检索结果-内蒙古大学图书馆

2nd International Conference on Intelligent Systems, Metaheuristics and Swarm Intelligence (ISMSI)

作者： Brito, Ricardo Fong, Simon Wu, Yaoyang Deb, Suash Univ Macau Fac Sci & Technol Dept Comp & Informat Sci Taipa Macau Peoples R China Victoria Univ Decis Sci & Modeling Program Melbourne Vic 8001 Australia

ISBN: (纸本)9781450364126

In this paper, we propose ParFeatArch Generator, a new algorithm for generating Neural Network architectures with optimal features and parameters through Particle Swarm Optimization. Selecting the best architecture for a Neural Network is usually done through a trial and error process, in which the number of layers is selected usually based on previous experience and then the network is trained and tested. When using Neural Networks as classifiers in feature selection algorithms, usually the number of layers in the Neural Network is selected prior to using the Neural Network as a classifier to the feature selection algorithm. In this work we propose a new generative algorithm called ParFeatArch Generator, which is based on PSO and combines the feature selection process with the Neural Network architecture selection process and parameter optimization in one algorithm which generates the Neural Network topology with optimal parameters while at the same time performs feature selection and evaluates the Neural Network topology to determine its quality. With the proposed algorithm, given a dataset, it is possible to end up with the optimal features on the dataset and with an optimal Neural Network classifier with optimal parameters for such features.

关键词： Particle Swarm Optimization (PSO) Neural Networks Feature Selection generative algorithms

来源：评论

学校读者我要写书评

暂无评论

ChatGPT in medical imaging higher education

引用

RADIOGRAPHY 2023年第4期29卷 792-799页

作者： Currie, G. Singh, C. Nelson, T. Nabasenja, C. Al-Hayek, Y. Spuur, K. Charles Sturt Univ Wagga Wagga NSW Australia Charles Sturt Univ Port Macquarie NSW Australia Charles Sturt Univ Sch Dent & Med Sci Locked Bag 588 Wagga Wagga NSW 2678 Australia

Introduction: Academic integrity among radiographers and nuclear medicine technologists/scientists in both higher education and scientific writing has been challenged by advances in artificial intelligence (AI). The recent release of ChatGPT, a chatbot powered by GPT-3.5 capable of producing accurate and human-like responses to questions in real-time, has redefined the boundaries of academic and scientific writing. These boundaries require objective evaluation. Method: ChatGPT was tested against six subjects across the first three years of the medical radiation science undergraduate course for both exams (n = 6) and written assignment tasks (n = 3). ChatGPT submissions were marked against standardised rubrics and results compared to student cohorts. Submissions were also evaluated by Turnitin for similarity and AI ***: ChatGPT powered by GPT-3.5 performed below the average student performance in all written tasks with an increasing disparity as subjects advanced. ChatGPT performed better than the average student in foundation or general subject examinations where shallow responses meet learning outcomes. For discipline specific subjects, ChatGPT lacked the depth, breadth, and currency of insight to provide pass level ***: ChatGPT simultaneously poses a risk to academic integrity in writing and assessment while affording a tool for enhanced learning environments. These risks and benefits are likely to be restricted to learning outcomes of lower taxonomies. Both risks and benefits are likely to be constrained by higher order taxonomies. Implications for practice: ChatGPT powered by GPT3.5 has limited capacity to support student cheating, introduces errors and fabricated information, and is readily identified by software as AI generated. Lack of depth of insight and appropriateness for professional communication also limits capacity as a learning enhancement tool.

关键词： ChatGPT Artificial intelligence Higher education Academic integrity generative algorithms Language model

来源：评论

学校读者我要写书评

暂无评论

Latent History 19

Latent History

引用

27th ACM International Conference on Multimedia (MM)

作者： Anadol, Refik Refik Anadol Studio Los Angeles CA 90026 USA

ISBN: (纸本)9781450368896

Latent History is a time and space exploration into Stockholm's past and ultimately present, through the deployment of machine learning algorithms trained on datasets from both archival and contemporary photographs. Through the exploration of photographic memories from the past 150 years, this exhibition aims to investigate and re-imagine collective memory, hidden layers of history, and the consciousness of a city that otherwise might remain unseen.

关键词： Machine learning archival data generative algorithms data visualization

来源：评论

学校读者我要写书评

暂无评论

Generating Neural Networks with Optimal Features through Particle Swarm Optimization 2017

Generating Neural Networks with Optimal Features through Par...

引用

International Conference on Big Data and Internet of Things (BDIOT)

作者： Brito, Ricardo Fong, Simon Zhuang, Yan Wu, Yaoyang Univ Macau Fac Sci & Technol Dept Comp & Informat Sci Taipa Macau Peoples R China

ISBN: (纸本)9781450354301

In this paper, we propose a new algorithm for generating Neural Network architectures with optimal features through Particle Swarm Optimization. Selecting the best architecture for a Neural Network is usually done through a trial and error process, in which the number of layers is selected usually based on previous experience and then the network is trained and tested. When using Neural Networks as classifiers in feature selection algorithms, usually the number of layers in the Neural Network is selected prior to using the Neural Network as a classifier to the feature selection algorithm. In this paper we propose a new generative algorithm based on PSO which combines the feature selection process with the Neural Network topology selection process in one algorithm which generates the Neural Network topology while at the same time performs feature selection and evaluates the Neural Network topology to determine its quality. With the proposed algorithm, given a dataset, it is possible to end up with the optimal features on the dataset and with an optimal Neural Network classifier for such features.

关键词： Particle Swarm Optimization (PSO) Neural Networks Feature Selection generative algorithms

来源：评论

学校读者我要写书评

暂无评论

WOODEN TRUSSES RECONSTRUCTION AND ANALYSIS THROUGH PARAMETRIC 3D MODELING 8

WOODEN TRUSSES RECONSTRUCTION AND ANALYSIS THROUGH PARAMETRI...

引用

8th International Workshop on 3D Virtual Reconstruction and Visualization of Complex Architectures (3D-ARCH)

作者： Prati, D. Zuppella, G. Mochi, G. Guardigli, L. Gulli, R. Univ Bologna DA Bologna Italy

This paper aims to indicate a new methodological approach, based on generative algorithms, to attempt a more in-depth and transversal understanding of the behavior of these wooden structures. The developed method accelerates modeling procedures and brings on new tools for analyzing these structural systems when surveyed through TLS devices. The main topic of this work is the most recent step of a wider research project that has analyzed a few wooden roofing structures in the area of bologna. These case studies are represented by a set of important churches in Bologna, all built between the 16th and 18th centuries, whose pitched roofs are supported by timber trusses. Among them, the most impressive is the wooden truss in the St. Peter Cathedral that has approximately 26 meters of span, 7 meters of height for nearly 9 tons of weight. It also shows a complex static conception with the coexistence of an external nondeformable triangle and an internal virtual discharging arc. The focus is on the transformation of the point cloud into 3D models using parametric modeling tools such as Grasshopper generative algorithms. These algorithms, once created for a single truss, allow to automatically generating 3D models of all trusses, changing only input parameters.

关键词： Building heritage Terrestrial Laser Scanning generative algorithms Structural systems reverse engineering Cloud to 3D model comparison

来源：评论

学校读者我要写书评

暂无评论

Anarchy A Library for Incremental Chaos 19

Anarchy A Library for Incremental Chaos

引用

14th International Conference on the Foundations of Digital Games (FDG)

作者： Mawhorter, Peter Wellesley Coll Wellesley MA 02181 USA

ISBN: (纸本)9781450372176

Pseudo-random number generators are ubiquitous components of content generation systems, because their outputs are difficult to predict but also repeatable given an initial seed. These properties make them especially useful as the basis for "random" decisions during a generative process, as they allow the process to be chaotic but also repeatable. This paper describes an open-source family of pseudo-random algorithms which allow for shuffling and distributing items in a reversible and incremental manner. To demonstrate the applicability of these algorithms, I show how they have been used in the creation of a word-search game which includes strong guarantees about the distribution of words that can be discovered.

关键词： generative algorithms Computational Creativity Pseudo-random Number Generation Noise Functions Chaos Procedural Content Generation

来源：评论

学校读者我要写书评

暂无评论

algorithms, Oppression, and Mental Illness on Social Media

Algorithms, Oppression, and Mental Illness on Social Media

引用

CHI Conference on Human Factors in Computing Systems (CHI)

作者： Feuston, Jessica L. Northwestern Univ Evanston IL 60208 USA

ISBN: (纸本)9781450359719

My research explores how individuals with mental illness express themselves online and off. Through digital ethnography, including interviews with Instagram users and manual collection of public content on Instagram, I have holistically examined the experience of mental illness as expressed through social media. This user-centric approach reveals and addresses the limitations of computational techniques, which my dissertation work will address by combining qualitative methods with generative algorithms to explore new 'ways of seeing' mental illness. I will create new tools enabling users to generate representations from their own posts in support of creating new representations of mental illness, advancing algorithmic fairness, and confronting technological forms of oppression online.

关键词： Mental illness social media digital ethnography generative algorithms anti-oppressive design

来源：评论

学校读者我要写书评

暂无评论

Analysis and management of structural deformations through parametric models and HBIM workflow in architectural heritage

引用

JOURNAL OF BUILDING ENGINEERING 2022年 45卷

作者： Moyano, Juan Gil-Arizon, Ignacio Nieto-Julian, Juan E. Marin-Garcia, David Univ Seville Dept Graph Express & Bldg Engn Higher Tech Sch Bldg Engn 4A Reina Mercedes Ave Seville 41012 Spain

Maintaining the structure and ornaments of historical buildings is essential to preserve cultural heritage in any society. Thus, dating the state and the evolution of the elements requires a special treatment, including the application of both advanced numerical analysis and non-invasive data acquisition techniques. In the latter, making digital copies of geometries through 3D reconstruction models is of great interest to compare and analyse structural evolutionary data accurately. For this purpose, appropriate software with containers of information correlated to the parametric elements in a BIM environment should be used. However, it is imperative to advance from static to dynamic models to collect the structural transformations caused by both the pass of time and other factors. The methodology followed in this paper is based on the experimentation by creating digital twins. The portico of a courtyard in a historical building from the 18th century was used as test bed. Based on the bibliographical recommendations, the terrestrial laser scanner is applied as a technique to acquire accurate data. The point cloud is used as a referential auxiliary to survey the model in the BIM platform with the Revit software. To assess the quality of the model built and to analyse the structural deviations between the parametric model and the actual geometry, the Dynamo script is used. To validate the experimentation, structural deviations are measured using both the parametric model and the point cloud with CloudCompare, a software for data treatment. The results were very positive because the deviation between the data obtained by Dynamo (c) and CloudCompare in the most unfavourable construction unit was between 0.5 and 1.17 cm, so these techniques are highly appropriate to review visual records and to analyse structural deviations. This new approach presents a new gap in the 3D reconstruction to date and control architectural structures, particularly in historical buildings.

关键词： HBIM Terrestrial laser scanning generative algorithms Structural systems reverse engineering Cultural management

来源：评论

学校读者我要写书评

暂无评论

The applications of machine learning in HIV neutralizing antibodies research-A systematic review

引用

ARTIFICIAL INTELLIGENCE IN MEDICINE 2022年 134卷 102429-102429页

作者： Danaila, Vlad-Rares Avram, Speranta Buiu, Catalin Univ Politehn Bucuresti Dept Automatic Control & Syst Engn 313 Splaiul Independentei Bucharest 060042 Romania Univ Bucharest Fac Biol Dept Anat Anim Physiol & Biophys 91 95 Splaiul Independentei Bucharest 050095 Romania

Machine learning algorithms play an essential role in bioinformatics and allow exploring the vast and noisy biological data in unrivaled ways. This paper is a systematic review of the applications of machine learning in the study of HIV neutralizing antibodies. This significant and vast research domain can pave the way to novel treatments and to a vaccine. We selected the relevant papers by investigating the available literature from the Web of Science and PubMed databases in the last decade. The computational methods are applied in neutralization potency prediction, neutralization span prediction against multiple viral strains, antibody- virus binding sites detection, enhanced antibodies design, and the study of the antibody-induced immune response. These methods are viewed from multiple angles spanning data processing, model description, feature selection, evaluation, and sometimes paper comparisons. The algorithms are diverse and include supervised, unsupervised, and generative types. Both classical machine learning and modern deep learning were taken into account. The review ends with our ideas regarding future research directions and challenges.

关键词： HIV antibody Neutralization potency Neutralization breadth Epitope detection Machine learning Deep learning Neural network Feature selection Unsupervised learning Clustering generative algorithms Data preprocessing

来源：评论

学校读者我要写书评

暂无评论

Digital and Interactive Learning and Teaching Methods in Descriptive Geometry

引用

Procedia - Social and Behavioral Sciences 2013年 106卷 873-885页

作者： Francesco Di Paola Pietro Pedone Maria Rita Pizzurro Department of Architecture (DARCH) Faculty of Engineering - Palermo University 90128 - Italy and Institute Euro Mediterranean of Science and Technology (IEMEST)-Palermo - Italy Student of Building Architecture (Ingegneria EDA) Politecnico di Milano 20133 - Italy Department of Architecture (DARCH) Faculty of Engineering - Palermo University 90128 – Italy

During the course of “Fundamentals and applications of Science of Representation - Geometric drawing” (held at the Faculty of Engineering at the University of Palermo) we successfully tested the adoption of informatics tools to enhance the comprehension and the critical analysis of complex figures in the geometrical space. The peculiarity in the teaching methodology was the adoption of interactive software products (Cabrì Géomètre and GeoGebra concerning dynamic and geometrical constructions; the well-known Rhinoceros plug-in, Grasshopper, about generating algorithms; Linceo regarding implementing the graphic display of complex solids in augmented reality). According to our experience within didactic laboratories, the adoption of ICT allowed us to stimulate and interest students towards subjects of descriptive and projective Geometry and the expected results are very satisfactory. In this paper we show some of the most interesting examples of geometric constructions created by students.

关键词： digital and interactive learning tools dynamic geometry generative algorithms augmented reality

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：