BackgroundNeuroscientific approaches have historically triggered changes in the conception of creativity and artistic experience, which can be revealed by noting the intersection of these fields of study in terms of v...
详细信息
BackgroundNeuroscientific approaches have historically triggered changes in the conception of creativity and artistic experience, which can be revealed by noting the intersection of these fields of study in terms of variables such as global trends, methodologies, objects of study, or application of new technologies;however, these neuroscientific approaches are still often considered as disciplines detached from the arts and humanities. In this light, the question arises as to what evidence the history of neurotechnologies provides at the intersection of creativity and aesthetic *** conducted a century-long bibliometric analysis of key parameters in multidisciplinary studies published in the Scopus database. Screening techniques based on the PrISMA method and advanced data analysis techniques were applied to 3612 documents metadata from the years 1922 to 2022. We made graphical representations of the results applying algorithmic and clusterization processes to keywords and authors *** the analyses, we found a) a shift from a personality-focus quantitative analysis to a field-focus qualitative approach, considering topics such as art, perception, aesthetics and beauty;b) The locus of interest in fMrI-supported neuroanatomy has been shifting toward EEG technologies and models based on machine learning and deep learning in recent years;c) four main clusters were identified in the study approaches: humanistic, creative, neuroaesthetic and medical;d) the neuroaesthetics cluster is the most central and relevant, mediating between creativity and neuroscience;e) neuroaesthetics and neuroethics are two of the neologism that better characterizes the challenges that this convergence of studies will have in the next *** a longitudinal analysis, we evidenced the great influence that neuroscience is having on the thematic direction of the arts and humanities. The perspective presented shows how this field is being consoli
Agent-based modelling (ABM) shows promise for animal movement studies. However, a robust, open-source and spatially explicit ABM coding platform is currently lacking. We present abmr, an r package for conducting conti...
详细信息
Agent-based modelling (ABM) shows promise for animal movement studies. However, a robust, open-source and spatially explicit ABM coding platform is currently lacking. We present abmr, an r package for conducting continental-scale ABM simulations across animal taxa. The package features two movement functions, each of which relies on the Ornstein-Uhlenbeck (OU) process. The theoretical background for abmr is discussed and the main functionalities are illustrated using example populations. Potential future additions to this open-source package may include the ability to specify multiple environmental variables or to model interactions between agents. Additionally, updates may offer opportunities for disease ecology and integration with otherr movement modelling packages.
In psychological research, variables often exhibit point-mass inflation—for example, many zero responses or other boundary lumps—that defy standard regression techniques. Hurdle models address this challenge by sepa...
详细信息
Spatio-temporal crime analysis is a critical component of modern law enforcement and urban planning, aiming to understand the dynamic nature of criminal activities within a geographic context. This study presents a co...
详细信息
Gaming is an important aspect of the new generation and with this aspect comes improvement, which can be concerning graphics, sounds, gameplay, interaction, orranking. The ranking is a healthy competition where diffe...
详细信息
ISBN:
(纸本)9781728185194
Gaming is an important aspect of the new generation and with this aspect comes improvement, which can be concerning graphics, sounds, gameplay, interaction, orranking. The ranking is a healthy competition where different players can know standing around the globe, which makes them more competitive and help them stand above all. PUBG is multiplayer gaming that is supported on various platforms with a huge number of players online every day. This huge number can lead to a huge ranking, to overcome this difficulty there is a package in r programming called H2O which helps the developer to work with large numbers of datasets and also apply all different types of algorithms ranging from Machine Learning as well as Deep Learning and various unsupervised Learning. The algorithms used in this research are Linearregression, random Forest in the category of Machine Learning & Deep Neural Network in the category of Deep Learning. The metric evaluation of all these algorithms was carried out by using MAE (Mean Absolute Error) for the ranking of different players.
Millennials are raised in a gadget-filled and highly networked marketing environment and received a great deal of attention from the marketers for being very optimistic and open to different digital products. Millenni...
详细信息
作者：
Vance, Eric A.Univ Colorado
Dept Appl Math Lab Interdisciplinary Stat Anal 1111 Engn Dr Boulder CO 80309 USA
Data science is collaborative and its students should learn teamwork and collaboration. Yet it can be a challenge to fit the teaching of such skills into the data science curriculum. Team-Based Learning (TBL) is a ped...
详细信息
Data science is collaborative and its students should learn teamwork and collaboration. Yet it can be a challenge to fit the teaching of such skills into the data science curriculum. Team-Based Learning (TBL) is a pedagogical strategy that can help educators teach data science better by flipping the classroom to employ small-group collaborative learning to actively engage students in doing data science. A consequence of this teaching method is helping students achieve the workforce-relevant data science learning goals of effective communication, teamwork, and collaboration. We describe the essential elements of TBL: accountability structures and feedback mechanisms to support students collaborating within permanent teams on well-designed application exercises to do data science. The results of our case study of using TBL to teach a modern, introductory data science course indicate that the course effectively taught reproducible data science workflows, beginning r programming, and communication and collaboration. Students also reported much room for improvement in their learning of statistical thinking and advanced r concepts. To help the data science education community adopt this appealing pedagogical strategy, we outline steps for deciding on using TBL, preparing and planning for it, and overcoming potential pitfalls when using TBL to teach data science.
Introduction: There are two main schools of thought about statistical inference: frequentist and Bayesian. The frequentist approach relies solely on available data for predictions, while the Bayesian approach incorpor...
详细信息
Introduction: There are two main schools of thought about statistical inference: frequentist and Bayesian. The frequentist approach relies solely on available data for predictions, while the Bayesian approach incorporates both data and prior knowledge about the event of interest. Bayesian methods were developed hundreds of years ago;however, they were rarely used due to computational challenges and conflicts between the two schools of thought. recent advances in computational capabilities and a shift toward leveraging prior knowledge for inferences have led to increased use of Bayesian ***: Many biostatisticians with expertise in frequentist approaches lack the skills to apply Bayesian techniques. To address this gap, four faculty experts in Bayesian modeling at the University of Michigan developed a practical, customized workshop series. The training, tailored to accommodate the schedules of full-time staff, focused on immersive, project-based learning rather than traditional lecture-based methods. Surveys were conducted to assess the impact of the ***: All 20 participants completed the program and when surveyed reported an increased understanding of Bayesian theory and greater confidence in using these techniques. Capstone projects demonstrated participants' ability to apply Bayesian methodology. The workshop not only enhanced the participants' skills but also positioned them to readily apply Bayesian techniques in their ***: Accommodating the schedules of full-time biostatistical staff enabled full participation. The immersive project-based learning approach resulted in building skills and increasing confidence among staff statisticians who were unfamiliar with Bayesian methods and their practical applications.
作者：
Lundell, Jill F.Department of Data Science
Dana-Farber Cancer Institute Department of Biostatistics Harvard T.H. Chan School of Public Health Boston MA United States
Statistical learning methods have been growing in popularity in recent years. Many of these procedures have parameters that must be tuned for models to perform well. research has been extensive in neural networks, but...
详细信息
Context: Technical Debt (TD) is a metaphor used to describe code that is "not quite right." Although TD studies have gained momentum, TD has yet to be studied as thoroughly in non-Object-Oriented (OO) or sci...
详细信息
ISBN:
(纸本)9781728187105
Context: Technical Debt (TD) is a metaphor used to describe code that is "not quite right." Although TD studies have gained momentum, TD has yet to be studied as thoroughly in non-Object-Oriented (OO) or scientific software such as r. r is a multi-paradigm programming language, whose popularity in data science and statistical applications has amplified in recent years. Due to r's inherent ability to expand through user-contributed packages, several community-led organizations were created to organize and peer-review packages in a concerted effort to increase their quality. Nonetheless, it is well-known that most r users do not have a technical programming background, being from multiple disciplines. Objective: The goal of this study is to investigate TD in the documentation of the peer-review of r packages led by rOpenSci. Method: We collected over 5,000 comments from 157 packages that had been reviewed and approved to be published at rOpenSci. We manually analyzed a sample dataset of these comments posted by package authors, editors of rOpenSci, and reviewers during the review process to investigate the types of TD present in these reviews. results: The findings of our study include (i) a taxonomy of TD derived from our analysis of the peer-reviews (ii) documentation debt as being the most prevalent type of debt (iii) different userroles are concerned with different types of TD. For instance, reviewers tend to report some types of TD more than otherroles, and the types of TD they report are different from those reported by the authors of a package. Conclusion: TD analysis in scientific software or peer-review is almost non-existent. Our study is a pioneer but within the context of r packages. However, our findings can serve as a starting point forreplication studies, given our public datasets, to perform similar analyses in other scientific software or to investigate the rationale behind our findings.
暂无评论