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检索条件"丛书名=Lecture Notes in Networks and Systems"

共 9495 条记录，以下是691-700 订阅

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Correlation of Spatiotemporal and EMG Measures with Lower Extremity Fugl-Meyer Assessment Score in Post-Stroke Walking 6th

Correlation of Spatiotemporal and EMG Measures with Lower Ex...

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6th Iberian Robotics Conference (Robot)

作者： Pinheiro, Cristiana Abreu, Luis Figueiredo, Joana Santos, Cristina P. Univ Minho Ctr MicroElectroMechan Syst CMEMS P-4800058 Guimaraes Portugal Univ Minho LABBELS Associat Lab Braga Portugal

ISBN: (纸本)9783031591662;9783031591679

Lower Extremity Fugl-Meyer Assessment (FMA-LE) is recommended as the primary outcome for assessing motor function in post-stroke population. However, the subjectivity, dependency on professional experience, and time-consuming visual inspection by healthcare professionals limit the use of FMALE in clinical practice. Contrarily to clinical scales, sensor-based assessments can automatically provide objective measurements of motor function. This work advances literature by evaluating the Spearman correlation between the FMA-LE clinical scores and both spatiotemporal and electromyographic (EMG) measures, acquired during different mobility walking tasks (self-selected speed, maximum speed, maximum cadence, maximum step length, and maximum step height). Data were extracted from ARRA dataset, including 27 post-stroke participants. The results showed that step length (0.44 <= r <= 0.60), stride time (-0.48 <= r <= -0.40), and cadence (0.40 <= r <= 0.46) spatiotemporal measures, and peak power frequency (PKF) EMG measure of gluteus medius (r = 0.42), lateral hamstring (0.40 <= r <= 0.46), and vastus medialis (0.42 <= r <= 0.45) muscles revealed significant strong correlations in multiple walking tasks. Overall, spatiotemporal measures presented higher correlations with FMA-LE than EMG measures. These findings are promising for future research to develop artificial intelligence methods to estimate the Lower FMA clinical scores for motor assessment, maximizing its use in clinical practice.

关键词： Healthcare Automation Human Motor Assessment Sensor-based Assessment

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Hesitant Intuitionistic Fuzzy Cognitive Map Based Fuzzy Time Series Forecasting Method 1

引用

International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Fulara, Suraj Prakash Pant, Shivani Pant, Manish Kumar, Sanjay Govind Ballabh Pant Univ Agr & Technol Dept Math Stat & Comp Sci Pantnagar 263145 Uttarakhand India Invertis Univ Dept Math Bareilly 243123 Uttar Pradesh India

ISBN: (数字)9783031700187

ISBN: (纸本)9783031700170;9783031700187

Intuitionistic fuzzy cognitive maps (IFCMs) have been proven effective in modeling and forecasting stationary time series with hesitancy and uncertainty. However, challenges persist in dealing when in time varying non stationary time series influenced by dynamic statistical features and availability of multiple intuitionistic fuzzy numbers (IFNs) for node in cognitive map. Hesitant intuitionistic fuzzy set (HIFS) provides an efficient tool that allows associating multiple IFNs time series data. In this study, we present the notion of hesitant intuitionistic fuzzy cognitive map (HIFCM) and propose a HIFCM based fuzzy time series forecasting approach. Weights associated with membership and non-membership grades of IFN are optimized by using particle swarm optimization. With a view to reveal the applicability and utility of the suggested forecasting technique, it is applied to time series data of enrolments of the University of Alabama. The model's performance is gauged in accordance to Root mean square error (RMSE), and a low value shows the model's superiority over other previously existing methods.

关键词： Hesitant intuitionistic fuzzy cognitive map Particle swarm optimization time series forecasting

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Text Sentiment Analysis on VIX's Impact on Market Sentiment Dynamics 6th

Text Sentiment Analysis on VIX's Impact on Market Sentiment ...

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6th International Conference on Soft Computing and Data Mining (SCDM)

作者： Liang, Zhuqin Ismail, Mohd Tahir Qu, Huimin Univ Sains Malaysia Sch Math Sci Gelugor 11800 Penang Malaysia Univ Malaya Ctr Sustainable Urban Planning & Real Estate SUPR Fac Built Environm Kuala Lumpur 50603 Malaysia

ISBN: (纸本)9783031669644;9783031669651

This paper examines the impact of the US VIX (Volatility Index) on the sentiment of Chinese investors. We collected comments related to stocks on Sina Weibo from 2019 to 2023, and classified all comments using sentiment analysis with SnowNLP. Based on this, we constructed the Chinese Investor Sentiment Index (CISI). We then studied the relationship between VIX and CISI using Pearson correlation, linear tests, and Granger causality tests, and found that the influence of VIX on Chinese investor sentiment is not significant. However, we observed a positive correlation between the Chinese stock index and sentiment in the comments. Therefore, we conclude that the sentiment in the US stock market is relatively independent from the sentiment of Chinese investors.

关键词： VIX Sentiment Analysis SnowNLP Correlation Granger Causality Tests

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Modified RCH-LEACH (MRCH) for Wireless Sensor networks (WSN) 9th

Modified RCH-LEACH (MRCH) for Wireless Sensor Networks (WSN)

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9th International Congress on Information and Communication Technology (ICICT)

作者： Singh, Rajat Kumar Verma, Shekhar Panchal, Akhilesh Dubey, Sweta Indian Inst Informat Technol Allahabad Allahabad Uttar Pradesh India IIIT Bhopal Bhopal India

ISBN: (纸本)9789819735587;9789819735594

The prime objective of WSN is to carry out the exchange of information using optimized amount of energy. WSN uses various clustering methods to route the information among the randomly deployed sensor nodes. Here, the primary role of nodes is to sense the surrounding information (data). In different clustering approaches, the Cluster Head (CH) selection will be a critical process in saving the node's as well as the network energy. The different parameters have been utilized for important roles in the CH selection as energy efficient. Here, we are presenting a modification in the already published algorithm called RCH-LEACH and known as MRCH for producing it as extra energy efficient. For the CH selection, the modified algorithm used the energy of alive nodes as one of the deciding parameters for choosing the percentage of nodes that will provide the optimal number of CH for efficient usage of energy. MRCH enhances the network lifetime against the same as of the RCH-LEACH and other similar algorithms. MRCH performance is equally good in terms of residual energy. MRCH has also been analyzed under the different scenarios of placement of Base Station (BS).

关键词： Clustering algorithms Residual energy Network lifetime

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Product Performance Measurement System for Ecommerce by Using Fuzzy AHP-TOPSIS

Product Performance Measurement System for Ecommerce by Usin...

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International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Cuvelek, Gozde Oztaysi, Basar Modanisa Elekt Magazacilik & Tic AS Istanbul Turkiye Istanbul Tech Univ Dept Ind Engn TR-34367 Istanbul Turkiye

ISBN: (纸本)9783031671944;9783031671951

Product performance measurement (PPM) is a fundamental aspect of e-commerce management. By maintaining a product performance measurement system e-commerce companies can track and analyze the performance of products which can provide valuable insights and help businesses make informed decisions and improve overall efficiency. PPM provides the necessary insights to optimize various aspects of the business, from product listings and inventory management to marketing strategies and customer satisfaction, ultimately contributing to the overall success of an e-commerce companies. In this paper we use and integrated fuzzy AHP-TOPSIS method to objectively measure the performance of products. A decision model with three criteria and nine sub criteria is established. The criteria used in the model include, economic perspective, customer engagement, and customer behavior. The sub criteria include, gross margin, demand, quantity of returns, impressions, page views, add to cart, page view conversion rate, customer reviews and cart abandonment rate. Fuzzy AHP is used to find the weights of each criteria and sub-criteria and Fuzzy TOPSIS is used to evaluate the products. The results show that the approach provides beneficial results in an efficient way.

关键词： Fuzzy AHP Fuzzy TOPSIS E-commerce Product performance

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Design and Development Cable Driven Parallel Robots Based on EtherCAT 7th

Design and Development Cable Driven Parallel Robots Based on...

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7th International Conference on Green Technology and Sustainable Development

作者： Viet Trung Nguyen Phuoc Tho Tuong Nguyen Luan Vu Truong Trung Duc Tran Hau Le Do Ho Chi Minh City Univ Technol & Educ Ho Chi Minh City Vietnam

ISBN: (纸本)9783031762314;9783031762321

Cable-Driven Parallel Robots (CDPRs) are a type of parallel robot that uses a flexible cable as a driven mechanism to control the moving platform. The biggest advantage of CDPR is that it can be easily configured for large workspaces. However, conventional industrial networks are limited in transmission distance as well as response time, which hinders flexibility as well as limits the expansion of the workspace of large CDPRs. Therefore, the choice of communication technology plays an important role in deploying and ensuring the stability of the robot. With the advantage of high data transmission speed and flexible scalability, EtherCAT is one of the optimal choices for the problem of needing transmission distance between large nodes such as cable robots. This paper studies the important problems of CDPR, such as kinematics, velocity, dynamics, and cable tension distribution, the calculation results are simulated, evaluated, and used to design the controller for CDPR using the EtherCAT communication network. The computational model was experimentally tested on a sample CDPR, and the experimental results were evaluated and analyzed, in addition, the article will discuss the development direction and practical application of CDPR when integrating EtherCAT technology.

关键词： Cable Robot EtherCAT Tesion Distribution Robot Controller

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Arduino Based Safety and Security System 13th

Arduino Based Safety and Security System

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13th Computer Science Online Conference

作者： Alhatmi, Ahlam Said Alnadhiri, Asma Salim Ramanathan, Vallikannu Al Hajri, Hamed Al Lawati, Hala AlZahra Coll Women Muscat Oman

ISBN: (纸本)9783031705946;9783031705953

The availability of security and safety is considered as one of the most important and basic requirements in order to ensure the successful conduct of business and various humanitarian activities.. The idea of this research paper is to design an Arduino-based security and safety system by measuring the level of gas spread in the building, and thus the device sends signal to the mobile phone when the gas leaks more.. This system is implemented using Android and uses a gas sensor device to detect gas. When the rate of gas diffusion increases in the building, the gas sensor senses the gas and sends data to the software to show the rate of gas diffusion. If the result is more than 400 J, the red LED lights up. This will indicate the people to be alert and do the necessary actions.

关键词： Arduino safety and security system gas sensor joules

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Detecting COVID-19 in Computed Tomography Images: A Novel Approach Utilizing Segmentation with UNet Architecture, Lung Extraction, and CNN Classifier

Detecting COVID-19 in Computed Tomography Images: A Novel Ap...

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Computing Conference

作者： Morani, Kenan Ayana, Esra Kaya Kollias, Dimitrios Unay, Devrim Izmir Democracy Univ Gursel Aksel Blv 14 TR-35140 Izmir Turkiye Yildiz Tech Univ TR-34349 Istanbul Turkiye Queen Mary Univ London 327 Mile End Rd London England

ISBN: (纸本)9783031622717;9783031622694;9783031622687

Our study introduces an innovative framework tailored for COVID-19 diagnosis utilizing a vast, meticulously annotated repository of CT scans (each comprising multiple slices). Our framework comprises three key Parts: the segmentation module (based on UNet and optionally incorporating slice removal techniques), the lung extraction module, and the final classification module. The distinctiveness of our approach lies in augmenting the original UNet model with batch normalization, thereby yielding lighter and more precise localization, essential for constructing a comprehensive COVID-19 diagnosis framework. To gauge the efficacy of our framework, we conducted a comparative analysis of other possible approaches. Our novel approach segmenting through UNet architecture, enhanced with Batch Norm, exhibited superior performance over conventional methods and alternative solutions, achieving High similarity coefficient on public data. Furthermore, at the slice level, our framework demonstrated remarkable validation accuracy and at the patient level, our approach outperformed other alternatives, surpassing baseline model. For the final diagnosis decisions, our framework employs a Convolutional Neural Network (CNN). Utilizing the COV19-CT Database, characterized by a vast array of CT scans with diverse slice types and meticulously marked for COVID-19 diagnosis, our framework exhibited enhancements over prior studies and surpassed numerous alternative methods on this dataset.

关键词： UNet segmentation Batch norm Lung extraction CNN Classifier Computed tomography F1 score

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Vehicular Connectivity Analysis Using Enhanced Quality Slotted ALOHA (EQS-ALOHA)

Vehicular Connectivity Analysis Using Enhanced Quality Slott...

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Computing Conference

作者： Iskandarani, Mahmoud Zaki Al Ahliyya Amman Univ Amman 19328 Jordan

ISBN: (纸本)9783031622755;9783031622731;9783031622724

This work investigates through simulation the effectiveness of Slotted ALOHA for vehicular Medium Access Control (MAC), which is affected by dynamic changes in traffic and vehicular movements. The objective is to reach acceptable level of throughput with fewer collisions under changing environment. The presented work proposes a new dynamic method to enable constant modification of the vehicles (nodes) slots status and readiness to transmit, by responding to the continuous change in vehicular density. This enables adaptive control of transmitting slots and allow to sustain data load (traffic) and throughput within an acceptable limits, regardless of traffic density. This is achieved by minimize collisions in response to traffic and throughput adaptive behavior. The objective of collision reduction and throughput improvement is achieved using a dynamic load line, which operates using a central dynamic point (Q-point), where a slope is built around this point. The location and value of such point is determined by mathematical expression used to constantly update the Packet Ready Probability (PCKprob), number of vehicles (Vi), with subsequent change in Collision Probability (Cp) and both traffic (G) and throughput values (S). The derived mathematical model, show promising results in terms of optimizing the conventional Slotted ALOHA and improving the vehicular connectivity. The work analyzed the performance of Slotted ALOHA with the realization that it suffers from main disadvantage at high vehicular density as throughput drops with increase in collision probability. The new proposed method would help in improving the performance of Slotted ALOHA.

关键词： Collisions Connected vehicles CSMA Intelligent transportation systems Network connectivity Slotted aloha

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A Graph-Attention Solution for Breakdown Prediction (GASBP)

A Graph-Attention Solution for Breakdown Prediction (GASBP)

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Intelligent systems Conference

作者： Doorshi, Raoof Khoshkangini, Reza Rajabi, Enayat Sahba, Amin Sahba, Ramin Malmo Univ Dept Comp Sci & Media Technol Internet Things & People Res Ctr Malmo Sweden Cape Breton Univ Sydney NS Canada Univ Texas San Antonio San Antonio TX USA

ISBN: (纸本)9783031663352;9783031663369

Breakdown prediction is one of the essential steps in the maintenance of machinery devices and vehicles. The utilization of machine learning in breakdown detection is not new and has gone a long way, however, using sensory measurements of vehicles to forecast faults is still a challenge to be completely overcome. The strength of graph-based techniques in solving complex problems, and the recent success of these approaches to various modeling problems, motivated us to utilize such approaches to tackle the complex task of breakdown prediction. Thus, in this study, we propose a graph-based system that contains two main modules. The first module deals with preprocessing data which is a crucial part of the approach. In the second module, we used and adapted the GMAN technique to find the temporal aspect of the measurements and map them to the breakdown, such that we ultimately built the model for the final breakdown prediction. Our preliminary evaluation experiments on the forestry vehicles' collected data showed promising.

关键词： Breakdown prediction Graph neural networks Graph attention

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