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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Zhang, Yindong Chen, Jie Wang, Li Chen, Miaohong Zhang, Guoming Li, Jianqiang Shenzhen University College of Computer Science and Software Engineering China Shenzhen University National Engineering Laboratory for Big Data System Computing Technology China Shenzhen Eye Hospital China

ISBN: (纸本)9798350337488

Retinopathy of Prematurity (ROP) is a retina disorder that affects premature infants with lower weights. If the patient cannot get the treatment in time when the illness reaches the last stage, irreversible vision loss will be caused. Nevertheless, there has been relatively little consideration given to the segmentation of the ridge, the key clinical characteristic of the illness. Additionally, existing research has not adequately addressed several segmentation issues, such as fragmentary topology, class imbalance, and false positives. This paper proposes a Densely Dilated U-Net (DD-UNet) improved from U-Net to tackle these challenges. Furthermore, the post-processing techniques based on the spatial relationship between vessels and ridges, along with the relative pixel counts of ridges and false positive results is integrated to mitigate false positive results in the predicted ridge. To enhance the precision of thin vessel, a sliding window sampling method is introduced for refined training. Compared with the state-of-the-art models in medical image segmentation, DD-UNet performs well in curvilinear structure segmentation of fundus image. For instance, our DD-UNet outperforms the Attention U-Net by 6.26% in terms of sensitivity and exhibits a 1.85% higher dice score in ridge segmentation. © 2023 IEEE.

关键词： curvilinear structure segmentation fundus image Retinopathy of Prematurity (ROP) ridge segmentation vessel segmentation

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Improved LOPCOW-SAW Method for Optimal Supplier Selection in Supply Chain Management 12

Improved LOPCOW-SAW Method for Optimal Supplier Selection in...

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12th International Conference on Cyber and IT Service Management, CITSM 2024

作者： Sumanto Sumarna Nurdin, Hafis Asra, Taufik Sobari, Irwan Agus Kuswanto, Herman Chaidir, Indra Akil, Ibnu Handono, Felix Wuryo Universitas Bina Sarana Informatika Informatics Faculty of Engineering and Informatics Jakarta Indonesia Universitas Nusa Mandiri Information System Faculty of Engineering and Informatics Jakarta Indonesia Universitas Bina Sarana Informatika Software Engineering Faculty of Engineering and Informatics Jakarta Indonesia Universitas Nusa Mandiri Universitas Bina Sarana Informatika Information System Faculty of Engineering and Informatics Indonesia Universitas Nusa Mandiri Universitas Bina Sarana Informatika Computer Engineering Faculty of Engineering and Informatics Indonesia

ISBN: (纸本)9798331528799

Supplier selection is a critical component of Supply Chain Management (SCM), as suppliers provide raw materials or services essential for supporting a company's operations. Traditional supplier selection methods often rely on subjective assessments to determine the weighting of criteria, which can lead to biases and suboptimal decision making. To address this issue, this study combines the Logarithmic Percentage Change of Weight (LOPCOW) method with the Simple Additive Weighting (SAW) method to enhance objectivity in the supplier selection process. The LOPCOW method is used to assign criterion weights objectively based on logarithmic percentage changes, which helps minimize subjectivity, These weights are then applied using the SAW method to evaluate and rank suppliers. The results of the study show that this combined approach is more reliable for selecting suppliers objectively and accurately. The study suggests integrating other Multi-Criteria Decision-Making (MCDM) methods to further strengthen the results while recommending the inclusion of real-time data analytics to improve the model's adaptability to dynamic market conditions. The LOPCOW-SAW approach can be applied across various industries for more effective and efficient SCM supplier selection. © 2024 IEEE.

关键词： Supply chain management

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Speech-Recognizing KIOSK Mobile Application for the Visually Impaired 14

Speech-Recognizing KIOSK Mobile Application for the Visually...

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14th International Conference on Education Technology and Computers, ICETC 2022

作者： Eun, Nahyun Ou, Soobin Kim, Mijin Yoo, Chaewon Lee, Jongwoo Smart System Software Lab Department of IT Engineering Women's University South Korea Korea Republic of

ISBN: (纸本)9781450397766

Recently, KIOSKs can be easily found in many places due to the increased labor cost burden and technology development. In particular, the restaurant industry increases the kiosk placement rate. However, the visually impaired have problems with KIOSKs consisting of touch screens and even describe it as a 'wall.' Based on speech recognition, we propose software that helps visually impaired people use kiosks independently. The speech recognition kiosk proposed in this paper guides the ordering process to users through sound. And users order foods by voice. This paper introduces the functional design of the speech-recognition kiosk, the implementation of the prototype, and the operation process of the application. © 2022 ACM.

关键词： Touch screens

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DRDnet22: Advanced convolutional techniques for early diabetic retinopathy detection in retinal images 15

DRDnet22: Advanced convolutional techniques for early diabet...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Mazumder, Md. Sakib Ali Shamrat, F M Javed Mehedi Mahmud, Imran Sharmin, Sharmin Hossain, Tanzim Biplab, Ekramul Kabir Daffodil International University Department of Software Engineering Dhaka Bangladesh Universiti Malaya Department of Computer System and Technology Kuala Lumpur Malaysia Institute of Information Technology University of Dhaka Dhaka Bangladesh

ISBN: (纸本)9798350370249

Diabetic Retinopathy (DR) is a prevalent eye complication among individuals with diabetes. Early detection of DR can prevent vision loss and lower associated problems. Manual diagnosis via retinal fundus images requires the expertise of medical professionals to assess several complex characteristics, including visual acuity tests, pupil dilation, and optical consistency tomography. The process is challenging, time-consuming, and prone to errors. This paper proposes a deep learning (DL) technique, DRDnet22, to detect and categorize DR into five distinct stages. The APTOS 2019 dataset is utilized in this study, which contains 3662 images. The study employs dense block and transition layer with global average pooling (GAP) techniques, and the combination of distinct Convolutional Networks (ConvNets) results in an enhanced representation beyond the utilization of features from a single ConvNet alone. To conduct an ablation analysis, the conventional pre-trained model's performance was compared. The performance evaluation points out that the proposed model achieved 81.6% accuracy, which is an advantage over other DCNN models. Despite facing a few inaccuracies, the model's competence in spotting vital features underscores its diagnostic potential. © 2024 IEEE.

关键词： Convolutional neural networks

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Research on Adaptive Evolution Architecture for Spacecraft Control system 2

Research on Adaptive Evolution Architecture for Spacecraft C...

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2nd Asia Conference on Advanced Robotics, Automation, and Control engineering, ARACE 2023

作者： Wang, Ruozhang Chen, Zhaohui Du, Janwei Beijing Institute of Control Engineering Software Center Beijing China Beijing Institute of Control Engineering Chief Engineer's Office Beijing China Beijing Institute of Control Engineering System Innovation Center Beijing China

ISBN: (纸本)9798350328363

With the continuous expansion of space missions and the growth on complexity of on-board software, improving the adaptive evolution ability of spacecraft control system becomes an important research issue. This paper focus on the adaptive evolution architecture of spacecraft software, which aims to solve the problems including software and hardware coupling, logic and information coupling, etc. And it introduces adaptive evolution layer to the architecture and enhances software flexibility through hierarchy and modularity. Besides, the dynamic parsing execution mechanism of evolution rule is proposed to provide the basic support for the dynamic adjustment through task scheduling, system parameters, and task logic. The architecture and mechanism have good application value for realizing adaptive evolution of spacecraft control system. © 2023 IEEE.

关键词： Memory architecture

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An Integrated Calibration Scheme for Attitude Benchmark of Micro-nano Satellites and Its Experiments Based on In-Orbit Data 8

An Integrated Calibration Scheme for Attitude Benchmark of M...

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8th International Conference on Automation, Control and Robotics engineering, CACRE 2023

作者： Li, Mingqun Luo, Tong Wang, Shaokai Li, He Lei, Yongjun Jiang, Qinghua Beijing Institute of Control Engineering Research and Development Center Beijing China Beijing Institute of Control Engineering System Design Department Beijing China Beijing Institute of Control Engineering Software Development Department Beijing China

ISBN: (纸本)9798350302776

The integrated calibration method of micro-nano satellite attitude benchmark is studied. Considering the magnetic effects and residual magnetism caused by the complex magnetic environment of the satellite, an accurate measurement model for magnetometers was adopted. By using the relationship between the measured and theoretical values of the geomagnetic field, the residual magnetism and magnetic sensitivity coefficients in the magnetometer measurement model were calibrated, through the least square method of uncertain parameters of the calibration. After modeling the installation error of the solar sensor, the calibration of the solar sensor is completed, so as to realize the integrated calibration of the attitude benchmark of the micro-nano satellite. Finally, this article conducted ground experiments using telemetry data from an in orbit satellite. The experimental results showed that the proposed method reduced sensor measurement errors, improved sensor benchmark consistency, and improved attitude determination accuracy from around 10 degrees to better than 0.2 degrees, verifying the effectiveness of the proposed method. © 2023 IEEE.

关键词： Calibration

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Integrated Boolean Sensing and Event Radius Model on Data Aggregation in Wireless Sensor Networks 11

Integrated Boolean Sensing and Event Radius Model on Data Ag...

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11th International Conference on Information Technology, ICIT 2023

作者： Adawy, Mohammad Almomani, Omar Tahboush, Muhannad Althunibat, Ahmad The World Islamic Sciences and Education University Department of Information System and Networks Jordan Al-Zaytoonah University of Jordan Department of Software Engineering Amman11733 Jordan

ISBN: (纸本)9798350320060

In Wireless Sensor Network (WSN), sensor nodes are densely and arbitrarily deployed in monitoring areas and most of them generate redundant data due to sense same events in the overlapping area. Thus, they spent more of energy from their limited batteries that reduce the chance of its survival and continuity. This paper integrates two mathematical models namely Boolean Sensing Model and Event Radius Model in the cluster WSN. The proposed model analyses an event coverage area to compute minimum number of active source nodes required to transmit data events to CH node rather than all nodes within cluster. OMNeT++ simulation tool has been using to performs experimental study and obtain the result. The simulation result shows that 4 source nodes are become active and transmit their data to CH node whereby 12 source nodes turn off and become sleep in the cluster. In addition, the proposed model reduces the source nodes energy consumption about 80 % comparing with LEACH scheme. © 2023 IEEE.

关键词： Sensor nodes

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Unlearnable 3D Point Clouds: Class-wise Transformation Is All You Need 38

Unlearnable 3D Point Clouds: Class-wise Transformation Is Al...

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38th Conference on Neural Information Processing systems, NeurIPS 2024

作者： Wang, Xianlong Li, Minghui Liu, Wei Zhang, Hangtao Hu, Shengshan Zhang, Yechao Zhou, Ziqi Jin, Hai National Engineering Research Center for Big Data Technology and System China Services Computing Technology and System Lab China Cluster and Grid Computing Lab China Hubei Engineering Research Center on Big Data Security China Hubei Key Laboratory of Distributed System Security China School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Software Engineering Huazhong University of Science and Technology China School of Computer Science and Technology Huazhong University of Science and Technology China

Traditional unlearnable strategies have been proposed to prevent unauthorized users from training on the 2D image data. With more 3D point cloud data containing sensitivity information, unauthorized usage of this new type data has also become a serious concern. To address this, we propose the first integral unlearnable framework for 3D point clouds including two processes: (i) we propose an unlearnable data protection scheme, involving a class-wise setting established by a category-adaptive allocation strategy and multi-transformations assigned to samples;(ii) we propose a data restoration scheme that utilizes class-wise inverse matrix transformation, thus enabling authorized-only training for unlearnable data. This restoration process is a practical issue overlooked in most existing unlearnable literature, i.e., even authorized users struggle to gain knowledge from 3D unlearnable data. Both theoretical and empirical results (including 6 datasets, 16 models, and 2 tasks) demonstrate the effectiveness of our proposed unlearnable framework. Our code is available at https://***/CGCL-codes/UnlearnablePC. © 2024 Neural information processing systems foundation. All rights reserved.

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Recommend Source Codes Considering Designing Patterns using Machine Learning Algorithm

Recommend Source Codes Considering Designing Patterns using ...

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2024 International Research Conference on Smart Computing and systems engineering, SCSE 2024

作者： Thennakoon, A.G.D.S. Wijeratne, P.M.A.K. Kumara, B.T.G.S. Sabaragamuwa University of Sri Lanka Faculty of Computing Department of Computing and Information System Belihuloya Sri Lanka Sabaragamuwa University of Sri Lanka Faculty of Computing Department of Software Engineering Belihuloya Sri Lanka

ISBN: (数字)9798350375688

ISBN: (纸本)9798350375688

As a result of the fact that design patterns offer templates that are necessary for addressing common problems and improving the communication, productivity, and maintainability of projects consistently, design patterns are of the highest importance in the process of developing software. Machine learning (ML) techniques, such as Support Vector Machine (SVM) and Decision Trees (DT), can be utilized to simplify the process of recognizing software design patterns in source code to educate machines on how to deal with complex data, unsupervised learning is used to recognize patterns, and supervised learning is used to map inputs to outputs. The research was carried out to employ ML to produce predictions about design patterns that are present in code. Initially, the procedure begins with the gathering of datasets from professionals in the field of software engineering. These datasets were eventually classified into three categories: Abstract Factory, Factory Method, and Singleton. Three different ML models and one deep learning model were applied to make predictions. K-Nearest Neighbors (KNN), SVM, DT and Long Short-Term Memory (LSTM) respectively. For the goal of creating such predictions, SVM which has been demonstrated to correctly recognize design patterns with an impressive 98.67% accuracy, is the suitable algorithm to use. The degree of cosine similarity among the input code snippets and the group code snippets is used to decide which 5 code suggestions are the next most relevant. © 2024 IEEE.

关键词： Support vector machines

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Towards optimized tensor code generation for deep learning on sunway many-core processor

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Frontiers of Computer Science 2024年第2期18卷 1-15页

作者： Mingzhen LI Changxi LIU Jianjin LIAO Xuegui ZHENG Hailong YANG Rujun SUN Jun XU Lin GAN Guangwen YANG Zhongzhi LUAN Depei QIAN State Key Laboratory of Software Development Environment Beijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China National University of Singapore Singapore 119077Singapore State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214000China Science and Technology on Special System Simulation Laboratory Beijing Simulation Center Beijing 100854China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China

The flourish of deep learning frameworks and hardware platforms has been demanding an efficient compiler that can shield the diversity in both software and hardware in order to provide application *** the existing deep learning compilers,TVM is well known for its efficiency in code generation and optimization across diverse hardware *** the meanwhile,the Sunway many-core processor renders itself as a competitive candidate for its attractive computational power in both scientific computing and deep learning *** paper combines the trends in these two ***,we propose swTVM that extends the original TVM to support ahead-of-time compilation for architecture requiring cross-compilation such as *** addition,we leverage the architecture features during the compilation such as core group for massive parallelism,DMA for high bandwidth memory transfer and local device memory for data locality,in order to generate efficient codes for deep learning workloads on *** experiment results show that the codes generated by swTVM achieve 1.79x improvement of inference latency on average compared to the state-of-the-art deep learning framework on Sunway,across eight representative *** work is the first attempt from the compiler perspective to bridge the gap of deep learning and Sunway processor particularly with productivity and efficiency in *** believe this work will encourage more people to embrace the power of deep learning and Sunwaymany-coreprocessor.

关键词： sunway processor deep learning compiler code generation performance optimization

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