b] (see Appendix C for details...transferred knowledge, providing a potential mechanism for predicting the effectiveness of transfer learning (and thereby avoiding negative transfer). One...learning from demonstration. We theoretically and empirically analyze the performance of the proposed method and derive, for the first time, regret

  15. A Learning Object Approach To Evidence based learning

    OpenAIRE

    Zabin Visram; Bruce Elson; Patricia Reynolds

    2005-01-01

    This paper describes the philosophy, development and framework of the body of elements formulated to provide an approach to evidence-based learning sustained by Learning Objects and web based technology Due to the demands for continuous improvement in the delivery of healthcare and in the continuous endeavour to improve the quality of life, there is a continuous need for practitioner's to update their knowledge by accomplishing accredited courses. The rapid advances in medical science has mea...

  16. An open, object-based modeling approach for simulating subsurface heterogeneity

    Science.gov (United States)

    Bennett, J.; Ross, M.; Haslauer, C. P.; Cirpka, O. A.

    2017-12-01

    Characterization of subsurface heterogeneity with respect to hydraulic and geochemical properties is critical in hydrogeology as their spatial distribution controls groundwater flow and solute transport. Many approaches of characterizing subsurface heterogeneity do not account for well-established geological concepts about the deposition of the aquifer materials; those that do (i.e. process-based methods) often require forcing parameters that are difficult to derive from site observations. We have developed a new method for simulating subsurface heterogeneity that honors concepts of sequence stratigraphy, resolves fine-scale heterogeneity and anisotropy of distributed parameters, and resembles observed sedimentary deposits. The method implements a multi-scale hierarchical facies modeling framework based on architectural element analysis, with larger features composed of smaller sub-units. The Hydrogeological Virtual Reality simulator (HYVR) simulates distributed parameter models using an object-based approach. Input parameters are derived from observations of stratigraphic morphology in sequence type-sections. Simulation outputs can be used for generic simulations of groundwater flow and solute transport, and for the generation of three-dimensional training images needed in applications of multiple-point geostatistics. The HYVR algorithm is flexible and easy to customize. The algorithm was written in the open-source programming language Python, and is intended to form a code base for hydrogeological researchers, as well as a platform that can be further developed to suit investigators' individual needs. This presentation will encompass the conceptual background and computational methods of the HYVR algorithm, the derivation of input parameters from site characterization, and the results of groundwater flow and solute transport simulations in different depositional settings.

  17. Project Scheduling Heuristics-Based Standard PSO for Task-Resource Assignment in Heterogeneous Grid

    OpenAIRE

    Chen, Ruey-Maw; Wang, Chuin-Mu

    2011-01-01

    The task scheduling problem has been widely studied for assigning resources to tasks in heterogeneous grid environment. Effective task scheduling is an important issue for the performance of grid computing. Meanwhile, the task scheduling problem is an NP-complete problem. Hence, this investigation introduces a named “standard“ particle swarm optimization (PSO) metaheuristic approach to efficiently solve the task scheduling problems in grid. Meanwhile, two promising heuristics based on multimo...

  18. Mobility Behavior of the Elderly: an attitude-based segmentation approach for a heterogeneous target group

    DEFF Research Database (Denmark)

    Haustein, Sonja

    2012-01-01

    The western population is ageing. Based on the assumption that the elderly are a quite heterogeneous population group with an increasing impact on the transport system, mobility types of the elderly were identified. By means of 1,500 standardized telephone interviews, mobility behavior and possib...... of the diverse lifestyles, attitudes, travel behavior and needs of the elderly. Furthermore, it identifies starting points for the reduction of car use....

  19. A Bootstrap Neural Network Based Heterogeneous Panel Unit Root Test: Application to Exchange Rates

    OpenAIRE

    Christian de Peretti; Carole Siani; Mario Cerrato

    2010-01-01

    This paper proposes a bootstrap artificial neural network based panel unit root test in a dynamic heterogeneous panel context. An application to a panel of bilateral real exchange rate series with the US Dollar from the 20 major OECD countries is provided to investigate the Purchase Power Parity (PPP). The combination of neural network and bootstrapping significantly changes the findings of the economic study in favour of PPP.

  20. Project- Based Learning and Problem-Based Learning: Are They Effective to Improve Student's Thinking Skills?

    OpenAIRE

    Anazifa, R. D; Djukri, D

    2017-01-01

    The study aims at finding (1) the effect of project-based learning and problem-based learning on student's creativity and critical thinking and (2) the difference effect of project-based learning and problem-based learning on student's creativity and critical thinking. This study is quasi experiment using non-equivalent control-group design. Research population of this study was all classes in eleventh grade of mathematics and natural science program of SMA N 1 Temanggung. The participants we...

  1. Simulation and case-based learning

    DEFF Research Database (Denmark)

    Ørngreen, Rikke; Guralnick, David

    2008-01-01

    Abstract- This paper has its origin in the authors' reflection on years of practical experiences combined with literature readings in our preparation for a workshop on learn-by-doing simulation and case-based learning to be held at the ICELW 2008 conference (the International Conference on E-Learning...... in the Workplace). The purpose of this paper is to describe the two online learning methodologies and to raise questions for future discussion. In the workshop, the organizers and participants work with and discuss differences and similarities within the two pedagogical methodologies, focusing on how...... they are applied in workplace related and e-learning contexts. In addition to the organizers, a small number of invited presenters will attend, giving demonstrations of their work within learn-by-doing simulation and cases-based learning, but still leaving ample of time for discussion among all participants....

  2. A family-based joint test for mean and variance heterogeneity for quantitative traits.

    Science.gov (United States)

    Cao, Ying; Maxwell, Taylor J; Wei, Peng

    2015-01-01

    Traditional quantitative trait locus (QTL) analysis focuses on identifying loci associated with mean heterogeneity. Recent research has discovered loci associated with phenotype variance heterogeneity (vQTL), which is important in studying genetic association with complex traits, especially for identifying gene-gene and gene-environment interactions. While several tests have been proposed to detect vQTL for unrelated individuals, there are no tests for related individuals, commonly seen in family-based genetic studies. Here we introduce a likelihood ratio test (LRT) for identifying mean and variance heterogeneity simultaneously or for either effect alone, adjusting for covariates and family relatedness using a linear mixed effect model approach. The LRT test statistic for normally distributed quantitative traits approximately follows χ(2)-distributions. To correct for inflated Type I error for non-normally distributed quantitative traits, we propose a parametric bootstrap-based LRT that removes the best linear unbiased prediction (BLUP) of family random effect. Simulation studies show that our family-based test controls Type I error and has good power, while Type I error inflation is observed when family relatedness is ignored. We demonstrate the utility and efficiency gains of the proposed method using data from the Framingham Heart Study to detect loci associated with body mass index (BMI) variability. © 2014 John Wiley & Sons Ltd/University College London.

  3. Study on evaluation method for heterogeneous sedimentary rocks based on forward model

    International Nuclear Information System (INIS)

    Masui, Yasuhiro; Kawada, Koji; Katoh, Arata; Tsuji, Takashi; Suwabe, Mizue

    2004-02-01

    It is very important to estimate the facies distribution of heterogeneous sedimentary rocks for geological disposal of high level radioactive waste. The heterogeneousness of sedimentary rocks is due to variable distribution of grain size and mineral composition. The objective of this study is to establish the evaluation method for heterogeneous sedimentary rocks based on forward model. This study consisted of geological study for Horonobe area and the development of soft wear for sedimentary model. Geological study was composed of following items. 1. The sedimentary system for Koetoi and Wakkanai formations in Horonobe area was compiled based on papers. 2. The cores of HDB-1 were observed mainly from sedimentological view. 3. The facies and compaction property of argillaceous rocks were studied based on physical logs and core analysis data of wells. 4. The structure maps, isochrone maps, isopach maps and restored geological sections were made. The soft wear for sedimentary model to show sedimentary system on a basin scale was developed. This soft wear estimates the facies distribution and hydraulic conductivity of sedimentary rocks on three dimensions scale by numerical simulation. (author)

  4. A Web-Based Learning Support System for Inquiry-Based Learning

    Science.gov (United States)

    Kim, Dong Won; Yao, Jingtao

    The emergence of the Internet and Web technology makes it possible to implement the ideals of inquiry-based learning, in which students seek truth, information, or knowledge by questioning. Web-based learning support systems can provide a good framework for inquiry-based learning. This article presents a study on a Web-based learning support system called Online Treasure Hunt. The Web-based learning support system mainly consists of a teaching support subsystem, a learning support subsystem, and a treasure hunt game. The teaching support subsystem allows instructors to design their own inquiry-based learning environments. The learning support subsystem supports students' inquiry activities. The treasure hunt game enables students to investigate new knowledge, develop ideas, and review their findings. Online Treasure Hunt complies with a treasure hunt model. The treasure hunt model formalizes a general treasure hunt game to contain the learning strategies of inquiry-based learning. This Web-based learning support system empowered with the online-learning game and founded on the sound learning strategies furnishes students with the interactive and collaborative student-centered learning environment.

  5. Supervised learning methods in modeling of CD4+ T cell heterogeneity

    OpenAIRE

    Lu, Pinyi; Abedi, Vida; Mei, Yongguo; Hontecillas, Raquel; Hoops, Stefan; Carbo, Adria; Bassaganya-Riera, Josep

    2015-01-01

    Background Modeling of the immune system – a highly non-linear and complex system – requires practical and efficient data analytic approaches. The immune system is composed of heterogeneous cell populations and hundreds of cell types, such as neutrophils, eosinophils, macrophages, dendritic cells, T cells, and B cells. Each cell type is highly diverse and can be further differentiated into subsets with unique and overlapping functions. For example, CD4+ T cells can be differentiated into T...

  6. Problem-Based Learning Approaches in Meteorology

    Science.gov (United States)

    Charlton-Perez, Andrew James

    2013-01-01

    Problem-Based Learning, despite recent controversies about its effectiveness, is used extensively as a teaching method throughout higher education. In meteorology, there has been little attempt to incorporate Problem-Based Learning techniques into the curriculum. Motivated by a desire to enhance the reflective engagement of students within a…

  7. Learning outcomes between Socioscientific Issues-Based Learning and Conventional Learning Activities

    OpenAIRE

    Piyaluk Wongsri; Prasart Nuangchalerm

    2010-01-01

    Problem statement: Socioscientific issues-based learning activity is essential for scientific reasoning skills and it could be used for analyzing problems be applied to each situation for more successful and suitable. The purposes of this research aimed to compare learning achievement, analytical thinking and moral reasoning of seventh grade students who were organized between socioscientific issues-based learning and conventional learning activities. Approach: The samples used in research we...

  8. A Regression-based K nearest neighbor algorithm for gene function prediction from heterogeneous data

    Directory of Open Access Journals (Sweden)

    Ruzzo Walter L

    2006-03-01

    Full Text Available Abstract Background As a variety of functional genomic and proteomic techniques become available, there is an increasing need for functional analysis methodologies that integrate heterogeneous data sources. Methods In this paper, we address this issue by proposing a general framework for gene function prediction based on the k-nearest-neighbor (KNN algorithm. The choice of KNN is motivated by its simplicity, flexibility to incorporate different data types and adaptability to irregular feature spaces. A weakness of traditional KNN methods, especially when handling heterogeneous data, is that performance is subject to the often ad hoc choice of similarity metric. To address this weakness, we apply regression methods to infer a similarity metric as a weighted combination of a set of base similarity measures, which helps to locate the neighbors that are most likely to be in the same class as the target gene. We also suggest a novel voting scheme to generate confidence scores that estimate the accuracy of predictions. The method gracefully extends to multi-way classification problems. Results We apply this technique to gene function prediction according to three well-known Escherichia coli classification schemes suggested by biologists, using information derived from microarray and genome sequencing data. We demonstrate that our algorithm dramatically outperforms the naive KNN methods and is competitive with support vector machine (SVM algorithms for integrating heterogenous data. We also show that by combining different data sources, prediction accuracy can improve significantly. Conclusion Our extension of KNN with automatic feature weighting, multi-class prediction, and probabilistic inference, enhance prediction accuracy significantly while remaining efficient, intuitive and flexible. This general framework can also be applied to similar classification problems involving heterogeneous datasets.

  9. A Learning Object Approach To Evidence based learning

    Directory of Open Access Journals (Sweden)

    Zabin Visram

    2005-06-01

    Full Text Available This paper describes the philosophy, development and framework of the body of elements formulated to provide an approach to evidence-based learning sustained by Learning Objects and web based technology Due to the demands for continuous improvement in the delivery of healthcare and in the continuous endeavour to improve the quality of life, there is a continuous need for practitioner's to update their knowledge by accomplishing accredited courses. The rapid advances in medical science has meant increasingly, there is a desperate need to adopt wireless schemes, whereby bespoke courses can be developed to help practitioners keep up with expanding knowledge base. Evidently, without current best evidence, practice risks becoming rapidly out of date, to the detriment of the patient. There is a need to provide a tactical, operational and effective environment, which allows professional to update their education, and complete specialised training, just-in-time, in their own time and location. Following this demand in the marketplace the information engineering group, in combination with several medical and dental schools, set out to develop and design a conceptual framework which form the basis of pioneering research, which at last, enables practitioner's to adopt a philosophy of life long learning. The body and structure of this framework is subsumed under the term Object oriented approach to Evidence Based learning, Just-in-time, via Internet sustained by Reusable Learning Objects (The OEBJIRLO Progression. The technical pillars which permit this concept of life long learning are pivoted by the foundations of object oriented technology, Learning objects, Just-in-time education, Data Mining, intelligent Agent technology, Flash interconnectivity and remote wireless technology, which allow practitioners to update their professional skills, complete specialised training which leads to accredited qualifications. This paper sets out to develop and

  10. Managing the Gap between Curriculum Based and Problem Based Learning

    DEFF Research Database (Denmark)

    Bygholm, Ann; Buus, Lillian

    2009-01-01

    /or but rather both/and. In this paper we describe an approach to design and delivery of online courses in computer science which on the one hand is based on a specified curriculum and on the other hand gives room for different learning strategies, problem based learning being one of them. We discuss......Traditionally there has been a clear distinction between curriculum based and problem based approaches to accomplish learning. Preferred approaches depend of course on conviction, culture, traditions and also on the specific learning situation. We will argue that it is not a question of either...

  11. Quantitative learning strategies based on word networks

    Science.gov (United States)

    Zhao, Yue-Tian-Yi; Jia, Zi-Yang; Tang, Yong; Xiong, Jason Jie; Zhang, Yi-Cheng

    2018-02-01

    Learning English requires a considerable effort, but the way that vocabulary is introduced in textbooks is not optimized for learning efficiency. With the increasing population of English learners, learning process optimization will have significant impact and improvement towards English learning and teaching. The recent developments of big data analysis and complex network science provide additional opportunities to design and further investigate the strategies in English learning. In this paper, quantitative English learning strategies based on word network and word usage information are proposed. The strategies integrate the words frequency with topological structural information. By analyzing the influence of connected learned words, the learning weights for the unlearned words and dynamically updating of the network are studied and analyzed. The results suggest that quantitative strategies significantly improve learning efficiency while maintaining effectiveness. Especially, the optimized-weight-first strategy and segmented strategies outperform other strategies. The results provide opportunities for researchers and practitioners to reconsider the way of English teaching and designing vocabularies quantitatively by balancing the efficiency and learning costs based on the word network.

  12. A least-effort principle based model for heterogeneous pedestrian flow considering overtaking behavior

    Science.gov (United States)

    Liu, Chi; Ye, Rui; Lian, Liping; Song, Weiguo; Zhang, Jun; Lo, Siuming

    2018-05-01

    In the context of global aging, how to design traffic facilities for a population with a different age composition is of high importance. For this purpose, we propose a model based on the least effort principle to simulate heterogeneous pedestrian flow. In the model, the pedestrian is represented by a three-disc shaped agent. We add a new parameter to realize pedestrians' preference to avoid changing their direction of movement too quickly. The model is validated with numerous experimental data on unidirectional pedestrian flow. In addition, we investigate the influence of corridor width and velocity distribution of crowds on unidirectional heterogeneous pedestrian flow. The simulation results reflect that widening corridors could increase the specific flow for the crowd composed of two kinds of pedestrians with significantly different free velocities. Moreover, compared with a unified crowd, the crowd composed of pedestrians with great mobility differences requires a wider corridor to attain the same traffic efficiency. This study could be beneficial in providing a better understanding of heterogeneous pedestrian flow, and quantified outcomes could be applied in traffic facility design.

  13. Research and Design of Dynamic Migration Access Control Technology Based on Heterogeneous Network

    Directory of Open Access Journals (Sweden)

    Wang Feng

    2017-01-01

    Full Text Available With the continuous development of wireless networks, the amount of privacy services in heterogeneous mobile networks is increasing, such as information storage, user access, and so on. Access control security issues for heterogeneous mobile radio network, this paper proposes a dynamic migration access control technology based on heterogeneous network. Through the system architecture of the mutual trust system, we can understand the real-time mobile node failure or abnormal state. To make the service can be terminated for the node. And adopt the 802.1X authentication way to improve the security of the system. Finally, it by combining the actual running test data, the trust update algorithm of the system is optimized to reduce the actual security threats in the environment. Experiments show that the system’s anti-attack, the success rate of access, bit error rate is in line with the expected results. This system can effectively reduce the system authentication information is illegally obtained after the network security protection mechanism failure and reduce the risk of user data leakage.

  14. Modelling heterogeneous ice nucleation on mineral dust and soot with parameterizations based on laboratory experiments

    Science.gov (United States)

    Hoose, C.; Hande, L. B.; Mohler, O.; Niemand, M.; Paukert, M.; Reichardt, I.; Ullrich, R.

    2016-12-01

    Between 0 and -37°C, ice formation in clouds is triggered by aerosol particles acting as heterogeneous ice nuclei. At lower temperatures, heterogeneous ice nucleation on aerosols can occur at lower supersaturations than homogeneous freezing of solutes. In laboratory experiments, the ability of different aerosol species (e.g. desert dusts, soot, biological particles) has been studied in detail and quantified via various theoretical or empirical parameterization approaches. For experiments in the AIDA cloud chamber, we have quantified the ice nucleation efficiency via a temperature- and supersaturation dependent ice nucleation active site density. Here we present a new empirical parameterization scheme for immersion and deposition ice nucleation on desert dust and soot based on these experimental data. The application of this parameterization to the simulation of cirrus clouds, deep convective clouds and orographic clouds will be shown, including the extension of the scheme to the treatment of freezing of rain drops. The results are compared to other heterogeneous ice nucleation schemes. Furthermore, an aerosol-dependent parameterization of contact ice nucleation is presented.

  15. Intra-tumor heterogeneity in breast cancer has limited impact on transcriptomic-based molecular profiling.

    Science.gov (United States)

    Karthik, Govindasamy-Muralidharan; Rantalainen, Mattias; Stålhammar, Gustav; Lövrot, John; Ullah, Ikram; Alkodsi, Amjad; Ma, Ran; Wedlund, Lena; Lindberg, Johan; Frisell, Jan; Bergh, Jonas; Hartman, Johan

    2017-11-29

    Transcriptomic profiling of breast tumors provides opportunity for subtyping and molecular-based patient stratification. In diagnostic applications the specimen profiled should be representative of the expression profile of the whole tumor and ideally capture properties of the most aggressive part of the tumor. However, breast cancers commonly exhibit intra-tumor heterogeneity at molecular, genomic and in phenotypic level, which can arise during tumor evolution. Currently it is not established to what extent a random sampling approach may influence molecular breast cancer diagnostics. In this study we applied RNA-sequencing to quantify gene expression in 43 pieces (2-5 pieces per tumor) from 12 breast tumors (Cohort 1). We determined molecular subtype and transcriptomic grade for all tumor pieces and analysed to what extent pieces originating from the same tumors are concordant or discordant with each other. Additionally, we validated our finding in an independent cohort consisting of 19 pieces (2-6 pieces per tumor) from 6 breast tumors (Cohort 2) profiled using microarray technique. Exome sequencing was also performed on this cohort, to investigate the extent of intra-tumor genomic heterogeneity versus the intra-tumor molecular subtype classifications. Molecular subtyping was consistent in 11 out of 12 tumors and transcriptomic grade assignments were consistent in 11 out of 12 tumors as well. Molecular subtype predictions revealed consistent subtypes in four out of six patients in this cohort 2. Interestingly, we observed extensive intra-tumor genomic heterogeneity in these tumor pieces but not in their molecular subtype classifications. Our results suggest that macroscopic intra-tumoral transcriptomic heterogeneity is limited and unlikely to have an impact on molecular diagnostics for most patients.

  16. Optimal monetary policy rules: the problem of stability under heterogeneous learning

    Czech Academy of Sciences Publication Activity Database

    Bogomolova, Anna; Kolyuzhnov, Dmitri

    -, č. 379 (2008), s. 1-34 ISSN 1211-3298 R&D Projects: GA MŠk LC542 Institutional research plan: CEZ:AV0Z70850503 Keywords : monetary policy rules * New Keynesian model * adaptive learning Subject RIV: AH - Economics http://www.cerge-ei.cz/pdf/wp/Wp379.pdf

  17. The Knowledge Graph for End-to-End Learning on Heterogeneous Knowledge

    NARCIS (Netherlands)

    Wilcke, W.X.; Bloem, P.; de Boer, Viktor

    2018-01-01

    In modern machine learning,raw data is the preferred input for our models. Where a decade ago data scientists were still engineering features, manually picking out the details we thought salient, they now prefer the data in their raw form. As long as we can assume that all relevant and irrelevant

  18. Evaluating Web-Based Learning Systems

    Science.gov (United States)

    Pergola, Teresa M.; Walters, L. Melissa

    2011-01-01

    Accounting educators continuously seek ways to effectively integrate instructional technology into accounting coursework as a means to facilitate active learning environments and address the technology-driven learning preferences of the current generation of students. Most accounting textbook publishers now provide interactive, web-based learning…

  19. Arts-based Methods and Organizational Learning

    DEFF Research Database (Denmark)

    This thematic volume explores the relationship between the arts and learning in various educational contexts and across cultures, but with a focus on higher education and organizational learning. Arts-based interventions are at the heart of this volume, which addresses how they are conceived, des...

  20. Playing styles based on experiential learning theory

    NARCIS (Netherlands)

    Bontchev, Boyan; Vassileva, Dessislava; Aleksieva-Petrova, Adelina; Petrov, Milen

    2018-01-01

    In recent years, many researchers have reported positive outcomes and effects from applying computer games to the educational process. The main preconditions for an effective game-based learning process include the presence of high learning interest and the desire to study hard. Therefore,

  1. Game-Based Life-Long Learning

    NARCIS (Netherlands)

    Kelle, Sebastian; Sigurðarson, Steinn; Westera, Wim; Specht, Marcus

    2010-01-01

    Kelle, S., Sigurðarson, S., Westera, W., & Specht, M. (2011). Game-Based Life-Long Learning. In G. D. Magoulas (Ed.), E-Infrastructures and Technologies for Lifelong Learning: Next Generation Environments (pp. 337-349). Hershey, PA: IGI Global.

  2. Predicting Learned Helplessness Based on Personality

    Science.gov (United States)

    Maadikhah, Elham; Erfani, Nasrollah

    2014-01-01

    Learned helplessness as a negative motivational state can latently underlie repeated failures and create negative feelings toward the education as well as depression in students and other members of a society. The purpose of this paper is to predict learned helplessness based on students' personality traits. The research is a predictive…

  3. Jigsaw Cooperative Learning: Acid-Base Theories

    Science.gov (United States)

    Tarhan, Leman; Sesen, Burcin Acar

    2012-01-01

    This study focused on investigating the effectiveness of jigsaw cooperative learning instruction on first-year undergraduates' understanding of acid-base theories. Undergraduates' opinions about jigsaw cooperative learning instruction were also investigated. The participants of this study were 38 first-year undergraduates in chemistry education…

  4. Web-Based Learning Environment Based on Students’ Needs

    Science.gov (United States)

    Hamzah, N.; Ariffin, A.; Hamid, H.

    2017-08-01

    Traditional learning needs to be improved since it does not involve active learning among students. Therefore, in the twenty-first century, the development of internet technology in the learning environment has become the main needs of each student. One of the learning environments to meet the needs of the teaching and learning process is a web-based learning environment. This study aims to identify the characteristics of a web-based learning environment that supports students’ learning needs. The study involved 542 students from fifteen faculties in a public higher education institution in Malaysia. A quantitative method was used to collect the data via a questionnaire survey by randomly. The findings indicate that the characteristics of a web-based learning environment that support students’ needs in the process of learning are online discussion forum, lecture notes, assignments, portfolio, and chat. In conclusion, the students overwhelmingly agreed that online discussion forum is the highest requirement because the tool can provide a space for students and teachers to share knowledge and experiences related to teaching and learning.

  5. Energy Efficiency Experiments on Samsung Exynos 5 Heterogeneous Multicore using OmpSs Task Based Programming

    OpenAIRE

    Holmgren, Rune

    2015-01-01

    This thesis explore the energy efficiency of task based programming with OpenMP SuperScalar (OmpSs) on the heterogeneous Samsung Exynos 5422 system on a chip. The system features small energy efficient cores, large high performance cores and a GPGPU, and OmpSs tasks were run on all three different processors. Experiments running a genetic algorithm and a Cholesky decomposition were used to gather results. The option of running applications on the energy efficient cores, on the high perfo...

  6. Design for game based learning platforms

    DEFF Research Database (Denmark)

    Sørensen, Birgitte Holm; Meyer, Bente

    2010-01-01

    This paper focuses on the challenges related to the design of game based learning platforms for formal learning contexts that are inspired by the pupil's leisure time related use of web 2.0. The paper is based on the project Serious Games on a Global Market Place (2007-2011) founded by the Danish...... of web 2.0 and integrates theories of learning, didactics, games, play, communication, multimodality and different pedagogical approaches. In relation to the introduced model the teacher role is discussed.......This paper focuses on the challenges related to the design of game based learning platforms for formal learning contexts that are inspired by the pupil's leisure time related use of web 2.0. The paper is based on the project Serious Games on a Global Market Place (2007-2011) founded by the Danish...... Council for Strategic Research, in which an online game-based platform for English as a foreign language in primary school is studied. The paper presents a model for designing for game based learning platforms. This design is based on cultural and ethnographic based research on children's leisure time use...

  7. Intelligent Web-Based Learning System with Personalized Learning Path Guidance

    Science.gov (United States)

    Chen, C. M.

    2008-01-01

    Personalized curriculum sequencing is an important research issue for web-based learning systems because no fixed learning paths will be appropriate for all learners. Therefore, many researchers focused on developing e-learning systems with personalized learning mechanisms to assist on-line web-based learning and adaptively provide learning paths…

  8. Brain-Based Learning and Standards-Based Elementary Science.

    Science.gov (United States)

    Konecki, Loretta R.; Schiller, Ellen

    This paper explains how brain-based learning has become an area of interest to elementary school science teachers, focusing on the possible relationships between, and implications of, research on brain-based learning to the teaching of science education standards. After describing research on the brain, the paper looks at three implications from…

  9. Pathway-based Analysis of the Hidden Genetic Heterogeneities in Cancers

    Directory of Open Access Journals (Sweden)

    Xiaolei Zhao

    2014-02-01

    Full Text Available Many cancers apparently showing similar phenotypes are actually distinct at the molecular level, leading to very different responses to the same treatment. It has been recently demonstrated that pathway-based approaches are robust and reliable for genetic analysis of cancers. Nevertheless, it remains unclear whether such function-based approaches are useful in deciphering molecular heterogeneities in cancers. Therefore, we aimed to test this possibility in the present study. First, we used a NCI60 dataset to validate the ability of pathways to correctly partition samples. Next, we applied the proposed method to identify the hidden subtypes in diffuse large B-cell lymphoma (DLBCL. Finally, the clinical significance of the identified subtypes was verified using survival analysis. For the NCI60 dataset, we achieved highly accurate partitions that best fit the clinical cancer phenotypes. Subsequently, for a DLBCL dataset, we identified three hidden subtypes that showed very different 10-year overall survival rates (90%, 46% and 20% and were highly significantly (P = 0.008 correlated with the clinical survival rate. This study demonstrated that the pathway-based approach is promising for unveiling genetic heterogeneities in complex human diseases.

  10. Toward Project-based Learning and Team Formation in Open Learning Environments

    NARCIS (Netherlands)

    Spoelstra, Howard; Van Rosmalen, Peter; Sloep, Peter

    2014-01-01

    Open Learning Environments, MOOCs, as well as Social Learning Networks, embody a new approach to learning. Although both emphasise interactive participation, somewhat surprisingly, they do not readily support bond creating and motivating collaborative learning opportunities. Providing project-based

  11. Team-based learning for midwifery education.

    Science.gov (United States)

    Moore-Davis, Tonia L; Schorn, Mavis N; Collins, Michelle R; Phillippi, Julia; Holley, Sharon

    2015-01-01

    Many US health care and education stakeholder groups, recognizing the need to prepare learners for collaborative practice in complex care environments, have called for innovative approaches in health care education. Team-based learning is an educational method that relies on in-depth student preparation prior to class, individual and team knowledge assessment, and use of small-group learning to apply knowledge to complex scenarios. Although team-based learning has been studied as an approach to health care education, its application to midwifery education is not well described. A master's-level, nurse-midwifery, didactic antepartum course was revised to a team-based learning format. Student grades, course evaluations, and aggregate American Midwifery Certification Board examination pass rates for 3 student cohorts participating in the team-based course were compared with 3 student cohorts receiving traditional, lecture-based instruction. Students had mixed responses to the team-based learning format. Student evaluations improved when faculty added recorded lectures as part of student preclass preparation. Statistical comparisons were limited by variations across cohorts; however, student grades and certification examination pass rates did not change substantially after the course revision. Although initial course revision was time-consuming for faculty, subsequent iterations of the course required less effort. Team-based learning provides students with more opportunity to interact during on-site classes and may spur application of knowledge into practice. However, it is difficult to assess the effect of the team-based learning approach with current measures. Further research is needed to determine the effects of team-based learning on communication and collaboration skills, as well as long-term performance in clinical practice. This article is part of a special series of articles that address midwifery innovations in clinical practice, education, interprofessional

  12. Problem Based Learning, curriculum development and change ...

    African Journals Online (AJOL)

    Problem Based Learning, curriculum development and change process at ... was started in 1924 and has been running a traditional curriculum for 79 years. ... Methods: The stages taken during the process were described and analysed.

  13. Problem Based Learning - Linking Students and Industry

    DEFF Research Database (Denmark)

    Fink, Flemming K.

    2006-01-01

    WG2_G4 Problem based learning – linking students and industry: a case study from Aalborg, Denmark Flemming K. Flink ELITE Aalborg University In Aalborg University, Denmark, all study programmes are organised around inter-disciplinary project work in groups. Up to 50% of the study work is problem-...... is essentially problem solving. The presentation looks into on campus POPBL and the Facilitated Work Based Learning (FBL) for continuing education. It also presents case examples of POPBL work....

  14. How competition and heterogeneous collaboration interact in prevocational game-based mathematics education

    NARCIS (Netherlands)

    ter Vrugte, Judith; de Jong, Anthonius J.M.; Vandercruysse, Sylke; Wouters, Pieter; van Oostendorp, Herre; Elen, Jan

    2015-01-01

    The present study addresses the effectiveness of an educational mathematics game for improving proportional reasoning in students from prevocational education. Though in theory game-based learning is promising, research shows that results are ambiguous and that we should look into ways to support

  15. On the Dual-Decomposition-Based Resource and Power Allocation with Sleeping Strategy for Heterogeneous Networks

    KAUST Repository

    Alsharoa, Ahmad M.

    2015-05-01

    In this paper, the problem of radio and power resource management in long term evolution heterogeneous networks (LTE HetNets) is investigated. The goal is to minimize the total power consumption of the network while satisfying the user quality of service determined by each target data rate. We study the model where one macrocell base station is placed in the cell center, and multiple small cell base stations and femtocell access points are distributed around it. The dual decomposition technique is adopted to jointly optimize the power and carrier allocation in the downlink direction in addition to the selection of turned off small cell base stations. Our numerical results investigate the performance of the proposed scheme versus different system parameters and show an important saving in terms of total power consumption. © 2015 IEEE.

  16. Heterogeneous Information about the Term Structure of Interest rates, Least-Squares Learning and Optimal Interest Rate Rules for Inflation Forecast Targeting

    NARCIS (Netherlands)

    Schaling, E.; Eijffinger, S.C.W.; Tesfaselassie, M.F.

    2004-01-01

    In this paper we incorporate the term structure of interest rates in a standard inflation forecast targeting framework.Learning about the transmission process of monetary policy is introduced by having heterogeneous agents - i.e. the central bank and private agents - who have different information

  17. Hot News Recommendation System from Heterogeneous Websites Based on Bayesian Model

    Directory of Open Access Journals (Sweden)

    Zhengyou Xia

    2014-01-01

    Full Text Available The most current news recommendations are suitable for news which comes from a single news website, not for news from different heterogeneous news websites. Previous researches about news recommender systems based on different strategies have been proposed to provide news personalization services for online news readers. However, little research work has been reported on utilizing hundreds of heterogeneous news websites to provide top hot news services for group customers (e.g., government staffs. In this paper, we propose a hot news recommendation model based on Bayesian model, which is from hundreds of different news websites. In the model, we determine whether the news is hot news by calculating the joint probability of the news. We evaluate and compare our proposed recommendation model with the results of human experts on the real data sets. Experimental results demonstrate the reliability and effectiveness of our method. We also implement this model in hot news recommendation system of Hangzhou city government in year 2013, which achieves very good results.

  18. Hot news recommendation system from heterogeneous websites based on bayesian model.

    Science.gov (United States)

    Xia, Zhengyou; Xu, Shengwu; Liu, Ningzhong; Zhao, Zhengkang

    2014-01-01

    The most current news recommendations are suitable for news which comes from a single news website, not for news from different heterogeneous news websites. Previous researches about news recommender systems based on different strategies have been proposed to provide news personalization services for online news readers. However, little research work has been reported on utilizing hundreds of heterogeneous news websites to provide top hot news services for group customers (e.g., government staffs). In this paper, we propose a hot news recommendation model based on Bayesian model, which is from hundreds of different news websites. In the model, we determine whether the news is hot news by calculating the joint probability of the news. We evaluate and compare our proposed recommendation model with the results of human experts on the real data sets. Experimental results demonstrate the reliability and effectiveness of our method. We also implement this model in hot news recommendation system of Hangzhou city government in year 2013, which achieves very good results.

  19. Fuzzy Logic-Based Model That Incorporates Personality Traits for Heterogeneous Pedestrians

    Directory of Open Access Journals (Sweden)

    Zhuxin Xue

    2017-10-01

    Full Text Available Most models designed to simulate pedestrian dynamical behavior are based on the assumption that human decision-making can be described using precise values. This study proposes a new pedestrian model that incorporates fuzzy logic theory into a multi-agent system to address cognitive behavior that introduces uncertainty and imprecision during decision-making. We present a concept of decision preferences to represent the intrinsic control factors of decision-making. To realize the different decision preferences of heterogeneous pedestrians, the Five-Factor (OCEAN personality model is introduced to model the psychological characteristics of individuals. Then, a fuzzy logic-based approach is adopted for mapping the relationships between the personality traits and the decision preferences. Finally, we have developed an application using our model to simulate pedestrian dynamical behavior in several normal or non-panic scenarios, including a single-exit room, a hallway with obstacles, and a narrowing passage. The effectiveness of the proposed model is validated with a user study. The results show that the proposed model can generate more reasonable and heterogeneous behavior in the simulation and indicate that individual personality has a noticeable effect on pedestrian dynamical behavior.

  20. Learning Radiology in an Integrated Problem-Based Learning (PBL ...

    African Journals Online (AJOL)

    Background: The Faculty of Medicine (FoM) has been training health professions in Uganda since 1924. Five years ago, it decided to change the undergraduate curriculum from traditional to Problem Based Learning (PBL) and adopted the SPICES model. Radiology was integrated into the different courses throughout the 5 ...

  1. Learning Physics through Project-Based Learning Game Techniques

    Science.gov (United States)

    Baran, Medine; Maskan, Abdulkadir; Yasar, Seyma

    2018-01-01

    The aim of the present study, in which Project and game techniques are used together, is to examine the impact of project-based learning games on students' physics achievement. Participants of the study consist of 34 9th grade students (N = 34). The data were collected using achievement tests and a questionnaire. Throughout the applications, the…

  2. Problem-Based Learning in Formal and Informal Learning Environments

    Science.gov (United States)

    Shimic, Goran; Jevremovic, Aleksandar

    2012-01-01

    Problem-based learning (PBL) is a student-centered instructional strategy in which students solve problems and reflect on their experiences. Different domains need different approaches in the design of PBL systems. Therefore, we present one case study in this article: A Java Programming PBL. The application is developed as an additional module for…

  3. Constructivism Based Learning: Design and Practice

    Directory of Open Access Journals (Sweden)

    Lia Kurniawati

    2016-06-01

    Full Text Available Abstract One of many problems in the madrasahs is that learning processes less-involve students actively (teacher-centered, thus, it affects to the improvement of learning outcomes and quality of the graduates. The purposes of this study are , firstly, to analyze what type of constructivism learning models, which can be developed to overcome madrasahs’ problems. Secondly, how to design and implement a learning plan based on the developed constructivism models. This research was conducted at Private Islamic Elementary School  (Madrasah Ad-Diyanah Ciputat, South Tangerang. Research method used in this study is descriptive-qualitative research. The results showed that the active learning models based on constructivism are suitable to be developed in the Madarasah, which were the models of Problem Based Learning (PBM, Realistic Learning, Inquiry Learning and Thematic Learning and also how the development of the learning processes from the lesson plans to the learning implementation showed a paradigm shifting from teacher-centered to student-centered. Abstrak Salah satu permasalahan di madrasah-madrasah adalah proses pembelajaran yang kurang melibatkan siswa secara aktif (berpusat pada guru, sehingga hal ini mengakibatkan pada peningkatan hasil belajar dan kualitas lulusan. Tujuan dari penelitian ini adalah, pertama, untuk menganalisis jenis model pembelajaran konstruktivisme apa yang dapat dikembangkan untuk mengatasi permasalahan di madrasah. Ke dua, bagaimana merancang dan melaksanakan rencana pembelajaran berdasarkan model konstruktivisme yang dikembangkan. Penelitian ini dilaksanakan di Sekolah Dasar Swasta (madrasah Ad-Diayanah Ciputat, Tangerang Selatan. Metode penelitian yang digunakan adalah metode deskriptif-kualitatif. Hasil penelitian menunjukkan bahwa model pembelajaran aktif yang berbasis konstruktivisme sesuai untuk dikembangkan di madrasah, yakni model pembelajaran Problem Based Learning (PBL, Pembelajaran Realistis, Pembelajaran

  4. Model of Recommendation System for for Indexing and Retrieving the Learning Object based on Multiagent System

    Directory of Open Access Journals (Sweden)

    Ronaldo Lima Rocha Campos

    2012-07-01

    Full Text Available This paper proposes a multiagent system application model for indexing, retrieving and recommendation learning objects stored in different and heterogeneous repositories. The objects within these repositories are described by filled fields using different metadata standards. The searching mechanism covers several different learning object repositories and the same object can be described in these repositories by the use of different types of fields. Aiming to improve accuracy and coverage in terms of recovering a learning object and improve the signification of the results we propose an information retrieval model based on the multiagent system approach and an ontological model to describe the knowledge domain covered.

  5. Joint sparsity based heterogeneous data-level fusion for target detection and estimation

    Science.gov (United States)

    Niu, Ruixin; Zulch, Peter; Distasio, Marcello; Blasch, Erik; Shen, Dan; Chen, Genshe

    2017-05-01

    Typical surveillance systems employ decision- or feature-level fusion approaches to integrate heterogeneous sensor data, which are sub-optimal and incur information loss. In this paper, we investigate data-level heterogeneous sensor fusion. Since the sensors monitor the common targets of interest, whose states can be determined by only a few parameters, it is reasonable to assume that the measurement domain has a low intrinsic dimensionality. For heterogeneous sensor data, we develop a joint-sparse data-level fusion (JSDLF) approach based on the emerging joint sparse signal recovery techniques by discretizing the target state space. This approach is applied to fuse signals from multiple distributed radio frequency (RF) signal sensors and a video camera for joint target detection and state estimation. The JSDLF approach is data-driven and requires minimum prior information, since there is no need to know the time-varying RF signal amplitudes, or the image intensity of the targets. It can handle non-linearity in the sensor data due to state space discretization and the use of frequency/pixel selection matrices. Furthermore, for a multi-target case with J targets, the JSDLF approach only requires discretization in a single-target state space, instead of discretization in a J-target state space, as in the case of the generalized likelihood ratio test (GLRT) or the maximum likelihood estimator (MLE). Numerical examples are provided to demonstrate that the proposed JSDLF approach achieves excellent performance with near real-time accurate target position and velocity estimates.

  6. Heterogeneity of pulmonary perfusion as a mechanistic image-based phenotype in emphysema susceptible smokers.

    Science.gov (United States)

    Alford, Sara K; van Beek, Edwin J R; McLennan, Geoffrey; Hoffman, Eric A

    2010-04-20

    Recent evidence suggests that endothelial dysfunction and pathology of pulmonary vascular responses may serve as a precursor to smoking-associated emphysema. Although it is known that emphysematous destruction leads to vasculature changes, less is known about early regional vascular dysfunction which may contribute to and precede emphysematous changes. We sought to test the hypothesis, via multidetector row CT (MDCT) perfusion imaging, that smokers showing early signs of emphysema susceptibility have a greater heterogeneity in regional perfusion parameters than emphysema-free smokers and persons who had never smoked (NS). Assuming that all smokers have a consistent inflammatory response, increased perfusion heterogeneity in emphysema-susceptible smokers would be consistent with the notion that these subjects may have the inability to block hypoxic vasoconstriction in patchy, small regions of inflammation. Dynamic ECG-gated MDCT perfusion scans with a central bolus injection of contrast were acquired in 17 NS, 12 smokers with normal CT imaging studies (SNI), and 12 smokers with subtle CT findings of centrilobular emphysema (SCE). All subjects had normal spirometry. Quantitative image analysis determined regional perfusion parameters, pulmonary blood flow (PBF), and mean transit time (MTT). Mean and coefficient of variation were calculated, and statistical differences were assessed with one-way ANOVA. MDCT-based MTT and PBF measurements demonstrate globally increased heterogeneity in SCE subjects compared with NS and SNI subjects but demonstrate similarity between NS and SNI subjects. These findings demonstrate a functional lung-imaging measure that provides a more mechanistically oriented phenotype that differentiates smokers with and without evidence of emphysema susceptibility.

  7. PEDLA: predicting enhancers with a deep learning-based algorithmic framework.

    Science.gov (United States)

    Liu, Feng; Li, Hao; Ren, Chao; Bo, Xiaochen; Shu, Wenjie

    2016-06-22

    Transcriptional enhancers are non-coding segments of DNA that play a central role in the spatiotemporal regulation of gene expression programs. However, systematically and precisely predicting enhancers remain a major challenge. Although existing methods have achieved some success in enhancer prediction, they still suffer from many issues. We developed a deep learning-based algorithmic framework named PEDLA (https://github.com/wenjiegroup/PEDLA), which can directly learn an enhancer predictor from massively heterogeneous data and generalize in ways that are mostly consistent across various cell types/tissues. We first trained PEDLA with 1,114-dimensional heterogeneous features in H1 cells, and demonstrated that PEDLA framework integrates diverse heterogeneous features and gives state-of-the-art performance relative to five existing methods for enhancer prediction. We further extended PEDLA to iteratively learn from 22 training cell types/tissues. Our results showed that PEDLA manifested superior performance consistency in both training and independent test sets. On average, PEDLA achieved 95.0% accuracy and a 96.8% geometric mean (GM) of sensitivity and specificity across 22 training cell types/tissues, as well as 95.7% accuracy and a 96.8% GM across 20 independent test cell types/tissues. Together, our work illustrates the power of harnessing state-of-the-art deep learning techniques to consistently identify regulatory elements at a genome-wide scale from massively heterogeneous data across diverse cell types/tissues.

  8. MHBCDA: Mobility and Heterogeneity aware Bandwidth Efficient Cluster based Data Aggregation for Wireless Sensor Network

    DEFF Research Database (Denmark)

    Dnyaneshwar, Mantri; Prasad, Neeli R.; Prasad, Ramjee

    2013-01-01

    Wireless Sensor Network (WSN) offers a variety of novel applications for mobile targets. It generates the large amount of redundant sensing data. The data aggregation techniques are extensively used to reduce the energy consumption and increase the network lifetime, although it has the side effect...... efficient. It exploits correlation of data packets generated by varying the packet generation rate. It prevents transmission of redundant data packets by improving energy consumption by 4.11% and prolongs the network life by 34.45% as compared with state-of-the-art solutions.......-based Data Aggregation (MHBCDA) algorithm for the randomly distributed nodes. It considers the mobile sink based packet aggregation for the heterogeneous WSN. It uses predefined region for the aggregation at cluster head to minimize computation and communication cost. The MHBCDA is energy and bandwidth...

  9. A Heterogeneous Wireless Identification Network for the Localization of Animals Based on Stochastic Movements

    Directory of Open Access Journals (Sweden)

    Ivana Raos

    2009-05-01

    Full Text Available The improvement in the transmission range in wireless applications without the use of batteries remains a significant challenge in identification applications. In this paper, we describe a heterogeneous wireless identification network mostly powered by kinetic energy, which allows the localization of animals in open environments. The system relies on radio communications and a global positioning system. It is made up of primary and secondary nodes. Secondary nodes are kinetic-powered and take advantage of animal movements to activate the node and transmit a specific identifier, reducing the number of batteries of the system. Primary nodes are battery-powered and gather secondary-node transmitted information to provide it, along with position and time data, to a final base station in charge of the animal monitoring. The system allows tracking based on contextual information obtained from statistical data.

  10. A multi-chip data acquisition system based on a heterogeneous system-on-chip platform

    CERN Document Server

    Fiergolski, Adrian

    2017-01-01

    The Control and Readout Inner tracking BOard (CaRIBOu) is a versatile readout system targeting a multitude of detector prototypes. It profits from the heterogeneous platform of the Zynq System-on-Chip (SoC) and integrates in a monolithic device front-end FPGA resources with a back-end software running on a hard-core ARM-based processor. The user-friendly Linux terminal with the pre-installed DAQ software is combined with the efficiency and throughput of a system fully implemented in the FPGA fabric. The paper presents the design of the SoC-based DAQ system and its building blocks. It also shows examples of the achieved functionality for the CLICpix2 readout ASIC.

  11. A key heterogeneous structure of fractal networks based on inverse renormalization scheme

    Science.gov (United States)

    Bai, Yanan; Huang, Ning; Sun, Lina

    2018-06-01

    Self-similarity property of complex networks was found by the application of renormalization group theory. Based on this theory, network topologies can be classified into universality classes in the space of configurations. In return, through inverse renormalization scheme, a given primitive structure can grow into a pure fractal network, then adding different types of shortcuts, it exhibits different characteristics of complex networks. However, the effect of primitive structure on networks structural property has received less attention. In this paper, we introduce a degree variance index to measure the dispersion of nodes degree in the primitive structure, and investigate the effect of the primitive structure on network structural property quantified by network efficiency. Numerical simulations and theoretical analysis show a primitive structure is a key heterogeneous structure of generated networks based on inverse renormalization scheme, whether or not adding shortcuts, and the network efficiency is positively correlated with degree variance of the primitive structure.

  12. Metaheuristic Based Scheduling Meta-Tasks in Distributed Heterogeneous Computing Systems

    Directory of Open Access Journals (Sweden)

    Hesam Izakian

    2009-07-01

    Full Text Available Scheduling is a key problem in distributed heterogeneous computing systems in order to benefit from the large computing capacity of such systems and is an NP-complete problem. In this paper, we present a metaheuristic technique, namely the Particle Swarm Optimization (PSO algorithm, for this problem. PSO is a population-based search algorithm based on the simulation of the social behavior of bird flocking and fish schooling. Particles fly in problem search space to find optimal or near-optimal solutions. The scheduler aims at minimizing makespan, which is the time when finishes the latest task. Experimental studies show that the proposed method is more efficient and surpasses those of reported PSO and GA approaches for this problem.

  13. Heterogeneous all-solid multicore fiber based multipath Michelson interferometer for high temperature sensing.

    Science.gov (United States)

    Duan, Li; Zhang, Peng; Tang, Ming; Wang, Ruoxu; Zhao, Zhiyong; Fu, Songnian; Gan, Lin; Zhu, Benpeng; Tong, Weijun; Liu, Deming; Shum, Perry Ping

    2016-09-05

    A compact high temperature sensor utilizing a multipath Michelson interferometer (MI) structure based on weak coupling multicore fiber (MCF) is proposed and experimentally demonstrated. The device is fabricated by program-controlled tapering the spliced region between single mode fiber (SMF) and a segment of MCF. After that, a spherical reflective structure is formed by arc-fusion splicing the end face of MCF. Theoretical analysis has been implemented for this specific multipath MI structure; beam propagation method based simulation and corresponding experiments were performed to investigate the effect of taper and spherical end face on system's performance. Benefiting from the multipath interferences and heterogeneous structure between the center core and surrounding cores of the all-solid MCF, an enhanced temperature sensitivity of 165 pm/°C up to 900°C and a high-quality interference spectrum with 25 dB fringe visibility were achieved.

  14. GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing

    Science.gov (United States)

    Fang, Ye; Ding, Yun; Feinstein, Wei P.; Koppelman, David M.; Moreno, Juana; Jarrell, Mark; Ramanujam, J.; Brylinski, Michal

    2016-01-01

    Computational modeling of drug binding to proteins is an integral component of direct drug design. Particularly, structure-based virtual screening is often used to perform large-scale modeling of putative associations between small organic molecules and their pharmacologically relevant protein targets. Because of a large number of drug candidates to be evaluated, an accurate and fast docking engine is a critical element of virtual screening. Consequently, highly optimized docking codes are of paramount importance for the effectiveness of virtual screening methods. In this communication, we describe the implementation, tuning and performance characteristics of GeauxDock, a recently developed molecular docking program. GeauxDock is built upon the Monte Carlo algorithm and features a novel scoring function combining physics-based energy terms with statistical and knowledge-based potentials. Developed specifically for heterogeneous computing platforms, the current version of GeauxDock can be deployed on modern, multi-core Central Processing Units (CPUs) as well as massively parallel accelerators, Intel Xeon Phi and NVIDIA Graphics Processing Unit (GPU). First, we carried out a thorough performance tuning of the high-level framework and the docking kernel to produce a fast serial code, which was then ported to shared-memory multi-core CPUs yielding a near-ideal scaling. Further, using Xeon Phi gives 1.9× performance improvement over a dual 10-core Xeon CPU, whereas the best GPU accelerator, GeForce GTX 980, achieves a speedup as high as 3.5×. On that account, GeauxDock can take advantage of modern heterogeneous architectures to considerably accelerate structure-based virtual screening applications. GeauxDock is open-sourced and publicly available at www.brylinski.org/geauxdock and https://figshare.com/articles/geauxdock_tar_gz/3205249. PMID:27420300

  15. GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing.

    Directory of Open Access Journals (Sweden)

    Ye Fang

    Full Text Available Computational modeling of drug binding to proteins is an integral component of direct drug design. Particularly, structure-based virtual screening is often used to perform large-scale modeling of putative associations between small organic molecules and their pharmacologically relevant protein targets. Because of a large number of drug candidates to be evaluated, an accurate and fast docking engine is a critical element of virtual screening. Consequently, highly optimized docking codes are of paramount importance for the effectiveness of virtual screening methods. In this communication, we describe the implementation, tuning and performance characteristics of GeauxDock, a recently developed molecular docking program. GeauxDock is built upon the Monte Carlo algorithm and features a novel scoring function combining physics-based energy terms with statistical and knowledge-based potentials. Developed specifically for heterogeneous computing platforms, the current version of GeauxDock can be deployed on modern, multi-core Central Processing Units (CPUs as well as massively parallel accelerators, Intel Xeon Phi and NVIDIA Graphics Processing Unit (GPU. First, we carried out a thorough performance tuning of the high-level framework and the docking kernel to produce a fast serial code, which was then ported to shared-memory multi-core CPUs yielding a near-ideal scaling. Further, using Xeon Phi gives 1.9× performance improvement over a dual 10-core Xeon CPU, whereas the best GPU accelerator, GeForce GTX 980, achieves a speedup as high as 3.5×. On that account, GeauxDock can take advantage of modern heterogeneous architectures to considerably accelerate structure-based virtual screening applications. GeauxDock is open-sourced and publicly available at www.brylinski.org/geauxdock and https://figshare.com/articles/geauxdock_tar_gz/3205249.

  16. Game-Based Learning Theory

    Science.gov (United States)

    Laughlin, Daniel

    2008-01-01

    Persistent Immersive Synthetic Environments (PISE) are not just connection points, they are meeting places. They are the new public squares, village centers, malt shops, malls and pubs all rolled into one. They come with a sense of 'thereness" that engages the mind like a real place does. Learning starts as a real code. The code defines "objects." The objects exist in computer space, known as the "grid." The objects and space combine to create a "place." A "world" is created, Before long, the grid and code becomes obscure, and the "world maintains focus.

  17. Confabulation Based Real-time Anomaly Detection for Wide-area Surveillance Using Heterogeneous High Performance Computing Architecture

    Science.gov (United States)

    2015-06-01

    CONFABULATION BASED REAL-TIME ANOMALY DETECTION FOR WIDE-AREA SURVEILLANCE USING HETEROGENEOUS HIGH PERFORMANCE COMPUTING ARCHITECTURE SYRACUSE...DETECTION FOR WIDE-AREA SURVEILLANCE USING HETEROGENEOUS HIGH PERFORMANCE COMPUTING ARCHITECTURE 5a. CONTRACT NUMBER FA8750-12-1-0251 5b. GRANT...processors including graphic processor units (GPUs) and Intel Xeon Phi processors. Experimental results showed significant speedups, which can enable

  18. An efficient and adaptive mutual authentication framework for heterogeneous wireless sensor network-based applications.

    Science.gov (United States)

    Kumar, Pardeep; Ylianttila, Mika; Gurtov, Andrei; Lee, Sang-Gon; Lee, Hoon-Jae

    2014-02-11

    Robust security is highly coveted in real wireless sensor network (WSN) applications since wireless sensors' sense critical data from the application environment. This article presents an efficient and adaptive mutual authentication framework that suits real heterogeneous WSN-based applications (such as smart homes, industrial environments, smart grids, and healthcare monitoring). The proposed framework offers: (i) key initialization; (ii) secure network (cluster) formation (i.e., mutual authentication and dynamic key establishment); (iii) key revocation; and (iv) new node addition into the network. The correctness of the proposed scheme is formally verified. An extensive analysis shows the proposed scheme coupled with message confidentiality, mutual authentication and dynamic session key establishment, node privacy, and message freshness. Moreover, the preliminary study also reveals the proposed framework is secure against popular types of attacks, such as impersonation attacks, man-in-the-middle attacks, replay attacks, and information-leakage attacks. As a result, we believe the proposed framework achieves efficiency at reasonable computation and communication costs and it can be a safeguard to real heterogeneous WSN applications.

  19. An Efficient and Adaptive Mutual Authentication Framework for Heterogeneous Wireless Sensor Network-Based Applications

    Directory of Open Access Journals (Sweden)

    Pardeep Kumar

    2014-02-01

    Full Text Available Robust security is highly coveted in real wireless sensor network (WSN applications since wireless sensors’ sense critical data from the application environment. This article presents an efficient and adaptive mutual authentication framework that suits real heterogeneous WSN-based applications (such as smart homes, industrial environments, smart grids, and healthcare monitoring. The proposed framework offers: (i key initialization; (ii secure network (cluster formation (i.e., mutual authentication and dynamic key establishment; (iii key revocation; and (iv new node addition into the network. The correctness of the proposed scheme is formally verified. An extensive analysis shows the proposed scheme coupled with message confidentiality, mutual authentication and dynamic session key establishment, node privacy, and message freshness. Moreover, the preliminary study also reveals the proposed framework is secure against popular types of attacks, such as impersonation attacks, man-in-the-middle attacks, replay attacks, and information-leakage attacks. As a result, we believe the proposed framework achieves efficiency at reasonable computation and communication costs and it can be a safeguard to real heterogeneous WSN applications.

  20. Modeling the heterogeneity of human dynamics based on the measurements of influential users in Sina Microblog

    Science.gov (United States)

    Wang, Chenxu; Guan, Xiaohong; Qin, Tao; Yang, Tao

    2015-06-01

    Online social network has become an indispensable communication tool in the information age. The development of microblog also provides us a great opportunity to study human dynamics that play a crucial role in the design of efficient communication systems. In this paper we study the characteristics of the tweeting behavior based on the data collected from Sina Microblog. The user activity level is measured to characterize how often a user posts a tweet. We find that the user activity level follows a bimodal distribution. That is, the microblog users tend to be either active or inactive. The inter-tweeting time distribution is then measured at both the aggregate and individual levels. We find that the inter-tweeting time follows a piecewise power law distribution of two tails. Furthermore, the exponents of the two tails have different correlations with the user activity level. These findings demonstrate that the dynamics of the tweeting behavior are heterogeneous in different time scales. We then develop a dynamic model co-driven by the memory and the interest mechanism to characterize the heterogeneity. The numerical simulations validate the model and verify that the short time interval tweeting behavior is driven by the memory mechanism while the long time interval behavior by the interest mechanism.

  1. Employing Measures of Heterogeneity and an Object-Based Approach to Extrapolate Tree Species Distribution Data

    Directory of Open Access Journals (Sweden)

    Trevor G. Jones

    2014-07-01

    Full Text Available Information derived from high spatial resolution remotely sensed data is critical for the effective management of forested ecosystems. However, high spatial resolution data-sets are typically costly to acquire and process and usually provide limited geographic coverage. In contrast, moderate spatial resolution remotely sensed data, while not able to provide the spectral or spatial detail required for certain types of products and applications, offer inexpensive, comprehensive landscape-level coverage. This study assessed using an object-based approach to extrapolate detailed tree species heterogeneity beyond the extent of hyperspectral/LiDAR flightlines to the broader area covered by a Landsat scene. Using image segments, regression trees established ecologically decipherable relationships between tree species heterogeneity and the spectral properties of Landsat segments. The spectral properties of Landsat bands 4 (i.e., NIR: 0.76–0.90 µm, 5 (i.e., SWIR: 1.55–1.75 µm and 7 (SWIR: 2.08–2.35 µm were consistently selected as predictor variables, explaining approximately 50% of variance in richness and diversity. Results have important ramifications for ongoing management initiatives in the study area and are applicable to wide range of applications.

  2. The study of the price of gold futures based on heterogeneous investors' overconfidence

    Institute of Scientific and Technical Information of China (English)

    Wei Jiang; Pupu Luan; Chunpeng Yang

    2014-01-01

    Purpose-The purpose of this paper is to research and analyze the price of gold futures based on heterogeneous investors' overconfidence.Design/methodology/approach-This paper divides the traders of gold futures market into two kinds:the speculators and arbitrageurs,and then constructs a market equilibrium model of futures pricing to analyze the behaviors of the two kinds of traders with overconfidence.After getting the decision-making function,the market equilibrium futures price is attained on the condition of market clearing.Then,this paper analyzes how the overconfidence impacts on futures price,volatility of the price of gold futures and the effects on individual utility.Findings-Under different market conditions,the overconfidence psychological impacts of heterogeneous investor on the price and volatility of futures are different,sometimes completely opposite.Originality/value-In the past literature,the relationships between overconfidence and the price or volatility are positive;however,the study shows that sometimes it is positive,and sometimes it is negative

  3. Heterogeneity of compulsive buyers based on impulsivity and compulsivity dimensions: a latent profile analytic approach.

    Science.gov (United States)

    Yi, Sunghwan

    2013-07-30

    Despite the recognition that compulsive buyers are not one homogenous group, there is a dearth of theory-guided empirical investigation. Furthermore, although compulsivity and impulsivity are used as major psychiatric criteria for diagnosing compulsive buyers, these dimensions have rarely been considered in assessing the heterogeneity issue. We fill this gap by applying the motivation shift model of addiction to compulsive buying and empirically assessing the heterogeneity issue in the bi-dimensional space represented by the buying impulsivity and compulsivity dimensions. These hypotheses were tested with latent profile analysis based on survey data (N=445). Consistent with the hypothesis, we identified the cluster of buyers with high buying compulsivity and impulsivity ("compulsive-impulsive buyers"), the cluster of buyers with low buying compulsivity and high impulsivity ("impulsive excessive buyers"), and the cluster of ordinary buyers. Furthermore, it was found that disparate clusters of buyers exhibit unique dispositional tendencies. Theoretical contributions and policy implications of the findings are discussed as well. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  4. An Efficient and Adaptive Mutual Authentication Framework for Heterogeneous Wireless Sensor Network-Based Applications

    Science.gov (United States)

    Kumar, Pardeep; Ylianttila, Mika; Gurtov, Andrei; Lee, Sang-Gon; Lee, Hoon-Jae

    2014-01-01

    Robust security is highly coveted in real wireless sensor network (WSN) applications since wireless sensors' sense critical data from the application environment. This article presents an efficient and adaptive mutual authentication framework that suits real heterogeneous WSN-based applications (such as smart homes, industrial environments, smart grids, and healthcare monitoring). The proposed framework offers: (i) key initialization; (ii) secure network (cluster) formation (i.e., mutual authentication and dynamic key establishment); (iii) key revocation; and (iv) new node addition into the network. The correctness of the proposed scheme is formally verified. An extensive analysis shows the proposed scheme coupled with message confidentiality, mutual authentication and dynamic session key establishment, node privacy, and message freshness. Moreover, the preliminary study also reveals the proposed framework is secure against popular types of attacks, such as impersonation attacks, man-in-the-middle attacks, replay attacks, and information-leakage attacks. As a result, we believe the proposed framework achieves efficiency at reasonable computation and communication costs and it can be a safeguard to real heterogeneous WSN applications. PMID:24521942

  5. 7YSZ coating prepared by PS-PVD based on heterogeneous nucleation

    Directory of Open Access Journals (Sweden)

    Ziqian DENG

    2018-04-01

    Full Text Available Plasma spray-physical vapor deposition (PS-PVD as a novel coating process based on low-pressure plasma spray (LPPS has been significantly used for thermal barrier coatings (TBCs. A coating can be deposited from liquid splats, nano-sized clusters, and the vapor phase forming different structured coatings, which shows obvious advantages in contrast to conventional technologies like atmospheric plasma spray (APS and electron beam-physical vapor deposition (EB-PVD. In addition, it can be used to produce thin, dense, and porous ceramic coatings for special applications because of its special characteristics, such as high power, very low pressure, etc. These provide new opportunities to obtain different advanced microstructures, thus to meet the growing requirements of modern functional coatings. In this work, focusing on exploiting the potential of gas-phase deposition from PS-PVD, a series of 7YSZ coating experiments with various process conditions was performed in order to better understand the deposition process in PS-PVD, where coatings were deposited on different substrates including graphite and zirconia. Meanwhile, various substrate temperatures were investigated for the same substrate. As a result, a deposition mechanism of heterogeneous nucleation has been presented showing that surface energy is an important influencing factor for coating structures. Besides, undercooling of the interface between substrate and vapor phase plays an important role in coating structures. Keywords: 7YSZ, Deposition mechanism, Heterogeneous nucleation, PS-PVD, TBC

  6. Heutagogy: An alternative practice based learning approach.

    Science.gov (United States)

    Bhoyrub, John; Hurley, John; Neilson, Gavin R; Ramsay, Mike; Smith, Margaret

    2010-11-01

    Education has explored and utilised multiple approaches in attempts to enhance the learning and teaching opportunities available to adult learners. Traditional pedagogy has been both directly and indirectly affected by andragogy and transformational learning, consequently widening our understandings and approaches toward view teaching and learning. Within the context of nurse education, a major challenge has been to effectively apply these educational approaches to the complex, unpredictable and challenging environment of practice based learning. While not offered as a panacea to such challenges, heutagogy is offered in this discussion paper as an emerging and potentially highly congruent educational framework to place around practice based learning. Being an emergent theory its known conceptual underpinnings and possible applications to nurse education need to be explored and theoretically applied. Through placing the adult learner at the foreground of grasping learning opportunities as they unpredictability emerge from a sometimes chaotic environment, heutagogy can be argued as offering the potential to minimise many of the well published difficulties of coordinating practice with faculty teaching and learning. Copyright © 2010 Elsevier Ltd. All rights reserved.

  7. E-learning: Web-based education.

    Science.gov (United States)

    Sajeva, Marco

    2006-12-01

    This review introduces state-of-the-art Web-based education and shows how the e-learning model can be applied to an anaesthesia department using Open Source solutions, as well as lifelong learning programs, which is happening in several European research projects. The definition of the term e-learning is still a work in progress due to the fact that technologies are evolving every day and it is difficult to improve teaching methodologies or to adapt traditional methods to a new or already existing educational model. The European Community is funding several research projects to define the new common market place for tomorrow's educational system; this is leading to new frontiers like virtual Erasmus inter-exchange programs based on e-learning. The first step when adapting a course to e-learning is to re-define the educational/learning model adopted: cooperative learning and tutoring are the two key concepts. This means that traditional lecture notes, books and exercises are no longer effective; teaching files must use rich multimedia content and have to be developed using the new media. This can lead to several pitfalls that can be avoided with an accurate design phase.

  8. The Effects of Students' Learning Anxiety and Motivation on the Learning Achievement in the Activity Theory Based Gamified Learning Environment

    Science.gov (United States)

    Su, Chung-Ho

    2017-01-01

    The advancement of mobile game-based learning has encouraged many related studies, which has enabled students to learn more and faster. To enhance the clinical path of cardiac catheterization learning, this paper has developed a mobile 3D-CCGBLS (3D Cardiac Catheterization Game-Based Learning System) with a learning assessment for cardiac…

  9. LEARNING DIFFICULTIES: AN ANALYSIS BASED ON VIGOTSKY

    Directory of Open Access Journals (Sweden)

    Adriane Cenci

    2010-06-01

    Full Text Available We aimed, along the text, to bring a reflection upon learning difficulties based on Socio-Historical Theory, relating what is observed in schools to what has been discussed about learning difficulties and the theory proposed by Vygotsky in the early XX century. We understand that children enter school carrying experiences and knowledge from their cultural group and that school ignores such knowledge very often. Then, it is in such disengagement that emerges what we started to call learning difficulties. One cannot forget to see a child as a whole – a student is a social being constituted by culture, language and specific values to which one must be attentive.

  10. EFFECTS OF INQUIRY TRAINING LEARNING MODEL BASED MULTIMEDIA AND MOTIVATION OF PHYSICS STUDENT LEARNING OUTCOMES

    OpenAIRE

    Hayati .; Retno Dwi Suyanti

    2013-01-01

    The objective in this research: (1) Determine a better learning model to improve learning outcomes physics students among learning model Inquiry Training based multimedia and Inquiry Training learning model. (2) Determine the level of motivation to learn in affects physics student learning outcomes. (3) Knowing the interactions between the model of learning and motivation in influencing student learning outcomes. This research is a quasi experimental. The population in this research was all s...

  11. Virtual Learning Environments and Learning Forms -experiments in ICT-based learning

    DEFF Research Database (Denmark)

    Helbo, Jan; Knudsen, Morten

    2004-01-01

    This paper report the main results of a three year experiment in ICT-based distance learning. The results are based on a full scale experiment in the education, Master of Industrial Information Technology (MII) and is one of many projects deeply rooted in the project Virtual Learning Environments...... and Learning forms (ViLL). The experiment was to transfer a well functioning on-campus engineering program based on project organized collaborative learning to a technology supported distance education program. After three years the experiments indicate that adjustments are required in this transformation....... The main problem is that we do not find the same self regulatoring learning effect in the group work among the off-campus students as is the case for on-campus students. Based on feedback from evaluation questionnaires and discussions with the students didactic adjustments have been made. The revised...

  12. Differentiating case-based learning from problem-based learning after a twoday introductory workshop on case-based learning

    Directory of Open Access Journals (Sweden)

    Aqil Mohammad Daher

    2017-12-01

    Full Text Available Background Considerable overlap exists between case-based learning (CBL and problem-based learning (PBL and differentiating between the two can be difficult for a lot of the academicians. Aims This study gauged the ability of members of medical school, familiar with a problem-based learning (PBL curriculum, to differentiate between case-based learning (CBL and PBL after a two-day workshop on CBL. Methods A questionnaire was distributed to all participants, attending the introductory course on CBL. It was designed to document the basic characteristics of the respondents, their preference for either CBL or PBL, their ability to recognize differences between CBL and PBL, and their overall perception of the course. Results Of the total workshop participants, 80.5 per cent returned the completed questionnaire. The mean age of the respondents was 44.12±12.31 years and women made up a slight majority. Majority favoured CBL over PBL and felt it was more clinical, emphasizes on self-directed learning, provides more opportunities for learning, permits in-depth exploration of cases, has structured environment and encourages the use of all learning resources. On the respondents’ ability to discriminate CBL from PBL, a weighted score of 39.9 per cent indicated a failure on the part of the respondents to correctly identify differences between CBL and PBL. Less than half opined that CBL was a worthwhile progression from PBL and about third would recommend CBL over PBL. Conclusion It seems that majority of the respondents failed to adequately differentiate between CBL and PBL and didn’t favour CBL over PBL.

  13. Incorporating Problem-Based Learning in Physical Education Teacher Education

    Science.gov (United States)

    Hushman, Glenn; Napper-Owen, Gloria

    2011-01-01

    Problem-based learning (PBL) is an educational method that identifies a problem as a context for student learning. Critical-thinking skills, deductive reasoning, knowledge, and behaviors are developed as students learn how theory can be applied to practical settings. Problem-based learning encourages self-direction, lifelong learning, and sharing…

  14. Problem Based Learning and sustainability

    DEFF Research Database (Denmark)

    Pizzol, Massimo; Løkke, Søren; Schmidt, Jannick Højrup

    and challenges that the PBL model offers for developing five key competences in sustainability: (i) system thinking, (ii) interpersonal competence, (iii) anticipatory competence, (iv) strategic competence, (v) normative competences. The study draws on the experiences from PBL activities performed at Aalborg...... University (AAU), Denmark, and focuses on the teaching of Life Cycle Assessment as a method for sustainability assessment. The objective is providing recommendations for future LCA teaching and learning. PBL activites performed at AAU were evaluated critically to detemine to what extent they addressed...... of how PBL-approaches were used to develop five specific competences in sustainability. It is concluded that -for the case fo LCA teaching at AAU- the PBL model included activities to develop system thinking, interpersonal competence, and normative competence. However, the PBL approach should...

  15. 3D Game-Based Learning System for Improving Learning Achievement in Software Engineering Curriculum

    Science.gov (United States)

    Su,Chung-Ho; Cheng, Ching-Hsue

    2013-01-01

    The advancement of game-based learning has encouraged many related studies, such that students could better learn curriculum by 3-dimension virtual reality. To enhance software engineering learning, this paper develops a 3D game-based learning system to assist teaching and assess the students' motivation, satisfaction and learning achievement. A…

  16. Inquiry-based Learning in Mathematics Education

    DEFF Research Database (Denmark)

    Dreyøe, Jonas; Larsen, Dorte Moeskær; Hjelmborg, Mette Dreier

    From a grading list of 28 of the highest ranked mathematics education journals, the six highest ranked journals were chosen, and a systematic search for inquiry-based mathematics education and related keywords was conducted. This led to five important theme/issues for inquiry-based learning...

  17. Project-Based Learning in Scottish Prisons

    Science.gov (United States)

    Sams, Kirsten

    2014-01-01

    The article describes the development of a project-based approach to learning in seven Scottish prisons. It argues that the project-based approach is ideally suited to prison education due to its flexibility and ability to enrich the relatively narrow prison curriculum and create meaningful links with wider society, reducing the isolation of…

  18. Base Station Activation and Linear Transceiver Design for Optimal Resource Management in Heterogeneous Networks

    Science.gov (United States)

    Liao, Wei-Cheng; Hong, Mingyi; Liu, Ya-Feng; Luo, Zhi-Quan

    2014-08-01

    In a densely deployed heterogeneous network (HetNet), the number of pico/micro base stations (BS) can be comparable with the number of the users. To reduce the operational overhead of the HetNet, proper identification of the set of serving BSs becomes an important design issue. In this work, we show that by jointly optimizing the transceivers and determining the active set of BSs, high system resource utilization can be achieved with only a small number of BSs. In particular, we provide formulations and efficient algorithms for such joint optimization problem, under the following two common design criteria: i) minimization of the total power consumption at the BSs, and ii) maximization of the system spectrum efficiency. In both cases, we introduce a nonsmooth regularizer to facilitate the activation of the most appropriate BSs. We illustrate the efficiency and the efficacy of the proposed algorithms via extensive numerical simulations.

  19. An XML-based loose-schema approach to managing diagnostic data in heterogeneous formats

    Energy Technology Data Exchange (ETDEWEB)

    Naito, O., E-mail: naito.osamu@jaea.go.j [Japan Atomic Energy Agency, 801-1 Mukouyama, Naka, Ibaraki 311-0193 (Japan)

    2010-07-15

    An approach to managing diagnostic data in heterogenous formats by using XML-based (eXtensible Markup Language) tag files is discussed. The tag file functions like header information in ordinary data formats but it is separate from the main body of data, human readable, and self-descriptive. Thus all the necessary information for reading the contents of data can be obtained without prior information or reading the data body itself. In this paper, modeling of diagnostic data and its representation in XML are studied and a very primitive implementation of this approach in C++ is presented. The overhead of manipulating XML in a proof-of-principle code was found to be small. The merits, demerits, and possible extensions of this approach are also discussed.

  20. An XML-based loose-schema approach to managing diagnostic data in heterogeneous formats

    International Nuclear Information System (INIS)

    Naito, O.

    2010-01-01

    An approach to managing diagnostic data in heterogenous formats by using XML-based (eXtensible Markup Language) tag files is discussed. The tag file functions like header information in ordinary data formats but it is separate from the main body of data, human readable, and self-descriptive. Thus all the necessary information for reading the contents of data can be obtained without prior information or reading the data body itself. In this paper, modeling of diagnostic data and its representation in XML are studied and a very primitive implementation of this approach in C++ is presented. The overhead of manipulating XML in a proof-of-principle code was found to be small. The merits, demerits, and possible extensions of this approach are also discussed.

  1. An Energy-Efficient Underground Localization System Based on Heterogeneous Wireless Networks

    Science.gov (United States)

    Yuan, Yazhou; Chen, Cailian; Guan, Xinping; Yang, Qiuling

    2015-01-01

    A precision positioning system with energy efficiency is of great necessity for guaranteeing personnel safety in underground mines. The location information of the miners' should be transmitted to the control center timely and reliably; therefore, a heterogeneous network with the backbone based on high speed Industrial Ethernet is deployed. Since the mobile wireless nodes are working in an irregular tunnel, a specific wireless propagation model cannot fit all situations. In this paper, an underground localization system is designed to enable the adaptation to kinds of harsh tunnel environments, but also to reduce the energy consumption and thus prolong the lifetime of the network. Three key techniques are developed and implemented to improve the system performance, including a step counting algorithm with accelerometers, a power control algorithm and an adaptive packets scheduling scheme. The simulation study and experimental results show the effectiveness of the proposed algorithms and the implementation. PMID:26016918

  2. A computational method based on the integration of heterogeneous networks for predicting disease-gene associations.

    Directory of Open Access Journals (Sweden)

    Xingli Guo

    Full Text Available The identification of disease-causing genes is a fundamental challenge in human health and of great importance in improving medical care, and provides a better understanding of gene functions. Recent computational approaches based on the interactions among human proteins and disease similarities have shown their power in tackling the issue. In this paper, a novel systematic and global method that integrates two heterogeneous networks for prioritizing candidate disease-causing genes is provided, based on the observation that genes causing the same or similar diseases tend to lie close to one another in a network of protein-protein interactions. In this method, the association score function between a query disease and a candidate gene is defined as the weighted sum of all the association scores between similar diseases and neighbouring genes. Moreover, the topological correlation of these two heterogeneous networks can be incorporated into the definition of the score function, and finally an iterative algorithm is designed for this issue. This method was tested with 10-fold cross-validation on all 1,126 diseases that have at least a known causal gene, and it ranked the correct gene as one of the top ten in 622 of all the 1,428 cases, significantly outperforming a state-of-the-art method called PRINCE. The results brought about by this method were applied to study three multi-factorial disorders: breast cancer, Alzheimer disease and diabetes mellitus type 2, and some suggestions of novel causal genes and candidate disease-causing subnetworks were provided for further investigation.

  3. BClass: A Bayesian Approach Based on Mixture Models for Clustering and Classification of Heterogeneous Biological Data

    Directory of Open Access Journals (Sweden)

    Arturo Medrano-Soto

    2004-12-01

    Full Text Available Based on mixture models, we present a Bayesian method (called BClass to classify biological entities (e.g. genes when variables of quite heterogeneous nature are analyzed. Various statistical distributions are used to model the continuous/categorical data commonly produced by genetic experiments and large-scale genomic projects. We calculate the posterior probability of each entry to belong to each element (group in the mixture. In this way, an original set of heterogeneous variables is transformed into a set of purely homogeneous characteristics represented by the probabilities of each entry to belong to the groups. The number of groups in the analysis is controlled dynamically by rendering the groups as 'alive' and 'dormant' depending upon the number of entities classified within them. Using standard Metropolis-Hastings and Gibbs sampling algorithms, we constructed a sampler to approximate posterior moments and grouping probabilities. Since this method does not require the definition of similarity measures, it is especially suitable for data mining and knowledge discovery in biological databases. We applied BClass to classify genes in RegulonDB, a database specialized in information about the transcriptional regulation of gene expression in the bacterium Escherichia coli. The classification obtained is consistent with current knowledge and allowed prediction of missing values for a number of genes. BClass is object-oriented and fully programmed in Lisp-Stat. The output grouping probabilities are analyzed and interpreted using graphical (dynamically linked plots and query-based approaches. We discuss the advantages of using Lisp-Stat as a programming language as well as the problems we faced when the data volume increased exponentially due to the ever-growing number of genomic projects.

  4. Problem-Based Learning: Exploiting Knowledge of How People Learn to Promote Effective Learning

    Science.gov (United States)

    Wood, E. J.

    2004-01-01

    There is much information from educational psychology studies on how people learn. The thesis of this paper is that we should use this information to guide the ways in which we teach rather than blindly using our traditional methods. In this context, problem-based learning (PBL), as a method of teaching widely used in medical schools but…

  5. Reinforcement Learning Based Artificial Immune Classifier

    Directory of Open Access Journals (Sweden)

    Mehmet Karakose

    2013-01-01

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

  6. Virtual Learning Environments and Learning Forms -experiments in ICT-based learning

    DEFF Research Database (Denmark)

    Helbo, Jan; Knudsen, Morten

    2004-01-01

    This paper report the main results of a three year experiment in ICT-based distance learning. The results are based on a full scale experiment in the education, Master of Industrial Information Technology (MII) and is one of many projects deeply rooted in the project Virtual Learning Environments...... didactic model has until now been a positive experience........ The main problem is that we do not find the same self regulatoring learning effect in the group work among the off-campus students as is the case for on-campus students. Based on feedback from evaluation questionnaires and discussions with the students didactic adjustments have been made. The revised...

  7. Prototype-based models in machine learning.

    Science.gov (United States)

    Biehl, Michael; Hammer, Barbara; Villmann, Thomas

    2016-01-01

    An overview is given of prototype-based models in machine learning. In this framework, observations, i.e., data, are stored in terms of typical representatives. Together with a suitable measure of similarity, the systems can be employed in the context of unsupervised and supervised analysis of potentially high-dimensional, complex datasets. We discuss basic schemes of competitive vector quantization as well as the so-called neural gas approach and Kohonen's topology-preserving self-organizing map. Supervised learning in prototype systems is exemplified in terms of learning vector quantization. Most frequently, the familiar Euclidean distance serves as a dissimilarity measure. We present extensions of the framework to nonstandard measures and give an introduction to the use of adaptive distances in relevance learning. © 2016 Wiley Periodicals, Inc.

  8. Supervised Filter Learning for Representation Based Face Recognition.

    Directory of Open Access Journals (Sweden)

    Chao Bi

    Full Text Available Representation based classification methods, such as Sparse Representation Classification (SRC and Linear Regression Classification (LRC have been developed for face recognition problem successfully. However, most of these methods use the original face images without any preprocessing for recognition. Thus, their performances may be affected by some problematic factors (such as illumination and expression variances in the face images. In order to overcome this limitation, a novel supervised filter learning algorithm is proposed for representation based face recognition in this paper. The underlying idea of our algorithm is to learn a filter so that the within-class representation residuals of the faces' Local Binary Pattern (LBP features are minimized and the between-class representation residuals of the faces' LBP features are maximized. Therefore, the LBP features of filtered face images are more discriminative for representation based classifiers. Furthermore, we also extend our algorithm for heterogeneous face recognition problem. Extensive experiments are carried out on five databases and the experimental results verify the efficacy of the proposed algorithm.

  9. Competition-Based Learning: A Model for the Integration of Competitions with Project-Based Learning Using Open Source LMS

    Science.gov (United States)

    Issa, Ghassan; Hussain, Shakir M.; Al-Bahadili, Hussein

    2014-01-01

    In an effort to enhance the learning process in higher education, a new model for Competition-Based Learning (CBL) is presented. The new model utilizes two well-known learning models, namely, the Project-Based Learning (PBL) and competitions. The new model is also applied in a networked environment with emphasis on collective learning as well as…

  10. Heterogeneous Gossip

    Science.gov (United States)

    Frey, Davide; Guerraoui, Rachid; Kermarrec, Anne-Marie; Koldehofe, Boris; Mogensen, Martin; Monod, Maxime; Quéma, Vivien

    Gossip-based information dissemination protocols are considered easy to deploy, scalable and resilient to network dynamics. Load-balancing is inherent in these protocols as the dissemination work is evenly spread among all nodes. Yet, large-scale distributed systems are usually heterogeneous with respect to network capabilities such as bandwidth. In practice, a blind load-balancing strategy might significantly hamper the performance of the gossip dissemination.

  11. Pathway-based outlier method reveals heterogeneous genomic structure of autism in blood transcriptome.

    Science.gov (United States)

    Campbell, Malcolm G; Kohane, Isaac S; Kong, Sek Won

    2013-09-24

    signal, and showed that outlier groups were distinct for each implicated pathway. Moreover, our results suggest that by seeking heterogeneity, pathway-based outlier analysis can reveal expression signals that are not apparent when considering only shared group differences.

  12. Mining Learning Social Networks for Cooperative Learning with Appropriate Learning Partners in a Problem-Based Learning Environment

    Science.gov (United States)

    Chen, Chih-Ming; Chang, Chia-Cheng

    2014-01-01

    Many studies have identified web-based cooperative learning as an increasingly popular educational paradigm with potential to increase learner satisfaction and interactions. However, peer-to-peer interaction often suffers barriers owing to a failure to explore useful social interaction information in web-based cooperative learning environments.…

  13. From scientifically based research to evidence based learning

    Directory of Open Access Journals (Sweden)

    Rosa Cera

    2016-02-01

    Full Text Available This essay is a reflection on the peculiarities of the scientifically based research and on the distinctive elements of the EBL (evidence based learning, methodology used in the study on the “Relationship between Metacognition, Self-efficacy and Self-regulation in Learning”. The EBL method, based on the standardization of data, explains how the students’ learning experience can be considered as a set of “data” and can be used to explain how and when the research results can be considered generalizable and transferable to other learning situations. The reflections present in this study have also allowed us to illustrate the impact that its results have had on the micro and macro level of reality. They helped to fill in the gaps concerning the learning/teaching processes, contributed to the enrichment of the scientific literature on this subject and allowed to establish standards through rigorous techniques such as systematic reviews and meta-analysis.

  14. DEVELOPMENT OF SCIENCE PROCESS SKILLS STUDENTS WITH PROJECT BASED LEARNING MODEL- BASED TRAINING IN LEARNING PHYSICS

    Directory of Open Access Journals (Sweden)

    Ratna Malawati

    2016-06-01

    Full Text Available This study aims to improve the physics Science Process Skills Students on cognitive and psychomotor aspects by using model based Project Based Learning training.The object of this study is the Project Based Learning model used in the learning process of Computationa Physics.The method used is classroom action research through two learning cycles, each cycle consisting of the stages of planning, implementation, observation and reflection. In the first cycle of treatment with their emphasis given training in the first phase up to third in the model Project Based Learning, while the second cycle is given additional treatment with emphasis discussion is collaboration in achieving the best results for each group of products. The results of data analysis showed increased ability to think Students on cognitive and Science Process Skills in the psychomotor.

  15. Simulation-based medical teaching and learning

    Directory of Open Access Journals (Sweden)

    Abdulmohsen H Al-Elq

    2010-01-01

    Full Text Available One of the most important steps in curriculum development is the introduction of simulation- based medical teaching and learning. Simulation is a generic term that refers to an artificial representation of a real world process to achieve educational goals through experiential learning. Simulation based medical education is defined as any educational activity that utilizes simulation aides to replicate clinical scenarios. Although medical simulation is relatively new, simulation has been used for a long time in other high risk professions such as aviation. Medical simulation allows the acquisition of clinical skills through deliberate practice rather than an apprentice style of learning. Simulation tools serve as an alternative to real patients. A trainee can make mistakes and learn from them without the fear of harming the patient. There are different types and classification of simulators and their cost vary according to the degree of their resemblance to the reality, or ′fidelity′. Simulation- based learning is expensive. However, it is cost-effective if utilized properly. Medical simulation has been found to enhance clinical competence at the undergraduate and postgraduate levels. It has also been found to have many advantages that can improve patient safety and reduce health care costs through the improvement of the medical provider′s competencies. The objective of this narrative review article is to highlight the importance of simulation as a new teaching method in undergraduate and postgraduate education.

  16. Producing and scrounging during Problem Based Learning

    Directory of Open Access Journals (Sweden)

    William L. Vickery

    2013-08-01

    Full Text Available When problem based learning occurs in a social context it is open to a common social behaviour, scrounging. In the animal behaviour literature, scroungers do not attempt to find resources themselves but rather exploit resources found by other group members (referred to as producers. We know from studies of animal behaviour (including humans that scrounging can be expected whenever animals exploit resources in groups. We also know that scrounging can have deleterious effects on the group. We can expect scrounging to occur during social learning because the exchange of information (which I will consider here as a resource is essential to social learning. This exchange can be seen as each individual scrounging from the other members of the group whenever the individual learns from the work of others. However, there is a danger if some individuals learn mostly through their own efforts while others indulge in “social loafing” relying heavily on colleagues to provide knowledge. Here I propose that game theory models developed to analyse feeding in animal societies may also apply to social learning. We know from studies of birds feeding in groups that scrounging behaviour depends on the extent to which resources can be shared. Further, when scrounging is prevalent groups tend to obtain fewer resources. By contrast, in social learning we attempt to facilitate sharing of knowledge. We thus encourage scrounging and run the risk of reducing learning within study groups. Here I analyse the role of scrounging in problem based learning. I argue that scrounging is inherent and necessary to any social learning process. However, it can have perverse effects if the acquisition of facts rather than understanding comes to dominate learning objectives. Further, disparities among individuals within a group can lead certain individuals to specialise in scrounging thus undermining the functioning of the group. I suggest that motivation, problem structure

  17. Statistical parameters of random heterogeneity estimated by analysing coda waves based on finite difference method

    Science.gov (United States)

    Emoto, K.; Saito, T.; Shiomi, K.

    2017-12-01

    Short-period (2 s) seismograms. We found that the energy of the coda of long-period seismograms shows a spatially flat distribution. This phenomenon is well known in short-period seismograms and results from the scattering by small-scale heterogeneities. We estimate the statistical parameters that characterize the small-scale random heterogeneity by modelling the spatiotemporal energy distribution of long-period seismograms. We analyse three moderate-size earthquakes that occurred in southwest Japan. We calculate the spatial distribution of the energy density recorded by a dense seismograph network in Japan at the period bands of 8-16 s, 4-8 s and 2-4 s and model them by using 3-D finite difference (FD) simulations. Compared to conventional methods based on statistical theories, we can calculate more realistic synthetics by using the FD simulation. It is not necessary to assume a uniform background velocity, body or surface waves and scattering properties considered in general scattering theories. By taking the ratio of the energy of the coda area to that of the entire area, we can separately estimate the scattering and the intrinsic absorption effects. Our result reveals the spectrum of the random inhomogeneity in a wide wavenumber range including the intensity around the corner wavenumber as P(m) = 8πε2a3/(1 + a2m2)2, where ε = 0.05 and a = 3.1 km, even though past studies analysing higher-frequency records could not detect the corner. Finally, we estimate the intrinsic attenuation by modelling the decay rate of the energy. The method proposed in this study is suitable for quantifying the statistical properties of long-wavelength subsurface random inhomogeneity, which leads the way to characterizing a wider wavenumber range of spectra, including the corner wavenumber.

  18. Agent-Based Modeling of Mitochondria Links Sub-Cellular Dynamics to Cellular Homeostasis and Heterogeneity.

    Directory of Open Access Journals (Sweden)

    Giovanni Dalmasso

    Full Text Available Mitochondria are semi-autonomous organelles that supply energy for cellular biochemistry through oxidative phosphorylation. Within a cell, hundreds of mobile mitochondria undergo fusion and fission events to form a dynamic network. These morphological and mobility dynamics are essential for maintaining mitochondrial functional homeostasis, and alterations both impact and reflect cellular stress states. Mitochondrial homeostasis is further dependent on production (biogenesis and the removal of damaged mitochondria by selective autophagy (mitophagy. While mitochondrial function, dynamics, biogenesis and mitophagy are highly-integrated processes, it is not fully understood how systemic control in the cell is established to maintain homeostasis, or respond to bioenergetic demands. Here we used agent-based modeling (ABM to integrate molecular and imaging knowledge sets, and simulate population dynamics of mitochondria and their response to environmental energy demand. Using high-dimensional parameter searches we integrated experimentally-measured rates of mitochondrial biogenesis and mitophagy, and using sensitivity analysis we identified parameter influences on population homeostasis. By studying the dynamics of cellular subpopulations with distinct mitochondrial masses, our approach uncovered system properties of mitochondrial populations: (1 mitochondrial fusion and fission activities rapidly establish mitochondrial sub-population homeostasis, and total cellular levels of mitochondria alter fusion and fission activities and subpopulation distributions; (2 restricting the directionality of mitochondrial mobility does not alter morphology subpopulation distributions, but increases network transmission dynamics; and (3 maintaining mitochondrial mass homeostasis and responding to bioenergetic stress requires the integration of mitochondrial dynamics with the cellular bioenergetic state. Finally, (4 our model suggests sources of, and stress conditions

  19. Cirrus cloud mimic surfaces in the laboratory: organic acids, bases and NOx heterogeneous reactions

    Science.gov (United States)

    Sodeau, J.; Oriordan, B.

    2003-04-01

    CIRRUS CLOUD MIMIC SURFACES IN THE LABORATORY:ORGANIC ACIDS, BASES AND NOX HETEROGENEOUS REACTIONS. B. ORiordan, J. Sodeau Department of Chemistry and Environment Research Institute, University College Cork, Ireland j.sodeau@ucc.ie /Fax: +353-21-4902680 There are a variety of biogenic and anthropogenic sources for the simple carboxylic acids to be found in the troposphere giving rise to levels as high as 45 ppb in certain urban areas. In this regard it is of note that ants of genus Formica produce some 10Tg of formic acid each year; some ten times that produced by industry. The expected sinks are those generally associated with tropospheric chemistry: the major routes studied, to date, being wet and dry deposition. No studies have been carried out hitherto on the role of water-ice surfaces in the atmospheric chemistry of carboxylic acids and the purpose of this paper is to indicate their potential function in the heterogeneous release of atmospheric species such as HONO. The deposition of formic acid on a water-ice surface was studied using FT-RAIR spectroscopy over a range of temperatures between 100 and 165K. In all cases ionization to the formate (and oxonium) ions was observed. The results were confirmed by TPD (Temperature Programmed Desorption) measurements, which indicated that two distinct surface species adsorb to the ice. Potential reactions between the formic acid/formate ion surface and nitrogen dioxide were subsequently investigated by FT-RAIRS. Co-deposition experiments showed that N2O3 and the NO+ ion (associated with water) were formed as products. A mechanism is proposed to explain these results, which involves direct reaction between the organic acid and nitrogen dioxide. Similar experiments involving acetic acid also indicate ionization on a water-ice surface. The results are put into the context of atmospheric chemistry potentially occuring on cirrus cloud surfaces.

  20. EFFECT OF PROBLEM BASED LEARNING IN COMPARISION WITH LECTURE BASED LEARNING IN FORENSIC MEDICINE

    Directory of Open Access Journals (Sweden)

    Padmakumar

    2015-09-01

    Full Text Available BACKGROUND: Problem based learning (PBL is an approach to learning and instruction in which students tackle problems in small groups under the supervision of a teacher. This style of learning assumed to foster increased retention of knowledge, improve student’s gene ral problem solving skills, enhance integration of basic science concepts in to clinical problems, foster the development of self - directed learning skills and strengthen student’s intrinsic motivation. AIM: The study was conducted to compare the effect of Problem based learning in comparison with lecture based learning. SETTING: A cross - sectional study was conducted among 2nd year MBBS students of Jubilee Mission Medical College and Research Institute, Thrissur during the period of December 2014 to March 20 15. METHODOLOGY: The batch is divided into two groups (A & B, 45 in each group. By using PBL method, blunt force injuries were taught to Group - A and sharp weapon injuries to group - B. By using lecture based learning (LBL method blunt force injuries were t aught to Group - B and sharp weapon injuries to group - A. At the end of the session a test in the form of MCQ was conducted on the students to evaluate their learning outcome. OBSERVATION AND RESU LTS: In session I, the average test score of LBL group was 8.16 and PBL group was 12. The difference was statistically significant. In session - II also 45 students has participated each in LBL and PBL classes. The average of test score of LBL group was 7.267 and PBL was 11.289, which was highly significant statistical ly . CONCLUSION: Study has proven that problem based learning is an effective teaching learning method when compared to conventional lecture based learning.

  1. The effect of discovery learning and problem-based learning on middle school students’ self-regulated learning

    Science.gov (United States)

    Miatun, A.; Muntazhimah

    2018-01-01

    The aim of this research was to determine the effect of learning models on mathematics achievement viewed from student’s self-regulated learning. The learning model compared were discovery learning and problem-based learning. The population was all students at the grade VIII of Junior High School in Boyolali regency. The samples were students of SMPN 4 Boyolali, SMPN 6 Boyolali, and SMPN 4 Mojosongo. The instruments used were mathematics achievement tests and self-regulated learning questionnaire. The data were analyzed using unbalanced two-ways Anova. The conclusion was as follows: (1) discovery learning gives better achievement than problem-based learning. (2) Achievement of students who have high self-regulated learning was better than students who have medium and low self-regulated learning. (3) For discovery learning, achievement of students who have high self-regulated learning was better than students who have medium and low self-regulated learning. For problem-based learning, students who have high and medium self-regulated learning have the same achievement. (4) For students who have high self-regulated learning, discovery learning gives better achievement than problem-based learning. Students who have medium and low self-regulated learning, both learning models give the same achievement.

  2. Simulation of DNAPL migration in heterogeneous translucent porous media based on estimation of representative elementary volume

    Science.gov (United States)

    Wu, Ming; Wu, Jianfeng; Wu, Jichun

    2017-10-01

    When the dense nonaqueous phase liquid (DNAPL) comes into the subsurface environment, its migration behavior is crucially affected by the permeability and entry pressure of subsurface porous media. A prerequisite for accurately simulating DNAPL migration in aquifers is then the determination of the permeability, entry pressure and corresponding representative elementary volumes (REV) of porous media. However, the permeability, entry pressure and corresponding representative elementary volumes (REV) are hard to determine clearly. This study utilizes the light transmission micro-tomography (LTM) method to determine the permeability and entry pressure of two dimensional (2D) translucent porous media and integrates the LTM with a criterion of relative gradient error to quantify the corresponding REV of porous media. As a result, the DNAPL migration in porous media might be accurately simulated by discretizing the model at the REV dimension. To validate the quantification methods, an experiment of perchloroethylene (PCE) migration is conducted in a two-dimensional heterogeneous bench-scale aquifer cell. Based on the quantifications of permeability, entry pressure and REV scales of 2D porous media determined by the LTM and relative gradient error, different models with different sizes of discretization grid are used to simulate the PCE migration. It is shown that the model based on REV size agrees well with the experimental results over the entire migration period including calibration, verification and validation processes. This helps to better understand the microstructures of porous media and achieve accurately simulating DNAPL migration in aquifers based on the REV estimation.

  3. Bayesian inference for heterogeneous caprock permeability based on above zone pressure monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Namhata, Argha; Small, Mitchell J.; Dilmore, Robert M.; Nakles, David V.; King, Seth

    2017-02-01

    The presence of faults/ fractures or highly permeable zones in the primary sealing caprock of a CO2 storage reservoir can result in leakage of CO2. Monitoring of leakage requires the capability to detect and resolve the onset, location, and volume of leakage in a systematic and timely manner. Pressure-based monitoring possesses such capabilities. This study demonstrates a basis for monitoring network design based on the characterization of CO2 leakage scenarios through an assessment of the integrity and permeability of the caprock inferred from above zone pressure measurements. Four representative heterogeneous fractured seal types are characterized to demonstrate seal permeability ranging from highly permeable to impermeable. Based on Bayesian classification theory, the probability of each fractured caprock scenario given above zone pressure measurements with measurement error is inferred. The sensitivity to injection rate and caprock thickness is also evaluated and the probability of proper classification is calculated. The time required to distinguish between above zone pressure outcomes and the associated leakage scenarios is also computed.

  4. A Reconfigurable Readout Integrated Circuit for Heterogeneous Display-Based Multi-Sensor Systems

    Directory of Open Access Journals (Sweden)

    Kyeonghwan Park

    2017-04-01

    Full Text Available This paper presents a reconfigurable multi-sensor interface and its readout integrated circuit (ROIC for display-based multi-sensor systems, which builds up multi-sensor functions by utilizing touch screen panels. In addition to inherent touch detection, physiological and environmental sensor interfaces are incorporated. The reconfigurable feature is effectively implemented by proposing two basis readout topologies of amplifier-based and oscillator-based circuits. For noise-immune design against various noises from inherent human-touch operations, an alternate-sampling error-correction scheme is proposed and integrated inside the ROIC, achieving a 12-bit resolution of successive approximation register (SAR of analog-to-digital conversion without additional calibrations. A ROIC prototype that includes the whole proposed functions and data converters was fabricated in a 0.18 μm complementary metal oxide semiconductor (CMOS process, and its feasibility was experimentally verified to support multiple heterogeneous sensing functions of touch, electrocardiogram, body impedance, and environmental sensors.

  5. Interference-Based Decode and Forward Scheme Using Relay Nodes in Heterogeneous Networks

    Directory of Open Access Journals (Sweden)

    Kentaro Nishimori

    2012-01-01

    Full Text Available This paper proposes interference-based decode and forward scheme that utilizes relay stations (RSs. In Long-Term-Evolution (LTE- Advanced, heterogeneous networks in which femto- and picocells are overlaid onto macrocells are extensively discussed. However, interference between macro- and pico(femtocells arises due to their different transmit power levels. Unlike conventional cooperative transmission schemes, the RS decodes interference in the first transmit timing period and forwards it to the user equipment (UE in the second period. Moreover, cooperative transmission can be achieved without stopping the transmission from the base station (BS to UE when forwarding the interference from the RS to the UE by utilizing the fact that signal-to-noise power ratio (SNR between the RS and UE is much greater than that between the BS and UE. The basic performance of the proposed method is shown based on computer simulation. Moreover, the interference temperature and shadowing effect are measured when considering the coexistence between macro- and femtocells, and the performance of the proposed method is verified using measured shadowing effect.

  6. Game Based Language Learning for Bilingual Adults

    DEFF Research Database (Denmark)

    Hautopp, Heidi; Hanghøj, Thorkild

    2014-01-01

    experiences with the central goals in communicative language teaching (CLT). The paper is based on a study of The Danish Simulator when integrated in a game‐based language course with 15 students at a language center in Copenhagen during spring, 2013. The Danish Simulator consists of language drills......, the analysis presents preliminary findings in relation to students’ different experiences of The Danish Simulator and the teacher’s redesign of the game based teaching. It is concluded that the meaningful use of The Danish Simulator in a game‐based language course for bilingual adults depends on the students......What happens when a single‐player training game enters a classroom context? The use of training activities in game‐based learning (GBL) has often been criticized for letting players perform mechanical operations with no reflection upon the learning experiences involved (e.g. Egenfeldt‐Nielsen, 2005...

  7. Fuzzy-logic based learning style prediction in e-learning using web ...

    Indian Academy of Sciences (India)

    tion, especially in web environments and proposes to use Fuzzy rules to handle the uncertainty in .... learning in safe and supportive environment ... working of the proposed Fuzzy-logic based learning style prediction in e-learning. Section 4.

  8. Deep and surface learning in problem-based learning: a review of the literature

    NARCIS (Netherlands)

    D.H.J.M. Dolmans (Diana); S.M.M. Loyens (Sofie); Marcq, H. (Hélène); D. Gijbels (David)

    2016-01-01

    textabstractIn problem-based learning (PBL), implemented worldwide, students learn by discussing professionally relevant problems enhancing application and integration of knowledge, which is assumed to encourage students towards a deep learning approach in which students are intrinsically interested

  9. Deep and surface learning in problem-based learning: a review of the literature

    NARCIS (Netherlands)

    D.H.J.M. Dolmans (Diana); S.M.M. Loyens (Sofie); H. Marcq (Hélène); D. Gijbels (David)

    2015-01-01

    textabstractIn problem-based learning (PBL), implemented worldwide, students learn by discussing professionally relevant problems enhancing application and integration of knowledge, which is assumed to encourage students towards a deep learning approach in which students are intrinsically interested

  10. Toward heterogeneity in feedforward network with synaptic delays based on FitzHugh-Nagumo model

    Science.gov (United States)

    Qin, Ying-Mei; Men, Cong; Zhao, Jia; Han, Chun-Xiao; Che, Yan-Qiu

    2018-01-01

    We focus on the role of heterogeneity on the propagation of firing patterns in feedforward network (FFN). Effects of heterogeneities both in parameters of neuronal excitability and synaptic delays are investigated systematically. Neuronal heterogeneity is found to modulate firing rates and spiking regularity by changing the excitability of the network. Synaptic delays are strongly related with desynchronized and synchronized firing patterns of the FFN, which indicate that synaptic delays may play a significant role in bridging rate coding and temporal coding. Furthermore, quasi-coherence resonance (quasi-CR) phenomenon is observed in the parameter domain of connection probability and delay-heterogeneity. All these phenomena above enable a detailed characterization of neuronal heterogeneity in FFN, which may play an indispensable role in reproducing the important properties of in vivo experiments.

  11. Investigating the Learning-Theory Foundations of Game-Based Learning: A Meta-Analysis

    Science.gov (United States)

    Wu, W-H.; Hsiao, H-C.; Wu, P-L.; Lin, C-H.; Huang, S-H.

    2012-01-01

    Past studies on the issue of learning-theory foundations in game-based learning stressed the importance of establishing learning-theory foundation and provided an exploratory examination of established learning theories. However, we found research seldom addressed the development of the use or failure to use learning-theory foundations and…

  12. An Adaptive E-Learning System Based on Students' Learning Styles: An Empirical Study

    Science.gov (United States)

    Drissi, Samia; Amirat, Abdelkrim

    2016-01-01

    Personalized e-learning implementation is recognized as one of the most interesting research areas in the distance web-based education. Since the learning style of each learner is different one must fit e-learning with the different needs of learners. This paper presents an approach to integrate learning styles into adaptive e-learning hypermedia.…

  13. Game based learning for computer science education

    NARCIS (Netherlands)

    Schmitz, Birgit; Czauderna, André; Klemke, Roland; Specht, Marcus

    2011-01-01

    Schmitz, B., Czauderna, A., Klemke, R., & Specht, M. (2011). Game based learning for computer science education. In G. van der Veer, P. B. Sloep, & M. van Eekelen (Eds.), Computer Science Education Research Conference (CSERC '11) (pp. 81-86). Heerlen, The Netherlands: Open Universiteit.

  14. Using Problem-Based Learning in Accounting

    Science.gov (United States)

    Hansen, James D.

    2006-01-01

    In this article, the author describes the process of writing a problem-based learning (PBL) problem and shows how a typical end-of-chapter accounting problem can be converted to a PBL problem. PBL uses complex, real-world problems to motivate students to identify and research the concepts and principles they need to know to solve these problems.…

  15. Dialogue as base for learning professional practice

    DEFF Research Database (Denmark)

    Hansen, Birgit Heimann

    2006-01-01

    and support during this transition are a major causes of anxiety. Morover, findings highlight the importance of clinicians and academic nurses working together to ensure that students are provided with the best possible opportunities for clinical learning. This paper discusses the dialogue as base...

  16. Repository Services for Outcome-based Learning

    NARCIS (Netherlands)

    Totschnig, Michael; Derntl, Michael; Gutiérrez, Israel; Najjar, Jad; Klemke, Roland; Klerkx, Joris; Duval, Erik; Müller, Franz

    2010-01-01

    Totschnig, M., Derntl, M., Gutiérrez, I., Najjar, J., Klemke, R., Klerkx, J., Duval, E., & Müller, F. (2010). Repository Services for Outcome-based Learning. Fourth International Workshop on Search and Exchange of e-le@rning Materials (SE@M’10). September, 27-28, 2010, Barcelona, Spain.

  17. Domesticating Digital Game-based Learning

    Directory of Open Access Journals (Sweden)

    Helga Dís Sigurdardottir

    2016-07-01

    Full Text Available This paper analyses the use of digital game-based learning (DGBL in schools in Norway. It investigates the types of games used in Norwegian schools and how pupils experience that practice. Digital game-based learning is being widely employed throughout Norway as a result of the increased focus on digital skills in Norwegian education. This paper analyses that development by way of focus group interviews with a total of sixty-four pupils at four schools. Drawing upon domestication and actor-network theory, the paper provides a novel approach to the study of DGBL. The broad empirical investigation into DGBL practices furthermore provides a contribution to scholarly literature on the subject. A noteworthy finding of this study is the diversity of games employed in schools—around 30 different titles— indicating that the choice of games lies at the discretion of individual teachers. Findings from this research show that the domestication of digital game-based learning occurs through the construction of complex game-based learning assemblages. This includes the classroom and home as gaming sites, group work and individual assignments as practices, and PCs and iPads as platforms.

  18. Brain-Based Learning. Research Brief

    Science.gov (United States)

    Walker, Karen

    2005-01-01

    What does brain-based research say about how adolescents learn? The 1990s was declared as the Decade of the Brain by President Bush and Congress. With the advancement of MRIs (Magnetic Resonance Imagining) and PET (positron emission tomography) scans, it has become much easier to study live healthy brains. As a result, the concept of…

  19. Teaching Gases through Problem-Based Learning

    Science.gov (United States)

    Baran, Mukadder

    2016-01-01

    The purpose of this study was to investigate not only the applicability of the method of Problem-Based Learning (PBL) to the lesson subject of "Gasses" within the scope of the 9th grade course of Chemistry in Hakkari Gazi High School but also the influence of this method on the students' achievement levels in chemistry and on their…

  20. Computer-Based Learning in Chemistry Classes

    Science.gov (United States)

    Pietzner, Verena

    2014-01-01

    Currently not many people would doubt that computers play an essential role in both public and private life in many countries. However, somewhat surprisingly, evidence of computer use is difficult to find in German state schools although other countries have managed to implement computer-based teaching and learning in their schools. This paper…

  1. Collaborative Communication in Work Based Learning Programs

    Science.gov (United States)

    Wagner, Stephen Allen

    2017-01-01

    This basic qualitative study, using interviews and document analysis, examined reflections from a Work Based Learning (WBL) program to understand how utilizing digital collaborative communication tools influence the educational experience. The Community of Inquiry (CoI) framework was used as a theoretical frame promoting the examination of the…

  2. Game-Based Learning: A Different Perspective

    Science.gov (United States)

    Royle, Karl

    2008-01-01

    Because the goals of games and the object of school-based learning are fundamentally mismatched, efforts to integrate games into the curriculum have largely fallen flat despite the best intentions of teachers and the gaming industry. Arguing that educational game designers should be investigating ways to get education into games rather than…

  3. Prototype-based models in machine learning

    NARCIS (Netherlands)

    Biehl, Michael; Hammer, Barbara; Villmann, Thomas

    2016-01-01

    An overview is given of prototype-based models in machine learning. In this framework, observations, i.e., data, are stored in terms of typical representatives. Together with a suitable measure of similarity, the systems can be employed in the context of unsupervised and supervised analysis of

  4. Producing and Scrounging during Problem Based Learning

    Science.gov (United States)

    Vickery, William L.

    2013-01-01

    When problem based learning occurs in a social context it is open to a common social behaviour, scrounging. In the animal behaviour literature, scroungers do not attempt to find resources themselves but rather exploit resources found by other group members (referred to as producers). We know from studies of animal behaviour (including humans) that…

  5. Problem Based Learning in Engineering Education

    DEFF Research Database (Denmark)

    Dahms, Mona-Lisa; Sauerbier, Gabriele; Stubbe, Korinna

    2006-01-01

    This paper describes a recent EU-project from five European Institutions. The aim was the development and implementation of a new international Master’s programme for staff development, directed towards the introduction of Problem Based Learning methods in the field of engineering education...

  6. Lights, Camera, Project-Based Learning!

    Science.gov (United States)

    Cox, Dannon G.; Meaney, Karen S.

    2018-01-01

    A physical education instructor incorporates a teaching method known as project-based learning (PBL) in his physical education curriculum. Utilizing video-production equipment to imitate the production of a televisions show, sixth-grade students attending a charter school invited college students to share their stories about physical activity and…

  7. Explanation-based learning in infancy.

    Science.gov (United States)

    Baillargeon, Renée; DeJong, Gerald F

    2017-10-01

    In explanation-based learning (EBL), domain knowledge is leveraged in order to learn general rules from few examples. An explanation is constructed for initial exemplars and is then generalized into a candidate rule that uses only the relevant features specified in the explanation; if the rule proves accurate for a few additional exemplars, it is adopted. EBL is thus highly efficient because it combines both analytic and empirical evidence. EBL has been proposed as one of the mechanisms that help infants acquire and revise their physical rules. To evaluate this proposal, 11- and 12-month-olds (n = 260) were taught to replace their current support rule (that an object is stable when half or more of its bottom surface is supported) with a more sophisticated rule (that an object is stable when half or more of the entire object is supported). Infants saw teaching events in which asymmetrical objects were placed on a base, followed by static test displays involving a novel asymmetrical object and a novel base. When the teaching events were designed to facilitate EBL, infants learned the new rule with as few as two (12-month-olds) or three (11-month-olds) exemplars. When the teaching events were designed to impede EBL, however, infants failed to learn the rule. Together, these results demonstrate that even infants, with their limited knowledge about the world, benefit from the knowledge-based approach of EBL.

  8. Making Work-Based Learning Work

    Science.gov (United States)

    Cahill, Charlotte

    2016-01-01

    Americans seeking employment often face a conundrum: relevant work experience is a prerequisite for many jobs, but it is difficult to gain the required experience without being in the workplace. Work-based learning--activities that occur in workplaces through which youth and adults gain the knowledge, skills, and experience needed for entry or…

  9. Security of Heterogeneous Content in Cloud Based Library Information Systems Using an Ontology Based Approach

    Directory of Open Access Journals (Sweden)

    Mihai DOINEA

    2014-01-01

    Full Text Available As in any domain that involves the use of software, the library information systems take advantages of cloud computing. The paper highlights the main aspect of cloud based systems, describing some public solutions provided by the most important players on the market. Topics related to content security in cloud based services are tackled in order to emphasize the requirements that must be met by these types of systems. A cloud based implementation of an Information Library System is presented and some adjacent tools that are used together with it to provide digital content and metadata links are described. In a cloud based Information Library System security is approached by means of ontologies. Aspects such as content security in terms of digital rights are presented and a methodology for security optimization is proposed.

  10. Random Finite Set Based Bayesian Filtering with OpenCL in a Heterogeneous Platform

    Directory of Open Access Journals (Sweden)

    Biao Hu

    2017-04-01

    Full Text Available While most filtering approaches based on random finite sets have focused on improving performance, in this paper, we argue that computation times are very important in order to enable real-time applications such as pedestrian detection. Towards this goal, this paper investigates the use of OpenCL to accelerate the computation of random finite set-based Bayesian filtering in a heterogeneous system. In detail, we developed an efficient and fully-functional pedestrian-tracking system implementation, which can run under real-time constraints, meanwhile offering decent tracking accuracy. An extensive evaluation analysis was carried out to ensure the fulfillment of sufficient accuracy requirements. This was followed by extensive profiling analysis to spot the potential bottlenecks in terms of execution performance, which were then targeted to come up with an OpenCL accelerated application. Video-throughput improvements from roughly 15 fps to 100 fps (6× were observed on average while processing typical MOT benchmark videos. Moreover, the worst-case frame processing yielded an 18× advantage from nearly 2 fps to 36 fps, thereby comfortably meeting the real-time constraints. Our implementation is released as open-source code.

  11. Fuzzy Logic based Handoff Latency Reduction Mechanism in Layer 2 of Heterogeneous Mobile IPv6 Networks

    Science.gov (United States)

    Anwar, Farhat; Masud, Mosharrof H.; Latif, Suhaimi A.

    2013-12-01

    Mobile IPv6 (MIPv6) is one of the pioneer standards that support mobility in IPv6 environment. It has been designed to support different types of technologies for providing seamless communications in next generation network. However, MIPv6 and subsequent standards have some limitations due to its handoff latency. In this paper, a fuzzy logic based mechanism is proposed to reduce the handoff latency of MIPv6 for Layer 2 (L2) by scanning the Access Points (APs) while the Mobile Node (MN) is moving among different APs. Handoff latency occurs when the MN switches from one AP to another in L2. Heterogeneous network is considered in this research in order to reduce the delays in L2. Received Signal Strength Indicator (RSSI) and velocity of the MN are considered as the input of fuzzy logic technique. This technique helps the MN to measure optimum signal quality from APs for the speedy mobile node based on fuzzy logic input rules and makes a list of interfaces. A suitable interface from the list of available interfaces can be selected like WiFi, WiMAX or GSM. Simulation results show 55% handoff latency reduction and 50% packet loss improvement in L2 compared to standard to MIPv6.

  12. Fuzzy Logic based Handoff Latency Reduction Mechanism in Layer 2 of Heterogeneous Mobile IPv6 Networks

    International Nuclear Information System (INIS)

    Anwar, Farhat; Masud, Mosharrof H; Latif, Suhaimi A

    2013-01-01

    Mobile IPv6 (MIPv6) is one of the pioneer standards that support mobility in IPv6 environment. It has been designed to support different types of technologies for providing seamless communications in next generation network. However, MIPv6 and subsequent standards have some limitations due to its handoff latency. In this paper, a fuzzy logic based mechanism is proposed to reduce the handoff latency of MIPv6 for Layer 2 (L2) by scanning the Access Points (APs) while the Mobile Node (MN) is moving among different APs. Handoff latency occurs when the MN switches from one AP to another in L2. Heterogeneous network is considered in this research in order to reduce the delays in L2. Received Signal Strength Indicator (RSSI) and velocity of the MN are considered as the input of fuzzy logic technique. This technique helps the MN to measure optimum signal quality from APs for the speedy mobile node based on fuzzy logic input rules and makes a list of interfaces. A suitable interface from the list of available interfaces can be selected like WiFi, WiMAX or GSM. Simulation results show 55% handoff latency reduction and 50% packet loss improvement in L2 compared to standard to MIPv6

  13. Cesium Carbonate as a Heterogeneous Base Catalyst for Synthesis of 2-Aminothiophenes via Gewald Reaction

    Energy Technology Data Exchange (ETDEWEB)

    Moeinpour, Farid [Islamic Azad University, Bandar Abbas Branch, Abbas (Iran, Islamic Republic of); Omidinia, Raheleh; Dorostkar-Ahmadi, Nadieh; Khoshdeli, Bentalhoda [Islamic Azad University, Mashhad Branch, Mashhad (Iran, Islamic Republic of)

    2011-06-15

    We have reported a new simple catalytic method for the synthesis of 2-aminothiophenes via Gewald reaction using Cs{sub 2}CO{sub 3} as an efficient, reusable and green heterogeneous catalyst under heating conditions in refluxing ethanol. The catalyst could be recycled after a simple workup and reused at least three runs without appreciable reduction in its catalytic activity. Low catalyst loading, clean reaction profiles, simple experimental and workup procedures and high yields are some advantages of this protocol. The synthesis of substituted 2-aminothiophenes is attractive to chemical researchers as they are important intermediates in organic synthesis and frequently used as the scaffold motif of a variety of agrochemicals, dyes, and biologically active products. Thus, because of their wide utility, researchers have synthesized the substituted 2-aminothiophenes via efficient and convenient methods. The one-pot cyclocondensation of ketones with an activated α-hydrogen, a cyanomethylene containing an electron-withdrawing group such as cyanoacetate and elemental sulfur in the presence of organic base, for example, morpholine, diethylamine, etc, known as the Gewald reaction, has been one of the most well-studied multicomponent reactions in recent years. To extend the scope of the reaction, many alterations have been made to the original Gewald's base-catalyzed, two-component combination of α-mercapto ketones with cyanoacetate by varying the components and the conditions.

  14. A QoS-Based Dynamic Queue Length Scheduling Algorithm in Multiantenna Heterogeneous Systems

    Directory of Open Access Journals (Sweden)

    Verikoukis Christos

    2010-01-01

    Full Text Available The use of real-time delay-sensitive applications in wireless systems has significantly grown during the last years. Therefore the designers of wireless systems have faced a challenging issue to guarantee the required Quality of Service (QoS. On the other hand, the recent advances and the extensive use of multiple antennas have already been included in several commercial standards, where the multibeam opportunistic transmission beamforming strategies have been proposed to improve the performance of the wireless systems. A cross-layer-based dynamically tuned queue length scheduler is presented in this paper, for the Downlink of multiuser and multiantenna WLAN systems with heterogeneous traffic requirements. To align with modern wireless systems transmission strategies, an opportunistic scheduling algorithm is employed, while a priority to the different traffic classes is applied. A tradeoff between the maximization of the throughput of the system and the guarantee of the maximum allowed delay is obtained. Therefore, the length of the queue is dynamically adjusted to select the appropriate conditions based on the operator requirements.

  15. A Matlab-Based Testbed for Integration, Evaluation and Comparison of Heterogeneous Stereo Vision Matching Algorithms

    Directory of Open Access Journals (Sweden)

    Raul Correal

    2016-11-01

    Full Text Available Stereo matching is a heavily researched area with a prolific published literature and a broad spectrum of heterogeneous algorithms available in diverse programming languages. This paper presents a Matlab-based testbed that aims to centralize and standardize this variety of both current and prospective stereo matching approaches. The proposed testbed aims to facilitate the application of stereo-based methods to real situations. It allows for configuring and executing algorithms, as well as comparing results, in a fast, easy and friendly setting. Algorithms can be combined so that a series of processes can be chained and executed consecutively, using the output of a process as input for the next; some additional filtering and image processing techniques have been included within the testbed for this purpose. A use case is included to illustrate how these processes are sequenced and its effect on the results for real applications. The testbed has been conceived as a collaborative and incremental open-source project, where its code is accessible and modifiable, with the objective of receiving contributions and releasing future versions to include new algorithms and features. It is currently available online for the research community.

  16. The optimal dynamic immunization under a controlled heterogeneous node-based SIRS model

    Science.gov (United States)

    Yang, Lu-Xing; Draief, Moez; Yang, Xiaofan

    2016-05-01

    Dynamic immunizations, under which the state of the propagation network of electronic viruses can be changed by adjusting the control measures, are regarded as an alternative to static immunizations. This paper addresses the optimal dynamical immunization under the widely accepted SIRS assumption. First, based on a controlled heterogeneous node-based SIRS model, an optimal control problem capturing the optimal dynamical immunization is formulated. Second, the existence of an optimal dynamical immunization scheme is shown, and the corresponding optimality system is derived. Next, some numerical examples are given to show that an optimal immunization strategy can be worked out by numerically solving the optimality system, from which it is found that the network topology has a complex impact on the optimal immunization strategy. Finally, the difference between a payoff and the minimum payoff is estimated in terms of the deviation of the corresponding immunization strategy from the optimal immunization strategy. The proposed optimal immunization scheme is justified, because it can achieve a low level of infections at a low cost.

  17. Learning styles: individualizing computer-based learning environments

    Directory of Open Access Journals (Sweden)

    Tim Musson

    1995-12-01

    Full Text Available While the need to adapt teaching to the needs of a student is generally acknowledged (see Corno and Snow, 1986, for a wide review of the literature, little is known about the impact of individual learner-differences on the quality of learning attained within computer-based learning environments (CBLEs. What evidence there is appears to support the notion that individual differences have implications for the degree of success or failure experienced by students (Ford and Ford, 1992 and by trainee end-users of software packages (Bostrom et al, 1990. The problem is to identify the way in which specific individual characteristics of a student interact with particular features of a CBLE, and how the interaction affects the quality of the resultant learning. Teaching in a CBLE is likely to require a subset of teaching strategies different from that subset appropriate to more traditional environments, and the use of a machine may elicit different behaviours from those normally arising in a classroom context.

  18. Prototype-based active learning for lemmatization

    CSIR Research Space (South Africa)

    Daelemans, W

    2009-09-01

    Full Text Available ] and Word Length [Long to Short] with the prototypical curves (e.g. Word Frequency [High to Low] and [Word Length Short to Long]). (With regard to the learning curves representing word frequency, refer to 4.1 for an explanation of why [High to Low... of language usage [15]. Secondly, in memory-based language processing [16] it has been argued, on the basis of com- parative machine learning experiments on natural lan- guage processing data, that exceptions are crucial for obtaining high generalization...

  19. Graph-based semi-supervised learning

    CERN Document Server

    Subramanya, Amarnag

    2014-01-01

    While labeled data is expensive to prepare, ever increasing amounts of unlabeled data is becoming widely available. In order to adapt to this phenomenon, several semi-supervised learning (SSL) algorithms, which learn from labeled as well as unlabeled data, have been developed. In a separate line of work, researchers have started to realize that graphs provide a natural way to represent data in a variety of domains. Graph-based SSL algorithms, which bring together these two lines of work, have been shown to outperform the state-of-the-art in many applications in speech processing, computer visi

  20. Automatic Knowledge Base Evolution by Learning Instances

    OpenAIRE

    Kim, Sundong

    2016-01-01

    Knowledge base is the way to store structured and unstructured data throughout the web. Since the size of the web is increasing rapidly, there are huge needs to structure the knowledge in a fully automated way. However fully-automated knowledge-base evolution on the Semantic Web is a major challenges, although there are many ontology evolution techniques available. Therefore learning ontology automatically can contribute to the semantic web society significantly. In this paper, we propose ful...

  1. Tumor Heterogeneity: Mechanisms and Bases for a Reliable Application of Molecular Marker Design

    Science.gov (United States)

    Diaz-Cano, Salvador J.

    2012-01-01

    Tumor heterogeneity is a confusing finding in the assessment of neoplasms, potentially resulting in inaccurate diagnostic, prognostic and predictive tests. This tumor heterogeneity is not always a random and unpredictable phenomenon, whose knowledge helps designing better tests. The biologic reasons for this intratumoral heterogeneity would then be important to understand both the natural history of neoplasms and the selection of test samples for reliable analysis. The main factors contributing to intratumoral heterogeneity inducing gene abnormalities or modifying its expression include: the gradient ischemic level within neoplasms, the action of tumor microenvironment (bidirectional interaction between tumor cells and stroma), mechanisms of intercellular transference of genetic information (exosomes), and differential mechanisms of sequence-independent modifications of genetic material and proteins. The intratumoral heterogeneity is at the origin of tumor progression and it is also the byproduct of the selection process during progression. Any analysis of heterogeneity mechanisms must be integrated within the process of segregation of genetic changes in tumor cells during the clonal expansion and progression of neoplasms. The evaluation of these mechanisms must also consider the redundancy and pleiotropism of molecular pathways, for which appropriate surrogate markers would support the presence or not of heterogeneous genetics and the main mechanisms responsible. This knowledge would constitute a solid scientific background for future therapeutic planning. PMID:22408433

  2. Tumor Heterogeneity: Mechanisms and Bases for a Reliable Application of Molecular Marker Design

    Directory of Open Access Journals (Sweden)

    Salvador J. Diaz-Cano

    2012-02-01

    Full Text Available Tumor heterogeneity is a confusing finding in the assessment of neoplasms, potentially resulting in inaccurate diagnostic, prognostic and predictive tests. This tumor heterogeneity is not always a random and unpredictable phenomenon, whose knowledge helps designing better tests. The biologic reasons for this intratumoral heterogeneity would then be important to understand both the natural history of neoplasms and the selection of test samples for reliable analysis. The main factors contributing to intratumoral heterogeneity inducing gene abnormalities or modifying its expression include: the gradient ischemic level within neoplasms, the action of tumor microenvironment (bidirectional interaction between tumor cells and stroma, mechanisms of intercellular transference of genetic information (exosomes, and differential mechanisms of sequence-independent modifications of genetic material and proteins. The intratumoral heterogeneity is at the origin of tumor progression and it is also the byproduct of the selection process during progression. Any analysis of heterogeneity mechanisms must be integrated within the process of segregation of genetic changes in tumor cells during the clonal expansion and progression of neoplasms. The evaluation of these mechanisms must also consider the redundancy and pleiotropism of molecular pathways, for which appropriate surrogate markers would support the presence or not of heterogeneous genetics and the main mechanisms responsible. This knowledge would constitute a solid scientific background for future therapeutic planning.

  3. MEMECAHKAN MASALAH GEOGRAFI MELALUI PROBLEM BASED LEARNING

    Directory of Open Access Journals (Sweden)

    Sujiono Sujiono

    2018-01-01

    Full Text Available This study aims to determine the effect of Problem Based Learning model on geography problem-solving sklills. This research model is quasi experiment with non-equivalent control group design. The subjects of the study were the students of XI IPS SMA Negeri 1 Pulau Laut Timur, academic year 2016/2017. The assessment instrument is an essay test based on an indicator of problem solving skills, ie (1 identifying problems; (2 formulate the problem; (3 finding alternative solutions; (4 choose alternative solutions; and (5 make conclusions. Data analysis using independent sample t-test model with 5% significance level. The results showed that there is an influence of PBL model on geography problem-solving sklills. The geography problem-solving skills of experimental class with PBL model is higher than control class with conventional model. Suggestion given, that is to make a plan of learning well and doing learning PBL on outdoor study.   Keywords Problem Based Learning, problem-solving skills, geography   http://dx.doi.org/10.17977/um022v2i22017p072

  4. Novel Machine Learning-Based Techniques for Efficient Resource Allocation in Next Generation Wireless Networks

    KAUST Repository

    AlQuerm, Ismail A.

    2018-02-21

    resources management in diverse wireless networks. The core operation of the proposed architecture is decision-making for resource allocation and system’s parameters adaptation. Thus, we develop the decision-making mechanism using different artificial intelligence techniques, evaluate the performance achieved and determine the tradeoff of using one technique over the others. The techniques include decision-trees, genetic algorithm, hybrid engine based on decision-trees and case based reasoning, and supervised engine with machine learning contribution to determine the ultimate technique that suits the current environment conditions. All the proposed techniques are evaluated using testbed implementation in different topologies and scenarios. LTE networks have been considered as a potential environment for demonstration of our proposed cognitive based resource allocation techniques as they lack of radio resource management. In addition, we explore the use of enhanced online learning to perform efficient resource allocation in the upcoming 5G networks to maximize energy efficiency and data rate. The considered 5G structures are heterogeneous multi-tier networks with device to device communication and heterogeneous cloud radio access networks. We propose power and resource blocks allocation schemes to maximize energy efficiency and data rate in heterogeneous 5G networks. Moreover, traffic offloading from large cells to small cells in 5G heterogeneous networks is investigated and an online learning based traffic offloading strategy is developed to enhance energy efficiency. Energy efficiency problem in heterogeneous cloud radio access networks is tackled using online learning in centralized and distributed fashions. The proposed online learning comprises improvement features that reduce the algorithms complexities and enhance the performance achieved.

  5. Component-Based Approach in Learning Management System Development

    Science.gov (United States)

    Zaitseva, Larisa; Bule, Jekaterina; Makarov, Sergey

    2013-01-01

    The paper describes component-based approach (CBA) for learning management system development. Learning object as components of e-learning courses and their metadata is considered. The architecture of learning management system based on CBA being developed in Riga Technical University, namely its architecture, elements and possibilities are…

  6. Digital game-based learning in secondary education

    NARCIS (Netherlands)

    Huizenga, J.C.

    2017-01-01

    This PhD thesis presents research on digital game-based learning in secondary education. The main research question is: How do digital games contribute to learning, engagement and motivation to learn? The thesis contains seven chapters. Chapter one is an introduction to digital game-based learning

  7. Gameplay Engagement and Learning in Game-Based Learning: A Systematic Review

    Science.gov (United States)

    Abdul Jabbar, Azita Iliya; Felicia, Patrick

    2015-01-01

    In this review, we investigated game design features that promote engagement and learning in game-based learning (GBL) settings. The aim was to address the lack of empirical evidence on the impact of game design on learning outcomes, identify how the design of game-based activities may affect learning and engagement, and develop a set of general…

  8. Investigating the Efficiency of Scenario Based Learning and Reflective Learning Approaches in Teacher Education

    Science.gov (United States)

    Hursen, Cigdem; Fasli, Funda Gezer

    2017-01-01

    The main purpose of this research is to investigate the efficiency of scenario based learning and reflective learning approaches in teacher education. The impact of applications of scenario based learning and reflective learning on prospective teachers' academic achievement and views regarding application and professional self-competence…

  9. Learning Tools for Knowledge Nomads: Using Personal Digital Assistants (PDAs) in Web-based Learning Environments.

    Science.gov (United States)

    Loh, Christian Sebastian

    2001-01-01

    Examines how mobile computers, or personal digital assistants (PDAs), can be used in a Web-based learning environment. Topics include wireless networks on college campuses; online learning; Web-based learning technologies; synchronous and asynchronous communication via the Web; content resources; Web connections; and collaborative learning. (LRW)

  10. What if Learning Analytics Were Based on Learning Science?

    Science.gov (United States)

    Marzouk, Zahia; Rakovic, Mladen; Liaqat, Amna; Vytasek, Jovita; Samadi, Donya; Stewart-Alonso, Jason; Ram, Ilana; Woloshen, Sonya; Winne, Philip H.; Nesbit, John C.

    2016-01-01

    Learning analytics are often formatted as visualisations developed from traced data collected as students study in online learning environments. Optimal analytics inform and motivate students' decisions about adaptations that improve their learning. We observe that designs for learning often neglect theories and empirical findings in learning…

  11. Educational Change towards Problem Based Learning

    DEFF Research Database (Denmark)

    Li, Huichun

    As a promising educational approach, PBL (Problem Based Learning) has been adopted by an increasing number of higher education institutions worldwide to replace the traditional lectured based educational approach. However, the organizational change towards PBL is not easy for higher education...... universities which are transforming their traditional educational approaches to PBL. Specifically, this book is concerned with how managers, staff members, and students interpret PBL and its implementation. It reveals that the challenges for implementing PBL are closely linked to organizational members...... institutions, especially for those with a long history of Lecture Based Learning. Therefore, it is necessary to investigate the challenges and obstacles for higher education institutions which are implementing PBL. In order to address the research concern, this book involves in an intensive exploration of two...

  12. Linear time relational prototype based learning.

    Science.gov (United States)

    Gisbrecht, Andrej; Mokbel, Bassam; Schleif, Frank-Michael; Zhu, Xibin; Hammer, Barbara

    2012-10-01

    Prototype based learning offers an intuitive interface to inspect large quantities of electronic data in supervised or unsupervised settings. Recently, many techniques have been extended to data described by general dissimilarities rather than Euclidean vectors, so-called relational data settings. Unlike the Euclidean counterparts, the techniques have quadratic time complexity due to the underlying quadratic dissimilarity matrix. Thus, they are infeasible already for medium sized data sets. The contribution of this article is twofold: On the one hand we propose a novel supervised prototype based classification technique for dissimilarity data based on popular learning vector quantization (LVQ), on the other hand we transfer a linear time approximation technique, the Nyström approximation, to this algorithm and an unsupervised counterpart, the relational generative topographic mapping (GTM). This way, linear time and space methods result. We evaluate the techniques on three examples from the biomedical domain.

  13. Creative Digital Worksheet Base on Mobile Learning

    Science.gov (United States)

    Wibawa, S. C.; Cholifah, R.; Utami, A. W.; Nurhidayat, A. I.

    2018-01-01

    The student is required to understand and act in the classroom and it is very important for selecting the media learning to determine the learning outcome. An instructional media is needed to help students achieve the best learning outcome. The objectives of this study are (1) to make Android-based student worksheet, (2) to know the students’ response on Android-based student worksheet in multimedia subject, (3) to determine the student result using Android-based student worksheet. The method used was Research and Development (R&D) using post-test-only in controlled quasi-experimental group design. The subjects of the study were 2 classes, a control class and an experimental class. The results showed (1) Android-based student worksheet was categorized very good as percentage of 85%; (2) the students’ responses was categorized very good as percentage of 86.42%; (3) the experimental class results were better than control class. The average result on cognitive tests on the experimental class was 89.97 and on control class was 78.31; whether the average result on psychomotor test on the experimental class was 89.90 and on the control class was 79.83. In conclusion, student result using Android-based student worksheet was better than those without it.

  14. Kinespell: Kinesthetic Learning Activity and Assessment in a Digital Game-Based Learning Environment

    Science.gov (United States)

    Cariaga, Ada Angeli; Salvador, Jay Andrae; Solamo, Ma. Rowena; Feria, Rommel

    Various approaches in learning are commonly classified into visual, auditory and kinesthetic (VAK) learning styles. One way of addressing the VAK learning styles is through game-based learning which motivates learners pursue knowledge holistically. The paper presents Kinespell, an unconventional method of learning through digital game-based learning. Kinespell is geared towards enhancing not only the learner’s spelling abilities but also the motor skills through utilizing wireless controllers. It monitors player’s performance through integrated assessment scheme. Results show that Kinespell may accommodate the VAK learning styles and is a promising alternative to established methods in learning and assessing students’ performance in Spelling.

  15. On the Dual-Decomposition-Based Resource and Power Allocation with Sleeping Strategy for Heterogeneous Networks

    KAUST Repository

    Alsharoa, Ahmad M.; Ghazzai, Hakim; Yaacoub, Elias; Alouini, Mohamed-Slim

    2015-01-01

    In this paper, the problem of radio and power resource management in long term evolution heterogeneous networks (LTE HetNets) is investigated. The goal is to minimize the total power consumption of the network while satisfying the user quality

  16. Distinction of heterogeneity on Au nanostructured surface based on phase contrast imaging of atomic force microscopy

    International Nuclear Information System (INIS)

    Jung, Mi; Choi, Jeong-Woo

    2010-01-01

    The discrimination of the heterogeneity of different materials on nanostructured surfaces has attracted a great deal of interest in biotechnology as well as nanotechnology. Phase imaging through tapping mode of atomic force microscopy (TMAFM) can be used to distinguish the heterogeneity on a nanostructured surface. Nanostructures were fabricated using anodic aluminum oxide (AAO). An 11-mercaptoundecanoic acid (11-MUA) layer adsorbed onto the Au nanodots through self-assembly to improve the bio-compatibility. The Au nanostructures that were modified with 11-MUA and the concave surfaces were investigated using the TMAFM phase images to compare the heterogeneous and homogeneous nanostructured surfaces. Although the topography and phase images were taken simultaneously, the images were different. Therefore, the contrast in the TMAFM phase images revealed the different compositional materials on the heterogeneous nanostructure surface.

  17. Ontology-based data integration from heterogeneous urban systems : A knowledge representation framework for smart cities

    NARCIS (Netherlands)

    Psyllidis, A.

    2015-01-01

    This paper presents a novel knowledge representation framework for smart city planning and management that enables the semantic integration of heterogeneous urban data from diverse sources. Currently, the combination of information across city agencies is cumbersome, as the increasingly available

  18. A Mindfulness-Based Compassionate Living Training in a Heterogeneous Sample of Psychiatric Outpatients : a Feasibility Study

    NARCIS (Netherlands)

    Bartels-Velthuis, Agna A.; Schroevers, Maya J.; van der Ploeg, Karen; Koster, Frits; Fleer, Joke; van den Brink, Erik

    We developed a novel compassion-focused training (mindfulness-based compassionate living; MBCL) and examined its effects in a heterogeneous psychiatric outpatient population with regard to feasibility and changes in levels of depression, anxiety, mindfulness and compassion. The training consisted of

  19. Dispersal and habitat connectivity in complex heterogeneous landscapes: an analysis with a GIS based random walk model

    NARCIS (Netherlands)

    Schippers, P.; Verboom, J.; Knaapen, J.P.; Apeldoorn, van R.

    1996-01-01

    A grid-based random walk model has been developed to simulate animal dispersal, taking landscape heterogeneity and linear barriers such as roads and rivers into account. The model can be used to estimate connectivity and has been parameterized for thebadger in the central part of the Netherlands.

  20. Achievement of learning outcome after implemented physical modules based on problem based learning

    Science.gov (United States)

    Isna, R.; Masykuri, M.; Sukarmin

    2018-03-01

    Implementation of Problem BasedLearning (PBL) modules can grow the students' thinking skills to solve the problems in daily life and equip the students into higher education levels. The purpose of this research is to know the achievement of learning outcome after implementation physics module based on PBL in Newton,s Law of Gravity. This research method use the experimental method with posttest only group design. To know the achievement of student learning outcomes was analyzed using t test through application of SPSS 18. Based on research result, it is found that the average of student learning outcomes after appliying physics module based on PBL has reached the minimal exhaustiveness criteria. In addition, students' scientific attitudes also improved at each meeting. Presentation activities which contained at learning sync are also able to practice speaking skills and broaden their knowledge. Looking at some shortcomings during the study, it is suggested the issues raised into learning should be a problem close to the life of students so that, the students are more active and enthusiastic in following the learning of physics.

  1. Project Scheduling Heuristics-Based Standard PSO for Task-Resource Assignment in Heterogeneous Grid

    Directory of Open Access Journals (Sweden)

    Ruey-Maw Chen

    2011-01-01

    Full Text Available The task scheduling problem has been widely studied for assigning resources to tasks in heterogeneous grid environment. Effective task scheduling is an important issue for the performance of grid computing. Meanwhile, the task scheduling problem is an NP-complete problem. Hence, this investigation introduces a named “standard“ particle swarm optimization (PSO metaheuristic approach to efficiently solve the task scheduling problems in grid. Meanwhile, two promising heuristics based on multimode project scheduling are proposed to help in solving interesting scheduling problems. They are the best performance resource heuristic and the latest finish time heuristic. These two heuristics applied to the PSO scheme are for speeding up the search of the particle and improving the capability of finding a sound schedule. Moreover, both global communication topology and local ring communication topology are also investigated for efficient study of proposed scheme. Simulation results demonstrate that the proposed approach in this investigation can successfully solve the task-resource assignment problems in grid computing and similar scheduling problems.

  2. C-C Coupling on Single-Atom-Based Heterogeneous Catalyst.

    Science.gov (United States)

    Zhang, Xiaoyan; Sun, Zaicheng; Wang, Bin; Tang, Yu; Nguyen, Luan; Li, Yuting; Tao, Franklin Feng

    2018-01-24

    Compared to homogeneous catalysis, heterogeneous catalysis allows for ready separation of products from the catalyst and thus reuse of the catalyst. C-C coupling is typically performed on a molecular catalyst which is mixed with reactants in liquid phase during catalysis. This homogeneous mixing at a molecular level in the same phase makes separation of the molecular catalyst extremely challenging and costly. Here we demonstrated that a TiO 2 -based nanoparticle catalyst anchoring singly dispersed Pd atoms (Pd 1 /TiO 2 ) is selective and highly active for more than 10 Sonogashira C-C coupling reactions (R≡CH + R'X → R≡R'; X = Br, I; R' = aryl or vinyl). The coupling between iodobenzene and phenylacetylene on Pd 1 /TiO 2 exhibits a turnover rate of 51.0 diphenylacetylene molecules per anchored Pd atom per minute at 60 °C, with a low apparent activation barrier of 28.9 kJ/mol and no cost of catalyst separation. DFT calculations suggest that the single Pd atom bonded to surface lattice oxygen atoms of TiO 2 acts as a site to dissociatively chemisorb iodobenzene to generate an intermediate phenyl, which then couples with phenylacetylenyl bound to a surface oxygen atom. This coupling of phenyl adsorbed on Pd 1 and phenylacetylenyl bound to O ad of TiO 2 forms the product molecule, diphenylacetylene.

  3. Design of a heterogeneous subcritical nuclear reactor with molten salts based on thorium

    International Nuclear Information System (INIS)

    Medina C, D.; Hernandez A, P.; Letechipia de L, C.; Vega C, H. R.; Sajo B, L.

    2015-09-01

    This paper presents the design of a heterogeneous subcritical nuclear reactor with molten salts based on thorium, with graphite moderator and a 252 Cf source, whose dose levels at the periphery allows its use in teaching and research activities. The design was realized by the Monte Carlo method, where the geometry, dimensions and the fuel was varied in order to obtain the best design. The result was a cubic reactor of 110 cm of side, with graphite moderator and reflector. In the central part having 9 ducts of 3 cm in diameter, eight of them are 110 cm long, which were placed on the Y axis; the separation between each duct is 10 cm. The central duct has 60 cm in length and this contains the 252 Cf source, also there are two irradiation channels and the other six contain a molten salt ( 7 LiF - BeF 2 - ThF 4 - UF 4 ) as fuel. For the design the k eff was calculated, neutron spectra and ambient dose equivalent. In the first instance the above was calculated for a virgin fuel, was called case 1; then a percentage of 233 U was used and the percentage of Th was decreased and was called case 2. This with the purpose of comparing two different fuels operating within the reactor. For the two irradiation ducts three positions are used: center, back and front, in each duct in order to have different flows. (Author)

  4. Multiple co-clustering based on nonparametric mixture models with heterogeneous marginal distributions.

    Science.gov (United States)

    Tokuda, Tomoki; Yoshimoto, Junichiro; Shimizu, Yu; Okada, Go; Takamura, Masahiro; Okamoto, Yasumasa; Yamawaki, Shigeto; Doya, Kenji

    2017-01-01

    We propose a novel method for multiple clustering, which is useful for analysis of high-dimensional data containing heterogeneous types of features. Our method is based on nonparametric Bayesian mixture models in which features are automatically partitioned (into views) for each clustering solution. This feature partition works as feature selection for a particular clustering solution, which screens out irrelevant features. To make our method applicable to high-dimensional data, a co-clustering structure is newly introduced for each view. Further, the outstanding novelty of our method is that we simultaneously model different distribution families, such as Gaussian, Poisson, and multinomial distributions in each cluster block, which widens areas of application to real data. We apply the proposed method to synthetic and real data, and show that our method outperforms other multiple clustering methods both in recovering true cluster structures and in computation time. Finally, we apply our method to a depression dataset with no true cluster structure available, from which useful inferences are drawn about possible clustering structures of the data.

  5. Multiple co-clustering based on nonparametric mixture models with heterogeneous marginal distributions.

    Directory of Open Access Journals (Sweden)

    Tomoki Tokuda

    Full Text Available We propose a novel method for multiple clustering, which is useful for analysis of high-dimensional data containing heterogeneous types of features. Our method is based on nonparametric Bayesian mixture models in which features are automatically partitioned (into views for each clustering solution. This feature partition works as feature selection for a particular clustering solution, which screens out irrelevant features. To make our method applicable to high-dimensional data, a co-clustering structure is newly introduced for each view. Further, the outstanding novelty of our method is that we simultaneously model different distribution families, such as Gaussian, Poisson, and multinomial distributions in each cluster block, which widens areas of application to real data. We apply the proposed method to synthetic and real data, and show that our method outperforms other multiple clustering methods both in recovering true cluster structures and in computation time. Finally, we apply our method to a depression dataset with no true cluster structure available, from which useful inferences are drawn about possible clustering structures of the data.

  6. Graphene-Based Nanomaterials as Heterogeneous Acid Catalysts: A Comprehensive Perspective

    Directory of Open Access Journals (Sweden)

    Bhaskar Garg

    2014-09-01

    Full Text Available Acid catalysis is quite prevalent and probably one of the most routine operations in both industrial processes and research laboratories worldwide. Recently, “graphene”, a two dimensional single-layer carbon sheet with hexagonal packed lattice structure, imitative of nanomaterials, has shown great potential as alternative and eco-friendly solid carbocatalyst for a variety of acid-catalyzed reactions. Owing to their exceptional physical, chemical, and mechanical properties, graphene-based nanomaterials (G-NMs offer highly stable Brønsted acidic sites, high mass transfer, relatively large surface areas, water tolerant character, and convenient recoverability as well as recyclability, whilst retaining high activity in acid-catalyzed chemical reactions. This comprehensive review focuses on the chemistry of G-NMs, including their synthesis, characterization, properties, functionalization, and up-to-date applications in heterogeneous acid catalysis. In line with this, in certain instances readers may find herein some criticisms that should be taken as constructive and would be of value in understanding the scope and limitations of current approaches utilizing graphene and its derivatives for the same.

  7. Immunophenotypic features of dedifferentiated skull base chordoma: An insight into the intratumoural heterogeneity

    Directory of Open Access Journals (Sweden)

    Kelvin Manuel Pińa Batista

    2017-12-01

    Full Text Available Chordomas are rare and low-grade malignant solid tumours, despite their histologically benign appearance, that arise in the bone from embryonic notochordal vestiges of the axial skeleton, a mesoderm-derived structure that is involved in the process of neurulation and embryonic development. Chordomas occurring in the skull base tend to arise in the basiocciput along the clivus. Three major morphological variants have been described (classical, chondroid, and atypical/dedifferentiated. The pathogenesis and molecular mechanisms involved in chordoma development remain uncertain. From a pathological standpoint, the microenvironment of a chordoma is heterogeneous, showing a dual epithelial-mesenchymal differentiation. These tumours are characterised by slow modality of biologic growth, local recurrence, low incidence of metastasis rates, and cancer stem cell (CSC phenotype. The main molecular findings are connected with brachyury immunoexpression and activation of the downstream Akt and mTOR signalling pathways. The differentiation between typical and atypical chordomas is relevant because the tumoural microenvironment and prognosis are partially different. This review provides an insight into the recent and relevant concepts and histochemical markers expressed in chordomas, with special emphasis on dedifferentiated chordomas and their prognostic implications.

  8. Multiple co-clustering based on nonparametric mixture models with heterogeneous marginal distributions

    Science.gov (United States)

    Yoshimoto, Junichiro; Shimizu, Yu; Okada, Go; Takamura, Masahiro; Okamoto, Yasumasa; Yamawaki, Shigeto; Doya, Kenji

    2017-01-01

    We propose a novel method for multiple clustering, which is useful for analysis of high-dimensional data containing heterogeneous types of features. Our method is based on nonparametric Bayesian mixture models in which features are automatically partitioned (into views) for each clustering solution. This feature partition works as feature selection for a particular clustering solution, which screens out irrelevant features. To make our method applicable to high-dimensional data, a co-clustering structure is newly introduced for each view. Further, the outstanding novelty of our method is that we simultaneously model different distribution families, such as Gaussian, Poisson, and multinomial distributions in each cluster block, which widens areas of application to real data. We apply the proposed method to synthetic and real data, and show that our method outperforms other multiple clustering methods both in recovering true cluster structures and in computation time. Finally, we apply our method to a depression dataset with no true cluster structure available, from which useful inferences are drawn about possible clustering structures of the data. PMID:29049392

  9. An Autonomous Mobile Agent-Based Distributed Learning Architecture-A Proposal and Analytical Analysis

    Directory of Open Access Journals (Sweden)

    I. Ahmed M. J. SADIIG

    2005-10-01

    Full Text Available An Autonomous Mobile Agent-Based Distributed Learning Architecture-A Proposal and Analytical Analysis Dr. I. Ahmed M. J. SADIIG Department of Electrical & Computer EngineeringInternational Islamic University GombakKuala Lumpur-MALAYSIA ABSTRACT The traditional learning paradigm invoving face-to-face interaction with students is shifting to highly data-intensive electronic learning with the advances in Information and Communication Technology. An important component of the e-learning process is the delivery of the learning contents to their intended audience over a network. A distributed learning system is dependent on the network for the efficient delivery of its contents to the user. However, as the demand of information provision and utilization increases on the Internet, the current information service provision and utilization methods are becoming increasingly inefficient. Although new technologies have been employed for efficient learning methodologies within the context of an e-learning environment, the overall efficiency of the learning system is dependent on the mode of distribution and utilization of its learning contents. It is therefore imperative to employ new techniques to meet the service demands of current and future e-learning systems. In this paper, an architecture based on autonomous mobile agents creating a Faded Information Field is proposed. Unlike the centralized information distribution in a conventional e-learning system, the information is decentralized in the proposed architecture resulting in increased efficiency of the overall system for distribution and utilization of system learning contents efficiently and fairly. This architecture holds the potential to address the heterogeneous user requirements as well as the changing conditions of the underlying network.

  10. Content Adaptation for Heterogeneous Mobile Devices using web-based Mobile Services

    OpenAIRE

    Schmohl, Robert;Baumgarten, Uwe;Köthner, Lars

    2017-01-01

    Recent advances in mobile computing have spawned a very heterogeneous environment of mobile devices. Those devices have di erent capabilities in providing mobile services to the user, implying the challenge of considering heterogeneous devices during mobile service development. This especially encompasses the task of adapting the content, which a mobile service provides to a specific mobile device. In this paper we present an approach using a service platform, which utilizes a content adaptat...

  11. Wavelet-based compression with ROI coding support for mobile access to DICOM images over heterogeneous radio networks.

    Science.gov (United States)

    Maglogiannis, Ilias; Doukas, Charalampos; Kormentzas, George; Pliakas, Thomas

    2009-07-01

    Most of the commercial medical image viewers do not provide scalability in image compression and/or region of interest (ROI) encoding/decoding. Furthermore, these viewers do not take into consideration the special requirements and needs of a heterogeneous radio setting that is constituted by different access technologies [e.g., general packet radio services (GPRS)/ universal mobile telecommunications system (UMTS), wireless local area network (WLAN), and digital video broadcasting (DVB-H)]. This paper discusses a medical application that contains a viewer for digital imaging and communications in medicine (DICOM) images as a core module. The proposed application enables scalable wavelet-based compression, retrieval, and decompression of DICOM medical images and also supports ROI coding/decoding. Furthermore, the presented application is appropriate for use by mobile devices activating in heterogeneous radio settings. In this context, performance issues regarding the usage of the proposed application in the case of a prototype heterogeneous system setup are also discussed.

  12. The development of learning material using learning cycle 5E model based stem to improve students’ learning outcomes in Thermochemistry

    Science.gov (United States)

    sugiarti, A. C.; suyatno, S.; Sanjaya, I. G. M.

    2018-04-01

    The objective of this study is describing the feasibility of Learning Cycle 5E STEM (Science, Technology, Engineering, and Mathematics) based learning material which is appropriate to improve students’ learning achievement in Thermochemistry. The study design used 4-D models and one group pretest-posttest design to obtain the information about the improvement of sudents’ learning outcomes. The subject was learning cycle 5E based STEM learning materials which the data were collected from 30 students of Science class at 11th Grade. The techniques used in this study were validation, observation, test, and questionnaire. Some result attain: (1) all the learning materials contents were valid, (2) the practicality and the effectiveness of all the learning materials contents were classified as good. The conclution of this study based on those three condition, the Learnig Cycle 5E based STEM learning materials is appropriate to improve students’ learning outcomes in studying Thermochemistry.

  13. Mapping Students Use of Technologies in Problem Based Learning Environments

    DEFF Research Database (Denmark)

    Rongbutsri, Nikorn; Khalid, Md. Saifuddin; Ryberg, Thomas

    2011-01-01

    This paper aims to understand how students use technology to enhance their learning in problem-based learning environments. The research methodology is based on both qualitative and quantitative studies. The results are based on students’ interviews, a survey and students’ reflections in course......-related blog posts; they show that students have positive perceptions toward using technologies in problem-based learning environments....

  14. Inquiry-Based Learning in China: Lesson Learned for School Science Practices

    Science.gov (United States)

    Nuangchalerm, Prasart

    2014-01-01

    Inquiry-based learning is widely considered for science education in this era. This study aims to explore inquiry-based learning in teacher preparation program and the findings will help us to understanding what inquiry-based classroom is and how inquiry-based learning are. Data were collected by qualitative methods; classroom observation,…

  15. EFFECTS OF INQUIRY TRAINING LEARNING MODEL BASED MULTIMEDIA AND MOTIVATION OF PHYSICS STUDENT LEARNING OUTCOMES

    Directory of Open Access Journals (Sweden)

    Hayati .

    2013-06-01

    Full Text Available The objective in this research: (1 Determine a better learning model to improve learning outcomes physics students among learning model Inquiry Training based multimedia and Inquiry Training learning model. (2 Determine the level of motivation to learn in affects physics student learning outcomes. (3 Knowing the interactions between the model of learning and motivation in influencing student learning outcomes. This research is a quasi experimental. The population in this research was all students in class XI SMA Negeri 1 T.P Sunggal Semester I 2012/2013. The sample of this research was consisted of two classes with a sample of 70 peoples who are determined by purposive sampling, the IPA XI-2 as a class experiment using a model-based multimedia learning Training Inquiry as many as 35 peoples and XI IPA-3 as a control class using learning model Inquiry Training 35 peoples. Hypotheses were analyzed using the GLM at significant level of 0.05 using SPSS 17.0 for Windows. Based on data analysis and hypothesis testing conducted found that: (1 Training Inquiry-based multimedia learning model in improving student learning outcomes rather than learning model physics Inquiry Training. (2 The results of studying physics students who have high motivation to learn better than students who have a low learning motivation. (3 From this research there was an interaction between learning model inquiry-based multimedia training and motivation to study on learning outcomes of students.

  16. A Survey of Technologies Supporting Virtual Project Based Learning

    DEFF Research Database (Denmark)

    Dirckinck-Holmfeld, Lone

    2002-01-01

    This paper describes a survey of technologies and to what extent they support virtual project based learning. The paper argues that a survey of learning technologies should be related to concrete learning tasks and processes. Problem oriented project pedagogy (POPP) is discussed, and a framework...... for evaluation is proposed where negotiation of meaning, coordination and resource management are identified as the key concepts in virtual project based learning. Three e-learning systems are selected for the survey, Virtual-U, Lotus Learningspace and Lotus Quickplace, as each system offers different strategies...... for e-learning. The paper concludes that virtual project based learning may benefit from facilities of all these systems....

  17. A Learning Algorithm based on High School Teaching Wisdom

    OpenAIRE

    Philip, Ninan Sajeeth

    2010-01-01

    A learning algorithm based on primary school teaching and learning is presented. The methodology is to continuously evaluate a student and to give them training on the examples for which they repeatedly fail, until, they can correctly answer all types of questions. This incremental learning procedure produces better learning curves by demanding the student to optimally dedicate their learning time on the failed examples. When used in machine learning, the algorithm is found to train a machine...

  18. Conduction and Narrow Escape in Dense, Disordered, Particulate-based Heterogeneous Materials

    Science.gov (United States)

    Lechman, Jeremy

    For optimal and reliable performance, many technological devices rely on complex, disordered heterogeneous or composite materials and their associated manufacturing processes. Examples include many powder and particulate-based materials found in phyrotechnic devices for car airbags, electrodes in energy storage devices, and various advanced composite materials. Due to their technological importance and complex structure, these materials have been the subject of much research in a number of fields. Moreover, the advent of new manufacturing techniques based on powder bed and particulate process routes, the potential of functional nano-structured materials, and the additional recognition of persistent shortcomings in predicting reliable performance of high consequence applications; leading to ballooning costs of fielding and maintaining advanced technologies, should motivate renewed efforts in understanding, predicting and controlling these materials' fabrication and behavior. Our particular effort seeks to understand the link between the top-down control presented in specific non-equilibrium processes routes (i.e., manufacturing processes) and the variability and uncertainty of the end product performance. Our ultimate aim is to quantify the variability inherent in these constrained dynamical or random processes and to use it to optimize and predict resulting material properties/performance and to inform component design with precise margins. In fact, this raises a set of deep and broad-ranging issues that have been recognized and as touching the core of a major research challenge at Sandia National Laboratories. In this talk, we will give an overview of recent efforts to address aspects of this vision. In particular the case of conductive properties of packed particulate materials will be highlighted. Combining a number of existing approaches we will discuss new insights and potential directions for further development toward the stated goal. Sandia National

  19. Base Station Placement Algorithm for Large-Scale LTE Heterogeneous Networks.

    Science.gov (United States)

    Lee, Seungseob; Lee, SuKyoung; Kim, Kyungsoo; Kim, Yoon Hyuk

    2015-01-01

    Data traffic demands in cellular networks today are increasing at an exponential rate, giving rise to the development of heterogeneous networks (HetNets), in which small cells complement traditional macro cells by extending coverage to indoor areas. However, the deployment of small cells as parts of HetNets creates a key challenge for operators' careful network planning. In particular, massive and unplanned deployment of base stations can cause high interference, resulting in highly degrading network performance. Although different mathematical modeling and optimization methods have been used to approach various problems related to this issue, most traditional network planning models are ill-equipped to deal with HetNet-specific characteristics due to their focus on classical cellular network designs. Furthermore, increased wireless data demands have driven mobile operators to roll out large-scale networks of small long term evolution (LTE) cells. Therefore, in this paper, we aim to derive an optimum network planning algorithm for large-scale LTE HetNets. Recently, attempts have been made to apply evolutionary algorithms (EAs) to the field of radio network planning, since they are characterized as global optimization methods. Yet, EA performance often deteriorates rapidly with the growth of search space dimensionality. To overcome this limitation when designing optimum network deployments for large-scale LTE HetNets, we attempt to decompose the problem and tackle its subcomponents individually. Particularly noting that some HetNet cells have strong correlations due to inter-cell interference, we propose a correlation grouping approach in which cells are grouped together according to their mutual interference. Both the simulation and analytical results indicate that the proposed solution outperforms the random-grouping based EA as well as an EA that detects interacting variables by monitoring the changes in the objective function algorithm in terms of system

  20. Inquiry based learning in physical education

    DEFF Research Database (Denmark)

    Østergaard, Lars Domino

    2014-01-01

    The present project is a case study founded on the decreasing motivation and engagement in physical education. The project suggests inquiry based learning (IBL) as an educational methodology. This may help to turn the trend as IBL has shown to engage and motivate students at different educational...... levels and within different subjects. In this pilot research project performed at a physical education teacher education program, qualitative methods were chosen to investigate students’ motivation and engagement within an IBL-unit in physical education and to accentuate challenges, advantages...... and disadvantages within the IBL-methodology in relation to students’ motivation. Instructed in guided inquiry, 32 students of physical education in a teacher training college worked with inquiry based learning in physical education over a four week period. During the IBL-unit, qualitative data such as the students...

  1. Contextual Approach with Guided Discovery Learning and Brain Based Learning in Geometry Learning

    Science.gov (United States)

    Kartikaningtyas, V.; Kusmayadi, T. A.; Riyadi

    2017-09-01

    The aim of this study was to combine the contextual approach with Guided Discovery Learning (GDL) and Brain Based Learning (BBL) in geometry learning of junior high school. Furthermore, this study analysed the effect of contextual approach with GDL and BBL in geometry learning. GDL-contextual and BBL-contextual was built from the steps of GDL and BBL that combined with the principles of contextual approach. To validate the models, it uses quasi experiment which used two experiment groups. The sample had been chosen by stratified cluster random sampling. The sample was 150 students of grade 8th in junior high school. The data were collected through the student’s mathematics achievement test that given after the treatment of each group. The data analysed by using one way ANOVA with different cell. The result shows that GDL-contextual has not different effect than BBL-contextual on mathematics achievement in geometry learning. It means both the two models could be used in mathematics learning as the innovative way in geometry learning.

  2. Game Based Learning (GBL) adoption model for universities: cesim ...

    African Journals Online (AJOL)

    Game Based Learning (GBL) adoption model for universities: cesim simulation. ... The global market has escalated the need of Game Based Learning (GBL) to offer a wide range of courses since there is a ... AJOL African Journals Online.

  3. Online constrained model-based reinforcement learning

    CSIR Research Space (South Africa)

    Van Niekerk, B

    2017-08-01

    Full Text Available Constrained Model-based Reinforcement Learning Benjamin van Niekerk School of Computer Science University of the Witwatersrand South Africa Andreas Damianou∗ Amazon.com Cambridge, UK Benjamin Rosman Council for Scientific and Industrial Research, and School... MULTIPLE SHOOTING Using direct multiple shooting (Bock and Plitt, 1984), problem (1) can be transformed into a structured non- linear program (NLP). First, the time horizon [t0, t0 + T ] is partitioned into N equal subintervals [tk, tk+1] for k = 0...

  4. Bridging disciplines through problem based learning

    DEFF Research Database (Denmark)

    Stentoft, Diana

    2011-01-01

    This paper examines whether a problem based approach to students’ learning may support interdisciplinary education at university level, where students are required to engage with the complexities inherent in constructing knowledge across disciplinary boundaries. These complexities include students...... engaging with multiple and conflicting epistemologies, identification and contextualisation of problems involving several disciplines in their solution etc. A practical example found in the case of newly developed BSc and MSc programs in Techno-Anthropology is provided.The paper includes some examples...

  5. Adding Social Elements to Game-Based Learning

    OpenAIRE

    Chien-Hung Lai; Yu-Chang Lin; Bin-Shyan Jong; Yen-Teh Hsia

    2014-01-01

    Game-based learning is to present the instruction by games in learning, with the main purpose of triggering learners’ motives instead of instructing the courses. Thus, increasing learning motive by game-based learning becomes a common instructional strategy to enhance learning achievement. However, it is not easy to design interesting games combined with courses. In 2011, Echeverria proposed a design to combine characteristics of games with elements of courses by matching the virtual scenario...

  6. Saul: Towards Declarative Learning Based Programming.

    Science.gov (United States)

    Kordjamshidi, Parisa; Roth, Dan; Wu, Hao

    2015-07-01

    We present Saul , a new probabilistic programming language designed to address some of the shortcomings of programming languages that aim at advancing and simplifying the development of AI systems. Such languages need to interact with messy, naturally occurring data, to allow a programmer to specify what needs to be done at an appropriate level of abstraction rather than at the data level, to be developed on a solid theory that supports moving to and reasoning at this level of abstraction and, finally, to support flexible integration of these learning and inference models within an application program. Saul is an object-functional programming language written in Scala that facilitates these by (1) allowing a programmer to learn, name and manipulate named abstractions over relational data; (2) supporting seamless incorporation of trainable (probabilistic or discriminative) components into the program, and (3) providing a level of inference over trainable models to support composition and make decisions that respect domain and application constraints. Saul is developed over a declaratively defined relational data model, can use piecewise learned factor graphs with declaratively specified learning and inference objectives, and it supports inference over probabilistic models augmented with declarative knowledge-based constraints. We describe the key constructs of Saul and exemplify its use in developing applications that require relational feature engineering and structured output prediction.

  7. Design of learner-centred constructivism based learning process

    OpenAIRE

    Schreurs, Jeanne; Al-Huneidi, Ahmad

    2012-01-01

    A Learner-centered learning is constructivism based and Competence directed. We define general competencies, domain competencies and specific course competencies. Constructivism based learning activities are based on constructivism theory. For each course module the intended learning level will be defined. A model is built for the design of a learner centered constructivism based and competency directed learning process. The application of it in two courses are presented. Constructivism ba...

  8. Research on detecting heterogeneous fibre from cotton based on linear CCD camera

    Science.gov (United States)

    Zhang, Xian-bin; Cao, Bing; Zhang, Xin-peng; Shi, Wei

    2009-07-01

    The heterogeneous fibre in cotton make a great impact on production of cotton textile, it will have a bad effect on the quality of product, thereby affect economic benefits and market competitive ability of corporation. So the detecting and eliminating of heterogeneous fibre is particular important to improve machining technics of cotton, advance the quality of cotton textile and reduce production cost. There are favorable market value and future development for this technology. An optical detecting system obtains the widespread application. In this system, we use a linear CCD camera to scan the running cotton, then the video signals are put into computer and processed according to the difference of grayscale, if there is heterogeneous fibre in cotton, the computer will send an order to drive the gas nozzle to eliminate the heterogeneous fibre. In the paper, we adopt monochrome LED array as the new detecting light source, it's lamp flicker, stability of luminous intensity, lumens depreciation and useful life are all superior to fluorescence light. We analyse the reflection spectrum of cotton and various heterogeneous fibre first, then select appropriate frequency of the light source, we finally adopt violet LED array as the new detecting light source. The whole hardware structure and software design are introduced in this paper.

  9. A system for tumor heterogeneity evaluation and diagnosis based on tumor markers measured routinely in the laboratory.

    Science.gov (United States)

    Hui, Liu; Rixv, Liu; Xiuying, Zhou

    2015-12-01

    To develop an efficient and reliable approach to estimate tumor heterogeneity and improve tumor diagnosis using multiple tumor markers measured routinely in the clinical laboratory. A total of 161 patients with different cancers were recruited as the cancer group, and 91 patients with non-oncological conditions were required as the non-oncological disease group. The control group comprised 90 randomly selected healthy subjects. AFP, CEA, CYFRA, CA125, CA153, CA199, CA724, and NSE levels were measured in all these subjects with a chemiluminescent microparticle immunoassay. The tumor marker with the maximum S/CO value (sample test value:cutoff value for discriminating individuals with and without tumors) was considered as a specific tumor marker (STM) for an individual. Tumor heterogeneity index (THI)=N/P (N: number of STMs; P: percentage of individuals with STMs in a certain tumor population) was used to quantify tumor heterogeneity: high THI indicated high tumor heterogeneity. The tumor marker index (TMI), TMI = STM×(number of positive tumor markers+1), was used for diagnosis. The THIs of lung, gastric, and liver cancers were 8.33, 9.63, and 5.2, respectively, while the ROC-areas under the curve for TMI were 0.862, 0.809, and 0.966. In this study, we developed a novel index for tumor heterogeneity based on the expression of various routinely evaluated serum tumor markers. Development of an evaluation system for tumor heterogeneity on the basis of this index could provide an effective diagnostic tool for some cancers. Copyright © 2015 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

  10. Word Sense Disambiguation Based on Large Scale Polish CLARIN Heterogeneous Lexical Resources

    Directory of Open Access Journals (Sweden)

    Paweł Kędzia

    2015-12-01

    Full Text Available Word Sense Disambiguation Based on Large Scale Polish CLARIN Heterogeneous Lexical Resources Lexical resources can be applied in many different Natural Language Engineering tasks, but the most fundamental task is the recognition of word senses used in text contexts. The problem is difficult, not yet fully solved and different lexical resources provided varied support for it. Polish CLARIN lexical semantic resources are based on the plWordNet — a very large wordnet for Polish — as a central structure which is a basis for linking together several resources of different types. In this paper, several Word Sense Disambiguation (henceforth WSD methods developed for Polish that utilise plWordNet are discussed. Textual sense descriptions in the traditional lexicon can be compared with text contexts using Lesk’s algorithm in order to find best matching senses. In the case of a wordnet, lexico-semantic relations provide the main description of word senses. Thus, first, we adapted and applied to Polish a WSD method based on the Page Rank. According to it, text words are mapped on their senses in the plWordNet graph and Page Rank algorithm is run to find senses with the highest scores. The method presents results lower but comparable to those reported for English. The error analysis showed that the main problems are: fine grained sense distinctions in plWordNet and limited number of connections between words of different parts of speech. In the second approach plWordNet expanded with the mapping onto the SUMO ontology concepts was used. Two scenarios for WSD were investigated: two step disambiguation and disambiguation based on combined networks of plWordNet and SUMO. In the former scenario, words are first assigned SUMO concepts and next plWordNet senses are disambiguated. In latter, plWordNet and SUMO are combined in one large network used next for the disambiguation of senses. The additional knowledge sources used in WSD improved the performance

  11. A Middleware Based Approach to Dynamically Deploy Location Based Services onto Heterogeneous Mobile Devices Using Bluetooth in Indoor Environment

    Science.gov (United States)

    Sadhukhan, Pampa; Sen, Rijurekha; Das, Pradip K.

    Several methods for providing location based service (LBS) to mobile devices in indoor environment using wireless technologies like WLAN, RFID and Bluetooth have been proposed, implemented and evaluated. However, most of them do not focus on heterogeneity of mobile platforms, memory constraint of mobile devices, the adaptability of client or device to the new services it discovers whenever it reaches a new location. In this paper, we have proposed a Middleware based approach of LBS provision in the indoor environment, where a Bluetooth enabled Base Station (BS) detects Bluetooth enabled mobile devices and pushes a proper client application only to those devices that belong to some registered subscriber of LBS. This dynamic deployment enables the mobile clients to access any new service without having preinstalled interface to that service beforehand and thus the client's memory consumption is reduced. Our proposed work also addresses the other issues like authenticating the clients before providing them LBSs and introducing paid services. We have evaluated its performance in term of file transfer time with respect to file size and throughput with respect to distance. Experimental results on service consumption time by the mobile client for different services are also presented.

  12. Ecoregion-Based Conservation Planning in the Mediterranean: Dealing with Large-Scale Heterogeneity

    Science.gov (United States)

    Giakoumi, Sylvaine; Sini, Maria; Gerovasileiou, Vasilis; Mazor, Tessa; Beher, Jutta; Possingham, Hugh P.; Abdulla, Ameer; Çinar, Melih Ertan; Dendrinos, Panagiotis; Gucu, Ali Cemal; Karamanlidis, Alexandros A.; Rodic, Petra; Panayotidis, Panayotis; Taskin, Ergun; Jaklin, Andrej; Voultsiadou, Eleni; Webster, Chloë; Zenetos, Argyro; Katsanevakis, Stelios

    2013-01-01

    Spatial priorities for the conservation of three key Mediterranean habitats, i.e. seagrass Posidonia oceanica meadows, coralligenous formations, and marine caves, were determined through a systematic planning approach. Available information on the distribution of these habitats across the entire Mediterranean Sea was compiled to produce basin-scale distribution maps. Conservation targets for each habitat type were set according to European Union guidelines. Surrogates were used to estimate the spatial variation of opportunity cost for commercial, non-commercial fishing, and aquaculture. Marxan conservation planning software was used to evaluate the comparative utility of two planning scenarios: (a) a whole-basin scenario, referring to selection of priority areas across the whole Mediterranean Sea, and (b) an ecoregional scenario, in which priority areas were selected within eight predefined ecoregions. Although both scenarios required approximately the same total area to be protected in order to achieve conservation targets, the opportunity cost differed between them. The whole-basin scenario yielded a lower opportunity cost, but the Alboran Sea ecoregion was not represented and priority areas were predominantly located in the Ionian, Aegean, and Adriatic Seas. In comparison, the ecoregional scenario resulted in a higher representation of ecoregions and a more even distribution of priority areas, albeit with a higher opportunity cost. We suggest that planning at the ecoregional level ensures better representativeness of the selected conservation features and adequate protection of species, functional, and genetic diversity across the basin. While there are several initiatives that identify priority areas in the Mediterranean Sea, our approach is novel as it combines three issues: (a) it is based on the distribution of habitats and not species, which was rarely the case in previous efforts, (b) it considers spatial variability of cost throughout this

  13. Biodiesel production from non-edible Silybum marianum oil using heterogeneous solid base catalyst under ultrasonication.

    Science.gov (United States)

    Takase, Mohammed; Chen, Yao; Liu, Hongyang; Zhao, Ting; Yang, Liuqing; Wu, Xiangyang

    2014-09-01

    The aim of this study is to investigate modified TiO2 doped with C4H4O6HK as heterogeneous solid base catalyst for transesterification of non-edible, Silybum marianum oil to biodiesel using methanol under ultrasonication. Upon screening the catalytic performance of modified TiO2 doped with different K-compounds, 0.7 C4H4O6HK doped on TiO2 was selected. The preparation of the catalyst was done using incipient wetness impregnation method. Having doped modified TiO2 with C4H4O6HK, followed by impregnation, drying and calcination at 600 °C for 6 h, the catalyst was characterized by XRD, FTIR, SEM, BET, TGA, UV and the Hammett indicators. The yield of the biodiesel was proportional to the catalyst basicity. The catalyst had granular and porous structures with high basicity and superior performance. Combined conditions of 16:1 molar ratio of methanol to oil, 5 wt.% catalyst amount, 60 °C reaction temperature and 30 min reaction time was enough for maximum yield of 90.1%. The catalyst maintained sustained activity after five cycles of use. The oxidative stability which was the main problem of the biodiesel was improved from 2.0 h to 3.2h after 30 days using ascorbic acid as antioxidant. The other properties including the flash point, cetane number and the cold flow ones were however, comparable to international standards. The study indicated that Ti-0.7-600-6 is an efficient, economical and environmentally, friendly catalyst under ultrasonication for producing biodiesel from S. marianum oil with a substantial yield. Copyright © 2014 Elsevier B.V. All rights reserved.

  14. Physically based probability criterion for exceeding radionuclide concentration limits in heterogeneous bedrock

    International Nuclear Information System (INIS)

    Worman, A.; Xu, S.; Dverstorp, B.

    2004-01-01

    A significant problem in a risk analysis of the repository for high-level nuclear waste is to estimate the barrier effect of the geosphere. The significant spatial variability of the rock properties implies that migrating RNs encounter a distribution of bedrock properties and mass-transfer mechanisms in different proportions along the transport paths. For practical reasons, we will never be able to know exactly this distribution of properties by performing a reasonable amount of measurements in a site investigation. On the contrary, recent experimental studies reveal that crystalline bedrock can possess a marked heterogeneity of various physical and geochemical properties that potentially may have a certain impact on the transport of RNs in fractured bedrock. Also current field investigation techniques provide only fragmentary information of the properties of the geosphere. This is a basic motivation for treating flows of water and solute elements in groundwaters by means of stochastic continuum models. The stochastic analysis is based on the idea that we know only certain point values of the property fields and use this information to estimate intermediate values. The probabilistic properties of the stochastic analysis are suitable input variables for risk analyses of the relevant sequence of extreme events for which empirical observations are rare or non-existing. The purpose of this paper is to outline the implications of the stochastic approach for estimating probabilities that certain concentration limits are exceeded at discharge points from. the bedrock in case of a leakage from the waste repository. The analysis is restricted to the water flow and solute transport in the bedrock alone without consideration of the full sequence of events in a full risk analysis and the Bayesian statistics involved in such conditioned (and cross-correlated) event series. The focus is on the implication for the risk analysis of the auto-covariance structure in bedrock

  15. Metal- and Carbon-Based Materials as Heterogeneous Electrocatalysts for CO₂ Reduction.

    Science.gov (United States)

    Khan, Azam; Ullah, Haseeb; Nasir, Jamal Abdul; Shuda, Suzanne; Chen, Wei; Khan, M Abdullah

    2018-05-01

    Climate change caused by continuous rising level of CO2 and the depletion of fossil fuels reserves has made it highly desirable to electrochemically convert CO2 into fuels and commodity chemicals. Implementing this approach will close the carbon cycle by recycling CO2 providing a sustainable way to store energy in the chemical bonds of portable molecular fuels. In order to make the process commercially viable, the challenge of slow kinetics of CO2 electroreduction and low energy efficiency of the process need to be addressed. To this end, this review summarizes the progress made in the past few years in the development of heterogeneous electrocatalysts with a focus on nanostructured material for CO2 reduction to CO, HCOOH/HCOO-, CH2O, CH4, H2C2O4/HC2O-4, C2H4, CH3OH, CH3CH2OH, etc. The electrocatalysts presented here are classified into metals, metal alloys, metal oxides, metal chalcogenides and carbon based materials on the basis of their elemental composition, whose performance is discussed in light of catalyst activity, product selectivity, Faradaic efficiency (FE), catalytic durability and in selected cases mechanism of CO2 electroreduction. The effect of particle size, morphology and solution-electrolyte type and composition on the catalyst property/activity is also discussed and finally some strategies are proposed for the development of CO2 electroreduction catalysts. The aim of this article is to review the recent advances in the field of CO2 electroreduction in order to further facilitate research and development in this area.

  16. Beyond Problem-Based Learning: Using Dynamic PBL in Chemistry

    Science.gov (United States)

    Overton, Tina L.; Randles, Christopher A.

    2015-01-01

    This paper describes the development and implementation of a novel pedagogy, dynamic problem-based learning. The pedagogy utilises real-world problems that evolve throughout the problem-based learning activity and provide students with choice and different data sets. This new dynamic problem-based learning approach was utilised to teach…

  17. Creation of Exercises for Team-Based Learning in Business

    Science.gov (United States)

    Timmerman, John E.; Morris, R. Franklin, Jr.

    2015-01-01

    Team-based learning (TBL) is an approach that builds on both the case method and problem-based learning and has been widely adopted in the sciences and healthcare disciplines. In recent years business disciplines have also discovered the value of this approach. One of the key characteristics of the team-based learning approach consists of…

  18. Students Learn How Nonprofits Utilize Volunteers through Inquiry-Based Learning

    Science.gov (United States)

    Bolton, Elizabeth B.; Brennan, M. A.; Terry, Bryan D.

    2009-01-01

    This article highlights how undergraduate students implemented inquiry-based learning strategies to learn how nonprofit organizations utilize volunteers. In inquiry-based learning, students begin with a problem or question with some degree of focus or structure provided by the professor. The student inquiry showcased in this article was based on a…

  19. Toward an Instructionally Oriented Theory of Example-Based Learning

    Science.gov (United States)

    Renkl, Alexander

    2014-01-01

    Learning from examples is a very effective means of initial cognitive skill acquisition. There is an enormous body of research on the specifics of this learning method. This article presents an instructionally oriented theory of example-based learning that integrates theoretical assumptions and findings from three research areas: learning from…

  20. Development of Web-Based Learning Application for Generation Z

    Science.gov (United States)

    Hariadi, Bambang; Dewiyani Sunarto, M. J.; Sudarmaningtyas, Pantjawati

    2016-01-01

    This study aimed to develop a web-based learning application as a form of learning revolution. The form of learning revolution includes the provision of unlimited teaching materials, real time class organization, and is not limited by time or place. The implementation of this application is in the form of hybrid learning by using Google Apps for…

  1. Lifelong Learning for All in Asian Communities: ICT Based Initiatives

    Science.gov (United States)

    Misra, Pradeep Kumar

    2011-01-01

    The necessity to adjust to the prerequisites of the knowledge based society and economy brought about the need for lifelong learning for all in Asian communities. The concept of lifelong learning stresses that learning and education are related to life as a whole - not just to work - and that learning throughout life is a continuum that should run…

  2. A Situated Cultural Festival Learning System Based on Motion Sensing

    Science.gov (United States)

    Chang, Yi-Hsing; Lin, Yu-Kai; Fang, Rong-Jyue; Lu, You-Te

    2017-01-01

    A situated Chinese cultural festival learning system based on motion sensing is developed in this study. The primary design principle is to create a highly interactive learning environment, allowing learners to interact with Kinect through natural gestures in the designed learning situation to achieve efficient learning. The system has the…

  3. Representation of Coordination Mechanisms in IMS Learning Design to Support Group-based Learning

    NARCIS (Netherlands)

    Miao, Yongwu; Burgos, Daniel; Griffiths, David; Koper, Rob

    2007-01-01

    Miao, Y., Burgos, D., Griffiths, D., & Koper, R. (2008). Representation of Coordination Mechanisms in IMS Learning Design to Support Group-based Learning. In L. Lockyer, S. Bennet, S. Agostinho & B. Harper (Eds.), Handbook of Research on Learning Design and Learning Objects: Issues, Applications and

  4. Community Based Learning and Civic Engagement: Informal Learning among Adult Volunteers in Community Organizations

    Science.gov (United States)

    Mundel, Karsten; Schugurensky, Daniel

    2008-01-01

    Many iterations of community based learning employ models, such as consciousness raising groups, cultural circles, and participatory action research. In all of them, learning is a deliberate part of an explicit educational activity. This article explores another realm of community learning: the informal learning that results from volunteering in…

  5. SVM and PCA Based Learning Feature Classification Approaches for E-Learning System

    Science.gov (United States)

    Khamparia, Aditya; Pandey, Babita

    2018-01-01

    E-learning and online education has made great improvements in the recent past. It has shifted the teaching paradigm from conventional classroom learning to dynamic web based learning. Due to this, a dynamic learning material has been delivered to learners, instead ofstatic content, according to their skills, needs and preferences. In this…

  6. What students learn in problem-based learning: a process analysis

    NARCIS (Netherlands)

    E.H.J. Yew (Elaine); H.G. Schmidt (Henk)

    2012-01-01

    textabstractThis study aimed to provide an account of how learning takes place in problem-based learning (PBL), and to identify the relationships between the learning-oriented activities of students with their learning outcomes. First, the verbal interactions and computer resources studied by nine

  7. Development of 3-D FBR heterogeneous core calculation method based on characteristics method

    International Nuclear Information System (INIS)

    Takeda, Toshikazu; Maruyama, Manabu; Hamada, Yuzuru; Nishi, Hiroshi; Ishibashi, Junichi; Kitano, Akihiro

    2002-01-01

    A new 3-D transport calculation method taking into account the heterogeneity of fuel assemblies has been developed by combining the characteristics method and the nodal transport method. In the axial direction the nodal transport method is applied, and the characteristics method is applied to take into account the radial heterogeneity of fuel assemblies. The numerical calculations have been performed to verify 2-D radial calculations of FBR assemblies and partial core calculations. Results are compared with the reference Monte-Carlo calculations. A good agreement has been achieved. It is shown that the present method has an advantage in calculating reaction rates in a small region

  8. Project based learning for reactor engineering education

    International Nuclear Information System (INIS)

    Narabayashi, Tadashi; Tsuji, Masashi; Shimazu, Yoichiro

    2009-01-01

    Trial in education of nuclear engineering in Hokkaido University has proved to be quite attractive for students. It is an education system called Project Based Learning (PBL), which is not based on education by lecture only but based mostly on practice of students in the classroom. The system was adopted four years ago. In the actual class, we separated the student into several groups of the size about 6 students. In the beginning of each class room time, a brief explanations of the related theory or technical bases. Then the students discuss in their own group how to precede their design calculations and do the required calculation and evaluation. The target reactor type of each group was selected by the group members for themselves at the beginning of the semester as the first step of the project. The reactor types range from a small in house type to that for a nuclear ship. At the end of the semester, each group presents the final design. The presentation experience gives students a kind of fresh sensation. Nowadays the evaluation results of the subject by the students rank in the highest in the faculty of engineering. Based on the considerations above, we designed the framework of our PBL for reactor engineering. In this paper, we will present some lessons learned in this PBL education system from the educational points of view. The PBL education program is supported by IAE/METI in Japan for Nuclear Engineering Education. (author)

  9. Dissociable contributions of the orbitofrontal and infralimbic cortex to pavlovian autoshaping and discrimination reversal learning: further evidence for the functional heterogeneity of the rodent frontal cortex.

    Science.gov (United States)

    Chudasama, Y; Robbins, Trevor W

    2003-09-24

    To examine possible heterogeneity of function within the ventral regions of the rodent frontal cortex, the present study compared the effects of excitotoxic lesions of the orbitofrontal cortex (OFC) and the infralimbic cortex (ILC) on pavlovian autoshaping and discrimination reversal learning. During the pavlovian autoshaping task, in which rats learn to approach a stimulus predictive of reward [conditional stimulus (CS+)], only the OFC group failed to acquire discriminated approach but was unimpaired when preoperatively trained. In the visual discrimination learning and reversal task, rats were initially required to discriminate a stimulus positively associated with reward. There was no effect of either OFC or ILC lesions on discrimination learning. When the stimulus-reward contingencies were reversed, both groups of animals committed more errors, but only the OFC-lesioned animals were unable to suppress the previously rewarded stimulus-reward association, committing more "stimulus perseverative" errors. In contrast, the ILC group showed a pattern of errors that was more attributable to "learning" than perseveration. These findings suggest two types of dissociation between the effects of OFC and ILC lesions: (1) OFC lesions impaired the learning processes implicated in pavlovian autoshaping but not instrumental simultaneous discrimination learning, whereas ILC lesions were unimpaired at autoshaping and their reversal learning deficit did not reflect perseveration, and (2) OFC lesions induced perseverative responding in reversal learning but did not disinhibit responses to pavlovian CS-. In contrast, the ILC lesion had no effect on response inhibitory control in either of these settings. The findings are discussed in the context of dissociable executive functions in ventral sectors of the rat prefrontal cortex.

  10. Power, Democracy and Problem-Based Learning

    DEFF Research Database (Denmark)

    Du, Xiangyun; Stentoft, Diana; Dahms, Mona-Lisa

    2007-01-01

      Problem Based Learning (PBL) as an educational approach has been increasingly applied in educational settings around the world. Given that PBL - as well as any other educational approach - is rooted in a given cultural context and thus carries the ‘fingerprint' of the specific context......, an interesting question is: To which extent is PBL a universally applicable approach to teaching and learning, i.e. an approach which can be implemented successfully to all times and in all societies, independent of differences in social, cultural, political and economic contexts? With this question...... participants are teachers involved in technical education, who have an interest in initiating changes towards PBL in their institutions and/or in their educational practices. The participants are located in various parts of the world and thus bring diverse experiences to the course and the MPBL programme...

  11. The didactic situation in geometry learning based on analysis of learning obstacles and learning trajectory

    Science.gov (United States)

    Sulistyowati, Fitria; Budiyono, Slamet, Isnandar

    2017-12-01

    This study aims to design a didactic situation based on the analysis of learning obstacles and learning trajectory on prism volume. The type of this research is qualitative and quantitative research with steps: analyzing the learning obstacles and learning trajectory, preparing the didactic situation, applying the didactic situation in the classroom, mean difference test of problem solving ability with t-test statistic. The subjects of the study were 8th grade junior high school students in Magelang 2016/2017 selected randomly from eight existing classes. The result of this research is the design of didactic situations that can be implemented in prism volume learning. The effectiveness of didactic situations that have been designed is shown by the mean difference test that is the problem solving ability of the students after the application of the didactic situation better than before the application. The didactic situation that has been generated is expected to be a consideration for teachers to design lessons that match the character of learners, classrooms and teachers themselves, so that the potential thinking of learners can be optimized to avoid the accumulation of learning obstacles.

  12. Multiclass classification for skin cancer profiling based on the integration of heterogeneous gene expression series.

    Science.gov (United States)

    Gálvez, Juan Manuel; Castillo, Daniel; Herrera, Luis Javier; San Román, Belén; Valenzuela, Olga; Ortuño, Francisco Manuel; Rojas, Ignacio

    2018-01-01

    Most of the research studies developed applying microarray technology to the characterization of different pathological states of any disease may fail in reaching statistically significant results. This is largely due to the small repertoire of analysed samples, and to the limitation in the number of states or pathologies usually addressed. Moreover, the influence of potential deviations on the gene expression quantification is usually disregarded. In spite of the continuous changes in omic sciences, reflected for instance in the emergence of new Next-Generation Sequencing-related technologies, the existing availability of a vast amount of gene expression microarray datasets should be properly exploited. Therefore, this work proposes a novel methodological approach involving the integration of several heterogeneous skin cancer series, and a later multiclass classifier design. This approach is thus a way to provide the clinicians with an intelligent diagnosis support tool based on the use of a robust set of selected biomarkers, which simultaneously distinguishes among different cancer-related skin states. To achieve this, a multi-platform combination of microarray datasets from Affymetrix and Illumina manufacturers was carried out. This integration is expected to strengthen the statistical robustness of the study as well as the finding of highly-reliable skin cancer biomarkers. Specifically, the designed operation pipeline has allowed the identification of a small subset of 17 differentially expressed genes (DEGs) from which to distinguish among 7 involved skin states. These genes were obtained from the assessment of a number of potential batch effects on the gene expression data. The biological interpretation of these genes was inspected in the specific literature to understand their underlying information in relation to skin cancer. Finally, in order to assess their possible effectiveness in cancer diagnosis, a cross-validation Support Vector Machines (SVM)-based

  13. Formation of equiaxed crystal structures in directionally solidified Al-Si alloys using Nb-based heterogeneous nuclei

    Science.gov (United States)

    Bolzoni, Leandro; Xia, Mingxu; Babu, Nadendla Hari

    2016-01-01

    The design of chemical compositions containing potent nuclei for the enhancement of heterogeneous nucleation in aluminium, especially cast alloys such as Al-Si alloys, is a matter of importance in order to achieve homogeneous properties in castings with complex geometries. We identified that Al3Nb/NbB2 compounds are effective heterogeneous nuclei and are successfully produced in the form of Al-2Nb-xB (x = 0.5, 1 and 2) master alloys. Our study shows that the inoculation of Al-10Si braze alloy with these compounds effectively promotes the heterogeneous nucleation of primary α-Al crystals and reduces the undercooling needed for solidification to take place. Moreover, we present evidences that these Nb-based compounds prevent the growth of columnar crystals and permit to obtain, for the first time, fine and equiaxed crystals in directionally solidified Al-10Si braze alloy. As a consequence of the potent heterogeneous particles, the size of the α-Al crystals was found to be less dependent on the processing conditions, especially the thermal gradient. Finally, we also demonstrate that the enhanced nucleation leads to the refinement of secondary phases such as eutectic silicon and primary silicon particles. PMID:28008967

  14. Evaluation of Segmentation Bases for the Heterogeneous Elderly Consumer Population: the Functional Food Market

    NARCIS (Netherlands)

    Zanden, van der L.D.T.; Kleef, van E.; Wijk, de R.A.; Trijp, van J.C.M.

    2014-01-01

    It is beneficial for both the public health community and the food industry to meet nutritional needs of elderly consumers through product formats that they want. The heterogeneity of the elderly market poses a challenge, however, and calls for market segmentation. Although many researchers have

  15. Can Learning Motivation Predict Learning Achievement? A Case Study of a Mobile Game-Based English Learning Approach

    Science.gov (United States)

    Tsai, Chia-Hui; Cheng, Ching-Hsue; Yeh, Duen-Yian; Lin, Shih-Yun

    2017-01-01

    This study applied a quasi-experimental design to investigate the influence and predictive power of learner motivation for achievement, employing a mobile game-based English learning approach. A system called the Happy English Learning System, integrating learning material into a game-based context, was constructed and installed on mobile devices…

  16. A New Design Approach to Game-Based learning

    DEFF Research Database (Denmark)

    Larsen, Lasse Juel

    2012-01-01

    to ground the student’s reason to learn. This paper proposes a different approach: using visualisation in immersive 3D worlds as both documentation of learning progress and as a reward system which motivates further learning. The overall design idea is to build a game based learning system from three......This paper puts forward a new design perspective for gamebased learning. The general idea is to abandon the long sought-after dream of designing a closed learning system, where students in both primary and secondary school could learn – without the interference of teachers – whatever subject......-based learning system, but will also confront aspects of modern learning theory, especially the notion of reference between the content of an assignment and the reality with which it should or could be connected (situated learning). The second idea promotes a way of tackling the common experience of the average...

  17. SPAM CLASSIFICATION BASED ON SUPERVISED LEARNING USING MACHINE LEARNING TECHNIQUES

    Directory of Open Access Journals (Sweden)

    T. Hamsapriya

    2011-12-01

    Full Text Available E-mail is one of the most popular and frequently used ways of communication due to its worldwide accessibility, relatively fast message transfer, and low sending cost. The flaws in the e-mail protocols and the increasing amount of electronic business and financial transactions directly contribute to the increase in e-mail-based threats. Email spam is one of the major problems of the today’s Internet, bringing financial damage to companies and annoying individual users. Spam emails are invading users without their consent and filling their mail boxes. They consume more network capacity as well as time in checking and deleting spam mails. The vast majority of Internet users are outspoken in their disdain for spam, although enough of them respond to commercial offers that spam remains a viable source of income to spammers. While most of the users want to do right think to avoid and get rid of spam, they need clear and simple guidelines on how to behave. In spite of all the measures taken to eliminate spam, they are not yet eradicated. Also when the counter measures are over sensitive, even legitimate emails will be eliminated. Among the approaches developed to stop spam, filtering is the one of the most important technique. Many researches in spam filtering have been centered on the more sophisticated classifier-related issues. In recent days, Machine learning for spam classification is an important research issue. The effectiveness of the proposed work is explores and identifies the use of different learning algorithms for classifying spam messages from e-mail. A comparative analysis among the algorithms has also been presented.

  18. Learning through Debate during Problem-Based Learning: An Active Learning Strategy

    Science.gov (United States)

    Mumtaz, Sadaf; Latif, Rabia

    2017-01-01

    We explored medical student's views and perceptions of a series of debates conducted during problem-based learning (PBL) practiced as a part of the Spiral curriculum at the Imam Abdulrahman Bin Faisal University, Saudi Arabia. A series of debates were employed during PBL sessions for second-year female medical students, over the period 2014-2016.…

  19. Learning from the problems of problem-based learning

    Directory of Open Access Journals (Sweden)

    Epstein Richard

    2004-01-01

    Full Text Available Abstract Background The last decade has witnessed a rapid expansion of biomedical knowledge. Despite this, fashions in medical education over the same period have shifted away from factual (didactic teaching and towards contextual, or problem-based, learning (PBL. This paradigm shift has been justified by studies showing that PBL improves reasoning and communication while being associated with few if any detectable knowledge deficits. Discussion Analysis of the literature indicates that the recent rapid rise of PBL has closely paralleled the timing of the information explosion. The growing dominance of PBL could thus worsen the problems of information management in medical education via several mechanisms: first, by creating the impression that a defined spectrum of core factual knowledge suffices for clinical competence despite ongoing knowledge expansion (quality cost; second, by dissuading teachers from refining the educational utility of didactic modalities (improvement cost; and third, by reducing faculty time for developing reusable resources to impart factual knowledge more efficiently (opportunity cost. Summary These costs of PBL imply a need for strengthening the knowledge base of 21st-century medical graduates. New initiatives towards this end could include the development of more integrated cognitive techniques for facilitating the comprehension of complex data; the design of differentiated medical curricula for producing graduates with defined high-priority skill sets; and the encouragement of more cost-effective faculty teaching activities focused on the prototyping and testing of innovative commercializable educational tools.

  20. A New Design Approach to game or play based learning

    DEFF Research Database (Denmark)

    Larsen, Lasse Juel

    to ground the students sense of meaning. This paper proposes another approach: using visualization in immersive 3D-worlds as documentation of learning progress while at the same time constituting a reward system which motivate further learning. The overall design idea is to build a game based learning......Abstract: The present paper proposes a new design perspective for game based learning. The general idea is to abandon the long and sought after dream of designing a closed learning system, where students from elementary school to high school without teachers’ interference could learn whatever...... game based learning system, but also confront aspects of modern learning theory especially the notion of reference between content of an assignment and the reality with which it should or could be connected (situated learning). The second idea promotes a way to tackle the common experience...

  1. Structuring a Multiproduct Sales Quota-Bonus Plan for a Heterogeneous Sales Force: A Practical Model-Based Approach

    OpenAIRE

    Murali K. Mantrala; Prabhakant Sinha; Andris A. Zoltners

    1994-01-01

    This paper presents an agency theoretic model-based approach that assists sales managers in determining the profit-maximizing structure of a common multiproduct sales quota-bonus plan for a geographically specialized heterogeneous sales force operating in a repetitive buying environment. This approach involves estimating each salesperson's utility function for income and effort and using these models to predict individual sales achievements and the associated aggregate profit for the firm und...

  2. Silica-based PLC with heterogeneously-integrated PDs for one-chip DP-QPSK receiver.

    Science.gov (United States)

    Kurata, Yu; Nasu, Yusuke; Tamura, Munehisa; Kasahara, Ryoichi; Aozasa, Shinichi; Mizuno, Takayuki; Yokoyama, Haruki; Tsunashima, Satoshi; Muramoto, Yoshifumi

    2012-12-10

    To realize a DP-QPSK receiver PLC, we heterogeneously integrated eight high-speed PDs on a silica-based PLC platform with a PBS, 90-degree optical hybrids and a VOA. The use of a 2.5%-Δ waveguide reduced the receiver PLC size to 11 mm x 11 mm. We successfully demonstrated 32 Gbaud DP-QPSK signal demodulation with the receiver PLC.

  3. Digital case-based learning system in school.

    Science.gov (United States)

    Gu, Peipei; Guo, Jiayang

    2017-01-01

    With the continuing growth of multi-media learning resources, it is important to offer methods helping learners to explore and acquire relevant learning information effectively. As services that organize multi-media learning materials together to support programming learning, the digital case-based learning system is needed. In order to create a case-oriented e-learning system, this paper concentrates on the digital case study of multi-media resources and learning processes with an integrated framework. An integration of multi-media resources, testing and learning strategies recommendation as the learning unit is proposed in the digital case-based learning framework. The learning mechanism of learning guidance, multi-media materials learning and testing feedback is supported in our project. An improved personalized genetic algorithm which incorporates preference information and usage degree into the crossover and mutation process is proposed to assemble the personalized test sheet for each learner. A learning strategies recommendation solution is proposed to recommend learning strategies for learners to help them to learn. The experiments are conducted to prove that the proposed approaches are capable of constructing personalized sheets and the effectiveness of the framework.

  4. Digital case-based learning system in school.

    Directory of Open Access Journals (Sweden)

    Peipei Gu

    Full Text Available With the continuing growth of multi-media learning resources, it is important to offer methods helping learners to explore and acquire relevant learning information effectively. As services that organize multi-media learning materials together to support programming learning, the digital case-based learning system is needed. In order to create a case-oriented e-learning system, this paper concentrates on the digital case study of multi-media resources and learning processes with an integrated framework. An integration of multi-media resources, testing and learning strategies recommendation as the learning unit is proposed in the digital case-based learning framework. The learning mechanism of learning guidance, multi-media materials learning and testing feedback is supported in our project. An improved personalized genetic algorithm which incorporates preference information and usage degree into the crossover and mutation process is proposed to assemble the personalized test sheet for each learner. A learning strategies recommendation solution is proposed to recommend learning strategies for learners to help them to learn. The experiments are conducted to prove that the proposed approaches are capable of constructing personalized sheets and the effectiveness of the framework.

  5. Applying Brain-Based Learning Principles to Athletic Training Education

    Science.gov (United States)

    Craig, Debbie I.

    2007-01-01

    Objective: To present different concepts and techniques related to the application of brain-based learning principles to Athletic Training clinical education. Background: The body of knowledge concerning how our brains physically learn continues to grow. Brain-based learning principles, developed by numerous authors, offer advice on how to…

  6. Investigative Primary Science: A Problem-Based Learning Approach

    Science.gov (United States)

    Etherington, Matthew B.

    2011-01-01

    This study reports on the success of using a problem-based learning approach (PBL) as a pedagogical mode of learning open inquiry science within a traditional four-year undergraduate elementary teacher education program. In 2010, a problem-based learning approach to teaching primary science replaced the traditional content driven syllabus. During…

  7. Project-Based Learning Not Just for STEM Anymore

    Science.gov (United States)

    Duke, Nell K.; Halvorsen, Anne-Lise; Strachan, Stephanie L.

    2016-01-01

    The popularity of project-based learning has been driven in part by a growing number of STEM schools and programs. But STEM subjects are not the only fertile ground for project-based learning (PBL). Social studies and literacy content, too, can be adapted into PBL units to benefit teaching and learning, the authors argue. They review key studies…

  8. Implementing Project Based Learning Approach to Graphic Design Course

    Science.gov (United States)

    Riyanti, Menul Teguh; Erwin, Tuti Nuriah; Suriani, S. H.

    2017-01-01

    The purpose of this study was to develop a learning model based Commercial Graphic Design Drafting project-based learning approach, was chosen as a strategy in the learning product development research. University students as the target audience of this model are the students of the fifth semester Visual Communications Design Studies Program…

  9. An XML-based Schema-less Approach to Managing Diagnostic Data in Heterogeneous Formats

    Energy Technology Data Exchange (ETDEWEB)

    Naito, O. [Japan Atomic Energy Agency, Ibaraki (Japan)

    2009-07-01

    Managing diagnostic data in heterogeneous formats is always a nuisance, especially when a new diagnostic technique requires a new data structure that does not fit in the existing data format. Ideally, it is best to have an all-purpose schema that can specify any data structures. But devising such a schema is a difficult task and the resultant data management system tends to be large and complicated. As a complementary approach, we can think of a system that has no specific schema but requires each of the data to describe itself without assuming any prior information. In this paper, a very primitive implementation of such a system based on extensible Markup Language (XML) is examined. The actual implementation is no more than an addition of a tiny XML meta-data file that describes the detailed format of the associated diagnostic data file. There are many ways to write and read such meta-data files. For example, if the data are in a standard format that is foreign to the existing system, just specify the name of the format and what interface to use for reading the data. If the data are in a non-standard arbitrary format, write what is written and how into the meta-data file at every occurrence of data output. And as a last resort, if the format of the data is too complicated, a code to read the data can be stored in the meta-data file. Of course, this schema-less approach has some drawbacks, two of which are the doubling of the number of files to be managed and the low performance of data handling, though the former can be a merit, when it is necessary to update the meta-data leaving the body data intact. The important point is that the necessary information to read the data is decoupled from data itself. The merits and demerits of this approach are discussed. This document is composed of an abstract followed by the presentation slides. (author)

  10. Problem-Based Learning: Student Engagement, Learning and Contextualized Problem-Solving. Occasional Paper

    Science.gov (United States)

    Mossuto, Mark

    2009-01-01

    The adoption of problem-based learning as a teaching method in the advertising and public relations programs offered by the Business TAFE (Technical and Further Education) School at RMIT University is explored in this paper. The effect of problem-based learning on student engagement, student learning and contextualised problem-solving was…

  11. Geologically based model of heterogeneous hydraulic conductivity in an alluvial setting

    Science.gov (United States)

    Fogg, Graham E.; Noyes, Charles D.; Carle, Steven F.

    Information on sediment texture and spatial continuity are inherent to sedimentary depositional facies descriptions, which are therefore potentially good predictors of spatially varying hydraulic conductivity (K). Analysis of complex alluvial heterogeneity in Livermore Valley, California, USA, using relatively abundant core descriptions and field pumping-test data, demonstrates a depositional-facies approach to characterization of subsurface heterogeneity. Conventional textural classifications of the core show a poor correlation with K; however, further refinement of the textural classifications into channel, levee, debris-flow, and flood-plain depositional facies reveals a systematic framework for spatial modeling of K. This geologic framework shows that most of the system is composed of very low-K flood-plain materials, and that the K measurements predominantly represent the other, higher-K facies. Joint interpretation of both the K and geologic data shows that spatial distribution of K in this system could not be adequately modeled without geologic data and analysis. Furthermore, it appears that K should not be assumed to be log-normally distributed, except perhaps within each facies. Markov chain modeling of transition probability, representing spatial correlation within and among the facies, captures the relevant geologic features while highlighting a new approach for statistical characterization of hydrofacies spatial variability. The presence of fining-upward facies sequences, cross correlation between facies, as well as other geologic attributes captured by the Markov chains provoke questions about the suitability of conventional geostatistical approaches based on variograms or covariances for modeling geologic heterogeneity. Résumé Les informations sur la texture des sédiments et leur continuité spatiale font partie des descriptions de faciès sédimentaires de dépôt. Par conséquent, ces descriptions sont d'excellents prédicteurs potentiels des

  12. Supporting Case-Based Learning in Information Security with Web-Based Technology

    Science.gov (United States)

    He, Wu; Yuan, Xiaohong; Yang, Li

    2013-01-01

    Case-based learning has been widely used in many disciplines. As an effective pedagogical method, case-based learning is also being used to support teaching and learning in the domain of information security. In this paper, we demonstrate case-based learning in information security by sharing our experiences in using a case study to teach security…

  13. Rethinking Game Based Learning: applying pedagogical standards to educational games

    NARCIS (Netherlands)

    Schmitz, Birgit; Kelle, Sebastian

    2010-01-01

    Schmitz, B., & Kelle, S. (2010, 1-6 February). Rethinking Game Based Learning: applying pedagogical standards to educational games. Presentation at JTEL Winter School 2010 on Advanced Learning Technologies, Innsbruck, Austria.

  14. The development of metacognitive-based genetic learning ...

    African Journals Online (AJOL)

    The development of metacognitive-based genetic learning Instruments at senior ... The results of the research are learning instrument product and textbook whose ... that these instruments have satisfied the criteria: very valid and very ideal.

  15. Enhancing learning in tertiary institutions through multimedia based ...

    African Journals Online (AJOL)

    Enhancing learning in tertiary institutions through multimedia based ... convenient and cost-effective courseware reengineering methodology of our age. ... Also discussed are the reasons for converting classroom courses to e-learning format.

  16. Creating Problem-Based Leadership Learning across the Curriculum

    Science.gov (United States)

    Thompson, Sara E.; Couto, Richard A.

    2016-01-01

    This chapter explores problem-based learning (PBL) as effective pedagogy to enhance leadership learning. Through institutional examples, research, and personal experiences, the authors provide a rationale for faculty and staff to utilize PBL across the curriculum.

  17. Scrum-Based Learning Environment: Fostering Self-Regulated Learning

    Science.gov (United States)

    Linden, Tanya

    2018-01-01

    Academics teaching software development courses are experimenting with teaching methods aiming to improve students' learning experience and learning outcomes. Since Agile software development is gaining popularity in industry due to positive effects on managing projects, academics implement similar Agile approaches in student-centered learning…

  18. Particle-based modeling of heterogeneous chemical kinetics including mass transfer

    Science.gov (United States)

    Sengar, A.; Kuipers, J. A. M.; van Santen, Rutger A.; Padding, J. T.

    2017-08-01

    Connecting the macroscopic world of continuous fields to the microscopic world of discrete molecular events is important for understanding several phenomena occurring at physical boundaries of systems. An important example is heterogeneous catalysis, where reactions take place at active surfaces, but the effective reaction rates are determined by transport limitations in the bulk fluid and reaction limitations on the catalyst surface. In this work we study the macro-micro connection in a model heterogeneous catalytic reactor by means of stochastic rotation dynamics. The model is able to resolve the convective and diffusive interplay between participating species, while including adsorption, desorption, and reaction processes on the catalytic surface. Here we apply the simulation methodology to a simple straight microchannel with a catalytic strip. Dimensionless Damkohler numbers are used to comment on the spatial concentration profiles of reactants and products near the catalyst strip and in the bulk. We end the discussion with an outlook on more complicated geometries and increasingly complex reactions.

  19. Particle-based modeling of heterogeneous chemical kinetics including mass transfer.

    Science.gov (United States)

    Sengar, A; Kuipers, J A M; van Santen, Rutger A; Padding, J T

    2017-08-01

    Connecting the macroscopic world of continuous fields to the microscopic world of discrete molecular events is important for understanding several phenomena occurring at physical boundaries of systems. An important example is heterogeneous catalysis, where reactions take place at active surfaces, but the effective reaction rates are determined by transport limitations in the bulk fluid and reaction limitations on the catalyst surface. In this work we study the macro-micro connection in a model heterogeneous catalytic reactor by means of stochastic rotation dynamics. The model is able to resolve the convective and diffusive interplay between participating species, while including adsorption, desorption, and reaction processes on the catalytic surface. Here we apply the simulation methodology to a simple straight microchannel with a catalytic strip. Dimensionless Damkohler numbers are used to comment on the spatial concentration profiles of reactants and products near the catalyst strip and in the bulk. We end the discussion with an outlook on more complicated geometries and increasingly complex reactions.

  20. Multilevel QoS-policy-based routing management architecture appropriate for heterogeneous network environments

    Science.gov (United States)

    Chatzaki, Magda; Sartzetakis, Stelios

    1998-09-01

    As telecom providers introduce new and more sophisticated services the necessity of a global, unified view of the network infrastructure becomes demanding. Today, heterogenous backbone networks are interconnected in order to provide global connectivity. Due to technological impairments the cost of network operation, the maintenance complexity and the overuse of resources are extremely high under the goal of supporting the diverting customer requirements. We propose a scheme for ATM QoS support in such heterogenous, multi-domain, multi-technology network environment. The objective is to optimize users' and networks' profits by giving them the opportunity to satisfy their requirements. Our approach introduces a manager able to take routing decisions supporting quality of service guarantees for the customers, while making efficient use of network resources.

  1. Computationally Probing the Performance of Hybrid, Heterogeneous, and Homogeneous Iridium-Based Catalysts for Water Oxidation

    Energy Technology Data Exchange (ETDEWEB)

    García-Melchor, Max [SUNCAT Center for Interface Science and Catalysis, Department of Chemical Engineering, Stanford University, Stanford CA (United States); Vilella, Laia [Institute of Chemical Research of Catalonia (ICIQ), The Barcelona Institute of Science and Technology (BIST),Tarragona (Spain); Departament de Quimica, Universitat Autonoma de Barcelona, Barcelona (Spain); López, Núria [Institute of Chemical Research of Catalonia (ICIQ), The Barcelona Institute of Science and Technology (BIST), Tarragona (Spain); Vojvodic, Aleksandra [SUNCAT Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory, Menlo Park CA (United States)

    2016-04-29

    An attractive strategy to improve the performance of water oxidation catalysts would be to anchor a homogeneous molecular catalyst on a heterogeneous solid surface to create a hybrid catalyst. The idea of this combined system is to take advantage of the individual properties of each of the two catalyst components. We use Density Functional Theory to determine the stability and activity of a model hybrid water oxidation catalyst consisting of a dimeric Ir complex attached on the IrO2(110) surface through two oxygen atoms. We find that homogeneous catalysts can be bound to its matrix oxide without losing significant activity. Hence, designing hybrid systems that benefit from both the high tunability of activity of homogeneous catalysts and the stability of heterogeneous systems seems feasible.

  2. Educational program on HPC technologies based on the heterogeneous cluster HybriLIT (LIT JINR

    Directory of Open Access Journals (Sweden)

    Vladimir V. Korenkov

    2017-12-01

    Full Text Available The article highlights the issues of training personnel for work with high-performance computing systems (HPC, as well as of support of the software and information environment which is necessary for the efficient use of heterogeneous computing resources and the development of parallel and hybrid applications. The heterogeneous computing cluster HybriLIT, which is one of the components of the Multifunctional Information and Computing Complex of JINR, is used as the main platform for training and re-training specialists, as well as for training students, graduate students and young scientists. The HybriLIT cluster is a dynamic, actively developing structure, incorporating the most advanced HPC computing architectures (graphics accelerators, Intel Xeon Phi coprocessors, and also it has a developed software and information environment, which in turn, makes it possible to build educational programs on the up-to-date level, and enables the learners to master both modern computing platforms and modern IT technologies.

  3. Personalized learning Ecologies in Problem and Project Based Learning Environments

    DEFF Research Database (Denmark)

    Rongbutsri, Nikorn; Ryberg, Thomas; Zander, Pär-Ola

    2012-01-01

    is in contrast to an artificial learning setting often found in traditional education. As many other higher education institutions, Aalborg University aims at providing learning environments that support the underlying pedagogical approach employed, and which can lead to different online and offline learning.......g. coordination, communication, negotiation, document sharing, calendars, meetings and version control. Furthermore, the pedagogical fabric of LMSs/VLEs have recently been called into question and critiqued by proponents of Personal Learning Environments (PLEs)(Ryberg, Buus, & Georgsen, 2011) . In sum....... making it important to understand and conceptualise students’ use of technology. Ecology is the study of relationship between organisms in an environment which is the set of circumstances surrounding that organism. Learning ecologies are the study of the relationship of a learner or a group of learners...

  4. Unraveling the hidden heterogeneities of breast cancer based on functional miRNA cluster.

    Directory of Open Access Journals (Sweden)

    Li Li

    Full Text Available It has become increasingly clear that the current taxonomy of clinical phenotypes is mixed with molecular heterogeneity, which potentially affects the treatment effect for involved patients. Defining the hidden molecular-distinct diseases using modern large-scale genomic approaches is therefore useful for refining clinical practice and improving intervention strategies. Given that microRNA expression profiling has provided a powerful way to dissect hidden genetic heterogeneity for complex diseases, the aim of the study was to develop a bioinformatics approach that identifies microRNA features leading to the hidden subtyping of complex clinical phenotypes. The basic strategy of the proposed method was to identify optimal miRNA clusters by iteratively partitioning the sample and feature space using the two-ways super-paramagnetic clustering technique. We evaluated the obtained optimal miRNA cluster by determining the consistency of co-expression and the chromosome location among the within-cluster microRNAs, and concluded that the optimal miRNA cluster could lead to a natural partition of disease samples. We applied the proposed method to a publicly available microarray dataset of breast cancer patients that have notoriously heterogeneous phenotypes. We obtained a feature subset of 13 microRNAs that could classify the 71 breast cancer patients into five subtypes with significantly different five-year overall survival rates (45%, 82.4%, 70.6%, 100% and 60% respectively; p = 0.008. By building a multivariate Cox proportional-hazards prediction model for the feature subset, we identified has-miR-146b as one of the most significant predictor (p = 0.045; hazard ratios = 0.39. The proposed algorithm is a promising computational strategy for dissecting hidden genetic heterogeneity for complex diseases, and will be of value for improving cancer diagnosis and treatment.

  5. Heterogeneity phantoms for visualization of 3D dose distributions by MRI-based polymer gel dosimetry

    International Nuclear Information System (INIS)

    Watanabe, Yoichi; Mooij, Rob; Mark Perera, G.; Maryanski, Marek J.

    2004-01-01

    Heterogeneity corrections in dose calculations are necessary for radiation therapy treatment plans. Dosimetric measurements of the heterogeneity effects are hampered if the detectors are large and their radiological characteristics are not equivalent to water. Gel dosimetry can solve these problems. Furthermore, it provides three-dimensional (3D) dose distributions. We used a cylindrical phantom filled with BANG-3 registered polymer gel to measure 3D dose distributions in heterogeneous media. The phantom has a cavity, in which water-equivalent or bone-like solid blocks can be inserted. The irradiated phantom was scanned with an magnetic resonance imaging (MRI) scanner. Dose distributions were obtained by calibrating the polymer gel for a relationship between the absorbed dose and the spin-spin relaxation rate of the magnetic resistance (MR) signal. To study dose distributions we had to analyze MR imaging artifacts. This was done in three ways: comparison of a measured dose distribution in a simulated homogeneous phantom with a reference dose distribution, comparison of a sagittally scanned image with a sagittal image reconstructed from axially scanned data, and coregistration of MR and computed-tomography images. We found that the MRI artifacts cause a geometrical distortion of less than 2 mm and less than 10% change in the dose around solid inserts. With these limitations in mind we could make some qualitative measurements. Particularly we observed clear differences between the measured dose distributions around an air-gap and around bone-like material for a 6 MV photon beam. In conclusion, the gel dosimetry has the potential to qualitatively characterize the dose distributions near heterogeneities in 3D

  6. Molecular heterogeneous catalysts derived from bipyridine-based organosilica nanotubes for C-H bond activation.

    Science.gov (United States)

    Zhang, Shengbo; Wang, Hua; Li, Mei; Han, Jinyu; Liu, Xiao; Gong, Jinlong

    2017-06-01

    Heterogeneous metal complex catalysts for direct C-H activation with high activity and durability have always been desired for transforming raw materials into feedstock chemicals. This study described the design and synthesis of one-dimensional organosilica nanotubes containing 2,2'-bipyridine (bpy) ligands in the framework (BPy-NT) and their post-synthetic metalation to provide highly active and robust molecular heterogeneous catalysts. By adjusting the ratios of organosilane precursors, very short BPy-NT with ∼50 nm length could be controllably obtained. The post-synthetic metalation of bipyridine-functionalized nanotubes with [IrCp*Cl(μ-Cl)] 2 (Cp* = η 5 -pentamethylcyclopentadienyl) and [Ir(cod)(OMe)] 2 (cod = 1,5-cyclooctadiene) afforded solid catalysts, IrCp*-BPy-NT and Ir(cod)-BPy-NT, which were utilized for C-H oxidation of heterocycles and cycloalkanes as well as C-H borylation of arenes. The cut-short nanotube catalysts displayed enhanced activities and durability as compared to the analogous homogeneous catalysts and other conventional heterogeneous catalysts, benefiting from the isolated active sites as well as the fast transport of substrates and products. After the reactions, a detailed characterization of Ir-immobilized BPy-NT via TEM, SEM, nitrogen adsorption, UV/vis, XPS, and 13 C CP MAS NMR indicated the molecular nature of the active species as well as stable structures of nanotube scaffolds. This study demonstrates the potential of BPy-NT with a short length as an integration platform for the construction of efficient heterogeneous catalytic systems for organic transformations.

  7. Services Recommendation System based on Heterogeneous Network Analysis in Cloud Computing

    OpenAIRE

    Junping Dong; Qingyu Xiong; Junhao Wen; Peng Li

    2014-01-01

    Resources are provided mainly in the form of services in cloud computing. In the distribute environment of cloud computing, how to find the needed services efficiently and accurately is the most urgent problem in cloud computing. In cloud computing, services are the intermediary of cloud platform, services are connected by lots of service providers and requesters and construct the complex heterogeneous network. The traditional recommendation systems only consider the functional and non-functi...

  8. Scaffolding in geometry based on self regulated learning

    Science.gov (United States)

    Bayuningsih, A. S.; Usodo, B.; Subanti, S.

    2017-12-01

    This research aim to know the influence of problem based learning model by scaffolding technique on junior high school student’s learning achievement. This research took location on the junior high school in Banyumas. The research data obtained through mathematic learning achievement test and self-regulated learning (SRL) questioner. Then, the data analysis used two ways ANOVA. The results showed that scaffolding has positive effect to the mathematic learning achievement. The mathematic learning achievement use PBL-Scaffolding model is better than use PBL. The high SRL category student has better mathematic learning achievement than middle and low SRL categories, and then the middle SRL category has better than low SRL category. So, there are interactions between learning model with self-regulated learning in increasing mathematic learning achievement.

  9. Towards the Sigma Online Learning Model for crowdsourced recommendations of good web-based learning resources

    OpenAIRE

    Aaberg, Robin Garen

    2016-01-01

    The web based learning resources is believed to be playing an active role in the learning environment of higher education today. This qualitative study is exploring how students at Bergen University College incorporate web-based learning resources in their learning activities. At the core of this research is the problem of retrieving good web-resources after their first discovery. Usefull and knowledge granting web-resources are discovered within a context of topics, objectives. It is here ar...

  10. A strategy learning model for autonomous agents based on classification

    Directory of Open Access Journals (Sweden)

    Śnieżyński Bartłomiej

    2015-09-01

    Full Text Available In this paper we propose a strategy learning model for autonomous agents based on classification. In the literature, the most commonly used learning method in agent-based systems is reinforcement learning. In our opinion, classification can be considered a good alternative. This type of supervised learning can be used to generate a classifier that allows the agent to choose an appropriate action for execution. Experimental results show that this model can be successfully applied for strategy generation even if rewards are delayed. We compare the efficiency of the proposed model and reinforcement learning using the farmer-pest domain and configurations of various complexity. In complex environments, supervised learning can improve the performance of agents much faster that reinforcement learning. If an appropriate knowledge representation is used, the learned knowledge may be analyzed by humans, which allows tracking the learning process

  11. Gene ontology based transfer learning for protein subcellular localization

    Directory of Open Access Journals (Sweden)

    Zhou Shuigeng

    2011-02-01

    Full Text Available Abstract Background Prediction of protein subcellular localization generally involves many complex factors, and using only one or two aspects of data information may not tell the true story. For this reason, some recent predictive models are deliberately designed to integrate multiple heterogeneous data sources for exploiting multi-aspect protein feature information. Gene ontology, hereinafter referred to as GO, uses a controlled vocabulary to depict biological molecules or gene products in terms of biological process, molecular function and cellular component. With the rapid expansion of annotated protein sequences, gene ontology has become a general protein feature that can be used to construct predictive models in computational biology. Existing models generally either concatenated the GO terms into a flat binary vector or applied majority-vote based ensemble learning for protein subcellular localization, both of which can not estimate the individual discriminative abilities of the three aspects of gene ontology. Results In this paper, we propose a Gene Ontology Based Transfer Learning Model (GO-TLM for large-scale protein subcellular localization. The model transfers the signature-based homologous GO terms to the target proteins, and further constructs a reliable learning system to reduce the adverse affect of the potential false GO terms that are resulted from evolutionary divergence. We derive three GO kernels from the three aspects of gene ontology to measure the GO similarity of two proteins, and derive two other spectrum kernels to measure the similarity of two protein sequences. We use simple non-parametric cross validation to explicitly weigh the discriminative abilities of the five kernels, such that the time & space computational complexities are greatly reduced when compared to the complicated semi-definite programming and semi-indefinite linear programming. The five kernels are then linearly merged into one single kernel for

  12. Measuring the Differences between Traditional Learning and Game-Based Learning Using Electroencephalography (EEG) Physiologically Based Methodology

    Science.gov (United States)

    Chen, Ching-Huei

    2017-01-01

    Students' cognitive states can reflect a learning experience that results in engagement in an activity. In this study, we used electroencephalography (EEG) physiologically based methodology to evaluate students' levels of attention and relaxation, as well as their learning performance within a traditional and game-based learning context. While no…

  13. How to Enhance Interdisciplinary Competence--Interdisciplinary Problem-Based Learning versus Interdisciplinary Project-Based Learning

    Science.gov (United States)

    Brassler, Mirjam; Dettmers, Jan

    2017-01-01

    Interdisciplinary competence is important in academia for both employability and sustainable development. However, to date, there are no specific interdisciplinary education models and, naturally, no empirical studies to assess them. Since problem-based learning (PBL) and project-based learning (PjBL) are learning approaches that emphasize…

  14. Improving self-regulated learning junior high school students through computer-based learning

    Science.gov (United States)

    Nurjanah; Dahlan, J. A.

    2018-05-01

    This study is back grounded by the importance of self-regulated learning as an affective aspect that determines the success of students in learning mathematics. The purpose of this research is to see how the improvement of junior high school students' self-regulated learning through computer based learning is reviewed in whole and school level. This research used a quasi-experimental research method. This is because individual sample subjects are not randomly selected. The research design used is Pretest-and-Posttest Control Group Design. Subjects in this study were students of grade VIII junior high school in Bandung taken from high school (A) and middle school (B). The results of this study showed that the increase of the students' self-regulated learning who obtain learning with computer-based learning is higher than students who obtain conventional learning. School-level factors have a significant effect on increasing of the students' self-regulated learning.

  15. Learning and Motivational Processes When Students Design Curriculum‐Based Digital Learning Games

    DEFF Research Database (Denmark)

    Weitze, Charlotte Lærke

    2016-01-01

    This design‐based research (DBR) project has developed an overall gamified learning design (big Game) to facilitate the learning process for adult students by inviting them to be their own learning designers through designing digital learning games (small games) in cross‐disciplinary subject...... matters. The DBR project has investigated and experimented with which elements, methods, and processes are important when aiming at creating a cognitive complex (Anderson and Krathwohl, 2001) and motivating learning process within a reusable game‐based learning design. This project took place in a co......, or programming provide a rich context for learning, since the construction of artefacts, in this case learning games, enables reflection and new ways of thinking. The students learned from reflection and interaction with the tools alone as well as in collaboration with peers. After analysing the students...

  16. Learning and Motivational Processes When Students Design Curriculum-Based Digital Learning Games

    DEFF Research Database (Denmark)

    Weitze, Charlotte Lærke

    2015-01-01

    This design-based research (DBR) project has developed an overall gamified learning design (big Game) to facilitate the learning process for adult students by inviting them to be their own learning designers through designing digital learning games (small games) in cross-disciplinary subject...... matters. The DBR project has investigated and experimented with which elements, methods, and processes are important when aiming at creating a cognitive complex (Anderson and Krathwohl, 2001) and motivating learning process within a reusable game-based learning design. This project took place in a co......, or programming provide a rich context for learning, since the construction of artefacts, in this case learning games, enables reflection and new ways of thinking. The students learned from reflection and interaction with the tools alone as well as in collaboration with peers. After analysing the students...

  17. The Effectiveness of Collaborative Academic Online Based Learning through Students’ Self-Regulated Learning

    Directory of Open Access Journals (Sweden)

    Erfan Priyambodo

    2016-11-01

    Full Text Available Nowdays, learning through e-learning is going rapidly, including the application BeSmart UNY. This application is providing collaborative method in teaching and learning. The aim of this study was to determine the effectiveness of the Collaborative Academic Online Based Learning method in teaching and learning toward students’ Self-Regulated Learning (SRL on Vocational School Chemistry courses. This study was quasi-experimental research method with one group pretest posttest design. Instruments used in this study were lesson plan and questionnaire of students’ SRL. This questionnaire is filled by students through BeSmart UNY.  In determining the differences SRL before and after teaching and learning processes, the data was analized by stastitical method.  The results showed that the implementation of the Collaborative Academic Online Based Learning method in teaching and learning was effective for improving students’ SRL.

  18. Access Selection Algorithm of Heterogeneous Wireless Networks for Smart Distribution Grid Based on Entropy-Weight and Rough Set

    Science.gov (United States)

    Xiang, Min; Qu, Qinqin; Chen, Cheng; Tian, Li; Zeng, Lingkang

    2017-11-01

    To improve the reliability of communication service in smart distribution grid (SDG), an access selection algorithm based on dynamic network status and different service types for heterogeneous wireless networks was proposed. The network performance index values were obtained in real time by multimode terminal and the variation trend of index values was analyzed by the growth matrix. The index weights were calculated by entropy-weight and then modified by rough set to get the final weights. Combining the grey relational analysis to sort the candidate networks, and the optimum communication network is selected. Simulation results show that the proposed algorithm can implement dynamically access selection in heterogeneous wireless networks of SDG effectively and reduce the network blocking probability.

  19. A Technology-based Model for Learning

    Directory of Open Access Journals (Sweden)

    Michael Williams

    2004-12-01

    Full Text Available The Math Emporium, opened in 1997, is an open 7000-squaremeter facility with 550+ workstations arranged in an array of widely spaced hexagonal "pods", designed to support group work at the same time maintaining an academic air. We operate it 24/7 with math support personnel in attendance 12 hours per day. Students have access to online course resources at all times, from anywhere. We have used this unique asset to transform traditional classroom-based courses into technology based learning programs that have no class meetings at all. The structure of the program is very different from the conventional one, having a new set of expectations and motivations. The results include: more effective students, substantial cost savings, economies of scale and scope and a stream-lined process for creating new on-line courses.

  20. Creative Writing, Problem-Based Learning, and Game-Based Learning Principles

    Science.gov (United States)

    Trekles, Anastasia M.

    2012-01-01

    This paper examines how virtual worlds and other advanced social media can be married with problem-based learning to encourage creativity and critical thinking in the English/Language Arts classroom, particularly for middle school, high school, and undergraduate college education. Virtual world experiences such as "Second Life," Jumpstart.com, and…

  1. Web-based Cooperative Learning in College Chemistry Teaching

    Directory of Open Access Journals (Sweden)

    Bin Jiang

    2014-03-01

    Full Text Available With the coming of information era, information process depend on internet and multi-media technology in education becomes the new approach of present teaching model reform. Web-based cooperative learning is becoming a popular learning approach with the rapid development of web technology. The paper aims to how to carry out the teaching strategy of web-based cooperative learning and applied in the foundation chemistry teaching.It was shown that with the support of modern web-based teaching environment, students' cooperative learning capacity and overall competence can be better improved and the problems of interaction in large foundation chemistry classes can be solved. Web-based cooperative learning can improve learning performance of students, what's more Web-based cooperative learning provides students with cooperative skills, communication skills, creativity, critical thinking skills and skills in information technology application.

  2. PENGEMBANGAN CASE BASE LEARNING PADA MATA KULIAH PEREKONOMIAN INDONESIA

    Directory of Open Access Journals (Sweden)

    Hastarini Dwi Atmani

    2011-05-01

    Full Text Available In this time, teacher centered learning is a methods in part of higher education in Indonsia. This method, students passively receive information.Case base learning is an instructional design model that is a variant of project oriented learning. Cases are factually-based, complex problems written to stimulate classroom discussion and collaborative analysis. This one, students construct knowledge through gathering and synthesizing information and integrating it with the general skills of inquiry, communication, critical thinking, and problem solving. Key words : active learning, case base learning.

  3. PERANCANGAN WEB BASED LEARNING SEBAGAI MEDIA PEMBELAJARAN BERBASIS ICT

    OpenAIRE

    Ricky Firmansyah; Iis Saidah

    2016-01-01

    ABSTRACT The media is very important component of communication process. The effectiveness of media is very influential on extent to which a communication role will be accepted by the audience with fast and precise, or vice versa. E-Learning is present as ICT based learning media that allows students and teachers interact in different places. Web Based Learning (WBL) is used as one part of the E-Learning. This study focuses on designing web-based ICT as a learning medium that is used for ...

  4. Enhancing students' learning in problem based learning: validation of a self-assessment scale for active learning and critical thinking

    NARCIS (Netherlands)

    Khoiriyah, U.; Roberts, C.; Jorm, C.; Vleuten, C.P. van der

    2015-01-01

    BACKGROUND: Problem based learning (PBL) is a powerful learning activity but fidelity to intended models may slip and student engagement wane, negatively impacting learning processes, and outcomes. One potential solution to solve this degradation is by encouraging self-assessment in the PBL

  5. Scene recognition based on integrating active learning with dictionary learning

    Science.gov (United States)

    Wang, Chengxi; Yin, Xueyan; Yang, Lin; Gong, Chengrong; Zheng, Caixia; Yi, Yugen

    2018-04-01

    Scene recognition is a significant topic in the field of computer vision. Most of the existing scene recognition models require a large amount of labeled training samples to achieve a good performance. However, labeling image manually is a time consuming task and often unrealistic in practice. In order to gain satisfying recognition results when labeled samples are insufficient, this paper proposed a scene recognition algorithm named Integrating Active Learning and Dictionary Leaning (IALDL). IALDL adopts projective dictionary pair learning (DPL) as classifier and introduces active learning mechanism into DPL for improving its performance. When constructing sampling criterion in active learning, IALDL considers both the uncertainty and representativeness as the sampling criteria to effectively select the useful unlabeled samples from a given sample set for expanding the training dataset. Experiment results on three standard databases demonstrate the feasibility and validity of the proposed IALDL.

  6. Adaptive E- Learning System Based on Personalized Learning Style

    African Journals Online (AJOL)

    pc

    2018-03-05

    Mar 5, 2018 ... motivation to this research is to improve the learner performance and achieve the ... valuable factor for enhancing learning process by adopting an effective .... Video. Reflective Intuitive. Primer Test. Verbal Sequential. Tutorial.

  7. Cognitive components underpinning the development of model-based learning.

    Science.gov (United States)

    Potter, Tracey C S; Bryce, Nessa V; Hartley, Catherine A

    2017-06-01

    Reinforcement learning theory distinguishes "model-free" learning, which fosters reflexive repetition of previously rewarded actions, from "model-based" learning, which recruits a mental model of the environment to flexibly select goal-directed actions. Whereas model-free learning is evident across development, recruitment of model-based learning appears to increase with age. However, the cognitive processes underlying the development of model-based learning remain poorly characterized. Here, we examined whether age-related differences in cognitive processes underlying the construction and flexible recruitment of mental models predict developmental increases in model-based choice. In a cohort of participants aged 9-25, we examined whether the abilities to infer sequential regularities in the environment ("statistical learning"), maintain information in an active state ("working memory") and integrate distant concepts to solve problems ("fluid reasoning") predicted age-related improvements in model-based choice. We found that age-related improvements in statistical learning performance did not mediate the relationship between age and model-based choice. Ceiling performance on our working memory assay prevented examination of its contribution to model-based learning. However, age-related improvements in fluid reasoning statistically mediated the developmental increase in the recruitment of a model-based strategy. These findings suggest that gradual development of fluid reasoning may be a critical component process underlying the emergence of model-based learning. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  8. Case-based learning in an electronic learning environment

    OpenAIRE

    John Graham

    2014-01-01

    The benefits of e-learning have been widely established. These benefits include reduced costs, time savings, flexibility, accessible learning, and convenience. Due to such benefits, it has attracted business, industry, the professions, and of course educational institutes to begin using this platform either to supplement traditional teaching strategies or offer it as a complete substitute for them. The benefits of teaching with case studies are also well-recognized. Working with real world si...

  9. Non-invasive quality evaluation of confluent cells by image-based orientation heterogeneity analysis.

    Science.gov (United States)

    Sasaki, Kei; Sasaki, Hiroto; Takahashi, Atsuki; Kang, Siu; Yuasa, Tetsuya; Kato, Ryuji

    2016-02-01

    In recent years, cell and tissue therapy in regenerative medicine have advanced rapidly towards commercialization. However, conventional invasive cell quality assessment is incompatible with direct evaluation of the cells produced for such therapies, especially in the case of regenerative medicine products. Our group has demonstrated the potential of quantitative assessment of cell quality, using information obtained from cell images, for non-invasive real-time evaluation of regenerative medicine products. However, image of cells in the confluent state are often difficult to evaluate, because accurate recognition of cells is technically difficult and the morphological features of confluent cells are non-characteristic. To overcome these challenges, we developed a new image-processing algorithm, heterogeneity of orientation (H-Orient) processing, to describe the heterogeneous density of cells in the confluent state. In this algorithm, we introduced a Hessian calculation that converts pixel intensity data to orientation data and a statistical profiling calculation that evaluates the heterogeneity of orientations within an image, generating novel parameters that yield a quantitative profile of an image. Using such parameters, we tested the algorithm's performance in discriminating different qualities of cellular images with three types of clinically important cell quality check (QC) models: remaining lifespan check (QC1), manipulation error check (QC2), and differentiation potential check (QC3). Our results show that our orientation analysis algorithm could predict with high accuracy the outcomes of all types of cellular quality checks (>84% average accuracy with cross-validation). Copyright © 2015 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

  10. Ontology-based knowledge representation for resolution of semantic heterogeneity in GIS

    Science.gov (United States)

    Liu, Ying; Xiao, Han; Wang, Limin; Han, Jialing

    2017-07-01

    Lack of semantic interoperability in geographical information systems has been identified as the main obstacle for data sharing and database integration. The new method should be found to overcome the problems of semantic heterogeneity. Ontologies are considered to be one approach to support geographic information sharing. This paper presents an ontology-driven integration approach to help in detecting and possibly resolving semantic conflicts. Its originality is that each data source participating in the integration process contains an ontology that defines the meaning of its own data. This approach ensures the automation of the integration through regulation of semantic integration algorithm. Finally, land classification in field GIS is described as the example.

  11. Voice based gender classification using machine learning

    Science.gov (United States)

    Raahul, A.; Sapthagiri, R.; Pankaj, K.; Vijayarajan, V.

    2017-11-01

    Gender identification is one of the major problem speech analysis today. Tracing the gender from acoustic data i.e., pitch, median, frequency etc. Machine learning gives promising results for classification problem in all the research domains. There are several performance metrics to evaluate algorithms of an area. Our Comparative model algorithm for evaluating 5 different machine learning algorithms based on eight different metrics in gender classification from acoustic data. Agenda is to identify gender, with five different algorithms: Linear Discriminant Analysis (LDA), K-Nearest Neighbour (KNN), Classification and Regression Trees (CART), Random Forest (RF), and Support Vector Machine (SVM) on basis of eight different metrics. The main parameter in evaluating any algorithms is its performance. Misclassification rate must be less in classification problems, which says that the accuracy rate must be high. Location and gender of the person have become very crucial in economic markets in the form of AdSense. Here with this comparative model algorithm, we are trying to assess the different ML algorithms and find the best fit for gender classification of acoustic data.

  12. The Effectiveness of the Gesture-Based Learning System (GBLS and Its Impact on Learning Experience

    Directory of Open Access Journals (Sweden)

    Moamer Ali Shakroum

    2016-06-01

    Full Text Available Several studies and experiments have been conducted in recent years to examine the value and the advantage of using the Gesture-Based Learning System (GBLS.The investigation of the influence of the GBLS mode on the learning outcomes is still scarce. Most previous studies did not address more than one category of learning outcomes (cognitive, affective outcomes, etc. at the same time when used to understand the impact of GBLS. Moreover, none of these studies considered the difference in students’ characteristics such as learning styles and spatial abilities. Therefore, a comprehensive empirical research on the impact of the GBLS mode on learning outcomes is needed. The purpose of this paper is to fill in the gap and to investigate the effectiveness of the GBLS mode on learning using Technology Mediated Learning (TML models. This study revealed that the GBLS mode has greater positive impact on students’ learning outcomes (cognitive and affective outcomes when compared with other two learning modes that are classified as Computer Simulation Software Learning (CSSL mode and conventional learning mode. In addition, this study also found that the GBLS mode is capable of serving all students with different learning styles and spatial ability levels. The results of this study revealed that the GBLS mode outperformed the existing learning methods by providing a unique learning experience that considers the differences between students. The results have also shown that the Kinect user interface can create an interactive and an enjoyable learning experience.

  13. Blended Learning Based on Schoology: Effort of Improvement Learning Outcome and Practicum Chance in Vocational High School

    Science.gov (United States)

    Irawan, Vincentius Tjandra; Sutadji, Eddy; Widiyanti

    2017-01-01

    The aims of this study were to determine: (1) the differences in learning outcome between Blended Learning based on Schoology and Problem-Based Learning, (2) the differences in learning outcome between students with prior knowledge of high, medium, and low, and (3) the interaction between Blended Learning based on Schoology and prior knowledge to…

  14. Development and Evaluation of a Computer-Based Learning Environment for Teachers: Assessment of Learning Strategies in Learning Journals

    Directory of Open Access Journals (Sweden)

    Inga Glogger

    2013-01-01

    Full Text Available Training teachers to assess important components of self-regulated learning such as learning strategies is an important, yet somewhat neglected, aspect of the integration of self-regulated learning at school. Learning journals can be used to assess learning strategies in line with cyclical process models of self-regulated learning, allowing for rich formative feedback. Against this background, we developed a computer-based learning environment (CBLE that trains teachers to assess learning strategies with learning journals. The contents of the CBLE and its instructional design were derived from theory. The CBLE was further shaped by research in a design-based manner. Finally, in two evaluation studies, student teachers (N1=44; N2=89 worked with the CBLE. We analyzed satisfaction, interest, usability, and assessment skills. Additionally, in evaluation study 2, effects of an experimental variation on motivation and assessment skills were tested. We found high satisfaction, interest, and good usability, as well as satisfying assessment skills, after working with the CBLE. Results show that teachers can be trained to assess learning strategies in learning journals. The developed CBLE offers new perspectives on how to support teachers in fostering learning strategies as central component of effective self-regulated learning at school.

  15. An Adaptive Learning Based Network Selection Approach for 5G Dynamic Environments

    Directory of Open Access Journals (Sweden)

    Xiaohong Li

    2018-03-01

    Full Text Available Networks will continue to become increasingly heterogeneous as we move toward 5G. Meanwhile, the intelligent programming of the core network makes the available radio resource be more changeable rather than static. In such a dynamic and heterogeneous network environment, how to help terminal users select optimal networks to access is challenging. Prior implementations of network selection are usually applicable for the environment with static radio resources, while they cannot handle the unpredictable dynamics in 5G network environments. To this end, this paper considers both the fluctuation of radio resources and the variation of user demand. We model the access network selection scenario as a multiagent coordination problem, in which a bunch of rationally terminal users compete to maximize their benefits with incomplete information about the environment (no prior knowledge of network resource and other users’ choices. Then, an adaptive learning based strategy is proposed, which enables users to adaptively adjust their selections in response to the gradually or abruptly changing environment. The system is experimentally shown to converge to Nash equilibrium, which also turns out to be both Pareto optimal and socially optimal. Extensive simulation results show that our approach achieves significantly better performance compared with two learning and non-learning based approaches in terms of load balancing, user payoff and the overall bandwidth utilization efficiency. In addition, the system has a good robustness performance under the condition with non-compliant terminal users.

  16. Evolutionary Game Theory-Based Evaluation of P2P File-Sharing Systems in Heterogeneous Environments

    Directory of Open Access Journals (Sweden)

    Yusuke Matsuda

    2010-01-01

    Full Text Available Peer-to-Peer (P2P file sharing is one of key technologies for achieving attractive P2P multimedia social networking. In P2P file-sharing systems, file availability is improved by cooperative users who cache and share files. Note that file caching carries costs such as storage consumption and processing load. In addition, users have different degrees of cooperativity in file caching and they are in different surrounding environments arising from the topological structure of P2P networks. With evolutionary game theory, this paper evaluates the performance of P2P file sharing systems in such heterogeneous environments. Using micro-macro dynamics, we analyze the impact of the heterogeneity of user selfishness on the file availability and system stability. Further, through simulation experiments with agent-based dynamics, we reveal how other aspects, for example, synchronization among nodes and topological structure, affect the system performance. Both analytical and simulation results show that the environmental heterogeneity contributes to the file availability and system stability.

  17. Learning for Sustainability Among Faith-Based Organizations in Kenya

    Science.gov (United States)

    Moyer, Joanne M.; Sinclair, A. John; Diduck, Alan P.

    2014-08-01

    The complex and unpredictable contexts in which environmental and development work take place require an adaptable, learning approach. Faith-based organizations (FBOs) play a significant role in sustainability work around the world, and provide a unique setting in which to study learning. This paper explores individual learning for sustainability within two FBOs engaged in sustainability work in Kenya. Learning outcomes covered a broad range of areas, including the sustainability framework, environment/conservation, skills, community work, interpersonal engagement, and personal and faith development. These outcomes were acquired through embodied experience and activity, facilitation by the workplace, interpersonal interaction, personal reflection, and Bible study and worship. Grounded categories were compared to learning domains and processes described by Mezirow's transformative learning theory. The findings indicate that for learning in the sustainability field, instrumental learning and embodied learning processes are particularly important, and consequently they require greater attention in the theory when applied in this field.

  18. Preparing Students for Flipped or Team-Based Learning Methods

    Science.gov (United States)

    Balan, Peter; Clark, Michele; Restall, Gregory

    2015-01-01

    Purpose: Teaching methods such as Flipped Learning and Team-Based Learning require students to pre-learn course materials before a teaching session, because classroom exercises rely on students using self-gained knowledge. This is the reverse to "traditional" teaching when course materials are presented during a lecture, and students are…

  19. What Is Game-Based Learning? Past, Present, and Future

    Science.gov (United States)

    Jan, Mingfong; Gaydos, Matthew

    2016-01-01

    This article aims at clarifying and conceptualizing game-based learning (GBL) in order to pinpoint directions for practices and research. The authors maintain that GBL should be conceptualized toward the transformation of a textbook-learning culture. The authors emphasize the importance of a paradigm shift in learning and a reorientation in…

  20. Designing Science Learning with Game-Based Approaches

    Science.gov (United States)

    Liu, Min; Rosenblum, Jason A.; Horton, Lucas; Kang, Jina

    2014-01-01

    Given the growing popularity of digital games as a form of entertainment, educators are interested in exploring using digital games as a tool to facilitate learning. In this study, we examine game-based learning by describing a learning environment that combines game elements, play, and authenticity in the real world for the purpose of engaging…

  1. Problem-Based Learning in Social Work Education

    DEFF Research Database (Denmark)

    Monrad, Merete; Mølholt, Anne-Kirstine

    2017-01-01

    ’ experiences of PBL. In this article we address this gap by exploring experiences of learning and learning preferences among master’s-level students in a Danish social work education setting where extensive problem-based project work is used. We find a discrepancy between students’ preferred learning and when...

  2. Collaborative Tasks in Wiki-Based Environment in EFL Learning

    Science.gov (United States)

    Zou, Bin; Wang, Dongshuo; Xing, Minjie

    2016-01-01

    Wikis provide users with opportunities to post and edit messages to collaborate in the language learning process. Many studies have offered findings to show positive impact of Wiki-based language learning for learners. This paper explores the effect of collaborative task in error correction for English as a Foreign Language learning in an online…

  3. Team-Based Learning Enhances Performance in Introductory Biology

    Science.gov (United States)

    Carmichael, Jeffrey

    2009-01-01

    Given the problems associated with the traditional lecture method, the constraints associated with large classes, and the effectiveness of active learning, continued development and testing of efficient student-centered learning approaches are needed. This study explores the effectiveness of team-based learning (TBL) in a large-enrollment…

  4. The Global Aspects of Brain-Based Learning

    Science.gov (United States)

    Connell, J. Diane

    2009-01-01

    Brain-Based Learning (BBL) can be viewed as techniques gleaned from research in neurology and cognitive science used to enhance teacher instruction. These strategies can also be used to enhance students' ability to learn using ways in which they feel most comfortable, neurologically speaking. Jensen (1995/2000) defines BBL as "learning in…

  5. Supporting Inquiry-based Learning with Google Glass (GPIM)

    NARCIS (Netherlands)

    Suarez, Angel; Ternier, Stefaan; Kalz, Marco; Specht, Marcus

    2015-01-01

    Wearable technology is a new genre of technology that is appearing to enhance learning in context. This manuscript introduces a Google Glass application to support Inquiry-based Learning (IBL). Applying Google Glass to IBL, we aim to transform the learning process into a more seamless, personal and

  6. Student Accountability in Team-Based Learning Classes

    Science.gov (United States)

    Stein, Rachel E.; Colyer, Corey J.; Manning, Jason

    2016-01-01

    Team-based learning (TBL) is a form of small-group learning that assumes stable teams promote accountability. Teamwork promotes communication among members; application exercises promote active learning. Students must prepare for each class; failure to do so harms their team's performance. Therefore, TBL promotes accountability. As part of the…

  7. Robot soccer action selection based on Q learning

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    This paper researches robot soccer action selection based on Q learning . The robot learn to activate particular behavior given their current situation and reward signal. We adopt neural network to implementations of Q learning for their generalization properties and limited computer memory requirements

  8. A Judgement-Based Model of Workplace Learning

    Science.gov (United States)

    Athanasou, James A.

    2004-01-01

    The purpose of this paper is to outline a judgement-based model of adult learning. This approach is set out as a Perceptual-Judgemental-Reinforcement approach to social learning under conditions of complexity and where there is no single, clearly identified correct response. The model builds upon the Hager-Halliday thesis of workplace learning and…

  9. The Office Software Learning and Examination System Design Based on Fragmented Learning Idea

    Directory of Open Access Journals (Sweden)

    Xu Ling

    2016-01-01

    Full Text Available Fragmented learning is that through the segmentation of learning content or learning time, make learners can use the fragmented time for learning fragmentated content, have the characteristics of time flexibility, learning targeted and high learning efficiency. Based on the fragmented learning ideas, combined with the teaching idea of micro class and interactive teaching, comprehensive utilization of flash animation design software, .NET development platform, VSTO technology, multimedia development technology and so on, design and develop a system integrated with learning, practice and examination of the Office software, which is not only conducive to the effective and personalized learning of students, but also conducive to the understanding the students’ situation of teachers, and liberate teachers from the heavy labor of mechanical, focus on promoting the formation of students’ knowledge system.

  10. Computer-based learning in neuroanatomy: A longitudinal study of learning, transfer, and retention

    Science.gov (United States)

    Chariker, Julia H.

    A longitudinal experiment was conducted to explore computer-based learning of neuroanatomy. Using a realistic 3D graphical model of neuroanatomy, and sections derived from the model, exploratory graphical tools were integrated into interactive computer programs so as to allow adaptive exploration. 72 participants learned either sectional anatomy alone or learned whole anatomy followed by sectional anatomy. Sectional anatomy was explored either in perceptually continuous animation or discretely, as in the use of an anatomical atlas. Learning was measured longitudinally to a high performance criterion. After learning, transfer to biomedical images and long-term retention was tested. Learning whole anatomy prior to learning sectional anatomy led to a more efficient learning experience. Learners demonstrated high levels of transfer from whole anatomy to sectional anatomy and from sectional anatomy to complex biomedical images. All learning groups demonstrated high levels of retention at 2--3 weeks.

  11. Practical chemical analysis of Pt and Pd based heterogeneous catalysts with hard X-ray photoelectron spectroscopy

    Energy Technology Data Exchange (ETDEWEB)

    Yoshikawa, H., E-mail: YOSHIKAWA.Hideki@nims.go.jp [National Institute for Materials Science, 1-2-1 Sengen, Tsukuba, Ibaraki 305-0047 (Japan); Matolínová, I.; Matolín, V. [Charles University in Prague, Faculty of Mathematics and Physics, V Holešovičkách 2, 18000 Prague 8 (Czech Republic)

    2013-10-15

    Highlights: •Hard X-ray photoelectron spectroscopy (HAXPES) enables interface analysis of catalyst. •HAXPES enables overall analysis of porous film of Pt-doped CeO{sub 2} and related catalyst. •HAXPES enables analysis of trace elements for Pd and Pt{sub 3}Ni nanoparticle catalysts. -- Abstract: Interfacial properties including configuration, porosity, chemical states, and atomic diffusion greatly affect the performance of supported heterogeneous catalysts. Hard X-ray photoelectron spectroscopy (HAXPES) can be used to analyze the interfaces of heterogeneous catalysts because of its large information depth of more than 20 nm. We use HAXPES to examine Pt-doped CeO{sub 2} and related thin film catalysts evaporated on Si, carbon, and carbon nanotube substrates, because Pt-doped CeO{sub 2} has great potential as a noble metal-based heterogeneous catalyst for fuel cells. The HAXPES measurements clarify that the dopant material, substrate material, and surface pretreatment of substrate are important parameters that affect the interfacial properties of Pt-doped CeO{sub 2} and related thin film catalysts. Another advantage of HAXPES measurement of heterogeneous catalysts is that it can be used for chemical analysis of trace elements by detecting photoelectrons from deep core levels, which have large photoionization cross-sections in the hard X-ray region. We use HAXPES for chemical analysis of trace elements in Pd nanoparticle catalysts immobilized on sulfur-terminated substrates and Pt{sub 3}Ni nanoparticle catalysts enveloped by dendrimer molecules.

  12. Effect of Worksheet Scaffolds on Student Learning in Problem-Based Learning

    Science.gov (United States)

    Choo, Serene S. Y.; Rotgans, Jerome I.; Yew, Elaine H. J.; Schmidt, Henk G.

    2011-01-01

    The purpose of this study was to investigate the effect of worksheets as a scaffolding tool on students' learning achievement in a problem-based learning (PBL) environment. Seventeen PBL classes (N = 241) were randomly assigned to two experimental groups--one with a worksheet provided and the other without. Students' learning of the topic at hand…

  13. Problem-Based Learning and Learning Approach: Is There a Relationship?

    Science.gov (United States)

    Groves, Michele

    2005-01-01

    Aim: To assess the influence of a graduate-entry PBL (problem-based learning) curriculum on individual learning style; and to investigate the relationship between learning style, academic achievement and clinical reasoning skill. Method: Subjects were first-year medical students completed the Study Process Questionnaire at the commencement, and…

  14. Problem-Based Learning to Foster Deep Learning in Preservice Geography Teacher Education

    Science.gov (United States)

    Golightly, Aubrey; Raath, Schalk

    2015-01-01

    In South Africa, geography education students' approach to deep learning has received little attention. Therefore the purpose of this one-shot experimental case study was to evaluate the extent to which first-year geography education students used deep or surface learning in an embedded problem-based learning (PBL) format. The researchers measured…

  15. Deep and Surface Learning in Problem-Based Learning: A Review of the Literature

    Science.gov (United States)

    Dolmans, Diana H. J. M.; Loyens, Sofie M. M.; Marcq, Hélène; Gijbels, David

    2016-01-01

    In problem-based learning (PBL), implemented worldwide, students learn by discussing professionally relevant problems enhancing application and integration of knowledge, which is assumed to encourage students towards a deep learning approach in which students are intrinsically interested and try to understand what is being studied. This review…

  16. iPad Learning Ecosystem: Developing Challenge-Based Learning Using Design Thinking

    Science.gov (United States)

    Marin, Catalina; Hargis, Jace; Cavanaugh, Cathy

    2013-01-01

    In order to maximize college English language students' learning, product development, 21st Century skills and engagement with real world meaningful challenges, a course was designed to integrate Challenge Based Learning (CBL) and iPad mobile learning technology. This article describes the course design, which was grounded in design thinking, and…

  17. Project based learning in organizations: towards a methodology for learning in groups

    NARCIS (Netherlands)

    Poell, R.F.; Krogt, F.J. van der

    2003-01-01

    This article introduces a methodology for employees in organizations to set up and carry out their own group learning projects. It is argued that employees can use project-based learning to make their everyday learning more systematic at times, without necessarily formalizing it. The article

  18. Project-based learning in organizations : Towards a methodology for learning in groups

    NARCIS (Netherlands)

    Poell, R.F.; van der Krogt, F.J.

    2003-01-01

    This article introduces a methodology for employees in organizations to set up and carry out their own group learning projects. It is argued that employees can use project-based learning to make their everyday learning more systematic at times, without necessarily formalizing it. The article

  19. Understanding and Predicting Student Self-Regulated Learning Strategies in Game-Based Learning Environments

    Science.gov (United States)

    Sabourin, Jennifer L.; Shores, Lucy R.; Mott, Bradford W.; Lester, James C.

    2013-01-01

    Self-regulated learning behaviors such as goal setting and monitoring have been found to be crucial to students' success in computer-based learning environments. Consequently, understanding students' self-regulated learning behavior has been the subject of increasing attention. Unfortunately, monitoring these behaviors in real-time has…

  20. The Effects of ePortfolio-Based Learning Model on Student Self-Regulated Learning

    Science.gov (United States)

    Nguyen, Lap Trung; Ikeda, Mitsuru

    2015-01-01

    Self-regulated learners are aware of their knowledge and skills and proactive in learning. They view learning as a controllable process and accept more responsibility for the results of this process. The research described in this article proposes, implements, and evaluates an ePortfolio-based self-regulated learning model. An ePortfolio system…

  1. Active-Learning versus Teacher-Centered Instruction for Learning Acids and Bases

    Science.gov (United States)

    Sesen, Burcin Acar; Tarhan, Leman

    2011-01-01

    Background and purpose: Active-learning as a student-centered learning process has begun to take more interest in constructing scientific knowledge. For this reason, this study aimed to investigate the effectiveness of active-learning implementation on high-school students' understanding of "acids and bases". Sample: The sample of this…

  2. Learning Outcomes in Vocational Education: A Business Plan Development by Production-Based Learning Model Approach

    Science.gov (United States)

    Kusumaningrum, Indrati; Hidayat, Hendra; Ganefri; Anori, Sartika; Dewy, Mega Silfia

    2016-01-01

    This article describes the development of a business plan by using production-based learning approach. In addition, this development also aims to maximize learning outcomes in vocational education. Preliminary analysis of curriculum and learning and the needs of the market and society become the basic for business plan development. To produce a…

  3. promoting self directed learning in simulation based discovery learning environments through intelligent support.

    NARCIS (Netherlands)

    Veermans, K.H.; de Jong, Anthonius J.M.; van Joolingen, Wouter

    2000-01-01

    Providing learners with computer-generated feedback on their learning process in simulationbased discovery environments cannot be based on a detailed model of the learning process due to the “open” character of discovery learning. This paper describes a method for generating adaptive feedback for

  4. PROJECT BASED LEARNING BERMUATAN ETNOMATEMATIKA DALAM PEMBELAJAR MATEMATIKA

    Directory of Open Access Journals (Sweden)

    I Wayan Eka Mahendra

    2017-03-01

    Full Text Available This study aims to determine differences simultaneously in motivation and mathematics learning outcomes between students taking project based learningmodel charged ethnomathematics and students who followed the conventional learning modelon the class VIII SMP Negeri 3 Abiansemalyear 2016/2017. It was a quasi experiment with a sample of 71 student obtain by using simple random sampling. The data were analyzed by one-way multivariate analysis (Manova.The results of this study indicate that there are differences in simultaneously in learning motivation and learning outcomes between students taking mathematics model project based learning charged ethnomathematics and students who followed the conventional learning model on the class VIII SMP Negeri 3 Abiansemal year 2016/2017. Besed on the research findings, junior high school teachers are suggested to improve their student learning outcome for mathematics. Teachers also need to use a learning models accurately and correctly.

  5. An Innovative Teaching Method To Promote Active Learning: Team-Based Learning

    Science.gov (United States)

    Balasubramanian, R.

    2007-12-01

    Traditional teaching practice based on the textbook-whiteboard- lecture-homework-test paradigm is not very effective in helping students with diverse academic backgrounds achieve higher-order critical thinking skills such as analysis, synthesis, and evaluation. Consequently, there is a critical need for developing a new pedagogical approach to create a collaborative and interactive learning environment in which students with complementary academic backgrounds and learning skills can work together to enhance their learning outcomes. In this presentation, I will discuss an innovative teaching method ('Team-Based Learning (TBL)") which I recently developed at National University of Singapore to promote active learning among students in the environmental engineering program with learning abilities. I implemented this new educational activity in a graduate course. Student feedback indicates that this pedagogical approach is appealing to most students, and promotes active & interactive learning in class. Data will be presented to show that the innovative teaching method has contributed to improved student learning and achievement.

  6. Aids to Computer-Based Multimedia Learning.

    Science.gov (United States)

    Mayer, Richard E.; Moreno, Roxana

    2002-01-01

    Presents a cognitive theory of multimedia learning that draws on dual coding theory, cognitive load theory, and constructivist learning theory and derives some principles of instructional design for fostering multimedia learning. These include principles of multiple representation, contiguity, coherence, modality, and redundancy. (SLD)

  7. Deep Learning through Concept-Based Inquiry

    Science.gov (United States)

    Donham, Jean

    2010-01-01

    Learning in the library should present opportunities to enrich student learning activities to address concerns of interest and cognitive complexity, but these must be tasks that call for in-depth analysis--not merely gathering facts. Library learning experiences need to demand enough of students to keep them interested and also need to be…

  8. Combining Correlation-Based and Reward-Based Learning in Neural Control for Policy Improvement

    DEFF Research Database (Denmark)

    Manoonpong, Poramate; Kolodziejski, Christoph; Wörgötter, Florentin

    2013-01-01

    Classical conditioning (conventionally modeled as correlation-based learning) and operant conditioning (conventionally modeled as reinforcement learning or reward-based learning) have been found in biological systems. Evidence shows that these two mechanisms strongly involve learning about...... associations. Based on these biological findings, we propose a new learning model to achieve successful control policies for artificial systems. This model combines correlation-based learning using input correlation learning (ICO learning) and reward-based learning using continuous actor–critic reinforcement...... learning (RL), thereby working as a dual learner system. The model performance is evaluated by simulations of a cart-pole system as a dynamic motion control problem and a mobile robot system as a goal-directed behavior control problem. Results show that the model can strongly improve pole balancing control...

  9. Comparison the Application of PBL (Project Based Learning and PBL (Problem Based Learning Learning Model on Online Marketing Subjects

    Directory of Open Access Journals (Sweden)

    Agnes Dini Mardani

    2017-09-01

    Full Text Available Purpose of this study are (1 the application of learning PjBL with PBL to improve study results students, (2 assessing the domain affective, cognitive, and psychomotor, (3 the difference study results use the PjBL with PBL to improve study results students. The research is research quantitative and including research apparent experiment (quasi eksperiment by taking sample class two classes X PM 1 as a class experiment and class X PM 2 as a class control. Research instruments used for data collection namely: (1 tests to pretes and postest used to determine the cognitive assessment, (2 sheets observation affective, (3 sheets of the process for the psychomotor. The trial research instruments use the validity and reabilitas. Analysis techniques data using: (1 test a prerequisite analysis consisting of normality test and the homogeneity (2 T test unpaired which ended with the help of computer programs spss. Based on the result of this research can be concluded that: (1 the application of PjBL (Project Based Learning and PBL (Problem Based Learning should be conducted well in accordance syntax learning, (2 assessing the cognitive students have a difference and class experiment having an average higher than class control, (3 assessing the results affective students have a difference and on the application of PjBL is better than PBL.

  10. An Educational Approach to Problem-based Learning

    Directory of Open Access Journals (Sweden)

    Nan-Chieh Chen

    2008-03-01

    Full Text Available This paper provides an analysis of the educational framework of problem-based learning (PBL. As known and used, PBL finds its root in the Structuralism and Pragmatism schools of philosophy. In this paper, the three main requirements of PBL, namely learning by doing, learning in context, and focusing on the student, are discussed within the context of these two schools of thought. Given these attributes, PBL also seems ideally suited for use in learning bioethics.

  11. IoT Security Techniques Based on Machine Learning

    OpenAIRE

    Xiao, Liang; Wan, Xiaoyue; Lu, Xiaozhen; Zhang, Yanyong; Wu, Di

    2018-01-01

    Internet of things (IoT) that integrate a variety of devices into networks to provide advanced and intelligent services have to protect user privacy and address attacks such as spoofing attacks, denial of service attacks, jamming and eavesdropping. In this article, we investigate the attack model for IoT systems, and review the IoT security solutions based on machine learning techniques including supervised learning, unsupervised learning and reinforcement learning. We focus on the machine le...

  12. BEBP: An Poisoning Method Against Machine Learning Based IDSs

    OpenAIRE

    Li, Pan; Liu, Qiang; Zhao, Wentao; Wang, Dongxu; Wang, Siqi

    2018-01-01

    In big data era, machine learning is one of fundamental techniques in intrusion detection systems (IDSs). However, practical IDSs generally update their decision module by feeding new data then retraining learning models in a periodical way. Hence, some attacks that comprise the data for training or testing classifiers significantly challenge the detecting capability of machine learning-based IDSs. Poisoning attack, which is one of the most recognized security threats towards machine learning...

  13. [Discovery-based teaching and learning strategies in health: problematization and problem-based learning].

    Science.gov (United States)

    Cyrino, Eliana Goldfarb; Toralles-Pereira, Maria Lúcia

    2004-01-01

    Considering the changes in teaching in the health field and the demand for new ways of dealing with knowledge in higher learning, the article discusses two innovative methodological approaches: problem-based learning (PBL) and problematization. Describing the two methods' theoretical roots, the article attempts to identify their main foundations. As distinct proposals, both contribute to a review of the teaching and learning process: problematization, focused on knowledge construction in the context of the formation of a critical awareness; PBL, focused on cognitive aspects in the construction of concepts and appropriation of basic mechanisms in science. Both problematization and PBL lead to breaks with the traditional way of teaching and learning, stimulating participatory management by actors in the experience and reorganization of the relationship between theory and practice. The critique of each proposal's possibilities and limits using the analysis of their theoretical and methodological foundations leads us to conclude that pedagogical experiences based on PBL and/or problematization can represent an innovative trend in the context of health education, fostering breaks and more sweeping changes.

  14. E-learning to supplement and synergise practice-based learning in the emergency department

    Institute of Scientific and Technical Information of China (English)

    Fatimah Lateef

    2012-01-01

    Practice-based learning involves on- the-job learning as well as learning ‘of-the job’ in its realistic setting. It gives trainees and interns the exposure to a diversity of encounters as well as an understanding of the different workplace models, strategies and capabilities. It is now very commonly utilized in teaching and training in medical disciplines. The whole process emphasizes active learning, with collaboration between learners and supervisors, for the eventual delivery of best clinical care to patients.

  15. Measuring the influence of Cooperative Learning and Project Based Learning on problem solvin skill.

    OpenAIRE

    García Martín, Javier; Pérez Martínez, Jorge Enrique

    2011-01-01

    The aim of this study is to evaluate the effects obtained after applying two active learning methodologies (cooperative learning and project based learning) to the achievement of the competence problem solving. This study was carried out at the Technical University of Madrid, where these methodologies were applied to two Operating Systems courses. The first hypothesis tested was whether the implementation of active learning methodologies favours the achievement of ?problem solving?. The secon...

  16. Applications of Task-Based Learning in TESOL

    Science.gov (United States)

    Shehadeh, Ali, Ed.; Coombe, Christine, Ed.

    2010-01-01

    Why are many teachers around the world moving toward task-based learning (TBL)? This shift is based on the strong belief that TBL facilitates second language acquisition and makes second language learning and teaching more principled and effective. Based on insights gained from using tasks as research tools, this volume shows how teachers can use…

  17. Designing and Evaluating Conative Game-Based Learning Scenarios

    DEFF Research Database (Denmark)

    Schønau-Fog, Henrik

    2014-01-01

    It is an essential prerequisite to design for motivation in game-based learning applications, tools and activities. However, how is it possible to design and evaluate motivational game-based learning scenarios in a systematic process-oriented manner based on conation and player engagement? While...... of ‘continuation desire’ such as interfacing with the scenario, exploration and socialising. This paper aims to combine the concepts of Player Engagement, Conation and Continuation Desire by focusing on the conative aspects which are the essential drivers for the desire to continue any learning activity......-based learning scenarios....

  18. The Effect of Learning Based on Technology Model and Assessment Technique toward Thermodynamic Learning Achievement

    Science.gov (United States)

    Makahinda, T.

    2018-02-01

    The purpose of this research is to find out the effect of learning model based on technology and assessment technique toward thermodynamic achievement by controlling students intelligence. This research is an experimental research. The sample is taken through cluster random sampling with the total respondent of 80 students. The result of the research shows that the result of learning of thermodynamics of students who taught the learning model of environmental utilization is higher than the learning result of student thermodynamics taught by simulation animation, after controlling student intelligence. There is influence of student interaction, and the subject between models of technology-based learning with assessment technique to student learning result of Thermodynamics, after controlling student intelligence. Based on the finding in the lecture then should be used a thermodynamic model of the learning environment with the use of project assessment technique.

  19. A versatile electrowetting-based digital microfluidic platform for quantitative homogeneous and heterogeneous bio-assays

    Science.gov (United States)

    Vergauwe, Nicolas; Witters, Daan; Ceyssens, Frederik; Vermeir, Steven; Verbruggen, Bert; Puers, Robert; Lammertyn, Jeroen

    2011-05-01

    Electrowetting-on-dielectric (EWOD) lab-on-a-chip systems have already proven their potential within a broad range of bio-assays. Nevertheless, research on the analytical performance of those systems is limited, yet crucial for a further breakthrough in the diagnostic field. Therefore, this paper presents the intrinsic possibilities of an EWOD lab-on-a-chip as a versatile platform for homogeneous and heterogeneous bio-assays with high analytical performance. Both droplet dispensing and splitting cause variations in droplet size, thereby directly influencing the assay's performance. The extent to which they influence the performance is assessed by a theoretical sensitivity analysis, which allows the definition of a basic framework for the reduction of droplet size variability. Taking advantage of the optimized droplet manipulations, both homogeneous and heterogeneous bio-assays are implemented in the EWOD lab-on-a-chip to demonstrate the analytical capabilities and versatility of the device. A fully on-chip enzymatic assay is realized with high analytical performance. It demonstrates the promising capabilities of an EWOD lab-on-a-chip in food-related and medical applications, such as nutritional and blood analyses. Further, a magnetic bio-assay for IgE detection using superparamagnetic nanoparticles is presented whereby the nanoparticles are used as solid carriers during the bio-assay. Crucial elements are the precise manipulation of the superparamagnetic nanoparticles with respect to dispensing and separation. Although the principle of using nano-carriers is demonstrated for protein detection, it can be easily extended to a broader range of bio-related applications like DNA sensing. In heterogeneous bio-assays the chip surface is actively involved during the execution of the bio-assay. Through immobilization of specific biological compounds like DNA, proteins and cells a reactive chip surface is realized, which enhances the bio-assay performance. To demonstrate

  20. Concept-Based Learning in Clinical Experiences: Bringing Theory to Clinical Education for Deep Learning.

    Science.gov (United States)

    Nielsen, Ann

    2016-07-01

    Concept-based learning is used increasingly in nursing education to support the organization, transfer, and retention of knowledge. Concept-based learning activities (CBLAs) have been used in clinical education to explore key aspects of the patient situation and principles of nursing care, without responsibility for total patient care. The nature of best practices in teaching and the resultant learning are not well understood. The purpose of this multiple-case study research was to explore and describe concept-based learning in the context of clinical education in inpatient settings. Four clinical groups (each a case) were observed while they used CBLAs in the clinical setting. Major findings include that concept-based learning fosters deep learning, connection of theory with practice, and clinical judgment. Strategies used to support learning, major teaching-learning foci, and preconditions for concept-based teaching and learning will be described. Concept-based learning is promising to support integration of theory with practice and clinical judgment through application experiences with patients. [J Nurs Educ. 2016;55(7):365-371.]. Copyright 2016, SLACK Incorporated.

  1. Towards heterogeneous robot team path planning: acquisition of multiple routes with a modified spline-based algorithm

    Directory of Open Access Journals (Sweden)

    Lavrenov Roman

    2017-01-01

    Full Text Available Our research focuses on operation of a heterogeneous robotic group that carries out point-to point navigation in GPS-denied dynamic environment, applying a combined local and global planning approach. In this paper, we introduce a homotopy-based high-level planner, which uses a modified splinebased path-planning algorithm. The algorithm utilizes Voronoi graph for global planning and a set of optimization criteria for local improvements of selected paths. The simulation was implemented in Matlab environment.

  2. Tumor Hypoxia: Causative Mechanisms, Microregional Heterogeneities, and the Role of Tissue-Based Hypoxia Markers.

    Science.gov (United States)

    Vaupel, Peter; Mayer, Arnulf

    Tumor hypoxia is a hallmark of solid malignant tumor growth, profoundly influences malignant progression and contributes to the development of therapeutic resistance. Pathogenesis of tumor hypoxia is multifactorial, with contributions from both acute and chronic factors. Spatial distribution of hypoxia within tumors is markedly heterogeneous and often changes over time, e.g., during a course of radiotherapy. Substantial changes in the oxygenation status can occur within the distance of a few cell layers, explaining the inability of currently used molecular imaging techniques to adequately assess this crucial trait. Due to the possible importance of tumor hypoxia for clinical decision-making, there is a great demand for molecular tools which may provide the necessary resolution down to the single cell level. Exogenous and endogenous markers of tumor hypoxia have been investigated for this purpose. Their potential use may be greatly enhanced by multiparametric in situ methods in experimental and human tumor tissue.

  3. Human Innate Lymphoid Cell Subsets Possess Tissue-Type Based Heterogeneity in Phenotype and Frequency

    DEFF Research Database (Denmark)

    Simoni, Yannick; Fehlings, Michael; Kloverpris, Henrik N.

    2017-01-01

    Animal models have highlighted the importance of innate lymphoid cells (ILCs) in multiple immune responses. However, technical limitations have hampered adequate characterization of ILCs in humans. Here, we used mass cytometry including a broad range of surface markers and transcription factors...... to accurately identify and profile ILCs across healthy and inflamed tissue types. High dimensional analysis allowed for clear phenotypic delineation of ILC2 and ILC3 subsets. We were not able to detect ILC1 cells in any of the tissues assessed, however, we identified intra-epithelial (ie)ILC1-like cells...... that represent a broader category of NK cells in mucosal and non-mucosal pathological tissues. In addition, we have revealed the expression of phenotypic molecules that have not been previously described for ILCs. Our analysis shows that human ILCs are highly heterogeneous cell types between individuals...

  4. Editorial - Keeping the Learning in Computer-Based Learning

    Directory of Open Access Journals (Sweden)

    William Kilbride

    2002-09-01

    Full Text Available Political rhetoric about knowledge economies and learning societies really ought to be an educationalist's dream. Add to that the revolutionary power of electronic media, and an insatiable hunger for archaeology among the public, archaeology teaching should be well placed to flourish. In England, the Department for Culture Media and Sport has just closed its call for interest in the multi-million pound Culture Online programme. The New Opportunities Fund has already spent fifty million pounds on digitisation alone, while the Heritage Lottery Fund is encouraging heritage agencies to distribute their data sets online. The JISC continues to expand its information environment, investing most recently in virtual learning environments. In Europe, the 6th Framework promises a single European Research Area, and grid technologies allow high quantities of data to empower an information society - supported by the millions of euros already invested in 'e-content'. All of these programmes, and many many more, provide openings for archaeologists to invest in training, teaching and learning. How can archaeology, in particular staff and students in our educational establishments, take best advantage of this information-rich, digitally-empowered learning society?

  5. Understanding Interorganizational Learning Based on Social Spaces and Learning Episodes

    Directory of Open Access Journals (Sweden)

    Anelise Rebelato Mozzato

    2014-07-01

    Full Text Available Different organizational settings have been gaining ground in the world economy, resulting in a proliferation of different forms of strategic alliances that translate into a growth in the number of organizations that have started to deal with interorganizational relationships with different actors. These circumstances reinforce Crossan, Lane, White and Djurfeldt (1995 and Crossan, Mauer and White (2011 in exploring what authors refer to as the fourth, interorganizational, level of learning. These authors, amongst others, suggest that the process of interorganizational learning (IOL warrants investigation, as its scope of analysis needs widening and deepening. Therefore, this theoretical essay is an attempt to understand IOL as a dynamic process found in interorganizational cooperative relationships that can take place in different structured and unstructured social spaces and that can generate learning episodes. According to this view, IOL is understood as part of an organizational learning continuum and is analyzed within the framework of practical rationality in an approach that is less cognitive and more social-behavioral.

  6. Interpretable Categorization of Heterogeneous Time Series Data

    Science.gov (United States)

    Lee, Ritchie; Kochenderfer, Mykel J.; Mengshoel, Ole J.; Silbermann, Joshua

    2017-01-01

    We analyze data from simulated aircraft encounters to validate and inform the development of a prototype aircraft collision avoidance system. The high-dimensional and heterogeneous time series dataset is analyzed to discover properties of near mid-air collisions (NMACs) and categorize the NMAC encounters. Domain experts use these properties to better organize and understand NMAC occurrences. Existing solutions either are not capable of handling high-dimensional and heterogeneous time series datasets or do not provide explanations that are interpretable by a domain expert. The latter is critical to the acceptance and deployment of safety-critical systems. To address this gap, we propose grammar-based decision trees along with a learning algorithm. Our approach extends decision trees with a grammar framework for classifying heterogeneous time series data. A context-free grammar is used to derive decision expressions that are interpretable, application-specific, and support heterogeneous data types. In addition to classification, we show how grammar-based decision trees can also be used for categorization, which is a combination of clustering and generating interpretable explanations for each cluster. We apply grammar-based decision trees to a simulated aircraft encounter dataset and evaluate the performance of four variants of our learning algorithm. The best algorithm is used to analyze and categorize near mid-air collisions in the aircraft encounter dataset. We describe each discovered category in detail and discuss its relevance to aircraft collision avoidance.

  7. Macroscopic heterogeneity of liver fat: an MR-based study in type-2 diabetic patients

    International Nuclear Information System (INIS)

    Capitan, Violaine; Lefevre, Pierre-Henri; Favelier, Sylvain; Loffroy, Romaric; Krause, Denis; Petit, Jean-Michel; Aho, Serge; Hillon, Patrick; Cercueil, Jean-Pierre; Guiu, Boris

    2012-01-01

    To assess the heterogeneity of liver fat deposition with MR of the liver in type-2 diabetic (T2D) patients. We enrolled 121 consecutive T2D patients. The reference standard was 3.0-T 1 H-MR spectroscopy. Hepatic steatosis was defined as liver fat content (LFC) ≥5.56 %. A triple-echo gradient-echo sequence corrected for T1 recovery and T2* decay was used to calculate LFC in left and right livers and hepatic segments. Analyses were performed using a linear mixed model. Fifty-nine (48.8 %) patients had liver steatosis, whereas 62 (51.2 %) did not. Steatosis was greater in the right than in the left liver (P < 0.0001) [mean difference: 1.32 % (range: 0.01-8.75 %)]. In seven patients (5.8 %), LFC was <5.56 % in one side of the liver, whereas it was ≥5.56 % in the other. Steatosis of the left and right liver was heterogeneous at the segmental level in both non-steatotic (P < 0.001 and P < 0.0001 respectively) and steatotic (P < 0.0001 and P = 0.0002 respectively) patients [mean maximum difference: 3.98 % (range: 0.74-19.32 %)]. In 23 patients (19 %), LFC was <5.56 % in one segment, whereas it was ≥5.56 % in at least one other. Overall, the mean segmental/lobar variability of steatosis is low. However, segmental variability can sometimes lead to a misdiagnosis. (orig.)

  8. Macroscopic heterogeneity of liver fat: an MR-based study in type-2 diabetic patients

    Energy Technology Data Exchange (ETDEWEB)

    Capitan, Violaine; Lefevre, Pierre-Henri; Favelier, Sylvain; Loffroy, Romaric; Krause, Denis [CHU (University Hospital), Department of Radiology, 14 rue Paul Gaffarel, BP 77908, Dijon (France); CHU (University Hospital), BP 77908, Dijon (France); Petit, Jean-Michel [CHU (University Hospital), Department of Endocrinology, Diabetology, and Metabolic Diseases, BP 77908, Dijon (France); CHU (University Hospital), BP 77908, Dijon (France); Aho, Serge [CHU (University Hospital), Department of Biostatistics and Medical Informatics, Dijon (France); CHU (University Hospital), BP 77908, Dijon (France); Hillon, Patrick [University of Burgundy, INSERM U866, BP 87900, Dijon (France); CHU (University Hospital), Department of Hepatology, BP 77908, Dijon (France); CHU (University Hospital), BP 77908, Dijon (France); Cercueil, Jean-Pierre; Guiu, Boris [CHU (University Hospital), Department of Radiology, 14 rue Paul Gaffarel, BP 77908, Dijon (France); University of Burgundy, INSERM U866, BP 87900, Dijon (France); CHU (University Hospital), BP 77908, Dijon (France)

    2012-10-15

    To assess the heterogeneity of liver fat deposition with MR of the liver in type-2 diabetic (T2D) patients. We enrolled 121 consecutive T2D patients. The reference standard was 3.0-T {sup 1}H-MR spectroscopy. Hepatic steatosis was defined as liver fat content (LFC) {>=}5.56 %. A triple-echo gradient-echo sequence corrected for T1 recovery and T2* decay was used to calculate LFC in left and right livers and hepatic segments. Analyses were performed using a linear mixed model. Fifty-nine (48.8 %) patients had liver steatosis, whereas 62 (51.2 %) did not. Steatosis was greater in the right than in the left liver (P < 0.0001) [mean difference: 1.32 % (range: 0.01-8.75 %)]. In seven patients (5.8 %), LFC was <5.56 % in one side of the liver, whereas it was {>=}5.56 % in the other. Steatosis of the left and right liver was heterogeneous at the segmental level in both non-steatotic (P < 0.001 and P < 0.0001 respectively) and steatotic (P < 0.0001 and P = 0.0002 respectively) patients [mean maximum difference: 3.98 % (range: 0.74-19.32 %)]. In 23 patients (19 %), LFC was <5.56 % in one segment, whereas it was {>=}5.56 % in at least one other. Overall, the mean segmental/lobar variability of steatosis is low. However, segmental variability can sometimes lead to a misdiagnosis. (orig.)

  9. The Effect of Animation in Multimedia Computer-Based Learning and Learning Style to the Learning Results

    Directory of Open Access Journals (Sweden)

    Muhammad RUSLI

    2017-10-01

    Full Text Available The effectiveness of a learning depends on four main elements, they are content, desired learning outcome, instructional method and the delivery media. The integration of those four elements can be manifested into a learning modul which is called multimedia learning or learning by using multimedia. In learning context by using computer-based multimedia, there are two main things that need to be noticed so that the learning process can run effectively: how the content is presented, and what the learner’s chosen way in accepting and processing the information into a meaningful knowledge. First it is related with the way to visualize the content and how people learn. The second one is related with the learning style of the learner. This research aims to investigate the effect of the type of visualization—static vs animated—on a multimedia computer-based learning, and learning styles—visual vs verbal, towards the students’ capability in applying the concepts, procedures, principles of Java programming. Visualization type act as independent variables, and learning styles of the students act as a moderator variable. Moreover, the instructional strategies followed the Component Display Theory of Merril, and the format of presentation of multimedia followed the Seven Principles of Multimedia Learning of Mayer and Moreno. Learning with the multimedia computer-based learning has been done in the classroom. The subject of this research was the student of STMIK-STIKOM Bali in odd semester 2016-2017 which followed the course of Java programming. The Design experiments used multivariate analysis of variance, MANOVA 2 x 2, with a large sample of 138 students in 4 classes. Based on the results of the analysis, it can be concluded that the animation in multimedia interactive learning gave a positive effect in improving students’ learning outcomes, particularly in the applying the concepts, procedures, and principles of Java programming. The

  10. System-on-Chip Environment: A SpecC-Based Framework for Heterogeneous MPSoC Design

    Directory of Open Access Journals (Sweden)

    Daniel D. Gajski

    2008-07-01

    Full Text Available The constantly growing complexity of embedded systems is a challenge that drives the development of novel design automation techniques. C-based system-level design addresses the complexity challenge by raising the level of abstraction and integrating the design processes for the heterogeneous system components. In this article, we present a comprehensive design framework, the system-on-chip environment (SCE which is based on the influential SpecC language and methodology. SCE implements a top-down system design flow based on a specify-explore-refine paradigm with support for heterogeneous target platforms consisting of custom hardware components, embedded software processors, dedicated IP blocks, and complex communication bus architectures. Starting from an abstract specification of the desired system, models at various levels of abstraction are automatically generated through successive step-wise refinement, resulting in a pin-and cycle-accurate system implementation. The seamless integration of automatic model generation, estimation, and verification tools enables rapid design space exploration and efficient MPSoC implementation. Using a large set of industrial-strength examples with a wide range of target architectures, our experimental results demonstrate the effectiveness of our framework and show significant productivity gains in design time.

  11. High-performance simulation-based algorithms for an alpine ski racer’s trajectory optimization in heterogeneous computer systems

    Directory of Open Access Journals (Sweden)

    Dębski Roman

    2014-09-01

    Full Text Available Effective, simulation-based trajectory optimization algorithms adapted to heterogeneous computers are studied with reference to the problem taken from alpine ski racing (the presented solution is probably the most general one published so far. The key idea behind these algorithms is to use a grid-based discretization scheme to transform the continuous optimization problem into a search problem over a specially constructed finite graph, and then to apply dynamic programming to find an approximation of the global solution. In the analyzed example it is the minimum-time ski line, represented as a piecewise-linear function (a method of elimination of unfeasible solutions is proposed. Serial and parallel versions of the basic optimization algorithm are presented in detail (pseudo-code, time and memory complexity. Possible extensions of the basic algorithm are also described. The implementation of these algorithms is based on OpenCL. The included experimental results show that contemporary heterogeneous computers can be treated as μ-HPC platforms-they offer high performance (the best speedup was equal to 128 while remaining energy and cost efficient (which is crucial in embedded systems, e.g., trajectory planners of autonomous robots. The presented algorithms can be applied to many trajectory optimization problems, including those having a black-box represented performance measure

  12. Student Perceptions of Team-based Learning vs Traditional Lecture-based Learning.

    Science.gov (United States)

    Frame, Tracy R; Cailor, Stephanie M; Gryka, Rebecca J; Chen, Aleda M; Kiersma, Mary E; Sheppard, Lorin

    2015-05-25

    To evaluate pharmacy student perceptions of team-based learning (TBL) vs traditional lecture-based learning formats. First professional year pharmacy students (N=111) at two universities used TBL in different courses during different semesters (fall vs spring). Students completed a 22-item team perceptions instrument before and after the fall semester. A 14-item teaching style preference instrument was completed at the end of the spring semester. Data were analyzed using Wilcoxon signed rank test and Mann-Whitney U test. Students who experienced TBL in the fall and went back to traditional format in the spring reported improved perceptions of teams and preferred TBL format over a traditional format more than students who experienced a traditional format followed by TBL. Students at both universities agreed that the TBL format assists with critical-thinking, problem-solving, and examination preparation. Students also agreed that teams should consist of individuals with different personalities and learning styles. When building teams, faculty members should consider ways to diversify teams by considering different views, perspectives, and strengths. Offering TBL early in the curriculum prior to traditional lecture-based formats is better received by students, as evidenced by anecdotal reports from students possibly because it allows students time to realize the benefits and assist them in building teamwork-related skills.

  13. Elucidating the impact of neurofibromatosis-1 germline mutations on neurofibromin function and dopamine-based learning.

    Science.gov (United States)

    Anastasaki, Corina; Woo, Albert S; Messiaen, Ludwine M; Gutmann, David H

    2015-06-15

    Neurofibromatosis type 1 (NF1) is a common autosomal dominant neurologic condition characterized by significant clinical heterogeneity, ranging from malignant cancers to cognitive deficits. Recent studies have begun to reveal rare genotype-phenotype correlations, suggesting that the specific germline NF1 gene mutation may be one factor underlying disease heterogeneity. The purpose of this study was to define the impact of the germline NF1 gene mutation on brain neurofibromin function relevant to learning. Herein, we employ human NF1-patient primary skin fibroblasts, induced pluripotent stem cells and derivative neural progenitor cells (NPCs) to demonstrate that NF1 germline mutations have dramatic effects on neurofibromin expression. Moreover, while all NF1-patient NPCs exhibit increased RAS activation and reduced cyclic AMP generation, there was a neurofibromin dose-dependent reduction in dopamine (DA) levels. Additionally, we leveraged two complementary Nf1 genetically-engineered mouse strains in which hippocampal-based learning and memory is DA-dependent to establish that neuronal DA levels and signaling as well as mouse spatial learning are controlled in an Nf1 gene dose-dependent manner. Collectively, this is the first demonstration that different germline NF1 gene mutations differentially dictate neurofibromin function in the brain. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  14. Characteristics of the Web-Based Learning Environment in Distance Education: Students' Perceptions of Their Learning Needs

    Science.gov (United States)

    Atan, Hanafi; Rahman, Zuraidah; Idrus, Rozhan M.

    2004-01-01

    A study was conducted regarding students' perceptions on the characteristics of the learning requirements in a web-based learning environment. Various aspects of on-line learning were studied including the general web-based support system for the students, the learning materials, instructional strategies of the learning materials and the learning…

  15. The quality and impact of computer supported collaborative learning (CSCL) in radiology case-based learning

    International Nuclear Information System (INIS)

    Kourdioukova, Elena V.; Verstraete, Koenraad L.; Valcke, Martin

    2011-01-01

    Objective: The aim of this research was to explore (1) clinical years students' perceptions about radiology case-based learning within a computer supported collaborative learning (CSCL) setting, (2) an analysis of the collaborative learning process, and (3) the learning impact of collaborative work on the radiology cases. Methods: The first part of this study focuses on a more detailed analysis of a survey study about CSCL based case-based learning, set up in the context of a broader radiology curriculum innovation. The second part centers on a qualitative and quantitative analysis of 52 online collaborative learning discussions from 5th year and nearly graduating medical students. The collaborative work was based on 26 radiology cases regarding musculoskeletal radiology. Results: The analysis of perceptions about collaborative learning on radiology cases reflects a rather neutral attitude that also does not differ significantly in students of different grade levels. Less advanced students are more positive about CSCL as compared to last year students. Outcome evaluation shows a significantly higher level of accuracy in identification of radiology key structures and in radiology diagnosis as well as in linking the radiological signs with available clinical information in nearly graduated students. No significant differences between different grade levels were found in accuracy of using medical terminology. Conclusion: Students appreciate computer supported collaborative learning settings when tackling radiology case-based learning. Scripted computer supported collaborative learning groups proved to be useful for both 5th and 7th year students in view of developing components of their radiology diagnostic approaches.

  16. Inquiry based learning: a student centered learning to develop mathematical habits of mind

    Science.gov (United States)

    Handayani, A. D.; Herman, T.; Fatimah, S.; Setyowidodo, I.; Katminingsih, Y.

    2018-05-01

    Inquiry based learning is learning that based on understanding constructivist mathematics learning. Learning based on constructivism is the Student centered learning. In constructivism, students are trained and guided to be able to construct their own knowledge on the basis of the initial knowledge that they have before. This paper explained that inquiry based learning can be used to developing student’s Mathematical habits of mind. There are sixteen criteria Mathematical Habits of mind, among which are diligent, able to manage time well, have metacognition ability, meticulous, etc. This research method is qualitative descriptive. The result of this research is that the instruments that have been developed to measure mathematical habits of mind are validated by the expert. The conclusion is the instrument of mathematical habits of mind are valid and it can be used to measure student’s mathematical habits of mind.

  17. Personalization and Contextualization of Learning Experiences based on Semantics

    Directory of Open Access Journals (Sweden)

    Nicola Capuano

    2014-04-01

    Full Text Available Context-aware e-learning is an educational model that foresees the selection of learning resources to make the e-learning content more relevant and suitable for the learner in his/her situation. The purpose of this paper is to demonstrate that an ontological approach can be used to define leaning contexts and to allow contextualizing learning experiences finding out relevant topics for each context. To do that, we defined a context model able to formally describe a learning context, an ontology-based model enabling the representation of a teaching domain (including context information and a methodology to generate personalized and context-aware learning experiences starting from them. Based on these theoretical components we improved an existing system for personalized e-learning with contextualisation features and experimented it with real users in two University courses. The results obtained from this experimentation have been compared with those achieved by similar systems.

  18. Learning based in projects to promote interdisciplinarity in Secondary School

    Directory of Open Access Journals (Sweden)

    Daniela Boff

    2016-02-01

    Full Text Available The project-based learning is an active learning strategy that helps break the paradigm of traditional teaching methods. The student is involved in the learning proposal that includes the PiBL, on which one is not passive and becomes the main actor in one's own teaching learning process. Within this learning strategy, the teacher becomes a mediator between theory and practice thus each different subject interact with one another in order to develop a topic that is mutual to all areas because the learning environment is naturally interdisciplinary. The idea of this kind of learning strategy was applied during a workshop that took place with primary and secondary schoolteachers in order to help them approach the strategy in the classroom, contributing with experiences and ideas towards the interdisciplinary based project.

  19. Learning services-based technological ecosystems

    OpenAIRE

    García-Peñalvo, Francisco J.; Hernández-García, Ángel; Conde, Miguel Á; Fidalgo-Blanco, Ángel; Sein-Echaluce, María L.; Alier, Marc; Llorens Largo, Faraón; Iglesias-Pradas, Santiago

    2015-01-01

    The gap between technology and learning methods has two important implications: on the one hand, we should not expect the integration of technological advances into teaching to be an easy task; and there is a danger that mature educational technologies and methods might not give an adequate answer to the demands and needs of society, underusing their transforming potential to improve learning processes. This study discusses the need for a new technological environment supporting learning serv...

  20. The Design and Analysis of Learning Effects for a Game-based Learning System

    OpenAIRE

    Wernhuar Tarng; Weichian Tsai

    2010-01-01

    The major purpose of this study is to use network and multimedia technologies to build a game-based learning system for junior high school students to apply in learning “World Geography" through the “role-playing" game approaches. This study first investigated the motivation and habits of junior high school students to use the Internet and online games, and then designed a game-based learning system according to situated and game-based learning theories. A teaching experiment was conducted to...