scholarly journals Constant optimization and feature standardization in multiobjective genetic programming

2021 ◽  
Author(s):  
Peter Rockett
Keyword(s):  
Genetic Programming ◽  
Real World ◽  
Parameter Tuning ◽  
Evolutionary Search ◽  
Clear Trend ◽  
Test Error ◽  
Open Research ◽  
Research Questions ◽  
Test Errors ◽  
Lower Test

AbstractThis paper extends the numerical tuning of tree constants in genetic programming (GP) to the multiobjective domain. Using ten real-world benchmark regression datasets and employing Bayesian comparison procedures, we first consider the effects of feature standardization (without constant tuning) and conclude that standardization generally produces lower test errors, but, contrary to other recently published work, we find much less clear trend for tree sizes. In addition, we consider the effects of constant tuning – with and without feature standardization – and observe that (1) constant tuning invariably improves test error, and (2) usually decreases tree size. Combined with standardization, constant tuning produces the best test error results; tree sizes, however, are increased. We also examine the effects of applying constant tuning only once at the end a conventional GP run which turns out to be surprisingly promising. Finally, we consider the merits of using numerical procedures to tune tree constants and observe that for around half the datasets evolutionary search alone is superior whereas for the remaining half, parameter tuning is superior. We identify a number of open research questions that arise from this work.

scholarly journals Users roles identification on online crowdsourced Q&A platforms and encyclopedias: a survey

2021 ◽  
Author(s):  
Akrati Saxena ◽  
Harita Reddy
Keyword(s):  
Network Analysis ◽  
Knowledge Sharing ◽  
Informal Learning ◽  
Social Roles ◽  
Online Discussion ◽  
State Of The Art ◽  
Temporal Analysis ◽  
The State ◽  
Open Research ◽  
Research Questions

AbstractOnline informal learning and knowledge-sharing platforms, such as Stack Exchange, Reddit, and Wikipedia have been a great source of learning. Millions of people access these websites to ask questions, answer the questions, view answers, or check facts. However, one interesting question that has always attracted the researchers is if all the users share equally on these portals, and if not then how the contribution varies across users, and how it is distributed? Do different users focus on different kinds of activities and play specific roles? In this work, we present a survey of users’ social roles that have been identified on online discussion and Q&A platforms including Usenet newsgroups, Reddit, Stack Exchange, and MOOC forums, as well as on crowdsourced encyclopedias, such as Wikipedia, and Baidu Baike, where users interact with each other through talk pages. We discuss the state of the art on capturing the variety of users roles through different methods including the construction of user network, analysis of content posted by users, temporal analysis of user activity, posting frequency, and so on. We also discuss the available datasets and APIs to collect the data from these platforms for further research. The survey is concluded with open research questions.

Influence of Task and Situational Variables on the Applicability of Vigilance Data to Physical Security

1980 ◽  
Vol 24 (1) ◽  
pp. 606-607
Author(s):  
Ben B. Morgan
Keyword(s):  
Real World ◽  
Human Performance ◽  
Clear Trend ◽  
General Belief ◽  
Situational Variables ◽  
Performance Requirements ◽  
Limited Applicability ◽  
Machine Systems ◽  
Inspection Tasks ◽  
The Many

Vigilance is one of the most thoroughly researched areas of human performance. Volumes have been written concerning vigilance performance in both laboratory and real-world settings, and there is a clear trend in the literature toward an increasing emphasis on the study of operational task behavior under environmental conditions that are common to real world jobs. Although a great deal of this research has been designed to test various aspects of the many theories of vigilance, there is a general belief that vigilance research is relevant and applicable to the performances required in real-world monitoring and inspection tasks. Indeed, many of the reported studies are justified on the basis of their apparent relevance to vigilance requirements in modern man-machine systems, industrial inspection tasks, and military jobs. There is a growing body of literature, however, which suggests that many vigilance studies are of limited applicability to operational task performance. For example, Kibler (1965) has argued that technological changes have altered job performance requirements to the extent that laboratory vigilance studies are no longer applicable to real-world jobs. Many others have simply been unable to reproduce the typical “vigilance decrement” in field situations. This has led Teichner (1974) to conclude that “the decremental function itself is more presumed than established.”

scholarly journals Guidelines for Immersive Virtual Reality in Psychological Research

2020 ◽  
Author(s):  
Madis Vasser ◽  
Jaan Aru
Keyword(s):  
Virtual Reality ◽  
Real World ◽  
Reliability And Validity ◽  
Optimal Level ◽  
Psychological Research ◽  
Research Tool ◽  
Immersive Virtual Reality ◽  
Research Paradigms ◽  
Research Questions ◽  
Practical Recommendations

Virtual reality (VR) holds immense promise as a research tool to deliver results that are generalizable to the real world. However, the methodology used in different VR studies varies substantially. While many of these approaches claim to use “immersive VR”, the different hardware and software choices lead to issues regarding reliability and validity of psychological VR research. Questions arise about quantifying presence, the optimal level of graphical realism, the problem of being in dual-realities and reproducibility of VR research. We discuss how VR research paradigms could be evaluated and offer a list of practical recommendations to have common guidelines for psychological VR research.

scholarly journals HyP-ABC: A Novel Automated Hyper-Parameter Tuning Algorithm Using Evolutionary Optimization

2021 ◽  
Author(s):  
Leila Zahedi ◽  
Farid Ghareh Mohammadi ◽  
M. Hadi Amini
Keyword(s):  
Parameter Optimization ◽  
Real World ◽  
Optimization Problems ◽  
State Of The Art ◽  
Parameter Tuning ◽  
Gradient Boosting ◽  
Support Vector ◽  
Wide Range ◽  
Extreme Gradient Boosting ◽  
Art Techniques

Machine learning techniques lend themselves as promising decision-making and analytic tools in a wide range of applications. Different ML algorithms have various hyper-parameters. In order to tailor an ML model towards a specific application, a large number of hyper-parameters should be tuned. Tuning the hyper-parameters directly affects the performance (accuracy and run-time). However, for large-scale search spaces, efficiently exploring the ample number of combinations of hyper-parameters is computationally challenging. Existing automated hyper-parameter tuning techniques suffer from high time complexity. In this paper, we propose HyP-ABC, an automatic innovative hybrid hyper-parameter optimization algorithm using the modified artificial bee colony approach, to measure the classification accuracy of three ML algorithms, namely random forest, extreme gradient boosting, and support vector machine. Compared to the state-of-the-art techniques, HyP-ABC is more efficient and has a limited number of parameters to be tuned, making it worthwhile for real-world hyper-parameter optimization problems. We further compare our proposed HyP-ABC algorithm with state-of-the-art techniques. In order to ensure the robustness of the proposed method, the algorithm takes a wide range of feasible hyper-parameter values, and is tested using a real-world educational dataset.

scholarly journals Lessons Learnt, Open Research Questions and Recommendations

2016 ◽  
pp. 279-292
Author(s):  
Christine Bismuth ◽  
Bernd Hansjürgens ◽  
Timothy Moss ◽  
Sebastian Hoechstetter ◽  
Klement Tockner ◽  
...  
Keyword(s):  
Open Research ◽  
Lessons Learnt ◽  
Research Questions

scholarly journals A comprehensive review of plus-minus ratings for evaluating individual players in team sports

2019 ◽  
Vol 18 (1) ◽  
pp. 1-23 ◽  
Author(s):  
Lars Magnus Hvattum
Keyword(s):  
Decision Making ◽  
Team Sports ◽  
Sports Analytics ◽  
Comprehensive Review ◽  
Sports Events ◽  
Open Research ◽  
New Directions ◽  
Individual Player ◽  
Research Questions ◽  
The Many

AbstractThe increasing availability of data from sports events has led to many new directions of research, and sports analytics can play a role in making better decisions both within a club and at the level of an individual player. The ability to objectively evaluate individual players in team sports is one aspect that may enable better decision making, but such evaluations are not straightforward to obtain. One class of ratings for individual players in team sports, known as plus-minus ratings, attempt to distribute credit for the performance of a team onto the players of that team. Such ratings have a long history, going back at least to the 1950s, but in recent years research on advanced versions of plus-minus ratings has increased noticeably. This paper presents a comprehensive review of contributions to plus-minus ratings in later years, pointing out some key developments and showing the richness of the mathematical models developed. One conclusion is that the literature on plus-minus ratings is quite fragmented, but that awareness of past contributions to the field should allow researchers to focus on some of the many open research questions related to the evaluation of individual players in team sports.

Use of E-Portfolios in Health Professions Education

2018 ◽  
pp. 208-233 ◽  
Author(s):  
Andrew G. Pearson ◽  
Brooke E. Harris-Reeves ◽  
Lana J. Mitchell ◽  
Jessica J. Vanderlelie
Keyword(s):  
Case Studies ◽  
Real World ◽  
Digital Technologies ◽  
Health Professions ◽  
Professional Preparation ◽  
Employability Skills ◽  
Tertiary Institutions ◽  
Institutional Contexts ◽  
Research Questions ◽  
Support Students

In light of the changing landscape of workforce demand, digital technologies are becoming increasingly important to support students with their studies and professional preparation. As such, tertiary institutions are embedding curriculum approaches focused on the development of employability skills and drawing upon technology in order to prepare students for the real world of work in a manner that is scalable and transferable. Digital technologies such as ePortfolios have become an increasingly utilized platform for reflection, evidencing professional competencies and professional branding. Within this chapter, the authors discuss the benefits and limitations of these platforms from the perspectives of students, staff, professional, and institutional contexts. Case studies are utilzsed to demonstrate ePortfolios in practice across the allied health disciplines and key research questions and solutions for the future are discussed.

scholarly journals Improving Model-Based Genetic Programming for Symbolic Regression of Small Expressions

2020 ◽  
pp. 1-27 ◽  
Author(s):  
M. Virgolin ◽  
T. Alderliesten ◽  
C. Witteveen ◽  
P. A. N. Bosman
Keyword(s):  
Genetic Programming ◽  
Real World ◽  
Symbolic Regression ◽  
New Approach ◽  
Model Based ◽  
Real World Datasets ◽  
Linkage Learning ◽  
Optimal Mixing ◽  
Crucial Parameter

The Gene-pool Optimal Mixing Evolutionary Algorithm (GOMEA) is a model-based EA framework that has been shown to perform well in several domains, including Genetic Programming (GP). Differently from traditional EAs where variation acts blindly, GOMEA learns a model of interdependencies within the genotype, that is, the linkage, to estimate what patterns to propagate. In this article, we study the role of Linkage Learning (LL) performed by GOMEA in Symbolic Regression (SR). We show that the non-uniformity in the distribution of the genotype in GP populations negatively biases LL, and propose a method to correct for this. We also propose approaches to improve LL when ephemeral random constants are used. Furthermore, we adapt a scheme of interleaving runs to alleviate the burden of tuning the population size, a crucial parameter for LL, to SR. We run experiments on 10 real-world datasets, enforcing a strict limitation on solution size, to enable interpretability. We find that the new LL method outperforms the standard one, and that GOMEA outperforms both traditional and semantic GP. We also find that the small solutions evolved by GOMEA are competitive with tuned decision trees, making GOMEA a promising new approach to SR.

scholarly journals Assembly and Maintenance of Sarcomere Thin Filaments and Associated Diseases

2020 ◽  
Vol 21 (2) ◽  
pp. 542 ◽  
Author(s):  
Kendal Prill ◽  
John F. Dawson
Keyword(s):  
Thin Filament ◽  
Reverse Genetics ◽  
Medical Intervention ◽  
Model Organisms ◽  
Skeletal Muscle Function ◽  
Thin Filaments ◽  
Physiological Processes ◽  
Open Research ◽  
Research Questions ◽  
Sarcomere Assembly

Sarcomere assembly and maintenance are essential physiological processes required for cardiac and skeletal muscle function and organism mobility. Over decades of research, components of the sarcomere and factors involved in the formation and maintenance of this contractile unit have been identified. Although we have a general understanding of sarcomere assembly and maintenance, much less is known about the development of the thin filaments and associated factors within the sarcomere. In the last decade, advancements in medical intervention and genome sequencing have uncovered patients with novel mutations in sarcomere thin filaments. Pairing this sequencing with reverse genetics and the ability to generate patient avatars in model organisms has begun to deepen our understanding of sarcomere thin filament development. In this review, we provide a summary of recent findings regarding sarcomere assembly, maintenance, and disease with respect to thin filaments, building on the previous knowledge in the field. We highlight debated and unknown areas within these processes to clearly define open research questions.

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