Academic literature on the topic 'Belief driven control'
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Journal articles on the topic "Belief driven control"
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Airaudo, Marco, Roberta Cardani, and Kevin J. Lansing. "Monetary policy and asset prices with belief-driven fluctuations." Journal of Economic Dynamics and Control 37, no. 8 (August 2013): 1453–78. http://dx.doi.org/10.1016/j.jedc.2013.03.002.
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Webb, Stephen, and Tomonari Furukawa. "Belief-Driven Manipulator Visual Servoing for Less Controlled Environments." Advanced Robotics 22, no. 5 (January 1, 2008): 547–72. http://dx.doi.org/10.1163/156855308x294888.
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Douglas, Karen M., Robbie M. Sutton, and Aleksandra Cichocka. "The Psychology of Conspiracy Theories." Current Directions in Psychological Science 26, no. 6 (December 2017): 538–42. http://dx.doi.org/10.1177/0963721417718261.
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What psychological factors drive the popularity of conspiracy theories, which explain important events as secret plots by powerful and malevolent groups? What are the psychological consequences of adopting these theories? We review the current research and find that it answers the first of these questions more thoroughly than the second. Belief in conspiracy theories appears to be driven by motives that can be characterized as epistemic (understanding one’s environment), existential (being safe and in control of one’s environment), and social (maintaining a positive image of the self and the social group). However, little research has investigated the consequences of conspiracy belief, and to date, this research does not indicate that conspiracy belief fulfills people’s motivations. Instead, for many people, conspiracy belief may be more appealing than satisfying. Further research is needed to determine for whom, and under what conditions, conspiracy theories may satisfy key psychological motives.
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Schulreich, Stefan, and Lars Schwabe. "Causal Role of the Dorsolateral Prefrontal Cortex in Belief Updating under Uncertainty." Cerebral Cortex 31, no. 1 (August 20, 2020): 184–200. http://dx.doi.org/10.1093/cercor/bhaa219.
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Abstract Adaptive performance in uncertain environments depends on the ability to continuously update internal beliefs about environmental states. Recent correlative evidence suggests that a frontoparietal network including the dorsolateral prefrontal cortex (dlPFC) supports belief updating under uncertainty, but whether the dlPFC serves a “causal” role in this process is currently not clear. To elucidate its contribution, we leveraged transcranial direct current stimulation (tDCS) over the right dlPFC, while 91 participants performed an incentivized belief-updating task. Participants also underwent a psychosocial stress or control manipulation to investigate the role of stress, which is known to modulate dlPFC functioning. We observed enhanced monetary value updating after anodal tDCS when it was normatively expected from a Bayesian perspective. A model-based analysis indicates that this effect was driven by belief updating. However, we also observed enhanced non-normative value updating, which might have been driven instead by expectancy violation. Enhanced normative and non-normative value updating reflected increased vs. decreased Bayesian rationality, respectively. Furthermore, cortisol increases were associated with enhanced positive, but not with negative, value updating. The present study thereby sheds light on the causal role of the right dlPFC in the remarkable human ability to navigate uncertain environments by continuously updating prior knowledge following new evidence.
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Zhang, Chaoyang, and Pingyu Jiang. "RFID-Driven Energy-Efficient Control Approach of CNC Machine Tools Using Deep Belief Networks." IEEE Transactions on Automation Science and Engineering 17, no. 1 (January 2020): 129–41. http://dx.doi.org/10.1109/tase.2019.2909043.
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Wang, Xiaoli, Xingxiao Lv, and Chunhua Yang. "Data-driven Extraction Method of Belief Rule for Reagent Addition in Antimony Rougher Flotation." IFAC-PapersOnLine 52, no. 14 (2019): 72–77. http://dx.doi.org/10.1016/j.ifacol.2019.09.166.
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Nishimura, Haruki, and Mac Schwager. "SACBP: Belief space planning for continuous-time dynamical systems via stochastic sequential action control." International Journal of Robotics Research 40, no. 10-11 (August 13, 2021): 1167–95. http://dx.doi.org/10.1177/02783649211037697.
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We propose a novel belief space planning technique for continuous dynamics by viewing the belief system as a hybrid dynamical system with time-driven switching. Our approach is based on the perturbation theory of differential equations and extends sequential action control to stochastic dynamics. The resulting algorithm, which we name SACBP, does not require discretization of spaces or time and synthesizes control signals in near real-time. SACBP is an anytime algorithm that can handle general parametric Bayesian filters under certain assumptions. We demonstrate the effectiveness of our approach in an active sensing scenario and a model-based Bayesian reinforcement learning problem. In these challenging problems, we show that the algorithm significantly outperforms other existing solution techniques including approximate dynamic programming and local trajectory optimization.
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Chaudhuri, Ananish. "Belief Heterogeneity and the Restart Effect in a Public Goods Game." Games 9, no. 4 (November 23, 2018): 96. http://dx.doi.org/10.3390/g9040096.
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We explore how subjects with heterogeneous beliefs respond to a surprise restart in a linear public goods game played for 20 rounds using either a “partners” or a “strangers” protocol. There are two restarts: one prior to Round 11 and another prior to Round 16. We elicit subject beliefs at the outset and classify subjects into three groups—Top, Middle, and Bottom—depending on their prior beliefs about their peers’ contributions to the public good. Then, we look at how these three groups respond, in terms of their beliefs and contributions, before and after the restart. We replicate the restart effect, but find that (i) it is much more pronounced for partner matching than for stranger matching and (ii) it is less pronounced in treatments with belief elicitation compared to control treatments where beliefs are not elicited. We also find that the restart has the effect of regenerating a sense of optimism among the subjects, which is reflected in increased contributions subsequently. This increase in contribution is driven mostly by those subjects who started the game with relatively more optimistic beliefs. Our results have implications for sustaining cooperation in social dilemma games.
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Noel, Jean-Paul, Kaushik J. Lakshminarasimhan, Hyeshin Park, and Dora E. Angelaki. "Increased variability but intact integration during visual navigation in Autism Spectrum Disorder." Proceedings of the National Academy of Sciences 117, no. 20 (May 1, 2020): 11158–66. http://dx.doi.org/10.1073/pnas.2000216117.
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Autism Spectrum Disorder (ASD) is a common neurodevelopmental disturbance afflicting a variety of functions. The recent computational focus suggesting aberrant Bayesian inference in ASD has yielded promising but conflicting results in attempting to explain a wide variety of phenotypes by canonical computations. Here, we used a naturalistic visual path integration task that combines continuous action with active sensing and allows tracking of subjects’ dynamic belief states. Both groups showed a previously documented bias pattern by overshooting the radial distance and angular eccentricity of targets. For both control and ASD groups, these errors were driven by misestimated velocity signals due to a nonuniform speed prior rather than imperfect integration. We tracked participants’ beliefs and found no difference in the speed prior, but there was heightened variability in the ASD group. Both end point variance and trajectory irregularities correlated with ASD symptom severity. With feedback, variance was reduced, and ASD performance approached that of controls. These findings highlight the need for both more naturalistic tasks and a broader computational perspective to understand the ASD phenotype and pathology.
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Chinchali, Sandeep P., Scott C. Livingston, Mo Chen, and Marco Pavone. "Multi-objective optimal control for proactive decision making with temporal logic models." International Journal of Robotics Research 38, no. 12-13 (August 15, 2019): 1490–512. http://dx.doi.org/10.1177/0278364919868290.
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The operation of today’s robots entails interactions with humans, e.g., in autonomous driving amidst human-driven vehicles. To effectively do so, robots must proactively decode the intent of humans and concurrently leverage this knowledge for safe, cooperative task satisfaction: a problem we refer to as proactive decision making. However, simultaneous intent decoding and robotic control requires reasoning over several possible human behavioral models, resulting in high-dimensional state trajectories. In this paper, we address the proactive decision-making problem using a novel combination of formal methods, control, and data mining techniques. First, we distill high-dimensional state trajectories of human–robot interaction into concise, symbolic behavioral summaries that can be learned from data. Second, we leverage formal methods to model high-level agent goals, safe interaction, and information-seeking behavior with temporal logic formulas. Finally, we design a novel decision-making scheme that maintains a belief distribution over models of human behavior, and proactively plans informative actions. After showing several desirable theoretical properties, we apply our framework to a dataset of humans driving in crowded merging scenarios. For it, temporal logic models are generated and used to synthesize control strategies using tree-based value iteration and deep reinforcement learning. In addition, we illustrate how data-driven models of human responses to informative robot probes, such as from generative models such as conditional variational autoencoders, can be clustered with formal specifications. Results from simulated self-driving car scenarios demonstrate that data-driven strategies enable safe interaction, correct model identification, and significant dimensionality reduction.
Dissertations / Theses on the topic "Belief driven control"
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Webb, Stephen Scott Mechanical & Manufacturing Engineering Faculty of Engineering UNSW. "Belief driven autonomous manipulator pose selection for less controlled environments." Publisher:University of New South Wales. Mechanical & Manufacturing Engineering, 2008. http://handle.unsw.edu.au/1959.4/43090.
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This thesis presents a new approach for selecting a manipulator arm configuration (a pose) in an environment where the positions of the work items are not able to be fully controlled. The approach utilizes a belief formed from a priori knowledge, observations and predictive models to select manipulator poses and motions. Standard methods for manipulator control provide a fully specified Cartesian pose as the input to a robot controller which is assumed to act as an ideal Cartesian motion device. While this approach simplifies the controller and makes it more portable, it is not well suited for less-controlled environments where the work item position or orientation may not be completely observable and where a measure of the accuracy of the available observations is required. The proposed approach suggests selecting a manipulator configuration using two types of rating function. When uncertainty is high, configurations are rated by combining a belief, represented by a probability density function, and a value function in a decision theoretic manner enabling selection of the sensor??s motion based on its probabilistic contribution to information gain. When uncertainty is low the mean or mode of the environment state probability density function is utilized in task specific linear or angular distances constraints to map a configuration to a cost. The contribution of this thesis is in providing two formulations that allow joint configurations to be found using non-linear optimization algorithms. The first formulation shows how task specific linear and angular distance constraints are combined in a cost function to enable a satisfying pose to be selected. The second formulation is based on the probabilistic belief of the predicted environment state. This belief is formed by utilizing a Bayesian estimation framework to combine the a priori knowledge with the output of sensor data processing, a likelihood function over the state space, thereby handling the uncertainty associated with sensing in a less controlled environment. Forward models are used to transform the belief to a predicted state which is utilized in motion selection to provide the benefits of a feedforward control strategy. Extensive numerical analysis of the proposed approach shows that using the fed-forward belief improves tracking performance by up to 19%. It is also shown that motion selection based on the dynamically maintained belief reduces time to target detection by up to 50% compared to two other control approaches. These and other results show how the proposed approach is effectively able to utilize an uncertain environment state belief to select manipulator arm configurations.
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Kruyswijk, Renske. "Socio–environmental factors, objectified body consciousness and drive for muscularity in undergraduate men / Renske Kruyswijk." Thesis, North-West University, 2010. http://hdl.handle.net/10394/4857.
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The display of the male body has recently become a common phenomenon in Western culture. The objectification of men is a new theoretical concept that originates from the more familiar concept of the perceived objectification, observation and evaluation of the female body (Fredrickson & Roberts, 1997). McKinley (as cited in Soban, 2006) terms this concept Objectified Body Consciousness (OBC). Past studies confirm that the concept of OBC may also be successfully applied to males (Grieve & Helmick, 2008; Tiggemann & Kuring, 2004), especially in relation to current cultural expectations for the male body (Grieve & Helmick, 2008; Soban, 2006). At an extreme level internalisation of the mesomorphic body shape as body ideal may lead to a Drive for Muscularity (DM; Grieve, 2007). Grieve and Helmick (2008) indicate that males who score high on objectification measures show higher incidences of DM. According to the socio–environmental theories of Grieve (2007) and McCabe and Ricciardelli (2004) males experience significant social pressures to achieve the muscular ideal. There is a scarcity of literature concerning body–image concerns and the muscular ideal within the South African male undergraduate population. This research was therefore exploratory in nature and aimed to determine whether undergraduate men with high levels of OBC differ significantly in DM from undergraduate men with low levels of OBC. In addition, the study investigated the existence of a correlation between OBC and DM and whether undergraduate men differ in DM in accordance with exposure to certain socio–environmental factors. The quantitative study employed a survey design (Mouton, 2001) and used the Objectified Body Consciousness Scale (OBCS; McKinley & Hyde, 1996) and the Drive for Muscularity Scale (DMS; McCreary & Sasse, 2000). A convenience sample of 278 undergraduate males (mean age = 19 years) was selected based on availability and readiness to partake in the study (Field, 2005). Participants were all males aged between 18 and 20 and residing on the North–West University Potchefstroom Campus. Results indicate that undergraduate men with either elevated or low levels of OBC do not differ in terms of their DM. No correlation exists between OBC and DM. A group of undergraduate men who read fitness and health–related magazines, participate in sport, exercise regularly and have used steroids and supplements in the past year was identified. This group presented with high incidences of Muscle Development Behaviour suggesting that they may be at risk of internalising an attitude of increasing muscularity that may result in DM.Thesis (M.A. (Clinical Psychology))--North-West University, Potchefstroom Campus, 2011.
Books on the topic "Belief driven control"
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Glannon, Walter. Behavior Control, Meaning, and Neuroscience. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190460723.003.0009.
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Neuroscience challenges our beliefs about agency and autonomy because it seems to imply that we have no control of our behavior: most brain processes are not transparent to us, we have no direct access to the efferent system, and we only experience the sensorimotor consequences of our unconscious motor plans. In this chapter, Walter Glannon argues that although unconscious processes drive many of our actions, this does not imply that conscious mental states have no causal role in our behavior and that we have no control over it. He argues that some degree of unconscious neural constraint on conscious mental states is necessary to modulate thought and action and promote flexible behavior and adaptability to environmental demands. He maintains that a nonreductive materialist account of the mind–brain relation makes it plausible to claim that mental states can cause changes in physical states of the brain.
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Magalhães, Rodrigo. Designing Organization Design. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198867333.001.0001.
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As a topic, organization design is poorly understood. While it is featured in most management textbooks as a chapter dedicated to organizational structures, it is unclear whether organization design is a one-off event or an ongoing process. Thus, it has traditionally been understood to be the same as an organizational configuration, with neat lines of communication and distribution of responsibilities, following pre-set typologies. However, what can be said to constitute organizational structure in this first half of the 21st century? The extraordinary growth of digital communications, the decreasing relevance of hierarchical bureaucracies, and the general demise of command-and-control have all but decimated the traditional notion of organizational structure. In this book it is argued that organization design needs a theoretical revamping. Using a mix of design and social sciences theories and concepts, the new approach is divided into three parts: design logics, design processes, and design leadership. A generic definition of organization design logics is offered, as a set of beliefs shared by managers and entrepreneurs in given sectors of the economy about the way organizations should be designed. Five logics and three types of designing processes are put forward. Logics: (1) the identity logic, (2) the normative logic, (3) the service logic, (4) the logic of effectual reasoning, (5) the logic of interactive structure. Processes: (1) intended design, (2) emergent design, (3) perceived design. For the leadership part, a model of leaderful organization design(ing) is proposed, with the following distinguishing features: (a) practice-based, (b) guided by values of democratic participation, (c) places meaning-making and meaning-taking at the centre of organizational life, (d) driven by design logics, which can be adopted and adapted to suit different internal and external environments.
Book chapters on the topic "Belief driven control"
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Spohn, Leon, Marcus Bergen, Nicolai Benz, Denis Vonscheidt, Hans-Jörg Haubner, and Marcus Strand. "I Believe I Can Fly—Gesture-Driven Quadrotor Control Based on a Fuzzy Control System." In Intelligent Autonomous Systems 14, 177–84. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-48036-7_13.
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More, Shammi, Simon B. Eickhoff, Julian Caspers, and Kaustubh R. Patil. "Confound Removal and Normalization in Practice: A Neuroimaging Based Sex Prediction Case Study." In Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track, 3–18. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-67670-4_1.
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AbstractMachine learning (ML) methods are increasingly being used to predict pathologies and biological traits using neuroimaging data. Here controlling for confounds is essential to get unbiased estimates of generalization performance and to identify the features driving predictions. However, a systematic evaluation of the advantages and disadvantages of available alternatives is lacking. This makes it difficult to compare results across studies and to build deployment quality models. Here, we evaluated two commonly used confound removal schemes–whole data confound regression (WDCR) and cross-validated confound regression (CVCR)–to understand their effectiveness and biases induced in generalization performance estimation. Additionally, we study the interaction of the confound removal schemes with Z-score normalization, a common practice in ML modelling. We applied eight combinations of confound removal schemes and normalization (pipelines) to decode sex from resting-state functional MRI (rfMRI) data while controlling for two confounds, brain size and age. We show that both schemes effectively remove linear univariate and multivariate confounding effects resulting in reduced model performance with CVCR providing better generalization estimates, i.e., closer to out-of-sample performance than WDCR. We found no effect of normalizing before or after confound removal. In the presence of dataset and confound shift, four tested confound removal procedures yielded mixed results, raising new questions. We conclude that CVCR is a better method to control for confounding effects in neuroimaging studies. We believe that our in-depth analyses shed light on choices associated with confound removal and hope that it generates more interest in this problem instrumental to numerous applications.
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Wang, Mingzhong, Jinjun Chen, Kotagiri Ramamohanarao, and Amy Unruh. "Multiple-Step Backtracking of Exception Handling in Autonomous Business Process Management." In Handbook of Research on Complex Dynamic Process Management, 251–70. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-60566-669-3.ch010.
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This chapter proposes a multiple-step backtracking mechanism to maintain a tradeoff between replanning and rigid backtracking for exception handling and recovery, thus enabling business process management (BPM) systems to operate robustly even in complex and dynamic environments. The concept of BDI (belief, desire and intention) agent is applied to model and construct the BPM system to inherit its advantages of adaptability and flexibility. Then, the flexible backtracking approach is introduced by utilizing the beneficial features of event-driven and means-end reasoning of BDI agents. Finally, we incorporate open nested transaction model to encapsulate plan execution and backtracking to gain the system level support of concurrency control and automatic recovery. With the ability of reasoning about task characteristics, our approach enables the system to find and commence a suitable plan prior to or in parallel with a compensation process when a failure occurs. This kind of computing allows us to achieve business goals efficiently in the presence of exceptions and failures.
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Wang, Mingzhong, Jinjun Chen, Kotagiri Ramamohanarao, and Amy Unruh. "Multiple-Step Backtracking of Exception Handling in Autonomous Business Process Management." In Enterprise Information Systems, 1081–98. IGI Global, 2011. http://dx.doi.org/10.4018/978-1-61692-852-0.ch413.
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This chapter proposes a multiple-step backtracking mechanism to maintain a tradeoff between replanning and rigid backtracking for exception handling and recovery, thus enabling business process management (BPM) systems to operate robustly even in complex and dynamic environments. The concept of BDI (belief, desire and intention) agent is applied to model and construct the BPM system to inherit its advantages of adaptability and flexibility. Then, the flexible backtracking approach is introduced by utilizing the beneficial features of event-driven and means-end reasoning of BDI agents. Finally, we incorporate open nested transaction model to encapsulate plan execution and backtracking to gain the system level support of concurrency control and automatic recovery. With the ability of reasoning about task characteristics, our approach enables the system to find and commence a suitable plan prior to or in parallel with a compensation process when a failure occurs. This kind of computing allows us to achieve business goals efficiently in the presence of exceptions and failures.
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Balderas-Contreras, Tomás, Gustavo Rodriguez-Gomez, and René Cumplido. "On Model-Driven Engineering of Reconfigurable Digital Control Hardware Systems." In Reconfigurable Embedded Control Systems, 190–208. IGI Global, 2011. http://dx.doi.org/10.4018/978-1-60960-086-0.ch008.
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The continuous increase in the degree of design complexity during the development process of modern digital hardware systems, come into being due to the increasing demand of more and more functionality under strict design constraints, has led to designers trying to alleviate this complexity by increasing the level of abstraction when describing the functionality of a system. Recent proposals in the field of Electronic Design Automation intend to use common programming languages, like C, C++, and Java, or dialects derived from them, to describe the behavior of a digital hardware system and then generate a lower-level representation, closer to the hardware implementation platform, from such description. This phenomenon led us to firmly believe that the process of describing the functionality of a digital circuit resembles more and more the process of developing software; and, thus, it is possible to experiment with the application of the latest trends in software engineering, like the Model-Driven Engineering (MDE) paradigm, to design digital hardware systems. In this chapter we describe the basic principles of MDE, and provide some hints about the kind of languages and transformation tools needed to design algorithms in the domain of digital control that could be transformed into a digital circuit. We intend to open doors and encourage the research on the design of digital control systems at higher levels of abstraction and their implementations in different kinds of hardware platforms, including reconfigurable devices.
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Sewart, Amy R., and Michelle G. Craske. "Flexible Principles for the Treatment of Adult Worry." In Flexibility within Fidelity, 25–41. Oxford University Press, 2021. http://dx.doi.org/10.1093/med-psych/9780197552155.003.0003.
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This chapter outlines various empirically supported cognitive-behavioral strategies driven by current understanding of worry-related mechanisms that may be implemented in the treatment of chronic worry. Excessive and uncontrollable worry is reliably observed across anxiety disorders, and it is most evident in generalized anxiety disorder (GAD), of which it is the cardinal symptom. At present, achieving treatment fidelity for cognitive behavioral therapy (CBT) for excessive worry requires cognitive restructuring—wherein targets can range from challenging overestimation of likelihood, severity of negative outcomes, or metacognitive beliefs about worry—and exposure, either in vivo or imaginal, as a means to provide extinction learning around feared outcomes involving uncertainty or aversive emotional experiences. It also requires behavioral experimentation through which worry-related cognitions are tested and challenged through “real-life” experiences, which may involve stimulus control/worry postponement; explicit removal of safety behaviors throughout all components of treatment; and incorporation of strategies to enhance problem orientation. Using a case formulation-driven approach, these elements can be flexibly applied in a systematic, responsive, and data-driven manner to target the deficits present in the individual.
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Hugo Criado del Valle, Carlos, and Parichehr Scharifi. "Cognitive Profile of Optimistic Offender Drivers Affected by Psychological Interventions for a Sustainable and Safer Driving’s Behavior." In Transportation Systems for Smart, Sustainable, Inclusive and Secure Cities [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.96249.
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An empirically verified fact is that the majority of traffic accidents occur as a result of risky behaviours that drivers assume, more or less, voluntarily. Drivers are not aware of the perception of risk and the subjective perception of control that we believe we have. We have delimitated the characteristics of a group of optimistic offender drivers, which reveal, on the hand, a great lack of understanding of the true impact that external factors can have on driving and; on the other hand, they tend to overestimate their abilities and overconfident in their ability to avoid accidents. In addition, these drivers do not usually experience negative emotions when they fail. All this, together is what increases the probability of suffering an accident. The consideration of the different cognitive profiles in the perception of the risk or challenge when facing potential traffic situations may provide us with a better understanding of the true nature of offending drivers. The need to carry out experimental studies using new assessment instruments (i.e. Eye tracking, Bio-Feedback, evoked potentials, etc.) can facilitate a better understanding of the cognitive processes that explain the attitudes and behaviors of drivers; and therefore, achieve a lower rate of car accidents.
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Swensen, Stephen J., and Tait D. Shanafelt. "Drivers of Burnout and Engagement." In Mayo Clinic Strategies To Reduce Burnout, edited by Stephen J. Swensen and Tait D. Shanafelt, 17–24. Oxford University Press, 2020. http://dx.doi.org/10.1093/med/9780190848965.003.0003.
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Future physicians complete their undergraduate studies with excellent mental and emotional health. Once these students enter medical school, their enthusiasm, vitality, idealism, and engagement are systematically eroded by the training process. Similarly, more nurses also experience burnout during their early working years. We believe a helpful way to look at burnout is to think about six characteristics of a health care system that, when working optimally, create engaged professionals and meaning and purpose in work. These characteristics are workload and job demands, efficiency and resources control and flexibility, organizational culture and values, social support and community at work, and work-life integration. When these six workplace dimensions do not function optimally, they become drivers of burnout.
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Haseeb, Muhammad. "Teaching Generation Z Students in the Technology-Driven World." In Cases on Digital Learning and Teaching Transformations in Higher Education, 52–66. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-9331-7.ch004.
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Today, higher education is experiencing significant changes in its recruitment, retention, graduation, and accreditation. Faculty professional development is considered a key for the success of Generation Z students. As a result, faculty are interested to modify their teaching environment. More and more faculty are flipping their traditional courses and offering either hybrid or online courses. Blended learning means that students receive instruction in both face-to-face and online environments. Embedded within the concept is an assumption that blended teaching environments also give students some control over the pace, flow, or focus of their learning activities. Also, blended learning prepares students for full online courses. Research indicates that empowering students to have organization in their education leads to many positive outcomes, including that students do better in inequality of access situations, are able to personalize their learning and achieve regardless of ability, and build dispositional skills, such as executive functioning, perseverance, self-awareness, and tolerance for uncertainty, that many believe are necessary to thrive in current and future societies. This chapter explains current practices and the potential of digital learning initiatives to teach Generation Z in the technology-driven world.
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Kennair, Leif Edward Ottesen, Ellen Beate Hansen Sandseter, and David Ball. "Risky Play and Growing Up: How to Understand the Overprotection of the Next Generation." In Pseudoscience. The MIT Press, 2018. http://dx.doi.org/10.7551/mitpress/9780262037426.003.0007.
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Much of the development of children, young people, and young adults is determined by opportunities for play and “real life” experience in their early years. This is not, as some believe, an optional or frivolous luxury, but an essential life experience for development of character, skills, self-awareness, and competence. Yet in recent years, evidence shows that opportunities for this at all ages have diminished in both quality and quantity in many countries. The reasons for this are multiple and complex, but one factor has been a drive to create a low risk or even risk-free society via the application of newly developed techniques of risk assessment and science-based methods of risk control. However, the health benefits of these public safety initiatives might have much less effect than people might believe and could, overall, be harmful through their prohibitions. We conclude that more research into the nature of risky play and risk exposure through teenage years and into adulthood is necessary, but tentatively propose that we need to also consider the possible effects of irrational overprotection. In addition to the conventional play setting, the current spread of trigger warning and safety rooms will be considered as an illustrative case affecting young adults. Rather than avoidance and consolidation of negative metacognitions about lack of control and vulnerability one needs to convey how science suggests that exposure or interventions to change perceptions of vulnerability may be more beneficial.
Conference papers on the topic "Belief driven control"
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Webb, Stephen, and Tomonari Furukawa. "Belief Driven Manipulator Control for Integrated Searching and Tracking." In 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, 2006. http://dx.doi.org/10.1109/iros.2006.282523.
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Qin, Beibei, Zengqiang Chen, Mingwei Sun, and Qinglin Sun. "Active Disturbance Rejection Control of Ship Course Based on Deep Belief Network." In 2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS). IEEE, 2019. http://dx.doi.org/10.1109/ddcls.2019.8908840.
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Su, Jing-Ru, Jian-Guo Wang, Zhong-Tao Xie, Yuan Yao, and Junjiang Liu. "A Method for EEG Contributory Channel Selection Based on Deep Belief Network." In 2019 IEEE 8th Data Driven Control and Learning Systems Conference (DDCLS). IEEE, 2019. http://dx.doi.org/10.1109/ddcls.2019.8909013.
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Yamada, Kenshiro, Makoto Kumon, and Tomonari Furukawa. "Belief-Driven Control Policy of a Drone with Microphones for Multiple Sound Source Search." In 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2019. http://dx.doi.org/10.1109/iros40897.2019.8968119.
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Vrijdag, A., and Y. Sang. "Fingerprinting the ship propulsion system: low hanging fruit or mission impossible?" In International Ship Control Systems Symposium. IMarEST, 2018. http://dx.doi.org/10.24868/issn.2631-8741.2018.013.
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In this paper the concept of ship propulsion system “fingerprinting” is explored as an alternative for data driven models that require extensive measured datasets collected over long periods of ship operation. As a first exploratory step a model of a ship in bollard pull conditions is linearised and its transfer functions are determined. Subsequently limited experimental data, involving sinusoidal excitation of the system input at a wide range of frequencies, is used to determine the system parameters. The resulting parameter estimates compare well against previously determined values. Although the developed ideas are far from ready to be used on full scale, the authors believe that the approach is promising enough to be developed further towards full scale application.
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Cook, M. J., T. Simpson, D. Garrett, and M. Thody. "Three laws good: Technology is a dangerous master." In International Ship Control Systems Symposium. IMarEST, 2018. http://dx.doi.org/10.24868/issn.2631-8741.2018.016.
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A philosophy of technology use has developed in many safety-critical industries that is based upon the view that human operators are feckless and unreliable system operators, so wherever possible should not be trusted to execute safety-critical tasks. The implicit view of automation is that it invariably improves system performance and increases reliability. After many decades or even centuries of machine and automation development human error remains one of the dominant features in failures of modern systems. The drive towards introducing automation has claimed a larger performance envelope, lower operating costs with fewer people, less risk of hazard realisation, and a more economical path in development. One of the aims of introducing automation is to introduce higher reliability in the belief that this implicitly brings with it increases in safety. As Leveson (2011) points out high reliability can be misleading because interactions between elements that are working as expected may trigger the system failure because of transverse consequences. The propagation of the view that human operators are the weakest operational link and the pervasive myths about the reliability of automated solutions, which affords automation the easier scenarios of task execution, need to be re-visited (Cook, Thody and Garrett, 2017). This should ensure that the best capability and optimal safety case is developed for future systems based upon operator and system in synergy. This may be especially true if the claims for automation are treated more aggressively in terms of liability.
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Canova, Marcello, Joseph Porembski, Kris Sevel, Yann Guezennec, and Steve Yurkovich. "Model-Based Control for Diesel Engine Start-Stop Operations With a Belted Starter/Alternator." In ASME 2007 International Mechanical Engineering Congress and Exposition. ASMEDC, 2007. http://dx.doi.org/10.1115/imece2007-41836.
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The coupling of an internal combustion engine with a starter/alternator is one of the most easily realizable hybrid electric vehicle configurations to achieve significant fuel economy savings in urban driving. A successful implementation of the starter alternator technology includes controlling the electric motor to start and stop the engine quickly and smoothly, without compromising the vehicle noise, vibration and harshness (NVH) signature. The issue becomes more critical in the case of Diesel hybrids, as the peak compression torque is much larger than in automotive spark ignition engines. This paper presents a model-based approach in control design for engine start/stop operations with a belted starter/alternator. Starting from previous modeling and experimental results, a nonlinear model of a belted starter/alternator coupled with a Diesel engine is developed for control algorithm development. With the introduction of a feed-forward control action proportional to the instantaneous engine torque, the starter/alternator controller is capable of consistently reducing the large torque fluctuations during the engine start. With this feedforward control action, the engine start control problem can be translated into a simpler disturbance rejection problem, given a prescribed speed trajectory. This facilitates a linearization of the complex nonlinear model to produce a control-oriented model on which feedback control can be designed. Using the control-oriented model thus developed, different linear control designs have been developed and compared. Further, a robustness study is conducted to evaluate the effect of noise and uncertainties common to such systems. The final results are tested on the original nonlinear truth model, demonstrating the capability of starting and stopping the engine with very limited torque and speed fluctuations.
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Li, Xiaobo, Jason Yap Chua, and Carl A. Moore. "Design and Control of a 3-D Wearable Cobot." In ASME 2005 International Mechanical Engineering Congress and Exposition. ASMEDC, 2005. http://dx.doi.org/10.1115/imece2005-81742.
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Cobots are specially designed robots that use continuously variable transmissions (CVTs) instead of traditional motor driven joints. With a cobot, the human experiences haptic effects through physical contact with the cobot’s end-effector. Safety is maintained through shared human-cobot control where the cobot velocity vector is split into 1) a speed that is proportional to the human’s input power and 2) a direction that is determined by the CVTs. We believe that cobots are an attractive choice for telerobotic master controllers because they are safe in contact with humans and are able to produce stable high quality virtual surfaces that can constrain the motion of the master to directions suitable for telerobotic task completion. This paper presents the design and control of a 3-D arm-wearable cobot for telerobotic operation. In our design a master cobot attaches to the user’s arm so that the user’s natural arm motions can be sensed and transmitted as the control signals for the slave robot. Furthermore, since the wearable arm is a cobot, virtual motion constraints may be safely placed on the master. Herein we describe the design of the wearable arm cobot and introduce a novel power assist mode, which makes it possible to control the cobot’s position relative inertia. The effectiveness of this control mode is investigated using simulations.
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Lobis, Yusuf Bachtiyar, Bhisma Murti, and Hanung Prasetya. "Influences of Peer Support Group and Psychosocio- Economic Determinants on Treatment Compliance in Hiv/Aids Patients in Sragen, Central Java." In The 7th International Conference on Public Health 2020. Masters Program in Public Health, Universitas Sebelas Maret, 2020. http://dx.doi.org/10.26911/the7thicph.02.59.
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Background: Adherence to treatment is important to reduce viral replication, improve clinical and immunological conditions, reduce the risk of developing ARV resistance, and reduce the risk of HIV transmission. Peer support is suspected to be one of the factors driving drug intake adherence in patients with chronic disease. This study aimed to examine the influences of peer support and psychosocio-economic determinants on treatment compliance in HIV/AIDS patients. Subjects and Method: This was a case control design study conducted in Sragen, Central Java, Indonesia. A sample of 200 people with HIV/AIDS (PLWH) was selected by fixed disease sampling. The dependent variable was treatment compliance. The independent variables were knowledge toward HIV/AIDS, perceived benefit, perceived belief, perceived threat, perceived susceptibility, perceived seriousness, perceived barrier, attitude, indirect experience, family support, and peer support. The data were obtained from medical record and questionnaire. The data were analyzed by a multiple logistic regression run on Stata 13. Results: Treatment compliance increased with strong peer support (b= 1.34; 95% CI= 0.31 to 2.38; p= 0.011), strong family support (b= 1.09; 95% CI= 0.16 to 2.02; p= 0.021), knowledge toward HIV/AIDS (b= 1.65; 95% CI= 0.67 to 2.64; p= 0.001), high perceived benefit (b= 1.23; 95% CI= 0.28 to 2.18; p= 0.011), perceived belief (b= 2.05; 95% CI= 0.98 to 3.12; p<0.001), and high perceived threat (b= 1.22; 95% CI= 0.30 to 2.13; p= 0.009). Treatment compliance decreased with negative attitude (b= -2.47; 95% CI= -3.58 to -1.37; p <0.001), low perceived susceptibility (b= -1.26; 95% CI= -2.24 to – 0.27; p= 0.012), low perceived seriousness (b= -1.11; 95% CI= -2.06 to -0.16; p=0.021), high perceived barrier (b= -1.76; 95% CI= -2.81 to -0.70; p= 0.001), and indirect experience (b= -1.10; 95% CI= -2.05 to -0.14; p= 0.024). Conclusion: Treatment compliance increases with strong peer support, strong family support, high knowledge toward HIV/AIDS, high perceived benefit, perceived belief, and high perceived threat. Treatment compliances decrease with negative attitude, low perceived susceptibility, low perceived seriousness, high perceived barrier, and indirect experience. Keywords: HIV/AIDS, treatment compliance, peer support, psychosocial economy Correspondence: Yusuf Bachtiyar Lobis. Masters Program in Public Health, Universitas Sebelas Maret. Jl. Ir. Sutami 36A, Surakarta 57126, Central Java. Email: bachtiyar03@gmail.com. Mobile: +628111388841. DOI: https://doi.org/10.26911/the7thicph.02.59
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Shomin, Michael, and Jonathan Fiene. "Teaching Manipulator Kinematics by Painting With Light." In ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/detc2011-47670.
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In this paper, we examine the creation and benefits of a new teaching platform to introduce and reinforce the key concepts of robotic manipulators in an introductory-level robotics course. This system combines a vintage PUMA 260 six-degree-of-freedom robotic arm with modern control circuitry and a Matlab API. The API operates as a servo controller for the robot, thereby allowing students to apply their knowledge of inverse kinematics to a real manipulator arm. To further motivate the exploration of manipulators, we have developed an open-ended project where students engage in the art of three-dimensional light painting. To facilitate this activity, a tricolor LED has been affixed to the end-effector of the robot. With a digital SLR camera, we take a long-exposure photograph as the robot is driven through a trajectory, effectively painting a picture with the end effector. We have also developed a method to quickly assemble pseudo-long-exposure photographs and videos using an inexpensive video camera. We believe this novel setup and project are an effective way to engage and motivate students to learn the underlying math and dynamics of robotic manipulators.