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"abstract": "Ramachandran Plots are an important tool for researchers in bio-chemistry to examine the stability of a molecule. In these plots, dihedral (torsion) angles of the protein's backbone are visualized ona plane, where different areas are known to be stable configurations. Unfortunately, the underlying atom positions are affected by uncer-tainty, which is usually captured and expressed using the b-value. For classic Ramachandran Plots, this uncertainty is not propagatedwhen computing the dihedral angles and neglected when visualizinga Ramachandran Plot. To solve this problem, this paper presentsan extended version of the Ramachandran Plot, which allows tocommunicate the uncertainty of atom positions along the compu-tation of dihedral angles and an intuitive visualization. We showthe effectiveness of the presented approach by examining differentRamachandran Plots for molecules and show how the inclusion ofuncertainty helps biochemistry researchers to determine the stabilityof a protein with higher accuracy.",
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"content": "Ramachandran Plots are an important tool for researchers in bio-chemistry to examine the stability of a molecule. In these plots, dihedral (torsion) angles of the protein's backbone are visualized ona plane, where different areas are known to be stable configurations. Unfortunately, the underlying atom positions are affected by uncer-tainty, which is usually captured and expressed using the b-value. For classic Ramachandran Plots, this uncertainty is not propagatedwhen computing the dihedral angles and neglected when visualizinga Ramachandran Plot. To solve this problem, this paper presentsan extended version of the Ramachandran Plot, which allows tocommunicate the uncertainty of atom positions along the compu-tation of dihedral angles and an intuitive visualization. We showthe effectiveness of the presented approach by examining differentRamachandran Plots for molecules and show how the inclusion ofuncertainty helps biochemistry researchers to determine the stabilityof a protein with higher accuracy.",
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"abstract": "The focus in deep learning research has been mostly to push the limits of prediction accuracy. However, this was often achieved at the cost of increased complexity, raising concerns about the interpretability and the reliability of deep networks. Recently, an increasing attention has been given to untangling the complexity of deep networks and quantifying their uncertainty for different computer vision tasks. Differently, the task of depth completion has not received enough attention despite the inherent noisy nature of depth sensors. In this work, we thus focus on modeling the uncertainty of depth data in depth completion starting from the sparse noisy input all the way to the final prediction. We propose a novel approach to identify disturbed measurements in the input by learning an input confidence estimator in a self-supervised manner based on the normalized convolutional neural networks (NCNNs). Further, we propose a probabilistic version of NCNNs that produces a statistically meaningful uncertainty measure for the final prediction. When we evaluate our approach on the KITTI dataset for depth completion, we outperform all the existing Bayesian Deep Learning approaches in terms of prediction accuracy, quality of the uncertainty measure, and the computational efficiency. Moreover, our small network with 670k parameters performs on-par with conventional approaches with millions of parameters. These results give strong evidence that separating the network into parallel uncertainty and prediction streams leads to state-of-the-art performance with accurate uncertainty estimates.",
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"abstract": "Uncertainty is the only certainty there is. Modeling data uncertainty is essential for regression, especially in unconstrained settings. Traditionally the direct regression formulation is considered and the uncertainty is modeled by modifying the output space to a certain family of probabilistic distributions. On the other hand, classification based regression and ranking based solutions are more popular in practice while the direct regression methods suffer from the limited performance. How to model the uncertainty within the present-day technologies for regression remains an open issue. In this paper, we propose to learn probabilistic ordinal embeddings which represent each data as a multivariate Gaussian distribution rather than a deterministic point in the latent space. An ordinal distribution constraint is proposed to exploit the ordinal nature of regression. Our probabilistic ordinal embeddings can be integrated into popular regression approaches and empower them with the ability of uncertainty estimation. Experimental results show that our approach achieves competitive performance. Code is available at https://github.com/Li-Wanhua/POEs.",
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"content": "Uncertainty is the only certainty there is. Modeling data uncertainty is essential for regression, especially in unconstrained settings. Traditionally the direct regression formulation is considered and the uncertainty is modeled by modifying the output space to a certain family of probabilistic distributions. On the other hand, classification based regression and ranking based solutions are more popular in practice while the direct regression methods suffer from the limited performance. How to model the uncertainty within the present-day technologies for regression remains an open issue. In this paper, we propose to learn probabilistic ordinal embeddings which represent each data as a multivariate Gaussian distribution rather than a deterministic point in the latent space. An ordinal distribution constraint is proposed to exploit the ordinal nature of regression. Our probabilistic ordinal embeddings can be integrated into popular regression approaches and empower them with the ability of uncertainty estimation. Experimental results show that our approach achieves competitive performance. Code is available at https://github.com/Li-Wanhua/POEs.",
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"abstract": "The recent launch of Google Wallet has brought the issue of technology solutions in mobile payments (m-payments) to the forefront. In deciding whether and when to adopt m-payments, senior managers in banks are concerned about uncertainties regarding future market conditions, technology standards, and consumer and merchant responses, especially their willingness to adopt. This study applies economic theory and modeling for decision-making under uncertainty to bank investments in m-payment systems technology. We assess the projected benefits and costs of investment as a continuous-time stochastic process to determine optimal investment timing. We find that the value of waiting to adopt jumps when the related business environment experiences relevant shocks. Also, when the rate of benefit flows, the time horizon for decision-making, and the time value of money change, the recommended investment timing and optimal investment value will change too. We also consider how network effects influence decision-making for this IT investment context.",
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"doi": "10.1109/ICCIS.2013.174",
"title": "Economic Evaluation of EOR Project Based on Options Differential Equation Method",
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"abstract": "China began to research the tertiary oil recovery process from the 1980s. This technology is very mature in the current, but the economic benefits for the EOR project evaluation studies are relatively less and simple, moreover, the evaluation method is single, almost all enterprises have chosen to use net present value method. But net present value method ignores the flexibility which is managed by the decision-makers under uncertainty, not suitable for oil field development investment project evaluation. Real option valuation and strategic decision-making are an important way of thinking, often used in the evaluation of oil exploration, but for oil and gas production, dynamic process of evaluation studies are rarely involved. As the EOR project has the option characteristics, this article will introduce the idea of real options to the EOR project and try to establish the differential equation model of the EOR project evaluation. Differential equations are used for tertiary oil recovery project to analyze the option value.",
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"content": "China began to research the tertiary oil recovery process from the 1980s. This technology is very mature in the current, but the economic benefits for the EOR project evaluation studies are relatively less and simple, moreover, the evaluation method is single, almost all enterprises have chosen to use net present value method. But net present value method ignores the flexibility which is managed by the decision-makers under uncertainty, not suitable for oil field development investment project evaluation. Real option valuation and strategic decision-making are an important way of thinking, often used in the evaluation of oil exploration, but for oil and gas production, dynamic process of evaluation studies are rarely involved. As the EOR project has the option characteristics, this article will introduce the idea of real options to the EOR project and try to establish the differential equation model of the EOR project evaluation. Differential equations are used for tertiary oil recovery project to analyze the option value.",
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"abstract": "A shift towards self-managed pension investments has allowed greater transparency, flexibility and control in the way individuals interact with their financial wealth. In contrast to traditional wealth management practices that rely on explicit assessments of individual risk aversion, platform-based investment management services can provide concise metrics that define individual risk aversion, but are computationally-intensive. Using a complete dataset obtained from the interaction of investors with investment management platforms, we provide a detailed insight into risk aversion by age, gender and reaction to investment performance history. We use a MapReduce model to efficiently gauge risk aversion levels in real-time to optimize individual glide paths and investment styles. The use of inferred assessments of risk aversion based on actual investor behavior is undermining the inefficient cohort-based approach to investment management. We anticipate they will eventually replace the need for subjective aversion assessments conducted by financial advisors.",
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"content": "A shift towards self-managed pension investments has allowed greater transparency, flexibility and control in the way individuals interact with their financial wealth. In contrast to traditional wealth management practices that rely on explicit assessments of individual risk aversion, platform-based investment management services can provide concise metrics that define individual risk aversion, but are computationally-intensive. Using a complete dataset obtained from the interaction of investors with investment management platforms, we provide a detailed insight into risk aversion by age, gender and reaction to investment performance history. We use a MapReduce model to efficiently gauge risk aversion levels in real-time to optimize individual glide paths and investment styles. The use of inferred assessments of risk aversion based on actual investor behavior is undermining the inefficient cohort-based approach to investment management. We anticipate they will eventually replace the need for subjective aversion assessments conducted by financial advisors.",
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"abstract": "Using a psychological approach toward designing a Multi-Criteria Decision Support Systems (MCDSS), three prominent design features -- risk profile, information horizon, and prospect format -- are embedded in a MCDSS to help users overcome a tendency to build overly conservative investment portfolios. Consistent with myopic loss aversion theory, users exhibit a decreased willingness to take calculated risks when a MCDSS presents risk profiles with more variation and larger probabilities and magnitudes of losses. Such risk profiles prove particularly problematic when extended information horizons (e.g., 10 years) prevail. Regardless of risk profile, a MCDSS can activate heuristic-based decision processes by presenting multi-trial prospects in a manner that overwhelms cognitive capacity. Implications for theory and practice are discussed.",
"abstracts": [
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"content": "Using a psychological approach toward designing a Multi-Criteria Decision Support Systems (MCDSS), three prominent design features -- risk profile, information horizon, and prospect format -- are embedded in a MCDSS to help users overcome a tendency to build overly conservative investment portfolios. Consistent with myopic loss aversion theory, users exhibit a decreased willingness to take calculated risks when a MCDSS presents risk profiles with more variation and larger probabilities and magnitudes of losses. Such risk profiles prove particularly problematic when extended information horizons (e.g., 10 years) prevail. Regardless of risk profile, a MCDSS can activate heuristic-based decision processes by presenting multi-trial prospects in a manner that overwhelms cognitive capacity. Implications for theory and practice are discussed.",
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"Portfolios",
"Retirement",
"Psychology",
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"abstracts": [
{
"abstractType": "Regular",
"content": "In this paper, we present a model in which the investment in software countermeasure system is at the same time uncertain of costs and benefits from maintenance system and diminish cyber attacks under jump-diffusion process, and needs investment time using the real options approach. The software security depends upon the time it takes to receive benefiting from the system once the decision to invest has been taken. The model account for uncertainty both in the unexpected events security defect and benefits from diminish attacking damage associated with the investment opportunity. Unexpected events such as new security threat are included into the models as Poisson jump processes. The practical significance of the paper is the application of the model to approximate the continuous time the value security investment, resulting in an easy to use decision aid for managers.",
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"normalizedAbstract": "In this paper, we present a model in which the investment in software countermeasure system is at the same time uncertain of costs and benefits from maintenance system and diminish cyber attacks under jump-diffusion process, and needs investment time using the real options approach. The software security depends upon the time it takes to receive benefiting from the system once the decision to invest has been taken. The model account for uncertainty both in the unexpected events security defect and benefits from diminish attacking damage associated with the investment opportunity. Unexpected events such as new security threat are included into the models as Poisson jump processes. The practical significance of the paper is the application of the model to approximate the continuous time the value security investment, resulting in an easy to use decision aid for managers.",
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"abstract": "Online retirement planning systems are intended to help individual investors accumulate sufficient savings to support comfortable retirement lifestyles. Although it would seem intuitive that decision makers would choose investment alternatives that provide the highest payoffs over time, individuals tend to construct overly conservative portfolios that yield relatively meager returns. In this study, we explore whether a Web-based decision support system (DSS) that offers advice can enhance decision making by increasing investors' willingness to take calculated risks. Because women tend to be more risk averse when considering financial matters and interact with technologies differently than men, such a DSS might prove especially useful for female investors. A field experiment using retirement plan participants demonstrates that building advice into a DSS helps investors overcome a tendency to hold conservative portfolios. Advice availability and gender interacted such that risk taking is lowest when the DSS fails to provide advice to female decision makers",
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{
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"content": "Online retirement planning systems are intended to help individual investors accumulate sufficient savings to support comfortable retirement lifestyles. Although it would seem intuitive that decision makers would choose investment alternatives that provide the highest payoffs over time, individuals tend to construct overly conservative portfolios that yield relatively meager returns. In this study, we explore whether a Web-based decision support system (DSS) that offers advice can enhance decision making by increasing investors' willingness to take calculated risks. Because women tend to be more risk averse when considering financial matters and interact with technologies differently than men, such a DSS might prove especially useful for female investors. A field experiment using retirement plan participants demonstrates that building advice into a DSS helps investors overcome a tendency to hold conservative portfolios. Advice availability and gender interacted such that risk taking is lowest when the DSS fails to provide advice to female decision makers",
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"affiliation": "University of Montana",
"fullName": "Clayton Arlen Looney",
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"abstract": "Intelligent agents operate in an environment that can be mostly not dynamic. This requires learning by trial and error in order to know better the environment and reach their goals. They also need cooperation among themselves. We use reinforcement learning and game theory techniques to discuss how intelligent agents learn and cooperate. As known, one of the properties of agents is that they are social. They must therefore be cooperative in the social environment where they are. This is possible by learning the environment facts by doing, sharing instantaneous information and learned knowledge. The cooperative agents will perform better than independent agents. What is the advantage of such cooperation? As an example, in this paper we shall especially show how cooperative trading agents can maximize their profits due to a good coordination by playing Nash equilibrium to ensure that each agent chooses the best strategy which gives a good payoff.",
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"content": "Intelligent agents operate in an environment that can be mostly not dynamic. This requires learning by trial and error in order to know better the environment and reach their goals. They also need cooperation among themselves. We use reinforcement learning and game theory techniques to discuss how intelligent agents learn and cooperate. As known, one of the properties of agents is that they are social. They must therefore be cooperative in the social environment where they are. This is possible by learning the environment facts by doing, sharing instantaneous information and learned knowledge. The cooperative agents will perform better than independent agents. What is the advantage of such cooperation? As an example, in this paper we shall especially show how cooperative trading agents can maximize their profits due to a good coordination by playing Nash equilibrium to ensure that each agent chooses the best strategy which gives a good payoff.",
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"fno": "3473a795",
"keywords": [
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"Nash Equilibrium"
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"affiliation": null,
"fullName": "Lasheng Yu",
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{
"affiliation": null,
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"title": "An Analysis of Manufacturers' R&D Decision-Making in Defense Procurement with Incomplete Information",
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"abstract": "This paper is intended to research the manufacturers’ decision-making for R&D investment in defense procurement with incomplete information. On the basis of constructing the model of R&D investment scale adjustment of defense procurement, it explores the equilibrium of manufacturers’ R&D investment decision-making in defense procurement on condition that the monopolistic contract valuation of manufacturers is incomplete information. It comes to the conclusion that: under certain conditions, manufacturers’ investment equilibrium of R&D projects is identical to the government expectation. However, if the monopolistic contract valuation of manufacturers is incomplete information, the investment equilibrium may deviate from the government expectation. And it’s even possible that manufacturers would retreat form the contest, which will severely influence the performance of government’s reimbursement policy. Therefore, in the practice of defense procurement R&D, the government must ensure that predicting the future demand accurately and adopting a definite objective of procurement in order to keep manufacturers’ anticipation about the monopolistic contact being consistent with it desired.",
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"content": "This paper is intended to research the manufacturers’ decision-making for R&D investment in defense procurement with incomplete information. On the basis of constructing the model of R&D investment scale adjustment of defense procurement, it explores the equilibrium of manufacturers’ R&D investment decision-making in defense procurement on condition that the monopolistic contract valuation of manufacturers is incomplete information. It comes to the conclusion that: under certain conditions, manufacturers’ investment equilibrium of R&D projects is identical to the government expectation. However, if the monopolistic contract valuation of manufacturers is incomplete information, the investment equilibrium may deviate from the government expectation. And it’s even possible that manufacturers would retreat form the contest, which will severely influence the performance of government’s reimbursement policy. Therefore, in the practice of defense procurement R&D, the government must ensure that predicting the future demand accurately and adopting a definite objective of procurement in order to keep manufacturers’ anticipation about the monopolistic contact being consistent with it desired.",
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"fullName": "Tang Yifang",
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"fullName": "Ji Bingan",
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"fullName": "Luo Yunfeng",
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"doi": "10.1109/ICTAI.2012.50",
"title": "Incorporating Fairness into Infinitely Repeated Games with Conflicting Interests for Conflicts Elimination",
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"abstract": "In many multi-agent applications, game theory can serve as a useful tool to model these multi-agent scenarios and analyse the strategic interactions among agents. Fairness is an important goal to consider in a variety of multi-agent applications such as resource allocation or job scheduling problems, but it is not taken into consideration in traditional game theory. However, in many cases the solution concepts of pure strategy or mixed strategy Nash equilibria from traditional game theory can lead to unfair and inefficient outcomes. In this paper, we explicitly introduce the concept of fairness strategy in the context of infinitely repeated game inspired from fairness motive observed in human behaviors. We show that using fairness strategy, not only the agents can receive equal payoffs (achieving fairness) but also the sum of their payoffs is maximized (achieving efficiency) in the infinitely repeated games with conflicting interests. More importantly, we prove that this desirable pair of fairness strategies is in a new type of equilibrium - fairness strategy equilibrium, which thus provides an intuitive solution concept for the agents to make their decisions and coordinate with other agents or even humans.",
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"abstract": "The effect of quantization of prior probabilities in a collection of distributed Bayesian binary hypothesis testing problems over which the priors themselves vary is studied, with focus on conflicting agents. Conflict arises from differences in Bayes costs, even when all agents desire correct decisions and agree on the meaning of correct. In a setting with fusion of local binary decisions by majority rule, Nash equilibrium local decision strategies are found. Assuming that agents follow Nash equilibrium decision strategies, designing quantizers for prior probabilities becomes a strategic form game, we discuss its Nash equilibria. We also propose two different constrained quantizer design games, find Nash equilibrium quantizer designs, and compare performance. The system has deadweight loss: equilibrium decisions are not Pareto optimal.",
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"content": "The effect of quantization of prior probabilities in a collection of distributed Bayesian binary hypothesis testing problems over which the priors themselves vary is studied, with focus on conflicting agents. Conflict arises from differences in Bayes costs, even when all agents desire correct decisions and agree on the meaning of correct. In a setting with fusion of local binary decisions by majority rule, Nash equilibrium local decision strategies are found. Assuming that agents follow Nash equilibrium decision strategies, designing quantizers for prior probabilities becomes a strategic form game, we discuss its Nash equilibria. We also propose two different constrained quantizer design games, find Nash equilibrium quantizer designs, and compare performance. The system has deadweight loss: equilibrium decisions are not Pareto optimal.",
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"abstract": "Although the employment of graduates has been systematically surveyed in Finland for years, the gender equality aspect has been largely ignored. As early career experiences are likely to affect the retention of female engineers also in Finland, this study aims to understand better the different factors contributing to the vertical gender segregation in engineering careers in order to find ways to enhance women’s qualitative and quantitative employment. A statistical analysis of 3153 responses to a survey about degree and career satisfaction, career progress, factors contributing to employment, competences required in work, and development of competences during university studies revealed several differences in women’s and men’s early career experiences and perceptions. The results indicate that engineering education provides men with a better starting point for an engineering career. Hence, corrective actions are needed already during the engineering studies to smoothen the women’s rockier road in the later working life.",
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"abstract": "Previous researches have suggested that psychological capital has important effect on career success, but the mediation mechanism of psychological capital works is poorly understood. A chain mediation model was constructed in this study, exploring the influence of psychological capital, person-organization fit and career commitment on the career success of internet e-commerce staff. 308 participants were included, the results showed that the psychological capital has significant positive effect on career success. Psychological capital can indirectly affect career success through three path: through the mediating role of person-organization fit; through the mediating role of career commitment; through the chain mediating role of person-organization fit and career commitment. The results showed that the realization of the career success of the internet e-commerce staff should not only attach importance to separate individual factors, organizational factors, more should attach great importance to the interaction of these factors.",
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"abstract": "As a non-intellectual factor in the learning process, academic emotion plays an important role in academic achievement and academic motivation. Among the many ways to evaluate academic emotion, physiological evaluation can give timely feedback, which plays an important role in the organization of teaching strategies, especially in large-scale teaching. Based on the advantages of physiological evaluation, this paper selects empirical research papers on the application of physiological feedback technology in education from the past 10 years (2011–2021) to carry out a literature review. The methods were a combination of qualitative and supplementary description to analyze the content of the papers (e.g., research methods, applied disciplines, evaluation indicators, and equipment improvement). At present, the challenges faced by the application of physiological feedback technology of academic emotion in practical teaching situations include: (1) imperfection of the theoretical system, (2) portability of equipment, (3) and ethical problems from laboratory to classroom. Recommendations for the future of teaching with physiological feedback technology include using the environmental factors of virtual learning environment to regulate academic emotion.",
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"content": "As a non-intellectual factor in the learning process, academic emotion plays an important role in academic achievement and academic motivation. Among the many ways to evaluate academic emotion, physiological evaluation can give timely feedback, which plays an important role in the organization of teaching strategies, especially in large-scale teaching. Based on the advantages of physiological evaluation, this paper selects empirical research papers on the application of physiological feedback technology in education from the past 10 years (2011–2021) to carry out a literature review. The methods were a combination of qualitative and supplementary description to analyze the content of the papers (e.g., research methods, applied disciplines, evaluation indicators, and equipment improvement). At present, the challenges faced by the application of physiological feedback technology of academic emotion in practical teaching situations include: (1) imperfection of the theoretical system, (2) portability of equipment, (3) and ethical problems from laboratory to classroom. Recommendations for the future of teaching with physiological feedback technology include using the environmental factors of virtual learning environment to regulate academic emotion.",
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"normalizedAbstract": "As a non-intellectual factor in the learning process, academic emotion plays an important role in academic achievement and academic motivation. Among the many ways to evaluate academic emotion, physiological evaluation can give timely feedback, which plays an important role in the organization of teaching strategies, especially in large-scale teaching. Based on the advantages of physiological evaluation, this paper selects empirical research papers on the application of physiological feedback technology in education from the past 10 years (2011–2021) to carry out a literature review. The methods were a combination of qualitative and supplementary description to analyze the content of the papers (e.g., research methods, applied disciplines, evaluation indicators, and equipment improvement). At present, the challenges faced by the application of physiological feedback technology of academic emotion in practical teaching situations include: (1) imperfection of the theoretical system, (2) portability of equipment, (3) and ethical problems from laboratory to classroom. Recommendations for the future of teaching with physiological feedback technology include using the environmental factors of virtual learning environment to regulate academic emotion.",
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"affiliation": "School of Educational Technology, Northwest Normal University,Lanzhou,China",
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"doi": "10.1109/FIE56618.2022.9962393",
"title": "Analysis of Academic Databases for Literature Review in the Computer Science Education Field",
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"abstract": "Literature review is a fundamental part of a research process, and systematic protocols for this activity have been used for a long time, mainly in the field of health. Specifically in the Computer Science Education area, the use of systematic literature review has grown. One of the steps in a systematic literature review (SLR) is the selection of academic databases in which to search for articles. There are several databases with academic documents that may be relevant to SLR, for example: Google Scholar, which indexes different types of documents, such as articles, dissertations, theses, and others; Scopus and Web of Science are large databases that index articles from different conferences and journals. ACM Digital Library and IEEE Xplore are also important sources of information in the field of Computer Education. These tools have different characteristics, some charge a fee, others have only information about the title and authors and do not have access to the full article, others have advanced features, with many filters. In this context, this article presents the following research questions: RQ1) What metadata can be extracted automatically from the databases?; RQ2) What kind of visualization tools are available?; RQ3) Do the documents returned by the databases cover the research topic?; RQ4) Do the databases have papers from the main CSE venues?; and RQ5) How many databases are required to perform a literature review in CSE? To answer these questions we used five academic databases: Google Scholar, Scopus, Web of Science, ACM Digital Library, and IEEE xplore. Regarding the results, Scopus and Web of Science have the best visualization of the documents and a robust query engine, however those academic databases are not free. ACM Digital library, IEEE Xplore, Scopus and Web of Science allow the automatic download of the papers’ metadata (author, title, abstract, affiliation and others). Specifically in the field of Computer Science Education, the ACM Digital Library and the IEEE Xplore have important papers from conferences (SIGCSE and FIE) and journals (ACM Transaction on Education and IEEE Transaction on Education). In this full paper, the results will be presented to help researchers to choose the most appropriate academic databases based on their requirements and available options.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Literature review is a fundamental part of a research process, and systematic protocols for this activity have been used for a long time, mainly in the field of health. Specifically in the Computer Science Education area, the use of systematic literature review has grown. One of the steps in a systematic literature review (SLR) is the selection of academic databases in which to search for articles. There are several databases with academic documents that may be relevant to SLR, for example: Google Scholar, which indexes different types of documents, such as articles, dissertations, theses, and others; Scopus and Web of Science are large databases that index articles from different conferences and journals. ACM Digital Library and IEEE Xplore are also important sources of information in the field of Computer Education. These tools have different characteristics, some charge a fee, others have only information about the title and authors and do not have access to the full article, others have advanced features, with many filters. In this context, this article presents the following research questions: RQ1) What metadata can be extracted automatically from the databases?; RQ2) What kind of visualization tools are available?; RQ3) Do the documents returned by the databases cover the research topic?; RQ4) Do the databases have papers from the main CSE venues?; and RQ5) How many databases are required to perform a literature review in CSE? To answer these questions we used five academic databases: Google Scholar, Scopus, Web of Science, ACM Digital Library, and IEEE xplore. Regarding the results, Scopus and Web of Science have the best visualization of the documents and a robust query engine, however those academic databases are not free. ACM Digital library, IEEE Xplore, Scopus and Web of Science allow the automatic download of the papers’ metadata (author, title, abstract, affiliation and others). Specifically in the field of Computer Science Education, the ACM Digital Library and the IEEE Xplore have important papers from conferences (SIGCSE and FIE) and journals (ACM Transaction on Education and IEEE Transaction on Education). In this full paper, the results will be presented to help researchers to choose the most appropriate academic databases based on their requirements and available options.",
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"normalizedAbstract": "Literature review is a fundamental part of a research process, and systematic protocols for this activity have been used for a long time, mainly in the field of health. Specifically in the Computer Science Education area, the use of systematic literature review has grown. One of the steps in a systematic literature review (SLR) is the selection of academic databases in which to search for articles. There are several databases with academic documents that may be relevant to SLR, for example: Google Scholar, which indexes different types of documents, such as articles, dissertations, theses, and others; Scopus and Web of Science are large databases that index articles from different conferences and journals. ACM Digital Library and IEEE Xplore are also important sources of information in the field of Computer Education. These tools have different characteristics, some charge a fee, others have only information about the title and authors and do not have access to the full article, others have advanced features, with many filters. In this context, this article presents the following research questions: RQ1) What metadata can be extracted automatically from the databases?; RQ2) What kind of visualization tools are available?; RQ3) Do the documents returned by the databases cover the research topic?; RQ4) Do the databases have papers from the main CSE venues?; and RQ5) How many databases are required to perform a literature review in CSE? To answer these questions we used five academic databases: Google Scholar, Scopus, Web of Science, ACM Digital Library, and IEEE xplore. Regarding the results, Scopus and Web of Science have the best visualization of the documents and a robust query engine, however those academic databases are not free. ACM Digital library, IEEE Xplore, Scopus and Web of Science allow the automatic download of the papers’ metadata (author, title, abstract, affiliation and others). Specifically in the field of Computer Science Education, the ACM Digital Library and the IEEE Xplore have important papers from conferences (SIGCSE and FIE) and journals (ACM Transaction on Education and IEEE Transaction on Education). In this full paper, the results will be presented to help researchers to choose the most appropriate academic databases based on their requirements and available options.",
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"title": "Literature Review on Work-Based Learning",
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"abstract": "Work-based learning is a teaching and learning method which requires students to go through practical training. In work-based learning, also employers are responsible for teaching as well as evaluation of the students. Students learn theory at the university and apply these academic and technical skills at their working place.This full paper aims to provide a literature review on how work-based learning is organised and implemented in engineering curricula. It also aims to find out the possible factors which are influential in work-based learning and to get information on how to provide work-based learning more effectively. We followed the guidelines for systematic literature reviews by Kitchenham and Charters [1] and asked the following research questions: RQ1: What are the problems faced by faculty and universities in conducting work-based learning? RQ2: What is the student motivation to join work-based learning programmes? RQ3: How the companies are involved and how the universities are organising the training of the company's work-based mentors? RQ4: What is the main model of work-based learning in universities? RQ5: What are the benefits (real or perceived) of work-based learning?According to the selection criteria, 42 papers on work-based learning in engineering curricula published from 2008 to 2018, were selected for the final review and conclusions.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Work-based learning is a teaching and learning method which requires students to go through practical training. In work-based learning, also employers are responsible for teaching as well as evaluation of the students. Students learn theory at the university and apply these academic and technical skills at their working place.This full paper aims to provide a literature review on how work-based learning is organised and implemented in engineering curricula. It also aims to find out the possible factors which are influential in work-based learning and to get information on how to provide work-based learning more effectively. We followed the guidelines for systematic literature reviews by Kitchenham and Charters [1] and asked the following research questions: RQ1: What are the problems faced by faculty and universities in conducting work-based learning? RQ2: What is the student motivation to join work-based learning programmes? RQ3: How the companies are involved and how the universities are organising the training of the company's work-based mentors? RQ4: What is the main model of work-based learning in universities? RQ5: What are the benefits (real or perceived) of work-based learning?According to the selection criteria, 42 papers on work-based learning in engineering curricula published from 2008 to 2018, were selected for the final review and conclusions.",
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"normalizedAbstract": "Work-based learning is a teaching and learning method which requires students to go through practical training. In work-based learning, also employers are responsible for teaching as well as evaluation of the students. Students learn theory at the university and apply these academic and technical skills at their working place.This full paper aims to provide a literature review on how work-based learning is organised and implemented in engineering curricula. It also aims to find out the possible factors which are influential in work-based learning and to get information on how to provide work-based learning more effectively. We followed the guidelines for systematic literature reviews by Kitchenham and Charters [1] and asked the following research questions: RQ1: What are the problems faced by faculty and universities in conducting work-based learning? RQ2: What is the student motivation to join work-based learning programmes? RQ3: How the companies are involved and how the universities are organising the training of the company's work-based mentors? RQ4: What is the main model of work-based learning in universities? RQ5: What are the benefits (real or perceived) of work-based learning?According to the selection criteria, 42 papers on work-based learning in engineering curricula published from 2008 to 2018, were selected for the final review and conclusions.",
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"abstracts": [
{
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"content": "Diversity in Computer Science and Engineering (CSE) majors has been a challenge in the US. Women, Hispanic/Latinx, Black/African American, and Native American students are minorities in CSE majors. Most universities and organizations have worked on outreach activities to these underrepresented minorities (URM). In this context, this paper presents a systematic literature mapping on educational initiatives in higher education for retention of Hispanic/Latinx students in CSE majors reported in the last ten years (2009-2018). The methodology was based on a systematic literature review protocol using four academic databases: Scopus, Web of Science, ACM Digital Library and IEEE Xplore. We found 76 papers about educational initiatives in CSE majors to retain URM students that include Hispanic/Latinx students. We classify the papers to get relevant information about institutions, type of educational initiatives, main conferences, and present these findings in this paper.",
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"title": "\"You're all a bunch of fucking feminists:\" Addressing the perceived conflict between gender and professional identities using the Montreal Massacre",
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"abstract": "A case study of the Montreal Massacre was employed in a core engineering thermodynamics class, using two video news clips to spur discussion about the event and about the intersection of gender identity and feminist politics with the engineering profession. In the pilot test of our lesson plan, students discussed strategies for addressing overt and subtle sexism, negotiating questions of dress in the profession, the ways they use gendered behavior or gender distancing as strategies, work-life balance, competition and women's success as a threat. Such concerns are not typically included in professionalization aspects of engineering curricula, but their importance for both women and men is evident. We present our lesson plan and discussion outcomes, and address multiple contexts in which this case can be utilized to teach about gender and engineering",
"abstracts": [
{
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"content": "A case study of the Montreal Massacre was employed in a core engineering thermodynamics class, using two video news clips to spur discussion about the event and about the intersection of gender identity and feminist politics with the engineering profession. In the pilot test of our lesson plan, students discussed strategies for addressing overt and subtle sexism, negotiating questions of dress in the profession, the ways they use gendered behavior or gender distancing as strategies, work-life balance, competition and women's success as a threat. Such concerns are not typically included in professionalization aspects of engineering curricula, but their importance for both women and men is evident. We present our lesson plan and discussion outcomes, and address multiple contexts in which this case can be utilized to teach about gender and engineering",
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"affiliation": "Assistant Professor, Picker Engineering Program, Smith College, driley@email.smith.edu",
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"abstract": "There are numerous initiatives to improve diversity within the computer science field. However, women still disproportionately drop CS majors and earn less than one quarter of CS bachelor's degrees in the United States. The extent to which CS students-especially male students-are aware of this gender gap is an open question. This paper reports on a study to investigate that question. We analyzed 325 CS1 students' survey responses and found significant differences between women's and men's awareness of the CS gender gap. Men were significantly less aware of the gender gap than women, and men had significantly milder beliefs about whether women experienced adversity in CS and whether there should be targeted efforts to support women. Twenty students (10 women and 10 men) participated in follow-up interviews after the survey, where they discussed their experiences and perceptions of the computer science gender gap. Even among students who were aware of the gender gap, many had a superficial understanding of its cause, believing it to be due to women having less natural interest in CS. We argue that these findings are a call-to-action: university CS curricula need to include diversity, equity, and inclusion (DEI) training so that students have a more complete understanding of this complex issue, and so that these misconceptions do not continue to be perpetuated into the workplace.",
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"abstract": "Public speaking is an effective way to move, persuade, and inspire. While many guidelines have been presented to teach public speaking skills, they are often based on anecdotal evidence and not customizable. Exploring high-quality speeches such as TED Talks could provide insights to eliminate limitations in existing guidelines. This study aims to explore and identify narration strategies by conducting visual analysis into the textural and acoustic information in public speeches. We present SpeechLens, an interactive visual analytics system to explore large-scale speech dataset with multiple level-of-details. SpeechLens features a novel focus+context design to enable intuitive and smooth analysis. Case studies indicate the effectiveness and usefulness of our approach.",
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"affiliation": "Xi'an Jiaotong University",
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"abstract": "It is becoming increasingly important that support is provided for users who are dealing with complex information spaces. The need is driven by the growing number of domains where there is a requirement for users to understand, navigate and manipulate large sets of computer based data; by the increasing size and complexity of this information and by the pressures to use this information efficiently. The paradigmatic example is the World Wide Web, but other domains include software systems, information systems and concurrent engineering. One approach to providing this support is to provide sophisticated visualisation tools which lead the users to form an intuitive understanding of the structure and behaviour of their domain and which provide mechanisms which allow them to manipulate objects within their system. The paper describes such a tool and a number of visualisation techniques that it implements.",
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"title": "Analysing Dissenting Votes Through Electronic Justice From Online Posts to Streets: A Real Case",
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"abstract": "This paper brings us a vision of what dissenting votes mean in an eSociety, particularly linked to eJustice, and a real case in Spanish jurisdictional process. As soon as judicial decision has an increasing repercussion, our hyper-connected society and social networks on the Internet take a relevant influential role, giving a never before seen feedback to the Judiciary. Easy access to case law, jurisdictional texts and judicial decisions in electronic form are elements with great impact, surpassing traditional publicity. An interesting case of study related to electronic media, and particularly through social networks, has been the dissenting vote of the rape case called “The Wolfpack”, known as “La manada” in Spain, that has crossed the borders of electronic protests to the streets, with demonstrations and reactions against it, particularly from feminist movements. Our hypothesis is that dissenting vote as an eSociety conceptualization has an electronic-digital component whose easy diffusion through the Internet makes it different from the traditional concept. It changes from being an ordinary procedural mechanism within a restricted scope of decision, to opening a debate at citizenship level. It involves nuances on transparency in the digital society, and of course in the idea of Open Justice as part of Open Government initiatives. As a field experience and methodological system, we will use electronic justice ICT tools, such as web-based HJ of the Constitutional Court of Spain and others to explore these considerations analytically.",
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"content": "This paper brings us a vision of what dissenting votes mean in an eSociety, particularly linked to eJustice, and a real case in Spanish jurisdictional process. As soon as judicial decision has an increasing repercussion, our hyper-connected society and social networks on the Internet take a relevant influential role, giving a never before seen feedback to the Judiciary. Easy access to case law, jurisdictional texts and judicial decisions in electronic form are elements with great impact, surpassing traditional publicity. An interesting case of study related to electronic media, and particularly through social networks, has been the dissenting vote of the rape case called “The Wolfpack”, known as “La manada” in Spain, that has crossed the borders of electronic protests to the streets, with demonstrations and reactions against it, particularly from feminist movements. Our hypothesis is that dissenting vote as an eSociety conceptualization has an electronic-digital component whose easy diffusion through the Internet makes it different from the traditional concept. It changes from being an ordinary procedural mechanism within a restricted scope of decision, to opening a debate at citizenship level. It involves nuances on transparency in the digital society, and of course in the idea of Open Justice as part of Open Government initiatives. As a field experience and methodological system, we will use electronic justice ICT tools, such as web-based HJ of the Constitutional Court of Spain and others to explore these considerations analytically.",
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"abstract": "This paper presents the results of semester-long integration of situating social justice content and contextual topics in a computer science data structures course at a Historically Black College. Computer Science (CS) education practices often include many active learning pedagogies that encourage students to develop internalized constructs of the theoretical underpinnings of programming languages and environments of computing applications with less focus on the applied concepts that personalize new-found skills for students in the classroom [3]. The primary objective of this innovative pedagogical practice focuses on reframing technical concepts in a computer science data structures class. In this work we motivate students to develop programming assignments that are framed as an aspect of a technical solution within the lens of social justice applications in an inquiry-based learning pedagogy. We show that by scaffolding the socio-innovative practices with topical content, students can experience topical-based competencies in the context of addressing real-world problems that can prepare them for problem-solving skills that will follow them beyond graduation.",
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"abstract": "In the literature, many dimensionality reduction methods have been proposed and applied to recognition tasks, including handwritten digits recognition, character recognition and string recognition. However, it is usually difficult for the researchers to decide which method is the optimal choice for the problem at hand. In this paper, we empirically compare some supervised dimensionality reduction methods on handwritten digits recognition, English letter recognition and ancient Arabic sub word recognition, to evaluate their performance on the recognition tasks. These compared methods include traditional linear dimensionality reduction approach (linear discriminant analysis, LDA), locality-based manifold learning approach (marginal Fisher analysis, MFA) and relational learning approach (probabilistic relational principal component analysis, PRPCA). Experimental results and statistical tests show that locality-based manifold learning approach (MFA) generally performs well in terms of recognition accuracy, but with high computational complexity, traditional linear dimensionality reduction approach (LDA) is efficient, but not necessarily to deliver the best result, relational learning approach (PRPCA) is promising, and more efforts should be dedicated to this area.",
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"content": "In the literature, many dimensionality reduction methods have been proposed and applied to recognition tasks, including handwritten digits recognition, character recognition and string recognition. However, it is usually difficult for the researchers to decide which method is the optimal choice for the problem at hand. In this paper, we empirically compare some supervised dimensionality reduction methods on handwritten digits recognition, English letter recognition and ancient Arabic sub word recognition, to evaluate their performance on the recognition tasks. These compared methods include traditional linear dimensionality reduction approach (linear discriminant analysis, LDA), locality-based manifold learning approach (marginal Fisher analysis, MFA) and relational learning approach (probabilistic relational principal component analysis, PRPCA). Experimental results and statistical tests show that locality-based manifold learning approach (MFA) generally performs well in terms of recognition accuracy, but with high computational complexity, traditional linear dimensionality reduction approach (LDA) is efficient, but not necessarily to deliver the best result, relational learning approach (PRPCA) is promising, and more efforts should be dedicated to this area.",
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"abstract": "Recently, various dimensionality reduction approaches have been proposed as alternatives to PCA or LDA. These improved approaches do not rely on a linearity assumption, and are hence capable of discovering more complex embeddings within different regions of the data sets. Despite their success on artificial datasets, it is not straightforward to predict which technique is the most appropriate for a given real dataset. In this paper, we empirically evaluate recent techniques on two real audio use cases: musical instrument loops used in music production and sound effects used in sound editing. ISOMAP and t-SNE are being compared to PCA in a visualization problem, where we end up with a two-dimensional view. Various evaluation measures are used: classification performance, as well as trustworthiness/continuity assessing the preservation of neighborhoods. Although PCA and ISOMAP can yield good continuity performance even locally (samples in the original space remain close-by in the low-dimensional one), they fail to preserve the structure of the data well enough to ensure that distinct subgroups remain separate in the visualization. We show that t-SNE presents the best performance, and can even be beneficial as a pre-processing stage for improving classification when the amount of labeled data is low.",
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"abstract": "We consider importance sampling (IS) to increase the efficiency of Monte Carlo integration, especially for pricing exotic options where the random input is multivariate normal. When the importance function (the product of integrand and original density) is multimodal, determining a good IS density is a difficult task. We propose an automated importance sampling density selection procedure (AISDE). AISDE selects an IS density as a mixture of multivariate normal densities with modes at certain local maxima of the importance function. When the simulation input is multivariate normal, we use principal component analysis to obtain a reduced-dimension, approximate importance function, which allows efficient identification of a good IS density via AISDE in original problem dimensions over 100. We present Monte Carlo experimental results on randomly generated option-pricing problems (including path-dependent options), demonstrating large and consistent efficiency improvement.",
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"abstract": "Motion analysis in sequential images has many applications in both modern military and civilian environments. Motion determination based on frame difference is to determine the number, location and size of moving targets using the spatial clue. Density-based clustering algorithm DBSCAN is introduced into motion determination in this paper, which can discover clusters of arbitrary shape as well as to distinguish noise in spatial database, but it can only work well on data sets where cluster densities are similar. However, significant density difference usually occurs among different moving regions in frame difference images, and DBSCAN can not work well on them. This paper proposed a non-uniform sampling method to smooth the density difference among different moving regions, which makes it possible to obtain reasonable clustering results by DBSCAN. On the other hand, the sampling scheme can reduce the size of point data dramatically, which speeds up the clustering process for moving targets. Some experiments demonstrate the effectiveness of the proposed method.",
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"content": "Motion analysis in sequential images has many applications in both modern military and civilian environments. Motion determination based on frame difference is to determine the number, location and size of moving targets using the spatial clue. Density-based clustering algorithm DBSCAN is introduced into motion determination in this paper, which can discover clusters of arbitrary shape as well as to distinguish noise in spatial database, but it can only work well on data sets where cluster densities are similar. However, significant density difference usually occurs among different moving regions in frame difference images, and DBSCAN can not work well on them. This paper proposed a non-uniform sampling method to smooth the density difference among different moving regions, which makes it possible to obtain reasonable clustering results by DBSCAN. On the other hand, the sampling scheme can reduce the size of point data dramatically, which speeds up the clustering process for moving targets. Some experiments demonstrate the effectiveness of the proposed method.",
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"abstract": "A new method of \"farthest point strategy\" (FPS) for progressive image acquisition is presented. Its main advantage is in retaining its uniformity with the increased density, providing an efficient means for sparse image sampling and display. In contrast to previously presented stochastic approaches, the FPS guarantees the uniformity in a deterministic min-max sense. Within this uniformity criterion, the sampling points are irregularly spaced, exhibiting superior antialiasing properties. A straightforward modification of the FPS yields an image-dependent adaptive sampling scheme. An efficient, O(N log(N)), algorithm for both versions is introduced, and several applications of the FPS are discussed.",
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"content": "A new method of \"farthest point strategy\" (FPS) for progressive image acquisition is presented. Its main advantage is in retaining its uniformity with the increased density, providing an efficient means for sparse image sampling and display. In contrast to previously presented stochastic approaches, the FPS guarantees the uniformity in a deterministic min-max sense. Within this uniformity criterion, the sampling points are irregularly spaced, exhibiting superior antialiasing properties. A straightforward modification of the FPS yields an image-dependent adaptive sampling scheme. An efficient, O(N log(N)), algorithm for both versions is introduced, and several applications of the FPS are discussed.",
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"abstract": "The usefulness of technical drawings as well as scientific illustrations such as medical drawings of human anatomy essentially depends on the placement of labels that describe all relevant parts of the figure. In order to not spoil or clutter the figure with text, the labels are often placed around the figure and are associated by thin connecting lines to their features, respectively. This labeling technique is known as external label placement. In this paper we introduce a flexible and general approach for external label placement assuming a contour of the figure prescribing the possible positions of the labels. While much research on external label placement aims for fast labeling procedures for interactive systems, we focus on highest-quality illustrations. Based on interviews with domain experts and a semi-automatic analysis of 202 handmade anatomical drawings, we identify a set of 18 layout quality criteria, naturally not all of equal importance. We design a new geometric label placement algorithm that is based only on the most important criteria. Yet, other criteria can flexibly be included in the algorithm, either as hard constraints not to be violated or as soft constraints whose violation is penalized by a general cost function. We formally prove that our approach yields labelings that satisfy all hard constraints and have minimum overall cost. Introducing several speedup techniques, we further demonstrate how to deploy our approach in practice. In an experimental evaluation on real-world anatomical drawings we show that the resulting labelings are of high quality and can be produced in adequate time.",
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