nils-herrmann/clean_scirepeval huggingface dataset:
Using a metric based tuning of Converted Measurement Kalman Filter (CMKF) for realistic target tracking scenario
Venue: 2019 Sixth Indian Control Conference (ICC)
Year: 2019

Converted measurement Kalman filter (CMKF) which is used in target tracking problems, converts polar measurements into Cartesian form to match Cartesian states. However, filter performance may degrade due to incorrect filter tuning of the biases and nonlinearities that arise due to the conversion. In this paper, the necessary converted measurement noise covariances have been derived in a 6 degree of freedom (6DOF) realistic target tracking scenario. In order to do so, the necessary frame conversions have also been accounted for to enable the estimation of the relative kinematics of the target. Thereafter, existing notions of robustness and sensitivity metrics have been suitably adapted to interpret the performance of CMKF in the 6DOF platform for various choices of tuning parameters and to predict the optimal tuning choice. The predicted performances and the optimal filter tuning choice have been validated in simulations in terms of the root mean squared errors (RMSE) for all measurements for 5000 Monte Carlo runs.
The Era of Digital Financial Innovation: Lessons from Economic History on Regulation
Year: 2020

While digital finance innovation has the potential to provide businesses and consumers with lower costs and a greater range of financial services, it has raised questions regarding the risks it poses to consumers, individual financial institutions, the financial system and the economy at large and how Canadian financial regulators should respond to those risks. This Commentary focuses on the major macro level risks that might arise, and sets out to answer three questions. What do we know from economic history about financial innovation in general and banking crises? What are some key areas arising from current and future digital financial innovation that regulators need to examine? And what are the implications for actions by Canadian regulators? Economic history gives us many examples of instances when financial innovations, rapid growth in credit supply and increased reliance on short term financing have led to financial instability and crises. Therefore, at a time of rapid changes in the financial sector, it is important that regulators pay close attention to what is happening and take appropriate action. After discussing key areas of concern for Canadian regulators, I recommend that they should: (i) Require the explainability of machine learning models used for lending decisions. As it is, artificial intelligence (AI) is being used in lending decisions at both regulated and largely unregulated institutions. If not properly examined by internal risk managers, it can lead to unsafe lending decisions. (ii) Take care not to rush into open banking regulations, for example regarding money moving apps, that could increase the likelihood of bank runs. (iii) Collect better and more timely data by type of financial institution on types of credit and short term financing. (iv) Extend the coverage of stress tests to examine stresses related to rapid new borrowing from non bank financial institutions, or shadow banks, that are not prudentially regulated. At the micro level, regulators will have to weigh closely the costs of new regulations against the benefits of financial innovations. At the macro level, however, the steps suggested in this Commentary should have little or no effect on the vast majority of digital financial innovations that are underway or contemplated in the near future. Therefore, there would be no real trade off between the increased stability coming from these actions and the increased competition, efficiency and range of financial services that should come from digital financial innovation.
La gestion des talents quatre questions a debattre au comite de direction
Year: 2016

Plus que jamais, la gestion des talents se maintient au sommet des preoccupations des dirigeants. En effet, dans un contexte d'affaires ou il n'y a pas de place pour l'erreur, il revient au comite de direction de chaque organisation de minimiser les risques d'echec en ce qui concerne l'attraction, la fidelisation et le developpement de ses talents prometteurs. Voici quatre questions qui meritent d'etre examinees attentivement pour fins de discussion.
ESP COURSE DESIGN: THE NEED ANALYSIS ON TOURISM DEPARTMENT IN INDONESIA VOCATIONAL HIGH SCHOOLS
Year: 2020

Centered on the 2013 Curriculum (Indonesia's national curriculum) English subject matter is equated to the high school standard. Both high school and vocational school students receive the same English content, while English is to be differentiated for special purposes for high school and vocational high school students. It is difficult to find an English textbook in a vocational school which fits into the department of the student. Additionally, there is often not enough time for teachers to develop English materials for vocational students. This study aims to explore the content that should be included in SMKN 1 Pangsid Kabupaten Sidenreng Rappang to design English language materials based on needs analysis in the Tourism Program and to find out the response of teachers to the development of English material in the Tourism Programme. Fundamental analysis uses Qualitative Descriptive, and the findings are described in terms. The study results indicate that the content to be included in the English language material in the SMKN 1 Pangsid Kabupaten Sidenreng Rappang tourism program is speaking and pronunciation for language skills and components; media videos and images; and asking questions about teaching techniques. Creation of English language materials consists of several speaking practice presentations, many videos to practice listening, speaking and reading, reading sections and documents, and some information that the Tourism Program learners need to know.
Distributed Reinforcement Learning for NOMA Enabled Mobile Edge Computing
Venue: 2020 IEEE International Conference on Communications Workshops (ICC Workshops)
Year: 2020

A novel non orthogonal multiple access (NOMA) enabled cache aided mobile edge computing (MEC) framework is proposed, for minimizing the sum energy consumption. The NOMA strategy enables mobile users to offload computation tasks to the access point (AP) simultaneously, which improves the spectrum efficiency. In this article, the considered resource allocation problem is formulated as a long term reward maximization problem that involves a joint optimization of task offloading decision, computation resource allocation, and caching decision. To tackle this nontrivial problem, a single agent Q learning (SAQ learning) algorithm is invoked to learn a long term resource allocation strategy from historical experience. Moreover, a Bayesian learning automata (BLA) based multi agent Q learning (MAQ learning) algorithm is proposed for task offloading decisions. More specifically, a BLA based action select scheme is proposed for the agents in MAQ learning to select the optimal actions in every state. The proposed BLA based action selection scheme is instantaneously self correcting, consequently, if the probabilities of two computing models (i.e. local computing and offloading computing) are not equal, the optimal action unveils eventually. Extensive simulations demonstrate that: 1) The proposed cache aided NOMA MEC framework significantly outperforms the other representative benchmark schemes under various network setups. 2) The effectiveness of the proposed BAL MAQ learning algorithm is confirmed from the comparison with the results of conventional reinforcement learning algorithms.
Doing What We Can with What We've Got: Reflections on PAR and the ECR Experience
Venue: Planning Theory Practice
Year: 2019

The label, Participatory Action Research (PAR) seems to be a good one, describing research oriented towards making change in which the interested parties actively participate. In identifying key principles or characteristics, proponents begin to tell us more about what drives it: a collective commitment to participation and democracy at all stages of the research process, from identifying issues to finding useful solutions (McIntyre, 2008; Reason Bradbury, 2008) This situates PAR as a self conscious reaction against 'traditional' and particularly positivistic approaches to social scientific research whereby 'neutral' researchers are in control of identifying research questions, extracting data from participants and deciding what it means and points towards its ethical and political co ordinates, as both critique and response to inequitable balances of power and resource. As Saija (2014) has made clear in this journal, this is not only political but also ideological, a commitment to engaging in democracy as process and working towards social change. It is hard to find a route to PAR within planning, then, without understanding it to some degree as a turn away from planning's problematic modernist legacy. We are implicated by association with a tradition that planned for people, that gave perceived material improvement with one hand whilst disenfranchising with the other, undoing community cohesion and attachments to place that had developed in some cases over many generations. From this starting point PAR can seem to represent a new moral benchmark, affirming our commitment to social justice and engaging participants from the start of projects in identifying, investigating and finding solutions to problems (McIntyre, 2008) As a way of enacting the laudable values that are still central to the planning project in collaboration with impacted people, we might even characterise this as an attempted return to planning's roots as a social movement. This ethical drive can lead to a temptation, however, to rely heavily on the distinction between good or genuine PAR and PAR that fails to hit the mark. Whilst thinking about what makes good PAR has to be central to reflective practice, it is also the case that any attempt to enact it will end up being, in some sense, an exercise in failure; or perhaps more constructively, in learning from failure. In highlighting this aspect of PAR I hope to contribute constructively to ongoing debates within the discipline and this journal, particularly in bringing together Raynor's (2019) recent contribution and the Interface on learning from mistakes (Campbell, Forester, Sanyal, 2018) Raynor persuasively argues that Early Career Researchers (ECRs) face particular structural barriers and disproportionate challenges in conducting PAR. My aim is to shed a different light on these issues through offering a complementary perspective, based on my experience as a PhD student and an ECR. Alongside making a case for the worth of imperfect PAR, I look to problematise the notion of the
A mixed research based model for pre service science teachers' digital literacy
Year: 2018

This study constructs a science teaching belief system to examine pre service science teachers' scientific epistemological beliefs (SEBs) and conceptions of teaching and learning (COTL) The aim of the study was to investigate the structural relations among pre service science teachers' SEBs, COTL and digital literacy skills and to determine the reasons for these relations. First, quantitative research was conducted to examine the structural relations among the variables, using structural equation modeling analysis on the data gathered from 979 pre service science teachers. Next, qualitative research investigated the reasons for these relations. Thus, the study has a sequential explanatory research design. The findings of the study showed that pre service science teachers' SEBs affected their constructivist conceptions positively. On the other hand, their SEBs were related to their traditional conceptions negatively. In addition, pre service teachers' COTL contribute more positively to their digital literacy skills if they hold constructivist conceptions. The previous experiences of pre service science teachers were also found to affect their beliefs and digital literacy skills. The findings contribute to the educational literature by focusing on the relationships among pre service science teachers' SEBs, COLT and digital literacy, which is one of the most important 21st century skills, in the context of pre service science teachers' belief systems. Pre service science teachers' SEBs had an effect on their COTL.Pre service science teachers' COTL contribute more positively to their digital literacy if they hold constructivist COTL.Pre service science teachers' previous experiences impact their beliefs and digital literacy skills.Digital literacy can be more effectively supported if pre service science teachers' belief systems are considered.
An Optimal Rewiring Strategy for Reinforcement Social Learning in Cooperative Multiagent Systems
Venue: ArXiv
Year: 2018

Multiagent coordination in cooperative multiagent systems (MASs) has been widely studied in both fixed agent repeated interaction setting and the static social learning framework. However, two aspects of dynamics in real world multiagent scenarios are currently missing in existing works. First, the network topologies can be dynamic where agents may change their connections through rewiring during the course of interactions. Second, the game matrix between each pair of agents may not be static and usually not known as a prior. Both the network dynamic and game uncertainty increase the coordination difficulty among agents. In this paper, we consider a multiagent dynamic social learning environment in which each agent can choose to rewire potential partners and interact with randomly chosen neighbors in each round. We propose an optimal rewiring strategy for agents to select most beneficial peers to interact with for the purpose of maximizing the accumulated payoff in repeated interactions. We empirically demonstrate the effectiveness and robustness of our approach through comparing with benchmark strategies. The performance of three representative learning strategies under our social learning framework with our optimal rewiring is investigated as well.
A comprehensive evaluation of polygenic score methods across cohorts in psychiatric disorders
Venue: medRxiv
Year: 2020

Polygenic scores (PGSs) which assess the genetic risk of individuals for a disease, are calculated as a weighted count of risk alleles identified in genome wide association studies (GWASs) PGS methods differ in terms of which DNA variants are included in the score and the weights assigned to them. PGSs are evaluated in independent target samples of individuals with known disease status. Evaluation of new PGS methods are made using simulated data or single target cohort, however, in real data sets there can be heterogeneity between target sample cohorts, which could reflect a number of real or artefactual factors. The Psychiatric Genomics Consortium working groups for schizophrenia (SCZ) and major depressive disorder (MDD) bring together many independently collected case control cohorts for GWAS meta analysis. These resources are used here in repeated application of leave one cohort out GWAS analyses, generating robust conclusions for PGS prediction applied across multiple target (left out) cohorts. Eight PGS methods (P+T, SBLUP, LDpred Inf, LDpred funct, LDpred, PRS CS, PRS CS auto, SBayesR) are compared. We found that SBayesR had the highest prediction evaluation statistics in most comparisons. For SCZ across 30 target cohorts, the SBayesR PGS achieved a mean area under the receiver operator characteristic curve (AUC) of 0.733, and explained 9.9% of variance on the liability scale. For MDD across 26 target cohorts, the AUC and variance explained were 0.601 and 4.0% respectively. The variance explained by the SBayesR PGS was 46% and 43% higher for SCZ and MDD, respectively, compared to the basic p value thresholding P+T method.
Interactive and interpretable machine learning models for human machine collaboration
Year: 2015

I envision a system that enables successful collaborations between humans and machine learning models by harnessing the relative strength to accomplish what neither can do alone. Machine learning techniques and humans have skills that complement each other machine learning techniques are good at computation on data at the lowest level of granularity, whereas people are better at abstracting knowledge from their experience, and transferring the knowledge across domains. The goal of this thesis is to develop a framework for human in the loop machine learning that enables people to interact effectively with machine learning models to make better decisions, without requiring in depth knowledge about machine learning techniques. Many of us interact with machine learning systems everyday. Systems that mine data for product recommendations, for example, are ubiquitous. However these systems compute their output without end user involvement, and there are typically no life or death consequences in the case the machine learning result is not acceptable to the user. In contrast, domains where decisions can have serious consequences (e.g. emergency response panning, medical decision making) require the incorporation of human experts' domain knowledge. These systems also must be transparent to earn experts' trust and be adopted in their workflow. The challenge addressed in this thesis is that traditional machine learning systems are not designed to extract domain experts' knowledge from natural workflow, or to provide pathways for the human domain expert to directly interact with the algorithm to interject their knowledge or to better understand the system output. For machine learning systems to make a real world impact in these important domains, these systems must be able to communicate with highly skilled human experts to leverage their judgment and expertise, and share useful information or patterns from the data. In this thesis, I bridge this gap by building human in the loop machine learning models and systems that compute and communicate machine learning results in ways that are compatible with the human decision making process, and that can readily incorporate human experts' domain knowledge. I start by building a machine learning model that infers human teams' planning decisions from the structured form of natural language of team meetings. I show that the model can infer a human teams' final plan with 86% accuracy
Reliable assessment of liver function using LiMAx.
Venue: The Journal of surgical research
Year: 2015

(13)C liver function breath tests can facilitate the assessment of hepatic function in vivo and may help surgeons to identify candidates for safe liver surgery. However, their acceptance into clinical practice is dependent on evaluation of technical efficacy and repeatability. The aims of this study were to evaluate the within subject repeatability of the LiMAx (maximum liver function capacity) test in healthy individuals and in surgical patients to determine liver function in the perioperative workup.  The LiMAx test, which is based on intravenous injection of (13)C methacetin at a dosage of 2 mg/kg body weight was performed in eighty six healthy subjects to determine a reference range. Twenty four subjects underwent repeat LiMAx testing the following day to assess within subject repeatability. Twenty one patients undergoing elective extra abdominal surgery under general anesthesia (GA group) received pre and post operative examinations.  The normal range of LiMAx was found to be 430 86 mg/kg/h and revealed a one sided cut off value of 315 mg/kg/h. The intraclass correlation coefficient of the repeat LiMAx tests was 0.85 (95% confidence interval 0.69 0.93) in the control group and 0.81 (95% confidence interval 0.60 0.92) in the group of patients with GA.  The LiMAx test shows excellent reproducibility in subjects with normal liver function. GA has no effect on test results.
Rigorous results, cross model justification, and the transfer of empirical warrant: the case of many body models in physics
Venue: Synthese
Year: 2008

This paper argues that a successful philosophical analysis of models and simulations must accommodate an account of mathematically rigorous results. Such rigorous results may be thought of as genuinely model specific contributions, which can neither be deduced from fundamental theory nor inferred from empirical data. Rigorous results provide new indirect ways of assessing the success of models and simulations and are crucial to understanding the connections between different models. This is most obvious in cases where rigorous results map different models on to one another. Not only does this put constraints on the extent to which performance in specific empirical contexts may be regarded as the main touchstone of success in scientific modelling, it also allows for the transfer of warrant across different models. Mathematically rigorous results can thus come to be seen as not only strengthening the cohesion between scientific strategies of modelling and simulation, but also as offering new ways of indirect confirmation.
Comparison of the Agricultural Cooperative Development in China and Vietnam Since De Collectivization
Year: 2012

China and Vietnam embarked on a transition process in the late 1970s and early 1980s, respectively. Collective farming was given a up and family farms were re established. At that stage, farmers were in urgent need of adjusted links to the upstream and downstream sectors. While the transition process went up in both countries rather similarly, it differed with respect to agricultural organizations. In China a "trial and error" process could be observed after the dissolution of the collective farms, whereas the Vietnamese government was eager to transform as many collective farms as possible into agricultural service cooperatives. Cooperation among farmers had to be organised informally in China, while in Vietnam agricultural cooperatives could continue operating, but under different rules. By 1997 the cooperative law became effective in Vietnam. It took another ten years to implement a similar law in China. In both countries, agricultural cooperatives expanded rapidly. In 2010, about ten percent of farm households in China and about 20 percent in Vietnam have become cooperative member. In both countries, there had been heavy government support and interference. However, this top down approach would have led to nothing, if there had not been a strong bottom up need by the farmers. In this way, cooperative development in both countries is unique in comparison to other transition economies as farmers are quite confident in making the best use out of "their" cooperatives.