检索结果-内蒙古大学图书馆

Proceedings of the 37th International Conference on Neural Information Processing Systems

作者： Rui Jiao Wenbing Huang Peijia Lin Jiaqi Han Pin Chen Yutong Lu Yang Liu Dept. of Comp. Sci. & Tech. Institute for AI Tsinghua University and Institute for AIR Tsinghua University Gaoling School of Artificial Intelligence Renmin University of China and Beijing Key Laboratory of Big Data Management and Analysis Methods Beijing China National Supercomputer Center in Guangzhou School of Computer Science and Engineering Sun Yat-sen University Stanford University

Crystal Structure Prediction (CSP) is crucial in various scientific disciplines. While CSP can be addressed by employing currently-prevailing generative models (e.g. diffusion models), this task encounters unique challenges owing to the symmetric geometry of crystal structures—the invariance of translation, rotation, and periodicity. To incorporate the above symmetries, this paper proposes DiffCSP, a novel diffusion model to learn the structure distribution from stable crystals. To be specific, DiffCSP jointly generates the lattice and atom coordinates for each crystal by employing a periodic-E(3)-equivariant denoising model, to better model the crystal geometry. Notably, different from related equivariant generative approaches, DiffCSP leverages fractional coordinates other than Cartesian coordinates to represent crystals, remarkably promoting the diffusion and the generation process of atom positions. Extensive experiments verify that our DiffCSP significantly outperforms existing CSP methods, with a much lower computation cost in contrast to DFT-based methods. Moreover, the superiority of DiffCSP is also observed when it is extended for ab initio crystal generation. Code is available at https://***/jiaor17/DiffCSP.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Stability and generalization of kernel clustering: from single kernel to multiple kernel 22

Stability and generalization of kernel clustering: from sing...

引用

Proceedings of the 36th International Conference on Neural Information Processing Systems

作者： Weixuan Liang Xinwang Liu Yong Liu Sihang Zhou Jun-Jie Huang Siwei Wang Jiyuan Liu Yi Zhang En Zhu School of Computer National University of Defense Technology (NUDT) Changsha China Gaoling School of Artificial Intelligence Renmin University of China Beijing China and Beijing Key Laboratory of Big Data Management and Analysis Methods Beijing China College of Intelligence Science and Technology NUDT Changsha China

ISBN: (纸本)9781713871088

Multiple kernel clustering (MKC) is an important research topic that has been widely studied for decades. However, current methods still face two problems: inefficient when handling out-of-sample data points and lack of theoretical study of the stability and generalization of clustering. In this paper, we propose a novel method that can efficiently compute the embedding of out-of-sample data with a solid generalization guarantee. Specifically, we approximate the eigen functions of the integral operator associated with the linear combination of base kernel functions to construct low-dimensional embeddings of out-of-sample points for efficient multiple kernel clustering. In addition, we, for the first time, theoretically study the stability of clustering algorithms and prove that the single-view version of the proposed method has uniform stability as O(Kn-3/2) and establish an upper bound of excess risk as Õ(Kn-3/2 + n-1/2), where K is the cluster number and n is the number of samples. We then extend the theoretical results to multiple kernel scenarios and find that the stability of MKC depends on kernel weights. As an example, we apply our method to a novel MKC algorithm termed SimpleMKKM and derive the upper bound of its excess clustering risk, which is tighter than the current results. Extensive experimental results validate the effectiveness and efficiency of the proposed method.

关键词：

来源：评论

学校读者我要写书评

暂无评论

ASYMPTOTIC EXPECTED T-FUNCTIONALS OF RANDOM POLYTOPES WITH APPLICATIONS TO Lp SURFACE AREAS

arXiv

引用

arXiv 2022年

作者： Hoehner, Steven Li, Ben Roysdon, Michael Thäle, Christoph Department of Mathematics & Computer Science Longwood University United States Department of Mathematical Methods in Physics Warsaw University Poland Institute for Computational and Experimental Research in Mathematics United States Department of Pure Mathematics Tel Aviv University Israel Faculty of Mathematics Ruhr University Bochum Germany

An asymptotic formula is proved for the expected T -functional of the convex hull of independent and identically distributed random points sampled from the Euclidean unit sphere in n according to an arbitrary positive continuous density. As an application, the approximation of the sphere by random polytopes in terms of Lp surface area differences is *** Codes 52A22, 52A27, 60D05 (Primary) 52A20, 52B11 (Secondary) Copyright © 2022, The Authors. All rights reserved.

关键词： Topology

来源：评论

学校读者我要写书评

暂无评论

Computing curved area labels in near-real time

arXiv

引用

arXiv 2020年

作者： Krumpe, Filip Mendel, Thomas University of Stuttgart Stuttgart Germany Institut of Formal Methods in Computer Science - Algorithmic Group

In the Area Labeling Problem one is after placing the label of a geographic area. Given the outer boundary of the area and an optional set of holes. The goal is to find a label position such that the label spans the area and is conform to its shape. The most recent research in this field from Barrault in 2001 proposes an algorithm to compute label placements based on curved support lines. His solution has some drawbacks as he is evaluating many very simi- lar solutions. Furthermore he needs to restrict the search space due to performance issues and therefore might miss interesting solutions. We propose a solution that evaluates the search space more broadly and much more e°cient. To achieve this we compute a skeleton of the polygon. The skeleton is pruned such that edges close to the boundary polygon are removed. In the so pruned skeleton we choose a set of candi- date paths to be longest distinct subpaths of the graph. Based on these candidates the label support lines are computed and the label positions evaluated.68U05, 68U35 Copyright © 2020, The Authors. All rights reserved.

关键词： Musculoskeletal system

来源：评论

学校读者我要写书评

暂无评论

As a mechanism that achieves the goal of decision management

As a mechanism that achieves the goal of decision management

引用

International Conference on Information science and Communications Technologies (ICISCT)

作者： Nodir Raximov Jurabek Quvondikov Xurshid Dusanov Barno Daminova Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Tashkent Uzbekistan Applied Mathematics and Informatics Jizzakh Branch Of National University Of Uzbekistan Named After Mirzo Ulugbek Jizzakh Uzbekistan Methods of teaching computer science Karshi State University Karshi Uzbekistan

ISBN: (纸本)9781665432597

Working with different data depending on the appearance and content of the object. Formation of types of objects and content of processes within the framework of human activity. Based on this, the control mechanism is also different. Management effects in the learning system are understood as the transfer of knowledge in the subject area to the student using the methods and tools formed by the teacher in the educational environment, taking into account all the factors generated in this process. The control system in this view is a simple system with a nonlinear feedback section. It combines complexes consisting of technical, software, telecommunications and methodological tools used in the educational process. They can be used to form alternative solutions not only by delivering parts of the training materials, but also by collecting and processing the information needed to manage the learning process. The training method is chosen according to the requirements of the learning environment and depends on the topic. If the chosen method is accepted, the training part is provided, which is fixed (question-answer or in another form), which makes it possible to work independently.

关键词： Training Learning systems Information science Organizations Control systems Software Communications technology

来源：评论

学校读者我要写书评

暂无评论

Engaging High School Students in Robotics and Artificial Intelligence Through Engineering Design Robotics Education

SSRN

引用

SSRN 2024年

作者： Novak, Elena Ahmadi, Sima Smith, Shannon Matar, Sophia Borgerding, Lisa Kent State University School of Teaching Learning and Curriculum Studies 150 Terrace Drive P.O. Box 5190 KentOH44242-0001 United States Kent State University College of Education Health and Human Services 150 Terrace Drive 408 KentOH44240 United States Kent State University ATR Lab Computer Science KentOH United States

Engineering design education is an effective instructional approach for enhancing students’ motivation, interest, and creativity while introducing them to the engineering design process (EDP). However, there is limited knowledge on how to integrate the EDP into robotics education. This pre-/posttest embedded mixed-methods study adds to the scarce body of literature on interdisciplinary education in engineering design, robotics, and artificial intelligence (AI). This project developed, implemented, and evaluated a project-based Engineering Design+Robotics+AI curriculum with novice computer science (CS) high school students. The curriculum introduced students to robotics, Machine Learning, and AI. Students’ collaborative robotics projects were framed using an EDP model to introduce students to engineering education and promote engagement and interest through design-based, hands-on learning. An analysis of quantitative and qualitative data revealed an improvement in students’ CS attitudes, collaboration, and social interactions after participating in the curriculum. Working on robotics engineering design challenges enhanced students’ project experiences and promoted creativity and engagement in the CS classroom. Recommendations for designing robotics projects using the engineering design robotics approach are discussed. © 2024, The Authors. All rights reserved.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Intelligent waste sorting for sustainable environment: A hybrid deep learning and transfer learning model

引用

Gondwana Research 2024年

作者： Kumar Lilhore, Umesh Simaiya, Sarita Dalal, Surjeet Radulescu, Magdalena Balsalobre-Lorente, Daniel Department of Computer Science and Engineering Galgotias University Greater Noida Uttar Pradesh India Department of Computer Science and Engineering Amity University Gurugram Haryana India Institute of Doctoral and Post-Doctoral Studies University Lucian Blaga of Sibiu Sibiu Romania UNEC Research Methods Application Center Azerbaijan State University of Economics (UNEC) Baku 1001 Istiqlaliyyat Str. 6 Azerbaijan Department of Applied Economics I University Castilla-La Mancha Spain Department of Management Faculty of Economics and Management Czech University of Life Sciences Prague Prague 16500 Czech Republic Economic Research Center (WCERC) Western Caspian University Baku Azerbaijan

The significance of waste disposal, classification, and monitoring has dramatically increased due to the increase in industrial development and the progress of intelligent urbanization. Since the last few decades, the utilization of Deep learning techniques has grown increasingly in waste management research. The efficiency of a waste reuse and recycling process relies on its capacity to restore resources to their original state, thereby minimizing pollution and promoting an ecologically sustainable framework. Selecting the optimal deep-learning method for classifying and predicting waste is challenging and time-consuming. This paper proposed intelligent garbage categorization using Bidirectional Long Short-Term Memory (Bi-LSTM) and CNN-based transfer learning to improve environmental sustainability. Organic and recyclable garbage are separated. To simplify trash categorization, a hybrid model combines TL-based CNN and Bi-LSTM. This study extensively examined the suggested technique with numerous CNN computational methods, including VGG-19, ResNet-34, AlexNet, ResNet-50, and VGG-16, using the ’TrashNet Waste’ database. Key findings show that our hybrid model outperforms existing models. Our classification accuracy is 96.78 %, 5.27 % higher than the best model. Our model also reduces misclassification by 7.25 %, proving its reliability. This comprehensive examination examined the computer models’ trash classification performance and provided specific viewpoints. The results explain each technique's pros and cons and show how useful they are in real-world circumstances. Waste classification is practical and sophisticated with a hybrid model. The effectiveness and cleverness of this model improve sustainable environmental practices. The proposed method's excellent performance suggests its seamless integration into practical waste management solutions. © 2024 International Association for Gondwana Research

关键词： Convolutional neural network (CNN) Deep learning Smart Waste Management Transfer Learning Waste classification

来源：评论

学校读者我要写书评

暂无评论

Multilevel model-based clustering: A new proposal of maximum-a-posteriori assignment

Multilevel model-based clustering: A new proposal of maximum...

引用

Biennial Conference of the International Federation of Classification Societies, IFCS 2017

作者： Bacci, Silvia Bartolucci, Francesco Pennoni, Fulvia Department of Statistics Computer Science Applications "Giuseppe Parenti" University of Florence Florence Italy Department of Economics University of Perugia Perugia Italy Department of Statistics and Quantitative Methods University of Milano-Bicocca Milano Italy

ISBN: (纸本)9789811533105

We deal with the problem of latent variable prediction in the context of multilevel latent class models for categorical responses provided by individuals nested in groups. In particular, we propose a posterior assignment rule that jointly predicts the individual- and group-level latent variables. This proposal is alternative to the common maximum-a-posteriori rule, which is based on first predicting the latent variables at cluster level and, then, those at individual level. To illustrate the proposal, we show the results of two simulation studies and two applications on data related to the national and the international assessment of student skills. © Springer Nature Singapore Pte Ltd 2020.

关键词： Regression analysis

来源：评论

学校读者我要写书评

暂无评论

Semantics Analytics of Origin-Destination Flows from Crowd Sensed Big Data

引用

computers, Materials & Continua 2019年第7期61卷 227-241页

作者： Ning Cao Shengfang Li Keyong Shen Sheng Bin Gengxin Sun Dongjie Zhu Xiuli Han Guangsheng Cao Abraham Campbell College of Computer Information and Engineering Nanchang Institute of TechnologyNanchangChina College of Information Engineering Sanming UniversitySanmingChina School of Data Science and Software Engineering Qingdao UniversityQingdaoChina School of Computer Science and Technology Harbin Institute of TechnologyWeihaiChina Public Teaching Department Qingdao Technical CollegeQingdaoChina School of Computer Science University College DublinDublinIreland

Monitoring,understanding and predicting Origin-destination(OD)flows in a city is an important problem for city planning and human ***-GPS traces,acted as one kind of typical crowd sensed data,it can be used to mine the semantics of OD *** this paper,we firstly construct and analyze a complex network of OD flows based on large-scale GPS taxi traces of a city in *** spatiotemporal analysis for the OD flows complex network showed that there were distinctive patterns in OD *** based on a novel complex network model,a semantics mining method of OD flows is proposed through compounding Points of Interests(POI)network and public transport network to the OD flows *** propose method would offer a novel way to predict the location characteristic and future traffic conditions accurately.

关键词： Origin-destination(OD)flows semantics analytics complex network big data analysis

来源：评论

学校读者我要写书评

暂无评论

Adoption of Artificial Intelligence for Diagnosis and Treatment of <i>Staphylococcus aureus</i>Infections Disease on Humans

引用

E-Health Telecommunication Systems and Networks 2020年第1期9卷 1-15页

作者： Kanayo Kizito Uka Stanley Ikechukwu Oguoma Chekwube Alphonsus Chukwu Chijioke Izuchukwu Emele Department of Computer Science Imo State University Owerri Nigeria Nnamdi Azikiwe Teaching Hospital Nnewi Nigeria

The aim of this paper is to develop an expert system that could aid medical practitioner to effectively diagnose and treat Staphylococcus aureus infections disease on a human. The objective of the research includes to develop an expert system for quick diagnosis and detection of Staphylococcus aureus bacteria on human skin, a system that aids in accurate treatment of staph infectious diseases by doctors, helps in quick decision making in the hospital, improves accuracy in drug prescription, and a system that will bring about computerized storage process, and to enlighten the knowledge workers on how to implement a computer based decision support systems and importance of it in the health care. The research was motivated due to delay in diagnosis and identification of Staphylococcus aureus bacteria and the fast rate at which infectious disease is spreading, delay in treatment of these bacteria, increase of guess work by health practitioners leading to delay in decision making and lack of electronic storage facility in the hospitals. Top down approach was used in the system design of this research while adopting expert system as the methodology and the programming language used was Java and database design used was MySQL. The result after design was a computerized standalone application that assists health practitioners (Doctor’s) in quick identification, diagnosis, prescription and treatment of Staphylococcus aureus bacteria on human skin. The expert system will facilitate quick decision making in the clinic.

关键词： Artificial Intelligence Expert System Diagnosis Treatment Staphylococcus aureus Infectious Disease

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：