检索结果-内蒙古大学图书馆

Estimation of Price Elasticity of Demand for Higher-class Car Travel on Commuter Trains

Quarterly Report of RTRI (Railway Technical Research Institute) 2025年第1期66卷 51-57页

作者： Matsumoto, Ryosuke Data Analytics Laboratory Information and Communication Technology Division

Higher-class Car (seat upgrade) fares on local trains affect not only demand for higher-class travel, but also ordinary class demand on the same trains. It is therefore important to estimate the impact of price changes on the demand for Higher-class Cars, especially during weekdays’ commuting time when overcrowding is at a high level. This research focuses on the two-stage pricing structure of Higher-class Car fares where prices jump by 210 JPY when the travel distance exceeds 50 km in the Tokyo area. Then, this research estimates the price elasticity using regression discontinuity design. The estimation results show that the elasticity is significantly larger than one, which means that the price sensitivity to demand is at a high level. Pricing decisions should be made carefully based on the estimation results of price elasticity and current overcrowding levels in Ordinary and Higher-class Cars. © 2025 Ken-yusha Inc.. All rights reserved.

关键词： Cost estimating

来源：评论

学校读者我要写书评

暂无评论

Evaluation Method for Implementation Effects of Disaster Countermeasures for Freight Railway Networks

引用

Quarterly Report of RTRI (Railway Technical Research Institute) 2023年第3期64卷 211-216页

作者： Okuda, Daiki Watanabe, Takuya Nakagawa, Shingo Suzuki, Takamasa Fukasawa, Noriko Data Analytics Laboratory Information and Communication Technology Division Japan Japan

We developed a method for evaluating the effect of disaster countermeasures using two indices: volume of freight transportation on a freight railway network during disruptions caused by natural disasters and sum of costs borne by freight railway operators during restoration periods. The evaluation method aims to support train operator decision-making regarding implementation of disaster countermeasures. A case study applying the evaluation method demonstrated that the method could provide appropriate evaluation results contributing to decision-making by operators. © 2023 Ken-yusha Inc.. All rights reserved.

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

Support System for Designing an Operation Plan of Extra Trains on High-Speed Railways

引用

Japanese Railway Engineering 2023年第1期63卷 1-3页

作者： Okuda, Daiki Matsumoto, Ryosuke Fukasawa, Noriko Data Analytics Laboratory Information and Communication Technology Division Railway Technical Research Institute Japan

We developed a method that can estimate passenger demand for each day in units of 30 minutes, and also developed a system that can propose extra trains that should be operated based on the method. The purpose of these developments is to support designing of a reasonable operation plans of extra trains on high-speed railways. The validity of the system was confirmed through accuracy verification using actual transportation data on one of the high-speed railway lines in Japan. © 2023 Japan Railway Engineers' Association. All rights reserved.

关键词： Railroad transportation

来源：评论

学校读者我要写书评

暂无评论

Experimental Design of Extractive Question-Answering Systems: Influence of Error Scores and Answer Length

引用

Journal of Artificial Intelligence Research 2024年 80卷 87-125页

作者： Farea, Amer Emmert-Streib, Frank Predictive Society and Data Analytics Lab Faculty of Information Technology and Communication Sciences Tampere University Tampere33100 Finland Faculty of Engineering and Information Technology Taiz University Taiz Yemen

Question-answering (QA) systems are becoming more and more important because they enable human-computer communication in a natural language. In recent years, significant progress has been made with transformer-based models that leverage deep learning in combination with large amounts of text data. However, a significant challenge with QA systems lies in their complexity rooted in the ambiguity and flexibility of a natural language. This makes even their evaluation a formidable task. For this reason, in this study, we focus on the evaluation of extractive question-answering (EQA) systems by conducting a large-scale analysis of distilBERT using benchmark data provided by the Stanford Question Answering dataset (SQuAD). Specifically, the main objectives of this paper are fourfold. First, we study the influence of the answer length on the performance and we demonstrate that there is an inverse correlation between both. Second, we study differences in exact match (EM) measures because there are different definitions commonly used in the literature. As a result, we find that despite the fact that all of those measures are named"exact match" these measures are actually different from each other. Third, we study the practical relevance of these different definitions because due to the ambivalent meaning of"exact match" in the literature, it is often unclear if reported improvements are genuine or only due to a change in the exact match measure. Importantly, our results show that differences between differently defined EM measures are in the same order of magnitude as reported differences found in the literature. This raises concerns about the robustness of reported results. Fourth, we provide guidelines to improve the experimental design of general EQA studies, aiming to enhance performance evaluation and minimize the potential for spurious results. ©2024 The Authors. Published by AI Access Foundation under Creative Commons Attribution License CC BY 4.0.

关键词： Large datasets

来源：评论

学校读者我要写书评

暂无评论

Acceleration Evaluation of a High-Speed Railway PC Box Girder Bridge with Slab Track 41st

Acceleration Evaluation of a High-Speed Railway PC Box Girde...

引用

41st IMAC, A Conference and Exposition on Structural Dynamics, 2023

作者： Yotsui, Haruki Matsuoka, Kodai Kaito, Kiyoyuki Department of Global Architecture Graduate School of Engineering Osaka University Osaka Suita-City Japan Data Analytics in Information and Communication Technology Division Railway Technical Research Institute Tokyo Kokubunji-City Japan

ISBN: (纸本)9783031366628

The resonance of railway bridges that occurs under high-speed trains passage is an important academic and practical issue. The bridge design code in Europe (Eurocode) sets an upper limit of 5 m/s2 on the bridge deck acceleration for a slab type track. However, the performance of high-speed railway bridges regarding train-induced deck acceleration specified in Eurocode has not been sufficiently verified. In this study, a slab track type PC box girder bridge in Japanese high-speed railway is targeted, and multipoint acceleration measurement is conducted. Based on the measurement results, the global and deck local modal characteristics are identified with ERA method, and the maximum deck acceleration is evaluated. As a result, the maximum deck acceleration of the bridge is much lower than the Eurocode limit value of 5 m/s2 even under the resonance condition. Unlike previous reports for European composite box girder bridges, the main deck vibration modes of the bridge are over 40 Hz, thus the deck local vibration did not affect the evaluation of deck acceleration. © 2024, The Society for Experimental Mechanics, Inc.

关键词： Acceleration

来源：评论

学校读者我要写书评

暂无评论

AKDC: Ambiguous Kernel Distance Clustering Algorithm for COVID-19 CT Scans Analysis

引用

IEEE Transactions on Systems, Man, and Cybernetics: Systems 2024年第10期54卷 6218-6229页

作者： Singh, Pritpal Huang, Yo-Ping The Quantum Optimization Research Lab Department of Data Science and Analytics Central University of Rajasthan Ajmer305817 India National Taipei University of Technology Department of Electrical Engineering Taipei10608 Taiwan National Taipei University Department of Computer Science and Information Engineering New Taipei City23741 Taiwan Chaoyang University of Technology Department of Information and Communication Engineering Taichung41349 Taiwan

Conventional soft clustering algorithms perform well on linearly distributed features, but their performance degrades on nonlinearly distributed features in high-dimensional space. In this study, a novel soft clustering algorithm, the ambiguous kernel distance clustering (AKDC) algorithm, is presented. This algorithm is developed by applying ambiguous set theory and the Gaussian kernel function. The ambiguous set theory defines the ambiguities inherent in each feature with four membership values: 1) true;2) false;3) true-ambiguous;and 4) false-ambiguous. The degree of membership values here forms a low-dimensional feature space that is not linearly distributed. Therefore, these nonlinearly distributed membership values are mapped into a high-dimensional feature space using the Gaussian kernel function. This study focuses on performing cluster analysis of computerized tomography scans of COVID-19 (CTSC-19) cases using AKDC. COVID-19, recognized as one of the most life-threatening diseases of this century, is highly contagious, and early diagnosis may prevent one-to-one transmission. Extensive empirical studies have been conducted with different types of CTSC-19 to demonstrate its effectiveness against existing kernel-based clustering and nonkernel-based clustering algorithms, namely mercer kernel fuzzy c-mean (MKFCM), kernel generalized FCM (KGFCM), kernel intuitionistic fuzzy entropy c-means (KIFECMs), morphological reconstruction and membership filtering clustering (FRFCM), and intuitionistic FCM based on membership information transferring and similarity measurements (IFCM-MS). The effectiveness of the proposed algorithm compared to the existing algorithms is evaluated using standard statistical metrics, such as dice index (DI), Jaccard index (JI), structural similarity index (SI), and correlation coefficient (CC). The empirical results show that AKDC is more effective than existing algorithms based on DI, JI, SI, and CC. © 2013 IEEE.

关键词： Clustering algorithms

来源：评论

学校读者我要写书评

暂无评论

Prediction of circularity of the holes in electrical discharge machining of inconel alloy using machine learning technique

引用

Interactions 2024年第1期245卷 1-10页

作者： Sujatha, M. Kavitha, B.C. Vimalarani, G. David, D. Beulah Muthukumar, K. Ram, S. Department of Electrical and Electronics Engineering Easwari Engineering College Chennai India Department of Electronics and Communication Engineering Hindustan Institute of Technology and Science Chennai India Department of Data Analytics Institute of Information Technology Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Thandalam Tamilnadu Chennai India Department of Electrical and Electronics Engineering Sri Krishna College of Engineering and Technology Coimbatore India

Accuracy and finishing of the component is playing an essential role in metal forming process. The quality of the product is depending on accuracy of the shape and size. The measurement of holes is a challenging task in electric discharge machining (EDM) of materials. Sometimes, the diameter of the holes are different and its seems to be conical shape. The circularity of the hole is not maintained due to over current, low voltage and improper electrode materials. In this article, the circularity of the holes and its dimensions are analyzed by coordinate measuring machine (CMM). The experimental results are compared with predicted results with the aid of machine learning technique through regularized random forest (RRF) model. Inconel 718 alloy is used as a work material for this experimental investigation. The material characterization and its performance against the EDM process are studied. Prediction of circularity of the holes by machining of inconel alloy is perfectly done by machine learning technique. It’s used to enhance the accuracy of the hole and performance of the process. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Metal forming

来源：评论

学校读者我要写书评

暂无评论

An Ambiguous Edge Detection Method for Computed Tomography Scans of Coronavirus Disease 2019 Cases

引用

IEEE Transactions on Systems, Man, and Cybernetics: Systems 2024年第1期54卷 352-364页

作者： Singh, Pritpal Huang, Yo-Ping Central University of Rajasthan Quantum Optimization Research Lab Department of Data Science and Analytics Ajmer305817 India Department of Electrical Engineering National Penghu University of Science and Technology Magong88046 Taiwan The Department of Electrical Engineering National Taipei University of Technology Taipei10608 Taiwan The Department of Computer Science and Information Engineering National Taipei University New Taipei City23741 Taiwan The Department of Information and Communication Engineering Chaoyang University of Technology Taichung41349 Taiwan

Recently, the coronavirus disease of 2019 (COVID-19), as named by the World Health Organization (WHO), has spread to over 200 countries. The WHO has declared this disease as a worldwide public health emergency. One of the most difficult tasks in combating this epidemic is to identify and segregate the afflicted people. The reverse transcription-polymerase chain reaction test (RT-PCR) is the most common pathology test used to diagnose this infection. Studies show that the RT-PCR test has a low-positive rate and sometimes becomes ineffective in diagnosing infection. In some cases, computed tomography (CT) scans reveal acute pneumonia and pulmonary anomalies. Therefore, CT scans are used together with RT-PCR tests to confirm infected people. Existing artificial intelligence and machine learning techniques require a large number of CT scans for training, which is a time-consuming process. Visual inspection shows that most CT scans of COVID-19 cases have broken, blurred, and ambiguous edges for infectious areas. Another major issue with these images is the heterogeneous intensity of the pixels, high noise, and low resolution. As a result of all these issues, the problem of effective edges/boundaries of various areas of CT scans of COVID-19 cases cannot be resolved by the current edge detection approach. Indeed, improper selection of edges can lead to an incorrect diagnosis of diseases through CT scans of COVID-19 cases. Therefore, there is an urgent need for a diagnostic method in addition to the RT-PCR test that can extract useful information from the minimum number of chest CT scans of suspected COVID-19 cases. This study introduces a new ambiguous edge detection method (AEDM) for identifying the edges/boundaries of different regions in CT scans of COVID-19 cases. The proposed AEDM is developed on the basis of ambiguous set (AS) theory, which is highly efficient in processing ambiguous pixel information. For simulation purposes, various CT scans of COVID-19 cases are c

关键词： Coronavirus

来源：评论

学校读者我要写书评

暂无评论

Dynamic Charging and Path Planning for UAV-Powered Rechargeable WSNs Using Multi-Agent Deep Reinforcement Learning

引用

IEEE Transactions on Automation Science and Engineering 2025年 22卷 15610-15626页

作者： Betalo, Mesfin Leranso Leng, Supeng Seid, Abegaz Mohammed Abishu, Hayla Nahom Erbad, Aiman Bai, Xiaoshan Shenzhen University College of Mechatronics and Control Engineering Shenzhen518060 China University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Hamad Bin Khalifa University Division of Information and Computing Technology College of Science and Engineering Doha Qatar Shenzhen University College of Mechatronics and Control Engineering National Engineering Laboratory for Big Data System Computing Technology Shenzhen518060 China

Unmanned Aerial Vehicle (UAV)-powered 5G/6G networks integrated with rechargeable wireless sensor networks (RWSNs) offer promising solutions for extending system lifetime, collecting data, and providing computing services and power to sensor nodes (SNs). UAVs offer significant advantages, including exceptional mobility, cost-effective deployment, and the ability to be easily reprogrammed for a wide range of missions. However, the limited onboard power capacity of UAVs, coupled with the lack of dynamic and intelligent charging station (CS) management and inefficient path planning, can lead to SN failure in dynamic mobile environments. To address these challenges, we propose an energy-efficient laser-charged UAV (LCU)-enabled RWSN environment, wherein UAVs, powered by laser beams from ground-based stations, provide services, collect data, and transfer energy to SNs. We formulate a joint optimization problem involving power allocation, dynamic charging strategy (DCS), and path planning to minimize task completion time and sensor node death time. Given the NP-hard nature of the problem, we employ a stochastic game model based on a Markov decision process (MDP) for its solution. To solve this problem, we propose a deep reinforcement learning (DRL) based algorithm that enables real-time charging scheduling decisions while optimizing network performance. We introduce a multi-agent double deep Q-network (MA-DDQN) model to determine the optimal trajectories for all UAVs in large and complex environments. Simulation results demonstrate that the MA-DDQN approach outperforms state-of-the-art techniques, showing significant improvements in terms of average delay, energy consumption, and task completion time. © 2004-2012 IEEE.

关键词： Stochastic models

来源：评论

学校读者我要写书评

暂无评论

Future-Ready Security in the Cloud with Post-Quantum Encryption

Future-Ready Security in the Cloud with Post-Quantum Encrypt...

引用

2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Dey, Kunal Chaudhary, Chetan Balaji, K.A. Department of Data Analytics and Mathematical Sciences Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Presidency University Department of Electronics and Communication Engineering Karnataka Bangalore India

ISBN: (纸本)9798350357769

Since the dawn of the web and its widespread usage, privacy of data has been a significant problem. Multiple systems have been suggested;however, data breaches still happen often. The advent of quantum science suggests a pressing need to develop a paradigm that would provide acceptable security of information for both conventional and quantum computer technology, since encrypting is now the most popular way of cloud data protection. Thus, although some encrypted systems will withstand the test of the quantum computer, the majority will become vulnerable and out-of-date. The article suggests a model that entails using an instance of the McElwee digital currency to secure restricted data, which is expected to displace Rivest Shamir Ad in the age of quantum science, and a version of the extent shortened dependent ring units' digital currency to safeguard cloud customer information. The suggested McElwee technique's modelling revealed that it had a lower temporal complexity than the current McElwee cryptosystem. The reliability of the suggested algorithms is further enhanced by the new tuning of the values for Sand P. Furthermore, the simulation of the suggested NTRU technique showed that, when compared to the current NTRU cryptosystem, the new NTRU system had a better time hardness. © 2023 IEEE.

关键词： Authorization and authentication Cloud technology Code-based cryptosystems Cryptography data security Hybrid cloud Lattice-based cryptosystems NTRU cryptosystem Post-Quantum Cryptography Quantum computing

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：