White, A. S.; Censlive, M.; Neilsen, D.
This paper investigates how control theory could be applied to learning processes in engineering education. The initial point for the analysis is White's Double Loop learning model of human automation control modified for the education process where a set of governing principals is chosen, probably by the course designer. After initial training the student decides unknowingly on a mental map or model. After observing how the real world is behaving, a strategy to achieve the governing variables is chosen and a set of actions chosen. This may not be a conscious operation, it maybe completely instinctive. These actions will cause some consequences but not until a certain time delay. The current model is compared with the work of Hollenbeck on goal setting, Nelson's model of self-regulation and that of Abdulwahed, Nagy and Blanchard at Loughborough who investigated control methods applied to the learning process.
White, A S; Censlive, M; Neilsen, D
This paper investigates how control theory could be applied to learning processes in engineering education. The initial point for the analysis is White's Double Loop learning model of human automation control modified for the education process where a set of governing principals is chosen, probably by the course designer. After initial training the student decides unknowingly on a mental map or model. After observing how the real world is behaving, a strategy to achieve the governing variables is chosen and a set of actions chosen. This may not be a conscious operation, it maybe completely instinctive. These actions will cause some consequences but not until a certain time delay. The current model is compared with the work of Hollenbeck on goal setting, Nelson's model of self-regulation and that of Abdulwahed, Nagy and Blanchard at Loughborough who investigated control methods applied to the learning process
Modjaev, A. D.; Leonova, N. M.
Recent years, a new scientific branch connected with the activities in social sphere management developing intensively and it is called "Social Cybernetics". In the framework of this scientific branch, theory and methods of management of social sphere are formed. Considerable attention is paid to the management, directly in real time. However, the decision of such management tasks is largely constrained by the lack of or insufficiently deep study of the relevant sections of the theory and methods of management. The article discusses the use of cybernetic principles in solving problems of control in social systems. Applying to educational activities a model of composite interrelated objects representing the behaviour of students at various stages of educational process is introduced. Statistical processing of experimental data obtained during the actual learning process is being done. If you increase the number of features used, additionally taking into account the degree and nature of variability of levels of current progress of students during various types of studies, new properties of students' grouping are discovered. L-clusters were identified, reflecting the behaviour of learners with similar characteristics during lectures. It was established that the characteristics of the clusters contain information about the dynamics of learners' behaviour, allowing them to be used in additional lessons. The ways of solving the problem of adaptive control based on the identified dynamic characteristics of the learners are planned.
Yen, John; Wang, Haojin; Daugherity, Walter C.
Fuzzy logic controllers have some often-cited advantages over conventional techniques such as PID control, including easier implementation, accommodation to natural language, and the ability to cover a wider range of operating conditions. One major obstacle that hinders the broader application of fuzzy logic controllers is the lack of a systematic way to develop and modify their rules; as a result the creation and modification of fuzzy rules often depends on trial and error or pure experimentation. One of the proposed approaches to address this issue is a self-learning fuzzy logic controller (SFLC) that uses reinforcement learning techniques to learn the desirability of states and to adjust the consequent part of its fuzzy control rules accordingly. Due to the different dynamics of the controlled processes, the performance of a self-learning fuzzy controller is highly contingent on its design. The design issue has not received sufficient attention. The issues related to the design of a SFLC for application to a petrochemical process are discussed, and its performance is compared with that of a PID and a self-tuning fuzzy logic controller.
449–456. MIT Press, 2006.  D. Koller and N. Friedman. Graphical Models. MIT Press, 2009.  J. Zico Kolter and Andrew Y. Ng. Regularization and...ICML ’09, pages 521–528, New York, NY, USA, 2009. ACM.  J. Zico Kolter and Andrew Y. Ng. Regularization and feature selection in least-squares...temporal differ- ence learning. In Proceedings of 27 th International Conference on Machine Learning, 2009.  J. Zico Z. Kolter . The Fixed Points of Off
Johnson, John A.; Stoner, Daphne L.; Larsen, Eric D.; Miller, Karen S.; Tolle, Charles R.
The present invention relates to process control where some of the controllable parameters are difficult or impossible to characterize. The present invention relates to process control in biotechnology of such systems, but not limited to. Additionally, the present invention relates to process control in biotechnology minerals processing. In the inventive method, an application of the present invention manipulates a minerals bioprocess to find local exterma (maxima or minima) for selected output variables/process goals by using a learning-based controller for bioprocess oxidation of minerals during hydrometallurgical processing. The learning-based controller operates with or without human supervision and works to find processor optima without previously defined optima due to the non-characterized nature of the process being manipulated.
This report provides a list of those findings particularly relevant to regulatory authorities that can be derived from the research and development activities in computerized process control conducted at the Halden Reactor Project. The report was prepared by a staff member of the US Nuclear Regulatory Commission working at Halden. It identifies those results that may be of use to regulatory organizations in three main areas: as support for new requirements, as part of regulatory evaluations of the acceptability of new methods and techniques, and in exploratory research and development of new approaches to improve operator performance. More than 200 findings arranged in nine major categories are presented. The findings were culled from Halden Reactor Project documents, which are listed in the report
Deisenroth, Marc Peter; Fox, Dieter; Rasmussen, Carl Edward
Autonomous learning has been a promising direction in control and robotics for more than a decade since data-driven learning allows to reduce the amount of engineering knowledge, which is otherwise required. However, autonomous reinforcement learning (RL) approaches typically require many interactions with the system to learn controllers, which is a practical limitation in real systems, such as robots, where many interactions can be impractical and time consuming. To address this problem, current learning approaches typically require task-specific knowledge in form of expert demonstrations, realistic simulators, pre-shaped policies, or specific knowledge about the underlying dynamics. In this paper, we follow a different approach and speed up learning by extracting more information from data. In particular, we learn a probabilistic, non-parametric Gaussian process transition model of the system. By explicitly incorporating model uncertainty into long-term planning and controller learning our approach reduces the effects of model errors, a key problem in model-based learning. Compared to state-of-the art RL our model-based policy search method achieves an unprecedented speed of learning. We demonstrate its applicability to autonomous learning in real robot and control tasks.
Statistical Process Control (SPC) charts are one of several tools used in quality control. Other tools include flow charts, histograms, cause and effect diagrams, check sheets, Pareto diagrams, graphs, and scatter diagrams. A control chart is simply a graph which indicates process variation over time. The purpose of drawing a control chart is to detect any changes in the process signalled by abnormal points or patterns on the graph. The Artificial Intelligence Support Center (AISC) of the Acquisition Logistics Division has developed a hybrid machine learning expert system prototype which automates the process of constructing and interpreting control charts.
Ludolph, Nicolas; Giese, Martin A; Ilg, Winfried
There is increasing evidence that sensorimotor learning under real-life conditions relies on a composition of several learning processes. Nevertheless, most studies examine learning behaviour in relation to one specific learning mechanism. In this study, we examined the interaction between reward-based skill acquisition and motor adaptation to changes of object dynamics. Thirty healthy subjects, split into two groups, acquired the skill of balancing a pole on a cart in virtual reality. In one group, we gradually increased the gravity, making the task easier in the beginning and more difficult towards the end. In the second group, subjects had to acquire the skill on the maximum, most difficult gravity level. We hypothesized that the gradual increase in gravity during skill acquisition supports learning despite the necessary adjustments to changes in cart-pole dynamics. We found that the gradual group benefits from the slow increment, although overall improvement was interrupted by the changes in gravity and resulting system dynamics, which caused short-term degradations in performance and timing of actions. In conclusion, our results deliver evidence for an interaction of reward-based skill acquisition and motor adaptation processes, which indicates the importance of both processes for the development of optimized skill acquisition schedules.
Monahan, Kevin M.
Simple microeconomic models that directly link yield learning to profitability in semiconductor manufacturing have been rare or non-existent. In this work, we review such a model and provide links to inspection capability and cost. Using a small number of input parameters, we explain current yield management practices in 200mm factories. The model is then used to extrapolate requirements for 300mm factories, including the impact of technology transitions to 130nm design rules and below. We show that the dramatic increase in value per wafer at the 300mm transition becomes a driver for increasing metrology and inspection capability and sampling. These analyses correlate well wtih actual factory data and often identify millions of dollars in potential cost savings. We demonstrate this using the example of grating-based overlay metrology for the 65nm node.
Endelt, Benny Ørtoft
Metal forming processes in general can be characterised as repetitive processes; this work will take advantage of this characteristic by developing an algorithm or control system which transfers process information from part to part, reducing the impact of repetitive uncertainties, e.g. a gradual...... changes in the material properties. The process is highly non-linear and the system plant is modelled using a non-linear finite element and the gain factors for the iterative learning controller is identified solving a non-linear optimal control problem. The optimal control problem is formulated as a non...
Full Text Available A new strategy for internal model control (IMC is proposed using a regression algorithm of quasilinear model with extreme learning machine (QL-ELM. Aimed at the chemical process with nonlinearity, the learning process of the internal model and inverse model is derived. The proposed QL-ELM is constructed as a linear ARX model with a complicated nonlinear coefficient. It shows some good approximation ability and fast convergence. The complicated coefficients are separated into two parts. The linear part is determined by recursive least square (RLS, while the nonlinear part is identified through extreme learning machine. The parameters of linear part and the output weights of ELM are estimated iteratively. The proposed internal model control is applied to CSTR process. The effectiveness and accuracy of the proposed method are extensively verified through numerical results.
Deschênes, Jean-Sebastien; Barka, Noureddine; Michaud, Mario; Paradis, Denis; Brousseau, Jean
A joint learning activity in process control is presented, in the context of a distance collaboration between engineering and technical-level students, in a similar fashion as current practices in the industry involving distance coordination and troubleshooting. The necessary infrastructure and the setup used are first detailed, followed by a…
Royer, Audrey S.; Rose, Minn L.; He, Bin
A brain-computer interface (BCI) can be used to accomplish a task without requiring motor output. Two major control strategies used by BCIs during task completion are process control and goal selection. In process control, the user exerts continuous control and independently executes the given task. In goal selection, the user communicates their goal to the BCI and then receives assistance executing the task. A previous study has shown that goal selection is more accurate and faster in use. An unanswered question is, which control strategy is easier to learn? This study directly compares goal selection and process control while learning to use a sensorimotor rhythm-based BCI. Twenty young healthy human subjects were randomly assigned either to a goal selection or a process control-based paradigm for eight sessions. At the end of the study, the best user from each paradigm completed two additional sessions using all paradigms randomly mixed. The results of this study were that goal selection required a shorter training period for increased speed, accuracy, and information transfer over process control. These results held for the best subjects as well as in the general subject population. The demonstrated characteristics of goal selection make it a promising option to increase the utility of BCIs intended for both disabled and able-bodied users.
Rana, Narender; Zhang, Yunlin; Wall, Donald; Dirahoui, Bachir; Bailey, Todd C.
Integrate circuit (IC) technology is going through multiple changes in terms of patterning techniques (multiple patterning, EUV and DSA), device architectures (FinFET, nanowire, graphene) and patterning scale (few nanometers). These changes require tight controls on processes and measurements to achieve the required device performance, and challenge the metrology and process control in terms of capability and quality. Multivariate data with complex nonlinear trends and correlations generally cannot be described well by mathematical or parametric models but can be relatively easily learned by computing machines and used to predict or extrapolate. This paper introduces the predictive metrology approach which has been applied to three different applications. Machine learning and predictive analytics have been leveraged to accurately predict dimensions of EUV resist patterns down to 18 nm half pitch leveraging resist shrinkage patterns. These patterns could not be directly and accurately measured due to metrology tool limitations. Machine learning has also been applied to predict the electrical performance early in the process pipeline for deep trench capacitance and metal line resistance. As the wafer goes through various processes its associated cost multiplies. It may take days to weeks to get the electrical performance readout. Predicting the electrical performance early on can be very valuable in enabling timely actionable decision such as rework, scrap, feedforward, feedback predicted information or information derived from prediction to improve or monitor processes. This paper provides a general overview of machine learning and advanced analytics application in the advanced semiconductor development and manufacturing.
Endelt, Benny Ørtoft; Volk, Wolfram
, there is a number of obstacles which need to be addressed before an industrial implementation is possible, e.g. the proposed control algorithms are often limited by the ability to sample process data with both sufficient accuracy and robustness - this lack of robust sampling technologies is one of the main barriers...
Boski, Marcin; Paszke, Wojciech
This paper deals with the problem of designing an iterative learning control algorithm for discrete linear systems using repetitive process stability theory. The resulting design produces a stabilizing output feedback controller in the time domain and a feedforward controller that guarantees monotonic convergence in the trial-to-trial domain. The results are also extended to limited frequency range design specification. New design procedure is introduced in terms of linear matrix inequality (LMI) representations, which guarantee the prescribed performances of ILC scheme. A simulation example is given to illustrate the theoretical developments.
Li, Jinna; Kiumarsi, Bahare; Chai, Tianyou; Lewis, Frank L; Fan, Jialu
Industrial flow lines are composed of unit processes operating on a fast time scale and performance measurements known as operational indices measured at a slower time scale. This paper presents a model-free optimal solution to a class of two time-scale industrial processes using off-policy reinforcement learning (RL). First, the lower-layer unit process control loop with a fast sampling period and the upper-layer operational index dynamics at a slow time scale are modeled. Second, a general optimal operational control problem is formulated to optimally prescribe the set-points for the unit industrial process. Then, a zero-sum game off-policy RL algorithm is developed to find the optimal set-points by using data measured in real-time. Finally, a simulation experiment is employed for an industrial flotation process to show the effectiveness of the proposed method.
Wang, Cong; Hill, David J
One of the amazing successes of biological systems is their ability to "learn by doing" and so adapt to their environment. In this paper, first, a deterministic learning mechanism is presented, by which an appropriately designed adaptive neural controller is capable of learning closed-loop system dynamics during tracking control to a periodic reference orbit. Among various neural network (NN) architectures, the localized radial basis function (RBF) network is employed. A property of persistence of excitation (PE) for RBF networks is established, and a partial PE condition of closed-loop signals, i.e., the PE condition of a regression subvector constructed out of the RBFs along a periodic state trajectory, is proven to be satisfied. Accurate NN approximation for closed-loop system dynamics is achieved in a local region along the periodic state trajectory, and a learning ability is implemented during a closed-loop feedback control process. Second, based on the deterministic learning mechanism, a neural learning control scheme is proposed which can effectively recall and reuse the learned knowledge to achieve closed-loop stability and improved control performance. The significance of this paper is that the presented deterministic learning mechanism and the neural learning control scheme provide elementary components toward the development of a biologically-plausible learning and control methodology. Simulation studies are included to demonstrate the effectiveness of the approach.
Ahn, Hyunsoo; Lee, Kwang Soon; Kim, Mansuk; Lee, Juhyun
Quadratic criterion-based iterative learning control (QILC) was applied to a numerical reactive batch distillation process, in which methacrylic anhydride (MAN) is produced through the reaction of methacrylic acid with acetic anhydride. The role of distillation is to shift the equilibrium conversion toward the direction of the product by removing acetic acid (AcH), a by-product of the reaction. Two temperatures at both ends of the column were controlled by individual control loops. A nonlinear PID controller manipulating the reflux ratio was employed to regulate the top temperature at the boiling point of AcH. A constrained QILC was used for the tracking of the reactor temperature. A time-varying reference trajectory for the reactor temperature that satisfies the target conversion and purity of MAN was obtained through repeated simulations and confirmation experiments in the pilot plant. The QILC achieved satisfactory tracking in several batch runs with gentle control movements, while the PID control as a substitute of the QILC in a comparative study exhibited unacceptable performance
Miklashevich N. V.
Full Text Available the article observes the main problems of organizing and carrying out the educational diagnosis in distance learning. Studying different approaches to monitoring showed that such control types as routine control and self-control are more efficient and effective. There is a difficulty of carrying out the control in distance learning: the need for accurate identification of the learner's personality. Despite existing technologies and recent developments in this area, the problem of preventing the test results from falsification is not fully resolved. According to the authors, the basic type of routine control when educating distantly remains the student obligatory attendance.
Full Text Available For a class of single-input single-output (SISO dual-rate sampling processes with disturbances and output delay, this paper presents a robust fault-tolerant iterative learning control algorithm based on output information. Firstly, the dual-rate sampling process with output delay is transformed into discrete system in state-space model form with slow sampling rate without time delay by using lifting technology; then output information based fault-tolerant iterative learning control scheme is designed and the control process is turned into an equivalent two-dimensional (2D repetitive process. Moreover, based on the repetitive process stability theory, the sufficient conditions for the stability of system and the design method of robust controller are given in terms of linear matrix inequalities (LMIs technique. Finally, the flow control simulations of two flow tanks in series demonstrate the feasibility and effectiveness of the proposed method.
Rahimi, Ebrahim; van den Berg, Jan; Veen, Wim
In recent educational literature, it has been observed that improving student's control has the potential of increasing his or her feeling of ownership, personal agency and activeness as means to maximize his or her educational achievement. While the main conceived goal for personal learning environments (PLEs) is to increase student's control by…
This paper analyses and compares the transnational learning processes in the employment field in the European Union and among the Nordic countries. Based theoretically on a social constructivist model of learning and methodologically on a questionnaire distributed to the relevant participants......, a number of hypotheses concerning transnational learning processes are tested. The paper closes with a number of suggestions regarding an optimal institutional setting for facilitating transnational learning processes.Key words: Transnational learning, Open Method of Coordination, Learning, Employment......, European Employment Strategy, European Union, Nordic countries....
Full Text Available Now software developed on the basis of artificial neural networks (ANN has been actively implemented in construction companies to support decision-making in organization and management of construction processes. ANN learning is the main stage of its development. A key question for supervised learning is how many number of training examples we need to approximate the true relationship between network inputs and output with the desired accuracy. Also designing of ANN architecture is related to learning problem known as “curse of dimensionality”. This problem is important for the study of construction process management because of the difficulty to get training data from construction sites. In previous studies the authors have designed a 4-layer feedforward ANN with a unit model of 12-5-4-1 to approximate estimation and prediction of roofing process. This paper presented the statistical learning side of created ANN with simple-error-minimization algorithm. The sample size to efficient training and the confidence interval of network outputs defined. In conclusion the authors predicted successful ANN learning in a large construction business company within a short space of time.
Wermter, Stefan; Löchel, Matthias
In this paper we describe a new approach for learning dialog act processing. In this approach we integrate a symbolic semantic segmentation parser with a learning dialog act network. In order to support the unforeseeable errors and variations of spoken language we have concentrated on robust data-driven learning. This approach already compares favorably with the statistical average plausibility method, produces a segmentation and dialog act assignment for all utterances in a robust manner,...
Full Text Available Shooting free throws plays an important role in basketball. The major problem in performing a correct free throw seems to be inappropriate training. Training is performed offline and it is often not that persistent. The aim of this paper is to consciously modify and control the free throw using biofeedback. Elbow and shoulder dynamics are calculated by an image processing technique equipped with a video image acquisition system. The proposed setup in this paper, named learning control system, is able to quantify and provide feedback of the above parameters in real time as audio signals. Therefore, it yielded to performing a correct learning and conscious control of shooting. Experimental results showed improvements in the free throw shooting style including shot pocket and locked position. The mean values of elbow and shoulder angles were controlled approximately on 89o and 26o, for shot pocket and also these angles were tuned approximately on 180o and 47o respectively for the locked position (closed to the desired pattern of the free throw based on valid FIBA references. Not only the mean values enhanced but also the standard deviations of these angles decreased meaningfully, which shows shooting style convergence and uniformity. Also, in training conditions, the average percentage of making successful free throws increased from about 64% to even 87% after using this setup and in competition conditions the average percentage of successful free throws enhanced about 20%, although using the learning control system may not be the only reason for these outcomes. The proposed system is easy to use, inexpensive, portable and real time applicable.
Pedersen, Simon; Løhndorf, Petar Durdevic; Yang, Zhenyu
, (ii) maximizing the production rate at the riser of an offshore production platform, by manipulating a topside choke valve through a learning switching model-free PID controller. The results show good steady-state performance, though a long settling time due to the unknown reference for no slugging...
Chua, Kao-Wei; Richler, Jennifer J; Gauthier, Isabel
Attention helps us focus on what is most relevant to our goals, and prior work has shown that aspects of attention can be learned. Learned inattention to parts can abolish holistic processing of faces, but it is unknown whether learned attention to parts is sufficient to cause a change from part-based to holistic processing with objects. We trained subjects to individuate nonface objects (Greebles) from 2 categories: Ploks and Glips. Diagnostic information was in complementary halves for the 2 categories. Holistic processing was then tested with Plok-Glip composites that combined the kind of part that was diagnostic or nondiagnostic during training. Exposure to Greeble parts resulted in general failures of selective attention for nondiagnostic composites, but face-like holistic processing was only observed for diagnostic composites. These results demonstrated a novel link between learned attentional control and the acquisition of holistic processing. (c) 2015 APA, all rights reserved).
Hall-Andersen, Lene Bjerg; Broberg, Ole
Purpose - The purpose of this paper is to shed light on the problematics of learning across knowledge boundaries in organizational settings. The paper specifically explores learning processes that emerge, when a new knowledge domain is introduced into an existing organizational practice with the ...
This paper details the development and implementation of a ''Process Control Program'' at Duke Power's three nuclear stations - Oconee, McGuire, and Catawba. Each station is required by Technical Specification to have a ''Process Control Program'' (PCP) to control all dewatering and/or solidification activities for radioactive wastes
Romine, Peter L.
This final report documents the development and installation of software and hardware for Robotic Welding Process Control. Primary emphasis is on serial communications between the CYRO 750 robotic welder, Heurikon minicomputer running Hunter & Ready VRTX, and an IBM PC/AT, for offline programming and control and closed-loop welding control. The requirements for completion of the implementation of the Rocketdyne weld tracking control are discussed. The procedure for downloading programs from the Intergraph, over the network, is discussed. Conclusions are made on the results of this task, and recommendations are made for efficient implementation of communications, weld process control development, and advanced process control procedures using the Heurikon.
Wang, Limin; Shen, Yiteng; Yu, Jingxian; Li, Ping; Zhang, Ridong; Gao, Furong
In order to cope with system disturbances in multi-phase batch processes with different dimensions, a hybrid robust control scheme of iterative learning control combined with feedback control is proposed in this paper. First, with a hybrid iterative learning control law designed by introducing the state error, the tracking error and the extended information, the multi-phase batch process is converted into a two-dimensional Fornasini-Marchesini (2D-FM) switched system with different dimensions. Second, a switching signal is designed using the average dwell-time method integrated with the related switching conditions to give sufficient conditions ensuring stable running for the system. Finally, the minimum running time of the subsystems and the control law gains are calculated by solving the linear matrix inequalities. Meanwhile, a compound 2D controller with robust performance is obtained, which includes a robust extended feedback control for ensuring the steady-state tracking error to converge rapidly. The application on an injection molding process displays the effectiveness and superiority of the proposed strategy.
Cheung, Kyung Mo; Cheung, Hwan
The process by which a student learns is extremely complicated. Whether he is simply learning facts, laws or formulae, changing his values or mastering a skill the way in which his brain functions is impossible to describe. The idea of learning domains is put forward not to explain in biological terms what happens in the brain but simply to attempt to break the system down into simpler units so that the learning process can be organized in an easier, more systematic way. In the most commonly used description of this process, the one described by BLOOM, this is BLOOM's Taxonomy. In addition to, I'd like to compare with the work of Lewis (Levels of Knowledge and Understanding). As a result, let us discuss about the most effective method in teaching in order to supply high-quality education
Sood, Akshay; Ghani, Khurshid R; Ahlawat, Rajesh; Modi, Pranjal; Abaza, Ronney; Jeong, Wooju; Sammon, Jesse D; Diaz, Mireya; Kher, Vijay; Menon, Mani; Bhandari, Mahendra
Traditional evaluation of the learning curve (LC) of an operation has been retrospective. Furthermore, LC analysis does not permit patient safety monitoring. To prospectively monitor patient safety during the learning phase of robotic kidney transplantation (RKT) and determine when it could be considered learned using the techniques of statistical process control (SPC). From January through May 2013, 41 patients with end-stage renal disease underwent RKT with regional hypothermia at one of two tertiary referral centers adopting RKT. Transplant recipients were classified into three groups based on the robotic training and kidney transplant experience of the surgeons: group 1, robot trained with limited kidney transplant experience (n=7); group 2, robot trained and kidney transplant experienced (n=20); and group 3, kidney transplant experienced with limited robot training (n=14). We employed prospective monitoring using SPC techniques, including cumulative summation (CUSUM) and Shewhart control charts, to perform LC analysis and patient safety monitoring, respectively. Outcomes assessed included post-transplant graft function and measures of surgical process (anastomotic and ischemic times). CUSUM and Shewhart control charts are time trend analytic techniques that allow comparative assessment of outcomes following a new intervention (RKT) relative to those achieved with established techniques (open kidney transplant; target value) in a prospective fashion. CUSUM analysis revealed an initial learning phase for group 3, whereas groups 1 and 2 had no to minimal learning time. The learning phase for group 3 varied depending on the parameter assessed. Shewhart control charts demonstrated no compromise in functional outcomes for groups 1 and 2. Graft function was compromised in one patient in group 3 (pcontrol chart analytic techniques. These methods allow determination of the duration of mentorship and identification of adverse events in a timely manner. A new operation
Full Text Available The e-learning educational process differs fundamentally from the teaching-learning process in the face-to-face teaching. A reason of differences is the nature of the distance education: the teacher cannot observe the student at work. Thus, the natural process of teaching, based on performing particular actions by teacher and students in relays, is disturbed. So, one has to consider the e-learning educational process as two separate sets of actions. The first, strongly regular, consists of teachers operations. The second, unorganized, contains the student activities. In the article some relations between the both structures are investigated. Moreover, some methods of arranging the set of students’ activities to better fit in with the educational goals are provided.
This year’s annual event promises to be both exciting and educational for those who wish to learn more about food processing. This column will provide a brief overview of the multitude of scientific sessions that reveal new research related to food processing. In addition to the symposia previewed h...
Knowlden, Adam P; Sharma, Manoj
Family-and-home-based interventions are an important vehicle for preventing childhood obesity. Systematic process evaluations have not been routinely conducted in assessment of these interventions. The purpose of this study was to plan and conduct a process evaluation of the Enabling Mothers to Prevent Pediatric Obesity Through Web-Based Learning and Reciprocal Determinism (EMPOWER) randomized control trial. The trial was composed of two web-based, mother-centered interventions for prevention of obesity in children between 4 and 6 years of age. Process evaluation used the components of program fidelity, dose delivered, dose received, context, reach, and recruitment. Categorical process evaluation data (program fidelity, dose delivered, dose exposure, and context) were assessed using Program Implementation Index (PII) values. Continuous process evaluation variables (dose satisfaction and recruitment) were assessed using ANOVA tests to evaluate mean differences between groups (experimental and control) and sessions (sessions 1 through 5). Process evaluation results found that both groups (experimental and control) were equivalent, and interventions were administered as planned. Analysis of web-based intervention process objectives requires tailoring of process evaluation models for online delivery. Dissemination of process evaluation results can advance best practices for implementing effective online health promotion programs. © 2014 Society for Public Health Education.
Gómez Sandra M.
Full Text Available A problem has been observed that creates difficulties in the normal and productive development of the English courses. Without any doubt, doing homework is very important in the learning process of a new language. Doubtless it affects the student’s active participation in the classroom and his relationship to partners and teachers. Because of this, a research project was done with the aim to finding out strategies to ensure students do homework and make it part of the learning process, erasing the image of homework as a punishment.
that part of the nursing education has been reduced in some countries as e.g. Denmark. The approach is presented through a model termed the 'Windmill of Learning Processes', which draws on empirical data from a qualitative investigation with an explorative and descriptive design, and on the theoretical......This article presents a new approach to student nurses' learning from their interaction with psychiatric patients. Using the approach can enable students and mentors to exploit students' learning opportunities, and help students to get the most out of their clinical placement in a time, where...... concepts of 'disjuncture', and 'everyday life activities'. 'Disjuncture' is defined as a situation in which there is disharmony between a person's experiences and the current situation. In such a situation there is potential for learning. My analysis of the empirical data led to the identification of a new...
Nunez, Heilyn Camacho; Cespedes, Paula
systems. It influences the business processes, and therefore a business practice should be redeveloped and redefined, furthermore the control over the ICT practice has become very important in the recent years. Some frameworks, methodologies and bodies of knowledge have been developed to support......, a small consulting company from Costa Rica, is using action learning to implement COBIT in the financial sector in Costa Rica....
National Aeronautics and Space Administration — The MPC (Model Process Control) language enables the capture, communication and preservation of a simulation instance, with sufficient detail that it can be...
Hayashi, Toshifumi; Kobayashi, Hiroshi.
A process control device comprises a memory device for memorizing a plant operation target, a plant state or a state of equipments related with each other as control data, a read-only memory device for storing programs, a plant instrumentation control device or other process control devices, an input/output device for performing input/output with an operator, and a processing device which conducts processing in accordance with the program and sends a control demand or a display demand to the input/output device. The program reads out control data relative to a predetermined operation target, compares and verify them with actual values to read out control data to be a practice premise condition which is further to be a practice premise condition if necessary, thereby automatically controlling the plant or requiring or displaying input. Practice presuming conditions for the operation target can be examined succesively in accordance with the program without constituting complicated logical figures and AND/OR graphs. (N.H.)
Gaussian processes (GPs) are natural generalisations of multivariate Gaussian random variables to infinite (countably or continuous) index sets. GPs have been applied in a large number of fields to a diverse range of ends, and very many deep theoretical analyses of various properties are available. This paper gives an introduction to Gaussian processes on a fairly elementary level with special emphasis on characteristics relevant in machine learning. It draws explicit connections to branches such as spline smoothing models and support vector machines in which similar ideas have been investigated. Gaussian process models are routinely used to solve hard machine learning problems. They are attractive because of their flexible non-parametric nature and computational simplicity. Treated within a Bayesian framework, very powerful statistical methods can be implemented which offer valid estimates of uncertainties in our predictions and generic model selection procedures cast as nonlinear optimization problems. Their main drawback of heavy computational scaling has recently been alleviated by the introduction of generic sparse approximations.13,78,31 The mathematical literature on GPs is large and often uses deep concepts which are not required to fully understand most machine learning applications. In this tutorial paper, we aim to present characteristics of GPs relevant to machine learning and to show up precise connections to other "kernel machines" popular in the community. Our focus is on a simple presentation, but references to more detailed sources are provided.
Crossley, Matthew J; Ashby, F Gregory
There is now abundant evidence that human learning and memory are governed by multiple systems. As a result, research is now turning to the next question of how these putative systems interact. For instance, how is overall control of behavior coordinated, and does learning occur independently within systems regardless of what system is in control? Behavioral, neuroimaging, and neuroscience data are somewhat mixed with respect to these questions. Human neuroimaging and animal lesion studies suggest independent learning and are mostly agnostic with respect to control. Human behavioral studies suggest active inhibition of behavioral output but have little to say regarding learning. The results of two perceptual category-learning experiments are described that strongly suggest that procedural learning does occur while the explicit system is in control of behavior and that this learning might be just as good as if the procedural system was controlling the response. These results are consistent with the idea that declarative memory systems inhibit the ability of the procedural system to access motor output systems but do not prevent procedural learning. (c) 2015 APA, all rights reserved).
Lutz, J.R.; Marsaudon, J.C.
The operation of the VIVITRON electrostatic accelerator designed since 1981 and under construction at the CRN since 1985 needs a dedicated process control set up. The study and design of this control system started in 1987. The electrostatic accelerators are rarely operated by a modern control system. So little knowledge is available in this field. The timing problems are generally weak but the Vivitron specific structure, with seven porticos in the tank and sophisticated beam handling in the terminal, imposes control equipment inside the tank under extreme severe conditions. Several steps are necessary to achieve the full size control system. Some tests in the MP used as a pilot machine supplied practical information about surrounding accelerator conditions inside the tank. They also provided better knowledge of the beam behavior, especially inside the accelerator tube
As sensor and computer technology continues to improve, it becomes a normal occurrence that we confront with high dimensional data sets. As in many areas of industrial statistics, this brings forth various challenges in statistical process control (SPC) and monitoring for which the aim...... is to identify “out-of-control” state of a process using control charts in order to reduce the excessive variation caused by so-called assignable causes. In practice, the most common method of monitoring multivariate data is through a statistic akin to the Hotelling’s T2. For high dimensional data with excessive...... amount of cross correlation, practitioners are often recommended to use latent structures methods such as Principal Component Analysis to summarize the data in only a few linear combinations of the original variables that capture most of the variation in the data. Applications of these control charts...
... Guidelines Asthma & Community Health Learn How to Control Asthma Language: English (US) Español (Spanish) Arabic Chinese Français ... Is Asthma Treated? Select a Language What Is Asthma? Asthma is a disease that affects your lungs. ...
Advanced life support systems have many interacting processes and limited resources. Controlling and optimizing advanced life support systems presents unique challenges. In particular, advanced life support systems are nonlinear coupled dynamical systems and it is difficult for humans to take all interactions into account to design an effective control strategy. In this project. we developed several reinforcement learning controllers that actively explore the space of possible control strategies, guided by rewards from a user specified long term objective function. We evaluated these controllers using a discrete event simulation of an advanced life support system. This simulation, called BioSim, designed by Nasa scientists David Kortenkamp and Scott Bell has multiple, interacting life support modules including crew, food production, air revitalization, water recovery, solid waste incineration and power. They are implemented in a consumer/producer relationship in which certain modules produce resources that are consumed by other modules. Stores hold resources between modules. Control of this simulation is via adjusting flows of resources between modules and into/out of stores. We developed adaptive algorithms that control the flow of resources in BioSim. Our learning algorithms discovered several ingenious strategies for maximizing mission length by controlling the air and water recycling systems as well as crop planting schedules. By exploiting non-linearities in the overall system dynamics, the learned controllers easily out- performed controllers written by human experts. In sum, we accomplished three goals. We (1) developed foundations for learning models of coupled dynamical systems by active exploration of the state space, (2) developed and tested algorithms that learn to efficiently control air and water recycling processes as well as crop scheduling in Biosim, and (3) developed an understanding of the role machine learning in designing control systems for
Moeller, Birte; Frings, Christian
A single encounter of a stimulus together with a response can result in a short-lived association between the stimulus and the response [sometimes called an event file, see Hommel, Müsseler, Aschersleben, & Prinz, (2001) Behavioral and Brain Sciences, 24, 910-926]. The repetition of stimulus-response pairings typically results in longer lasting learning effects indicating stimulus-response associations (e.g., Logan & Etherton, (1994) Journal of Experimental Psychology: Learning, Memory, and Cognition, 20, 1022-1050]. An important question is whether or not what has been described as stimulus-response binding in action control research is actually identical with an early stage of incidental learning (e.g., binding might be seen as single-trial learning). Here, we present evidence that short-lived binding effects can be distinguished from learning of longer lasting stimulus-response associations. In two experiments, participants always responded to centrally presented target letters that were flanked by response irrelevant distractor letters. Experiment 1 varied whether distractors flanked targets on the horizontal or vertical axis. Binding effects were larger for a horizontal than for a vertical distractor-target configuration, while stimulus configuration did not influence incidental learning of longer lasting stimulus-response associations. In Experiment 2, the duration of the interval between response n - 1 and presentation of display n (500 ms vs. 2000 ms) had opposing influences on binding and learning effects. Both experiments indicate that modulating factors influence stimulus-response binding and incidental learning effects in different ways. We conclude that distinct underlying processes should be assumed for binding and incidental learning effects.
Conde, Miguel Ángel; García-Peñalvo, Francisco José; Casany, Marià José; Alier Forment, Marc
Learning processes are changing related to technological and sociological evolution, taking this in to account, a new learning strategy must be considered. Specifically what is needed is to give an effective step towards the eLearning 2.0 environments consolidation. This must imply the fusion of the advantages of the traditional LMS (Learning Management System) - more formative program control and planning oriented - with the social learning and the flexibility of the web 2.0 educative applications.
Biggs, John B.
This manual describes the theory behind the Learning Process Questionnaire (LPQ) used in Australia and defines what the subscale and scale scores mean. The LPQ is a 36-item self-report questionnaire that yields scores on three basic motives for learning and three learning strategies, and on the approaches to learning that are formed by these…
Quinn, A.; Kárný, Miroslav
Roč. 21, č. 10 (2007), s. 827-855 ISSN 0890-6327 R&D Projects: GA AV ČR 1ET100750401 Grant - others:MŠk ČR(CZ) 2C06001 Program:2C Institutional research plan: CEZ:AV0Z10750506 Keywords : Nestacionární procesy * učení * Dirichletovy procesy * zapomínání Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.776, year: 2007 http://library.utia.cas.cz/separaty/2007/as/karny- learning for nonstationary dirichlet processes.pdf
This research set out to explore how a group of nine educators from a Catholic Church school in Malta, who have attended the Let Me Learn professional Learning process (LMLpLp), experienced personal and professional transformation. This study investigates those factors influencing participants in their transformative learning journey. It also explores the dynamics of transformative learning and whether individual transformation affects the school’s transformative learning experience. More spe...
When NASA started plarning for manned space travel in 1959, the myriad challenges of sustaining life in space included a seemingly mundane but vitally important problem: How and what do you feed an astronaut? There were two main concerns: preventing food crumbs from contaminating the spacecraft's atmosphere or floating into sensitive instruments, and ensuring complete freedom from potentially catastrophic disease-producing bacteria, viruses, and toxins. To solve these concerns, NASA enlisted the help of the Pillsbury Company. Pillsbury quickly solved the first problem by coating bite-size foods to prevent crumbling. They developed the hazard analysis and critical control point (HACCP) concept to ensure against bacterial contamination. Hazard analysis is a systematic study of product, its ingredients, processing conditions, handling, storage, packing, distribution, and directions for consumer use to identify sensitive areas that might prove hazardous. Hazard analysis provides a basis for blueprinting the Critical Control Points (CCPs) to be monitored. CCPs are points in the chain from raw materials to the finished product where loss of control could result in unacceptable food safety risks. In early 1970, Pillsbury plants were following HACCP in production of food for Earthbound consumers. Pillsbury's subsequent training courses for Food and Drug Administration (FDA) personnel led to the incorporation of HACCP in the FDA's Low Acid Canned Foods Regulations, set down in the mid-1970s to ensure the safety of all canned food products in the U.S.
Local learning processes are a vital part of any dynamic assimilation of transferred technology. The paper raises the question about the interaction between the training paradigms, which transnational corporations introduce in their subsidiaries in Malaysia and the specific basis for learning...... of Malaysian labour. Experiences from Malaysian industry indicate that local learning processes are shaped, among other things, by the concept of knowledge in a particular training programme, labour market structures, and learning cultures....
Arndt, W [ed.
Papers from the workshop Process Control by Microprocessors being organized by the Karlsruhe Nuclear Research Center, Project PDV, together with the VDI/VDE-Gesellschaft fuer Mess- und Regelungstechnik are presented. The workshop was held on December 13 and 14, 1978 at the facilities of the Nuclear Research Center. The papers are arranged according to the topics of the workshop; one chapter deals with today's state of the art of microprocessor hardware and software technology; 5 chapters are dedicated to applications. The report also contains papers which will not be presented at the workshop. Both the workshop and the report are expected to improve and distribute the know-how about this modern technology.
Then we describe how the method of regularization is used to control complexity in learning. We discuss two examples of regularization, one in which the function space used is ﬁnite dimensional, and another in which it is a reproducing kernel Hilbert space. Our exposition follows the formulation of Cucker and Smale.
Evermann, Joerg; Rehse, Jana-Rebecca; Fettke, Peter
Predicting business process behaviour is an important aspect of business process management. Motivated by research in natural language processing, this paper describes an application of deep learning with recurrent neural networks to the problem of predicting the next event in a business process. This is both a novel method in process prediction, which has largely relied on explicit process models, and also a novel application of deep learning methods. The approach is evaluated on two real da...
Riether, Carsten; Doenlen, Raphaël; Pacheco-López, Gustavo; Niemi, Maj-Britt; Engler, Andrea; Engler, Harald; Schedlowski, Manfred
During the last 30 years of psychoneuroimmunology research the intense bi-directional communication between the central nervous system (CNS) and the immune system has been demonstrated in studies on the interaction between the nervous-endocrine-immune systems. One of the most intriguing examples of such interaction is the capability of the CNS to associate an immune status with specific environmental stimuli. In this review, we systematically summarize experimental evidence demonstrating the behavioural conditioning of peripheral immune functions. In particular, we focus on the mechanisms underlying the behavioural conditioning process and provide a theoretical framework that indicates the potential feasibility of behaviourally conditioned immune changes in clinical situations.
Vladimir D. Shadrikov
Full Text Available A system genetics approach has been employed to study students’ mental development.Ability development is considered in terms of mastering of intellectualoperations. The study endeavors to identify the components of certain abilitiesconsciously acquired by a student in the process of learning. The study was arrangedin two directions: the teaching of students to master intellectual operationsand use them in their work with training materials, and psychological testingof control and experimental student groups before and after training tests todiagnose the level of intellectual development. The study involved teachers andstudents of primary and secondary school.
Sánchez, Luis E.; Mitchell, Ross
This paper explores how project developers and their consultants, government regulators and stakeholders can learn from the impact assessment (IA) process, thus potentially improving its effectiveness and enhancing project sustainability. Despite the benefits that learning can bring to an organization, failure to learn appears commonplace both within the IA process and, once approved, subsequent industrial development. To nurture organizational learning through IA, enabling structures that foster information sharing and interpretation and enhance organizational memory are needed. In this paper learning outcomes are grouped into three categories: acquisition of knowledge and skills, developing new behaviors and developing sustainability-oriented norms and values. Means to achieve such outcomes include education and training, experiential learning, learning through public participation (social learning) and a ‘learning organization approach’. Societal expectations increasingly demand not only projects that ‘pass’ the review criteria of regulators, financiers and the community, but IA processes capable of delivering sustainable outcomes that include learning and sharing of knowledge. It is proposed that learning be treated as a purposeful – not as an accidental – outcome of IA, and facilitated by adopting a ‘learning organization approach’ coupled with best practice such as early stakeholder engagement. - Highlights: • Proponents are challenged to develop projects that deliver sustainable outcomes. • Passing the test of government approval may be insufficient to obtain a social license. • Learning by all stakeholders is vital to meet these challenges. • Learning outcomes have to go beyond instrumental learning to reach new behaviors, norms and values. • A “learning organization approach” can promote mutual learning and improve project design.
Sánchez, Luis E., E-mail: email@example.com [Escola Politécnica, University of São Paulo, Av. Prof. Mello Moraes, 2373, 05508-900 São Paulo (Brazil); Mitchell, Ross, E-mail: firstname.lastname@example.org [Shell International Exploration & Production BV (Netherlands)
This paper explores how project developers and their consultants, government regulators and stakeholders can learn from the impact assessment (IA) process, thus potentially improving its effectiveness and enhancing project sustainability. Despite the benefits that learning can bring to an organization, failure to learn appears commonplace both within the IA process and, once approved, subsequent industrial development. To nurture organizational learning through IA, enabling structures that foster information sharing and interpretation and enhance organizational memory are needed. In this paper learning outcomes are grouped into three categories: acquisition of knowledge and skills, developing new behaviors and developing sustainability-oriented norms and values. Means to achieve such outcomes include education and training, experiential learning, learning through public participation (social learning) and a ‘learning organization approach’. Societal expectations increasingly demand not only projects that ‘pass’ the review criteria of regulators, financiers and the community, but IA processes capable of delivering sustainable outcomes that include learning and sharing of knowledge. It is proposed that learning be treated as a purposeful – not as an accidental – outcome of IA, and facilitated by adopting a ‘learning organization approach’ coupled with best practice such as early stakeholder engagement. - Highlights: • Proponents are challenged to develop projects that deliver sustainable outcomes. • Passing the test of government approval may be insufficient to obtain a social license. • Learning by all stakeholders is vital to meet these challenges. • Learning outcomes have to go beyond instrumental learning to reach new behaviors, norms and values. • A “learning organization approach” can promote mutual learning and improve project design.
Puranam, Phanish; Swamy, M.
Coupled learning processes, in which specialists from different domains learn how to make interdependent choices among alternatives, are common in organizations. We explore the role played by initial representations held by the learners in coupled learning processes using a formal agent-based model....... We find that initial representations have important consequences for the success of the coupled learning process, particularly when communication is constrained and individual rates of learning are high. Under these conditions, initial representations that generate incorrect beliefs can outperform...... one that does not discriminate among alternatives, or even a mix of correct and incorrect representations among the learners. We draw implications for the design of coupled learning processes in organizations. © 2016 INFORMS....
Weil, Richard; Apostolakis, George
This paper presents an organizational learning work process for use at nuclear power plants or other high-risk industries. Relying on insights gained from surveying organizational learning activities at nuclear power plants, the proposed work process synthesizes distributed learning activities and improves upon existing organizational learning processes. A root-cause analysis that targets organizational factors is presented. Additionally, a more accurate and objective methodology for prioritizing operating experience is presented. This methodology was applied to a case study during a workshop with utility personnel held at MIT. (author)
Van Meeuwen, Ludo; Jarodzka, Halszka; Brand-Gruwel, Saskia; Van Merriënboer, Jeroen; De Bock, Jeano; Kirschner, Paul A.
Van Meeuwen, L., Jarodzka, H., Brand-Gruwel, S., Van Merriënboer, J. J. G., De Bock, J. J. P. R., & Kirschner, P. A. (2010, August). Processes mediating expertise in air traffic control. Meeting of the EARLI SIG6/7 Instructional Design and Learning and Instruction with Computers, Ulm, Germany.
Full Text Available A new method with a two-layer hierarchy is presented based on a neural proportional-integral-derivative (PID iterative learning method over the communication network for the closed-loop automatic tuning of a PID controller. It can enhance the performance of the well-known simple PID feedback control loop in the local field when real networked process control applied to systems with uncertain factors, such as external disturbance or randomly delayed measurements. The proposed PID iterative learning method is implemented by backpropagation neural networks whose weights are updated via minimizing tracking error entropy of closed-loop systems. The convergence in the mean square sense is analysed for closed-loop networked control systems. To demonstrate the potential applications of the proposed strategies, a pressure-tank experiment is provided to show the usefulness and effectiveness of the proposed design method in network process control systems.
Chen Maoyin; Shang Yun; Zhou Donghua
Combining a shift method and the repetitive learning strategy, a repetitive learning controller is proposed to stabilize unstable periodic orbits (UPOs) within chaotic attractors in the sense of least mean square. If nonlinear parts in chaotic systems satisfy Lipschitz condition, the proposed controller can be simplified into a simple proportional repetitive learning controller
Modern Schools, 1976
The dramatic use of bold colors in the interior design of the Greenhill Middle School in Dallas, Texas, is an example of how a learning environment can stimulate student interest and enthusiasm. (Author/MLF)
Heckendoin, F.M. II
The Defense Waste Processing Facility (DWPF) for waste vitrification at the Savannah River Plant (SRP) is in the final design stage. Instrumentation to provide the parameter sensing required to assure the quality of the two-foot-diameter, ten-foot-high waste canister is in the final stage of development. All step of the process and instrumentation are now operating as nearly full-scale prototypes at SRP. Quality will be maintained by assuring that only the intended material enters the canisters, and by sensing the resultant condition of the filled canisters. Primary emphasis will be on instrumentation of the process
Marden, Jason R.
In distributed architecture control problems, there is a collection of interconnected decision-making components that seek to realize desirable collective behaviors through local interactions and by processing local information. Applications range from autonomous vehicles to energy to transportation. One approach to control of such distributed architectures is to view the components as players in a game. In this approach, two design considerations are the components’ incentives and the rules that dictate how components react to the decisions of other components. In game-theoretic language, the incentives are defined through utility functions, and the reaction rules are online learning dynamics. This chapter presents an overview of this approach, covering basic concepts in game theory, special game classes, measures of distributed efficiency, utility design, and online learning rules, all with the interpretation of using game theory as a prescriptive paradigm for distributed control design.
Mansvelder-Longayroux, D.D.; Beijaard, D.; Verloop, N.; Vermunt, J.D.
In this study, we aimed to develop a framework that could be used to describe the value of the learning portfolio for the learning process of individual student teachers. Retrospective interviews with 21 student teachers were used, as were their portfolio-evaluation reports on their experiences of
Mansvelder-Longayroux, Desiree D.; Beijaard, Douwe; Verloop, Nico; Vermunt, Jan D.
In this study, we aimed to develop a framework that could be used to describe the value of the learning portfolio for the learning process of individual student teachers. Retrospective interviews with 21 student teachers were used, as were their portfolio-evaluation reports on their experiences Of
Holm-Nielsen, Jens Bo; Oleskowicz-Popiel, Piotr
Efficient monitoring and control of anaerobic digestion (AD) processes are necessary in order to enhance biogas plant performance. The aim of monitoring and controlling the biological processes is to stabilise and optimise the production of biogas. The principles of process analytical technology...
Full Text Available The Business School at the Bern University of Applied Sciences is offering a new MScBA degree program in business development. The paper presents a practical report about the action learning approach in the course 'Business Analysis and Design'. Our problem-based approach is more than simply 'learning by doing'. In a world of increasing complexity, taking action alone will not result in a learning effect per se. What is imperative is to structure and facilitate the learning process on different levels: individual construction of mental models; understanding needs and developing adequate solutions; critical reflection of methods and processes. Reflective practice, where individuals are learning from their own professional experiences rather than from formal teaching or knowledge transfer, may be the most important source for lifelong learning.
de Vries, Theodorus J.A.; Velthuis, W.J.R.; Idema, L.J.
For motion control, learning feedforward controllers (LFFCs) should be applied when accurate process modelling is difficult. When controlling such processes with LFFCs in the form of multidimensional B-spline networks, large network sizes and a poor generalising ability may result, known as the
Arnold, Kathleen M; Umanath, Sharda; Thio, Kara; Reilly, Walter B; McDaniel, Mark A; Marsh, Elizabeth J
Writing is often used as a tool for learning. However, empirical support for the benefits of writing-to-learn is mixed, likely because the literature conflates diverse activities (e.g., summaries, term papers) under the single umbrella of writing-to-learn. Following recent trends in the writing-to-learn literature, the authors focus on the underlying cognitive processes. They draw on the largely independent writing-to-learn and cognitive psychology learning literatures to identify important cognitive processes. The current experiment examines learning from 3 writing tasks (and 1 nonwriting control), with an emphasis on whether or not the tasks engaged retrieval. Tasks that engaged retrieval (essay writing and free recall) led to better final test performance than those that did not (note taking and highlighting). Individual differences in structure building (the ability to construct mental representations of narratives; Gernsbacher, Varner, & Faust, 1990) modified this effect; skilled structure builders benefited more from essay writing and free recall than did less skilled structure builders. Further, more essay-like responses led to better performance, implicating the importance of additional cognitive processes such as reorganization and elaboration. The results highlight how both task instructions and individual differences affect the cognitive processes involved when writing-to-learn, with consequences for the effectiveness of the learning strategy. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Tsukada, Akira; Suzuki, Katsuo; Fujii, Yoshio; Shinohara, Yoshikuni
In this report a problem is studied to construct a fuzzy controller for a mobile robot to move autonomously along a given reference direction curve, for which control rules are generated and acquired through an adaptive learning process. An adaptive learning fuzzy controller has been developed for a mobile robot. Good properties of the controller are shown through the travelling experiments of the mobile robot. (author)
Abbas, A.; Alhammadi, H. Y.; Romagnoli, J. A.
In this paper, we discuss our approach in teaching the final-year course Process Systems Engineering. Students are given ownership of the course by transferring to them the responsibility of learning. A project-based group environment stimulates learning while solving a real engineering problem. We discuss postgraduate student involvement and how…
Ceri, Stefano; Matera, Maristella; Raffio, Alessandro; Spoelstra, Howard
Ceri, S., Matera, M., Raffio, A. & Spoelstra, H. (2007). Flexible Processes in Project-Centred Learning. In E. Duval, R. Klamma, and M. Wolpers (Eds.), European Conference on Technology Enhanced Learning, Lecture Notes in Computer Science, Vol. 4753, pp. 463-468. Berlin Heidelberg: Springer-Verlag
Zhang, Suyi; Mano, Hiroaki; Ganesh, Gowrishankar; Robbins, Trevor; Seymour, Ben
Pavlovian conditioning underlies many aspects of pain behavior, including fear and threat detection , escape and avoidance learning , and endogenous analgesia . Although a central role for the amygdala is well established , both human and animal studies implicate other brain regions in learning, notably ventral striatum and cerebellum . It remains unclear whether these regions make different contributions to a single aversive learning process or represent independent learning mechanisms that interact to generate the expression of pain-related behavior. We designed a human parallel aversive conditioning paradigm in which different Pavlovian visual cues probabilistically predicted thermal pain primarily to either the left or right arm and studied the acquisition of conditioned Pavlovian responses using combined physiological recordings and fMRI. Using computational modeling based on reinforcement learning theory, we found that conditioning involves two distinct types of learning process. First, a non-specific "preparatory" system learns aversive facial expressions and autonomic responses such as skin conductance. The associated learning signals-the learned associability and prediction error-were correlated with fMRI brain responses in amygdala-striatal regions, corresponding to the classic aversive (fear) learning circuit. Second, a specific lateralized system learns "consummatory" limb-withdrawal responses, detectable with electromyography of the arm to which pain is predicted. Its related learned associability was correlated with responses in ipsilateral cerebellar cortex, suggesting a novel computational role for the cerebellum in pain. In conclusion, our results show that the overall phenotype of conditioned pain behavior depends on two dissociable reinforcement learning circuits. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
Mod Ali, N.
Complete text of publication follows. Accurate radiation dosimetry can provide quality assurance in radiation processing. Considerable relevant experiences in dosimetry by the SSDL-MINT has necessitate the development of methods making measurement at gamma plant traceable to the national standard. It involves the establishment of proper calibration procedure and selection of appropriate transfer system/technique to assure adequate traceability to a primary radiation standard. The effort forms the basis for irradiation process control, the legal approval of the process by the public health authorities (medical product sterilization and food preservation) and the safety and acceptance of the product
Zhang, Suyi; Mano, Hiroaki; Lee, Michael; Yoshida, Wako; Kawato, Mitsuo; Robbins, Trevor W; Seymour, Ben
Tonic pain after injury characterises a behavioural state that prioritises recovery. Although generally suppressing cognition and attention, tonic pain needs to allow effective relief learning to reduce the cause of the pain. Here, we describe a central learning circuit that supports learning of relief and concurrently suppresses the level of ongoing pain. We used computational modelling of behavioural, physiological and neuroimaging data in two experiments in which subjects learned to terminate tonic pain in static and dynamic escape-learning paradigms. In both studies, we show that active relief-seeking involves a reinforcement learning process manifest by error signals observed in the dorsal putamen. Critically, this system uses an uncertainty ('associability') signal detected in pregenual anterior cingulate cortex that both controls the relief learning rate, and endogenously and parametrically modulates the level of tonic pain. The results define a self-organising learning circuit that reduces ongoing pain when learning about potential relief. © 2018, Zhang et al.
Mano, Hiroaki; Lee, Michael; Yoshida, Wako; Kawato, Mitsuo; Robbins, Trevor W
Tonic pain after injury characterises a behavioural state that prioritises recovery. Although generally suppressing cognition and attention, tonic pain needs to allow effective relief learning to reduce the cause of the pain. Here, we describe a central learning circuit that supports learning of relief and concurrently suppresses the level of ongoing pain. We used computational modelling of behavioural, physiological and neuroimaging data in two experiments in which subjects learned to terminate tonic pain in static and dynamic escape-learning paradigms. In both studies, we show that active relief-seeking involves a reinforcement learning process manifest by error signals observed in the dorsal putamen. Critically, this system uses an uncertainty (‘associability’) signal detected in pregenual anterior cingulate cortex that both controls the relief learning rate, and endogenously and parametrically modulates the level of tonic pain. The results define a self-organising learning circuit that reduces ongoing pain when learning about potential relief. PMID:29482716
Full Text Available The utilization of smartphones is increasingly developing among the students. It causes various modifications of attitude and behavior, that media literacy nowadays becomes highly important. Therefore, media literacy shall become the priority for related parties specifically parents and teachers. In addition to helping to find information and to conduct fast communication, smartphone is also functions in formal learning process among the students.The aim of this research is to acknowledge the utilization of smartphones in formal learning process. This study uses qualitative descriptive method which makes serious efforts in describing and depicting utilization of smartphones in learning process among Junior High School students in Bandung. The research result shows that smartphones may function as a device to channel messages and to stimulate the mind, feeling and desire of the students which may encourage learning process in them and to give positive values and to bridge media literacy among the students.
Repperger, D. W.; Goodyear, C.
An active controller was used to help train naive subjects involved in a compensatory tracking task. The controller is called active in this context because it moves the subject's hand in a direction to improve tracking. It is of interest here to question whether the active controller helps the subject to learn a task more rapidly than the passive controller. Six subjects, inexperienced to compensatory tracking, were run to asymptote root mean square error tracking levels with an active controller or a passive controller. The time required to learn the task was defined several different ways. The results of the different measures of learning were examined across pools of subjects and across controllers using statistical tests. The comparison between the active controller and the passive controller as to their ability to accelerate the learning process as well as reduce levels of asymptotic tracking error is reported here.
Mao, Hua; Chen, Yingke; Jaeger, Manfred
. The proposed learning algorithm is adapted from algorithms for learning deterministic probabilistic finite automata, and extended to include both probabilistic and nondeterministic transitions. The algorithm is empirically analyzed and evaluated by learning system models of slot machines. The evaluation......Constructing an accurate system model for formal model verification can be both resource demanding and time-consuming. To alleviate this shortcoming, algorithms have been proposed for automatically learning system models based on observed system behaviors. In this paper we extend the algorithm...... on learning probabilistic automata to reactive systems, where the observed system behavior is in the form of alternating sequences of inputs and outputs. We propose an algorithm for automatically learning a deterministic labeled Markov decision process model from the observed behavior of a reactive system...
Gebelin, B.; Couture, R.
This process and apparatus is characterized by 2 methods, for examination of cluster of nuclear control rods. Foucault current analyzer which examines fraction by fraction all the control rods. This examination is made by rotation of the cluster. Doubtful rods are then analysed by ultrasonic probe [fr
The presence of outliers and contaminations in the output of the process highly affects the performance of the design structures of commonly used control charts and hence makes them of less practical use. One of the solutions to deal with this problem is to use control charts which are robust
Lam, J M; Globas, C; Hosp, J A; Karnath, H-O; Wächter, T; Luft, A R
The ability to learn is assumed to support successful recovery and rehabilitation therapy after stroke. Hence, learning impairments may reduce the recovery potential. Here, the hypothesis is tested that stroke survivors have deficits in feedback-driven implicit learning. Stroke survivors (n=30) and healthy age-matched control subjects (n=21) learned a probabilistic classification task with brain activation measured using functional magnetic resonance imaging in a subset of these individuals (17 stroke and 10 controls). Stroke subjects learned slower than controls to classify cues. After being rewarded with a smiley face, they were less likely to give the same response when the cue was repeated. Stroke subjects showed reduced brain activation in putamen, pallidum, thalamus, frontal and prefrontal cortices and cerebellum when compared with controls. Lesion analysis identified those stroke survivors as learning-impaired who had lesions in frontal areas, putamen, thalamus, caudate and insula. Lesion laterality had no effect on learning efficacy or brain activation. These findings suggest that stroke survivors have deficits in reinforcement learning that may be related to dysfunctional processing of feedback-based decision-making, reward signals and working memory. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.
Dr. Harmen Schaap; Dr. Liesbeth Baartman; Prof.Dr. Elly de Bruijn
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,
Yurdugül, Halil; Menzi Çetin, Nihal
Problem Statement: Learners can access and participate in online learning environments regardless of time and geographical barriers. This brings up the umbrella concept of learner autonomy that contains self-directed learning, self-regulated learning and the studying process. Motivation and learning strategies are also part of this umbrella…
Fawzy, A S; Hinton, O R
This paper presents three schemes for the solution of the optimal control of fermentation process. It also shows the advantages of using microprocessors in controlling and monitoring this process. A linear model of the system is considered. An optimal feedback controller is determined which maintains the states (substrate and organisms concentration) at desired values when the system is subjected to disturbances in the influent substrate and organisms concentration. Simulation results are presented for the three cases.
Tanji, Jun-ichi; Kinoshita, Mitsuo
A self-organizing fuzzy controller is able to use linguistic decision rules of control strategy and has a strong adaptive property by virture of its rule learning function. While a simple linguistic description of the learning algorithm first introduced by Procyk, et al. has much flexibility for applications to a wide range of different processes, its detailed formulation, in particular with control stability and learning process convergence, is not clear. In this paper, we describe the formulation of an analytical basis for a self-organizing fuzzy controller by using a method of model reference adaptive control systems (MRACS) for which stability in the adaptive loop is theoretically proven. A detailed formulation is described regarding performance evaluation and rule modification in the rule learning process of the controller. Furthermore, an improved learning algorithm using adaptive rule is proposed. An adaptive rule gives a modification coefficient for a rule change estimating the effect of disturbance occurrence in performance evaluation. The effect of introducing an adaptive rule to improve the learning convergency is described by using a simple iterative formulation. Simulation tests are presented for an application of the proposed self-organizing fuzzy controller to the pressure control system in a Boiling Water Reactor (BWR) plant. Results with the tests confirm the improved learning algorithm has strong convergent properties, even in a very disturbed environment. (author)
Fischer, Hans Ernst; von Aufschnaiter, Stephan
Reviews four hypotheses about learning: Comenius's transmission-reception theory, information processing theory, Gestalt theory, and Piagetian theory. Uses the categories preunderstanding, conceptual change, and learning processes to classify and assess investigations on learning processes. (PR)
Full Text Available Designing an effective criterion and learning algorithm for find the best structure is a major problem in the control design process. In this paper, the fuzzy optimal control methodology is applied to the design of the feedback loops of an Exothermic Continuous Stirred Tank Reactor system. The objective of design process is to find an optimal structure/gains of the Robust and Optimal Takagi Sugeno Fuzzy Controller (ROFLC. The control signal thus obtained will minimize a performance index, which is a function of the tracking/regulating errors, the quantity of the energy of the control signal applied to the system, and the number of fuzzy rules. The genetic learning is proposed for constructing the ROFLC. The chromosome genes are arranged into two parts, the binary-coded part contains the control genes and the real-coded part contains the genes parameters representing the fuzzy knowledge base. The effectiveness of this chromosome formulation enables the fuzzy sets and rules to be optimally reduced. The performances of the ROFLC are compared to these found by the traditional PD controller with Genetic Optimization (PD_GO. Simulations demonstrate that the proposed ROFLC and PD_GO has successfully met the design specifications.
Grondman, Ivo; Vaandrager, Maarten; Buşoniu, Lucian; Babuska, Robert; Schuitema, Erik
We propose two new actor-critic algorithms for reinforcement learning. Both algorithms use local linear regression (LLR) to learn approximations of the functions involved. A crucial feature of the algorithms is that they also learn a process model, and this, in combination with LLR, provides an efficient policy update for faster learning. The first algorithm uses a novel model-based update rule for the actor parameters. The second algorithm does not use an explicit actor but learns a reference model which represents a desired behavior, from which desired control actions can be calculated using the inverse of the learned process model. The two novel methods and a standard actor-critic algorithm are applied to the pendulum swing-up problem, in which the novel methods achieve faster learning than the standard algorithm.
Fluhr, Christian Yves Andre
This research thesis concerns the field of artificial intelligence. It addresses learning algorithms applied to automatic processing of languages. The author first briefly describes some mechanisms of human intelligence in order to describe how these mechanisms are simulated on a computer. He outlines the specific role of learning in various manifestations of intelligence. Then, based on the Markov's algorithm theory, the author discusses the notion of learning algorithm. Two main types of learning algorithms are then addressed: firstly, an 'algorithm-teacher dialogue' type sanction-based algorithm which aims at learning how to solve grammatical ambiguities in submitted texts; secondly, an algorithm related to a document system which structures semantic data automatically obtained from a set of texts in order to be able to understand by references to any question on the content of these texts
Ford, Roger G.; Delgado, Hector; Tilley, Randy
The 1996 Summer Faculty Fellowship Program and Kennedy Space Center (KSC) served as the basis for a research effort into statistical process control for KSC processing. The effort entailed several tasks and goals. The first was to develop a customized statistical process control (SPC) course for the Safety and Mission Assurance Trends Analysis Group. The actual teaching of this course took place over several weeks. In addition, an Internet version of the same course complete with animation and video excerpts from the course when it was taught at KSC was developed. The application of SPC to shuttle processing took up the rest of the summer research project. This effort entailed the evaluation of SPC use at KSC, both present and potential, due to the change in roles for NASA and the Single Flight Operations Contractor (SFOC). Individual consulting on SPC use was accomplished as well as an evaluation of SPC software for KSC use in the future. A final accomplishment of the orientation of the author to NASA changes, terminology, data format, and new NASA task definitions will allow future consultation when the needs arise.
Kirichenko, A.; van Zanten, H.
In this paper we provide theoretical support for the so-called "Sigmoidal Gaussian Cox Process" approach to learning the intensity of an inhomogeneous Poisson process on a d-dimensional domain. This method was proposed by Adams, Murray and MacKay (ICML, 2009), who developed a tractable computational
Gorez, R.; Klán, Petr
Roč. 22, č. 2 (2011), s. 58-62 ISSN 0929-2268 Institutional research plan: CEZ:AV0Z10300504 Keywords : process model s * PID control * second order dynamics Subject RIV: JB - Sensors, Measurment, Regulation
Zimmermann, J. [Max-Planck-Institut fuer Physik, Foehringer Ring 6, 80805 Munich (Germany)]. E-mail: email@example.com
The basics of statistical learning are reviewed with a special emphasis on general principles and problems for all different types of learning methods. Different aspects of controlling these methods in a physically adequate way will be discussed. All principles and guidelines will be exercised on examples for statistical learning methods in high energy and astrophysics. These examples prove in addition that statistical learning methods very often lead to a remarkable performance gain compared to the competing classical algorithms.
The basics of statistical learning are reviewed with a special emphasis on general principles and problems for all different types of learning methods. Different aspects of controlling these methods in a physically adequate way will be discussed. All principles and guidelines will be exercised on examples for statistical learning methods in high energy and astrophysics. These examples prove in addition that statistical learning methods very often lead to a remarkable performance gain compared to the competing classical algorithms
Written by two of the world's leading researchers in the field, this is a systematic introduction to the fundamental principles of coherent control, and to the underlying physics and chemistry.This fully updated second edition is enhanced by 80% and covers the latest techniques and applications, including nanostructures, attosecond processes, optical control of chirality, and weak and strong field quantum control. Developments and challenges in decoherence-sensitive condensed phase control as well as in bimolecular control are clearly described.Indispensable for atomic, molecular and chemical
Full Text Available Reinforcement Learning (RL has been proposed to deal with ramp control problems under dynamic traffic conditions; however, there is a lack of sufficient research on the behaviour and impacts of different learning parameters. This paper describes a ramp control agent based on the RL mechanism and thoroughly analyzed the influence of three learning parameters; namely, learning rate, discount rate and action selection parameter on the algorithm performance. Two indices for the learning speed and convergence stability were used to measure the algorithm performance, based on which a series of simulation-based experiments were designed and conducted by using a macroscopic traffic flow model. Simulation results showed that, compared with the discount rate, the learning rate and action selection parameter made more remarkable impacts on the algorithm performance. Based on the analysis, some suggestionsabout how to select suitable parameter values that can achieve a superior performance were provided.
Kulkarni,Sanjeev R; Dmitry M. Malioutov
The modern financial industry has been required to deal with large and diverse portfolios in a variety of asset classes often with limited market data available. Financial Signal Processing and Machine Learning unifies a number of recent advances made in signal processing and machine learning for the design and management of investment portfolios and financial engineering. This book bridges the gap between these disciplines, offering the latest information on key topics including characterizing statistical dependence and correlation in high dimensions, constructing effective and robust risk measures, and their use in portfolio optimization and rebalancing. The book focuses on signal processing approaches to model return, momentum, and mean reversion, addressing theoretical and implementation aspects. It highlights the connections between portfolio theory, sparse learning and compressed sensing, sparse eigen-portfolios, robust optimization, non-Gaussian data-driven risk measures, graphical models, causal analy...
Ziyad, Nigel; Cox, E. Lucien; Chouikha, Mohamed F.
This paper explains the use of a Stochastic Learning Automata (SLA) to control switching between three systems to produce the desired output response. The SLA learns the optimal choice of the damping ratio for each system to achieve a desired result. We show that the SLA can learn these states for the control of an unknown system with the proper choice of the error criteria. The results of using a single automaton are compared to using multiple automata.
Bandura, Albert; Jeffery, Robert W.
Results were interpreted supporting a social learning view of observational learning that emphasizes contral processing of response information in the acquisition phase and motor reproduction and incentive processes in the overt enactment of what has been learned. (Author)
Bailey, Richard; Pickard, Angela
This paper was stimulated by the authors' attempt to understand the process of skill learning in dance. Its stimulus was a period of fieldwork based at the Royal Ballet School in London, and subsequent discussions with the school's teachers and with academic colleagues about how it was that the young dancers developed their characteristic set of…
Muehleck, Jeanette K.; Smith, Cathleen L.; Allen, Janine M.
To better understand the learning that transpires in advising, we used Anderson et al.'s (2001) revision of Bloom's (1956) taxonomy and Krathwohl, Bloom, and Masia's (1964) affective taxonomy to analyze eight student-reported advising outcomes from Smith and Allen (2014). Using the cognitive processes and knowledge domains of Anderson et al.'s…
Romine, Peter L.; Adenwala, Jinen A.
The research and analysis performed, and software developed, and hardware/software recommendations made during 1992 in development of the PC-based data acquisition system for support of Welding Process Modeling and Control is reported. A need was identified by the Metals Processing Branch of NASA Marshall Space Flight Center, for a mobile data aquisition and analysis system, customized for welding measurement and calibration. Several hardware configurations were evaluated and a PC-based system was chosen. The Welding Measurement System (WMS) is a dedicated instrument, strictly for the use of data aquisition and analysis. Although the WMS supports many of the functions associated with the process control, it is not the intention for this system to be used for welding process control.
Mitsel, A. A.; Cherniaeva, N. V.
The article discusses models, methods and algorithms of determining student's optimal individual educational trajectory. A new method of controlling the learning trajectory has been developed as a dynamic model of learning trajectory control, which uses score assessment to construct a sequence of studied subjects.
Sorgenfrei, Christian; Smolnik, Stefan
E-learning systems are considerably changing education and organizational training. With the advancement of online-based learning systems, learner control over the instructional process has emerged as a decisive factor in technology-based forms of learning. However, conceptual work on the role of learner control in e-learning has not advanced…
Bursley, James K; Nestor, Adrian; Tarr, Michael J; Creswell, J David
Offline processing has been shown to strengthen memory traces and enhance learning in the absence of conscious rehearsal or awareness. Here we evaluate whether a brief, two-minute offline processing period can boost associative learning and test a memory reactivation account for these offline processing effects. After encoding paired associates, subjects either completed a distractor task for two minutes or were immediately tested for memory of the pairs in a counterbalanced, within-subjects functional magnetic resonance imaging study. Results showed that brief, awake, offline processing improves memory for associate pairs. Moreover, multi-voxel pattern analysis of the neuroimaging data suggested reactivation of encoded memory representations in dorsolateral prefrontal cortex during offline processing. These results signify the first demonstration of awake, active, offline enhancement of associative memory and suggest that such enhancement is accompanied by the offline reactivation of encoded memory representations.
James K Bursley
Full Text Available Offline processing has been shown to strengthen memory traces and enhance learning in the absence of conscious rehearsal or awareness. Here we evaluate whether a brief, two-minute offline processing period can boost associative learning and test a memory reactivation account for these offline processing effects. After encoding paired associates, subjects either completed a distractor task for two minutes or were immediately tested for memory of the pairs in a counterbalanced, within-subjects functional magnetic resonance imaging study. Results showed that brief, awake, offline processing improves memory for associate pairs. Moreover, multi-voxel pattern analysis of the neuroimaging data suggested reactivation of encoded memory representations in dorsolateral prefrontal cortex during offline processing. These results signify the first demonstration of awake, active, offline enhancement of associative memory and suggest that such enhancement is accompanied by the offline reactivation of encoded memory representations.
Ryu, Yeong Soon; Longman, Richard W.
In a previous paper, learning control algorithms were developed based on adaptive control ideas for linear time variant systems. The learning control methods were shown to have certain advantages over their adaptive control counterparts, such as the ability to produce zero tracking error in time varying systems, and the ability to eliminate repetitive disturbances. In recent years, certain adaptive control algorithms have been developed for multi-body dynamic systems such as robots, with global guaranteed convergence to zero tracking error for the nonlinear system euations. In this paper we study the relationship between such adaptive control methods designed for this specific class of nonlinear systems, and the learning control problem for such systems, seeking to converge to zero tracking error in following a specific command repeatedly, starting from the same initial conditions each time. The extension of these methods from the adaptive control problem to the learning control problem is seen to be trivial. The advantages and disadvantages of using learning control based on such adaptive control concepts for nonlinear systems, and the use of other currently available learning control algorithms are discussed.
McMullen, David W.
Until the rise of cognitive psychology, models of the teaching-learning process (TLP) stressed external rather than internal variables. Models remained general descriptions until control theory introduced explicit system analyses. Cybernetic models emphasize feedback and adaptivity but give little attention to creativity. Research on artificial…
Chu, Baeksuk; Kim, Dongnam; Hong, Daehie; Park, Jooyoung; Chung, Jin Taek; Kim, Tae-Hyung
The main purpose of tunnel ventilation system is to maintain CO pollutant concentration and VI (visibility index) under an adequate level to provide drivers with comfortable and safe driving environment. Moreover, it is necessary to minimize power consumption used to operate ventilation system. To achieve the objectives, the control algorithm used in this research is reinforcement learning (RL) method. RL is a goal-directed learning of a mapping from situations to actions without relying on exemplary supervision or complete models of the environment. The goal of RL is to maximize a reward which is an evaluative feedback from the environment. In the process of constructing the reward of the tunnel ventilation system, two objectives listed above are included, that is, maintaining an adequate level of pollutants and minimizing power consumption. RL algorithm based on actor-critic architecture and gradient-following algorithm is adopted to the tunnel ventilation system. The simulations results performed with real data collected from existing tunnel ventilation system and real experimental verification are provided in this paper. It is confirmed that with the suggested controller, the pollutant level inside the tunnel was well maintained under allowable limit and the performance of energy consumption was improved compared to conventional control scheme.
大村, 基将; 紅林, 秀治
We considered a learning programming process based on software design for technology education. Lessons of computer program-aided measurement and control are for beginners to learn programming. These lessons are efficient to learn the step of programming, but the main of the lessons are works of typing the sample programming and debugging. Therefore, these lessons have a fundamental lack of the concept of design. Then we considered learning processes of programming and applied the process of ...
Reading aloud and solving simple arithmetic calculation intervention (Learning therapy improves inhibition, verbal episodic memory, focus attention, and processing speed in healthy elderly people: Evidence from a randomized controlled trial
Full Text Available BackgroundPrevious reports have described that simple cognitive training using reading aloud and solving simple arithmetic calculations, so-called learning therapy, can improve executive functions and processing speed in the older adults. Nevertheless, it is not well-known whether learning therapy improve a wide range of cognitive functions or not. We investigated the beneficial effects of learning therapy on various cognitive functions in healthy older adults.MethodsWe used a single-blinded intervention with two groups (learning therapy group: LT and waiting list control group: WL. Sixty-four elderly were randomly assigned to LT or WL. In LT, participants performed reading Japanese aloud and solving simple calculations training tasks for 6 months. WL did not participate in the intervention. We measured several cognitive functions before and after 6 months intervention periods.ResultsCompared to WL, results revealed that LT improved inhibition performance in executive functions (Stroop: LT (Mean = 3.88 vs. WL (Mean = 1.22, adjusted p =.013 and reverse Stroop LT (Mean = 3.22 vs. WL (Mean = 1.59, adjusted p =.015, verbal episodic memory (logical memory: LT (Mean = 4.59 vs. WL (Mean = 2.47, adjusted p =.015, focus attention(D-CAT: LT (Mean = 2.09 vs. WL (Mean = -0.59, adjusted p =.010 and processing speed compared to the waiting list control group (digit symbol coding: LT (Mean = 5.00 vs. WL (Mean = 1.13, adjusted p =.015 and symbol search: LT (Mean = 3.47 vs. WL (Mean = 1.81, adjusted p =.014.DiscussionThis RCT can showed the benefit of learning therapy on inhibition of executive functions, verbal episodic memory, focus attention, and processing speed in healthy elderly people. Our results were discussed under overlapping hypothesis.Trial registrationThis trial was registered in The University Hospital Medical Information Network Clinical Trials Registry (UMIN000006998.
Gorbunova, Tatiana N.
The subject of the research is to build methodologies to evaluate the student knowledge by testing. The author points to the importance of feedback about the mastering level in the learning process. Testing is considered as a tool. The object of the study is to create the test system models for defence practice problems. Special attention is paid…
Fu, Wai-Tat; Anderson, John R
Acquisition of interactive skills involves the use of internal and external cues. Experiment 1 showed that when actions were interdependent, learning was effective with and without external cues in the single-task condition but was effective only with the presence of external cues in the dual-task condition. In the dual-task condition, actions closer to the feedback were learned faster than actions farther away but this difference was reversed in the single-task condition. Experiment 2 tested how knowledge acquired in single and dual-task conditions would transfer to a new reward structure. Results confirmed the two forms of learning mediated by the secondary task: A declarative memory encoding process that simultaneously assigned credits to actions and a reinforcement-learning process that slowly propagated credits backward from the feedback. The results showed that both forms of learning were engaged during training, but only at the response selection stage, one form of knowledge may dominate over the other depending on the availability of attentional resources. (c) 2008 APA, all rights reserved
Shoenbill, Kimberly; Song, Yiqiang; Cobb, Nichelle L; Drezner, Marc K; Mendonca, Eneida A
Clinical research involving humans is critically important, but it is a lengthy and expensive process. Most studies require institutional review board (IRB) approval. Our objective is to identify predictors of delays or accelerations in the IRB review process and apply this knowledge to inform process change in an effort to improve IRB efficiency, transparency, consistency and communication. We analyzed timelines of protocol submissions to determine protocol or IRB characteristics associated with different processing times. Our evaluation included single variable analysis to identify significant predictors of IRB processing time and machine learning methods to predict processing times through the IRB review system. Based on initial identified predictors, changes to IRB workflow and staffing procedures were instituted and we repeated our analysis. Our analysis identified several predictors of delays in the IRB review process including type of IRB review to be conducted, whether a protocol falls under Veteran's Administration purview and specific staff in charge of a protocol's review. We have identified several predictors of delays in IRB protocol review processing times using statistical and machine learning methods. Application of this knowledge to process improvement efforts in two IRBs has led to increased efficiency in protocol review. The workflow and system enhancements that are being made support our four-part goal of improving IRB efficiency, consistency, transparency, and communication.
Betancort, Moises; Carreiras, Manuel; Acuna-Farina, Carlos
Two experiments were carried out to investigate the processing of the empty category PRO and the time-course of this in Spanish. Eye movements were recorded while participants read sentences in which a matrix clause was followed by a subordinate infinitival clause, so that the subject or the object of the main clause could act as controller of…
Yoon, Seung Won; Song, Ji Hoon; Lim, Doo Hun
This integrative literature review synthesizes the concepts and process of organizational knowledge creation with theories of individual learning. The knowledge conversion concept (Nonaka & Takeuchi, 1995; Nonaka, Toyama, & Byosiere, 2001) is used as the basis of the organizational knowledge creation process, while major learning theories relevant…
Soroush, Masoud; Weinberger, Charles B.
This manuscript presents a successful application of inductive learning in process modeling. It describes two process modeling courses that use inductive learning methods such as inquiry learning and problem-based learning, among others. The courses include a novel collection of multi-disciplinary complementary process modeling examples. They were…
Full Text Available The issue of controlling that data processing in an experiment results not affected by the presence of outliers is relevant for statistical control and learning studies. Learning schemes should thus be tested for their capacity of handling outliers in the observed training set so to achieve reliable estimates with respect to the crucial bias and variance aspects. We describe possible ways of endowing neural networks with statistically robust properties by defining feasible error criteria. It is convenient to cast neural nets in state space representations and apply both Kalman filter and stochastic approximation procedures in order to suggest statistically robustified solutions for on-line learning.
Haruno, M; Wolpert, D M; Kawato, M
Humans demonstrate a remarkable ability to generate accurate and appropriate motor behavior under many different and often uncertain environmental conditions. We previously proposed a new modular architecture, the modular selection and identification for control (MOSAIC) model, for motor learning and control based on multiple pairs of forward (predictor) and inverse (controller) models. The architecture simultaneously learns the multiple inverse models necessary for control as well as how to select the set of inverse models appropriate for a given environment. It combines both feedforward and feedback sensorimotor information so that the controllers can be selected both prior to movement and subsequently during movement. This article extends and evaluates the MOSAIC architecture in the following respects. The learning in the architecture was implemented by both the original gradient-descent method and the expectation-maximization (EM) algorithm. Unlike gradient descent, the newly derived EM algorithm is robust to the initial starting conditions and learning parameters. Second, simulations of an object manipulation task prove that the architecture can learn to manipulate multiple objects and switch between them appropriately. Moreover, after learning, the model shows generalization to novel objects whose dynamics lie within the polyhedra of already learned dynamics. Finally, when each of the dynamics is associated with a particular object shape, the model is able to select the appropriate controller before movement execution. When presented with a novel shape-dynamic pairing, inappropriate activation of modules is observed followed by on-line correction.
Jackson, Dontae L.
In the world of aviation, air traffic controllers are an integral part in the overall level of safety that is provided. With a number of controllers reaching retirement age, the Air Traffic Collegiate Training Initiative (AT-CTI) was created to provide a stronger candidate pool. However, AT-CTI Instructors have found that a number of AT-CTI students are unable to memorize types of aircraft effectively. This study focused on the basic learning styles (auditory, visual, and kinesthetic) of students and created a teaching method to try to increase memorization in AT-CTI students. The participants were asked to take a questionnaire to determine their learning style. Upon knowing their learning styles, participants attended two classroom sessions. The participants were given a presentation in the first class, and divided into a control and experimental group for the second class. The control group was given the same presentation from the first classroom session while the experimental group had a group discussion and utilized Middle Tennessee State University's Air Traffic Control simulator to learn the aircraft types. Participants took a quiz and filled out a survey, which tested the new teaching method. An appropriate statistical analysis was applied to determine if there was a significant difference between the control and experimental groups. The results showed that even though the participants felt that the method increased their learning, there was no significant difference between the two groups.
Reinforcement Learning (RL) methods are relatively new in the field of aerospace guidance, navigation, and control. This dissertation aims to exploit RL methods to improve the autonomy and online learning of aerospace systems with respect to the a priori unknown system and environment, dynamical
Høskuldsson, Agnar; Rodionova, O.; Pomerantsev, A.
and having three or more stages. The methods are applied to a process control of a multi-stage production process having 25 variables and one output variable. When moving along the process, variables change their roles. It is shown how the methods of path modeling can be applied to estimate variables...... be performed regarding the foreseeable output property y, and with respect to an admissible range of correcting actions for the parameters of the next stage. In this paper the basic principles of path modeling is presented. The mathematics is presented for processes having only one stage, having two stages...... of the next stage with the purpose of obtaining optimal or almost optimal quality of the output variable. An important aspect of the methods presented is the possibility of extensive graphic analysis of data that can provide the engineer with a detailed view of the multi-variate variation in data....
Gavriushenko, Mariia; Lindberg, Renny S. N.; Khriyenko, Oleksiy
Personalized learning is increasingly gaining popularity, especially with the development of information technology and modern educational resources for learning. Each person is individual and has different knowledge background, different kind of memory, different learning speed. Teacher can adapt learning course, learning instructions or learning material according to the majority of learners in class, but that means that learning process is not adapted to the personality of each...
Giurintano, S. L.
The chaining, position, and dual-process hypotheses of serial learning (SL) as well as serial recall, reordering, and relearning of paired-associate learning were examined to establish learning patterns. Results provide evidence for dual-process hypothesis. (DS)
Tarn, J. H.; Kuo, L. T.; Juang, K. Y.; Lin, C. E.
It is known that an effective control system is the key condition for successful implementation of high-performance magnetic servo systems. Major issues to design such control systems are nonlinearity; unmodeled dynamics, such as secondary effects for copper resistance, stray fields, and saturation; and that disturbance rejection for the load effect reacts directly on the servo system without transmission elements. One typical approach to design control systems under these conditions is a special type of nonlinear feedback called gain scheduling. It accommodates linear regulators whose parameters are changed as a function of operating conditions in a preprogrammed way. In this paper, an on-line learning fuzzy control strategy is proposed. To inherit the wealth of linear control design, the relations between linear feedback and fuzzy logic controllers have been established. The exercise of engineering axioms of linear control design is thus transformed into tuning of appropriate fuzzy parameters. Furthermore, fuzzy logic control brings the domain of candidate control laws from linear into nonlinear, and brings new prospects into design of the local controllers. On the other hand, a self-learning scheme is utilized to automatically tune the fuzzy rule base. It is based on network learning infrastructure; statistical approximation to assign credit; animal learning method to update the reinforcement map with a fast learning rate; and temporal difference predictive scheme to optimize the control laws. Different from supervised and statistical unsupervised learning schemes, the proposed method learns on-line from past experience and information from the process and forms a rule base of an FLC system from randomly assigned initial control rules.
Kuhnle, Alexander; Copestake, Ann
We discuss problems with the standard approaches to evaluation for tasks like visual question answering, and argue that artificial data can be used to address these as a complement to current practice. We demonstrate that with the help of existing 'deep' linguistic processing technology we are able to create challenging abstract datasets, which enable us to investigate the language understanding abilities of multimodal deep learning models in detail, as compared to a single performance value ...
Apfelbaum, Keith S.; McMurray, Bob
Previous research on associative learning has uncovered detailed aspects of the process, including what types of things are learned, how they are learned, and where in the brain such learning occurs. However, perceptual processes, such as stimulus recognition and identification, take time to unfold. Previous studies of learning have not addressed…
Lisa Katharina Pendt
Full Text Available Parkinson's disease, which affects the basal ganglia, is known to lead to various impairments of motor control. Since the basal ganglia have also been shown to be involved in learning processes, motor learning has frequently been investigated in this group of patients. However, results are still inconsistent, mainly due to skill levels and time scales of testing. To bridge across the time scale problem, the present study examined de novo skill learning over a long series of practice sessions that comprised early and late learning stages as well as retention. 19 non-demented, medicated, mild to moderate patients with Parkinson's disease and 19 healthy age and gender matched participants practiced a novel throwing task over five days in a virtual environment where timing of release was a critical element. Six patients and seven control participants came to an additional long-term retention testing after seven to nine months. Changes in task performance were analyzed by a method that differentiates between three components of motor learning prominent in different stages of learning: Tolerance, Noise and Covariation. In addition, kinematic analysis related the influence of skill levels as affected by the specific motor control deficits in Parkinson patients to the process of learning. As a result, patients showed similar learning in early and late stages compared to the control subjects. Differences occurred in short-term retention tests; patients' performance constantly decreased after breaks arising from poorer release timing. However, patients were able to overcome the initial timing problems within the course of each practice session and could further improve their throwing performance. Thus, results demonstrate the intact ability to learn a novel motor skill in non-demented, medicated patients with Parkinson's disease and indicate confounding effects of motor control deficits on retention performance.
The control of production processes is the subject of several disciplines, such as statistical process control (SPC), total productive maintenance (TPM), and automated process control (APC). Although these disciplines are traditionally separated (both in science and in business practice), their
Xie, Danfeng; Zhang, Lei; Bai, Li
Deep learning is a subfield of machine learning, which aims to learn a hierarchy of features from input data. Nowadays, researchers have intensively investigated deep learning algorithms for solving challenging problems in many areas such as image classification, speech recognition, signal processing, and natural language processing. In this study, we not only review typical deep learning algorithms in computer vision and signal processing but also provide detailed information on how to apply...
.... The UMass effort marries high-level process descriptions, discrete event analysis and model checking, learning and stochastic exploration, and a control theoretic substrate to accomplish these goals...
A licensed pharmaceutical process is required to be executed within the validated ranges throughout the lifetime of product manufacturing. Changes to the process usually require the manufacturer to demonstrate that the safety and efficacy of the product remains unchanged. Recent changes in the
Full Text Available The research objective was to produce a model of learning entrepreneurship by using SWOT analysis, which was currently being run with the concept of large classes and small classes. The benefits of this study was expected to be useful for the Binus Entrepreneurship Center (BEC unit to create a map development learning entrepreneurship. Influences that would be generated by using SWOT Analysis were very wide as the benefits of the implementation of large classes and small classes for students and faculty. Participants of this study were Binus student of various majors who were taking courses EN001 and EN002. This study used research and development that examining the theoretical learning components of entrepreneurship education (teaching and learning dimension, where there were six dimensions of the survey which was a fundamental element in determining the framework of entrepreneurship education. Research finds that a strategy based on a matrix of factors is at least eight strategies for improving the learning process of entrepreneurship. From eight strategies are one of them strategies to increase collaboration BEC with family support. This strategy is supported by the survey results to the three majors who are following the EN001 and EN002, where more than 85% of the students are willing to do an aptitude test to determine the advantages and disadvantages of self-development and more of 54% of the students are not willing to accept the wishes of their parents because they do not correspond to his ideals. Based on the above results, it is suggested for further research, namely developing entrepreneurship research by analyzing other dimensions.
Full Text Available In the article, the acute problem of implementation of pedagogical innovations and online technologies into the educational process is analyzed. The article explores the advantages of blended learning as a latter-day educational program in comparison with traditional campus learning. Blended learning is regarded worldwide as the combination of classroom face-to-face sessions with interactive learning opportunities created online. The purpose of the article is to identify blended learning transformational potential impacting students and teachers by ensuring a more personalized learning experience. The concept of blended learning, as a means to enhance foreign language teaching and learning in the classroom during the traditional face-to-face interaction between a teacher and a student, combined with computer-mediated activities, is examined. In the article, the main classification of blended learning models is established. There are four main blended learning models which include both face-to-face instruction time and online learning: Rotation Model, Flex Model, A La Carte Model, and Enriched Virtual Model. Once implemented successfully, a blended model can take advantage of both brick-and-mortar and digital worlds, providing significant benefits for the educational establishments and learners. To integrate any of the blended learning models, a teacher can create online activities that enable learners to explore the topic online at home, and then develop face-to-face interactions to dig deeper into the subject matter at the lesson. The use of blended learning models in order to expand educational opportunities for students while the foreign language acquisition, by increasing the availability and flexibility of education, taking into account student individual learning needs, with some element of student control over time, place and pace, is explored. The realization of blended learning models in regards to age and physiological peculiarities of
Full Text Available Language as a communication tool has an important role in human interaction. Language can be used to convey ideas, ideas, feelings, desires, and so forth to others. To be able to communicate well certainly should be able to adjust the language used. One of the main functions of communication is to maintain the continuity of the relationship between the narrator and hearer. Language is an important pillar in the formation of character, in addition to religious education and moral education. In education, teachers must have pedagogical, professional, personal, and social. Teachers who have a good competence speech acts certainly have a good and well mannered to students. In the learning process, teachers and students communicate in give and receive course materials. The learning process is certainly not only provides knowledge alone, but give the values of character to students. In this case, the teacher must have a principle that must be controlled properly, correctly and precisely. Thus, teachers are expected to master the communication and understanding the principles of politeness in speaking well and correctly. The goal is a description of a form of politeness in the learning process. This research is a descriptive study which seeks to describe a form of politeness in the learning process. Data collection method used is the method refer to the data collection techniques are 1 recording technique using a tape recorder, and 2 technical note on the data card. Furthermore, methods of data analysis using pragmatic frontier.
Norman, Elisabeth; Price, Mark C; Jones, Emma
In response to concerns with existing procedures for measuring strategic control over implicit knowledge in artificial grammar learning (AGL), we introduce a more stringent measurement procedure. After two separate training blocks which each consisted of letter strings derived from a different grammar, participants either judged the grammaticality of novel letter strings with respect to only one of these two grammars (pure-block condition), or had the target grammar varying randomly from trial to trial (novel mixed-block condition) which required a higher degree of conscious flexible control. Random variation in the colour and font of letters was introduced to disguise the nature of the rule and reduce explicit learning. Strategic control was observed both in the pure-block and mixed-block conditions, and even among participants who did not realise the rule was based on letter identity. This indicated detailed strategic control in the absence of explicit learning. Copyright © 2011 Elsevier Inc. All rights reserved.
Verwoerd, M.H.A.; Meinsma, Gjerrit; de Vries, Theodorus J.A.
This paper advocates a new approach to study the relation between causal iterative learning control (ILC) and conventional feedback control. Central to this approach is the introduction of the set of admissible pairs (of operators) defined with respect to a family of iterations. Considered are two
Kang, Sin Chun; Kim, Raeh Yeon; Kim, Yang Su; Oh, Min; Yeo, Yeong Gu; Jung, Yeon Su
This book is about chemical process control, which includes the basis of process control with conception, function, composition of system and summary, change of laplace and linearization, modeling of chemical process, transfer function and block diagram, the first dynamic property of process, the second dynamic property of process, the dynamic property of combined process, control structure of feedback on component of control system, the dynamic property of feedback control loop, stability of closed loop control structure, expression of process, modification and composition of controller, analysis of vibration response and adjustment controller using vibration response.
Mendez, Juan A.; Gonzalez, Evelio J.
As it happens in other fields of engineering, blended learning is widely used to teach process control topics. In this paper, the inclusion of a reactive element--a Fuzzy Logic based controller--is proposed for a blended learning approach in an introductory control engineering course. This controller has been designed in order to regulate the…
Nikacevic, N.M.; Huesman, A.E.M.; Hof, Van den P.M.J.; Stankiewicz, A.
This is a review and position article discussing the role and prospective for process control in process intensification. Firstly, the article outlines the classical role of control in process systems, presenting an overview of control systems’ development, from basic PID control to the advanced
Duvarci, Sevil; Pare, Denis
We review recent work on the role of intrinsic amygdala networks in the regulation of classically conditioned defensive behaviors, commonly known as conditioned fear. These new developments highlight how conditioned fear depends on far more complex networks than initially envisioned. Indeed, multiple parallel inhibitory and excitatory circuits are differentially recruited during the expression versus extinction of conditioned fear. Moreover, shifts between expression and extinction circuits involve coordinated interactions with different regions of the medial prefrontal cortex. However, key areas of uncertainty remain, particularly with respect to the connectivity of the different cell types. Filling these gaps in our knowledge is important because much evidence indicates that human anxiety disorders results from an abnormal regulation of the networks supporting fear learning. PMID:24908482
Lestariani, Ida; Sujadi, Imam; Pramudya, Ikrar
The purpose of research to describe the implementation of performance assessment on algebra learning process. The subject in this research is math educator of SMAN 1 Ngawi class X. This research includes descriptive qualitative research type. Techniques of data collecting are done by observation method, interview, and documentation. Data analysis technique is done by data reduction, data presentation, and conclusion. The results showed any indication that the steps taken by the educator in applying the performance assessment are 1) preparing individual worksheets and group worksheets, 2) preparing rubric assessments for independent worksheets and groups and 3) making performance assessments rubric to learners’ performance results with individual or groups task.
The strategy obviously adopted by the well-established manufacturers is to offer 'easy-to-handle' equipment to gain new customers, and there is a variety of new compact systems or personal computers being put on the market. The changes and improvements within the processing sector proceed more or less in silence; high-capacity storage devices and multiprocessor configurations are obtainable at a moderate price, offering a greater variety of basic functions and enhanced control possibilities. Redundancy problems are handled with greater flexibility, and batch programs are advancing. Data communication has become a common feature, transmission speed and bus length have been improved. Important improvements have been made with regard to data display; even medium-sized equipment now offer the possibility of making dynamic flow-sheets and reserving space for process history display, and the hierarchy of displays has been considerably simplified. The user software also has been made more easy, 'fill-in-the-blancs' is the prevailing motto for dialog configurations, and such big terms as process computer' or 'programming skill' are passing into oblivion. (orig./HP) [de
Full Text Available Background: It has been demonstrated that educational programs that focus on study skills could improve learning strategies and academic success of university students. Due to the important role of such supportive programs aimed at the fresh students, this survey was carried out to investigate the effectiveness of an optional course of learning and study skills on learning and study skills of second year medical students. Methods: This quasi-experimental research was performed on 32 eligible medical students in Isfahan University of Medical Sciences, who chose the optional course of learning and study skills. Both of intervention and control groups completed Learning and Study Strategies Inventory (LASSI at the beginning and the end of semester. Students in the intervention group studied different components of reading and learning skills using team working. Their final scores were calculated based on written reports on application of study skills in exams (portfolio, self-evaluation form and their progress in LASSI test. The mean differences of scores before and after intervention in each of ten test scales were compared between two groups. Results: The results showed that the mean difference scores in attitude, time management, information processing, main ideas selection, study aids and self-testing scales were significantly higher in the intervention group (p < 0.05 for all. Conclusions: This optional course successfully improved learning strategies in the corresponding classroom activities. However, there was no improvement in the motivational scale which is tightly related to the educational success. Therefore, the implementation of educational programs with an emphasis on meta-cognitional aspects of learning is recommended.
Rahmah, A.; Santoso, H. B.; Hasibuan, Z. A.
ICT advancement is a sure thing with the impact influencing many domains, including learning in both formal and informal situations. It leads to a new mindset that we should not only utilize the given ICT to support the learning process, but also improve it gradually involving a lot of factors. These phenomenon is called e-learning process evolution. Accordingly, this study attempts to explore maturity level concept to provide the improvement direction gradually and progression monitoring for the individual e-learning process. Extensive literature review, observation, and forming constructs are conducted to develop a conceptual framework for e-learning process maturity level. The conceptual framework consists of learner, e-learning process, continuous improvement, evolution of e-learning process, technology, and learning objectives. Whilst, evolution of e-learning process depicted as current versus expected conditions of e-learning process maturity level. The study concludes that from the e-learning process maturity level conceptual framework, it may guide the evolution roadmap for e-learning process, accelerate the evolution, and decrease the negative impact of ICT. The conceptual framework will be verified and tested in the future study.
The accuracy of today's color management systems fails to satisfy the requirements of the graphic arts market. A first explanation for this is that color calibration charts on which these systems rely, because of print technical reasons, are subject to color deviations and inconsistencies. A second reason is that colorimetry describes the human visual perception of color differences and has no direct relation to the rendering technology itself of a proofing or printing device. The author explains that only firm process control of the many parameters in offset printing by means of a system as for example EUROSTANDARD System Brunner, can lead to accurate and consistent calibration of scanner, display, proof and print. The same principles hold for the quality management of digital presses.
Dzelzkalēja, L; Kapenieks, J
Effective assessment is an important way for improving the learning process. There are existing guidelines for assessing the learning process, but they lack holistic digital knowledge society considerations. In this paper the authors propose a method for real-time evaluation of students’ learning process and, consequently, for quality evaluation of teaching materials both in the classroom and in the distance learning environment. The main idea of the proposed Color code method (CCM) is to use...
Park, Gee Yong; Seong, Poong Hyun
In order to reduce the load of tuning works by trial-and-error for obtaining the best control performance of conventional fuzzy control algorithm, a fuzzy control algorithm with learning function is investigated in this work. This fuzzy control algorithm can make its rule base and tune the membership functions automatically by use of learning function which needs the data from the control actions of the plant operator or other controllers. Learning process in fuzzy control algorithm is to find the optimal values of parameters, which consist of the membership functions and the rule base, by gradient descent method. Learning speed of gradient descent is significantly improved in this work with the addition of modified momentum. This control algorithm is applied to the steam generator level control by computer simulations. The simulation results confirm the good performance of this control algorithm for level control and show that the fuzzy learning algorithm has the generalization capability for the relation of inputs and outputs and it also has the excellent capability of disturbance rejection
an equally widespread process at the meso-level is a workflow called Lecture-Recitation-Seatwork-Plenary session (abbreviated as LeReSeP). These two structures are discussed and analysed, and they are criticised on a theoretical basis for being too teacher-centred, and leaving insufficient room....... A course consists of several modules integrating several workflows, each of which comprises several interaction sequences. Two common processes are identified. At the micro-level, the most common interaction sequence is (the teacher's) Initiation- (student's) Response- (teacher's) Feedback (IRF) while...... for developing more complex competences in students. A number of alternative interaction sequences and workflows are described and discussed. These alternatives all have their advantages, but they are evaluated as more complex, troublesome, and inconvenient to work with. Teaching and learning materials support...
Ming Zhedong; Zhao Fuyu
Considering the characteristics of pressurizer dynamic process, the fuzzy control system that takes the advantages of both fuzzy controller and PID controller is designed for the dynamic process in pressurizer. The simulation results illustrate this type of composite control system is with better qualities than those of single fuzzy controller and single PID controller. (authors)
Syafiie, S; Tadeo, F; Villafin, M; Alonso, A A
A control technique based on Reinforcement Learning is proposed for the thermal sterilization of canned foods. The proposed controller has the objective of ensuring a given degree of sterilization during Heating (by providing a minimum temperature inside the cans during a given time) and then a smooth Cooling, avoiding sudden pressure variations. For this, three automatic control valves are manipulated by the controller: a valve that regulates the admission of steam during Heating, and a valve that regulate the admission of air, together with a bleeder valve, during Cooling. As dynamical models of this kind of processes are too complex and involve many uncertainties, controllers based on learning are proposed. Thus, based on the control objectives and the constraints on input and output variables, the proposed controllers learn the most adequate control actions by looking up a certain matrix that contains the state-action mapping, starting from a preselected state-action space. This state-action matrix is constantly updated based on the performance obtained with the applied control actions. Experimental results at laboratory scale show the advantages of the proposed technique for this kind of processes. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.
Park, Gee Yong
A fuzzy learning algorithm is developed in order to construct the useful control rules and tune the membership functions in the fuzzy logic controller used for water level control of nuclear steam generator. The fuzzy logic controllers have shown to perform better than conventional controllers for ill-defined or complex processes such as nuclear steam generator. Whereas the fuzzy logic controller does not need a detailed mathematical model of a plant to be controlled, its structure is to be made on the basis of the operator's linguistic information experienced from the plant operations. It is not an easy work and also there is no systematic way to translate the operator's linguistic information into quantitative information. When the linguistic information of operators is incomplete, tuning the parameters of fuzzy controller is to be performed for better control performance. It is the time and effort consuming procedure that controller designer has to tune the structure of fuzzy logic controller for optimal performance. And if the number of control inputs is many and the rule base is constructed in multidimensional space, it is very difficult for a controller designer to tune the fuzzy controller structure. Hence, the difficulty in putting the experimental knowledge into quantitative (or numerical) data and the difficulty in tuning the rules are the major problems in designing fuzzy logic controller. In order to overcome the problems described above, a learning algorithm by gradient descent method is included in the fuzzy control system such that the membership functions are tuned and the necessary rules are created automatically for good control performance. For stable learning in gradient descent method, the optimal range of learning coefficient not to be trapped and not to provide too slow learning speed is investigated. With the optimal range of learning coefficient, the optimal value of learning coefficient is suggested and with this value, the gradient
Kopčeková, Alena; Kopček, Michal; Tanuška, Pavol
The Business Intelligence technology, which represents a strong tool not only for decision making support, but also has a big potential in other fields of application, is discussed in this paper. Necessary fundamental definitions are offered and explained to better understand the basic principles and the role of this technology for company management. Article is logically divided into five main parts. In the first part, there is the definition of the technology and the list of main advantages. In the second part, an overview of the system architecture with the brief description of separate building blocks is presented. Also, the hierarchical nature of the system architecture is shown. The technology life cycle consisting of four steps, which are mutually interconnected into a ring, is described in the third part. In the fourth part, analytical methods incorporated in the online analytical processing and data mining used within the business intelligence as well as the related data mining methodologies are summarised. Also, some typical applications of the above-mentioned particular methods are introduced. In the final part, a proposal of the knowledge discovery system for hierarchical process control is outlined. The focus of this paper is to provide a comprehensive view and to familiarize the reader with the Business Intelligence technology and its utilisation.
As the concepts of machine learning and artificial intelligence continue to grow in importance in the context of internet related applications it is still in its infancy when it comes to process control within the semiconductor industry. Especially the branch of mask manufacturing presents a challenge to the concepts of machine learning since the business process intrinsically induces pronounced product variability on the background of small plate numbers. In this paper we present the architectural set up of a machine learning algorithm which successfully deals with the demands and pitfalls of mask manufacturing. A detailed motivation of this basic set up followed by an analysis of its statistical properties is given. The machine learning set up for mask manufacturing involves two learning steps: an initial step which identifies and classifies the basic global CD patterns of a process. These results form the basis for the extraction of an optimized training set via balanced sampling. A second learning step uses this training set to obtain the local as well as global CD relationships induced by the manufacturing process. Using two production motivated examples we show how this approach is flexible and powerful enough to deal with the exacting demands of mask manufacturing. In one example we show how dedicated covariates can be used in conjunction with increased spatial resolution of the CD map model in order to deal with pathological CD effects at the mask boundary. The other example shows how the model set up enables strategies for dealing tool specific CD signature differences. In this case the balanced sampling enables a process control scheme which allows usage of the full tool park within the specified tight tolerance budget. Overall, this paper shows that the current rapid developments off the machine learning algorithms can be successfully used within the context of semiconductor manufacturing.
This book is intended for IT professionals working with Hyper-V, Azure cloud, VMM, and private cloud technologies who are looking for a quick way to get up and running with System Center 2012 R2 App Controller. To get the most out of this book, you should be familiar with Microsoft Hyper-V technology. Knowledge of Virtual Machine Manager is helpful but not mandatory.
Iversen, Ann-Merete; Pedersen, Anni Stavnskær; Kjær-Rasmussen, Lone Krogh
The article introduces a new term in higher education: learner-led approaches in education (LED). This does not represent a single approach or dogma to replace existing dogmas, but a way of approaching learning and education that mirrors the complexity of society as it develops. LED is based...... on the assumption that all students have their own unique approach to learning and therefore have the potential to design learning processes that are meaningful for them. This removes focus from the teacher and the teaching to the learner and the learning. It builds on the student’s motivation and experienced...... meaningfulness as a driving force, and hence the term learner led. The methods applied in LED change over time, as different learners and teachers together co-create and design methods and approaches appropriate at that particular time, in that particular context and for that particular student or group...
The seventeenth of a series of workshops sponsored by the IEEE Signal Processing Society and organized by the Machine Learning for Signal Processing Technical Committee (MLSP-TC). The field of machine learning has matured considerably in both methodology and real-world application domains and has...... become particularly important for solution of problems in signal processing. As reflected in this collection, machine learning for signal processing combines many ideas from adaptive signal/image processing, learning theory and models, and statistics in order to solve complex real-world signal processing......, and two papers from the winners of the Data Analysis Competition. The program included papers in the following areas: genomic signal processing, pattern recognition and classification, image and video processing, blind signal processing, models, learning algorithms, and applications of machine learning...
Carr, James; Gannon-Leary, Pat
A major obstacle to the diffusion of management development learning technologies from Higher Education Institutions to Small and Medium-sized Enterprises (SMEs) is a lack of understanding about how SME learners learn. This article examines the nature of learning in SMEs and considers the incidence of informal support for informal learning.…
Modern digital automation techniques allow the application of demanding types of process control. These types of process control are characterized by their belonging to higher levels in a multilevel model. Functional and technical aspects of the performance of digital automation plants are presented and explained. A modern automation system is described considering special procedures of process control (e.g. real time diagnosis)
Adali, Tulay; Miller, David J.; Diamantaras, Konstantinos I.
By putting the accent on learning from the data and the environment, the Machine Learning for SP (MLSP) Technical Committee (TC) provides the essential bridge between the machine learning and SP communities. While the emphasis in MLSP is on learning and data-driven approaches, SP defines the main...... applications of interest, and thus the constraints and requirements on solutions, which include computational efficiency, online adaptation, and learning with limited supervision/reference data....
Braun, Daniel A.; Aertsen, Ad; Paz, Rony; Vaadia, Eilon; Rotter, Stefan; Mehring, Carsten
When faced with unpredictable environments, the human motor system has been shown to develop optimized adaptation strategies that allow for online adaptation during the control process. Such online adaptation is to be contrasted to slower over-trial learning that corresponds to a trial-by-trial update of the movement plan. Here we investigate the interplay of both processes, i.e., online adaptation and over-trial learning, in a visuomotor experiment performed by macaques. We show that simple non-adaptive control schemes fail to perform in this task, but that a previously suggested adaptive optimal feedback control model can explain the observed behavior. We also show that over-trial learning as seen in learning and aftereffect curves can be explained by learning in a radial basis function network. Our results suggest that both the process of over-trial learning and the process of online adaptation are crucial to understand visuomotor learning. PMID:21720526
Perales, José C; Navas, Juan F; Ruiz de Lara, Cristian M; Maldonado, Antonio; Catena, Andrés
Causal learning is the ability to progressively incorporate raw information about dependencies between events, or between one's behavior and its outcomes, into beliefs of the causal structure of the world. In spite of the fact that some cognitive biases in gambling disorder can be described as alterations of causal learning involving gambling-relevant cues, behaviors, and outcomes, general causal learning mechanisms in gamblers have not been systematically investigated. In the present study, we compared gambling disorder patients against controls in an instrumental causal learning task. Evidence of illusion of control, namely, overestimation of the relationship between one's behavior and an uncorrelated outcome, showed up only in gamblers with strong current symptoms. Interestingly, this effect was part of a more complex pattern, in which gambling disorder patients manifested a poorer ability to discriminate between null and positive contingencies. Additionally, anomalies were related to gambling severity and current gambling disorder symptoms. Gambling-related biases, as measured by a standard psychometric tool, correlated with performance in the causal learning task, but not in the expected direction. Indeed, performance of gamblers with stronger biases tended to resemble the one of controls, which could imply that anomalies of causal learning processes play a role in gambling disorder, but do not seem to underlie gambling-specific biases, at least in a simple, direct way.
Full Text Available The MOPEM project includes two fixed scenarios that have been defined to convey the idea of "learning paths". Our aim in this paper is to demonstrate the contexts and conditions for flexible learning paths that can be tailored to meet individual needs. The concept of this kind of specialised path is to enable learners to individualise the learning process and to adjust it to their personal needs. We will outline the background and pro- vide examples to explain the concept of learning stations which we use in our four courses: Online Marketing, CRM Systems, Business Communications and Event Marketing. This idea of "freely" combining subject matter naturally leads to the ques- tion of multi-applicability for the learning blocks in various educational contexts. The answers to this question are interest- ing not only in terms of the feasibility of learning paths from a content and didactic point of view, but also with regard to the economic viability of E-Learning or Blended Learning Systems, which ultimately require technical implementation. In addition we will present some first thoughts on the design of a prototype "Content Pool". It would, however, only make sense to develop and implement this within the scope of a follow-up project.
Goedhart, Menno; van Kampen, E.; Armanini, S.F.; de Visser, C.C.; Chu, Q.
Flight control of Flapping Wing Micro Air Vehicles is challenging, because of their complex dynamics and variability due to manufacturing inconsistencies. Machine Learning algorithms can be used to tackle these challenges. A Policy Gradient algorithm is used to tune the gains of a
Full Text Available In dynamic environments, when faced with a choice of which learning strategy to adopt, do people choose to mostly explore (maximizing their long term gains or exploit (maximizing their short term gains? More to the point, how does this choice of learning strategy influence one’s later ability to control the environment? In the present study, we explore whether people’s self-reported learning strategies and levels of arousal (i.e., surprise, stress correspond to performance measures of controlling a Highly Uncertain or Moderately Uncertain dynamic environment. Generally, self-reports suggest a preference for exploring the environment to begin with. After which, those in the Highly Uncertain environment generally indicated they exploited more than those in the Moderately Uncertain environment; this difference did not impact on performance on later tests of people’s ability to control the dynamic environment. Levels of arousal were also differentially associated with the uncertainty of the environment. Going beyond behavioral data, our model of dynamic decision-making revealed that, in actual fact, there was no difference in exploitation levels between those in the highly uncertain or moderately uncertain environments, but there were differences based on sensitivity to negative reinforcement. We consider the implications of our findings with respect to learning and strategic approaches to controlling dynamic uncertainty.
Gadzella, B. M.; And Others
The Inventory of Learning Processes (ILP) was developed by Schmeck, Ribich, and Ramanaiah in 1977 as a self-report inventory to assess learning style through a behavioral-oriented approach. The ILP was revised by Schmeck in 1983. The Revised ILP contains six scales: (1) Deep Processing; (2) Elaborative Processing; (3) Shallow Processing; (4)…
Frederiksen, Signe Hedeboe
Entrepreneurial process increasingly attracts attention as an opportunity to learn in higher education. Students learn “through” enterprise, when they actively engage in an entrepreneurial process while reflecting on their actions and experiences. In this qualitative field study, I investigate how...... postgraduate students pursued opportunities to learn in a process-driven entrepreneurship module. Drawing on situated learning theory, I find that students tried to access learning opportunities through a constant dynamic of participation which involved contradictory participatory stances. The learning through...... paradigm in enterprise education imposes conditions on the learning environment and involves images of a particular learner, who is able to take advantage of this learning opportunity. The findings indicate a contradictory process of becoming a legitimate entrepreneurial learner which is more uncertain...
Trewartha, Kevin M.; Garcia, Angeles; Wolpert, Daniel M.
Motor learning has been shown to depend on multiple interacting learning processes. For example, learning to adapt when moving grasped objects with novel dynamics involves a fast process that adapts and decays quickly—and that has been linked to explicit memory—and a slower process that adapts and decays more gradually. Each process is characterized by a learning rate that controls how strongly motor memory is updated based on experienced errors and a retention factor determining the movement-to-movement decay in motor memory. Here we examined whether fast and slow motor learning processes involved in learning novel dynamics differ between younger and older adults. In addition, we investigated how age-related decline in explicit memory performance influences learning and retention parameters. Although the groups adapted equally well, they did so with markedly different underlying processes. Whereas the groups had similar fast processes, they had different slow processes. Specifically, the older adults exhibited decreased retention in their slow process compared with younger adults. Within the older group, who exhibited considerable variation in explicit memory performance, we found that poor explicit memory was associated with reduced retention in the fast process, as well as the slow process. These findings suggest that explicit memory resources are a determining factor in impairments in the both the fast and slow processes for motor learning but that aging effects on the slow process are independent of explicit memory declines. PMID:25274819
Trewartha, Kevin M; Garcia, Angeles; Wolpert, Daniel M; Flanagan, J Randall
Motor learning has been shown to depend on multiple interacting learning processes. For example, learning to adapt when moving grasped objects with novel dynamics involves a fast process that adapts and decays quickly-and that has been linked to explicit memory-and a slower process that adapts and decays more gradually. Each process is characterized by a learning rate that controls how strongly motor memory is updated based on experienced errors and a retention factor determining the movement-to-movement decay in motor memory. Here we examined whether fast and slow motor learning processes involved in learning novel dynamics differ between younger and older adults. In addition, we investigated how age-related decline in explicit memory performance influences learning and retention parameters. Although the groups adapted equally well, they did so with markedly different underlying processes. Whereas the groups had similar fast processes, they had different slow processes. Specifically, the older adults exhibited decreased retention in their slow process compared with younger adults. Within the older group, who exhibited considerable variation in explicit memory performance, we found that poor explicit memory was associated with reduced retention in the fast process, as well as the slow process. These findings suggest that explicit memory resources are a determining factor in impairments in the both the fast and slow processes for motor learning but that aging effects on the slow process are independent of explicit memory declines. Copyright © 2014 the authors 0270-6474/14/3413411-11$15.00/0.
Lessons learned from the London Exercise and Pregnant (LEAP) Smokers randomised controlled trial process evaluation: implications for the design of physical activity for smoking cessation interventions during pregnancy.
Giatras, Nikoletta; Wanninkhof, Elisabeth; Leontowitsch, Miranda; Lewis, Beth; Taylor, Adrian; Cooper, Sue; Ussher, Michael
The challenges of delivering interventions for pregnant smokers have been poorly documented. Also, the process of promoting a physical activity intervention for pregnant smokers has not been previously recorded. This study describes the experiences of researchers conducting a randomised controlled trial of physical activity as an aid to smoking cessation during pregnancy and explores how the effectiveness of future interventions could be improved. Two focus groups, with independent facilitators, were conducted with six researchers who had enrolled pregnant smokers in the LEAP trial, provided the interventions, and administered the research measures. Topics included recruitment, retention and how the physical activity intervention for pregnant smokers was delivered and how it was adapted when necessary to suit the women. The focus groups were audio-recorded, transcribed verbatim and subjected to thematic analysis. Five themes emerged related to barriers or enablers to intervention delivery: (1) nature of the intervention; (2) personal characteristics of trial participants; (3) practical issues; (4) researchers' engagement with participants; (5) training and support needs. Researchers perceived that participants may have been deterred by the intensive and generic nature of the intervention and the need to simultaneously quit smoking and increase physical activity. Women also appeared hampered by pregnancy ailments, social deprivation, and poor mental health. Researchers observed that their status as health professionals was valued by participants but it was challenging to maintain contact with participants. Training and support needs were identified for dealing with pregnant teenagers, participants' friends and family, and post-natal return to smoking. Future exercise interventions for smoking cessation in pregnancy may benefit by increased tailoring of the intervention to the characteristics of the women, including their psychological profile, socio
Lessons learned from the London Exercise and Pregnant (LEAP Smokers randomised controlled trial process evaluation: implications for the design of physical activity for smoking cessation interventions during pregnancy
Full Text Available Abstract Background The challenges of delivering interventions for pregnant smokers have been poorly documented. Also, the process of promoting a physical activity intervention for pregnant smokers has not been previously recorded. This study describes the experiences of researchers conducting a randomised controlled trial of physical activity as an aid to smoking cessation during pregnancy and explores how the effectiveness of future interventions could be improved. Methods Two focus groups, with independent facilitators, were conducted with six researchers who had enrolled pregnant smokers in the LEAP trial, provided the interventions, and administered the research measures. Topics included recruitment, retention and how the physical activity intervention for pregnant smokers was delivered and how it was adapted when necessary to suit the women. The focus groups were audio-recorded, transcribed verbatim and subjected to thematic analysis. Results Five themes emerged related to barriers or enablers to intervention delivery: (1 nature of the intervention; (2 personal characteristics of trial participants; (3 practical issues; (4 researchers’ engagement with participants; (5 training and support needs. Researchers perceived that participants may have been deterred by the intensive and generic nature of the intervention and the need to simultaneously quit smoking and increase physical activity. Women also appeared hampered by pregnancy ailments, social deprivation, and poor mental health. Researchers observed that their status as health professionals was valued by participants but it was challenging to maintain contact with participants. Training and support needs were identified for dealing with pregnant teenagers, participants’ friends and family, and post-natal return to smoking. Conclusions Future exercise interventions for smoking cessation in pregnancy may benefit by increased tailoring of the intervention to the characteristics of the
Bao Jianzhong; Chen Xiulan; Cao Hong; Zhai Jianqing
Based on the irradiation processing practice of the nuclear technique application laboratory of Yangzhou Institute of Agricultural Science, the quality control of irradiation processing products is discussed
Apfelbaum, Keith S.; McMurray, Bob
Previous research on associative learning has uncovered detailed aspects of the process, including what types of things are learned, how they are learned, and where in the brain such learning occurs. However, perceptual processes, such as stimulus recognition and identification, take time to unfold. Previous studies of learning have not addressed when, during the course of these dynamic recognition processes, learned representations are formed and updated. If learned representations are formed and updated while recognition is ongoing, the result of learning may incorporate spurious, partial information. For example, during word recognition, words take time to be identified, and competing words are often active in parallel. If learning proceeds before this competition resolves, representations may be influenced by the preliminary activations present at the time of learning. In three experiments using word learning as a model domain, we provide evidence that learning reflects the ongoing dynamics of auditory and visual processing during a learning event. These results show that learning can occur before stimulus recognition processes are complete; learning does not wait for ongoing perceptual processing to complete. PMID:27471082
Bernard, J.A.; Aviles, B.N.; Lanning, D.D.
Lessons learned during the course of the now decade-old MIT program on the digital control of nuclear reactors are enumerated. Relative to controller structure, these include the importance of a separate safety system, the need for signal validation, the role of supervisory algorithms, the significance of command validation, and the relevance of automated reasoning. Relative to controller implementation, these include the value of nodal methods to the creation of real-time reactor physics and thermal hydraulic models, the advantages to be gained from the use of real-time system models, and the importance of a multi-tiered structure to the simultaneous achievement of supervisory, global, and local control. Block diagrams are presented of proposed controllers and selected experimental and simulation-study results are shown. In addition, a history is given of the MIT program on reactor digital control
Concurrent Learning of Control in Multi-agent Sequential Decision Tasks The overall objective of this project was to develop multi-agent reinforcement... learning (MARL) approaches for intelligent agents to autonomously learn distributed control policies in decentral- ized partially observable... learning of policies in Dec-POMDPs, established performance bounds, evaluated these algorithms both theoretically and empirically, The views
The 21st IEEE International Workshop on Machine Learning for Signal Processing will be held in Beijing, China, on September 18–21, 2011. The workshop series is the major annual technical event of the IEEE Signal Processing Society's Technical Committee on Machine Learning for Signal Processing...
The integration of agricultural and science curricular content that capitalizes on natural and inherent connections represents a challenge for secondary agricultural educators. The purpose of this case study was to create information about the employment of Cooperative Learning Groups (CLG) to enhance the science integrating learning objectives…
Kuldas, Seffetullah; Ismail, Hairul Nizam; Hashim, Shahabuddin; Bakar, Zainudin Abu
This review aims to provide an insight into human learning processes by examining the role of cognitive and emotional unconscious processing in mentally integrating visual and verbal instructional materials. Reviewed literature shows that conscious mental integration does not happen all the time, nor does it necessarily result in optimal learning. Students of all ages and levels of experience cannot always have conscious awareness, control, and the intention to learn or promptly and continually organize perceptual, cognitive, and emotional processes of learning. This review suggests considering the role of unconscious learning processes to enhance the understanding of how students form or activate mental associations between verbal and pictorial information. The understanding would assist in presenting students with spatially-integrated verbal and pictorial instructional materials as a way of facilitating mental integration and improving teaching and learning performance.
Chowdhary, Girish; Kingravi, Hassan A; How, Jonathan P; Vela, Patricio A
Most current model reference adaptive control (MRAC) methods rely on parametric adaptive elements, in which the number of parameters of the adaptive element are fixed a priori, often through expert judgment. An example of such an adaptive element is radial basis function networks (RBFNs), with RBF centers preallocated based on the expected operating domain. If the system operates outside of the expected operating domain, this adaptive element can become noneffective in capturing and canceling the uncertainty, thus rendering the adaptive controller only semiglobal in nature. This paper investigates a Gaussian process-based Bayesian MRAC architecture (GP-MRAC), which leverages the power and flexibility of GP Bayesian nonparametric models of uncertainty. The GP-MRAC does not require the centers to be preallocated, can inherently handle measurement noise, and enables MRAC to handle a broader set of uncertainties, including those that are defined as distributions over functions. We use stochastic stability arguments to show that GP-MRAC guarantees good closed-loop performance with no prior domain knowledge of the uncertainty. Online implementable GP inference methods are compared in numerical simulations against RBFN-MRAC with preallocated centers and are shown to provide better tracking and improved long-term learning.
Douglas, Elliot P.; Chiu, Chu-Chuan
This paper describes implementation and testing of an active learning, team-based pedagogical approach to instruction in engineering. This pedagogy has been termed Process Oriented Guided Inquiry Learning (POGIL), and is based upon the learning cycle model. Rather than sitting in traditional lectures, students work in teams to complete worksheets…
Martens, Herm; Nagtzaam, Ivo; Heeneman, Sylvia
Objectives To obtain a deeper understanding of how the e-learning program, Education in Dermatology (ED), affects the acquisition of dermatological knowledge and the underlying learning processes of medical students in their clinical phase. Methods The study used a mixed method design with a convergent parallel collection of data. Medical students (n=62) from Maastricht University (The Netherlands) were randomized to either a conventional teaching group (control group n=30) or conventional teaching plus the e-learning program (application on smartphone) group (e-learning group n=32). Pre- and post-intervention knowledge test results were analysed using an independent t-test. Individual semi-structured interviews (n=9) were conducted and verbatim-transcribed recordings were analysed using King’s template analysis. Results The e-learning program positively influenced students’ level of knowledge and their process of learning. A significant difference was found in the post-test scores for the control group (M=51.4, SD=6.43) and the e-learning group (M=73.09, SD=5.12); t(60)=-14.75, pe-learning program stimulated students’ learning as the application promoted the identification and recognition of skin disorders, the use of references, creation of documents and sharing information with colleagues. Conclusions This study demonstrated that use of the e-learning program led to a significant improvement in basic dermatological knowledge. The underlying learning processes indicated that e-learning programs in dermatology filled a vital gap in the understanding of clinical reasoning in dermatology. These results might be useful when developing (clinical) teaching formats with a special focus on visual disciplines. PMID:29352748
Fransen, Frederike; Martens, Herm; Nagtzaam, Ivo; Heeneman, Sylvia
To obtain a deeper understanding of how the e-learning program, Education in Dermatology (ED), affects the acquisition of dermatological knowledge and the underlying learning processes of medical students in their clinical phase. The study used a mixed method design with a convergent parallel collection of data. Medical students (n=62) from Maastricht University (The Netherlands) were randomized to either a conventional teaching group (control group n=30) or conventional teaching plus the e-learning program (application on smartphone) group (e-learning group n=32). Pre- and post-intervention knowledge test results were analysed using an independent t-test. Individual semi-structured interviews (n=9) were conducted and verbatim-transcribed recordings were analysed using King's template analysis. The e-learning program positively influenced students' level of knowledge and their process of learning. A significant difference was found in the post-test scores for the control group (M=51.4, SD=6.43) and the e-learning group (M=73.09, SD=5.12); t(60)=-14.75, pe-learning program stimulated students' learning as the application promoted the identification and recognition of skin disorders, the use of references, creation of documents and sharing information with colleagues. This study demonstrated that use of the e-learning program led to a significant improvement in basic dermatological knowledge. The underlying learning processes indicated that e-learning programs in dermatology filled a vital gap in the understanding of clinical reasoning in dermatology. These results might be useful when developing (clinical) teaching formats with a special focus on visual disciplines.
Cheng, Jie; Qian, Zhaogang; Irani, Keki B.; Etemad, Hossein; Elta, Michael E.
To meet the ever-increasing demand of the rapidly-growing semiconductor manufacturing industry it is critical to have a comprehensive methodology integrating techniques for process optimization real-time monitoring and adaptive process control. To this end we have accomplished an integrated knowledge-based approach combining latest expert system technology machine learning method and traditional statistical process control (SPC) techniques. This knowledge-based approach is advantageous in that it makes it possible for the task of process optimization and adaptive control to be performed consistently and predictably. Furthermore this approach can be used to construct high-level and qualitative description of processes and thus make the process behavior easy to monitor predict and control. Two software packages RIST (Rule Induction and Statistical Testing) and KARSM (Knowledge Acquisition from Response Surface Methodology) have been developed and incorporated with two commercially available packages G2 (real-time expert system) and ULTRAMAX (a tool for sequential process optimization).
Full Text Available Youth of all ages are indicating an interest in starting a business. However, few classes on business start-up and management are available. Young people who are actively engaged in learning business management concepts also develop life skills such as decision making, communicating, and learning to learn. Studies have shown that youth who are in participatory, entrepreneurship classes develop a positive attitude toward starting a business. This article addresses how the experiential learning model provides an opportunity for youth to develop entrepreneurial skills. The entrepreneurial learning model is a learning process of doing, reflecting, and then applying.
Buerger, L.; Gossanyi, A.; Parkanyi, T.; Szabo, G.; Vegh, E.
A multiprocessor process control system is described. During its development the reliability was the most important aspect because it is used in the computerized control of a 5 MW research reactor. DUAL-PROCESS is fully compatible with the earlier single processor control system PROCESS-24K. The paper deals in detail with the communication, synchronization, error detection and error recovery problems of the operating system. (author)
Weitze, Charlotte Lærke
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...
Weitze, Charlotte Lærke
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...
Ringtved, Ulla L.; Miligan, Sandra; Corrin, Linda
Design for teaching in scaled courses is shifting away from replication of the traditional on-campus or online teaching-learning relationship towards exploiting the distinctive characteristic and potentials of that environment to transform both teaching and learning. This involves consideration...... design and would benefit from learning analytics support? What is the character of analytics that can be deployed to help deliver good design of online learning platforms? What are the theoretical and pedagogical bases inherent in different analytics designs? These and other questions will be examined...
Full Text Available The main objective of this paper is to design a cost effective controller for real time implementation of pressure process using Infineon micro controller (SAB 80C517A. Model Identification is performed and it is found to be First Order Plus Dead Time Process (FOPDT. The performance measure is tabulated for different parameter and it is found that Proportional (P controller is suitable for controlling the process.
Schreurs, Jeanne; Al-Huneidi, Ahmad
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...
Full Text Available Complex Event Processing (CEP has become the key part of Internet of Things (IoT. Proactive CEP can predict future system states and execute some actions to avoid unwanted states which brings new hope to intelligent transportation control. In this paper, we propose a proactive CEP architecture and method for intelligent transportation control. Based on basic CEP technology and predictive analytic technology, a networked distributed Markov decision processes model with predicting states is proposed as sequential decision model. A Q-learning method is proposed for this model. The experimental evaluations show that this method works well when used to control congestion in in intelligent transportation systems.
Bersimis, Sotiris; Psarakis, Stelios; Panaretos, John
In this paper we discuss the basic procedures for the implementation of multivariate statistical process control via control charting. Furthermore, we review multivariate extensions for all kinds of univariate control charts, such as multivariate Shewhart-type control charts, multivariate CUSUM control charts and multivariate EWMA control charts. In addition, we review unique procedures for the construction of multivariate control charts, based on multivariate statistical techniques such as p...
Lev-Ari, L; Hirschmann, S; Dyskin, O; Goldman, O; Hirschmann, I
The Rubber Hand Illusion (RHI) has previously been used to depict the hierarchy between visual, tactile and perceptual stimuli. Studies on schizophrenia inpatients (SZs) have found mixed results in the ability to first learn the illusion, and have yet to explain the learning process involved. This study's aim was two-fold: to examine the learning process of the RHI in SZs and healthy controls over time, and to better understand the relationship between psychotic symptoms and the RHI. Thirty schizophrenia inpatients and 30 healthy controls underwent five different trials of the RHI over a two-week period. As has been found in previous studies, SZs felt the initial illusion faster than healthy controls did, but their learning process throughout the trials was inconsistent. Furthermore, for SZs, no correlations between psychotic symptoms and the learning of the illusion emerged. Healthy individuals show a delayed reaction to first feeling the illusion (due to latent inhibition), but easily learn the illusion over time. For SZs, both strength of the illusion and the ability to learn the illusion over time are inconsistent. The cognitive impairment in SZ impedes the learning process of the RHI, and SZs are unable to utilize the repetition of the process as healthy individuals can. Copyright © 2015 Elsevier Masson SAS. All rights reserved.
Harvard Univ., Cambridge, MA. Graduate School of Education.
THIS SUPPLEMENTARY BIBLIOGRAPHY LISTS MATERIALS ON VARIOUS FACETS OF HUMAN LEARNING. APPROXIMATELY 60 UNANNOTATED REFERENCES ARE PROVIDED FOR DOCUMENTS DATING FROM 1954 TO 1966. JOURNAL ARTICLES, BOOKS, RESEARCH REPORTS, AND CONFERENCE PAPERS ARE LISTED. SOME SUBJECT AREAS INCLUDED ARE (1) LEARNING PARAMETERS AND ABILITY, (2) RETENTION AND…
Colardyn, Danielle; White, Kathleen M.
From a search of (mostly French) literature, a hypothesis was formulated that students with both academic training and work experience would solve a practical learning problem more easily than students with academic learning only. A study was conducted at the Conservatoire National des Arts et Metiers in Paris to test this hypothesis. Two groups,…
McDougle, Samuel D; Bond, Krista M; Taylor, Jordan A
A popular model of human sensorimotor learning suggests that a fast process and a slow process work in parallel to produce the canonical learning curve (Smith et al., 2006). Recent evidence supports the subdivision of sensorimotor learning into explicit and implicit processes that simultaneously subserve task performance (Taylor et al., 2014). We set out to test whether these two accounts of learning processes are homologous. Using a recently developed method to assay explicit and implicit learning directly in a sensorimotor task, along with a computational modeling analysis, we show that the fast process closely resembles explicit learning and the slow process approximates implicit learning. In addition, we provide evidence for a subdivision of the slow/implicit process into distinct manifestations of motor memory. We conclude that the two-state model of motor learning is a close approximation of sensorimotor learning, but it is unable to describe adequately the various implicit learning operations that forge the learning curve. Our results suggest that a wider net be cast in the search for the putative psychological mechanisms and neural substrates underlying the multiplicity of processes involved in motor learning. Copyright © 2015 the authors 0270-6474/15/359568-12$15.00/0.
Yata, Chikahiko; Hamamoto, Kengo; Oguri, Takenori
This study analyzed the learning activities in a textbook on technology education for teachers, in order to examine the learning processes and learning scenes detailed therein. Results of analyzing learning process, primary learning activity found each contents framework. Other learning activities designated to be related to complementary in learning process. Results of analyzing learning scene, 14 learning scenes, among them "Scene to recognize the impact on social life and progress of techn...
Wieringa, Jakob Edo
Statistical Process Control (SPC) aims at quality improvement through reduction of variation. The best known tool of SPC is the control chart. Over the years, the control chart has proved to be a successful practical technique for monitoring process measurements. However, its usefulness in practice
On June 4th, 2009, the third Dutch Process Control Security Event took place in Amsterdam. The event, organised by the Dutch National Infrastructure against Cybercrime (NICC), attracted both Dutch process control experts and members of the European SCADA and Control Systems Information Exchange
Jantzen, Jan; Verbruggen, Henk; Østergaard, Jens-Jørgen
Control problems in the process industry are dominated by non-linear and time-varying behaviour, many inner loops, and much interaction between the control loops. Fuzzy controllers have in some cases nevertheless mimicked the control actions of a human operator. Simple fuzzy controllers can...... be designed starting from PID controllers, and in more complex cases these can be used in connection with model-based predictive control. For high level control and supervisory control several simple controllers can be combined in a priority hierarchy such as the one developed in the cement industry...
Barnard, Julie; Carleton, Anita; Stamper, Darrell E. (Technical Monitor)
This paper presents a cooperative effort where the Software Engineering Institute and the Space Shuttle Onboard Software Project could experiment applying Statistical Process Control (SPC) analysis to inspection activities. The topics include: 1) SPC Collaboration Overview; 2) SPC Collaboration Approach and Results; and 3) Lessons Learned.
This paper concerns the application of Process Control Techniques (PCTs) for the improvement of the technical performance of discrete production processes. Successful applications of these techniques, such as Statistical Process Control Techniques (SPC), can be found in the literature. However, some
Wind erosion continues to threaten the sustainability of our nations' soil, air, and water resources. To effectively apply conservation systems to prevent wind driven soil loss, an understanding of the fundamental processes of wind erosion is necessary so that land managers can better recognize the ...
Sriskandarajah, Nadarajah; Cerf, Marianne; Noe, Egon
As an introduction to the workshop where 18 papers and posters were presented on the theme of ‘Learning as a Process’, the linked nature of the learning – knowing – acting field in rural development in Europe is emphasised. The workshop took up the issues of human interactions in foster learning...... processes, capacity building and development of collective action as a bottom-up process....
Bhusry, Mamta; Ranjan, Jayanthi
Purpose: The purpose of this paper is to emphasize the need for knowledge management (KM) in the teaching-learning process in technical educational institutions (TEIs) in India, and to assert the impact of information technology (IT) based KM intervention in the teaching-learning process. Design/methodology/approach: The approach of the paper is…
Berends, J.J.; Lammers, I.S.
This paper offers a process analysis of organizational learning as it unfolds in a social and temporal context. Building upon the 4I framework (Crossan et al. 1999), we examine organizational learning processes in a longitudinal case study of an implementation of knowledge management in an
Berends, J.J.; Lammers, I.S.
In this paper we analyze the process characteristics of organizational learning. A wide variety of process models of organizational learning have been proposed in the literature, but these models have not been systematically investigated. In this paper we use Van de Ven and Poole's (1995) taxonomy
Martínez Muñoz, Miriam; Jiménez Rodríguez, María Lourdes; Gutiérrez de Mesa, José Antonio
This work is part of a research project whose main objective is to understand the impact that the use of Information and Communication Technology (ICT) has on the teaching and learning process on the subject of Physics. We will show that, with the use of a storm simulator, physics students improve their learning process on one hand they understand…
Full Text Available To be successful at manipulating objects one needs to apply simultaneously well controlled movements and contact forces. We present a computational theory of how the brain may successfully generate a vast spectrum of interactive behaviors by combining two independent processes. One process is competent to control movements in free space and the other is competent to control contact forces against rigid constraints. Free space and rigid constraints are singularities at the boundaries of a continuum of mechanical impedance. Within this continuum, forces and motions occur in compatible pairs connected by the equations of Newtonian dynamics. The force applied to an object determines its motion. Conversely, inverse dynamics determine a unique force trajectory from a movement trajectory. In this perspective, we describe motor learning as a process leading to the discovery of compatible force/motion pairs. The learned compatible pairs constitute a local representation of the environment's mechanics. Experiments on force field adaptation have already provided us with evidence that the brain is able to predict and compensate the forces encountered when one is attempting to generate a motion. Here, we tested the theory in the dual case, i.e. when one attempts at applying a desired contact force against a simulated rigid surface. If the surface becomes unexpectedly compliant, the contact point moves as a function of the applied force and this causes the applied force to deviate from its desired value. We found that, through repeated attempts at generating the desired contact force, subjects discovered the unique compatible hand motion. When, after learning, the rigid contact was unexpectedly restored, subjects displayed after effects of learning, consistent with the concurrent operation of a motion control system and a force control system. Together, theory and experiment support a new and broader view of modularity in the coordinated control of forces and
Portal monitors are an important part of the material protection, control, and accounting (MPC and A) programs in Russia and the US. Although portal monitors are only a part of an integrated MPC and A system, they are an effective means of controlling the unauthorized movement of special nuclear material (SNM). Russian technical experts have gained experience in the use of SNM portal monitors from US experts ad this has allowed them to use the monitors more effectively. Several Russian institutes and companies are designing and manufacturing SNM portal monitors in Russia. Interactions between Russian and US experts have resulted in improvements to the instruments. SNM portal monitor technology has been effectively transferred from the US to Russia and should be a permanent part of the Russian MPC and A Program. Progress in the implementation of the monitors and improvements to how they are used are discussed
Dimitrieva, Evica; Atanasova-Pacemska, Tatjana; Pacemska, Sanja
This paper is based on the research of the technological process of automatic filling of bottles of wine in winery in Stip, Republic of Macedonia. The statistical process control using statistical control card is created. The results and recommendations for improving the process are discussed.
Genio, Anthony Del
As background for consideration of the climates of the other terrestrial planets in our solar system and the potential habitability of rocky exoplanets, we discuss the basic physics that controls the Earths present climate, with particular emphasis on the energy and water cycles. We define several dimensionless parameters relevant to characterizing a planets general circulation, climate and hydrological cycle. We also consider issues associated with the use of past climate variations as indicators of future anthropogenically forced climate change, and recent advances in understanding projections of future climate that might have implications for Earth-like exoplanets.
Christensen, Ann-Dorte; Rasmussen, Palle
In this article democratic learning is conceptualised with inspiration from two academic traditions, one being the conceptions of citizenship, political identities and deliberative democracy in political sociology; the other theories and research on social and lifelong learning. The first part......'s empowerment and inclusion in the Danish democratic model. On the background of these two analyses the authors finally discuss some current democratic problems with integrating the diversity represented by ethnic minority groups. The discussion emphasizes the learning theory perspective on the initiative...... of the article outlines the authors' understanding of the core concepts involved. In the second part these conceptual discussions are related to two themes: the question of public adaptation of historical experiences in connection with the German reunification and the learning perspectives related to women...
Mnih, Volodymyr; Kavukcuoglu, Koray; Silver, David; Rusu, Andrei A.; Veness, Joel; Bellemare, Marc G.; Graves, Alex; Riedmiller, Martin; Fidjeland, Andreas K.; Ostrovski, Georg; Petersen, Stig; Beattie, Charles; Sadik, Amir; Antonoglou, Ioannis; King, Helen; Kumaran, Dharshan; Wierstra, Daan; Legg, Shane; Hassabis, Demis
The theory of reinforcement learning provides a normative account, deeply rooted in psychological and neuroscientific perspectives on animal behaviour, of how agents may optimize their control of an environment. To use reinforcement learning successfully in situations approaching real-world complexity, however, agents are confronted with a difficult task: they must derive efficient representations of the environment from high-dimensional sensory inputs, and use these to generalize past experience to new situations. Remarkably, humans and other animals seem to solve this problem through a harmonious combination of reinforcement learning and hierarchical sensory processing systems, the former evidenced by a wealth of neural data revealing notable parallels between the phasic signals emitted by dopaminergic neurons and temporal difference reinforcement learning algorithms. While reinforcement learning agents have achieved some successes in a variety of domains, their applicability has previously been limited to domains in which useful features can be handcrafted, or to domains with fully observed, low-dimensional state spaces. Here we use recent advances in training deep neural networks to develop a novel artificial agent, termed a deep Q-network, that can learn successful policies directly from high-dimensional sensory inputs using end-to-end reinforcement learning. We tested this agent on the challenging domain of classic Atari 2600 games. We demonstrate that the deep Q-network agent, receiving only the pixels and the game score as inputs, was able to surpass the performance of all previous algorithms and achieve a level comparable to that of a professional human games tester across a set of 49 games, using the same algorithm, network architecture and hyperparameters. This work bridges the divide between high-dimensional sensory inputs and actions, resulting in the first artificial agent that is capable of learning to excel at a diverse array of challenging tasks.
Mnih, Volodymyr; Kavukcuoglu, Koray; Silver, David; Rusu, Andrei A; Veness, Joel; Bellemare, Marc G; Graves, Alex; Riedmiller, Martin; Fidjeland, Andreas K; Ostrovski, Georg; Petersen, Stig; Beattie, Charles; Sadik, Amir; Antonoglou, Ioannis; King, Helen; Kumaran, Dharshan; Wierstra, Daan; Legg, Shane; Hassabis, Demis
The theory of reinforcement learning provides a normative account, deeply rooted in psychological and neuroscientific perspectives on animal behaviour, of how agents may optimize their control of an environment. To use reinforcement learning successfully in situations approaching real-world complexity, however, agents are confronted with a difficult task: they must derive efficient representations of the environment from high-dimensional sensory inputs, and use these to generalize past experience to new situations. Remarkably, humans and other animals seem to solve this problem through a harmonious combination of reinforcement learning and hierarchical sensory processing systems, the former evidenced by a wealth of neural data revealing notable parallels between the phasic signals emitted by dopaminergic neurons and temporal difference reinforcement learning algorithms. While reinforcement learning agents have achieved some successes in a variety of domains, their applicability has previously been limited to domains in which useful features can be handcrafted, or to domains with fully observed, low-dimensional state spaces. Here we use recent advances in training deep neural networks to develop a novel artificial agent, termed a deep Q-network, that can learn successful policies directly from high-dimensional sensory inputs using end-to-end reinforcement learning. We tested this agent on the challenging domain of classic Atari 2600 games. We demonstrate that the deep Q-network agent, receiving only the pixels and the game score as inputs, was able to surpass the performance of all previous algorithms and achieve a level comparable to that of a professional human games tester across a set of 49 games, using the same algorithm, network architecture and hyperparameters. This work bridges the divide between high-dimensional sensory inputs and actions, resulting in the first artificial agent that is capable of learning to excel at a diverse array of challenging tasks.
Higgins, Ronald C.; Messer, George H.
Two applications of statistical process control to the process of education are described. Discussed are the use of prompt feedback to teachers and prompt feedback to students. A sample feedback form is provided. (CW)
"Concepts like Taylorism, lean production and learning organisation draw attention to the point that work organisation can appear in different forms and it is generally recognised that different conditions tend to produce different forms. Still, there is a tendency to underplay how different these generative conditions are. In this article the issue of learning organisation is placed in focus, drawing upon experiences from Scandinavian workplace development programmes. These...
Mosca, Joseph B.; Agacer, Gilder; Flaming, Linda; Buzza, John
Assurance of learning process plays a major role in higher education and has increased the accountability on the part of instructors at all levels. This paper will discuss the role of assurance processes in teaching and the ways to measure these processes of student learning. The research focus will be to determine if student engagement in problem…
The primary purpose of this document is to describe the overall process control strategy for monitoring and controlling the functions associated with the Phase 1B high-level waste feed delivery. This document provides the basis for process monitoring and control functions and requirements needed throughput the double-shell tank system during Phase 1 high-level waste feed delivery. This document is intended to be used by (1) the developers of the future Process Control Plan and (2) the developers of the monitoring and control system
Wu, Yun-Wu; Weng, Kuo-Hua; Young, Li-Ming
Generally, in the foundation course of architectural design, much emphasis is placed on teaching of the basic design skills without focusing on teaching students to apply the basic design concepts in their architectural designs or promoting students' own creativity. Therefore, this study aims to propose a concept transformation learning model to…
Wang, Mu-Hao; Hung, Yung-Tse; Shammas, Nazih
This edited book has been designed to serve as a natural resources engineering reference book as well as a supplemental textbook. This volume is part of the Handbook of Environmental Engineering series, an incredible collection of methodologies that study the effects of pollution and waste in their three basic forms: gas, solid, and liquid. It complements two other books in the series including Environmental and Natural Resources Engineering and Integrated Natural Resources Management that serve as a basis for advanced study or specialized investigation of the theory and analysis of various natural resources systems. This book covers the management of many waste sources including those from agricultural livestock, deep-wells, industries manufacturing dyes, and municipal solid waste incinerators. The purpose of this book is to thoroughly prepare the reader for understanding the sources, treatment and control methods of toxic wastes shown to have harmful effects on the environment. Chapters provide information ...
Full Text Available The tools for quality management are used for quality improvement throughout the whole Europe and developed countries. Simple statistics are considered one of the most basic methods. The goal was to apply the simple statistical methods to practice and to solve problems by using them. Selected methods are used for processing the list of internal discrepancies within the organization, and for identification of the root cause of the problem and its appropriate solution. Seven basic quality tools are simple graphical tools, but very effective in solving problems related to quality. They are called essential because they are suitable for people with at least basic knowledge in statistics; therefore, they can be used to solve the vast majority of problems.
Coedo, A.G.; Dorado, M.T.; Padilla, I.
This paper illustrates the role of analysis in enabling metallurgical industry to meet quality demands. For example, for the steel industry the demands by the automotive, aerospace, power generation, tinplate packaging industries and issue of environment near steel plants. Although chemical analysis technology continues to advance, achieving improved speed, precision and accuracy at lower levels of detection, the competitiveness of manufacturing industry continues to drive property demands at least at the same rate. Narrower specification ranges, lower levels of residual elements and economic pressures prescribe faster process routes, all of which lead to increased demands on the analytical function. These damands are illustrated by examples from several market sectors in which customer issues are considered together with ther analytical implications. (Author) 5 refs
Ku, David Tawei; Huang, Yung-Hsin
This study developed a decision making process for the selection of rapid e-learning tools that could match different learning domains. With the development of the Internet, the speed of information updates has become faster than ever. E-learning has rapidly become the mainstream for corporate training and academic instruction. In order to reduce…
May, Gary S
A practical guide to semiconductor manufacturing from process control to yield modeling and experimental design Fundamentals of Semiconductor Manufacturing and Process Control covers all issues involved in manufacturing microelectronic devices and circuits, including fabrication sequences, process control, experimental design, process modeling, yield modeling, and CIM/CAM systems. Readers are introduced to both the theory and practice of all basic manufacturing concepts. Following an overview of manufacturing and technology, the text explores process monitoring methods, including those that focus on product wafers and those that focus on the equipment used to produce wafers. Next, the text sets forth some fundamentals of statistics and yield modeling, which set the foundation for a detailed discussion of how statistical process control is used to analyze quality and improve yields. The discussion of statistical experimental design offers readers a powerful approach for systematically varying controllable p...
Fosshage, Erik D
This report examines the lessons learned process by a review of the literature in a variety of disciplines, and is intended as a guidepost for organizations that are considering the implementation of their own closed-loop learning process. Lessons learned definitions are provided within the broader context of knowledge management and the framework of a learning organization. Shortcomings of existing practices are summarized in an attempt to identify common pitfalls that can be avoided by organizations with fledgling experiences of their own. Lessons learned are then examined through a dual construct of both process and mechanism, with emphasis on integrating into organizational processes and promoting lesson reuse through data attributes that contribute toward changed behaviors. The report concludes with recommended steps for follow-on efforts.
Barzin, R.; Abd Shukor, S.R.; Ahmad, A.L.
Process Intensification (PI) is a revolutionary approach to design, development and implementation of process and plant. PI technology offers improved environment in a chemical process in terms of better products, and processes which are safer, cleaner, smaller - and cheaper. PI is a strategy of making dramatic reductions in the size of unit operations within chemical plants, in order to achieve given production objectives. However, PI technology would be handicapped if such system is not properly controlled. There are some foreseeable problems in order to control such processes for instance, dynamic interaction between components that make up a control loop, response time of the instrumentations, availability of proper sensor and etc. In some cases, in order to control these systems, advanced control solutions have been applied i.e. model predictive controllers (MPC) and its different algorithms such as quadratic generalized predictive control (QGPC) and self tuning quadratic generalized predictive control (STQGPC). Nevertheless in some cases simpler solutions could be applied to control such system for example proportional integral controller in the control of reactive distillation systems. As mentioned, conventional control systems like proportional-integral, proportional-integral-derivative (PID) controllers and their different structures can be used in PI systems but due to inherent nonlinearity and fast responsiveness of PI systems, digital controllers-regarding to their robustness-are mostly applied in order to control PI systems. Regarding to the fact that choosing the appropriate control strategy is the most essential part of making PI systems possible to be handle easily, taxonomy of the usage of various control structure in controlling PI systems is proposed. This paper offers an overview and discussion on identifying potential problems of instrumentation in PI technology and available control strategies
Minewater is a subset of groundwater, subject to broadly similar hydrochemical processes. In 'normal' groundwaters, access to oxidizing species is poor and acid-base reactions tend to dominate over oxidation reactions. Acid-base reactions such as carbonate dissolution and silicate hydrolysis consume protons and carbon dioxide, and release alkalinity and base cations. In mines, the atmospheric environment is rapidly introduced to the deep reducing geosphere (or vice versa in the case of mine waste deposits). This carries the possibility of intense and rapid oxidation of sulphide minerals such as pyrite, to such an extent that these acid-generating redox reactions may dominate over acid-base 'neutralization' reactions and result in the phenomenon of 'acid rock drainage' (ARD). In ARD, a negative correlation is typically observed between pH and concentrations of many metals and metalloids, base cations and sulphate. This correlation is due to genetic co-variation - generation of protons, sulphate and metals in sulphide weathering reactions, pH-dependent solubility of many ARD-related metals and low pH intensifying carbonate dissolution and silicate hydrolysis to release aluminium, silica and base cations. This paper examines the reactions involved in ARD generation and neutralization, and attempts to clarify key concepts such as pH, Eh, alkalinity, acidity and equilibrium constants. Refs. 42 (author)
Wang, Z.; Shao, S.; Ding, J.
This paper proposes a new method for learning and tuning Fuzzy Logic Controllers. The self-learning scheme in this paper is composed of Bucket-Brigade and Genetic Algorithm. The proposed method is tested on the cart-pole system. Simulation results show that our approach has good learning and control performance
Freeman, Chris T; Burridge, Jane H; Hughes, Ann-Marie; Meadmore, Katie L
Iterative learning control (ILC) has its origins in the control of processes that perform a task repetitively with a view to improving accuracy from trial to trial by using information from previous executions of the task. This brief shows how a classic application of this technique – trajectory following in robots – can be extended to neurological rehabilitation after stroke. Regaining upper limb movement is an important step in a return to independence after stroke, but the prognosis for such recovery has remained poor. Rehabilitation robotics provides the opportunity for repetitive task-oriented movement practice reflecting the importance of such intense practice demonstrated by conventional therapeutic research and motor learning theory. Until now this technique has not allowed feedback from one practice repetition to influence the next, also implicated as an important factor in therapy. The authors demonstrate how ILC can be used to adjust external functional electrical stimulation of patients’ mus...
Rak, Natalia; Bellebaum, Christian; Thoma, Patrizia
The feedback-related negativity (FRN) and the P300 have been related to the processing of one's own and other individuals' feedback during both active and observational learning. The aim of the present study was to elucidate the role of trait-empathic responding with regard to the modulation of the neural correlates of observational learning in particular. Thirty-four healthy participants completed an active and an observational learning task. On both tasks, the participants' aim was to maximize their monetary gain by choosing from two stimuli the one that showed the higher probability of reward. Participants gained insight into the stimulus-reward contingencies according to monetary feedback presented after they had made an active choice or by observing the choices of a virtual partner. Participants showed a general improvement in learning performance on both learning tasks. P200, FRN, and P300 amplitudes were larger during active, as compared with observational, learning. Furthermore, nonreward elicited a significantly more negative FRN than did reward in the active learning task, while only a trend was observed for observational learning. Distinct subcomponents of trait cognitive empathy were related to poorer performance and smaller P300 amplitudes for observational learning only. Taken together, both the learning performance and event-related potentials during observational learning are affected by different aspects of trait cognitive empathy, and certain types of observational learning may actually be disrupted by a higher tendency to understand and adopt other people's perspectives.
Full Text Available In the introduction, we write about the process of learning mathematics: the development of mathematical concepts, numerical and spatial imagery on reading and understanding of texts, etc. The central part of the paper is devoted to the study, in which we find that identifying the learning processes associated with learning difficulties of students in mathematics, is not statistically significantly different between primary school teachers and teachers of mathematics. Both groups expose the development of numerical concepts, logical reasoning, and reading and understanding the text as the ones with which difficulties in learning mathematics appear the most frequently. All the processes of learning that the teachers assessed as the ones that represent the greatest barriers to learning have a fairly uniform average estimates of the degree of complexity, ranging from 2.6 to 2.8, which is very close to the estimate makes learning very difficult.
Arts, G.R.J.; Coolen, F.P.A.; Laan, van der P.
New methods for statistical process control are presented, where the inferences have a nonparametric predictive nature. We consider several problems in process control in terms of uncertainties about future observable random quantities, and we develop inferences for these random quantities hased on
Arts, G.R.J.; Coolen, F.P.A.; Laan, van der P.
Statistical process control (SPC) is used to decide when to stop a process as confidence in the quality of the next item(s) is low. Information to specify a parametric model is not always available, and as SPC is of a predictive nature, we present a control chart developed using nonparametric
To illustrate where the fundamental difference between expert systems in classical diagnosis and in industrial control lie, the work of process control instrumentation is used as an example for the job of expert systems. Starting from the general process of problem-solving, two classes of expert systems can be defined accordingly. (orig.) [de
Ma, Min; Van Oystaeyen, Fred
The authors' aim was to arrive at a measurable model of the creative process by putting creativity in the context of a learning process. The authors aimed to provide a rather detailed description of how creative thinking fits in a general description of the learning process without trying to go into an analysis of a biological description of the…
Jajat Sudrajat; Muhammad Ali Rahman; Antonius Sianturi; Vendy Vendy
The research objective was to produce a model of learning entrepreneurship by using SWOT analysis, which was currently being run with the concept of large classes and small classes. The benefits of this study was expected to be useful for the Binus Entrepreneurship Center (BEC) unit to create a map development learning entrepreneurship. Influences that would be generated by using SWOT Analysis were very wide as the benefits of the implementation of large classes and small classes for students...
Full Text Available Quality has become one of the most important customer decision factors in the selection among the competing product and services. Consequently, understanding and improving quality is a key factor leading to business success, growth and an enhanced competitive position. Hence quality improvement program should be an integral part of the overall business strategy. According to TQM, the effective way to improve the Quality of the product or service is to improve the process used to build the product. Hence, TQM focuses on process, rather than results as the results are driven by the processes. Many techniques are available for quality improvement. Statistical Process Control (SPC is one such TQM technique which is widely accepted for analyzing quality problems and improving the performance of the production process. This article illustrates the step by step procedure adopted at a soap manufacturing company to improve the Quality by reducing process variability using Statistical Process Control.
Owens, David H
This book develops a coherent theoretical approach to algorithm design for iterative learning control based on the use of optimization concepts. Concentrating initially on linear, discrete-time systems, the author gives the reader access to theories based on either signal or parameter optimization. Although the two approaches are shown to be related in a formal mathematical sense, the text presents them separately because their relevant algorithm design issues are distinct and give rise to different performance capabilities. Together with algorithm design, the text demonstrates that there are new algorithms that are capable of incorporating input and output constraints, enable the algorithm to reconfigure systematically in order to meet the requirements of different reference signals and also to support new algorithms for local convergence of nonlinear iterative control. Simulation and application studies are used to illustrate algorithm properties and performance in systems like gantry robots and other elect...
Larsson, Ingalill; Sundén, Anne; Ekvall Hansson, Eva
Patient education (PE) is a core treatment of osteoarthritis (OA) with the aim to increase persons' knowledge, self-efficacy, and empowerment. To describe person's various experiences of learning processes in PE for OA. Phenomenography. Semi-structured interviews were performed with the same persons, pre- (11) and post- (9) education. Various experiences on learning processes were found and were described in an outcome space. Achieving knowledge describes self-regulated learning and strongly relates to Control, which describes a high order cognitive learning skill, and minor to Confirm, which describes a cognitive learning skill based on recognition and application. Receiving knowledge describes the expectancy of learning regulated from the educator and strongly relates to Comply, which describes a low-order cognitive learning skill, and minor to Confirm. Different experiences of motivation and learning impact on persons' learning processes which, in turn, influence the persons' capability to accomplish self-efficacy and empowerment. The outcome space may serve as a basis for discussions between healthcare educators involved in PE to better understand what learning implies and to develop PE further.
G. N. Boychenko
Full Text Available At the present stage, broad information and communication technologies (ICT usage in educational practices is one of the leading trends of global education system development. This trend has led to the instructional interaction models transformation. Scientists have developed the theory of distributed cognition (Salomon, G., Hutchins, E., and distributed education and training (Fiore, S. M., Salas, E., Oblinger, D. G., Barone, C. A., Hawkins, B. L.. Educational process is based on two separated in time and space sub-processes of learning and teaching which are aimed at the organization of fl exible interactions between learners, teachers and educational content located in different non-centralized places.The purpose of this design research is to fi nd a solution for the problem of formalizing distributed learning process design and realization that is signifi cant in instructional design. The solution to this problem should take into account specifi cs of distributed interactions between team members, which becomes collective subject of distributed cognition in distributed learning process. This makes it necessary to design roles and functions of the individual team members performing distributed educational activities. Personal educational objectives should be determined by decomposition of team objectives into functional roles of its members with considering personal and learning needs and interests of students.Theoretical and empirical methods used in the study: theoretical analysis of philosophical, psychological, and pedagogical literature on the issue, analysis of international standards in the e-learning domain; exploration on practical usage of distributed learning in academic and corporate sectors; generalization, abstraction, cognitive modelling, ontology engineering methods.Result of the research is methodology for design and implementation of distributed learning process based on the competency approach. Methodology proposed by
Eberhart, Russ; Hu, Xiaohui; Chen, Yaobin
Report developed under STTR contract for topic "Cognitive models for learning to control dynamic systems" demonstrated a swarm intelligence learning algorithm and its application in unmanned aerial vehicle (UAV) mission planning...
Grau, James W.; Huie, J. Russell; Garraway, Sandra M.; Hook, Michelle A.; Crown, Eric D.; Baumbauer, Kyle M.; Lee, Kuan H.; Hoy, Kevin C.; Ferguson, Adam R.
How nociceptive signals are processed within the spinal cord, and whether these signals lead to behavioral signs of neuropathic pain, depends upon their relation to other events and behavior. Our work shows that these relations can have a lasting effect on spinal plasticity, inducing a form of learning that alters the effect of subsequent nociceptive stimuli. The capacity of lower spinal systems to adapt, in the absence of brain input, is examined in spinally transected rats that receive a nociceptive shock to the tibialis anterior muscle of one hind leg. If shock is delivered whenever the leg is extended (controllable stimulation), it induces an increase in flexion duration that minimizes net shock exposure. This learning is not observed in subjects that receive the same amount of shock independent of leg position (uncontrollable stimulation). These two forms of stimulation have a lasting, and divergent, effect on subsequent learning: controllable stimulation enables learning whereas uncontrollable stimulation disables it (learning deficit). Uncontrollable stimulation also enhances mechanical reactivity. We review evidence that training with controllable stimulation engages a brain-derived neurotrophic factor (BDNF)-dependent process that can both prevent and reverse the consequences of uncontrollable shock. We relate these effects to changes in BDNF protein and TrkB signaling. Controllable stimulation is also shown to counter the effects of peripheral inflammation (from intradermal capsaicin). A model is proposed that assumes nociceptive input is gated at an early sensory stage. This gate is sensitive to current environmental relations (between proprioceptive and nociceptive input), allowing stimulation to be classified as controllable or uncontrollable. We further propose that the status of this gate is affected by past experience and that a history of uncontrollable stimulation will promote the development of neuropathic pain. PMID:22934018
James W Grau
Full Text Available How nociceptive signals are processed within the spinal cord, and whether these signals lead to behavioral signs of neuropathic pain, depends upon their relation to other events and behavior. Our work shows that these relations can have a lasting effect on spinal plasticity, inducing a form of learning that alters the effect of subsequent nociceptive stimuli. The capacity of lower spinal systems to adapt, in the absence of brain input, is examined in spinally transected rats that receive a nociceptive shock to the tibialis anterior muscle of one hind leg. If shock is delivered whenever the leg is extended (controllable stimulation, it induces an increase in flexion duration that minimizes net shock exposure. This learning is not observed in subjects that receive the same amount of shock independent of leg position (uncontrollable stimulation. These two forms of stimulation have a lasting, and divergent, effect on subsequent learning: Controllable stimulation enables learning whereas uncontrollable stimulation disables it (learning deficit. Uncontrollable stimulation also enhances mechanical reactivity (allodynia. We review evidence that training with controllable stimulation engages a BDNF-dependent process that can both prevent and reverse the consequences of uncontrollable shock. We relate these effects to changes in BDNF protein and TrkB signaling. Controllable stimulation is also shown to counter the effects of peripheral inflammation (from intradermal capsaicin. A model is proposed that assumes nociceptive input is gated at an early stage, within the dorsal horn. his gate is sensitive to current environmental relations (between proprioceptive and nociceptive input, allowing stimulation to be classified as controllable or uncontrollable. We further propose that the status of this gate is affected by past experience and that a history of uncontrollable stimulation will promote the development of neuropathic pain.
Hommes, Juliette; Arah, Onyebuchi A.; de Grave, Willem; Schuwirth, Lambert W. T.; Scherpbier, Albert J. J. A.; Bos, Gerard M. J.
Objective Medical schools struggle with large classes, which might interfere with the effectiveness of learning within small groups due to students being unfamiliar to fellow students. The aim of this study was to assess the effects of making a large class seem small on the students' collaborative learning processes. Design A randomised controlled intervention study was undertaken to make a large class seem small, without the need to reduce the number of students enrolling in the medical programme. The class was divided into subsets: two small subsets (n = 50) as the intervention groups; a control group (n = 102) was mixed with the remaining students (the non-randomised group n∼100) to create one large subset. Setting The undergraduate curriculum of the Maastricht Medical School, applying the Problem-Based Learning principles. In this learning context, students learn mainly in tutorial groups, composed randomly from a large class every 6–10 weeks. Intervention The formal group learning activities were organised within the subsets. Students from the intervention groups met frequently within the formal groups, in contrast to the students from the large subset who hardly enrolled with the same students in formal activities. Main Outcome Measures Three outcome measures assessed students' group learning processes over time: learning within formally organised small groups, learning with other students in the informal context and perceptions of the intervention. Results Formal group learning processes were perceived more positive in the intervention groups from the second study year on, with a mean increase of β = 0.48. Informal group learning activities occurred almost exclusively within the subsets as defined by the intervention from the first week involved in the medical curriculum (E-I indexes>−0.69). Interviews tapped mainly positive effects and negligible negative side effects of the intervention. Conclusion Better group learning processes can be
Hommes, Juliette; Arah, Onyebuchi A; de Grave, Willem; Schuwirth, Lambert W T; Scherpbier, Albert J J A; Bos, Gerard M J
Medical schools struggle with large classes, which might interfere with the effectiveness of learning within small groups due to students being unfamiliar to fellow students. The aim of this study was to assess the effects of making a large class seem small on the students' collaborative learning processes. A randomised controlled intervention study was undertaken to make a large class seem small, without the need to reduce the number of students enrolling in the medical programme. The class was divided into subsets: two small subsets (n=50) as the intervention groups; a control group (n=102) was mixed with the remaining students (the non-randomised group n∼100) to create one large subset. The undergraduate curriculum of the Maastricht Medical School, applying the Problem-Based Learning principles. In this learning context, students learn mainly in tutorial groups, composed randomly from a large class every 6-10 weeks. The formal group learning activities were organised within the subsets. Students from the intervention groups met frequently within the formal groups, in contrast to the students from the large subset who hardly enrolled with the same students in formal activities. Three outcome measures assessed students' group learning processes over time: learning within formally organised small groups, learning with other students in the informal context and perceptions of the intervention. Formal group learning processes were perceived more positive in the intervention groups from the second study year on, with a mean increase of β=0.48. Informal group learning activities occurred almost exclusively within the subsets as defined by the intervention from the first week involved in the medical curriculum (E-I indexes>-0.69). Interviews tapped mainly positive effects and negligible negative side effects of the intervention. Better group learning processes can be achieved in large medical schools by making large classes seem small.
Moll, Kristina; Göbel, Silke M; Gooch, Debbie; Landerl, Karin; Snowling, Margaret J
High comorbidity rates between reading disorder (RD) and mathematics disorder (MD) indicate that, although the cognitive core deficits underlying these disorders are distinct, additional domain-general risk factors might be shared between the disorders. Three domain-general cognitive abilities were investigated in children with RD and MD: processing speed, temporal processing, and working memory. Since attention problems frequently co-occur with learning disorders, the study examined whether these three factors, which are known to be associated with attention problems, account for the comorbidity between these disorders. The sample comprised 99 primary school children in four groups: children with RD, children with MD, children with both disorders (RD+MD), and typically developing children (TD controls). Measures of processing speed, temporal processing, and memory were analyzed in a series of ANCOVAs including attention ratings as covariate. All three risk factors were associated with poor attention. After controlling for attention, associations with RD and MD differed: Although deficits in verbal memory were associated with both RD and MD, reduced processing speed was related to RD, but not MD; and the association with RD was restricted to processing speed for familiar nameable symbols. In contrast, impairments in temporal processing and visuospatial memory were associated with MD, but not RD. © Hammill Institute on Disabilities 2014.
Turner, R; Deisenroth, MP; Rasmussen, CE
18.10.13 KB. Ok to add author version to spiral, authors hold copyright. State-space inference and learning with Gaussian processes (GPs) is an unsolved problem. We propose a new, general methodology for inference and learning in nonlinear state-space models that are described probabilistically by non-parametric GP models. We apply the expectation maximization algorithm to iterate between inference in the latent state-space and learning the parameters of the underlying GP dynamics model. C...
Sørensen, Birgitte Holm; Levinsen, Karin
The present paper is based on two empirical research studies. The Netbook 1:1 project (2009–2012), funded by the municipality of Gentofte and Microsoft Denmark, is complete, while Students’ digital production and students as learning designers (2013–2015), funded by the Danish Ministry of Educati...... as a learning practice in a digitalised learning context focuses on students as actors, adressing their self‐reflections, responses to feedback from peers and feedforward processes....
McCoy, Thomasin E.; Conrad, Amy L.; Richman, Lynn C.; Nopoulos, Peg C.; Bell, Edward F.
The purpose of this study was to evaluate immediate auditory and visual memory processes in learning disability subtypes of 40 children born preterm. Three subgroups of children were examined: (a) primary language disability group (n = 13), (b) perceptual-motor disability group (n = 14), and (c) no learning disability diagnosis group without identified language or perceptual-motor learning disability (n = 13). Between-group comparisons indicate no significant differences in immediate auditory...
Johnson, B.M.; Koplow, A.S.; Stoll, F.E.; Waetje, W.D.
This paper discusses lessons learned about change control at the Waste Reduction Operations Complex (WROC) and Waste Experimental Reduction Facility (WERF) of the Idaho National Engineering Laboratory (INEL). WROC and WERF have developed and implemented change control and an as-built drawing process and have identified structures, systems, and components (SSCS) for configuration management. The operations have also formed an Independent Review Committee to minimize costs and resources associated with changing documents. WROC and WERF perform waste management activities at the INEL. WROC activities include storage, treatment, and disposal of hazardous and mixed waste. WERF provides volume reduction of solid low-level waste through compaction, incineration, and sizing operations. WROC and WERF's efforts aim to improve change control processes that have worked inefficiently in the past
Wu, Chengzhi; Qi, Bo; Chen, Chunlin; Dong, Daoyi
Robust control design for quantum unitary transformations has been recognized as a fundamental and challenging task in the development of quantum information processing due to unavoidable decoherence or operational errors in the experimental implementation of quantum operations. In this paper, we extend the systematic methodology of sampling-based learning control (SLC) approach with a gradient flow algorithm for the design of robust quantum unitary transformations. The SLC approach first uses a "training" process to find an optimal control strategy robust against certain ranges of uncertainties. Then a number of randomly selected samples are tested and the performance is evaluated according to their average fidelity. The approach is applied to three typical examples of robust quantum transformation problems including robust quantum transformations in a three-level quantum system, in a superconducting quantum circuit, and in a spin chain system. Numerical results demonstrate the effectiveness of the SLC approach and show its potential applications in various implementation of quantum unitary transformations.
Sørensen, Birgitte Holm; Levinsen, Karin Tweddell
The present paper is based on two empirical research studies. The "Netbook 1:1" project (2009-2012), funded by the municipality of Gentofte and Microsoft Denmark, is complete, while "Students' digital production and students as learning designers" (2013-2015), funded by the Danish Ministry of Education, is ongoing. Both…
THE OBJECTIVES OF SECOND LANGUAGE TEACHING, AND SPECIFIC DIRECTIONS FOR PRESENTING AND DRILLING STRUCTURES BY THE USE OF CERTAIN GESTURES, WERE PRESENTED. RECOMMENDATIONS FOR CONCENTRATING EFFORTS ON THE ESSENTIALS OF LANGUAGE LEARNING REVOLVED AROUND AN EMPHASIS ON THE TEACHING OF THE LANGUAGE ITSELF RATHER THAN ABOUT ITS HISTORY, VOCABULARY,…
Ritamaki, O.; Luhtaniemi, H. [Rautaruukki Engineering (Finland)
The paper presents the latest development of the Coking Process Management System (CPMS) at Raahe Steel. The latest third generation system is based on the previous system with the addition of fuzzy logic controllers. (The previous second generation system was based simultaneous feed forward and feedback control.) The system development has resulted in balanced coke oven battery heating, decreased variation in process regulation between shifts and increase of process information for operators. The economic results are very satisfactory. 7 figs.
A major challenge in process operation is to reduce costs and increase system efficiency whereas the complexity of automated process engineering, control and monitoring systems increases continuously. To cope with this challenge the design, implementation and operation of process monitoring systems for control room operation have to be treated as an ensemble. This is only possible if the engineering of the monitoring information is focused on the production objective and is lead in close coll...
Koleva, L.; Koleva, E.; Batchkova, I.; Mladenov, G.
The ISO/IEC 62264 standard is widely used for integration of the business systems of a manufacturer with the corresponding manufacturing control systems based on hierarchical equipment models, functional data and manufacturing operations activity models. In order to achieve the integration of control systems, formal object communication models must be developed, together with manufacturing operations activity models, which coordinate the integration between different levels of control. In this article, the development of integrated control system for electron beam welding process is presented as part of a fully integrated control system of an electron beam plant, including also other additional processes: surface modification, electron beam evaporation, selective melting and electron beam diagnostics.
These proceedings contains refereed papers presented at the sixteenth IEEE Workshop on Machine Learning for Signal Processing (MLSP'2006), held in Maynooth, Co. Kildare, Ireland, September 6-8, 2006. This is a continuation of the IEEE Workshops on Neural Networks for Signal Processing (NNSP......). The name of the Technical Committee, hence of the Workshop, was changed to Machine Learning for Signal Processing in September 2003 to better reflect the areas represented by the Technical Committee. The conference is organized by the Machine Learning for Signal Processing Technical Committee...... the same standard as the printed version and facilitates the reading and searching of the papers. The field of machine learning has matured considerably in both methodology and real-world application domains and has become particularly important for solution of problems in signal processing. As reflected...
The dependence of a bulk facility handling Purex Process on the control measurement system for evaluating the process performance needs hardly be emphasized. process control, Plant control, inventory control and quality control are the four components of the control measurement system. The scope and requirements of each component are different and the measurement methods are selected accordingly. However, each measurement system has six important elements. These are described in detail. The quality assurance programme carried out by the laboratory as a mechanism through which the quality of measurements is regularly tested and stated in quantitative terms is also explained in terms of internal and external quality assurance, with examples. Suggestions for making the control measurement system more responsive to the operational needs in future are also briefly discussed. (author)
Chen, Yingke; Nielsen, Thomas Dyhre
deterministic Markov decision processes from data by actively guiding the selection of input actions. The algorithm is empirically analyzed by learning system models of slot machines, and it is demonstrated that the proposed active learning procedure can significantly reduce the amount of data required...... demanding process, and this shortcoming has motivated the development of algorithms for automatically learning system models from observed system behaviors. Recently, algorithms have been proposed for learning Markov decision process representations of reactive systems based on alternating sequences...... of input/output observations. While alleviating the problem of manually constructing a system model, the collection/generation of observed system behaviors can also prove demanding. Consequently we seek to minimize the amount of data required. In this paper we propose an algorithm for learning...
Control chart is the most important statistical tool to manage the business processes. It is a graph of measurements on a quality characteristic of the process on the vertical axis plotted against time on the horizontal axis. The graph is completed with control limits that cause variation mark. Once
Hang, Hanyuan; Feng, Yunlong; Steinwart, Ingo; Suykens, Johan A K
This letter investigates the supervised learning problem with observations drawn from certain general stationary stochastic processes. Here by general, we mean that many stationary stochastic processes can be included. We show that when the stochastic processes satisfy a generalized Bernstein-type inequality, a unified treatment on analyzing the learning schemes with various mixing processes can be conducted and a sharp oracle inequality for generic regularized empirical risk minimization schemes can be established. The obtained oracle inequality is then applied to derive convergence rates for several learning schemes such as empirical risk minimization (ERM), least squares support vector machines (LS-SVMs) using given generic kernels, and SVMs using gaussian kernels for both least squares and quantile regression. It turns out that for independent and identically distributed (i.i.d.) processes, our learning rates for ERM recover the optimal rates. For non-i.i.d. processes, including geometrically [Formula: see text]-mixing Markov processes, geometrically [Formula: see text]-mixing processes with restricted decay, [Formula: see text]-mixing processes, and (time-reversed) geometrically [Formula: see text]-mixing processes, our learning rates for SVMs with gaussian kernels match, up to some arbitrarily small extra term in the exponent, the optimal rates. For the remaining cases, our rates are at least close to the optimal rates. As a by-product, the assumed generalized Bernstein-type inequality also provides an interpretation of the so-called effective number of observations for various mixing processes.
Havinga, Gosse Tjipke
Inevitable variations in process and material properties limit the accuracy of metal forming processes. Robust optimization methods or control systems can be used to improve the production accuracy. Robust optimization methods are used to design production processes with low sensitivity to the
Ali, Emad; Idriss, Arimiyawo
Recently, chemical engineering education moves towards utilizing simulation soft wares to enhance the learning process especially in the field of process control. These training simulators provide interactive learning through visualization and practicing which will bridge the gap between the theoretical abstraction of textbooks and the…
The foreign language vocabulary learning research literature often attributes strong mnemonic potency to the cognitive processing of meaning when learning words. Routinely cited as support for this idea are experiments by Craik and Tulving (C&T) demonstrating superior recognition and recall of studied words following semantic tasks ("deep"…
Biehl, M.; Freking, A.; Reents, G.; Schlösser, E.
From the recent analysis of supervised learning by on-line gradient descent in multilayered neural networks it is known that the necessary process of student specialization can be delayed significantly. We demonstrate that this phenomenon also occurs in various models of unsupervised learning. A
Lee, Doris; McCool, John; Napieralski, Laura
Graduate students (n=134) used the analytic hierarchy process, which weights expressed preferences, to rate four learning activities: lectures, discussion/reflection, individual projects, and group projects. Their preferences for discussion/reflection and individual projects were independent of auditory, visual, and kinesthetic learning styles.…
Geijsel, F.; Meijers, F.
The aim of this paper is to offer an additional perspective to the understanding of educational change processes by clarifying the significance of identity learning. Today’s innovations require changes in teachers’ professional identity. Identity learning involves a relation between social‐cognitive
Full Text Available Three case studies of in-house developed e-learning education in public organizations with different pedagogical approaches are used as a starting point for discussion regarding the implementation challenges of e-learning at work. The aim of this article is to contribute to the understanding of integrating mechanisms of e-learning outcomes into work processes in large, public organizations. The case studies were analyzed from a socio-cultural perspective using the MOA-model as a frame of reference. Although the pedagogical approaches for all of the cases seemed to be relevant and most of the learners showed overall positive attitudes towards the courses, there were problems with integration of the e-learning outcomes into work processes. There were deficiencies in the adaption of the course contents to the local educational needs. There was also a lack of adjusting the local work organization and work routines in order to facilitate the integration of the e-learning outcomes into the work processes. A lack of local management engagement affected the learners’ motivation negatively. Group discussions in local work groups facilitated the integration of the e-learning outcomes. Much of the difficulties of integrating e-learning outcomes into work processes in big organizations are related to the problems with adjusting centrally developed e-learning courses to local needs and a lack of co-operation among among the developers (often IT-professionals and the Human Resources Department of the organizations.
Ana Belén Escrig-Tena
The objective of this paper deals with the influence exerted by TQM on the capability to promote the process of organisational learning, as one of the competencies that the introduction of TQM helps to develop, We discuss the extent to which the critical factors of TQM favour both the exploration of new knowledge that can modify organisational behaviour, and the exploitation of current learning,
A model derived from information processing theory is described, which helps to explain the complex verbal learning of students and suggests implications for lecturing techniques. Other factors affecting learning, which are not covered by the model, are discussed in relationship to it: student's intellectual development and effects of individual…
The importance of emotions in the process of intercultural learning has been recognised, but the topic has not been extensively theorised. This theoretical review article synthesises the research literature on emotions in the context of teachers' intercultural learning. The article argues that emotions are a vital part of any change, and thus play…
This paper reflects on how action learning sets (ALSs) were used to support organisational change initiatives. It sets the scene with contextualising the inclusion of change projects in a masters programme. Action learning is understood to be a dynamic process where a team meets regularly to help individual members address issues through a highly…
Full Text Available The integration of online learning in university courses is considered to be both inevitable and necessary. Thus there is an increasing need to raise awareness among educators and course designers about the critical issues impacting on online learning. The aim of this study, therefore, was to assess the differences between two groups of first-year Business Sciences learners (online and conventional learners in terms of biographic and demographic characteristics and locus of control. The study population consisted of 586 first-year learners of whom 185 completed the Locus of Control Inventory (LCI. The results show that the two groups of learners do not differ statistically significantly from each other with respect to locus of control. The findings and their implications are also discussed. Opsomming Die integrasie van aanlyn-leer in universiteitskursusse word beskou as sowel onafwendbaar as noodsaaklik. Daar is dus ’n toenemende behoefte om bewustheid onder opvoedkundiges en kursusontwerpers te kweek oor die kritiese aspekte wat ’n impak op aanlyn-leer het (Morgan, 1996. Daarom was die doel van hierdie ondersoek om die verskille tussen twee groepe eerstejaarleerders in Bestuurs- en Ekonomiese Wetenskap (aanlyn en konvensionele leerders te bepaal ten opsigte van biografiese en demografiese eienskappe en lokus van beheer. Die populasie het bestaan uit 586 eerstejaarleerders waarvan 185 die Lokus van Beheer Vraelys voltooi het. Die resultate toon dat die twee groepe leerders nie statisties beduidend van mekaar verskil het met betrekking tot lokus van beheer nie. Die bevindinge en implikasies word ook bespreek.
Full Text Available The discrete control processes with state evaluation in time of dynamical system is considered. A general model of control problems with integral-time cost criterion by a trajectory is studied and a general scheme for solving such classes of problems is proposed. In addition the game-theoretical and multicriterion models for control problems are formulated and studied.
Ricardez-Sandoval, Luis A.; Blankespoor, Wesley; Budman, Hector M.
This paper describes an experiment performed by the fourth year chemical engineering students in the process control laboratory at the University of Waterloo. The objective of this experiment is to test the capabilities of a constrained Model Predictive Controller (MPC) to control the operation of a Double Pipe Heat Exchanger (DPHE) in real time.…
Babary, J.P. [Centre National d`Etudes Spatiales (CNES), 31 - Toulouse (France). Laboratoire d`Analyse et d`Architecture des Systemes; Simeonov, I. [Institute of Microbiology, Bulgarian Academy of Sciences (Bulgaria); Ljubenova, V. [Institute of Control and System Research, BAS (Country unknown/Code not available); Dochain, D. [Universite Catholique de Louvain (UCL), Louvain-la-Neuve (Belgium)
Biotechnological processes (BTP) involve living organisms. In the anaerobic fermentation (biogas production process) the organic matter is mineralized by microorganisms into biogas (methane and carbon dioxide) in the absence of oxygen. The biogas is an additional energy source. Generally this process is carried out as a continuous BTP. It has been widely used in life process and has been confirmed as a promising method of solving some energy and ecological problems in the agriculture and industry. Because of the very restrictive on-line information the control of this process in continuous mode is often reduced to control of the biogas production rate or the concentration of the polluting organic matter (de-pollution control) at a desired value in the presence of some perturbations. Investigations show that classical linear controllers have good performances only in the linear zone of the strongly non-linear input-output characteristics. More sophisticated robust and with variable structure (VSC) controllers are studied. Due to the strongly non-linear dynamics of the process the performances of the closed loop system may be degrading in this case. The aim of this paper is to investigate different linearizing algorithms for control of a continuous non-linear methane fermentation process using the dilution rate as a control action and taking into account some practical implementation aspects. (authors) 8 refs.
Filar, Jerzy; Chen, Anyue
The general theory of stochastic processes and the more specialized theory of Markov processes evolved enormously in the second half of the last century. In parallel, the theory of controlled Markov chains (or Markov decision processes) was being pioneered by control engineers and operations researchers. Researchers in Markov processes and controlled Markov chains have been, for a long time, aware of the synergies between these two subject areas. However, this may be the first volume dedicated to highlighting these synergies and, almost certainly, it is the first volume that emphasizes the contributions of the vibrant and growing Chinese school of probability. The chapters that appear in this book reflect both the maturity and the vitality of modern day Markov processes and controlled Markov chains. They also will provide an opportunity to trace the connections that have emerged between the work done by members of the Chinese school of probability and the work done by the European, US, Central and South Ameri...
Full Text Available Abstract The hydrodealkylation process of toluene (HDA has been used as a case study in a large number of control studies. However, in terms of industrial application, this process has become obsolete and is nowadays superseded by new technologies capable of processing heavy aromatic compounds, which increase the added value of the raw materials, such as the process of transalkylation and disproportionation of toluene (TADP. TADP also presents more complex feed and product streams and challenging operational characteristics both in the reactor and separator sections than in HDA. This work is aimed at proposing the TADP process as a new benchmark for plantwide control studies in lieu of the HAD process. For this purpose, a nonlinear dynamic rigorous model for the TADP process was developed using Aspen Plus™ and Aspen Dynamics™ and industrial conditions. Plantwide control structures (oriented to control and to the process were adapted and applied for the first time for this process. The results show that, even though both strategies are similar in terms of control performance, the optimization of economic factors must still be sought.
Niewoehner, Kevin R.; Carter, John (Technical Monitor)
The research accomplishments for the cooperative agreement 'Online Learning Flight Control for Intelligent Flight Control Systems (IFCS)' include the following: (1) previous IFC program data collection and analysis; (2) IFC program support site (configured IFC systems support network, configured Tornado/VxWorks OS development system, made Configuration and Documentation Management Systems Internet accessible); (3) Airborne Research Test Systems (ARTS) II Hardware (developed hardware requirements specification, developing environmental testing requirements, hardware design, and hardware design development); (4) ARTS II software development laboratory unit (procurement of lab style hardware, configured lab style hardware, and designed interface module equivalent to ARTS II faceplate); (5) program support documentation (developed software development plan, configuration management plan, and software verification and validation plan); (6) LWR algorithm analysis (performed timing and profiling on algorithm); (7) pre-trained neural network analysis; (8) Dynamic Cell Structures (DCS) Neural Network Analysis (performing timing and profiling on algorithm); and (9) conducted technical interchange and quarterly meetings to define IFC research goals.
The article is concerned with the question: How do construction firms implement new technology on construction projects? A model of the implementation process is presented based on a review of the construction innovation literature, innovation theory, and organisational learning theories....
Mr. Glan Devadhas G; Dr.Pushpakumar S.
Chemical process control is a challenging problem due to the strong on*line non*linearity and extreme sensitivity to disturbances of the process. Ziegler – Nichols tuned PI and PID controllers are found to provide poor performances for higher*order and non–linear systems. This paper presents an application of one*step*ahead fuzzy as well as ANFIS (adaptive*network*based fuzzy inference system) tuning scheme for an Continuous Stirred Tank Reactor CSTR process. The controller is designed based ...
Jens G. Balchen
Full Text Available A simple method has been investigated for the total or partial removal of the effect of non-linear process phenomena in multi-variable feedback control systems. The method is based upon computing the control variables which will drive the process at desired rates. It is shown that the effect of model errors in the linearization of the process can be partly removed through the use of large feedback gains. In practice there will be limits on how large gains can he used. The sensitivity to parameter errors is less pronounced and the transient behaviour is superior to that of ordinary PI controllers.
Villardón-Gallego, Lourdes; Yániz, Concepción
Introduction: Affective strategies for coping with affective states linked to the learning process may be oriented toward controlling emotions or toward controlling motivation. Both types affect performance, directly and indirectly. The objective of this research was to design an instrument for measuring the affective strategies used by university…
Weitze, Charlotte Lærke
, 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...... another. The study found that the students benefitted from this way of learning as a valid variation to more conventional teaching approaches, and teachers found that the students learned at least the same amount or more compared to traditional teaching processes. The students were able to think outside...
Pawlicki, Todd; Whitaker, Matthew
The purpose of this work was to highlight the importance of controlling process variability for successful quality assurance (QA). We describe the method of statistical process control for characterizing and controlling a process. Traditionally, QA has been performed by comparing some important measurement (e.g., linear accelerator output) against a corresponding specification. Although useful in determining the fitness of a particular measurement, this approach does not provide information about the underlying process behavior over time. A modern view of QA is to consider the time-ordered behavior of a process. Every process displays characteristic behaviors that are independent of the specifications imposed on it. The goal of modern QA is, not only to ensure that a process is on-target, but that it is also operating with minimal variation. This is accomplished by way of a data-driven approach using process behavior charts. The development of process behavior charts, historically known as control charts, and process behavior (action) limits are described. The effect these concepts have on quality management is also discussed
Full Text Available Learning what behaviour is appropriate in a specific context by observing the actions of others and their outcomes is a key constituent of human cognition, because it saves time and energy and reduces exposure to potentially dangerous situations. Observational learning of associative rules relies on the ability to map the actions of others onto our own, process outcomes, and combine these sources of information. Here, we combined newly developed experimental tasks and functional magnetic resonance imaging (fMRI to investigate the neural mechanisms that govern such observational learning. Results show that the neural systems involved in individual trial-and-error learning and in action observation and execution both participate in observational learning. In addition, we identified brain areas that specifically activate for others' incorrect outcomes during learning in the posterior medial frontal cortex (pMFC, the anterior insula and the posterior superior temporal sulcus (pSTS.
Monfardini, Elisabetta; Gazzola, Valeria; Boussaoud, Driss; Brovelli, Andrea; Keysers, Christian; Wicker, Bruno
Learning what behaviour is appropriate in a specific context by observing the actions of others and their outcomes is a key constituent of human cognition, because it saves time and energy and reduces exposure to potentially dangerous situations. Observational learning of associative rules relies on the ability to map the actions of others onto our own, process outcomes, and combine these sources of information. Here, we combined newly developed experimental tasks and functional magnetic resonance imaging (fMRI) to investigate the neural mechanisms that govern such observational learning. Results show that the neural systems involved in individual trial-and-error learning and in action observation and execution both participate in observational learning. In addition, we identified brain areas that specifically activate for others' incorrect outcomes during learning in the posterior medial frontal cortex (pMFC), the anterior insula and the posterior superior temporal sulcus (pSTS).
The present article highlights the importance of the motivational construct for the foreign language learning (FLL) process. More specifically, in the present article it is argued that motivation is likely to play a significant role at all three stages of the FLL process as they are discussed within the information processing model of FLL, namely,…
Jensen, Annie Aarup; Kjær-Rasmussen, Lone Krogh; Iversen, Ann-Merete
Learning, leading and letting go of control – Learner Led Approaches in Education Annie Aarup Jensen, Lone Krogh Kjær-Rasmussen, Ann-Merete Iversen and Anni Stavnskær Pedersen Abstract The aim of the paper is to introduce a new term in teaching in Higher Education: Learner Led Approaches...... in Education: LED. The sources of inspiration are many as are the experiences we draw from. Problem-based project work (PBL) being one, various classical teacher centered methods, and last but not least a variety of methods aiming towards developing creativity, innovational skills and entrepreneurship. LED...... is inspired by collaboration between professors from Aalborg University, Cornwall College and University College of Northern Denmark. Moravec (2008) claims that educational systems still operate in 1.0 or perhaps 2.0 mode while the surrounding cultures and societies operate in 3.0 mode. The amount...
These proceedings contains refereed papers presented at the Fifteenth IEEE Workshop on Machine Learning for Signal Processing (MLSP’2005), held in Mystic, Connecticut, USA, September 28-30, 2005. This is a continuation of the IEEE Workshops on Neural Networks for Signal Processing (NNSP) organized...... by the NNSP Technical Committee of the IEEE Signal Processing Society. The name of the Technical Committee, hence of the Workshop, was changed to Machine Learning for Signal Processing in September 2003 to better reflect the areas represented by the Technical Committee. The conference is organized...... by the Machine Learning for Signal Processing Technical Committee with sponsorship of the IEEE Signal Processing Society. Following the practice started two years ago, the bound volume of the proceedings is going to be published by IEEE following the Workshop, and we are pleased to offer to conference attendees...
Jarvers, Christian; Brosch, Tobias; Brechmann, André; Woldeit, Marie L; Schulz, Andreas L; Ohl, Frank W; Lommerzheim, Marcel; Neumann, Heiko
Biologically plausible modeling of behavioral reinforcement learning tasks has seen great improvements over the past decades. Less work has been dedicated to tasks involving contingency reversals, i.e., tasks in which the original behavioral goal is reversed one or multiple times. The ability to adjust to such reversals is a key element of behavioral flexibility. Here, we investigate the neural mechanisms underlying contingency-reversal tasks. We first conduct experiments with humans and gerbils to demonstrate memory effects, including multiple reversals in which subjects (humans and animals) show a faster learning rate when a previously learned contingency re-appears. Motivated by recurrent mechanisms of learning and memory for object categories, we propose a network architecture which involves reinforcement learning to steer an orienting system that monitors the success in reward acquisition. We suggest that a model sensory system provides feature representations which are further processed by category-related subnetworks which constitute a neural analog of expert networks. Categories are selected dynamically in a competitive field and predict the expected reward. Learning occurs in sequentialized phases to selectively focus the weight adaptation to synapses in the hierarchical network and modulate their weight changes by a global modulator signal. The orienting subsystem itself learns to bias the competition in the presence of continuous monotonic reward accumulation. In case of sudden changes in the discrepancy of predicted and acquired reward the activated motor category can be switched. We suggest that this subsystem is composed of a hierarchically organized network of dis-inhibitory mechanisms, dubbed a dynamic control network (DCN), which resembles components of the basal ganglia. The DCN selectively activates an expert network, corresponding to the current behavioral strategy. The trace of the accumulated reward is monitored such that large sudden
Learning to rank refers to machine learning techniques for training a model in a ranking task. Learning to rank is useful for many applications in information retrieval, natural language processing, and data mining. Intensive studies have been conducted on its problems recently, and significant progress has been made. This lecture gives an introduction to the area including the fundamental problems, major approaches, theories, applications, and future work.The author begins by showing that various ranking problems in information retrieval and natural language processing can be formalized as tw
Yu, Ding-Li; Chang, T K; Yu, Ding-Wen
Fault tolerant control of dynamic processes is investigated in this paper using an auto-tuning PID controller. A fault tolerant control scheme is proposed composing an auto-tuning PID controller based on an adaptive neural network model. The model is trained online using the extended Kalman filter (EKF) algorithm to learn system post-fault dynamics. Based on this model, the PID controller adjusts its parameters to compensate the effects of the faults, so that the control performance is recovered from degradation. The auto-tuning algorithm for the PID controller is derived with the Lyapunov method and therefore, the model predicted tracking error is guaranteed to converge asymptotically. The method is applied to a simulated two-input two-output continuous stirred tank reactor (CSTR) with various faults, which demonstrate the applicability of the developed scheme to industrial processes.
A major challenge in process operation is to reduce costs and increase system efficiency whereas the complexity of automated process engineering, control and monitoring systems increases continuously. To cope with this challenge the design, implementation and operation of process monitoring systems for control room operation have to be treated as an ensemble. This is only possible if the engineering of the monitoring information is focused on the production objective and is lead in close collaboration of control room teams, exploitation personnel and process specialists. In this paper some principles for the engineering of monitoring information for control room operation are developed at the example of the exploitation of a particle accelerator at the European Laboratory for Nuclear Research (CERN).
This monograph opens up new horizons for engineers and researchers in academia and in industry dealing with or interested in new developments in the field of system identification and control. It emphasizes guidelines for working solutions and practical advice for their implementation rather than the theoretical background of Gaussian process (GP) models. The book demonstrates the potential of this recent development in probabilistic machine-learning methods and gives the reader an intuitive understanding of the topic. The current state of the art is treated along with possible future directions for research. Systems control design relies on mathematical models and these may be developed from measurement data. This process of system identification, when based on GP models, can play an integral part of control design in data-based control and its description as such is an essential aspect of the text. The background of GP regression is introduced first with system identification and incorporation of prior know...
This paper provides a summary of lessons learned from experiences on the Waste Isolation Pilot Plant (WJPP) Project in implementation of quality assurance controls surrounding inputs for performance assessment analysis. Since the performance assessment (PA) process is inherent in compliance determination for any waste repository, these lessons-learned are intended to be useful to investigators, analysts, and Quality Assurance (QA) practitioners working on high level waste disposal projects. On the WIPP Project, PA analyses for regulatory-compliance determination utilized several inter-related computer programs (codes) that mathematically modeled phenomena such as radionuclide release, retardation, and transport. The input information for those codes are the parameters that are the subject of this paper. Parameters were maintained in a computer database, which was then queried electronically by the PA codes whenever input was needed as the analyses were run
Full Text Available Sentences such as The ship was sunk to collect the insurance exhibit an unusual form of anaphora, implicit control, where neither anaphor nor antecedent is audible. The nonfinite reason clause has an understood subject, PRO, that is anaphoric; here it may be understood as naming the agent of the event of the host clause. Yet since the host is a short passive, this agent is realized by no audible dependent. The putative antecedent to PRO is therefore implicit, which it normally cannot be. What sorts of representations subserve the comprehension of this dependency? Here we present four self-paced reading time studies directed at this question. Previous work showed no processing cost for implicit versus explicit control, and took this to support the view that PRO is linked syntactically to a silent argument in the passive. We challenge this conclusion by reporting that we also find no processing cost for remote implicit control, as in: The ship was sunk. The reason was to collect the insurance. Here the dependency crosses two independent sentences, and so cannot, we argue, be mediated by syntax. Our Experiments 1-4 examined the processing of both implicit (short passive and explicit (active or long passive control in both local and remote configurations. Experiments 3 and 4 added either three days ago or just in order to the local conditions, to control for the distance between the passive and infinitival verbs, and for the predictability of the reason clause, respectively. We replicate the finding that implicit control does not impose an additional processing cost. But critically we show that remote control does not impose a processing cost either. Reading times at the reason clause were never slower when control was remote. In fact they were always faster. Thus efficient processing of local implicit control cannot show that implicit control is mediated by syntax; nor, in turn, that there is a silent but grammatically active argument in passives.
By using data from an online language learning beliefs survey (n?=?841), defining language learning experience in terms of participants' multilingualism, and using a domain-specific language learning locus of control (LLLOC) instrument, this article examines whether more experienced language learners can also be seen as more autonomous language…
Georgina Amayuela Mora
Full Text Available The fundamental purpose of this article is to characterize the assertiveness as a component of the communicative competence. The study of the communicative process is a current need, since from the quality of the communication depends to a great extent the student’s formation. The learning process in the university context requires an assertive communicative process. In this paper the assertiveness is defined as a communicative skill and is valued the importance of an assertive behavior through its positive impact in the learning process.
Stankov Stanko P.
Full Text Available In this paper, the control of the plant for mineral wool production consisting of a number of the technological units of different sizes and complexity is considered. The application of modern equipment based on PLC (Programmable Logic Controller and SCADA (Supervisory Control And Data Acquisition configuration provides optimal control of technological process. Described supervisory and control system is consisting of a number of units doing decentralized distributed control of technological entities where all possible situation are considered during work of machines and devices, which are installed in electric drive and are protected from technological and electrical accident. Transformer station and diesel engine, raw materials transport and dosage, processes in dome oven, centrifuges, polycondensation (PC chamber, burners, compressor station, binder preparation and dosage, wool cutting, completed panel packing and their transport to storehouse are controlled. Process variables and parameters like as level, flow, velocity, temperature, pressure, etc. are controlled. Control system is doing identification of process states changes, diagnostic and prediction of errors and provides prediction of behavior of control objects when input flows of materials and generates optimal values of control variables due to decreasing downtime and technic - economical requires connected to wool quality to be achieved. Supervisory and control system either eliminates unwanted changes in the production line or restricts them within the allowable limits according to the technology. In this way, the optimization of energy and raw materials consumption and appropriate products quality is achieved, where requirements are satisfied in accordance with process safety and environmental standards. SCADA provides a visual representation of controlled and uncontrolled parts of the technological process, processing alarms and events, monitoring of the changes of relevant
Porr, Bernd; von Ferber, Christian; Wörgötter, Florentin
In "Isotropic Sequence Order Learning" (pp. 831-864 in this issue), we introduced a novel algorithm for temporal sequence learning (ISO learning). Here, we embed this algorithm into a formal nonevaluating (teacher free) environment, which establishes a sensor-motor feedback. The system is initially guided by a fixed reflex reaction, which has the objective disadvantage that it can react only after a disturbance has occurred. ISO learning eliminates this disadvantage by replacing the reflex-loop reactions with earlier anticipatory actions. In this article, we analytically demonstrate that this process can be understood in terms of control theory, showing that the system learns the inverse controller of its own reflex. Thereby, this system is able to learn a simple form of feedforward motor control.
Full Text Available A novel model-based nonlinear control strategy is proposed using an experimental pH neutralization process. The control strategy involves a non linear neural network (NN model, in the context of internal model control (IMC. When integrated into the internal model control scheme, the resulting controller is shown to have favorable practical implications as well as superior performance. The designed model based online IMC controller was implemented to a laboratory scaled pH process in real time using dSPACE 1104 interface card. The responses of pH and acid flow rate shows good tracking for both the set point and load chances over the entire nonlinear region.
Gorrini, V.; Bersini, H.
Various issues related to the automatic construction and on-line adaptation of fuzzy controllers are addressed. A Direct Adaptive Fuzzy Control (this is an adaptive control methodology requiring a minimal knowledge of the processes to be coupled with) derived in a way reminiscent of neurocontrol methods, is presented. A classical fuzzy controller and a fuzzy realization of a PID controller is discussed. These systems implement a highly non-linear control law, and provide to be quite robust, even in the case of noisy inputs. In order to identify dynamic processes of order superior to one, we introduce a more complex architecture, called Recurrent Fuzzy System, that use some fuzzy internal variables to perform an inferential chaining.I
Maggi, F.M.; Corapi, D.; Russo, A.; Lupu, E.; Visaggio, G.; Muehlen, zur M.; Su, J.
Discovering the Business Process (BP) model underpinning existing practices through analysis of event logs, allows users to understand, analyse and modify the process. But, to be useful, the BP model must be kept in line with practice throughout its lifetime, as changes occur to the business
N. N. Barbashov
Full Text Available An important task of modern mathematical statistics with its methods based on the theory of probability is a scientific estimate of measurement results. There are certain costs under control, and under ineffective control when a customer has got defective products these costs are significantly higher because of parts recall.When machining the parts, under the influence of errors a range scatter of part dimensions is offset towards the tolerance limit. To improve a processing accuracy and avoid defective products involves reducing components of error in machining, i.e. to improve the accuracy of machine and tool, tool life, rigidity of the system, accuracy of the adjustment. In a given time it is also necessary to adapt machine.To improve an accuracy and a machining rate there, currently become extensively popular various the in-process gaging devices and controlled machining that uses adaptive control systems for the process monitoring. Improving the accuracy in this case is compensation of a majority of technological errors. The in-cycle measuring sensors (sensors of active control allow processing accuracy improvement by one or two quality and provide a capability for simultaneous operation of several machines.Efficient use of in-cycle measuring sensors requires development of methods to control the accuracy through providing the appropriate adjustments. Methods based on the moving average, appear to be the most promising for accuracy control since they include data on the change in some last measured values of the parameter under control.
Full Text Available Pengaruh Pembelajaran Inkuiri Terbimbing dengan Mind Map terhadap Keterampilan Proses Sains dan Hasil Belajar IPA Abstract: Science learning in junior high school aims to enable students conducts scientific inquiry, improves knowledge, concepts, and science skills. Organization materials for students supports learning process so that needs to be explored techniques that allows students to enable it. This study aimed to determine the effect of guided inquiry learning with mind map on science process skills and cognitive learning outcomes. This experimental quasi studey used pretest-posttest control group design and consisted eighth grade students of SMP Negeri 1 Papalang Mamuju of West Sulawesi. The results showed there where significant positive effect of guided inquiry learning with mind map on process science skills and cognitive learning outcomes. Key Words: guided inquiry, mind map, science process skills, cognitive learning outcomes Abstrak: Pembelajaran Ilmu Pengetahuan Alam (IPA di SMP bertujuan agar siswa dapat melakukan inkuiri ilmiah, meningkatkan pengetahuan, konsep, dan keterampilan IPA. Dalam pembelajaran, organisasi materi berperan penting dalam memudahkan anak belajar sehingga perlu ditelaah teknik yang memudahkan siswa membuat organisasi materi. Penelitian ini bertujuan mengetahui pengaruh pembelajaran inkuiri terbimbing dengan mind map terhadap keterampilan proses sains dan hasil belajar kognitif. Penelitian kuasi eksperimen ini menggunakan rancangan pre test-post test control group design dengan subjek penelitian siswa kelas VIII SMP Negeri 1 Papalang. Hasil penelitian menunjukkan ada pengaruh positif yang signifikan pembelajaran inkuiri terbimbing dengan mind map terhadap kemampuan keterampilan proses sains dan hasil belajar kognitif siswa. Kata kunci: inkuiri terbimbing, mind map, keterampilan proses sains, hasil belajar kognitif
Patricia K. Lebow; Timothy M. Young; Stan Lebow
This paper is the first stage of a study that attempts to improve the process of manufacturing treated lumber through the use of statistical process control (SPC). Analysis of industrial and auditing agency data sets revealed there are differences between the industry and agency probability density functions (pdf) for normalized retention data. Resampling of batches of...
Mansouri, Seyed Soheil
chemical processes; for example, intensified processes such as reactive distillation. Most importantly, it identifies and eliminates potentially promising design alternatives that may have controllability problems later. To date, a number of methodologies have been proposed and applied on various problems......, that the same principles that apply to a binary non-reactive compound system are valid also for a binary-element or a multi-element system. Therefore, it is advantageous to employ the element based method for multicomponent reaction-separation systems. It is shown that the same design-control principles...
Hardt, D.E.; Eagar, T.W.; Lang, J.H.; Jones, L.
The Gas Metal Arc Welding Process is characterized by many important process outputs, all of which should be controlled to ensure consistent high performance joints. However, application of multivariable control methods is confounded by the strong physical coupling of typical outputs of bead shape and thermal properties. This coupling arises from the three dimensional thermal diffusion processes inherent in welding, and cannot be overcome without significant process modification. This paper presents data on the extent of coupling of the process, and proposes process changes to overcome such strong output coupling. Work in rapid torch vibration to change the heat input distribution is detailed, and methods for changing the heat balance between base and fill material heat are described
Angelov, Samuil; Vonk, Jochem; Vidyasankar, Krishnamurthy; Grefen, Paul
E-contracts express the rights and obligations of parties through a formal, digital representation of the contract provisions. In process intensive relationships, e-contracts contain business processes that a party promises to perform for the counter party, optionally allowing monitoring of the execution of the promised processes. In this paper, we describe an approach in which the counter party is allowed to control the process execution. This approach will lead to more flexible and efficient business relations which are essential in the context of modern, highly dynamic and complex collaborations among companies. We present a specification of the process controls available to the consumer and their support in the private process specification of the provider.
Alex De La Cruz
Full Text Available The present article shows the design and construction of a classifier didactical machine through artificial vision. The implementation of the machine is to be used as a learning module of mechatronic processes. In the project, it is described the theoretical aspects that relate concepts of mechanical design, electronic design and software management which constitute popular field in science and technology, which is mechatronics. The design of the machine was developed based on the requirements of the user, through the concurrent design methodology to define and materialize the appropriate hardware and software solutions. LabVIEW 2015 was implemented for high-speed image acquisition and analysis, as well as for the establishment of data communication with a programmable logic controller (PLC via Ethernet and an open communications platform known as Open Platform Communications - OPC. In addition, the Arduino MEGA 2560 platform was used to control the movement of the step motor and the servo motors of the module. Also, is used the Arduino MEGA 2560 to control the movement of the stepper motor and servo motors in the module. Finally, we assessed whether the equipment meets the technical specifications raised by running specific test protocols.
Howell, J.A.; Whiteson, R.
Process control consists of two basic elements: a model of the process and knowledge of the desired control algorithm. In some cases the level of the control algorithm is merely supervisory, as in an alarm-reporting or anomaly-detection system. If the model of the process is known, then a set of equations may often be solved explicitly to provide the control algorithm. Otherwise, the model has to be discovered through empirical studies. Neural networks have properties that make them useful in this application. They can learn (make internal models from experience or observations). The problem of anomaly detection in materials control systems fits well into this general control framework. To successfully model a process with a neutral network, a good set of observables must be chosen. These observables must in some sense adequately span the space of representable events, so that a signature metric can be built for normal operation. In this way, a non-normal event, one that does not fit within the signature, can be detected. In this paper, we discuss the issues involved in applying a neural network model to anomaly detection in materials control systems. These issues include data selection and representation, network architecture, prediction of events, the use of simulated data, and software tools. 10 refs., 4 figs., 1 tab
Donker, M.N. van den; Kilper, T.; Grunsky, D.; Rech, B.; Houben, L.; Kessels, W.M.M.; Sanden, M.C.M. van de
Applying in situ process diagnostics, we identified several process drifts occurring in the parallel plate plasma deposition of microcrystalline silicon (μc-Si:H). These process drifts are powder formation (visible from diminishing dc-bias and changing spatial emission profile on a time scale of 10 0 s), transient SiH 4 depletion (visible from a decreasing SiH emission intensity on a time scale of 10 2 s), plasma heating (visible from an increasing substrate temperature on a time scale of 10 3 s) and a still puzzling long-term drift (visible from a decreasing SiH emission intensity on a time scale of 10 4 s). The effect of these drifts on the crystalline volume fraction in the deposited films is investigated by selected area electron diffraction and depth-profiled Raman spectroscopy. An example shows how the transient depletion and long-term drift can be prevented by suitable process control. Solar cells deposited using this process control show enhanced performance. Options for process control of plasma heating and powder formation are discussed
Stubler, W.F.; O'Hara, J..M.
New human-system interface technologies provide opportunities for improving operator and plant performance. However, if these technologies are not properly implemented, they may introduce new challenges to performance and safety. This paper reports the results from a survey of human factors considerations that arise in the implementation of advanced human-system interface technologies in process control and other complex systems. General trends were identified for several areas based on a review of technical literature and a combination of interviews and site visits with process control organizations. Human factors considerations are discussed for two of these areas, automation and controls
Full Text Available Essential ingredients for fault-tolerant control are the ability to represent system behaviour following the occurrence of a fault, and the ability to exploit this representation for deciding control actions. Gaussian processes seem to be very promising candidates for the first of these, and model predictive control has a proven capability for the second. We therefore propose to use the two together to obtain fault-tolerant control functionality. Our proposal is illustrated by several reasonably realistic examples drawn from flight control.
Will, H.; Mackin, M. A.
Computer program provides natural-language process control from IBM PC or compatible computer. Sets up process-control system that either runs without operator or run by workers who have limited programming skills. Includes three smaller programs. Two of them, written in FORTRAN 77, record data and control research processes. Third program, written in Pascal, generates FORTRAN subroutines used by other two programs to identify user commands with device-driving routines written by user. Also includes set of input data allowing user to define user commands to be executed by computer. Requires personal computer operating under MS-DOS with suitable hardware interfaces to all controlled devices. Also requires FORTRAN 77 compiler and device drivers written by user.
Fahriye Altınay Aksal
Full Text Available The impact of the digital age within learning and social interaction has been growing rapidly. The realm of digital age and computer mediated communication requires reconsidering instruction based on collaborative interactive learning process and socio-contextual experience for learning. Social networking sites such as facebook can help create group space for digital dialogue to inform, question and challenge within a frame of connectivism as learning theory within the digital age. The aim of this study is to elaborate the practice of connectivism as learning theory in terms of internship course. Facebook group space provided social learning platform for dialogue and negotiation beside the classroom learning and teaching process in this study. The 35 internship students provided self-reports within a frame of this qualitative research. This showed how principles of theory practiced and how this theory and facebook group space contribute learning, selfleadership, decision making and reflection skills. As the research reflects a practice of new theory based on action research, learning is not individualistic attempt in the digital age as regards the debate on learning in digital age within a frame of connectivism
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.
This book chapter introduces a novel process systems engineering framework that integrates process control with sustainability assessment tools for the simultaneous evaluation and optimization of process operations. The implemented control strategy consists of a biologically-inspired, multi-agent-based method. The sustainability and performance assessment of process operating points is carried out using the U.S. E.P.A.’s GREENSCOPE assessment tool that provides scores for the selected economic, material management, environmental and energy indicators. The indicator results supply information on whether the implementation of the controller is moving the process towards a more sustainable operation. The effectiveness of the proposed framework is illustrated through a case study of a continuous bioethanol fermentation process whose dynamics are characterized by steady-state multiplicity and oscillatory behavior. This book chapter contribution demonstrates the application of novel process control strategies for sustainability by increasing material management, energy efficiency, and pollution prevention, as needed for SHC Sustainable Uses of Wastes and Materials Management.
Bukkems, B.H.M.; Kostic, D.; Jager, de A.G.; Steinbuch, M.
A combination of model-based and Iterative Learning Control is proposed as a method to achieve high-quality motion control of direct-drive robots in repetitive motion tasks. We include both model-based and learning components in the total control law, as their individual properties influence the
Cercy, M.; Peeler, D.; Stone, M.
This report provides a historical overview and lessons learned associated with the SRS sludge batch (SB) qualification and processing programs. The report covers the framework of the requirements for waste form acceptance, the DWPF Glass Product Control Program (GPCP), waste feed acceptance, examples of how the program complies with the specifications, an overview of the Startup Program, and a summary of continuous improvements and lessons learned. The report includes a bibliography of previous reports and briefings on the topic.
Full Text Available The purpose of this study is to determine the effects on motivation and success within the application of blended learning environments in the foreign language class. The research sample is formed by third grade students studying in the tourism and hotel management programs of the faculty for tourism and the faculty of economics and administrative sciences at the Nevsehir Hacı Bektas Veli University (Turkey in fall semester of the 2012-2013 academic year. The research group consists of 62 students and there of 35 students belong to the experimental group and the other 27 persons belong to the control group. While the experimental group was subject to 14 hours online and 6 hours traditional face to face learning, the control group was subject to only 6 hours traditional face to face learning. The research has been completed after a 10 week application. The data on the research have been collected with German course achievement tests via the German Language Learning Motivation Scale. The results reveal that the experimental group of students attending the German classes in blended learning environments has more success and higher motivation compared to the control group attending German language classes in the traditional learning environment. Even if the learners achieve certain success and motivation findings in the classroom and face to face environments performed along with teaching-learning activities mainly in control of the instructor, the success and motivation effect of the blended learning environment could not be achieved.
Nørgård, Peter Magnus; Sørensen, Paul Haase; Poulsen, Niels Kjølstad
This paper presents a novel approach to design of generalized predictive controllers (GPC) for nonlinear processes. A neural network is used for modelling the process and a gain-scheduling type of GPC is subsequently designed. The combination of neural network models and predictive control has...... frequently been discussed in the neural network community. This paper proposes an approximate scheme, the approximate predictive control (APC), which facilitates the implementation and gives a substantial reduction in the required amount of computations. The method is based on a technique for extracting...... linear models from a nonlinear neural network and using them in designing the control system. The performance of the controller is demonstrated in a simulation study of a pneumatic servo system...
Full Text Available A predictive variable gain strategy in iterative learning control (ILC is introduced. Predictive variable gain iterative learning control is constructed to improve the performance of trajectory tracking. A scheme based on predictive variable gain iterative learning control for eliminating undesirable vibrations of PMSM system is proposed. The basic idea is that undesirable vibrations of PMSM system are eliminated from two aspects of iterative domain and time domain. The predictive method is utilized to determine the learning gain in the ILC algorithm. Compression mapping principle is used to prove the convergence of the algorithm. Simulation results demonstrate that the predictive variable gain is superior to constant gain and other variable gains.
Simonson, Shawn R.; Shadle, Susan E.
Process Oriented Guided Inquiry Learning (POGIL) uses specially designed activities and cooperative learning to teach content and to actively engage students in inquiry, analytical thinking and teamwork. It has been used extensively in Chemistry education, but the use of POGIL is not well documented in other physical and biological sciences. This…
Nakamura, Yasuyuki; Nishi, Shinnosuke; Muramatsu, Yuta; Yasutake, Koichi; Yamakawa, Osamu; Tagawa, Takahiro
In this paper, we introduce a mathematical model for collaborative learning and the answering process for multiple-choice questions. The collaborative learning model is inspired by the Ising spin model and the model for answering multiple-choice questions is based on their difficulty level. An intensive simulation study predicts the possibility of…
to highly optimised industrial host strains. The focus of this project is instead on en-gineering of the process. The question to be answered in this thesis is, given a highly optimised industrial host strain, how can we operate the fermentation process in order to maximise the productivity of the system...... (2012). This model describes the fungal processes operated in the fermentation pilot plant at Novozymes A/S. This model is investigated using uncertainty analysis methods in order to as-sess the applicability to control applications. A mechanistic model approach is desirable, as it is a predictive....... This provides a prediction of the future trajectory of the process, so that it is possible to guide the system to the desired target mass. The control strategy is applied on-line at 550L scale in the Novozymes A/S fermentation pilot plant, and the method is challenged with four diﬀerent sets of process...
This book is the result of a united effort of six European universities to create an overall course on the appplication of artificial intelligence (AI) in process control. The book includes an introduction to key areas including; knowledge representation, expert, logic, fuzzy logic, neural network, and object oriented-based approaches in AI. Part two covers the application to control engineering, part three: Real-Time Issues, part four: CAD Systems and Expert Systems, part five: Intelligent Control and part six: Supervisory Control, Monitoring and Optimization.
Maher, M.; Bahhou, B.; Roux, G. [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France); Maher, M. [Faculte des Sciences, Rabat (Morocco). Lab. de Physique
This paper presents a multivariable adaptive control of a continuous-flow fermentation process for the alcohol production. The linear quadratic control strategy is used for the regulation of substrate and ethanol concentrations in the bioreactor. The control inputs are the dilution rate and the influent substrate concentration. A robust identification algorithm is used for the on-line estimation of linear MIMO model`s parameters. Experimental results of a pilot-plant fermenter application are reported and show the control performances. (authors) 8 refs.
Business processes (industries, administration, hospitals, etc.) become nowadays more and more complex and it is difficult to have a complete understanding of them. The goal of the thesis is to show that machine learning techniques can be used successfully for understanding a process on the basis of
Kragten, M.; Admiraal, W.; Rijlaarsdam, G.
Process diagrams describe how a system functions (e.g. photosynthesis) and are an important type of representation in Biology education. In the present study, we examined students’ learning activities while studying process diagrams, related to their resulting comprehension of these diagrams. Each
Gieskes, J.F.B.; Langenberg, Ilse
Product Innovation is described as a continuous and cross-functional process involving all stages in the product life cycle. This approach gives way to study product innovation processes from a continuous improvement and learning viewpoint. The Continuous Improvement in the global product MAnagement
Baird, J.; Plummer, R.; Haug, C.C.; Huitema, D.
Learning is gaining attention in relation to governance processes for contemporary environmental challenges; however, scholarship at the nexus of learning and environmental governance lacks clarity and understanding about how to define and measure learning, and the linkages between learning, social
The objective of this study is to investigate the benefits of the adoption of electronic learning (E-Learning)in teaching and learning processes. E-Learning is an educational approach that utilizes computer technology, particularly digital technologies that are internet-based, to provide instruction and learning experiences. The definition of e-learning refers to a wide range of applications and processes designed to deliver instruction through electronic means. This means is normally employe...
Arlinah Imam Rahardjo
Full Text Available PCU-CAMEL (Petra Christian University-Computer Aided Mechanical Engineering Department Learning Environment has been developed to integrate the use of this web-based learning environment into the traditional, face-to-face setting of class activities. This integrated learning method is designed as an effort to enrich and improve the teaching-learning process at Petra Christian University. A study was conducted to introduce the use of PCU-CAMEL as a tool in evaluating teaching learning process. The study on this method of evaluation was conducted by using a case analysis on the integration of PCU-CAMEL to the traditional face-to-face meetings of LIS (Library Information System class at the Informatics Engineering Department of Petra Christian University. Students’ responses documented in some features of PCU-CAMEL were measured and analyzed to evaluate the effectiveness of this integrated system in developing intrinsic motivation of the LIS students of the first and second semester of 2004/2005 to learn. It is believed that intrinsic motivation can drive students to learn more. From the study conducted, it is concluded that besides its capability in developing intrinsic motivation, PCU-CAMEL as a web-based learning environment, can also serve as an effective tool for both students and instructors to evaluate the teaching-learning process. However, some weaknesses did exist in using this method of evaluating teaching-learning process. The free style and unstructured form of the documentation features of this web-based learning environment can lead to ineffective evaluation results
Starrenburg, J.G.; Starrenburg, J.G.; van Luenen, W.T.C.; van Luenen, W.T.C.; Oelen, W.; Oelen, W.; van Amerongen, J.
This paper describes the design and realisation of an on-line learning posetracking controller for a three-wheeled mobile robot vehicle. The controller consists of two components. The first is a constant-gain feedback component, designed on the basis of a second-order model. The second is a learning
Aslani, Mohammad; Seipel, Stefan; Wiering, Marco
Traffic signal control can be naturally regarded as a reinforcement learning problem. Unfortunately, it is one of the most difficult classes of reinforcement learning problems owing to its large state space. A straightforward approach to address this challenge is to control traffic signals based on
Monahan, Kevin M.
Process window control enables accelerated design-rule shrinks for both logic and memory manufacturers, but simple microeconomic models that directly link the effects of process window control to maximum profitability are rare. In this work, we derive these links using a simplified model for the maximum rate of profit generated by the semiconductor manufacturing process. We show that the ability of process window control to achieve these economic objectives may be limited by variability in the larger manufacturing context, including measurement delays and process variation at the lot, wafer, x-wafer, x-field, and x-chip levels. We conclude that x-wafer and x-field CD control strategies will be critical enablers of density, performance and optimum profitability at the 90 and 65nm technology nodes. These analyses correlate well with actual factory data and often identify millions of dollars in potential incremental revenue and cost savings. As an example, we show that a scatterometry-based CD Process Window Monitor is an economically justified, enabling technology for the 65nm node.
Regalbuto, M.C.; Misra, B.; Chamberlain, D.B.; Leonard, R.A.; Vandegrift, G.F.
The Generic TRUEX Model (GTM) was used to design a flowsheet for the TRUEX solvent extraction process that would be used to determine its instrumentation and control requirements. Sensitivity analyses of the key process variables, namely, the aqueous and organic flow rates, feed compositions, and the number of contactor stages, were carried out to assess their impact on the operation of the TRUEX process. Results of these analyses provide a basis for the selection of an instrument and control system and the eventual implementation of a control algorithm. Volume Two of this report is an evaluation of the instruments available for measuring many of the physical parameters. Equations that model the dynamic behavior of the TRUEX process have been generated. These equations can be used to describe the transient or dynamic behavior of the process for a given flowsheet in accordance with the TRUEX model. Further work will be done with the dynamic model to determine how and how quickly the system responds to various perturbations. The use of perturbation analysis early in the design stage will lead to a robust flowsheet, namely, one that will meet all process goals and allow for wide control bounds. The process time delay, that is, the speed with which the system reaches a new steady state, is an important parameter in monitoring and controlling a process. In the future, instrument selection and point-of-variable measurement, now done using the steady-state results reported here, will be reviewed and modified as necessary based on this dynamic method of analysis
This unique text/reference describes in detail the latest advances in unsupervised process monitoring and fault diagnosis with machine learning methods. Abundant case studies throughout the text demonstrate the efficacy of each method in real-world settings. The broad coverage examines such cutting-edge topics as the use of information theory to enhance unsupervised learning in tree-based methods, the extension of kernel methods to multiple kernel learning for feature extraction from data, and the incremental training of multilayer perceptrons to construct deep architectures for enhanced data
Three case studies of in-house developed e-learning education in public organizations with different pedagogical approaches are used as a starting point for discussion regarding the implementation challenges of e-learning at work. The aim of this article is to contribute to the understanding of integrating mechanisms of e-learning outcomes into work processes in large, public organizations. The case studies were analyzed from a socio-cultural perspective using the MOA-model as a frame of refe...
AFRL-RH-WP-TR-2016-0074 ACTIVE LEARNING FOR AUTOMATIC AUDIO PROCESSING OF UNWRITTEN LANGUAGES (ALAPUL) Dimitra Vergyri Andreas Kathol Wen Wang...FA8650-15-C-9101 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) *Dimitra Vergyri; Andreas Kathol; Wen Wang; Chris Bartels; Julian VanHout...feature transform through deep auto-encoders for better phone recognition performance. We target iterative learning to improve the system through
Fosshage, Erik D.; Drewien, Celeste A.; Eras, Kenneth; Hartwig, Ronald Craig; Post, Debra S.; Stoecker, Nora Kathleen
The Lessons Learned Process Improvement Team was tasked to gain an understanding of the existing lessons learned environment within the major programs at Sandia National Laboratories, identify opportunities for improvement in that environment as compared to desired attributes, propose alternative implementations to address existing inefficiencies, perform qualitative evaluations of alternative implementations, and recommend one or more near-term activities for prototyping and/or implementation. This report documents the work and findings of the team.
Tosun, Cemal; Taskesenligil, Yavuz
The aim of this study was to investigate the effect of Problem-Based Learning (PBL) on undergraduate students' learning about solutions and their physical properties, and on their scientific processing skills. The quasi experimental study was carried out through non-equivalent control and comparison groups pre-post test design. The data were…
Full Text Available The paper deals with new training technologies development based on approach to distance learning website, implemented in the laboratory of a Traffic Engineering study branch at Faculty of Transport. The discussed computing interface allows students complete knowledge of traffic controllers’ architecture and machine language programming fundamentals. These training facilities are available at home; at their remote terminal. The training resources consist of electronic / computer based training; guidebooks and software units. The laboratory provides the students with an interface entering into simulation packages and programming interfaces, supporting the web training facilities. The courseware complexity selection is one of the most difficult factors in intelligent training unit’s development. The dynamically configured application provides the user with his individually set structure of the training resources. The trainee controls the application structure and complexity, from the time he started. For simplifying the training process and studying activities, several unifications were provided. The introduced ideas need various standardisations, simplifying the e-learning units’ development and application control processes , . Further training facilities development concerns virtual laboratory environment organisation in laboratories of Transport Faculty.
Process-oriented learning designs are innovative learning activities that include a set of inter-related learning tasks and are generic (could be used across disciplines). An example includes a problem-solving process widely used in problem-based learning today. Most of the existing process-oriented learning designs are not documented, let alone…
van Soeren, Mary; Devlin-Cop, Sandra; Macmillan, Kathleen; Baker, Lindsay; Egan-Lee, Eileen; Reeves, Scott
Simulated learning activities are increasingly being used in health professions and interprofessional education (IPE). Specifically, IPE programs are frequently adopting role-play simulations as a key learning approach. Despite this widespread adoption, there is little empirical evidence exploring the teaching and learning processes embedded within this type of simulation. This exploratory study provides insight into the nature of these processes through the use of qualitative methods. A total of 152 clinicians, 101 students and 9 facilitators representing a range of health professions, participated in video-recorded role-plays and debrief sessions. Videotapes were analyzed to explore emerging issues and themes related to teaching and learning processes related to this type of interprofessional simulated learning experience. In addition, three focus groups were conducted with a subset of participants to explore perceptions of their educational experiences. Five key themes emerged from the data analysis: enthusiasm and motivation, professional role assignment, scenario realism, facilitator style and background and team facilitation. Our findings suggest that program developers need to be mindful of these five themes when using role-plays in an interprofessional context and point to the importance of deliberate and skilled facilitation in meeting desired learning outcomes.
Forrin, Noah D; MacLeod, Colin M
In three experiments, we tested a relative-speed-of-processing account of color-word contingency learning, a phenomenon in which color identification responses to high-contingency stimuli (words that appear most often in particular colors) are faster than those to low-contingency stimuli. Experiment 1 showed equally large contingency-learning effects whether responding was to the colors or to the words, likely due to slow responding to both dimensions because of the unfamiliar mapping required by the key press responses. For Experiment 2, participants switched to vocal responding, in which reading words is considerably faster than naming colors, and we obtained a contingency-learning effect only for color naming, the slower dimension. In Experiment 3, previewing the color information resulted in a reduced contingency-learning effect for color naming, but it enhanced the contingency-learning effect for word reading. These results are all consistent with contingency learning influencing performance only when the nominally irrelevant feature is faster to process than the relevant feature, and therefore are entirely in accord with a relative-speed-of-processing explanation.
Epting, U; CERN. Geneva. TS Department
System providers are today creating process control systems based on remote connectivity using internet technology, effectively exposing these systems to the same threats as corporate computers. It is becoming increasingly difficult and costly to patch/maintain the technical infrastructure monitoring and control systems to remove these vulnerabilities. A strategy including risk assessment, security policy issues, service level agreements between the IT department and the controls engineering groups must be defined. In addition an increased awareness of IT security in the controls system engineering domain is needed. As consequence of these new factors the control system architectures have to take into account security requirements, that often have an impact on both operational aspects as well as on the project and maintenance cost. Manufacturers of industrial control system equipment do however also propose progressively security related solutions that can be used for our active projects. The paper discusses ...
Proper management of dynamic systems (e.g. cooling systems of nuclear power plants or production and warehousing) is important to ensure public safety and economic success. So far, research has provided broad evidence for systematic shortcomings in individuals' control performance of dynamic systems. This research aims to investigate whether groups manifest synergy (Larson, 2010) and outperform individuals and if so, what processes lead to these performance advantages. In three experiments - including simulations of a nuclear power plant and a business setting - I compare the control performance of three-person-groups to the average individual performance and to nominal groups (N = 105 groups per experiment). The nominal group condition captures the statistical advantage of aggregated group judgements not due to social interaction. First, results show a superior performance of groups compared to individuals. Second, a meta-analysis across all three experiments shows interaction-based process gains in dynamic control tasks: Interacting groups outperform the average individual performance as well as the nominal group performance. Third, group interaction leads to stable individual improvements of group members that exceed practice effects. In sum, these results provide the first unequivocal evidence for interaction-based performance gains of groups in dynamic control tasks and imply that employers should rely on groups to provide opportunities for individual learning and to foster dynamic system control at its best.
Carcagno, R.; Ganni, V.
This paper presents a methodology to describe process control requirements for helium refrigeration plants. The SSC requires a greater level of automation for its refrigeration plants than is common in the cryogenics industry, and traditional methods (e.g., written descriptions) used to describe process control requirements are not sufficient. The methodology presented in this paper employs tabular and graphic representations in addition to written descriptions. The resulting document constitutes a tool for efficient communication among the different people involved in the design, development, operation, and maintenance of the control system. The methodology is not limited to helium refrigeration plants, and can be applied to any process with similar requirements. The paper includes examples
Brown, C. W. [Babcock International Group PLC (formerly UKAEA Ltd) B21 Forss, Thurso, Caithness, Scotland (United Kingdom)
Dounreay was the UK's centre of fast reactor research and development from 1955 until 1994 and is now Scotland's largest nuclear clean up and demolition project. After four decades of research, Dounreay is now a site of construction, demolition and waste management, designed to return the site to as near as practicable to its original condition. Dounreay has a turnover in the region of Pounds 150 million a year and employs approximately 900 people. It subcontracts work to 50 or so companies in the supply chain and this provides employment for a similar number of people. The plan for decommissioning the site anticipates all redundant buildings will be cleared in the short term. The target date to achieve interim end state by 2039 is being reviewed in light of Government funding constraints, and will be subject to change through the NDA led site management competition. In the longer term, controls will be put in place on the use of contaminated land until 2300. In supporting the planning, management and organisational aspects for this complex decommissioning programme an integrated programme controls system has been developed and deployed. This consists of a combination of commercial and bespoke tools integrated to support all aspects of programme management, namely scope, schedule, cost, estimating and risk in order to provide baseline and performance management data based upon the application of earned value management principles. Through system evolution and lessons learned, the main benefits of this approach are management data consistency, rapid communication of live information, and increased granularity of data providing summary and detailed reports which identify performance trends that lead to corrective actions. The challenges of such approach are effective use of the information to realise positive changes, balancing the annual system support and development costs against the business needs, and maximising system performance. (author)
Chauvel, Guillaume; Maquestiaux, François; Didierjean, André; Joubert, Sven; Dieudonné, Bénédicte; Verny, Marc
Does normal aging inexorably lead to diminished motor learning abilities? This article provides an overview of the literature on the question, with particular emphasis on the functional dissociation between two sets of memory processes: declarative, effortful processes, and non-declarative, automatic processes. There is abundant evidence suggesting that aging does impair learning when past memories of former actions are required (episodic memory) and recollected through controlled processing (working memory). However, other studies have shown that aging does not impair learning when motor actions are performed non verbally and automatically (tapping procedural memory). These findings led us to hypothesize that one can minimize the impact of aging on the ability to learn new motor actions by favouring procedural learning. Recent data validating this hypothesis are presented. Our findings underline the importance of developing new motor learning strategies, which "bypass" declarative, effortful memory processes.
Thibault, J [Dept. of Chemical Engineering, Laval Univ., Quebec City, PQ (Canada); Najim, K [CNRS, URA 192, GRECO SARTA, Ecole Nationale Superieure d' Ingenieurs de Genie Chimique, 31 - Toulouse (France)
A variable structure learning automaton is used as an optimization and control of a continuous stirred tank fermenter. The alogrithm requires no modelling of the process. The use of appropriate learning rules enables to locate the optimum dilution rate in order to maximize an objective cost function. It is shown that a hierarchical structure of automata can adapt to environmental changes and can also modify efficiently the domain of variation of the control variable in order to encompass the optimum value. (orig.)
Tsiang, T. H.; Wanamaker, John L.
A precise control of composite material processing would not only improve part quality, but it would also directly reduce the overall manufacturing cost. The development and incorporation of sensors will help to generate real-time information for material processing relationships and equipment characteristics. In the present work, the thermocouple, pressure transducer, and dielectrometer technologies were investigated. The monitoring sensors were integrated with the computerized control system in three non-autoclave fabrication techniques: hot-press, self contained tool (self heating and pressurizing), and pressure vessel). The sensors were implemented in the parts and tools.
A wide variety of safety systems are in use today in the process industries. Most of these systems rely on control software using procedural programming languages. This study investigates the use of functional graphical languages for controls in the process industry. Different vendor proprietary software and languages are investigated and evaluation criteria are outlined based on ability to meet regulatory requirements, reference sites involving applications with similar safety concerns, QA/QC procedures, community of users, type and user-friendliness of the man-machine interface, performance of operational code, and degree of flexibility. (author) 16 refs., 4 tabs
Rehmat, Amirali G.; Patel, Jitendra G.
An apparatus and process for control and maintenance of fluidized beds under non-steady state conditions. An ash removal conduit is provided for removing solid particulates from a fluidized bed separate from an ash discharge conduit in the lower portion of the grate supporting such a bed. The apparatus and process of this invention is particularly suitable for use in ash agglomerating fluidized beds and provides control of the fluidized bed before ash agglomeration is initiated and during upset conditions resulting in stable, sinter-free fluidized bed maintenance.
Numerical cognition relies on interactions within and between multiple functional brain systems, including those subserving quantity processing, working memory, declarative memory, and cognitive control. This chapter describes recent advances in our understanding of memory and control circuits in mathematical cognition and learning. The working memory system involves multiple parietal-frontal circuits which create short-term representations that allow manipulation of discrete quantities over several seconds. In contrast, hippocampal-frontal circuits underlying the declarative memory system play an important role in formation of associative memories and binding of new and old information, leading to the formation of long-term memories that allow generalization beyond individual problem attributes. The flow of information across these systems is regulated by flexible cognitive control systems which facilitate the integration and manipulation of quantity and mnemonic information. The implications of recent research for formulating a more comprehensive systems neuroscience view of the neural basis of mathematical learning and knowledge acquisition in both children and adults are discussed. © 2016 Elsevier B.V. All rights reserved.
Numerical cognition relies on interactions within and between multiple functional brain systems, including those subserving quantity processing, working memory, declarative memory, and cognitive control. This chapter describes recent advances in our understanding of memory and control circuits in mathematical cognition and learning. The working memory system involves multiple parietal–frontal circuits which create short-term representations that allow manipulation of discrete quantities over several seconds. In contrast, hippocampal–frontal circuits underlying the declarative memory system play an important role in formation of associative memories and binding of new and old information, leading to the formation of long-term memories that allow generalization beyond individual problem attributes. The flow of information across these systems is regulated by flexible cognitive control systems which facilitate the integration and manipulation of quantity and mnemonic information. The implications of recent research for formulating a more comprehensive systems neuroscience view of the neural basis of mathematical learning and knowledge acquisition in both children and adults are discussed. PMID:27339012
Rubio-Herrero, Javier; Chandan, Vikas; Siegel, Charles M.; Vishnu, Abhinav; Vrabie, Draguna L.
Buildings consume a significant amount of energy worldwide. Several building optimization and control use cases require models of energy consumption which are control oriented, have high predictive capability, imposes minimal data pre-processing requirements, and have the ability to be adapted continuously to account for changing conditions as new data becomes available. Data driven modeling techniques, that have been investigated so far, while promising in the context of buildings, have been unable to simultaneously satisfy all the requirements mentioned above. In this context, deep learning techniques such as Recurrent Neural Networks (RNNs) hold promise, empowered by advanced computational capabilities and big data opportunities. In this paper, we propose a deep learning based methodology for the development of control oriented models for building energy management and test in on data from a real building. Results show that the proposed methodology outperforms other data driven modeling techniques significantly. We perform a detailed analysis of the proposed methodology along dimensions such as topology, sensitivity, and downsampling. Lastly, we conclude by envisioning a building analytics suite empowered by the proposed deep framework, that can drive several use cases related to building energy management.
McKittrick, Brendan J
The concept of parallel processing is not a new one, but the application of it to control engineering tasks is a relatively recent development, made possible by contemporary hardware and software innovation. It has long been accepted that, if properly orchestrated several processors/CPUs when combined can form a powerful processing entity. What prevented this from being implemented in commercial systems was the adequacy of the microprocessor for most tasks and hence the expense of a multi-pro...
McKernan, John L; Ellenbecker, Michael J
Exothermic or heated processes create potentially unsafe work environments for an estimated 5-10 million American workers each year. Excessive heat and process contaminants have the potential to cause acute health effects such as heat stroke, and chronic effects such as manganism in welders. Although millions of workers are exposed to exothermic processes, insufficient attention has been given to continuously improving engineering technologies for these processes to provide effective and efficient control. Currently there is no specific occupational standard established by OSHA regarding exposure to heat from exothermic processes, therefore it is important to investigate techniques that can mitigate known and potential adverse occupational health effects. The current understanding of engineering controls for exothermic processes is primarily based on a book chapter written by W. C. L. Hemeon in 1955. Improvements in heat transfer and meteorological theory necessary to design improved process controls have occurred since this time. The research presented involved a review of the physical properties, heat transfer and meteorological theories governing buoyant air flow created by exothermic processes. These properties and theories were used to identify parameters and develop equations required for the determination of buoyant volumetric flow to assist in improving ventilation controls. Goals of this research were to develop and describe a new (i.e. proposed) flow equation, and compare it to currently accepted ones by Hemeon and the American Conference of Governmental Industrial Hygienists (ACGIH). Numerical assessments were conducted to compare solutions from the proposed equations for plume area, mean velocity and flow to those from the ACGIH and Hemeon. Parameters were varied for the dependent variables and solutions from the proposed, ACGIH, and Hemeon equations for plume area, mean velocity and flow were analyzed using a randomized complete block statistical
Woo, Wai; Sulaiman, Hamzah; Othman, Mohd; Saat, Mohd
This book presents important research findings and recent innovations in the field of machine learning and signal processing. A wide range of topics relating to machine learning and signal processing techniques and their applications are addressed in order to provide both researchers and practitioners with a valuable resource documenting the latest advances and trends. The book comprises a careful selection of the papers submitted to the 2015 International Conference on Machine Learning and Signal Processing (MALSIP 2015), which was held on 15–17 December 2015 in Ho Chi Minh City, Vietnam with the aim of offering researchers, academicians, and practitioners an ideal opportunity to disseminate their findings and achievements. All of the included contributions were chosen by expert peer reviewers from across the world on the basis of their interest to the community. In addition to presenting the latest in design, development, and research, the book provides access to numerous new algorithms for machine learni...
emphasis on initiating learning processes in the client enter-prise in a way that will develop the OHS management capabilities of that enterprise. This presentation is based on a research program focussing on how OHS consultants go about when they are involved in consultancy on technological change...... processes in client enter-prises. Specifically the learning perspective will be touched upon. The research programme included four cases in different client enterprises: 1) New tech-nology in a logistic department of a brewery, 2) new pharmaceutical process facility, 3) design of a new catering centre...... in another institution than pre-sent the users to blueprints and then ask them to put forward technical suggestions to im-prove the workplace design. In conclusion, the study pointed out that the OHS consultants had different work practices on learning aspects of their consultancy. Several constraining...
Full Text Available As customers demand easier access to individualized products and services, companies now face an ongoing problem of how to deliver flexible and innovative solutions while maintaining efficiency and competitiveness. In this environment, the only sustainable form of competitive advantage rests in the ability to learn faster than the competition (de Geus, 1988. The article returns to the somewhat forgotten concept of the learning organization and explores how its principles can be applied with the use of dynamic business process management (dynamic BPM. Enabling in this concept individual or team-based limited experimentation and providing conditions for learning though experience in the course of performing business processes allows for the constant creation of practical knowledge. This article provides examples of how dynamic BPM facilitates the constant creation and verification of practical knowledge, with the aim of improving and adapting processes to maintain the competitive advantage of the organization.
Full Text Available Products of forming processes are subject to quality fluctuations due to uncertainty in semi-finished part properties as well as process conditions and environment. An approach to cope with these uncertainties is the implementation of a closed-loop control taking into account the actual product properties measured by sensors or estimated by a mathematical process model. Both methods of uncertainty control trade off with a financial effort. In case of sensor integration the effort is the cost of the sensor including signal processing as well as the design and manufacturing effort for integration. In case of an estimation model the effort is mainly determined by the time and knowledge needed to derive the model, identify the parameters and implement the model into the PLC. The risk of mismatch between model and reality as well as the risk of wrong parameter identification can be assumed as additional uncertainty (model uncertainty. This paper evaluates controlled and additional uncertainty by taking into account process boundary conditions like the degree of fluctuations in semi-finished part properties. The proposed evaluation is demonstrated by the analysis of exemplary processes.
Berglund, M; Karltun, A
This paper was based on case study research at the Swedish Mail Service Division and it addresses learning time to sort mail at new districts and means to support the learning process on an individual as well as organizational level. The study population consisted of 46 postmen and one team leader in the Swedish Mail Service Division. Data were collected through measurements of time for mail sorting, interviews and a focus group. The study showed that learning to sort mail was a much more complex process and took more time than expected by management. Means to support the learning process included clarification of the relationship between sorting and the topology of the district, a good work environment, increased support from colleagues and management, and a thorough introduction for new postmen. The identified means to support the learning process require an integration of human, technological and organizational aspects. The study further showed that increased operations flexibility cannot be reinforced without a systems perspective and thorough knowledge about real work activities and that ergonomists can aid businesses to acquire this knowledge.
Full Text Available This paper presents a hybrid dynamic control approach to the realization of humanoid biped robotic walk, focusing on the policy gradient episodic reinforcement learning with fuzzy evaluative feedback. The proposed structure of controller involves two feedback loops: a conventional computed torque controller and an episodic reinforcement learning controller. The reinforcement learning part includes fuzzy information about Zero-Moment- Point errors. Simulation tests using a medium-size 36-DOF humanoid robot MEXONE were performed to demonstrate the effectiveness of our method.
Valache, Cornelia Mariana
The paper presents the process of 'Training Change Control' at Cernavoda NPP. This process is a systematic approach that allows determination of the most effective training and/or non-training solutions for challenges that may influence the content and conditions for a training program or course. Changes may be the result of: - response to station systems or equipment modifications; - new or revised procedures; - regulatory requirements; - external organizations requirements; - internal evaluations meaning feedback from trainees, trainers, management or post-training evaluations; - self-assessments; - station condition reports; - operating experience (OPEX); - modifications of job scope; - management input. The Training Change Control Process at Cernavoda NPP includes the following aspects. The first step is the identification of all the initiating factors for a potential training change. Then, retain only those, which could have an impact on training and classify them in two categories: as deficiencies or as enhancement suggestions. The process is different for the two categories. The deficiency category supposes the application of the Training Needs Analysis (TNA) process. This is a performance-oriented process, resulting in more competent employees, solving existing and potential performance problems. By using needs analysis to systematically determine what people or courses and programs are expected to do and gathering data to reveal what they are really doing, we can receive a clear picture of the problem and then we can establish corrective action plans to fix it. The process is supported by plant subjects matter and by training specialists. On the other hand, enhancements suggestions are assessed by designated experienced persons and then are implemented in the training process. Regarding these two types of initiating factors for the training change control process, the final result consists of a training improvement, raising the effectiveness, efficiency or
Full Text Available A radical educational reform occurred in Turkey in 2005; and curriculum of primary education courses was renewed. New curriculum was prepared based on constructivist approach. In this scope, curriculum of Turkish course was also renewed. This study aims at evaluating applications and opinions of teachers and students about learning and teaching process prescribed in Turkish Course (1st-5th Grades Curriculum. Within the scope of the study, semi-structured interview was made with 10 teachers and 12 students. In addition, process teaching a text was evaluated via structured observation method in 5 different classes. According to the results of the study, primary school teachers find some stages in learning – teaching process prescribed in the curriculum unnecessary and therefore do not apply them. Teachers mentioned that some texts are above the student level; and they sometimes experience time and material problems. It was seen in the present study that teachers do not have enough information about learning and teaching process in the new curriculum; they do not have high success levels in the applications; and they usually do not apply the forms for evaluating the process in the curriculum. It was found out that, in spite of these problems, courses are student-centred as prescribed in the curriculum; and students have positive opinions about stages of learning and teaching process.
Williams, Camille K.; Tseung, Victrine; Carnahan, Heather
Studies of self-controlled practice have shown benefits when learners controlled feedback schedule, use of assistive devices and task difficulty, with benefits attributed to information processing and motivational advantages of self-control. Although haptic assistance serves as feedback, aids task performance and modifies task difficulty, researchers have yet to explore whether self-control over haptic assistance could be beneficial for learning. We explored whether self-control of haptic assistance would be beneficial for learning a tracing task. Self-controlled participants selected practice blocks on which they would receive haptic assistance, while participants in a yoked group received haptic assistance on blocks determined by a matched self-controlled participant. We inferred learning from performance on retention tests without haptic assistance. From qualitative analysis of open-ended questions related to rationales for/experiences of the haptic assistance that was chosen/provided, themes emerged regarding participants’ views of the utility of haptic assistance for performance and learning. Results showed that learning was directly impacted by the frequency of haptic assistance for self-controlled participants only and view of haptic assistance. Furthermore, self-controlled participants’ views were significantly associated with their requested haptic assistance frequency. We discuss these findings as further support for the beneficial role of self-controlled practice for motor learning. PMID:29255438
Full Text Available Stripper columns are used for sweetening crude oil, and they must hold product hydrogen sulfide content as near the set points as possible in the faces of upsets. Since product quality cannot be measured easily and economically online, the control of product quality is often achieved by maintaining a suitable tray temperature near its set point. Tray temperature control method, however, is not a proper option for a multi-component stripping column because the tray temperature does not correspond exactly to the product composition. To overcome this problem, secondary measurements can be used to infer the product quality and adjust the values of the manipulated variables. In this paper, we have used a novel inferential control approach base on adaptive network fuzzy inference system (ANFIS for stripping process. ANFIS with different learning algorithms is used for modeling the process and building a composition estimator to estimate the composition of the bottom product. The developed estimator is tested, and the results show that the predictions made by ANFIS structure are in good agreement with the results of simulation by ASPEN HYSYS process simulation package. In addition, inferential control by the implementation of ANFIS-based online composition estimator in a cascade control scheme is superior to traditional tray temperature control method based on less integral time absolute error and low duty consumption in reboiler.
Khany, Reza; Amiri, Majid
Theoretical developments in second or foreign language motivation research have led to a better understanding of the convoluted nature of motivation in the process of language acquisition. Among these theories, action control theory has recently shown a good deal of explanatory power in second language learning contexts and in the presence of…
Mears, Lisa; Stocks, Stuart; Sin, Gürkan
Bioprocesses are inherently sensitive to fluctuations in processing conditions and must be tightly regulated to maintain cellular productivity. Industrial fermentations are often difficult to replicate across production sites or between facilities as the small operating differences in the equipment...... of a fermentation. Industrial fermentation processes are typically operated in fed batch mode, which also poses specific challenges for process monitoring and control. This is due to many reasons including non-linear behaviour, and a relatively poor understanding of the system dynamics. It is therefore challenging...
Di Giacomo, Dina; Ranieri, Jessica; Lacasa, Pilar
Large use of technology improved quality of life across aging and favoring the development of digital skills. Digital skills can be considered an enhancing to human cognitive activities. New research trend is about the impact of the technology in the elaboration information processing of the children. We wanted to analyze the influence of technology in early age evaluating the impact on cognition. We investigated the performance of a sample composed of n. 191 children in school age distributed in two groups as users: high digital users and low digital users. We measured the verbal and visuoperceptual cognitive performance of children by n. 8 standardized psychological tests and ad hoc self-report questionnaire. Results have evidenced the influence of digital exposition on cognitive development: the cognitive performance is looked enhanced and better developed: high digital users performed better in naming, semantic, visual memory and logical reasoning tasks. Our finding confirms the data present in literature and suggests the strong impact of the technology using not only in the social, educational and quality of life of the people, but also it outlines the functionality and the effect of the digital exposition in early age; increased cognitive abilities of the children tailor digital skilled generation with enhanced cognitive processing toward to smart learning.
This article reports and reflects on the learning achievements and the educational experiences in connection with the first years of the curriculum in Architecture at Aalborg University ?s Civil Engineer Education in Architecture & Design. In the article I will focus on the learning activity and ...... the students need in order to concentrate, mobilize creativity and find the personal design language which is a precondition for making good architecture....... and the method that are developed during the semester when working with an Integrated Design Process combining architecture, design, functional aspects, energy consumption, indoor environment, technology, and construction. I will emphasize the importance of working with different tools in the design process, e...
Full Text Available Inaccurate system parameters and unpredicted external disturbances affect the performance of non-linear controllers. In this paper, a new adaptive control algorithm under the reinforcement framework is proposed to stabilize a quadrotor helicopter. Based on a command-filtered non-linear control algorithm, adaptive elements are added and learned by policy-search methods. To predict the inaccurate system parameters, a new kernel-based regression learning method is provided. In addition, Policy learning by Weighting Exploration with the Returns (PoWER and Return Weighted Regression (RWR are utilized to learn the appropriate parameters for adaptive elements in order to cancel the effect of external disturbance. Furthermore, numerical simulations under several conditions are performed, and the ability of adaptive trajectory-tracking control with reinforcement learning are demonstrated.
Kozubal, A.J.; Weiss, R.E.
When we initiated the control system design for the Ground Test Accelerator (GTA), we envisioned a system that would be flexible enough to handle the changing requirements of an experimental project. This control system would use a developers' toolkit to reduce the cost and time to develop applications for GTA, and through the use of open standards, the system would accommodate unforeseen requirements as they arose. Furthermore, we would attempt to demonstrate on GTA a level of automation far beyond that achieved by existing accelerator control systems. How well did we achieve these goals? What were the stumbling blocks to deploying the control system, and what assumptions did we make about requirements that turned out to be incorrect? In this paper we look at the process of developing a control system that evolved into what is now the ''Experimental Physics and Industrial Control System'' (EPICS). Also, we assess the impact of this system on the GTA project, as well as the impact of GTA on EPICS. The lessons learned on GTA will be valuable for future projects
Lim, Yongseob; Ulsoy, A Galip
Process Control for Sheet-Metal Stamping presents a comprehensive and structured approach to the design and implementation of controllers for the sheet metal stamping process. The use of process control for sheet-metal stamping greatly reduces defects in deep-drawn parts and can also yield large material savings from reduced scrap. Sheet-metal forming is a complex process and most often characterized by partial differential equations that are numerically solved using finite-element techniques. In this book, twenty years of academic research are reviewed and the resulting technology transitioned to the industrial environment. The sheet-metal stamping process is modeled in a manner suitable for multiple-input multiple-output control system design, with commercially available sensors and actuators. These models are then used to design adaptive controllers and real-time controller implementation is discussed. Finally, experimental results from actual shopfloor deployment are presented along with ideas for further...
WL-TR-93-1153 INVESTIGATION OF DRIVE-REINFORCEMEN% LEARNING AND APPLICATION OF LEARNING TO FLIGHT CONTROL AD-A277 442 WALTER L. BAKER (ED), STEPHEN ...OF LEARNING TO FUIGHT CONTROL PE 62204 ___ ___ ___ ___ __ ___ ___ ___ ___ ___ ___ __ PR 2003 6. AUTHOR(S) TA 05 WALTER L. BAKER (ED), STEPHEN C. ATKINS...34 Computers and Thought, E. A. Freigenbaum and J. Feldman (eds.), Mc- Graw Hill, New York, (1959).  Holland, J. H., "Escaping Brittleness: The Possibility
Elaine H.J. Yew
Full Text Available In this review, we provide an overview of the process of problem-based learning (PBL and the studies examining the effectiveness of PBL. We also discuss a number of naturalistic and empirical studies that have examined the process of PBL and how its various components impact students’ learning. We conclude that the studies comparing the relative effectiveness of PBL are generally consistent in demonstrating its superior efficacy for longer-term knowledge retention and in the application of knowledge. Studies on the process of PBL, however, are still inconclusive as to which component(s of PBL most significantly impact students’ learning, although causal studies have demonstrated that all the phases of PBL are necessary in influencing students’ learning outcomes.
DePasque, Samantha; Tricomi, Elizabeth
Learning commonly requires feedback about the consequences of one's actions, which can drive learners to modify their behavior. Motivation may determine how sensitive an individual might be to such feedback, particularly in educational contexts where some students value academic achievement more than others. Thus, motivation for a task might influence the value placed on performance feedback and how effectively it is used to improve learning. To investigate the interplay between intrinsic motivation and feedback processing, we used functional magnetic resonance imaging (fMRI) during feedback-based learning before and after a novel manipulation based on motivational interviewing, a technique for enhancing treatment motivation in mental health settings. Because of its role in the reinforcement learning system, the striatum is situated to play a significant role in the modulation of learning based on motivation. Consistent with this idea, motivation levels during the task were associated with sensitivity to positive versus negative feedback in the striatum. Additionally, heightened motivation following a brief motivational interview was associated with increases in feedback sensitivity in the left medial temporal lobe. Our results suggest that motivation modulates neural responses to performance-related feedback, and furthermore that changes in motivation facilitate processing in areas that support learning and memory. Copyright © 2015. Published by Elsevier Inc.
DePasque, Samantha; Tricomi, Elizabeth
Learning commonly requires feedback about the consequences of one’s actions, which can drive learners to modify their behavior. Motivation may determine how sensitive an individual might be to such feedback, particularly in educational contexts where some students value academic achievement more than others. Thus, motivation for a task might influence the value placed on performance feedback and how effectively it is used to improve learning. To investigate the interplay between intrinsic motivation and feedback processing, we used functional magnetic resonance imaging (fMRI) during feedback-based learning before and after a novel manipulation based on motivational interviewing, a technique for enhancing treatment motivation in mental health settings. Because of its role in the reinforcement learning system, the striatum is situated to play a significant role in the modulation of learning based on motivation. Consistent with this idea, motivation levels during the task were associated with sensitivity to positive versus negative feedback in the striatum. Additionally, heightened motivation following a brief motivational interview was associated with increases in feedback sensitivity in the left medial temporal lobe. Our results suggest that motivation modulates neural responses to performance-related feedback, and furthermore that changes in motivation facilitates processing in areas that support learning and memory. PMID:26112370
Rottman, Benjamin Margolin; Marcum, Zachary A; Thorpe, Carolyn T; Gellad, Walid F
Non-adherence to medications is one of the largest contributors to sub-optimal health outcomes. Many theories of adherence include a 'value-expectancy' component in which a patient decides to take a medication partly based on expectations about whether it is effective, necessary, and tolerable. We propose reconceptualising this common theme as a kind of 'causal learning' - the patient learns whether a medication is effective, necessary, and tolerable, from experience with the medication. We apply cognitive psychology theories of how people learn cause-effect relations to elaborate this causal-learning challenge. First, expectations and impressions about a medication and beliefs about how a medication works, such as delay of onset, can shape a patient's perceived experience with the medication. Second, beliefs about medications propagate both 'top-down' and 'bottom-up', from experiences with specific medications to general beliefs about medications and vice versa. Third, non-adherence can interfere with learning about a medication, because beliefs, adherence, and experience with a medication are connected in a cyclic learning problem. We propose that by conceptualising non-adherence as a causal-learning process, clinicians can more effectively address a patient's misconceptions and biases, helping the patient develop more accurate impressions of the medication.
Harms, Madeline B; Shannon Bowen, Katherine E; Hanson, Jamie L; Pollak, Seth D
Children who experience severe early life stress show persistent deficits in many aspects of cognitive and social adaptation. Early stress might be associated with these broad changes in functioning because it impairs general learning mechanisms. To explore this possibility, we examined whether individuals who experienced abusive caregiving in childhood had difficulties with instrumental learning and/or cognitive flexibility as adolescents. Fifty-three 14-17-year-old adolescents (31 exposed to high levels of childhood stress, 22 control) completed an fMRI task that required them to first learn associations in the environment and then update those pairings. Adolescents with histories of early life stress eventually learned to pair stimuli with both positive and negative outcomes, but did so more slowly than their peers. Furthermore, these stress-exposed adolescents showed markedly impaired cognitive flexibility; they were less able than their peers to update those pairings when the contingencies changed. These learning problems were reflected in abnormal activity in learning- and attention-related brain circuitry. Both altered patterns of learning and neural activation were associated with the severity of lifetime stress that the adolescents had experienced. Taken together, the results of this experiment suggest that basic learning processes are impaired in adolescents exposed to early life stress. These general learning mechanisms may help explain the emergence of social problems observed in these individuals. © 2017 The Authors. Developmental Science Published by John Wiley & Sons Ltd.
Eight invited papers on the general theme of 'Dosimetry and Control of Radiation Processing', presented at a one day symposium held at the National Physical Laboratory, are collected together in this document. Seven of the papers are selected and indexed separately. (author)
Grasz, E.L.; Merrill, R.D.; Couture, S.A.
At present waste and residue processing includes steps that require human interaction. The risk of exposure to unknown hazardous materials and the potential for radiation contamination motivates the desire to remove operators from these processes. Technologies that facilitate this include glove box robotics, modular systems for remote and automated servicing, and interactive controls that minimize human intervention. LLNL is developing an automated system which is designed to supplant the operator for glove box tasks, thus protecting the operator from the risk of radiation exposure and minimizing operator-associated waste. Although most of the processing can be automated with minimal human interaction, there are some tasks where intelligent intervention is both desirable and necessary to adapt to Enexpected circumstances and events. These activities require that the operator interact with the process using a remote manipulator which provides or reflects a natural feel to the operator. The remote manipulation system which was developed incorporates sensor fusion and interactive control, and provides the operator with an effective means of controlling the robot in a potentially unknown environment. This paper describes recent accomplishments in technology development and integration, and outlines the future goals of Lawrence Livermore National Laboratory for achieving this integrated interactive control capability
On May 21st , 2008, the Dutch National Infrastructure against Cyber Crime (NICC) organised their first Process Control Security Event. Mrs. Annemarie Zielstra, the NICC programme manager, opened the event. She welcomed the over 100 representatives of key industry sectors. “Earlier studies in the
Im-Bolter, Nancie; Johnson, Janice; Ling, Daphne; Pascual-Leone, Juan
The current study tested 2 models of inhibition in 45 children with language impairment and 45 children with normally developing language; children were aged 7 to 12 years. Of interest was whether a model of inhibition as a mental-control process (i.e., executive function) or as a mental resource would more accurately reflect the relations among…
Luiijf, H.A.M.; Zielstra, A.
On December 1st, 2009, the fourth Dutch Process Control Security Event took place in Baarn, The Netherlands. The security event with the title ‘Manage IT!’ was organised by the Dutch National Infrastructure against Cybercrime (NICC). Mid of November, a group of over thirty people participated in the
Hopkins, B. L.
Incorporating statistical process control (SPC) methods into applied behavior analysis is discussed. It is claimed that SPC methods would likely reduce applied behavior analysts' intimate contacts with problems and would likely yield poor treatment and research decisions. Cases and data presented by Pfadt and Wheeler (1995) are cited as examples.…
This fact sheet briefly reviews the procedures that exist to control the process of food irradiation. It also summarizes the difficulties in identifying irradiated food, which stem from the fact that irradiation does not physically change the food or cause significant chemical changes in foods. 4 refs
Van Meeuwen, Ludo; Jarodzka, Halszka; Brand-Gruwel, Saskia; Van Merriënboer, Jeroen; De Bock, Jeano; Kirschner, Paul A.
Van Meeuwen, L. W., Jarodzka, H., Brand-Gruwel, S., Van Merriënboer, J. J. G., De Bock, J. J. P. R., & Kirschner, P. A. (2010, September). Processes mediating expertise in air traffic control. Poster presented at the European Association for Aviation Psychology Conference, Budapest.
Cantarero, Gabriela; Lloyd, Ashley; Celnik, Pablo
Plasticity of synaptic connections in the primary motor cortex (M1) is thought to play an essential role in learning and memory. Human and animal studies have shown that motor learning results in long-term potentiation (LTP)-like plasticity processes, namely potentiation of M1 and a temporary occlusion of additional LTP-like plasticity. Moreover, biochemical processes essential for LTP are also crucial for certain types of motor learning and memory. Thus, it has been speculated that the occlusion of LTP-like plasticity after learning, indicative of how much LTP was used to learn, is essential for retention. Here we provide supporting evidence of it in humans. Induction of LTP-like plasticity can be abolished using a depotentiation protocol (DePo) consisting of brief continuous theta burst stimulation. We used transcranial magnetic stimulation to assess whether application of DePo over M1 after motor learning affected (1) occlusion of LTP-like plasticity and (2) retention of motor skill learning. We found that the magnitude of motor memory retention is proportional to the magnitude of occlusion of LTP-like plasticity. Moreover, DePo stimulation over M1, but not over a control site, reversed the occlusion of LTP-like plasticity induced by motor learning and disrupted skill retention relative to control subjects. Altogether, these results provide evidence of a link between occlusion of LTP-like plasticity and retention and that this measure could be used as a biomarker to predict retention. Importantly, attempts to reverse the occlusion of LTP-like plasticity after motor learning comes with the cost of reducing retention of motor learning.
Groenendijk, Talita; Janssen, Tanja; Rijlaarsdam, Gert; van den Bergh, Huub
Previous research has shown that observation can be effective for learning in various domains, for example, argumentative writing and mathematics. The question in this paper is whether observational learning can also be beneficial when learning to perform creative tasks in visual and verbal arts. We hypothesized that observation has a positive effect on performance, process, and motivation. We expected similarity in competence between the model and the observer to influence the effectiveness of observation. Sample. A total of 131 Dutch students (10(th) grade, 15 years old) participated. Two experiments were carried out (one for visual and one for verbal arts). Participants were randomly assigned to one of three conditions; two observational learning conditions and a control condition (learning by practising). The observational learning conditions differed in instructional focus (on the weaker or the more competent model of a pair to be observed). We found positive effects of observation on creative products, creative processes, and motivation in the visual domain. In the verbal domain, observation seemed to affect the creative process, but not the other variables. The model similarity hypothesis was not confirmed. Results suggest that observation may foster learning in creative domains, especially in the visual arts. © 2011 The British Psychological Society.
Richardson, W; Majoras, R E [Oxford Instruments, Inc. P.O. Box 2560, Oak Ridge TN 37830 (United States); Joo, I O; Seymour, R S [Accu-Labs Research, Inc. 4663 Table Mountain Drive, Golden CO 80403 (United States)
Statistical process control(SPC) allows for the identification of problems in alpha spectroscopy processes before they occur, unlike standard laboratory Q C which only identifies problems after a process fails. SPC tools that are directly applicable to alpha spectroscopy include individual X-charts and X-bar charts, process capability plots, and scatter plots. Most scientists are familiar with the concepts the and methods employed by SPC. These tools allow analysis of process bias, precision, accuracy and reproducibility as well as process capability. Parameters affecting instrument performance are monitored and analyzed using SPC methods. These instrument parameters can also be compared to sampling, preparation, measurement, and analysis Q C parameters permitting the evaluation of cause effect relationships. Three examples of SPC, as applied to alpha spectroscopy , are presented. The first example investigates background contamination using averaging to show trends quickly. A second example demonstrates how SPC can identify sample processing problems, analyzing both how and why this problem occurred. A third example illustrates how SPC can predict when an alpha spectroscopy process is going to fail. This allows for an orderly and timely shutdown of the process to perform preventative maintenance, avoiding the need to repeat costly sample analyses. 7 figs., 2 tabs.
Richardson, W.; Majoras, R.E.; Joo, I.O.; Seymour, R.S.
Statistical process control(SPC) allows for the identification of problems in alpha spectroscopy processes before they occur, unlike standard laboratory Q C which only identifies problems after a process fails. SPC tools that are directly applicable to alpha spectroscopy include individual X-charts and X-bar charts, process capability plots, and scatter plots. Most scientists are familiar with the concepts the and methods employed by SPC. These tools allow analysis of process bias, precision, accuracy and reproducibility as well as process capability. Parameters affecting instrument performance are monitored and analyzed using SPC methods. These instrument parameters can also be compared to sampling, preparation, measurement, and analysis Q C parameters permitting the evaluation of cause effect relationships. Three examples of SPC, as applied to alpha spectroscopy , are presented. The first example investigates background contamination using averaging to show trends quickly. A second example demonstrates how SPC can identify sample processing problems, analyzing both how and why this problem occurred. A third example illustrates how SPC can predict when an alpha spectroscopy process is going to fail. This allows for an orderly and timely shutdown of the process to perform preventative maintenance, avoiding the need to repeat costly sample analyses. 7 figs., 2 tabs
Thiessen, Erik D
Statistical learning has been studied in a variety of different tasks, including word segmentation, object identification, category learning, artificial grammar learning and serial reaction time tasks (e.g. Saffran et al. 1996 Science 274: , 1926-1928; Orban et al. 2008 Proceedings of the National Academy of Sciences 105: , 2745-2750; Thiessen & Yee 2010 Child Development 81: , 1287-1303; Saffran 2002 Journal of Memory and Language 47: , 172-196; Misyak & Christiansen 2012 Language Learning 62: , 302-331). The difference among these tasks raises questions about whether they all depend on the same kinds of underlying processes and computations, or whether they are tapping into different underlying mechanisms. Prior theoretical approaches to statistical learning have often tried to explain or model learning in a single task. However, in many cases these approaches appear inadequate to explain performance in multiple tasks. For example, explaining word segmentation via the computation of sequential statistics (such as transitional probability) provides little insight into the nature of sensitivity to regularities among simultaneously presented features. In this article, we will present a formal computational approach that we believe is a good candidate to provide a unifying framework to explore and explain learning in a wide variety of statistical learning tasks. This framework suggests that statistical learning arises from a set of processes that are inherent in memory systems, including activation, interference, integration of information and forgetting (e.g. Perruchet & Vinter 1998 Journal of Memory and Language 39: , 246-263; Thiessen et al. 2013 Psychological Bulletin 139: , 792-814). From this perspective, statistical learning does not involve explicit computation of statistics, but rather the extraction of elements of the input into memory traces, and subsequent integration across those memory traces that emphasize consistent information (Thiessen and Pavlik
De Callatay, A.
A project of layered software architecture is proposed: a safety-critical real-time non-stop simple kernel system includes a layer avoiding threatening actions from operators or programs in other control systems. Complex process-control applications (such as fuzzy systems) are useful for the smooth operation of the system, optimum productivity, efficient diagnostics, and safe management of degraded modes of operation. Defects in these complex process-control applications do not have an impact on safety if their commands have first to be accepted by a safety-critical module. The development, testing, and certification of complex applications computed in the outside layers can be made simpler and less expensive than for those in the kernel. Avoidance systems use rule-base systems having negative fuzzy conditions and actions. Animal and human behaviour cannot be explained without active avoidance
Maria Dominika Niron
Full Text Available The aim of this study was to find out the effective kindergarten teacher’s behaviour in influencing, mobilizing, and developing students in teaching learning process. This research was phenomenological qualitative research. The main instruments of this research were the researcher and observation manual. The focus of this research was the way teachers teach in the learning process in group A of Indriyasana Kindergarten, Indriarini Kindergarten, and ABA Pokoh Kindergarten. The data validity of this research was tested by using repeated observation, resource triangulation, and technique triangulation. The componential data was analyzed by employing inductive technique from Spradley’s qualitative model and Miles and Huberman analysis model. The result of the research showed that teacher’s effective ways to influence, mobilize, and develop students in teaching learning process are as follows: 1. Reciting yell, clap yell, and asking students to sing. The content of yell, clap yell, and song was appropriate with values which were developed based on vision, mission, and the goal of Kindergarten institution. Yells, clap yell, and song were democratic and they were the form of the value of learning leadership. 2. In some situations, there was a tendency where the teacher used more autocratic way to influence, mobilize, and develop students in learning process such as the verbal way in which teacher call students’ name and non-verbal way in which teacher put his index finger on his lip as a sign to ask students to be quiet. The other non-verbal ways were: shaking head as a sign of disagreement, raising thumb as a sign of reinforcement, and nodding as a sign of agreement. Sometimes, teachers also used laissez-fair methods such as neglecting students/letting students behave as they want. Keywords: leadership, teacher’s leadership behaviour, learning process in Kindergarten
A minicomputer controlled test system for testing process control and monitoring systems is described. This system, in service for over one year, has demonstrated that computerized control of such testing has a real potential for expanding the scope of the testing, improving accuracy of testing, and significantly reducing the time required to do the testing. The test system is built around a 16-bit minicomputer with 12K of memory. The system programming language is BASIC with the addition of assembly level routines for communication with the peripheral devices. The peripheral devices include a 100 channel scanner, analog-to-digital converter, visual display, and strip printer. (auth)
Full Text Available A radical educational reform occurred in Turkey in 2005; and curriculum of primary education courses was renewed. New curriculum was prepared based on constructivist approach. In this scope, curriculum of Turkish course was also renewed. This study aimsat evaluating applications and opinions of teachers and students about learning and teaching process prescribed in Turkish Course (1st-5th Grades Curriculum. Within the scope of the study, semi-structured interview was made with 10 teachers and 12 students.In addition, process teaching a text was evaluated via structured observation method in 5 different classes. According to the results of the study, primary school teachers find some stages in learning – teaching process prescribed in the curriculum unnecessary andtherefore do not apply them. Teachers mentioned that some texts are above the student level; and they sometimes experience time and material problems. It was seen in the present study that teachers do not have enough information about learning and teachingprocess in the new curriculum; they do not have high success levels in the applications; and they usually do not apply the forms for evaluating the process in the curriculum. It was found out that, in spite of these problems, courses are student-centred as prescribed inthe curriculum; and students have positive opinions about stages of learning and teaching process.
Full Text Available Research-based Learning (RbL extends Inquiry and Project-based Learning by facilitating an early stage exposure and training for future scientists through authentic research activities. In this paper, an iterative problem-centric RbL process is introduced, and its activities and management aspects are described. The process helps implement course-integrated research systematically and practically. Furthermore, the novel process follows constructivist methods in incorporating inquiry, scaffolding, open-ended projects, as well as a goal oriented learning approach. The RbL process is adopted in two advanced computing courses, at two different universities: a leading comprehensive Western university and a new university in a developing country. The paper summarizes new lessons learned in these rewarding experiences. In particular, the instructor should help students start their projects, by providing them with previous work or data and pre-approving the papers to review by students. He should also maintain a continuous feedback to and from students to keep the students motivated and help the instructor refine and adapt the RBL process. We note that research collaborators can help students in identifying the research topics early. The paper also shows how to alleviate difficulties that may be encountered by students who find the novel approach demanding, and consequently it also helps the instructors better manage the course contents.
Full Text Available The main research objective of this paper is to point out potentials and limitations of the Internet in the process of learning in higher education, through review and analysis of literature. The results of this theoretical study emphasize positive aspects of the Internet use in the learning process of university students that arise from the Internet features such as high technical capabilities, power, speed, universality and accessibility, as well as high sensitivity of young people to the means of new media. The positive effects of the applica-tion of the Internet were pointed out in research studies that analysed the pro-cess of innovation in higher education, the changes in the culture of learning, or certain aspects of personality development of university students. In contrast, some studies pointed out the limitations that may occur when using the Internet in the learning process related primarily to the credibility of the infor-mation, light and entertaining content dominance, and dependence on technology. Accordingly, it is recommended to adopt the measures on a larger scale that will affect the greater use of the Internet in the process of acquiring knowledge, especially in the field of higher education.
Barthlow, Michelle J.; Watson, Scott B.
A nonequivalent, control group design was used to investigate student achievement in secondary chemistry. This study investigated the effect of process-oriented guided inquiry learning (POGIL) in high school chemistry to reduce alternate conceptions related to the particulate nature of matter versus traditional lecture pedagogy. Data were…
López-Tarjuelo, Juan; Luquero-Llopis, Naika; García-Mollá, Rafael; Quirós-Higueras, Juan David; Bouché-Babiloni, Ana; Juan-Senabre, Xavier Jordi; de Marco-Blancas, Noelia; Ferrer-Albiach, Carlos; Santos-Serra, Agustín
To assess the electron beam monitoring statistical process control (SPC) in linear accelerator (linac) daily quality control. We present a long-term record of our measurements and evaluate which SPC-led conditions are feasible for maintaining control. We retrieved our linac beam calibration, symmetry, and flatness daily records for all electron beam energies from January 2008 to December 2013, and retrospectively studied how SPC could have been applied and which of its features could be used in the future. A set of adjustment interventions designed to maintain these parameters under control was also simulated. All phase I data was under control. The dose plots were characterized by rising trends followed by steep drops caused by our attempts to re-center the linac beam calibration. Where flatness and symmetry trends were detected they were less-well defined. The process capability ratios ranged from 1.6 to 9.3 at a 2% specification level. Simulated interventions ranged from 2% to 34% of the total number of measurement sessions. We also noted that if prospective SPC had been applied it would have met quality control specifications. SPC can be used to assess the inherent variability of our electron beam monitoring system. It can also indicate whether a process is capable of maintaining electron parameters under control with respect to established specifications by using a daily checking device, but this is not practical unless a method to establish direct feedback from the device to the linac can be devised. Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.
Eguchi, Toru; Sekiai, Takaaki; Yamada, Akihiro; Shimizu, Satoru; Fukai, Masayuki
A control technology using Reinforcement Learning (RL) and Radial Basis Function (RBF) Network has been developed to reduce environmental load substances exhausted from power and industrial plants. This technology consists of the statistic model using RBF Network, which estimates characteristics of plants with respect to environmental load substances, and RL agent, which learns the control logic for the plants using the statistic model. In this technology, it is necessary to design an appropriate reward function given to the agent immediately according to operation conditions and control goals to control plants flexibly. Therefore, we propose an automatic reward adjusting method of RL for plant control. This method adjusts the reward function automatically using information of the statistic model obtained in its learning process. In the simulations, it is confirmed that the proposed method can adjust the reward function adaptively for several test functions, and executes robust control toward the thermal power plant considering the change of operation conditions and control goals.
Chen, Hung Yi; Huang, Shiuh Jer
The twin-roll strip casting process is a steel-strip production method which combines continuous casting and hot rolling processes. The production line from molten liquid steel to the final steel-strip is shortened and the production cost is reduced significantly as compared to conventional continuous casting. The quality of strip casting process depends on many process parameters, such as molten steel level in the pool, solidification position, and roll gap. Their relationships are complex and the strip casting process has the properties of nonlinear uncertainty and time-varying characteristics. It is difficult to establish an accurate process model for designing a model-based controller to monitor the strip quality. In this paper, a model-free adaptive neural network controller is developed to overcome this problem. The proposed control strategy is based on a neural network structure combined with a sliding-mode control scheme. An adaptive rule is employed to on-line adjust the weights of radial basis functions by using the reaching condition of a specified sliding surface. This surface has the on-line learning ability to respond to the system's nonlinear and time-varying behaviors. Since this model-free controller has a simple control structure and small number of control parameters, it is easy to implement. Simulation results, based on a semi experimental system dynamic model and parameters, are executed to show the control performance of the proposed intelligent controller. In addition, the control performance is compared with that of a traditional Pid controller
Several methods have been developed for measuring the extent to which implicitly learned knowledge can be applied in a strategic, flexible manner. Examples include generation exclusion tasks in Serial Reaction Time (SRT) learning (Goschke, 1998; Destrebecqz and Cleeremans, 2001) and 2-grammar classification tasks in Artificial Grammar Learning (AGL; Dienes et al., 1995; Norman et al., 2011). Strategic control has traditionally been used as a criterion for determining whether acquired knowledg...
Andersen, Torben Ole; Pedersen, Henrik Clemmensen; Hansen, Michael R.
In this paper the robustness of a class of learning control algorithms to state disturbances, output noise, and errors in initial conditions is studied. We present a simple learning algorithm and exhibit, via a concise proof, bounds on the asymptotic trajectory errors for the learned input...... and the corresponding state and output trajectories. Furthermore, these bounds are continuous functions of the bounds on the initial condition errors, state disturbance, and output noise, and the bounds are zero in the absence of these disturbances....
The German approach is based on the utilisation of the conceptual elements of the PRISCA information system developed by Siemens and on operational experience with screen-based process control in a conventional power plant. In the French approach, the screen-based control room for the N4 plants, designed from scratch, has undergone extensive simulator tests for validation before going into realisation. It is now used in the commissioning phase of the first N4 plants. The design of the control room for the European Pressurized Water Reactor will be based on the common experience of Siemens and Electricite de France. Its main elements are several separate operator workstations, a safety control area used as a back-up for postulated failures of the workstations, and a commonly utilisable plant overview for the operators' coordination. (orig./HP) [de
Mamdani, A.; Efstathiou, J. (eds.)
This report brings together recent developments both in expert systems and in optimisation, and deals with current applications in industry. Part One is concerned with Artificial Intellegence in planning and scheduling and with rule-based control implementation. The tasks of control maintenance, rescheduling and planning are each discussed in relation to new theoretical developments, techniques available, and sample applications. Part Two covers model based control techniques in which the control decisions are used in a computer model of the process. Fault diagnosis, maintenance and trouble-shooting are just some of the activities covered. Part Three contains case studies of projects currently in progress, giving details of the software available and the likely future trends. One of these, on qualitative plant modelling as a basis for knowledge-based operator aids in nuclear power stations is indexed separately.
Mamdani, A.; Efstathiou, J.
This report brings together recent developments both in expert systems and in optimisation, and deals with current applications in industry. Part One is concerned with Artificial Intellegence in planning and scheduling and with rule-based control implementation. The tasks of control maintenance, rescheduling and planning are each discussed in relation to new theoretical developments, techniques available, and sample applications. Part Two covers model based control techniques in which the control decisions are used in a computer model of the process. Fault diagnosis, maintenance and trouble-shooting are just some of the activities covered. Part Three contains case studies of projects currently in progress, giving details of the software available and the likely future trends. One of these, on qualitative plant modelling as a basis for knowledge-based operator aids in nuclear power stations is indexed separately. (author)
This document, part of a series offering guidance on pollution control regulations issued by Her Majesty's Inspectorate of Pollution, (HMIP) focuses on petroleum processes such as oil refining and other associated processes. The various industrial processes used, their associated pollution release routes into the environment and techniques for controlling these releases are all discussed. Environmental quality standards are related to national and international agreements on pollution control and abatement. HMIP's work on air, water and land pollution monitoring is also reported. (UK)
Chincoli, Michele; Liotta, Antonio
Current trends in interconnecting myriad smart objects to monetize on Internet of Things applications have led to high-density communications in wireless sensor networks. This aggravates the already over-congested unlicensed radio bands, calling for new mechanisms to improve spectrum management and energy efficiency, such as transmission power control. Existing protocols are based on simplistic heuristics that often approach interference problems (i.e., packet loss, delay and energy waste) by increasing power, leading to detrimental results. The scope of this work is to investigate how machine learning may be used to bring wireless nodes to the lowest possible transmission power level and, in turn, to respect the quality requirements of the overall network. Lowering transmission power has benefits in terms of both energy consumption and interference. We propose a protocol of transmission power control through a reinforcement learning process that we have set in a multi-agent system. The agents are independent learners using the same exploration strategy and reward structure, leading to an overall cooperative network. The simulation results show that the system converges to an equilibrium where each node transmits at the minimum power while respecting high packet reception ratio constraints. Consequently, the system benefits from low energy consumption and packet delay.
Koush, Yury; Meskaldji, Djalel-E; Pichon, Swann; Rey, Gwladys; Rieger, Sebastian W; Linden, David E J; Van De Ville, Dimitri; Vuilleumier, Patrik; Scharnowski, Frank
Most mental functions are associated with dynamic interactions within functional brain networks. Thus, training individuals to alter functional brain networks might provide novel and powerful means to improve cognitive performance and emotions. Using a novel connectivity-neurofeedback approach based on functional magnetic resonance imaging (fMRI), we show for the first time that participants can learn to change functional brain networks. Specifically, we taught participants control over a key component of the emotion regulation network, in that they learned to increase top-down connectivity from the dorsomedial prefrontal cortex, which is involved in cognitive control, onto the amygdala, which is involved in emotion processing. After training, participants successfully self-regulated the top-down connectivity between these brain areas even without neurofeedback, and this was associated with concomitant increases in subjective valence ratings of emotional stimuli of the participants. Connectivity-based neurofeedback goes beyond previous neurofeedback approaches, which were limited to training localized activity within a brain region. It allows to noninvasively and nonpharmacologically change interconnected functional brain networks directly, thereby resulting in specific behavioral changes. Our results demonstrate that connectivity-based neurofeedback training of emotion regulation networks enhances emotion regulation capabilities. This approach can potentially lead to powerful therapeutic emotion regulation protocols for neuropsychiatric disorders. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: firstname.lastname@example.org.
Kiumarsi, Bahare; Vamvoudakis, Kyriakos G; Modares, Hamidreza; Lewis, Frank L
This paper reviews the current state of the art on reinforcement learning (RL)-based feedback control solutions to optimal regulation and tracking of single and multiagent systems. Existing RL solutions to both optimal and control problems, as well as graphical games, will be reviewed. RL methods learn the solution to optimal control and game problems online and using measured data along the system trajectories. We discuss Q-learning and the integral RL algorithm as core algorithms for discrete-time (DT) and continuous-time (CT) systems, respectively. Moreover, we discuss a new direction of off-policy RL for both CT and DT systems. Finally, we review several applications.
Montgomery, R. C.; Mekel, R.; Nachmias, S.
This report contains a complete description of a learning control system designed for the F8-DFBW aircraft. The system is parameter-adaptive with the additional feature that it 'learns' the variation of the control system gains needed over the flight envelope. It, thus, generates and modifies its gain schedule when suitable data are available. The report emphasizes the novel learning features of the system: the forms of representation of the flight envelope and the process by which identified parameters are used to modify the gain schedule. It contains data taken during piloted real-time 6 degree-of-freedom simulations that were used to develop and evaluate the system.
Mahmoudi, Babak; Pohlmeyer, Eric A; Prins, Noeline W; Geng, Shijia; Sanchez, Justin C
Our goal was to design an adaptive neuroprosthetic controller that could learn the mapping from neural states to prosthetic actions and automatically adjust adaptation using only a binary evaluative feedback as a measure of desirability/undesirability of performance. Hebbian reinforcement learning (HRL) in a connectionist network was used for the design of the adaptive controller. The method combines the efficiency of supervised learning with the generality of reinforcement learning. The convergence properties of this approach were studied using both closed-loop control simulations and open-loop simulations that used primate neural data from robot-assisted reaching tasks. The HRL controller was able to perform classification and regression tasks using its episodic and sequential learning modes, respectively. In our experiments, the HRL controller quickly achieved convergence to an effective control policy, followed by robust performance. The controller also automatically stopped adapting the parameters after converging to a satisfactory control policy. Additionally, when the input neural vector was reorganized, the controller resumed adaptation to maintain performance. By estimating an evaluative feedback directly from the user, the HRL control algorithm may provide an efficient method for autonomous adaptation of neuroprosthetic systems. This method may enable the user to teach the controller the desired behavior using only a simple feedback signal.
In the Los Alamos National Laboratory (LANL) hydrothermal process, waste streams are first pressurized and heated as they pass through a continuous flow tubular reactor vessel. The waste is maintained at reaction temperature of 300--550 C where organic destruction and sludge reformation occur. This report documents LANL activities in process modeling and control undertaken in FY94 to support hydrothermal process development. Key issues discussed include non-ideal flow patterns (e.g. axial dispersion) and their effect on reactor performance, the use and interpretation of inert tracer experiments, and the use of computational fluid mechanics to evaluate novel hydrothermal reactor designs. In addition, the effects of axial dispersion (and simplifications to rate expressions) on the estimated kinetic parameters are explored by non-linear regression to experimental data. Safety-related calculations are reported which estimate the explosion limits of effluent gases and the fate of hydrogen as it passes through the reactor. Development and numerical solution of a generalized one-dimensional mathematical model is also summarized. The difficulties encountered in using commercially available software to correlate the behavior of high temperature, high pressure aqueous electrolyte mixtures are summarized. Finally, details of the control system and experiments conducted to empirically determine the system response are reported
Most nuclear plants in North America were designed and built in the late 60 and 70. The regulatory nature of this industry over the years has made design changes at the plant level difficult, if not impossible, to implement. As a result, many plants in this world region have been getting by on technology that is over 40 years behind the times. What this translates into is that the plants have not been able to take advantage of the huge technology gains that have been made in process control during this period. As a result, most of these plants are much less efficient and productive than they could be. One particular area of the plant that is receiving a lot of attention is the feedwater heaters. These systems were put in place to improve efficiency, but most are not operating correctly. This paper will present a case study where one progressive mid-western utility decided that enough was enough and implemented a process control audit of their heater systems. The audit clearly pointed out the existing problems with the current process control system. It resulted in a proposal for the implementation of a state of the art, digital distributed process control system for the heaters along with a complete upgrade of the level controls and field devices that will stabilize heater levels, resulting in significant efficiency gains and lower maintenance bills. Overall the payback period for this investment should be less than 6 months and the plant is now looking for more opportunities that can provide even bigger gains. (author)
Romansky, Radi; Noninska, Irina
The article discuses an approach to investigate processes for regulation the security and privacy control at a heterogenous e-learning environment realized as a combination of traditional and cloud means and tools. Authors' proposal for combined architecture of e-learning system is presented and main subsystems and procedures are discussed. A formalization of the processes for using different types resources (public, private internal and private external) is proposed. The apparatus of Markovian chains (MC) is used for modeling and analytical investigation of the secure access to the resources is used and some assessments are presented.
Oprins, E.A.P.B.; Bruggraaff, E.; Roe, R.
This chapter describes a competence-based assessment system, called CBAS, for air traffic control (ATC) simulator and on-the-job training (OJT), developed at Air Traffic Control The Netherlands (LVNL). In contrast with simulator training, learning processes in OJT are difficult to assess, because
Bauch, Garland T.
Most failures occur at interfaces between organizations and hardware. Processing interface requirements at the start of a project life cycle will reduce the likelihood of costly interface changes/failures later. This can be done by adding Interface Control Documents (ICDs) to the Project top level drawing tree, providing technical direction to the Projects for interface requirements, and by funding the interface requirements function directly from the Project Manager's office. The interface requirements function within the Project Systems Engineering and Integration (SE&I) Office would work in-line with the project element design engineers early in the life cycle to enhance communications and negotiate technical issues between the elements. This function would work as the technical arm of the Project Manager to help ensure that the Project cost, schedule, and risk objectives can be met during the Life Cycle. Some ICD Lessons Learned during the Space Shuttle Program (SSP) Life Cycle will include the use of hardware interface photos in the ICD, progressive life cycle design certification by analysis, test, & operations experience, assigning interface design engineers to Element Interface (EI) and Project technical panels, and linking interface design drawings with project build drawings
Kofoed, Lise Busk; Rosenørn, Torben; Jensen, Lars Peter
The initiating question guiding this study is how employee participation can be established during an organizational change process in order to improve the employees' involvement in the design of their future work environment. A case study in which an "experimentarium" (learning lab) was conducted...
Wagner, Holly H.; Hill, Nicole R.
This article explored counselor development within the entry transition into counselor education programs using 4 interviews and interpretive dialogues with 8 beginning counselors. Six categories resulted from the authors' grounded theory analysis: Anticipation, Evolving Identity, Growth and Learning, Coping, Choosing to Trust the Process, and…
Biggs, John B.
This manual describes the theory behind the Study Process Questionnaire (SPQ) and explains what the subscale and scale scores mean. The SPQ is a 42-item self-report questionnaire used in Australia to assess the extent to which a tertiary student at a college or university endorses different approaches to learning and the motives and strategies…
Bailey, Frank S.; Yocum, Russell G.
The purpose of this personal experience as a narrative investigation is to describe how an auditory processing learning disability exacerbated--and how spirituality and religiosity relieved--suicidal ideation, through the lived experiences of an individual born and raised in the United States. The study addresses: (a) how an auditory processing…
Examines the claim that it is necessary to change an organization's culture in order to bring about organizational change. Considers the purported causal relationship between the role of the leader and organizational learning and develops the notion of culture as cognitive process based on research in cultural anthropology and cognitive science.…
Sorensen, Birgitte Holm
Describes a development project for the use of computer graphics and video in connection with an inservice training course for primary education teachers in Denmark. Topics addressed include research approaches to computers; computer graphics in learning processes; activities relating to computer graphics; the role of the teacher; and student…
The studies reported herein are intended to provide more certainty regarding estimates of the costs of controlling environmental residuals from oil shale technologies being readied for commercial application. The need for this study was evident from earlier work conducted by the Office of Environment for the Department of Energy Oil Shale Commercialization Planning, Environmental Readiness Assessment in mid-1978. At that time there was little reliable information on the costs for controlling residuals and for safe handling of wastes from oil shale processes. The uncertainties in estimating costs of complying with yet-to-be-defined environmental standards and regulations for oil shale facilities are a critical element that will affect the decision on proceeding with shale oil production. Until the regulatory requirements are fully clarified and processes and controls are investigated and tested in units of larger size, it will not be possible to provide definitive answers to the cost question. Thus, the objective of this work was to establish ranges of possible control costs per barrel of shale oil produced, reflecting various regulatory, technical, and financing assumptions. Two separate reports make up the bulk of this document. One report, prepared by the Denver Research Institute, is a relatively rigorous engineering treatment of the subject, based on regulatory assumptions and technical judgements as to best available control technologies and practices. The other report examines the incremental cost effect of more conservative technical and financing alternatives. An overview section is included that synthesizes the products of the separate studies and addresses two variations to the assumptions.
Isnur Haryudo, Subuh; Imam Agung, Achmad; Firmansyah, Rifqi
The purpose of this research is to develop learning media of control technique using Matrix Laboratory software with industry requirement approach. Learning media serves as a tool for creating a better and effective teaching and learning situation because it can accelerate the learning process in order to enhance the quality of learning. Control Techniques using Matrix Laboratory software can enlarge the interest and attention of students, with real experience and can grow independent attitude. This research design refers to the use of research and development (R & D) methods that have been modified by multi-disciplinary team-based researchers. This research used Computer based learning method consisting of computer and Matrix Laboratory software which was integrated with props. Matrix Laboratory has the ability to visualize the theory and analysis of the Control System which is an integration of computing, visualization and programming which is easy to use. The result of this instructional media development is to use mathematical equations using Matrix Laboratory software on control system application with DC motor plant and PID (Proportional-Integral-Derivative). Considering that manufacturing in the field of Distributed Control systems (DCSs), Programmable Controllers (PLCs), and Microcontrollers (MCUs) use PID systems in production processes are widely used in industry.
Jared A. Linck
Full Text Available The role of executive functioning in second language (L2 aptitude remains unclear. Whereas some studies report a relationship between working memory (WM and L2 learning, others have argued against this association. Similarly, being bilingual appears to benefit inhibitory control, and individual differences in inhibitory control are related to online L2 processing. The current longitudinal study examines whether these two components of executive functioning predict learning gains in an L2 classroom context using a pretest/posttest design. We assessed 25 university students in language courses, who completed measures of WM and inhibitory control. They also completed a proficiency measure at the beginning and end of a semester and reported their grade point average (GPA. WM was positively related to L2 proficiency and learning, but inhibitory control was not. These results support the notion that WM is an important component of L2 aptitude, particularly for predicting the early stages of L2 classroom learning.
Full Text Available Methods of statistical evaluation of quality SPC (item 20 of the documentation system of quality control of ISO norm, series 900 of various processes, products and services belong amongst basic qualitative methods that enable us to analyse and compare data pertaining to various quantitative parameters. Also they enable, based on the latter, to propose suitable interventions with the aim of improving these processes, products and services. Theoretical basis and applicatibily of the principles of the: - diagnostics of a cause and effects, - Paret analysis and Lorentz curve, - number distribution and frequency curves of random variable distribution, - Shewhart regulation charts, are presented in the contribution.
Pawlicki, Todd; Whitaker, Matthew; Boyer, Arthur L.
Every quality assurance process uncovers random and systematic errors. These errors typically consist of many small random errors and a very few number of large errors that dominate the result. Quality assurance practices in radiotherapy do not adequately differentiate between these two sources of error. The ability to separate these types of errors would allow the dominant source(s) of error to be efficiently detected and addressed. In this work, statistical process control is applied to quality assurance in radiotherapy for the purpose of setting action thresholds that differentiate between random and systematic errors. The theoretical development and implementation of process behavior charts are described. We report on a pilot project is which these techniques are applied to daily output and flatness/symmetry quality assurance for a 10 MV photon beam in our department. This clinical case was followed over 52 days. As part of our investigation, we found that action thresholds set using process behavior charts were able to identify systematic changes in our daily quality assurance process. This is in contrast to action thresholds set using the standard deviation, which did not identify the same systematic changes in the process. The process behavior thresholds calculated from a subset of the data detected a 2% change in the process whereas with a standard deviation calculation, no change was detected. Medical physicists must make decisions on quality assurance data as it is acquired. Process behavior charts help decide when to take action and when to acquire more data before making a change in the process
The aim of the research was to determine the relationships which exist between academic success, learning strategies and locus of control. In order to achieve this aim a small-scale quantitative study, utilising two inventories, was done. The first measuring instrument is the Learning and Study Strategies Inventory, which is ...
Purser, Harry R. M.; Farran, Emily K.; Courbois, Yannick; Lemahieu, Axelle; Mellier, Daniel; Sockeel, Pascal; Blades, Mark
The aim of this study was to investigate route-learning ability in 67 children aged 5 to 11 years and to relate route-learning performance to the components of Baddeley's model of working memory. Children carried out tasks that included measures of verbal and visuospatial short-term memory and executive control and also measures of verbal and…
Peterson, Christopher; And Others
Experiences with uncontrollable events may lead to the expectation that future events will elude control, resulting in disruptions in motivation, emotion, and learning. This text explores this phenomenon, termed learned helplessness, tracking it from its discovery to its entrenchment in the psychological canon. The volume summarizes and integrates…
Van Meeuwen, Ludo; Brand-Gruwel, Saskia; Van Merriënboer, Jeroen; De Bock, Jeano; Kirschner, Paul A.
Van Meeuwen, L. W., Brand-Gruwel, S., Van Merriënboer, J. J. G., De Bock, J. J. P. R., & Kirschner, P. A. (2010, August). Indicators for successful learning in air traffic control training. Paper presented at the 5th EARLI SIG 14 Learning and Professional Development Conference. Munich, Germany.
Hinojosa, J.; Nefti, S.; Kaymak, U.
Reinforcement learning (RL) is a valuable learning method when the systems require a selection of control actions whose consequences emerge over long periods for which input-output data are not available. In most combinations of fuzzy systems and RL, the environment is considered to be
Derex, Maxime; Feron, Romain; Godelle, Bernard; Raymond, Michel
Human cultural traits typically result from a gradual process that has been described as analogous to biological evolution. This observation has led pioneering scholars to draw inspiration from population genetics to develop a rigorous and successful theoretical framework of cultural evolution. Social learning, the mechanism allowing information to be transmitted between individuals, has thus been described as a simple replication mechanism. Although useful, the extent to which this idealization appropriately describes the actual social learning events has not been carefully assessed. Here, we used a specifically developed computer task to evaluate (i) the extent to which social learning leads to the replication of an observed behaviour and (ii) the consequences it has for fitness landscape exploration. Our results show that social learning does not lead to a dichotomous choice between disregarding and replicating social information. Rather, it appeared that individuals combine and transform information coming from multiple sources to produce new solutions. As a consequence, landscape exploration was promoted by the use of social information. These results invite us to rethink the way social learning is commonly modelled and could question the validity of predictions coming from models considering this process as replicative. © 2015 The Author(s) Published by the Royal Society. All rights reserved.
The aim of the research is to explore the possibilities and methodological solutions of using kinaesthetic teaching style in the teaching/learning process in basic school and its impact on pupil involvement in learning activities and attainment of goals. Qualitative and quantitative methods - experienced teacher’s survey and student-trainee survey after observation and analysys of lessons at school are used during the study. It is concluded that: 1)the kinesthetic style of learning involve...
Marcus Vinícius Lara
Full Text Available The use of Information and Communication Technologies (ICTs in the academic environment of biomedical area has gained much importance, both for their ability to complement the understanding of the subject obtained in the classroom, is the ease of access, or makes more pleasure the learning process, since these tools are present in everyday of the students and use a simple language. Considering that, this study aims to report the experience of building learning objects in human physiology as a tool for learning facilitation, and discuss the impact of this teaching methodology
Mansouri, Seyed Soheil; Sales-Cruz, Mauricio; Huusom, Jakob Kjøbsted
on the element concept, which is used to translate a system of compounds into elements. The operation of the reactive distillation column at the highest driving force and other candidate points is analyzed through analytical solution as well as rigorous open-loop and closed-loop simulations. By application...... of this approach, it is shown that designing the reactive distillation process at the maximum driving force results in an optimal design in terms of controllability and operability. It is verified that the reactive distillation design option is less sensitive to the disturbances in the feed at the highest driving...
Teicher, Uwe; Achour, Anas Ben; Nestler, Andreas; Brosius, Alexander; Lauer, Günter
The machining operation drilling is part of the standard repertoire for medical applications. This machining cycle, which is usually a multi-stage process, generates the geometric element for the subsequent integration of implants, which are screwed into the bone in subsequent processes. In addition to the form, shape and position of the generated drill hole, it is also necessary to use a technology that ensures an operation with minimal damage. A surface damaged by excessive mechanical and thermal energy input shows a deterioration in the healing capacity of implants and represents a structure with complications for inflammatory reactions. The resulting loads are influenced by the material properties of the bone, the used technology and the tool properties. An important aspect of the process analysis is the fact that machining of bone is in most of the cases a manual process that depends mainly on the skills of the operator. This includes, among other things, the machining time for the production of a drill hole, since manual drilling is a force-controlled process. Experimental work was carried out on the bone of a porcine mandible in order to investigate the interrelation of the applied load during drilling. It can be shown that the load application can be subdivided according to the working feed direction. The entire drilling process thus consists of several time domains, which can be divided into the geometry-generating feed motion and a retraction movement of the tool. It has been shown that the removal of the tool from the drill hole has a significant influence on the mechanical load input. This fact is proven in detail by a new evaluation methodology. The causes of this characteristic can also be identified, as well as possible ways of reducing the load input.
Amer, T. S.; Mohrweis, Lawrence C.
This study describes the multifaceted components of an assessment process. The paper explains a novel approach in which an advisory council participated in a "fun," hands-on activity to rank-order learning outcomes. The top ranked learning competency, as identified by the advisory council, was the need for students to gain a better…
The characteristic features of expert systems are explained in detail, and the systems' application in process control engineering. Four points of main interest are there, namely: Applications for diagnostic tasks, for safety analyses, planning, and training and expert training. For the modelling of the technical systems involved in all four task fields mentioned above, an object-centred approach has shown to be the suitable method, as process control techniques are determined by technical objects that in principle are specified by data sheets, schematic representations, flow charts, and plans. The graphical surface allows these data to be taken into account, so that the object can be displayed in the way best suited to the individual purposes. (orig./GL) [de
Radiation sources have been used in process control for over 40 years. Their use in inspection, implying visual examination, although of much earlier origin in the form of gamma radiography, is also of recent emergence in the form of tomographic methods. This paper firstly reviews the justification for the continued world-wide usage of isotopic methods. It then reviews a selection of innovative process control applications, based on radiation sources, as illustrations of the present state of the art and also describes recent progress in inspection methods including progress in the development of on-line facilities. For all applications involving radiation sources, careful selection of parameters is required to achieve the highest efficiency compatible with an integrity suitable for the intended application. The paper concludes with a brief discussion of the common principles on which the fabrication of sources is based in order to satisfy national and international safety legislation. (author)
Schaap, H.; Baartman, L.K.J.; Bruijn, de E.
Learning in vocational schools and workplaces are the two main components of vocational education. Students have to develop professional competences by building meaningful relations between knowledge, skills and attitudes. There are, however, some major concerns about the combination of learning in
The Learning Technologies in the Workplace Awards were launched by the Conference Board of Canada in April 2001 with funding from Human Resources Development Canada's Office of Learning Technologies. This paper described the innovative and outstanding efforts made by the winner, North Atlantic. The North Atlantic refinery is located on an inlet on the Avalon Peninsula approximately 135 kilometres west of St. John's, Newfoundland. Each day, 105,000 barrels of oil are processed for export to 25 countries. In 1998, the company recognized that better training was required in the areas of improved safety, performance, and employee innovation and capacity. The isolation faced by the employees was a key driver behind the decision to implement the TRAQS training program in 1999 for e-learning developed by Illuminatus. This on-line training program also features testing through CHALLENGE, a software package compatible with TRAQS learning management system. Process emergency simulation exercises were developed by North Atlantic which are now being used externally. Job-specific technical information is delivered through the local area network (LAN). The keys to success were identified as being: innovative organizational culture; vision and action; executive management support, commitment to learning and employee development; positive work life balance; union cooperation; technology intensive workplace; linking learning with work process and performance management; and, tracking and certification.
van Nort, Douglas
This dissertation presents research into the creation of systems for the control of sound synthesis and processing. The focus differs from much of the work related to digital musical instrument design, which has rightly concentrated on the physicality of the instrument and interface: sensor design, choice of controller, feedback to performer and so on. Often times a particular choice of sound processing is made, and the resultant parameters from the physical interface are conditioned and mapped to the available sound parameters in an exploratory fashion. The main goal of the work presented here is to demonstrate the importance of the space that lies between physical interface design and the choice of sound manipulation algorithm, and to present a new framework for instrument design that strongly considers this essential part of the design process. In particular, this research takes the viewpoint that instrument designs should be considered in a musical control context, and that both control and sound dynamics must be considered in tandem. In order to achieve this holistic approach, the work presented in this dissertation assumes complementary points of view. Instrument design is first seen as a function of musical context, focusing on electroacoustic music and leading to a view on gesture that relates perceived musical intent to the dynamics of an instrumental system. The important design concept of mapping is then discussed from a theoretical and conceptual point of view, relating perceptual, systems and mathematically-oriented ways of examining the subject. This theoretical framework gives rise to a mapping design space, functional analysis of pertinent existing literature, implementations of mapping tools, instrumental control designs and several perceptual studies that explore the influence of mapping structure. Each of these reflect a high-level approach in which control structures are imposed on top of a high-dimensional space of control and sound synthesis
Savi, M.B.M.B.; Camozzato, T.S.C.; Soares, F.A.P.; Nandi, D.M.
The Repeat Analysis Index (IRR) is one of the items contained in the Quality Control Program dictated by brazilian law of radiological protection and should be performed frequently, at least every six months. In order to extract more and better information of IRR, this study presents the Statistical Quality Control applied to reject rate through Statistical Process Control (Control Chart for Attributes ρ - GC) and the Pareto Chart (GP). Data collection was performed for 9 months and the last four months of collection was given on a daily basis. The Limits of Control (LC) were established and Minitab 16 software used to create the charts. IRR obtained for the period was corresponding to 8.8% ± 2,3% and the generated charts analyzed. Relevant information such as orders for X-ray equipment and processors were crossed to identify the relationship between the points that exceeded the control limits and the state of equipment at the time. The GC demonstrated ability to predict equipment failures, as well as the GP showed clearly what causes are recurrent in IRR. (authors) [pt
Full Text Available This paper presents the results of a study that examines the impact on end-of-year examination grades of the level of student engagement in the e-learning process. The study relates to a level one undergraduate module delivered using a mixture of traditional lectures and e-learning based methods. Greater online interaction is found to have a positive and statistically significant impact on performance. One extra hour of e-learning participation is found to increase the module mark by approximately one percent. The paper also examines the data for the presence of interaction effects between e-learning engagement and personal characteristics. This is undertaken to identify whether or not personal-characteristic-related learning style differences influence the extent to which students benefit from e-learning. It is found that, after controlling for other factors, female students benefited less from e-leaning material than their male counterparts. Tentative evidence is also found of a negative interaction effect in relation to overseas students. It is concluded that in order to improve teaching effectiveness and academic achievement, higher education should consider aiming to develop e-learning teaching strategies that encourage greater engagement and also take into consideration the different learning styles found within the student body.
The transfer of technologies by the foreign electronic industries operating in Malaysia involves training of workers for various purposes. The upgrading of skills to assimilate the transferred technology aims at increasing productivity and product quality. Communicating awareness about work hazards...... is meant to reduce breakdowns in production and workers' accidents. How do the training paradigms, which transnationals introduce in their subsidiaries in Malaysia, interact with the preconditions of learning with the local labour force? In shaping local learning processes, what is the scope for workers...
Ding, L.; Gustafsson, T.
A general description of a flotation process is given. The dynamic model of a MIMO nonlinear subprocess in flotation, i. e. the pulp levels in five compartments in series is developed and the model is verified with real data from a production plant. In order to reject constant disturbances five extra states are introduced and the model is modified. An exact linearization has been made for the non-linear model and a linear quadratic gaussian controller is proposed based on the linearized model. The simulation result shows an improved performance of the pulp level control when the set points are changed or a disturbance occur. In future the controller will be tested in production. (author)
Full Text Available Presents control methods, differentiated by the time of receipt of information used: a priori, a posteriori and current. When used a priori information to determine the mode of cutting is carried out by simulation the process of cutting allowance, where the shape of the workpiece and the details are presented in the form of wireframes. The office for current information provides for a system of adaptive control and modernization of CNC machine, where in the input of the unit shall be computed by using established optimization software. For the control by a posteriori information of the proposed method of correction of shape-generating trajectory in the second pass measurement surface of the workpiece formed by the first pass. Developed programs that automatically design the adjusted file for machining.
A brazing operation involves joining two parts made of different materials, using a filler material that has a melting temperature lower than the base materials used. The temperature of the process must be carefully controlled, sometimes with an accuracy of about 1°C, because overshooting the prescribed temperature results in detrimental metallurgic phenomena and joints of poor quality. The brazing system is composed of an operating cabinet, a mid-frequency generator, a vacuum chamber with an induction coil inside and the parts that have to be brazed. Until now, to operate this system two operators were required: one to continuously read the temperature with an optical pyrometer and another to manually adjust the current in the induction coil according to his intuition and prediction gained only by experience. The improvement that we made to the system involved creating an automatic temperature control unit, using a PID closed loop controller that reads the temperature of the parts and adjusts automatically the current in the coil. Using the PID controller, the brazing engineer can implement a certain temperature slope for the current brazing process. (authors)
Lewis, F L; Vamvoudakis, Kyriakos G
Approximate dynamic programming (ADP) is a class of reinforcement learning methods that have shown their importance in a variety of applications, including feedback control of dynamical systems. ADP generally requires full information about the system internal states, which is usually not available in practical situations. In this paper, we show how to implement ADP methods using only measured input/output data from the system. Linear dynamical systems with deterministic behavior are considered herein, which are systems of great interest in the control system community. In control system theory, these types of methods are referred to as output feedback (OPFB). The stochastic equivalent of the systems dealt with in this paper is a class of partially observable Markov decision processes. We develop both policy iteration and value iteration algorithms that converge to an optimal controller that requires only OPFB. It is shown that, similar to Q -learning, the new methods have the important advantage that knowledge of the system dynamics is not needed for the implementation of these learning algorithms or for the OPFB control. Only the order of the system, as well as an upper bound on its "observability index," must be known. The learned OPFB controller is in the form of a polynomial autoregressive moving-average controller that has equivalent performance with the optimal state variable feedback gain.
Learning processes in global education have not been significantly theorized, with the notable exception of the application of transformative learning theory. No theory of learning is complete, and to understand the complexity of learning, multiple theoretical lenses must be applied. This article looks at Jarvis's (2006) model of lifelong learning…
Brunstrom, Jeffrey M
Most of our food likes and disliked are learned. Relevant forms of associative learning have been identified in animals. However, observations of the same associative processes are relatively scarce in humans. The first section of this paper outlines reasons why this might be the case. Emphasis is placed on recent research exploring individual differences and the importance or otherwise of hunger and contingency awareness. The second section briefly considers the effect of learning on meal size, and the author revisits the question of how learned associations might come to influence energy intake in humans.
Gocke, P.; Debatin, J.F.; Duerselen, L.F.J.
Systematic process management and efficient quality control is rapidly gaining importance in our healthcare system. What does this mean for diagnostic radiology departments?To improve efficiency, quality and productivity the workflow within the department of diagnostic and interventional radiology at the University Hospital of Essen were restructured over the last two years. Furthermore, a controlling system was established. One of the pursued aims was to create a quality management system as a basis for the subsequent certification according to the ISO EN 9001:2000 norm.Central to the success of the workflow reorganisation was the training of selected members of the department's staff in process and quality management theory. Thereafter, a dedicated working group was created to prepare the reorganisation and the subsequent ISO certification with the support of a consulting partner. To assure a smooth implementation of the restructured workflow and create acceptance for the required ISO-9001 documentation, the entire staff was familiarized with the basic ideas of process- and quality-management in several training sessions.This manuscript summarizes the basic concepts of process and quality management as they were taught to our staff. A direct relationship towards diagnostic radiology is maintained throughout the text. (orig.) [de
Bakker, B.; Whiteson, S.; Kester, L.; Groen, F.C.A.; Babuška, R.; Groen, F.C.A.
Traffic light control is one of the main means of controlling road traffic. Improving traffic control is important because it can lead to higher traffic throughput and reduced traffic congestion. This chapter describes multiagent reinforcement learning techniques for automatic optimization of
Bakker, B.; Whiteson, S.; Kester, L.J.H.M.; Groen, F.C.A.
Traffic light control is one of the main means of controlling road traffic. Improving traffic control is important because it can lead to higher traffic throughput and reduced traffic congestion. This chapter describes multiagent reinforcement learning techniques for automatic optimization of
Seke, F. R.; Sumilat, J. M.; Kembuan, D. R. E.; Kewas, J. C.; Muchtar, H.; Ibrahim, N.
Project-based learning is a learning method that uses project activities as the core of learning and requires student creativity in completing the project. The aims of this study is to investigate the influence of project-based learning methods on students with a high level of creativity in learning the Programmable Logic Controller (PLC). This study used experimental methods with experimental class and control class consisting of 24 students, with 12 students of high creativity and 12 students of low creativity. The application of project-based learning methods into the PLC courses combined with the level of student creativity enables the students to be directly involved in the work of the PLC project which gives them experience in utilizing PLCs for the benefit of the industry. Therefore, it’s concluded that project-based learning method is one of the superior learning methods to apply on highly creative students to PLC courses. This method can be used as an effort to improve student learning outcomes and student creativity as well as to educate prospective teachers to become reliable educators in theory and practice which will be tasked to create qualified human resources candidates in order to meet future industry needs.
Full Text Available Today, not only diverse design-related disciplines are required to actively deal with the digitization of information and its potentials and side effects for education processes. In Germany, technology didactics developed in vocational education and computer science education in general education, both separated from media pedagogy as an after-school program. Media education is not a subject in German schools yet. However, in the paper we argue for an interdisciplinary approach to learn about computational modeling in creative processes and aesthetic contexts. It crosses the borders of programming technology, arts and design processes in meaningful contexts. Educational scenarios using smart textile environments are introduced and reflected for project based learning.
Cardoza, David; Langhojer, Florian; Trallero-Herrero, Carlos; Weinacht, Thomas; Monti, Oliver L.A.
We interpret the results of a molecular fragmentation learning control experiment. We show that in the case of a system where control can be related to the structure of the optimal pulse matching the vibrational dynamics of the molecule, a simple change of pulse-shape basis in which the learning algorithm performs the search can reduce the dimensionality of the search space to one or two degrees of freedom
Schmidt, James R; Crump, Matthew J C; Cheesman, Jim; Besner, Derek
The results of four experiments provide evidence for controlled processing in the absence of awareness. Participants identified the colour of a neutral distracter word. Each of four words (e.g., MOVE) was presented in one of the four colours 75% of the time (Experiments 1 and 4) or 50% of the time (Experiments 2 and 3). Colour identification was faster when the words appeared in the colour they were most often presented in relative to when they appeared in another colour, even for participants who were subjectively unaware of any contingencies between the words and the colours. An analysis of sequence effects showed that participants who were unaware of the relation between distracter words and colours nonetheless controlled the impact of the word on performance depending on the nature of the previous trial. A block analysis of contingency-unaware participants revealed that contingencies were learned rapidly in the first block of trials. Experiment 3 showed that the contingency effect does not depend on the level of awareness, thus ruling out explicit strategy accounts. Finally, Experiment 4 showed that the contingency effect results from behavioural control and not from semantic association or stimulus familiarity. These results thus provide evidence for implicit control.
Sandoval Hamón Leyla Angélica
Full Text Available The European Higher Education Area promotes the change in teaching-learning, where students have a more active role in their educational process. The main objective of this work is to analyse the use of an alternative proposal, focus in student-based teamwork activities, who seek to favour the acquisition and deepening of knowledge and skills. The implementation of this research was carried out by means of a longitudinal study in the subject of the degree of Economics, with the development of the methodology of Project Based Learning integrating the ICTs and improving the evaluation process (e.g. establishing headings and psychometric analysis of knowledge tests. The results of the research showed an improvement in the learning process from the observation, collection of works, analysis of knowledge tests and the official survey by students to assess the activity and the development of their competitors.
Rahardini, Riris Riezqia Budy; Suryadarma, I. Gusti Putu; Wilujeng, Insih
This research was aimed to know the effectiveness of science learning that integrated with local potential to improve student`s science process skill. The research was quasi experiment using non-equivalent control group design. The research involved all student of Muhammadiyah Imogiri Junior High School on grade VII as a population. The sample in this research was selected through cluster random sampling, namely VII B (experiment group) and VII C (control group). Instrument that used in this research is a nontest instrument (science process skill observation's form) adapted Desak Megawati's research (2016). The aspect of science process skills were making observation and communication. The data were using univariat (ANOVA) analyzed at 0,05 significance level and normalized gain score for science process skill increase's category. The result is science learning that integrated with local potential was effective to improve science process skills of student (Sig. 0,00). This learning can increase science process skill, shown by a normalized gain score value at 0,63 (medium category) in experiment group and 0,29 (low category) in control group.
Green, C S; Bavelier, D
While humans have an incredible capacity to acquire new skills and alter their behavior as a result of experience, enhancements in performance are typically narrowly restricted to the parameters of the training environment, with little evidence of generalization to different, even seemingly highly related, tasks. Such specificity is a major obstacle for the development of many real-world training or rehabilitation paradigms, which necessarily seek to promote more general learning. In contrast to these typical findings, research over the past decade has shown that training on 'action video games' produces learning that transfers well beyond the training task. This has led to substantial interest among those interested in rehabilitation, for instance, after stroke or to treat amblyopia, or training for various precision-demanding jobs, for instance, endoscopic surgery or piloting unmanned aerial drones. Although the predominant focus of the field has been on outlining the breadth of possible action-game-related enhancements, recent work has concentrated on uncovering the mechanisms that underlie these changes, an important first step towards the goal of designing and using video games for more definite purposes. Game playing may not convey an immediate advantage on new tasks (increased performance from the very first trial), but rather the true effect of action video game playing may be to enhance the ability to learn new tasks. Such a mechanism may serve as a signature of training regimens that are likely to produce transfer of learning. Copyright Â© 2012 Elsevier Ltd. All rights reserved.
Green, C.S.; Bavelier, D.
While humans have an incredible capacity to acquire new skills and alter their behavior as a result of experience, enhancements in performance are typically narrowly restricted to the parameters of the training environment, with little evidence of generalization to different, even seemingly highly related, tasks. Such specificity is a major obstacle for the development of many real-world training or rehabilitation paradigms, which necessarily seek to promote more general learning. In contrast to these typical findings, research over the past decade has shown that training on ‘action video games’ produces learning that transfers well beyond the training task. This has led to substantial interest among those interested in rehabilitation, for instance, after stroke or to treat amblyopia, or training for various precision-demanding jobs, for instance, endoscopic surgery or piloting unmanned aerial drones. Although the predominant focus of the field has been on outlining the breadth of possible action-game-related enhancements, recent work has concentrated on uncovering the mechanisms that underlie these changes, an important first step towards the goal of designing and using video games for more definite purposes. Game playing may not convey an immediate advantage on new tasks (increased performance from the very first trial), but rather the true effect of action video game playing may be to enhance the ability to learn new tasks. Such a mechanism may serve as a signature of training regimens that are likely to produce transfer of learning. PMID:22440805
Online education is a growing trend world wide - eg. in-service training in large, especially trans- and multinational organizations (Turban et al. 2006); online and blended mode educations at universities (J. Drummond Bone 2004, OECD-report 2004); and educational programmes in developing countries...... (Daniel et al. 2005, D'Antoni 2005). Concurrently sharing of knowledge and online community building in general are acknowledged as important drivers in informal learning processes, while online learning in formalized educations tend towards an increasing adoption of collaborative learning...... as the pedagogic frame (Laurillard 2002, Salmon 2003). However, as one major driver in the general adoption of online education is economy, yet another trend is to raise the volume of learners passing through any education pr. time unit....
descriptive approach was chosen. The theoretical framework includes Jarvis’ concept of ‘disjuncture’, because it offers a theoretical way of understanding the empirical phenomenon of ‘non-routine-situations’. Heller’s concept of ‘everyday life activities’ is also drawn on, for its contribution......When the Danish government converted the national practice-oriented nursing qualification from a vocational course to a bachelor’s degree in 2002, the clinical training component was scaled back. Accordingly, mentors needed to optimise students’ learning from this curtailed clinical practice...... participant which takes place just after the researcher’s observation of the participant in interaction with a patient. The role of the researcher is to be a catalyst for the reflection. Using qualitative content analysis, a model of student nurses learning processes, termed the ‘Windmill of Learning...
Yun-Ping, Sun; Jun-Min, Li; Hui-Lin, Wang; Jiang-An, Wang
In this paper, a learning control approach is applied to the generalized projective synchronisation (GPS) of different chaotic systems with unknown periodically time-varying parameters. Using the Lyapunov–Krasovskii functional stability theory, a differential-difference mixed parametric learning law and an adaptive learning control law are constructed to make the states of two different chaotic systems asymptotically synchronised. The scheme is successfully applied to the generalized projective synchronisation between the Lorenz system and Chen system. Moreover, numerical simulations results are used to verify the effectiveness of the proposed scheme. (general)
Full Text Available Process-oriented thinking has become the major paradigm for managing companies and other organizations. The push for better processes has been even more intense due to rapidly evolving client needs, borderless global markets and innovations swiftly penetrating the market. Thus, education is decisive for successfully introducing and implementing Business Process Management (BPM initiatives. However, BPM education has been an area of challenge. This special issue aims to provide current research on various aspects of BPM education. It is an initial effort for consolidating better practices, experiences and pedagogical outcomes founded with empirical evidence to contribute towards the three pillars of education: learning, teaching, and disseminating knowledge in BPM.
Diyah Atiek Mustikawati
Full Text Available This study aimed to describe a form of code switching and code mixing specific form found in the teaching and learning activities in the classroom as well as determining factors influencing events stand out that form of code switching and code mixing in question.Form of this research is descriptive qualitative case study which took place in Al Mawaddah Boarding School Ponorogo. Based on the analysis and discussion that has been stated in the previous chapter that the form of code mixing and code switching learning activities in Al Mawaddah Boarding School is in between the use of either language Java language, Arabic, English and Indonesian, on the use of insertion of words, phrases, idioms, use of nouns, adjectives, clauses, and sentences. Code mixing deciding factor in the learning process include: Identification of the role, the desire to explain and interpret, sourced from the original language and its variations, is sourced from a foreign language. While deciding factor in the learning process of code, includes: speakers (O1, partners speakers (O2, the presence of a third person (O3, the topic of conversation, evoke a sense of humour, and just prestige. The significance of this study is to allow readers to see the use of language in a multilingual society, especially in AL Mawaddah boarding school about the rules and characteristics variation in the language of teaching and learning activities in the classroom. Furthermore, the results of this research will provide input to the ustadz / ustadzah and students in developing oral communication skills and the effectiveness of teaching and learning strategies in boarding schools.
Lombardi, Josephine; Muhamad, Nur; Weidenbach, M.
OZ Minerals' Prominent Hill copper- gold concentrator is located 130 km south east of the town of Coober Pedy in the Gawler Craton of South Australia. The concentrator was built in 2008 and commenced commercial production in early 2009. The Prominent Hill concentrator is comprised of a conventional grinding and flotation processing plant with a 9.6 Mtpa ore throughput capacity. The flotation circuit includes six rougher cells, an IseMill for regrinding the rougher concentrate and a Jameson cell heading up the three stage conventional cell cleaner circuit. In total there are four level controllers in the rougher train and ten level controllers in the cleaning circuit for 18 cells. Generic proportional — integral and derivative (PID) control used on the level controllers alone propagated any disturbances downstream in the circuit that were generated from the grinding circuit, hoppers, between cells and interconnected banks of cells, having a negative impact on plant performance. To better control such disturbances, FloatStar level stabiliser was selected for installation on the flotation circuit to account for the interaction between the cells. Multivariable control was also installed on the five concentrate hoppers to maintain consistent feed to the cells and to the IsaMill. An additional area identified for optimisation in the flotation circuit was the mass pull rate from the rougher cells. FloatStar flow optimiser was selected to be installed subsequent to the FloatStar level stabiliser. This allowed for a unified, consistent and optimal approach to running the rougher circuit. This paper describes the improvement in the stabilisation of the circuit achieved by the FloatStar level stabiliser by using the interaction matrix between cell level controllers and the results and benefits of implementing the FloatStar flow optimiser on the rougher train.
Gandomkar, Roghayeh; Mirzazadeh, Azim; Jalili, Mohammad; Yazdani, Kamran; Fata, Ladan; Sandars, John
This study was designed to identify the self-regulated learning (SRL) processes of medical students during a biomedical science learning task and to examine the associations of the SRL processes with previous performance in biomedical science examinations and subsequent performance on a learning task. A sample of 76 Year 1 medical students were recruited based on their performance in biomedical science examinations and stratified into previous high and low performers. Participants were asked to complete a biomedical science learning task. Participants' SRL processes were assessed before (self-efficacy, goal setting and strategic planning), during (metacognitive monitoring) and after (causal attributions and adaptive inferences) their completion of the task using an SRL microanalytic interview. Descriptive statistics were used to analyse the means and frequencies of SRL processes. Univariate and multiple logistic regression analyses were conducted to examine the associations of SRL processes with previous examination performance and the learning task performance. Most participants (from 88.2% to 43.4%) reported task-specific processes for SRL measures. Students who exhibited higher self-efficacy (odds ratio [OR] 1.44, 95% confidence interval [CI] 1.09-1.90) and reported task-specific processes for metacognitive monitoring (OR 6.61, 95% CI 1.68-25.93) and causal attributions (OR 6.75, 95% CI 2.05-22.25) measures were more likely to be high previous performers. Multiple analysis revealed that similar SRL measures were associated with previous performance. The use of task-specific processes for causal attributions (OR 23.00, 95% CI 4.57-115.76) and adaptive inferences (OR 27.00, 95% CI 3.39-214.95) measures were associated with being a high learning task performer. In multiple analysis, only the causal attributions measure was associated with high learning task performance. Self-efficacy, metacognitive monitoring and causal attributions measures were associated
Günther, Christian W.; Rinderle, S.B.; Reichert, M.U.; van der Aalst, Wil M.P.; Recker, Jan
Traditional information systems struggle with the requirement to provide flexibility and process support while still enforcing some degree of control. Accordingly, adaptive process management systems (PMSs) have emerged that provide some flexibility by enabling dynamic process changes during
Olga R. Harbych-Moshora
Full Text Available Today higher educational institutions should prepare a specialist, who is able to work successfully in globalized market conditions. Accent is made stronger on universal preparation of graduate student and his adaptation to jobs market, as well as on personal orientation of educational process and its informatization. The article considers a concept of distance learning technologies and their support systems. Designed system of distance learning for IT-specialists preparation based on a platform Moodle is a result of the study. The system ensures hierarchic organization of learning courses thanks to using an interactive multimedia clips in Adobe Flash format. As well as there is a possibility to organize various forms of learning and knowledge control.
Witt, Karsten; Daniels, Christine; Daniel, Victoria; Schmitt-Eliassen, Julia; Volkmann, Jens; Deuschl, Günther
Implicit memory and learning mechanisms are composed of multiple processes and systems. Previous studies demonstrated a basal ganglia involvement in purely cognitive tasks that form stimulus response habits by reinforcement learning such as implicit classification learning. We will test the basal ganglia influence on two cognitive implicit tasks previously described by Berry and Broadbent, the sugar production task and the personal interaction task. Furthermore, we will investigate the relationship between certain aspects of an executive dysfunction and implicit learning. To this end, we have tested 22 Parkinsonian patients and 22 age-matched controls on two implicit cognitive tasks, in which participants learned to control a complex system. They interacted with the system by choosing an input value and obtaining an output that was related in a complex manner to the input. The objective was to reach and maintain a specific target value across trials (dynamic system learning). The two tasks followed the same underlying complex rule but had different surface appearances. Subsequently, participants performed an executive test battery including the Stroop test, verbal fluency and the Wisconsin card sorting test (WCST). The results demonstrate intact implicit learning in patients, despite an executive dysfunction in the Parkinsonian group. They lead to the conclusion that the basal ganglia system affected in Parkinson's disease does not contribute to the implicit acquisition of a new cognitive skill. Furthermore, the Parkinsonian patients were able to reach a specific goal in an implicit learning context despite impaired goal directed behaviour in the WCST, a classic test of executive functions. These results demonstrate a functional independence of implicit cognitive skill learning and certain aspects of executive functions.
Full Text Available The purpose of the present study was to investigate differences among secondary school students in cognitive and metacognitive processes in self-regulated learning (SRL according to year of education, learning program, sex and achievement. Beside this, the autors were interested in the relationship between (metacognitive components of self-regulated learning. The theoretical framework of the research was the four-component model of self-regulated learning by Hofer, Yu and Pintrich (1998. The focus was on the first part of the model which is about cognitive structure and cognitive strategies.Metacognitive awareness inventory (Shraw and Sperling Dennison, 1994 and Cognitive strategies awareness questionnaire (Pečjak, 2000, in Peklaj and Pečjak, 2002 were applied. In a sample of 321 students, differences in perception of importance of cognitive strategies among students attending different grades (1st and 4th, students attending different learning programs, students of different gender and students with different achievements emerged. Students' achievement in the whole sample was related to amount of metacognitive awareness. In the sample of 4-year students and students attending professional secondary schools, students' achievement was additionally related to appraisal of importance elaboration and organizational strategies. Further statistical analyses of relationship between components in SRL showed high positive correlation between cognitive and metacognitive components.
Full Text Available Recent research on the memory operations used in language comprehension has revealed a selective profile of interference effects during memory retrieval. Dependencies such as subject-verb agreement show strong facilitatory interference effects from structurally inappropriate but feature-matching distractors, leading to illusions of grammaticality (Dillon, Mishler, Sloggett, & Phillips, 2013; Pearlmutter, Garnsey, & Bock, 1999; Wagers, Lau, & Phillips, 2009. In contrast, dependencies involving reflexive anaphors are generally immune to interference effects (Dillon et al., 2013; Sturt, 2003; Xiang, Dillon, & Phillips, 2009. This contrast has led to the proposal that all anaphors that are subject to structural constraints are immune to facilitatory interference. Here we use an animacy manipulation to examine whether adjunct control dependencies, which involve an interpreted anaphoric relation between a null subject and its licensor, are also immune to facilitatory interference effects. Our results show reliable facilitatory interference in the processing of adjunct control dependencies, which challenges the generalization that anaphoric dependencies as a class are immune to such effects. To account for the contrast between adjunct control and reflexive dependencies, we suggest that variability within anaphora could reflect either an inherent primacy of animacy cues in retrieval processes, or differential degrees of match between potential licensors and the retrieval probe.
Sheaffer, Donald A.; Renzi, Ronald F.; Tung, David M.; Schroder, Kevin
Method and system for producing high quality welds in welding processes, in general, and gas tungsten arc (GTA) welding, in particular by controlling weld penetration. Light emitted from a weld pool is collected from the backside of a workpiece by optical means during welding and transmitted to a digital video camera for further processing, after the emitted light is first passed through a short wavelength pass filter to remove infrared radiation. By filtering out the infrared component of the light emitted from the backside weld pool image, the present invention provides for the accurate determination of the weld pool boundary. Data from the digital camera is fed to an imaging board which focuses on a 100.times.100 pixel portion of the image. The board performs a thresholding operation and provides this information to a digital signal processor to compute the backside weld pool dimensions and area. This information is used by a control system, in a dynamic feedback mode, to automatically adjust appropriate parameters of a welding system, such as the welding current, to control weld penetration and thus, create a uniform weld bead and high quality weld.
Ahring, B K; Angelidaki, I [The Technical Univ. of Denmark, Dept. of Environmental Science and Engineering, Lyngby (Denmark)
Many modern large-scale biogas plants have been constructed recently, increasing the demand for proper monitoring and control of these large reactor systems. For monitoring the biogas process, an easy to measure and reliable indicator is required, which reflects the metabolic state and the activity of the bacterial populations in the reactor. In this paper, we discuss existing indicators as well as indicators under development which can potentially be used to monitor the state of the biogas process in a reactor. Furthermore, data are presented from two large scale thermophilic biogas plants, subjected to temperature changes and where the concentration of volatile fatty acids was monitored. The results clearly demonstrated that significant changes in the concentration of the individual VFA occurred although the biogas production was not significantly changed. Especially the concentrations of butyrate, isobutyrate and isovalerate showed significant changes. Future improvements of process control could therefore be based on monitoring of the concentration of specific VFA`s together with information about the bacterial populations in the reactor. The last information could be supplied by the use of modern molecular techniques. (au) 51 refs.
Giebel, S; Rainer, M
Models for financial asset dynamics usually take into account their inherent unpredictable nature by including a suitable stochastic component into their process. Unknown (forward) values of financial assets (at a given time in the future) are usually estimated as expectations of the stochastic asset under a suitable risk-neutral measure. This estimation requires the stochastic model to be calibrated to some history of sufficient length in the past. Apart from inherent limitations, due to the stochastic nature of the process, the predictive power is also limited by the simplifying assumptions of the common calibration methods, such as maximum likelihood estimation and regression methods, performed often without weights on the historic time series, or with static weights only. Here we propose a novel method of "intelligent" calibration, using learning neural networks in order to dynamically adapt the parameters of the stochastic model. Hence we have a stochastic process with time dependent parameters, the dynamics of the parameters being themselves learned continuously by a neural network. The back propagation in training the previous weights is limited to a certain memory length (in the examples we consider 10 previous business days), which is similar to the maximal time lag of autoregressive processes. We demonstrate the learning efficiency of the new algorithm by tracking the next-day forecasts for the EURTRY and EUR-HUF exchange rates each.
E-learning now accounts for a substantial proportion of medical education provision. This progress has required significant investment and this investment has in turn come under increasing scrutiny so that the costs of e-learning may be controlled and its returns maximised. There are multiple methods by which the costs of e-learning can be controlled and its returns maximised. This short paper reviews some of those methods that are likely to be most effective and that are likely to save costs without compromising quality. Methods might include accessing free or low-cost resources from elsewhere; create short learning resources that will work on multiple devices; using open source platforms to host content; using in-house faculty to create content; sharing resources between institutions; and promoting resources to ensure high usage. Whatever methods are used to control costs or increase value, it is most important to evaluate the impact of these methods.
Cools, Roshan; Roberts, Angela C; Robbins, Trevor W
5-Hydroxytryptamine (5-HT, serotonin) has long been implicated in a wide variety of emotional, cognitive and behavioural control processes. However, its precise contribution is still not well understood. Depletion of 5-HT enhances behavioural and brain responsiveness to punishment or other aversive signals, while disinhibiting previously rewarded but now punished behaviours. Findings suggest that 5-HT modulates the impact of punishment-related signals on learning and emotion (aversion), but also promotes response inhibition. Exaggerated aversive processing and deficient response inhibition could underlie distinct symptoms of a range of affective disorders, namely stress- or threat-vulnerability and compulsive behaviour, respectively. We review evidence from studies with human volunteers and experimental animals that begins to elucidate the neurobiological systems underlying these different effects.
Ezequiel Gibbon Gautério
Full Text Available The aim of this article was to study some indicators of academic performance (number of students per class, dropout rate, failure rate and scores obtained by the students to identify a pattern of behavior that would enable to implement improvements in the teaching-learning process. The sample was composed of five classes of undergraduate courses in Engineering. The data were collected for three years. Initially an exploratory analysis with analytical and graphical techniques was performed. An analysis of variance and Tukey’s test investigated some sources of variability. This information was used in the construction of control charts. We have found evidence that classes with more students are associated with higher failure rates and lower mean. Moreover, when the course was later in the curriculum, the students had higher scores. The results showed that although they have been detected some special causes interfering in the process, it was possible to stabilize it and to monitor it.