检索结果-内蒙古大学图书馆

A stochastic production frontier model for evaluating the performance efficiency of artificial intelligence investment worldwide

引用

Decision Analytics Journal 2024年 12卷

作者： Sun, Ying-Chih Cosgun, Ozlem Sharman, Raj Mulgund, Pavankumar Delen, Dursun East Central University Department of Business Administration Information Management and Business Analytics Montclair State University Management Science and Systems University at Buffalo Department of Management Information Systems University of Memphis Department of Management Science and Information Systems Center for Health Systems Innovation Spears School of Business Oklahoma State University Department of Industrial Engineering College of Engineering and Natural Sciences Istinye University

As artificial intelligence (AI) begins to take center stage in technological innovations, it is essential to understand the business value of AI innovation efforts and investments. While some early work at the firm level exists, there is a shortage of literature that takes a larger country-level perspective. This study investigated the effect of AI innovation efforts on production efficiency across countries using stochastic production frontier approaches. In addition, our model also included the traditional economic inputs of capital and labor. We used both the Cobb–Douglas function and Constant Elastic Substitution model specifications. The significant findings of this study are as follows: Innovation efforts in AI measured by the number of AI-related patents and capital investment in AI have a substantial effect on economic output. The significance of AI investments indicates the need for a robust digital infrastructure as a prerequisite for harnessing AI capabilities. The complementary relationship between labor and AI-related patents implies that high-skilled labor is often necessary to incorporate AI inputs into production. However, as AI capabilities develop, they weaken the effect on labor input. The study also distinguishes between AI innovation (research and development activities indicated by AI patents) and the production efficiency of AI investments (return on every dollar invested), highlighting that more AI innovation does not always translate into better production efficiency. The findings indicate that while the United States leads innovation in AI, the UK has the best production efficiency. China ranked fourth in AI innovation and has the lowest production efficiency among the countries included in the study. © 2024 The Author(s)

关键词： Artificial intelligence Cobb–Douglas function Innovation Production efficiency Stochastic production frontier

来源：评论

学校读者我要写书评

暂无评论

Near field radio link design in fat phantom for Wireless Capsule Endoscopy application

Near field radio link design in fat phantom for Wireless Cap...

引用

2022 Malaysia-Japan Workshop on Radio Technology, MJWRT 2022

作者： Kamaruddin, Nur Amalina Kamardin, Kamilia Yamada, Yoshihide Zainudin, Norsiha Arima, Takuji Michishita, Naobumi Takahashi, Masaharu Communication Systems and Network IKohza Department of Electronic Systems Engineering Malaysia-Japan International Institute of Technology Universiti Teknologi Malaysia Kuala Lumpur54100 Malaysia Department of Electrical Engineering Faculty of Engineering University of Malaya Kuala Lumpur50603 Malaysia Dept. of Electronic and Information Engineering Tokyo University of Agriculture and Technology Koganei Tokyo184-8588 Japan National Defense Academy Yokosuka Japan Center for Frontier Medical Engineering Chiba University Chiba Japan

Medical devices such as Wireless Capsule Endoscopy (WCE) that need wireless imaging and monitoring, operating at 402 MHz, is considered to be in the near field region due to the distance being shorter than the wavelength. In this paper, the radio link calculation method in the near field region is investigated. Normal Mode Helical Antenna (NMHA) is used as the transmitter antenna which is placed inside of a fat phantom of 11.6 F/m and the receiver antenna at distance 0.1 to 1.0 m apart. For link budget establishment, parameters such as power density, W and receiver antenna effective area, Ae are investigated through electromagnetic simulation. The distance dependency of W is examined and the result of W 1/(distance)2 is obtained. The relation of Ae of the receiver antenna is found to be the size of the cross-section area of the antenna. A radio link equation is formed by employing W, Ae and other propagation loss factors of a medium and is then compared with the power received, PR and S21 obtained from simulation. The agreement between calculated and simulated results shows that this equation can be used in the near field region. © Published under licence by IOP Publishing Ltd.

关键词： Receiving antennas

来源：评论

学校读者我要写书评

暂无评论

AMulti-Layers information Fused Deep Architecture for Skin Cancer Classification in Smart Healthcare

引用

Computers, Materials & Continua 2025年第6期83卷 5299-5321页

作者： Veena Dillshad Muhammad Attique Khan Muhammad Nazir Jawad Ahmad Dina Abdulaziz AlHammadi Taha Houda Hee-Chan Cho Byoungchol Chang Department of Computer Science HITEC UniversityTaxila47080Pakistan Department of Artificial Intelligence College of Computer Engineering and SciencePrince Mohammad Bin Fahd UniversityAl-Khobar31952Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Center for Computational Social Science Hanyang UniversitySeoul01000Republic of Korea Department of Computer Science Hanynag UniversitySeoul01000Republic of Korea

Globally,skin cancer is a prevalent form of malignancy,and its early and accurate diagnosis is critical for patient *** evaluation of skin lesions is essential,but several challenges,such as long waiting times and subjective interpretations,make this task *** recent advancement of deep learning in healthcare has shownmuch success in diagnosing and classifying skin cancer and has assisted dermatologists in *** learning improves the speed and precision of skin cancer diagnosis,leading to earlier prediction and *** this work,we proposed a novel deep architecture for skin cancer classification in innovative *** proposed framework performed data augmentation at the first step to resolve the imbalance issue in the selected *** proposed architecture is based on two customized,innovative Convolutional neural network(CNN)models based on small depth and filter *** the first model,four residual blocks are added in a squeezed fashion with a small filter *** the second model,five residual blocks are added with smaller depth and more useful weight information of the lesion *** make models more useful,we selected the hyperparameters through Bayesian Optimization,in which the learning rate is *** training the proposed models,deep features are extracted and fused using a novel information entropy-controlled Euclidean Distance *** final features are passed on to the classifiers,and classification results are ***,the proposed trained model is interpreted through LIME-based localization on the HAM10000 *** experimental process of the proposed architecture is performed on two dermoscopic datasets,HAM10000 and *** obtained an improved accuracy of 90.8%and 99.3%on these datasets,***,the proposed architecture returned 91.6%for the cancer *** conclusion,the proposed architecture accuracy is compared with several pre-trained and state-of-the-art

关键词： Smart health skin cancer internet of things deep learning residual blocks fusion optimization

来源：评论

学校读者我要写书评

暂无评论

Identification of Additive Continuous-time systems in Open and Closed Loop

arXiv

引用

arXiv 2024年

作者： González, Rodrigo A. Classens, Koen Rojas, Cristian R. Welsh, James S. Oomen, Tom Control Systems Technology Section Department of Mechanical Engineering Eindhoven University of Technology Eindhoven Netherlands Division of Decision and Control Systems KTH Royal Institute of Technology Stockholm10044 Sweden School of Engineering University of Newcastle Callaghan2308 NSW Australia Delft Center for Systems and Control Delft University of Technology Delft Netherlands

When identifying electrical, mechanical, or biological systems, parametric continuous-time identification methods can lead to interpretable and parsimonious models when the model structure aligns with the physical properties of the system. Traditional linear system identification may not consider the most parsimonious model when relying solely on unfactored transfer functions, which typically result from standard direct approaches. This paper presents a novel identification method that delivers additive models for both open and closed-loop setups. The estimators that are derived are shown to be generically consistent, and can admit the identification of marginally stable additive systems. Numerical simulations show the efficacy of the proposed approach, and its performance in identifying a modal representation of a flexible beam is verified using experimental data. © 2024, CC BY-NC-ND.

关键词： Continuous time systems

来源：评论

学校读者我要写书评

暂无评论

Effects of various information scenarios on layer-wise relevance propagation-based interpretable convolutional neural networks for air handling unit fault diagnosis

引用

Building Simulation 2024年第10期17卷 1709-1730页

作者： Chenglong Xiong Guannan Li Ying Yan Hanyuan Zhang Chengliang Xu Liang Chen School of Urban Construction Wuhan University of Science and TechnologyWuhan 430065China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing University of Information Science and TechnologyNanjing 210044China Shandong Key Laboratory of Intelligent Buildings Technology School of Information and Electrical EngineeringShandong Jianzhu UniversityJinan 250101China Key Laboratory of Low-grade Energy Utilization Technologies and Systems(Chongqing University) Ministry of Education of ChinaChongqing UniversityChongqing 400044 China State Key Laboratory of Green Building in Western China Xi’an University of Architecture&TechnologyXi’an 710055China

Deep learning(DL),especially convolutional neural networks(CNNs),has been widely applied in air handling unit(AHU)fault diagnosis(FD).However,its application faces two major ***,the accessibility of operational state variables for AHU systems is limited in practical,and the effectiveness and applicability of existing DL methods for diagnosis require further ***,the interpretability performance of DL models under various information scenarios needs further *** address these challenges,this study utilized publicly available ASHRAE RP-1312 AHU fault data and employed CNNs to construct three FD models under three various information ***,the layer-wise relevance propagation(LRP)method was used to interpret and explain the effects of these three various information scenarios on the CNN *** R-threshold was proposed to systematically differentiate diagnostic criteria,which further elucidates the intrinsic reasons behind correct and incorrect decisions made by the *** results showed that the CNN-based diagnostic models demonstrated good applicability under the three various information scenarios,with an average diagnostic accuracy of 98.55%.The LRP method provided good interpretation and explanation for understanding the decision mechanism of CNN models for the unlimited information *** the very limited information scenario,since the variables are restricted,although LRP can reveal key variables in the model’s decision-making process,these key variables have certain limitations in terms of data and physical explanations for further improving the model’s ***,an in-depth analysis of model parameters—such as the number of convolutional layers,learning rate,βparameters,and training set size—was conducted to examine their impact on the interpretative *** study contributes to clarifying the effects of various information scenarios on the diagnostic performance and interpr

关键词： air handling unit(AHU) fault diagnosis convolutional neural network(CNN) layer-wise relevance propagation(LRP) interpretation and explanation various information scenarios

来源：评论

学校读者我要写书评

暂无评论

Feasibility Guaranteed Traffic Merging Control Using Control Barrier Functions

arXiv

引用

arXiv 2022年

作者： Xu, Kaiyuan Xiao, Wei Cassandras, Christos G. Division of Systems Engineering Center for Information and Systems Engineering Boston University BrooklineMA02446 United States Computer Science and Artificial Intelligence Lab Massachusetts Institute of Technology United States

We consider the merging control problem for Connected and Automated Vehicles (CAVs) aiming to jointly minimize travel time and energy consumption while providing speed-dependent safety guarantees and satisfying velocity and acceleration constraints. Applying the joint optimal control and control barrier function (OCBF) method, a controller that optimally tracks the unconstrained optimal control solution while guaranteeing the satisfaction of all constraints is efficiently obtained by transforming the optimal tracking problem into a sequence of quadratic programs (QPs). However, these QPs can become infeasible, especially under tight control bounds, thus failing to guarantee safety constraints. We solve this problem by deriving a control-dependent feasibility constraint corresponding to each CBF constraint which is added to each QP and we show that each such modified QP is guaranteed to be feasible. Extensive simulations of the merging control problem illustrate the effectiveness of this feasibility guaranteed controller. Copyright © 2022, The Authors. All rights reserved.

关键词： Quadratic programming

来源：评论

学校读者我要写书评

暂无评论

Statistical Analysis of Block Coordinate Descent Algorithms for Linear Continuous-time System Identification

arXiv

引用

arXiv 2024年

作者： González, Rodrigo A. Classens, Koen Rojas, Cristian R. Welsh, James S. Oomen, Tom The Department of Mechanical Engineering Eindhoven University of Technology Eindhoven Netherlands The Division of Decision and Control Systems KTH Royal Institute of Technology Stockholm Sweden The School of Engineering University of Newcastle NSW Australia The Delft Center for Systems and Control Delft University of Technology Delft Netherlands

Block coordinate descent is an optimization technique that is used for estimating multi-input single-output (MISO) continuous-time models, as well as single-input single output (SISO) models in additive form. Despite its widespread use in various optimization contexts, the statistical properties of block coordinate descent in continuous-time system identification have not been covered in the literature. The aim of this paper is to formally analyze the bias properties of the block coordinate descent approach for the identification of MISO and additive SISO systems. We characterize the asymptotic bias at each iteration, and provide sufficient conditions for the consistency of the estimator for each identification setting. The theoretical results are supported by simulation examples. © 2024, CC BY-NC-ND.

关键词： Additives

来源：评论

学校读者我要写书评

暂无评论

A Method for Searching Documents using Knowledge Bases 2021

A Method for Searching Documents using Knowledge Bases

引用

23rd International Conference on information Integration and Web Intelligence, iiWAS 2021

作者： Aso, Taro Amagasa, Toshiyuki Kitagawa, Hiroyuki Graduate School of Systems and Information Engineering University of Tsukuba Japan Center for Computational Sciences University of Tsukuba Japan

ISBN: (纸本)9781450395564

We propose a document search method using knowledge bases (KBs) to explore documents through mentioned entities and their relationship. Documents are one of the most popular media to accumulate and transmit information. People often want to search for necessary documents or explore necessary information across multiple documents. However, it is generally difficult to find the target documents (or information) in particular when the search conditions are complicated, or the conditions are implicitly represented. Thus, users cannot represent their information needs in terms of a query, such as keywords. To address this problem, we exploit knowledge bases (KBs). More precisely, we extract entities mentioned in the documents and link them with the KBs, allowing users to explore the documents through the entities and their relationships. Furthermore, we propose a user-friendly interface to query documents and the relevant information. We experimentally show the proposed system performs better than the search system with a popular full-text search engine in some search tasks. © 2021 ACM.

关键词： Search engines

来源：评论

学校读者我要写书评

暂无评论

NavPathNet: Onboard Trajectory Prediction for Two-Wheelers using Navigation Maps

NavPathNet: Onboard Trajectory Prediction for Two-Wheelers u...

引用

IEEE Symposium on Intelligent Vehicle

作者： Fabian Immel Alessandro Moia Haohao Hu Intelligent Systems and Production Engineering FZI Research Center for Information Technology Karlsruhe Germany Robert Bosch GmbH Gerlingen-Schillerhoehe Germany Institute of Measurement and Control Systems Karlsruhe Institute of Technology (KIT) Karlsruhe Germany

ISBN: (数字)9798350348811

ISBN: (纸本)9798350348828

This work proposes NavPathNet, a graph neural network based trajectory prediction system capable of accurately predicting the trajectory of a two-wheeler with onboard sensors for up to 6 seconds using the vehicle state and only navigation map information. Possible paths are generated from the local road network in a regular navigation map using Bézier curves and a multimodal prediction captures the different possibilities of the road network. A kinematic model integrated into the network allows to give guarantees on physical realism and on motion constraints, essential for safety-relevant *** proposed system was trained and evaluated on an in-house e-bike data set and was able to reach a top 1 final displacement error of 2 m for four seconds and 3.8 m for six seconds of prediction time, significantly outperforming other baselines. The improvement in prediction quality compared to purely physical models opens up new possibilities for driver assistance systems in connected vehicles.

关键词： Connected vehicles Navigation Intelligent vehicles Roads Kinematics Predictive models Graph neural networks

来源：评论

学校读者我要写书评

暂无评论

Towards a Modular Machine Learning Architecture for Human Activity Recognition

Towards a Modular Machine Learning Architecture for Human Ac...

引用

IEEE Sensors Applications Symposium, SAS

作者： Marc Schroth Dennis Birkenmaier Wilhelm Stork Dept. of Embedded Systems and Sensors Engineering FZI Research Center for Information Technology Karlsruhe Germany Institute of Information Processing Technologies Karlsruhe Institute of Technology KIT Karlsruhe Germany

ISBN: (数字)9798350369250

ISBN: (纸本)9798350369267

As the population grows older and older, technology is used to mitigate the effects on the society. In order to support people living as long in their preferred environment as possible, human activity recognition plays an important role to develop systems that suit the needs of humans. With the advent of machine learning the techniques used for the activity recognition changed drastically. Often times so called end - to-end learning is applied, which is inherently flawed in terms of flexibility, as the whole model needs to be retrained when parts of the system change, e.g. a change of the used sensor technology. The system proposed in this paper consists of seven sensor nodes which comprise a wireless sensor network. Each node measures the received signal strength and is attached to a kitchen utensil, including one gateway node. Based on this data, a modular machine learning architecture is developed, which is capable of recognising each sub step in the cooking recipe and the recipe as a whole. Experimental studies show promising results and are detailed in this paper. With this information, the system gains the ability to support the user by recognising missing or wrong steps in the cooking process, which can be of direct use for elderly people with mild cognitive impairments in order for them to be able living in their preferred environment as long as possible.

关键词： Wireless sensor networks Sociology Machine learning Logic gates Human activity recognition Synthetic aperture sonar Statistics

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：