检索结果-内蒙古大学图书馆

Emerging Smart Technologies and Applications (eSmarTA), International Conference on

作者： Abdulfattah E. Ba Alawi Ahmed N. Nusari Ferhat Bozkurt İbrahim Yücel Özbek Computer Engineering Department Faculty of Engineering Ataturk University Erzurum Turkey Software Engineering Department Faculty of Engineering & IT Taiz University Taiz Yemen Electrical and Electronics Engineering Department Faculty of Engineering Ataturk University Erzurum Turkey Computer and Control Engineering Department Faculty of Engineering Sana’a University Sana’a Yemen Electrical and Electronics Department Faculty of Engineering Ataturk University Erzurum Turkey

ISBN: (数字)9798350354133

ISBN: (纸本)9798350354140

The Arabic language is one of the most common spoken languages. Due to the complex structure and extensive range of potential meanings of Arabic texts, it is a challenging task to perform sentiment analysis using Natural Language Processing (NLP) approaches. Traditional methods of sentiment analysis often fail to perform Arabic sentiment analysis tasks. In this study, a fusion majority voting technique was employed to enhance the performance of Arabic sentiment analysis. The proposed method integrates four models (i.e. AraBERv1, MARBERT, Modified MARBERT, and AraBERv2 ) to analyze Arabic sentiments. Then, the outputs of these four models were forwarded to a fusion stage the perform majority voting and show the corresponding identified class. This technique is called FusionAraSA which relies on integrating four models and fusion to expand the application of pre-trained models. The FusionAraSA approach shows promising performance reaching more than 95% in terms of both accuracy and F1 Score utilizing two publicly available Arabic datasets. The results obtained using FusionAraSA illustrate the exceptional performance and the feasibility of this model in Arabic sentiment analysis. Additionally, the findings highlight the remarkable potential of the fusion model and underscore the necessity for further research to unravel the intricacies of Arabic dialects. Moreover, the FusionAraSA model represents a major step towards building more complex, culturally sensitive, and technologically advanced Arabic language analysis architecture.

关键词： Sentiment analysis Analytical models Accuracy Architecture Buildings Task analysis

来源：评论

学校读者我要写书评

暂无评论

Intelligent pedagogic agents (IPAs) in GEA2, an educational game to teach STEM topics 10th

Intelligent pedagogic agents (IPAs) in GEA2, an educational ...

引用

10th International Conference in Methodologies and Intelligent Systems for Technology Enhanced Learning, MIS4TEL 2020

作者： Ferro, Lauren S. Sapio, Francesco Mecella, Massimo Temperini, Marco Terracina, Annalisa Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy

ISBN: (纸本)9783030522865

In this work we present an Intelligent Pedagogic Agent (IPA) we developed to act within the Gea2: A New Earth educational game. The IPA was designed and developed based on a pilot study, where information was gathered from students and teachers of four classes of two high school institutions. The IPA has the ability to be conversational in Natural Language, and is also capable of autonomous intervention through the use of unsolicited hints during learner’s gameplay. The autonomous intervention is based on both the detection of player’s emotions, and the state of player’s game. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

关键词： Serious games

来源：评论

学校读者我要写书评

暂无评论

Meta-Analysis of cortical inhibitory interneurons markers landscape and their performances in scRNA-seq studies.

Meta-Analysis of cortical inhibitory interneurons markers la...

引用

2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021

作者： Martini, Lorenzo Bardini, Roberta DI Carlo, Stefano Politecnico di Torino Control and Computer Engineering Department Torino10129 Italy

ISBN: (纸本)9781665401265

The mammalian cortex contains a great variety of neuronal cells. In particular, GABAergic interneurons, which play a major role in neuronal circuit function, exhibit an extraordinary diversity of cell types. In this regard, single-cell RNA-seq analysis is crucial to study cellular heterogeneity. To identify and analyze rare cell types, it is necessary to reliably label cells through known markers. In this way, all the related studies are dependent on the quality of the employed marker genes. Therefore, in this work, we investigate how a set of chosen inhibitory interneurons markers perform. The gene set consists of both immunohistochemistry-derived genes and single-cell RNA-seq taxonomy ones. We employed various human and mouse datasets of the brain cortex, consequently processed with the Monocle3 pipeline. We defined metrics based on the relations between unsupervised cluster results and the marker expression. Specifically, we calculated the specificity, the fraction of cells expressing, and some metrics derived from decision tree analysis like entropy gain and impurity reduction. The results highlighted the strong reliability of some markers but also the low quality of others. More interestingly, though, a correlation emerges between the general performances of the genes set and the experimental quality of the datasets. Therefore, the proposed method allows evaluating the quality of a dataset in relation to its reliability regarding the inhibitory interneurons cellular heterogeneity study. © 2021 IEEE.

关键词： RNA

来源：评论

学校读者我要写书评

暂无评论

Sparsification of Deep Neural Networks via Ternary Quantization

Sparsification of Deep Neural Networks via Ternary Quantizat...

引用

IEEE Workshop on Machine Learning for Signal Processing

作者： Luca Dordoni Andrea Migliorati Giulia Fracastoro Sophie Fosson Tiziano Bianchi Enrico Magli Department of Electronics and Telecommunications Politecnico di Torino Turin Italy Department of Control and Computer Engineering Politecnico di Torino Turin Italy

ISBN: (数字)9798350372250

ISBN: (纸本)9798350372267

In recent years, the demand for compact deep neural networks (DNN s) has increased consistently, driven by the necessity to deploy them in environments with limited resources such as mobile or embedded devices. Our work aims to tackle this challenge by proposing a combination of two techniques: sparsification and t ernarization o f network parameters. We extend the plain binarization by introducing a sparsification interval centered around O. The network parameters falling in this interval are set to 0 and effectively removed from the net-work topology. Despite the increased complexity required by the ternarization scheme compared to a binary quantizer, we obtain remarkable sparsity rates that yield parameter distri-butions with significantly compressible sources with entropy lower than 1 bits/symbol.

关键词： Training Quantization (signal) Accuracy Network topology Conferences Artificial neural networks Machine learning Entropy Topology Complexity theory

来源：评论

学校读者我要写书评

暂无评论

Robot-assisted superficial hyperthermia treatments: the ROBHOT system

Robot-assisted superficial hyperthermia treatments: the ROBH...

引用

IEEE International Conference on Automation Science and engineering (CASE)

作者： Marco Ferro Pierfrancesco Pavoni Marilena Vendittelli Department of Department of Computer Control and Management Engineering "Antonio Ruberti" Sapienza University of Rome Rome Italy Medlogix Srl Rome Italy

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

This paper presents the design, implemetation and experimental validation of the ROBHOT Technology Demonstrator, a new system for robot-assisted superficial hyperthermia treatments. The system features impedance-based interaction control for accurate and safe delivery of the treatment, a digital twin of the operative setup, communication modules with a pre-operative planning software. Results of the system validation in a relevant experimental environment are reported. A video clip presenting an overview of the system and the validation experiments is available at https://***/rNxMaD-teNo.

关键词： Accuracy Tracking Force Software Safety Planning Hyperthermia System validation Robots Oscillators

来源：评论

学校读者我要写书评

暂无评论

Broadband usage for rural communities in the North Island of Aotearoa New Zealand

引用

Intelligent and Converged Networks 2022年第3期3卷 244-259页

作者： Ming Xiang William Liu Edmund Lai Jairo Gutierrez Luca Chiaraviglio Jinsong Wu Control Science and Engineering South China University of TechnologyGuangzhou 510300Chinaand also with the South China Sea Institute of Planning and Environmental ResearchMinistry of Natural ResourcesGuangzhou 510300China Department of Computer Science and Software Engineering School of EngineeringComputer and Mathematical SciencesAuckland University of TechnologyAuckland 1010New Zealand Department of Electronic Engineering University of Rome“Tor Vergata”Rome 00133Italy Consorzio Nazionale Interuniversitario per le Telecomunicazioni(CNIT) Parma 43124Italy Department of Electrical Engineering Universidad de ChileSantiago 92101Chile

New Zealand government’s Rural Broadband Initiative(RBI)aims to invest 400 million New Zealand dollar to provide 99%of New Zealanders with access to 50 Mbps peak broadband speed,with the remaining 1%at 10 Mbps by *** 2017,stage 1 of the RBI has been completed,and research is needed to find out the level of usage,proficiency,and productivity achieved by ***,a survey was carried out to learn whether the rural residents and their communities are making good use of the new fast broadband *** survey collected data from 217 rural residents from North Island,and the results indicate that about half of the interview respondents are satisfied with the new broadband speed and the reliability which is offered by RBI stage ***,there is about 28%of the respondents disagreed with *** majority of the Internet uses for rural residents are information searching,reading news,online entertainment,and online *** that,only a small proportion of respondents know how to utilize the Internet in their work/business and benefit/profit from it,e.g.,using cloud technology capabilities and online marketing campaigns,*** ***,we argue that information and communications technologies(ICT)adoption is not only the availability of the infrastructure but also the beneficial outcomes of Internet *** other words,Internet skills in-depth training and education need to catch up with the infrastructure deployment,which is useful to fuel the digital productivity and inclusion for booming rural *** survey data-driven findings presented in this paper could serve as a reference to inform government policymakers and those who wish to create,invest,and take actions to speed up the economic and social growth of rural communities in Aotearoa New Zealand through the Internet while shifting from the Internet speed and traffic volume-driven to a more effective Internet connectivity and value-added driven rural economy.

关键词： data driven approach data-supported decision and policy making digital exclusion information and communications technologies(ICT)adoption effective connectivity rural broadband usage rural economic development

来源：评论

学校读者我要写书评

暂无评论

Semantic API Alignment: Linking High-level User Goals to APIs

arXiv

引用

arXiv 2024年

作者： Feldt, Robert Coppola, Riccardo The Software Engineering division of Chalmers Institute of Technology Göteborg Sweden The Department of Computer and Control Engineering of Politecnico di Torino Turin Italy

Large Language Models (LLMs) are becoming key in automating and assisting various software development tasks, including text-based tasks in requirements engineering but also in coding. Typically, these models are used to automate small portions of existing tasks, but we present a broader vision to span multiple steps from requirements engineering to implementation using existing libraries. This approach, which we call Semantic API Alignment (SEAL), aims to bridge the gap between a user’s high-level goals and the specific functions of one or more APIs. In this position paper, we propose a system architecture where a set of LLM-powered "agents" match such high-level objectives with appropriate API calls. This system could facilitate automated programming by finding matching links or, alternatively, explaining mismatches to guide manual intervention or further development. As an initial pilot, our paper demonstrates this concept by applying LLMs to Goal-Oriented Requirements engineering (GORE), via sub-goal analysis, for aligning with REST API specifications, specifically through a case study involving a GitHub statistics API. We discuss the potential of our approach to enhance complex tasks in software development and requirements engineering and outline future directions for research. © 2024, CC BY.

关键词： Requirements engineering

来源：评论

学校读者我要写书评

暂无评论

ConQ: Binary Quantization of Neural Networks via Concave Regularization

ConQ: Binary Quantization of Neural Networks via Concave Reg...

引用

IEEE Workshop on Machine Learning for Signal Processing

作者： Andrea Migliorati Giulia Fracastoro Sophie Fosson Tiziano Bianchi Enrico Magli Department of Electronics and Telecommunications Politecnico di Torino Turin Italy Department of Control and Computer Engineering Politecnico di Torino Turin Italy

ISBN: (数字)9798350372250

ISBN: (纸本)9798350372267

The increasing demand for deep neural networks (DNNs) in resource-constrained systems propels the interest in heavily quantized architectures such as networks with binarized weights. However, despite huge progress in the field, the gap with full-precision performance is far from closed. Today's most effective methods for quantization are rooted in proximal gradient descent theory. In this work, we propose ConQ, a novel concave regularization approach to train effective DNNs with binarized weights. Motivated by theoretical investigation, we argue that the proposed concave regularizer, which allows the removal of the singularity point at 0, presents a more effective shape than previously considered models in terms of accuracy and convergence rate. We present a theoretical convergence analysis of ConQ, with specific i nsights o n b oth c onvex a nd n on-convex s ettings. An extensive experimental evaluation shows that ConQ outperforms the accuracy of competing regularization methods for networks with binarized weights.

关键词： Gradient methods Accuracy Quantization (signal) Limiting Shape Conferences Machine learning Artificial neural networks Propulsion Convergence

来源：评论

学校读者我要写书评

暂无评论

Risk-Aware Real-Time Task Allocation for Stochastic Multi-Agent Systems under STL Specifications

arXiv

引用

arXiv 2024年

作者： Engelaar, Maico H.W. Zhang, Zengjie Vlahakis, Eleftherios E. Dimarogonas, Dimos V. Lazar, Mircea Haesaert, Sofie Department of Electrical Engineering Control Systems Group Eindhoven University of Technology Netherlands Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden

This paper addresses the control synthesis of heterogeneous stochastic linear multi-agent systems with real-time allocation of signal temporal logic (STL) specifications. Based on previous work, we decompose specifications into sub-specifications on the individual agent level. To leverage the efficiency of task allocation, a heuristic filter evaluates potential task allocation based on STL robustness, and subsequently, an auctioning algorithm determines the definitive allocation of specifications. Finally, a control strategy is synthesized for each agent-specification pair using tube-based model predictive control (MPC), ensuring provable probabilistic satisfaction. We demonstrate the efficacy of the proposed methods using a multi-shuttle scenario that highlights a promising extension to automated driving applications like vehicle routing. © 2024, CC BY-NC-ND.

关键词： Stochastic systems

来源：评论

学校读者我要写书评

暂无评论

Towards Rigorous Dataset Quality Standards for Deep Learning Tasks in Precision Agriculture: A Case Study Exploration

SSRN

引用

SSRN 2024年

作者： Carraro, Alberto Saurio, Gaetano Marinello, Francesco University of Padova Department of Land Environment Agriculture and Forestry Italy Sapienza University of Rome Department of Computer Control Management and Engineering Italy

Deep Learning (DL) through Convolutional Neural Networks (CNNs) has emerged as a critical player in classifying plant diseases from images. This prominence has intensified the demand for a substantial volume of annotated training data. However, acquiring such data is costly and intricate, fraught with subtle challenges. In the domain of plants, where data collection can be even more complex, this study scrutinises how one dataset was gathered. Specifically, it delves into the nuances of collecting images of grapevine leaves in an open field for a binary classification task, discerning the presence or absence of Esca *** to rigorous dataset quality standards during image collection is paramount in precision agriculture. Errors made in this phase can have devastating repercussions on all subsequent work. For instance, collections of photos may exhibit a consistent disparity in background characteristics between images belonging to different classes. This persistent difference can lead a deep-learning algorithm to learn undesired correlations, even though the algorithm's performances are excellent because the train and test sets possess the same kind of disparity © 2024, The Authors. All rights reserved.

关键词： Deep learning

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：