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检索条件"任意字段=13th International Conference on Intelligent and Adaptive Systems and Software Engineering"

共 5485 条记录，以下是81-90 订阅

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Path Planning Using adaptive RRT*-Connect Algorithm Base on NURBS Curve Smoothing 13

Path Planning Using Adaptive RRT*-Connect Algorithm Base on ...

引用

13th IEEE international conference on CYBER Technology in Automation, Control, and intelligent systems, CYBER 2023

作者： Jia, Zhenming Cheng, Hongtai Tian, Meng School of Mechanical Engineering and Automation Northeastern University Shenyang110819 China

ISBN: (纸本)9798350315196

Optimal Path Planning for Robots refers to the autonomous search and planning of the shortest and smoothest path between the start and end points while avoiding obstacles in the space. this article presents an adaptive RRT*-Connect global path planning method based on NURBS curve smoothing (NARRT*-Connect). Building on the RRT*-Connect path planning, an adaptive step size adjustment strategy is introduced to accelerate the path search. In addition, NURBS curves are used for secondary path smoothing optimization, which does not require moving control points but only defines appropriate weighting criteria, ensuring that the path is smoothed while controlling local path changes within a safe threshold. through simulation and experimentation, NARRT*-Connect is studied and compared with RRT*-Connect, RRT*, and other algorithms. the results indicate that the NARRT*-Connect algorithm can significantly improve iteration speed, generate shorter paths, and facilitate secondary safety smoothing of the paths. © 2023 IEEE.

关键词： Motion planning

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Effects of Gait Onomatopoeia on the Impression of Robots 13

Effects of Gait Onomatopoeia on the Impression of Robots

引用

Joint 13th international conference on Soft Computing and intelligent systems and 25th international Symposium on Advanced intelligent systems, SCIS and ISIS 2024

作者： Umeda, Takumi Kanoh, Masayoshi Graduate School of Engineering Chukyo University 101-2 Yagotohonmachi Showa-ku Nagoya466-8666 Japan School of Engineering Chukyo University 101-2 Yagotohonmachi Showa-ku Nagoya466-8666 Japan

ISBN: (纸本)9798350373332

In this study, we investigate whether the impression of a robot's gait can be altered by introducing onomatopoeic words such as phonomimes and phenomimes associated with its movement. Since mimetic words and sound words have high sound symbolism, the impression of gait onomatopoeia can potentially be formulated by using mimetic words and sound words instead of emotional words. We prepared two types of robot and four types of voice to investigate the impression of onomatopoeia and the effect of emotional expression through questionnaires, taking into consideration the impression changes by the difference of the robot's appearance and voice quality. Following cluster analysis of the questionnaire results, we classified the 14 types of onomatopoeia into four groups (busy onomatopoeia, powerful onomatopoeia, adorable onomatopoeia, and unenergetic onomatopoeia). Multiple comparisons of the means of the questionnaire results for each group showed that (1) busy onomatopoeia lowers the impression of happiness and sadness, (2) powerful onomatopoeia lowers happiness but raises width, (3) adorable onomatopoeia lowers anger, disgust, surprise, fear, and dynamism while raising softness, and (4) unenergetic onomatopoeia lowers anger, happiness, quickness, and dynamism while raising sadness. © 2024 IEEE.

关键词： Cluster analysis

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Modelling Mechanical Communication and Collective Motion of Cancer Cells 13

Modelling Mechanical Communication and Collective Motion of ...

引用

Joint 13th international conference on Soft Computing and intelligent systems and 25th international Symposium on Advanced intelligent systems, SCIS and ISIS 2024

作者： Hosono, Ryousuke Nakano, Tadashi Hsu, Yu-Hsiang Tang, William C. Osaka City University Department of Electrical and Information Engineering Osaka Japan Graduate School of Informatics Osaka Metropolitan University Osaka Japan Institute of Applied Mechanics National Taiwan University Taipei Taiwan Graduate School of Advanced Technology Taipei Taiwan University of California Biomedical Engineering Department IrvineCA United States

ISBN: (纸本)9798350373332

Understanding the communication mechanisms that drive collective behaviors in cancer is crucial for elucidating cancer progression and metastasis. To investigate communication mechanisms and their impacts on collective cell behaviors in can-cer, our previous study employed time-lapse imaging techniques on cancer cells placed on substrates containing fluorescent beads. In these experiments, we observed bead movements that reflect mechanical cell communication through substrate dynamics and collective cell motions. In this study, our objective is to develop a computational model to reproduce the experimental observations from our previous study. We demonstrated that the model developed in this paper substantiated previous experimental findings and established a foundation for further investigations into the communication mechanisms and collective behaviors in cancer. © 2024 IEEE.

关键词： Lung cancer

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Prediction of Cardiovascular Disease Development for CEA Patients Using Multimodal Learning 13

Prediction of Cardiovascular Disease Development for CEA Pat...

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Joint 13th international conference on Soft Computing and intelligent systems and 25th international Symposium on Advanced intelligent systems, SCIS and ISIS 2024

作者： Ishida, Shuya Morita, Kento Hatakeyama, Kinta Ren, Nice Watanabe, Shogo Kobashi, Syoji Iihara, Koji Wakabayashi, Tetsushi Graduate School of Engineering Mie University Japan National Cerebral and Cardiovascular Center Japan Graduate School of Engineering University of Hyogo Japan

ISBN: (纸本)9798350373332

Carotid endarterectomy (CEA) is a surgical treatment for carotid artery stenosis for stroke prevention. Although CEA has been shown to be effective in patients with severe plaque stenosis, predicting long-term outcomes after CEA re-mains difficult. there are many studies that predict prognosis using patients' clinical data, but there are no studies that predict prognosis using carotid plaque pathological images. this study aims to predict the development of cardiovascular disease within one year after surgery in patients undergoing CEA using multimodal learning that combines carotid plaque pathological images, patient's clinical data, and pathologists' interpretation. Moreover, the proposed method contributes to detecting pathological factors and clinical features associated with the development of cardiovascular disease. Pathological risk scores obtained by the anomaly detection model were combined with clinical information and textual features obtained by TF-IDF and they are classified by XGBoost, resulting in a ROC-AUC of 0.850 and a PR-AUC of 0.816. these values showed better classification performance than when each feature was used alone. © 2024 IEEE.

关键词： Cardiovascular surgery

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A Denoising Method from Low-dose CT Images Based on Improved U-Net with Attention Mechanism 13

A Denoising Method from Low-dose CT Images Based on Improved...

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Joint 13th international conference on Soft Computing and intelligent systems and 25th international Symposium on Advanced intelligent systems, SCIS and ISIS 2024

作者： Sawada, Shuji Li, Guangxu Murakami, Seiichi Kamiya, Tohru Kyushu Institute of Technology Mechanical and Control Engineering Fukuoka Kitakyushu Japan Tiangong University Electronics and Information Engineering XiQing Tianjin China Junshin Gakuen University Fukuoka Radiological Science Faculty of Health Sciences Fukuoka Japan

ISBN: (纸本)9798350373332

Japan has the highest number of CT scanners per million population among developed countries, and the annual medical radiation dose is about four times the world average. Screening of high-risk populations with low-dose CT has been shown to reduce lung cancer mortality. However, in order to obtain image quality comparable to that of normal-dose CT, it is necessary to accurately estimate the image noise of low-dose CT. In this paper, we apply a noise reduction method using convolutional neural networks: the CNN model is based on U-Net, a fully convolutional network with encoder-decoder structure, with two convolutional layer modifications and three attention mechanisms. Experimental results using whole body slice CT images of piglets show that the proposed method is useful by comparing with CT images of normal dose and by evaluating image quality using peak signal-to-noise ratio (PSNR). © 2024 IEEE.

关键词： Computerized tomography

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Survival Time Prediction of Patients with Soft Tissue Tumor Using Biopsy Pathological Images 13

Survival Time Prediction of Patients with Soft Tissue Tumor ...

引用

Joint 13th international conference on Soft Computing and intelligent systems and 25th international Symposium on Advanced intelligent systems, SCIS and ISIS 2024

作者： Takahashi, Kota Morita, Kento Hagi, Tomohito Nakamura, Tomoki Asanuma, Kunihiro Sudo, Akihiro Wakabayashi, Tetsushi Graduate School of Engineering Mie University Department of Information Engineering Japan Graduate School of Medicine Mie University Department of Orthopedic Surgery Japan

ISBN: (纸本)9798350373332

Malignant soft tissue tumor are rare cancers and uncommon diseases. Ideally, rare cancers should be diagnosed by a pathologist who specializes in that organ, but there is a chronic shortage of pathologists in Japan. Pathological diagnosis by artificial intelligence (AI) is required to improve the reliability of diagnosis and to support pathological diagnosis of rare diseases. there are several studies to predict the prognosis of cancer patients using pathology images, but most of them requires a large dataset and capable machine learning model such as convolutional neural networks (CNN). Since soft tissue tumors are rare diseases, large datasets cannot be collected, and existing approaches would not perform enough for clinical diagnosis. therefore, this paper proposes a survival time prediction method using unsupervised machine learning algorithms that extracts pathological image feature by autoencoder, and K-means clustering and K Nearest Neighbor (KNN) regression perform the survival time prediction based on the extracted image features. the experiments on 27 soft tissue tumor patients showed that the proposed method predicted the survival time with an average error of 17.89 months. © 2024 IEEE.

关键词： Biopsy

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Design and Implementation of an Android-based intelligent Archive System for Talent Cultivation 13

Design and Implementation of an Android-based Intelligent Ar...

引用

13th IEEE international conference on Communication systems and Network Technologies, CSNT 2024

作者： Lin, Jun Wuhan Business University Hubei Wuhan430056 China

ISBN: (纸本)9798350305463

With the popularization of mobile internet, smartphones have become an indispensable tool in people's lives. In order to adapt to the development of the times, universities have also developed mobile application software. Talent cultivation is an important component of teaching work in universities and plays a crucial role in improving teaching quality. the article was based on the Android platform to design and implement an intelligent talent cultivation file system, which realized functions such as attendance management, score query, class ranking, and exam score analysis for students, and tested and optimized the system. the experimental results showed that the system had high processing efficiency (Max: 94.7%) and short response time (Min: 196ms), which could more effectively provide technical support for students and teachers. © 2024 IEEE.

关键词： intelligent systems

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Registration Method for Head CT and MR Images Based on TransMorph Incorporated ASPP 13

Registration Method for Head CT and MR Images Based on Trans...

引用

Joint 13th international conference on Soft Computing and intelligent systems and 25th international Symposium on Advanced intelligent systems, SCIS and ISIS 2024

作者： Murakami, Tomoaki Yamamoto, Akiyoshi Kamiya, Tohru Kyushu Institute of Technology Department of Mechanical and Control Engineering Kitakyushu Fukuoka Japan Tobata Kyoritsu Hospital Kitakyushu Fukuoka Japan Engineering Kyushu Institute of Technology Department of Mechanical and Control Kitakyushu Fukuoka Japan

ISBN: (纸本)9798350373332

In recent years, with the development of diagnostic imaging equipment, image fusion, which fuses medical images from multiple modalities, has been proposed as a diagnostic imaging application. this has the advantage of integrating images with different characteristics and resolutions into a single composite image, which compensates for the missing information of each and facilitates the reading of lesions. Examples of the use of fusion images include surgical simulation and CyberKnife-based surgery. To create a fusion image, the two images must be aligned. Currently, this is often done manually, which increases the burden on the surgeon and introduces problems such as variations in accuracy depending on the surgeon's skill. therefore, this paper describes the development of an automatic registration method for creating a fusion image between head CT and MRI, which is necessary for CyberKnife-based surgery of brain tumors. the method uses TransMorph, a registration model, as the base model, and a new model is constructed by adding ECAM and ASPP. As a result, the proposed method with the introduction of ASPP to the base model shows an improvement in the mutual information value and succeeds in improving the accuracy. © 2024 IEEE.

关键词： Medical imaging

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Effects of Fairness Concern on Decisions and Performance in IT Supply Chain 13

Effects of Fairness Concern on Decisions and Performance in ...

引用

13th international conference on Logistics and systems engineering

作者： Ren, Tinghai Liu, Kaixuan Wang, Dafei Zeng, Nengmin College of Industry and Commerce Guizhou University of Finance and Economics Guiyang550001 China School of Economics and Management Harbin Engineering University Harbin150001 China

ISBN: (纸本)9781713896708

In practice, the downstream service integrator may focus on the equity of interest allocation in the IT supply chain (ITSC). However, less attention is paid to this issue in the previous research on IT sourcing. In this thesis, we take into account an ITSC consisting of a software developer, a service integrator, and customer enterprises (clients). the upstream developer first empowers its software to the integrator. By being free pre-sale services, like consultation and demand analysis, the integrator sells the software to the clients. then the clients could buy the extended warranty service (EWS) from the developer after buying the software. Especially, pre-sale services quality can directly influence software sales and indirectly affect the sales of EWS. We are surprised to find that the fairness concern of the integrator will cause the integrator to lower (raise) its software sale prices when the customer’s sensitivity to the software price is below (above) a certain critical threshold. However, when the clients’ sensitivity to the EWS price is lower (higher) than a critical value, the integrator’s fairness concern can stimulate the developer to enhance (decrease) its software authorized price. Moreover, the integrator’s fairness concern always makes the integrator decrease the pre-sales service quality and the developer cut the price of the EWS. Our analysis also indicates that the integrator’s fairness concern can reduce the need for software and EWS of clients. the integrator’s fairness concern not only leads to a decline in the developer's profit, but also a decline in its profits. However, the loss of profit for the developer caused by the integrator’s fairness concern may be greater than that for the integrator. © 2024 Proceedings of the 13th international conference on Logistics and systems engineering. All rights reserved.

关键词： Supply chains

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AI-Driven Virtual Mock Interview Development 13

AI-Driven Virtual Mock Interview Development

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Joint 13th international conference on Soft Computing and intelligent systems and 25th international Symposium on Advanced intelligent systems, SCIS and ISIS 2024

作者： Mishra, Prabhat Kumar Arulappan, Arun Kumar Ra, In-Ho thanga Mariappan, L. Gina Rose, G. Lee, Young-Seok School of Computer Science Engineering and Information Systems Vit University Vellore India School of Computer and Software Kunsan National University Gunsan Korea Republic of Anna University Department of Computer Technology Chennai India

ISBN: (纸本)9798350373332

the integration of Artificial Intelligence (AI) into educational technologies marks a significant shift in learning methodologies and operational dynamics within educational institutions. At the forefront is an AI-driven virtual mock interview platform designed to address the high Customer Acquisition Costs (CAC) in the edtech sector, especially for interview preparation services. this initiative harnesses a blend of AI technologies, including ADA 2 for creating context-aware embeddings and Machine Learning (ML), to transform the traditional mock interview process into a dynamic, cost-effective system. Central to the platform is its use of advanced Natural Language Processing (NLP) techniques and GPT-4 Large Language Model (LLM), automating the process of mock interviews and providing personalized feedback, ensuring a preparation journey that meets specific candidate needs and mirrors real interview scenarios. A key evaluation among 100 students from a cohort of 1800 demonstrated a 90% cost reduction for three mock interviews, reducing expenses from 3000 to just 300 per candidate. this cost efficiency significantly enhances access to quality interview preparation, improving student satisfaction and accessibility. Moreover, the platform provides valuable insights into student performance, setting a new standard in educational technology by offering an effective, personalized interview preparation experience. this project reflects a holistic approach to student development and the critical role of technology in addressing the evolving needs of learners. © 2024 IEEE.

关键词： Cost reduction

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