检索结果-内蒙古大学图书馆

2024 IEEE International Conference on Agrosystem Engineering, Technology and Applications, AGRETA 2024

作者： Guimaraes, Carlos Solon Soares Pereira, Carlos Eduardo De Freitas, Edison Pignaton Gomes, Victor Emmanuel De Oliveira Nardelli, Vitor Camargo Vizzotto, Marcos Rodrigues Senai Institute of Innovation in Sensing Systems Department of Software RS São Leopoldo93025-753 Brazil Federal University of Rio Grande Do Sul Department of Electrical Automation and Energy Systems RS Porto Alegre90035-190 Brazil Institute of Informatics - Computer Networks Group Federal University of Rio Grande Do Sul RS Porto Alegre91501-970 Brazil Senai Institute of Innovation in Sensing Systems Division Manager of Operations in Technology and Innovation RS Porto Alegre91140-001 Brazil Senai Institute of Innovation in Sensing Systems RS São Leopoldo93025-753 Brazil

ISBN: (纸本)9798350373660

Precision agriculture is a domain in fast expansion, demanding flexible approaches to deploy customized solutions to specific needs in short time windows. In this context, this work proposes a service-oriented architecture and microservices to support Unmanned Aerial Vehicles systems development for this sector. The proposal presents a framework and middleware designed to offer modular and reusable software components with an intermediate layer to facilitate integration, communication, control, and data management between different systems in an agricultural application setting. This paper presents the design of this approach with a glance to the roadmap to its implementation. © 2024 IEEE.

关键词： Precision agriculture

来源：评论

学校读者我要写书评

暂无评论

Data Fusion in Neuromarketing: Multimodal Analysis of Biosignals, Lifecycle Stages, Current Advances, Datasets, Trends, and Challenges

SSRN

引用

SSRN 2023年

作者： Pérez, Mario Quiles Beltrán, Enrique Tomás Martínez Bernal, Sergio López Prat, Eduardo Horna Del Campo, Luis Montesano Maimó, Lorenzo Fernández Celdrán, Alberto Huertas Department of Information and Communications Engineering University of Murcia Murcia30100 Spain Bit&Brain Technologies S.L Zaragoza50006 Spain Department of Computer Architecture and Technology University of Murcia Murcia30100 Spain Communication Systems Group CSG Department of Informatics IfI University of Zurich UZH ZürichCH—8050 Switzerland

The primary goal of any company is to increase its profits by improving both the quality of its products and how they are advertised. In this context, neuromarketing seeks to enhance the promotion of products and generate a greater acceptance on potential buyers. Traditionally, neuromarketing studies have relied on a single biosignal to obtain feedback from presented stimuli. However, thanks to new devices and technological advances studying this area of knowledge, recent trends indicate a shift towards the fusion of diverse biosignals. An example is the usage of electroencephalography for understanding the impact of an advertisement at the neural level and visual tracking to identify the stimuli that induce such impacts. This emerging pattern determines which biosignals to employ for achieving specific neuromarketing objectives. Furthermore, the fusion of data from multiple sources demands advanced processing methodologies. Despite these complexities, there is a lack of literature that adequately collates and organizes the various data sources and the applied processing techniques for the research objectives pursued. To address these challenges, the current paper conducts a comprehensive analysis of the objectives, biosignals, and data processing techniques employed in neuromarketing research. This study provides both the technical definition and a graphical distribution of the elements under revision. Additionally, it presents a categorization based on research objectives and provides an overview of the combinatory methodologies employed. After this, the paper examines primary public datasets designed for neuromarketing research together with others whose main purpose is not neuromarketing, but can be used for this matter. Ultimately, this work provides a historical perspective on the evolution of techniques across various phases over recent years and enumerates key lessons learned. © 2023, The Authors. All rights reserved.

关键词： Life cycle

来源：评论

学校读者我要写书评

暂无评论

Automated clustering and knowledge acquisition support for beginners 24

Automated clustering and knowledge acquisition support for b...

引用

24th KES International Conference on Knowledge-Based and Intelligent Information and Engineering systems, KES 2020

作者： Kamoshida, Ryota Ishikawa, Fuyuki Research and Development Group Hitachi Ltd. Tokyo Japan Information Systems Architecture Science Research Division National Institute of Informatics Tokyo Japan Department of Informatics University of Electro-Communications Tokyo Japan

Although automated machine learning (AutoML) is receiving attention in the field of data science, most AutoML open source software focuses on supervised learning tasks, and little attention has been given to unsupervised learning tasks. Moreover, AutoML has a disadvantage in that it tends to deprive users of a chance to acquire knowledge about machine learning and data science because it usually works as a black box. The purpose of this study is to help inexperienced data scientists and machine learning engineers conduct clustering data analysis, which is an unsupervised learning task, while simultaneously enabling them to acquire knowledge about clustering data analysis by extending our existing AutoML software, the machine learning support system (MALSS). The MALSS helps with clustering data analysis by automatically determining the optimal number of clusters, which is one of the main purposes of clustering data analysis. Furthermore, the MALSS helps users to acquire knowledge about clustering data analysis by generating a report after automated clustering data analysis is conducted. We validated the effectiveness of our approach by using open datasets and by running an experiment on a crowdsourcing platform. © 2020 The Authors. Published by Elsevier B.V.

关键词： Unsupervised learning

来源：评论

学校读者我要写书评

暂无评论

Self-consumption rises due to energy crises? An evaluation of prosumers’ consumption behavior in 2022

Self-consumption rises due to energy crises? An evaluation o...

引用

International Conference on European Electricity Market, EEM

作者： Sabine Pelka Peter Conradie Laurens de Vries Vasilios Anatolitis Emma Martens Emile Chappin Merkouris Karaliopoulos Filippos Anagnostopoulos Sabine Preuß Energy and Industry Group Faculty of Technology Policy and Management Delft University of Technology Delft the Netherlands Fraunhofer Institute for Systems and Innovation Research Karlsruhe Germany Department of Industrial Systems Engineering and Product Design Faculty of Engineering and Architecture Ghent University Belgium Imec-Mict-UGent Ghent Belgium Department of Informatics Athens University of Economics and Business Athens Greece Institute for European Energy and Climate Policy (IEECP) Amsterdam Netherlands

Prosumers with photovoltaic systems can reduce their electricity expenses by increasing their consumption of self-generated electricity. This makes them more resilient to price shocks, like the 2022 European energy crisis. We evaluate how prosumers adapt their consumption behavior in response to such political uncertainty and increasing electricity prices. The collected survey and smart meter data allow us to evaluate the perceived self-reported and measured impact on *** intentions due to the energy crisis are more clearly displayed by the survey than by the measured self-consumption. While solar radiation predominantly explains self-consumption changes, Google searches on electricity-related topics have limited explanatory power. However, considering time lags and the interaction with solar radiation leads to more nuanced insights on the effect of Google searches. Depending on the level of solar radiation, the effect of Google searches ranges from decreasing the daily self-consumption by 26.45 Wh to increasing it by 69.45 Wh.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Deep Learning/PUF-based Item Identification for Supply Chain Management in a Distributed Ledger Framework

Deep Learning/PUF-based Item Identification for Supply Chain...

引用

Blockchain Computing and Applications (BCCA), International Conference on

作者： Carmelo Felicetti Antonella Guzzo Giuseppe Manco Francesco Pasqua Ettore Ritacco Antonino Rullo Domenico Saccà Department of Informatics Modelling Electronics and Systems (DIMES) University of Calabria Rende Italy Institute for High Performance Computing and Networking National Research Council (ICAR-CNR) Rende Italy Open Knowledge Technologies (OKT) Relatech Group Rende Italy Computer Science Department University of Udine Udine Italy

Item identification is an important issue in modern supply chains where product items are traced by means of electronic tags that, despite the advantages they bring in terms of automation, are still subject to counterfeiting attacks such as tag modification, cloning, and re-application. To counter these threats (i) tags must be able to safely demonstrate their identity without giving attackers the ability to clone them or modify their content, and (ii) auxiliary identification techniques should be adopted in the case tags are removed from original items and reapplied to fake ones. Using Physically Unclonable Functions as tag “digital fingerprint” has proven to be a viable solution for tag authentication. On the other hand, artificial intelligence has proven its effectiveness in the field of object identification. In this paper we describe a tag architecture immune to cloning and modification attacks, and illustrate how this can be coupled with a product item in a supply chain scenario to confer a stable and durable identity for authentication, in order to identify the items and track them in a distributed ledger framework. We also propose a deep learning approach to perform anti-counterfeiting controls when tag reapplication attacks are in place.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Image Captioning with Reinforcement Learning

Image Captioning with Reinforcement Learning

引用

computer Vision and Machine Intelligence (CVMI), International Conference on

作者： Anand Verma Saurabh Agarwal K.V. Arya Ivan Petrlik Roberto Esparza Ciro Rodriguez Department of Information Technology ABV-IIITM Gwalior Madhya Pradesh India Department of Computer Science and Engineering Multimedia and Information Security Research Group ABV-Indian Institute of Information Technology and Management Gwalior India Faculty of Industrial and Systems Engineering National University Federico Villarreal Lima Peru Faculty of Systems Engineering and Informatics National University Mayor de San Marcos

Image captioning involves generating a natural language description that accurately represents the content and context of an image. To achieve this, image captioning utilises various machine learning techniques and fields, such as computer vision and natural language processing. In the field of image captioning, a lot of advances have been made with encoder-decoder models and reinforcement learning algorithms. However, there are still problems of imbalance between testing and training, as reinforcement learning only handles single comparator metrics such as CIDEr, SPICE, and BLEU and could not perform better in multiple metrics at once. Which is why a lack of diversity can be seen in generated captions. This idea proposes a general technique for collaborative updating that can bridge the gap between evaluation measures and test metrics to produce captions that are more human-like. To increase the precision of image captions, the approach involves using a compiled reward system that considers multiple evaluation metrics to compare the generated sentence with the provided sentences. We will evaluate the model's performance and the reward updating process on standard datasets like MS COCO.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Ranking matters: Does the new format select the best teams for the knockout phase in the UEFA Champions League?

arXiv

引用

arXiv 2025年

作者： Csató, László Devriesere, Karel Goossens, Dries Gyimesi, András Lambers, Roel Spieksma, Frits Laboratory on Engineering and Management Intelligence Research Group of Operations Research and Decision Systems Budapest Hungary Institute of Operations and Decision Sciences Department of Operations Research and Actuarial Sciences Hungary Ghent University Department of Business Informatics and Operations Management Belgium FlandersMake@UGent – core lab CVAMO Ghent Belgium University of Pécs Hungary Eindhoven University of Technology Department of Mathematics and Computer Science Netherlands

Starting in the 2024/25 season, the Union of European Football Associations (UEFA) has fundamentally changed the format of its club competitions: the group stage has been replaced by a league phase played by 36 teams in an incomplete round robin format. This makes ranking the teams based on their results challenging because teams play against different sets of opponents, whose strengths vary. In this research note, we apply several well-known ranking methods for incomplete round robin tournaments to the 2024/25 UEFA Champions League league phase. Our results show that it is doubtful whether the currently used point-based system provides the best ranking of the *** Codes 15A06, 91B14 Copyright © 2025, The Authors. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

PROV-IO+: A Cross-Platform Provenance Framework for Scientific Data on HPC systems

arXiv

引用

arXiv 2023年

作者： Han, Runzhou Zheng, Mai Byna, Suren Tang, Houjun Dong, Bin Dai, Dong Chen, Yong Kim, Dongkyun Hassoun, Joseph Thorsley, David Wolf, Matthew Department of Electrical and Computer Engineering Iowa State University United States Department of Computer Science and Engineering The Ohio State University United States Scientific Data Management Group Lawrence Berkeley National Laboratory United States Computer Science Department University of North Carolina Charlotte United States Systems Architecture Lab Samsung United States Samsung Advanced Institute of Technology Samsung Korea Republic of

Data provenance, or data lineage, describes the life cycle of data. In scientific workflows on HPC systems, scientists often seek diverse provenance (e.g., origins of data products, usage patterns of datasets). Unfortunately, existing provenance solutions cannot address the challenges due to their incompatible provenance models and/or system implementations. In this paper, we analyze four representative scientific workflows in collaboration with the domain scientists to identify concrete provenance needs. Based on the first-hand analysis, we propose a provenance framework called PROV-IO+, which includes an I/O-centric provenance model for describing scientific data and the associated I/O operations and environments precisely. Moreover, we build a prototype of PROV-IO+ to enable end-to-end provenance support on real HPC systems with little manual effort. The PROV-IO+ framework can support both containerized and non-containerized workflows on different HPC platforms with flexibility in selecting various classes of provenance. Our experiments with realistic workflows show that PROV-IO+ can address the provenance needs of the domain scientists effectively with reasonable performance (e.g., less than 3.5% tracking overhead for most experiments). Moreover, PROV-IO+ outperforms a state-of-the-art system (i.e., ProvLake) in our experiments. © 2023, CC BY-NC-SA.

关键词： Life cycle

来源：评论

学校读者我要写书评

暂无评论

Evaluation of the Montenegrin Academic Digital Innovation Hub 27

Evaluation of the Montenegrin Academic Digital Innovation Hu...

引用

27th International Conference on Information Technology, IT 2023

作者： Lakovic, Luka Kara, Peter A. Ognjanovic, Ivana Bokor, Laszlo Sendelj, Ramo Reich, Christoph Roganovic, Milovan Zoulias, Emmanouil Erakovic, Jevto Radusinovic, Tanja Rakocevic, Nada Simon, Aniko University of Donja Gorica Faculty for Information Systems and Technologies Podgorica81000 Montenegro Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Networked Systems and Services Budapest1111 Hungary Faculty of Science Engineering and Computing Kingston University Wireless Multimedia and Networking Research Group Department of Computer Science School of Computer Science and Mathematics LondonKT1 2EE United Kingdom University of Donja Gorica Humanistic Studies Podgorica81000 Montenegro Furtwangen University Institute of Data Science Cloud Computing and It Security Furtwangen78120 Germany Clinical Centre of Montenegro Clinic for Neurology Podgorica81000 Montenegro National and Kapodistrian University of Athens Faculty of Nursing School of Health Sciences Goudi 11527 Greece Chamber of Economy of Montenegro Podgorica81000 Montenegro Sigma Technology Budapest1093 Hungary

ISBN: (纸本)9798350397512

In the era of global digitalization, digital innovation hubs have become essential, as they function as transforming forces. In this paper, we provide an analysis of the Montenegrin Academic Digital Innovation Hub by applying multi-criteria qualitative evaluation over several criteria: process flow of fully digitized operations of the Hub (with aspects of the innovation life-cycle, ethics, and security), resource management, strategic goals, and feasibility. The paper also proposes a model of comprehensive resource management via the perspective of smart specialization priorities of Montenegro. © 2023 IEEE.

关键词： Life cycle

来源：评论

学校读者我要写书评

暂无评论

Assistive Technical Communication of Montenegrin eServices: a Case Study 27

Assistive Technical Communication of Montenegrin eServices: ...

引用

27th International Conference on Information Technology, IT 2023

作者： Simon, Aniko Lakovic, Luka Kovacevic, Pavle Kara, Peter A. Ognjanovic, Ivana Sendelj, Ramo Reich, Christoph Roganovic, Milovan Mantas, John Bokor, Laszlo Sigma Technology Budapest1093 Hungary University of Donja Gorica Faculty for Information Systems and Technologies Podgorica81000 Montenegro Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Networked Systems and Services Budapest1111 Hungary Kingston University Wireless Multimedia and Networking Research Group Department of Computer Science School of Computer Science and Mathematics Faculty of Science Engineering and Computing LondonKT1 2EE United Kingdom University of Donja Gorica Humanistic Studies Podgorica81000 Montenegro Furtwangen University Institute of Data Science Cloud Computing and It Security Furtwangen78120 Germany Clinical Centre of Montenegro Clinic for Neurology Podgorica81000 Montenegro National and Kapodistrian University of Athens Faculty of Nursing School of Health Sciences Goudi 11527 Greece

ISBN: (纸本)9798350397512

With the advancement of information technology in the recent decades, digital and online services have become essential components of everyday life in Europe. Montenegro is no different in this regard. However, as digital literacy in the country is still in a developing phase in comparison with most countries of the EU, a higher portion of its citizens may rely on assistive technical communication. In this paper, we provide a case study on the assistive technical communication of Montenegrin eServices. The work addresses the sectors of online banking, healthcare services, higher education, national administrative services, and utilities. Our findings highlight the diversity in terms of implemented assistive technical communication, and distinguish usage contexts on the level of adequacy. Yet as the functionalities of Montenegrin eServices are expected to gradually expand in the upcoming years, assistive technical communication must aim to handle the higher extents of service complexity. © 2023 IEEE.

关键词：

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：