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A novel CatractNetDetect deep learning model for effective cataract classification through data fusion of fundus images

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Discover Artificial Intelligence 2024年第1期4卷 1-27页

作者： Ismail, Walaa N. Alsalamah, Hessah A. Department of Management Information Systems College of Business Al Yamamah University Riyadh11512 Saudi Arabia College of Computer and Information Sciences King Saud University Riyadh4545 Saudi Arabia Computer Engineering Department College of Engineering and Architecture Al Yamamah University Riyadh11512 Saudi Arabia

Cataracts are common eye disorders characterized by the clouding of the lens, preventing light from passing through and impairing vision. Various factors, including changes in the lens’s hydration or alterations in its proteins, may contribute to their development. Regular eye examinations conducted by an ophthalmologist or optometrist are imperative for detecting cataracts and other ocular conditions early on. Manual checks by caregivers pose several problems, including subjectivity, human error, and a lack of expertise. Biomedical fusion involves combining or linking various characteristics specific to certain diseases from different medical imaging resources. The primary objectives of this approach in disease classification are to reduce the error rate and increase the number of retrieved features. The aim of this study is to evaluate the outcomes associated with fusing visual features related to left and right eye cataract characteristics. Additionally, we investigate the impact of limited variability in deep learning models, specifically in the classification of cataract fundus versus normal fundus images. To address this issue, this study introduces CataractNetDetect, an innovative multi-label deep learning classification system that fuses feature representations from pairs of fundus images (e.g., left and right eyes) for the automatic diagnosis of various ocular disorders. Our focus is on achieving improved performance by stacking discriminative deep feature representations to combine two fundus images into a unified feature representation. Several deep learning architectures are utilized as feature descriptors, including ResNet-50, DenseNet-121, and Inception-V3, enhancing the resilience and quality of representations. Fine-tuning of these DL architectures is conducted using the ImageNet dataset, followed by an integrated stacking approach combining ResNet-50, DenseNet-121, and Inception-V3 models. The model is trained on the publicly available ODIR-5k datas

关键词： Medical imaging

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Forecasting and managing urban futures: machine learning models and optimization of urban expansion

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Asian Journal of Civil Engineering 2024年第6期25卷 4673-4682页

作者： Abid, Mohammed Talib Aljarrah, Njood Shraa, Tamer Alghananim, Haneen Marouf Department of Architecture College of Engineering Al-Nahrain University Baghdah Iraq Computer Sciences Faculty of Information Technology and Computer Sciences Ajloun National University Ajloun Jordan Faculty of Science and Information Technology Cyber Security Irbid National University Irbid Jordan Faculty of Engineering Architecture Department Ain Shams University Cairo Egypt

This paper presents a novel method for predicting and controlling urban growth by combining convolutional neural networks (CNN) with Spider Monkey Optimization (SMO) to efficiently use their combined capabilities. This strategy utilizes sophisticated machine learning algorithms to forecast urban development patterns, while optimization technologies enhance these forecasts by including sustainable urban design ideas. Integration plays a crucial role in tackling the difficulties presented by fast urbanization, including issues related to land use, resource administration, and environmental sustainability in the fields of civil and architectural engineering. The study employs large datasets to assess the efficacy of CNN models in detecting urban expansion patterns and enhances these models with optimization scenarios encompassing land use, traffic flow, electricity efficiency, water resources, and waste management, all with the goal of enhancing urban sustainability. The findings demonstrate a significant improvement in the precision of predictions and the ability to maintain positive results, highlighting the crucial role of integrating machine learning and optimization in urban planning methodologies. This method not only provides urban planners and politicians with strong and effective tools for making decisions but also creates opportunities for implementing creative and sustainable solutions for urban growth. The results provide a substantial contribution to the existing urban planning literature by demonstrating the actual use of these technologies in regulating urban expansion. This will stimulate more study in this rapidly evolving subject. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Convolutional neural networks Machine learning Optimization techniques Spider monkey optimization Sustainable urban planning Urban expansion

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Analysis and Practice of Ideological and Political Education in computer Public Basic Courses in architecture Universities Based on Machine Learning and Deep Learning 24

Analysis and Practice of Ideological and Political Education...

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2024 Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Education Digitalization and computer Science, EDCS 2024

作者： Lv, Cheng Department of Computer Science School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture Beijing100044 China

ISBN: (纸本)9798400710360

In response to the shortcomings of ideological and political education in the computer basic course of our school, the teaching team has conducted in-depth research on the connotation of ideological and political education in the course, accurately grasped the direction of ideological and political education in the course, innovatively proposed the"progressive method of ideological and political education", and constructed an integrated curriculum system of ideological and political education in the course;Using Orange3 software and machine learning algorithms to deeply explore the ideological and political elements of the curriculum, constructing an analytical model, formulating personalized teaching and learning strategies, and constructing a double-layer teaching evaluation system that emphasizes both morality and ability. Through the analysis of course data, it is shown that the effectiveness of ideological and political education in the curriculum has been comprehensively improved, and the quality of teaching has been comprehensively enhanced. © 2024 Copyright held by the owner/author(s).

关键词： Adversarial machine learning

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Course construction based on FD-QM standards and analysis and mining of course data 24

Course construction based on FD-QM standards and analysis an...

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2024 International Conference on Intelligent Education and computer Technology, IECT 2024

作者： Lv, Cheng Department of Computer Science School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture Beijing100044 China

ISBN: (纸本)9798400709920

In response to the shortcomings of the SPOC course "Introduction to Computational Thinking"at Beijing University of Civil Engineering and architecture, the teaching team has transformed and improved the course design and practice based on the existing High quality undergraduate courses in Beijing universities and Beijing Curriculum Ideological and Political Demonstration Course. We aim to maintain consistency and linkage in learning objectives, learning assessments, teaching materials, learning activities, and course technology under the principle of consistent construction. Learning objectives are clearer and more measurable;learning assessment is more scientific, diverse, and reliable;Curriculum resources can meet the needs of students at different levels and majors;learning activities can fully mobilize students' subjective initiative;Curriculum technology helps to achieve learning objectives, and can reflect the characteristics of the discipline, with universality and progressiveness. Through the construction and practice of the FD-QM standard, the course team has established the principles of course standardization, clarified the direction of course material construction, drawn a knowledge graph of course knowledge points, accurately grasped the degree of learning objectives, upgraded the "characteristic"teaching resource library, enhanced student interest, and integrated ideological and political education into the curriculum, ultimately achieving a comprehensive improvement in the quality of course teaching. © 2024 ACM.

关键词： Knowledge graph

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The Mechanism for Synchronizing CNC System with External Devices by Using a Part Program

The Mechanism for Synchronizing CNC System with External Dev...

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2023 International Russian Automation Conference, RusAutoCon 2023

作者： Martinov, Georgi Salamatin, Evgeny Moscow State University of Technology "STANKIN" Department of Computer-Architecture Control Systems Moscow Russia

ISBN: (纸本)9798350345551

The problem of synchronizing parallel tasks in control systems at the level of the part program is reviewed. A general solution, based on a high-level part programming language extension, is proposed for synchronizing parallel tasks within one control system as well as tasks performed by several different control systems. A scheme for synchronizing the CNC with external autonomous devices through the Common PLC Memory, to which the part program, the PLC program and the inputs and outputs (I/Os) of electric automation have access, has been developed. A set of functions in a high-level part programming language, providing zeroing a certain number of bytes, writing bit, byte, long and float data types to the Common PLC Memory and reading them from it, has been implemented. As a part of practical research, a test stand on the basis of the AxiOMA Control CNC system, that controls actuators via the EtherCAT protocol, was assembled;master and slave part programs were implemented;tests, confirming the operability of the mechanism for synchronizing CNC system with external devices by using a part program, were carried out. © 2023 IEEE.

关键词： Control systems

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Development and Use of OPC UA Tools for Data Collection and Monitoring of Technological Equipment

Development and Use of OPC UA Tools for Data Collection and ...

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2023 International Russian Smart Industry Conference, SmartIndustryCon 2023

作者： Martinov, Georgi Al Khoury, Akram Issa, Ahed Moscow State University of Technology STANKIN Department of Computer-Architecture Control Systems Moscow Russia

ISBN: (纸本)9781665464291

The aim of this research is to develop a specialized system for collecting and storing CNC machines data considering the possibilities of innovative technologies of OPC UA protocol, in this work an OPC UA information model was proposed and realized in OPC UA server which reflects the logical structure of a CNC machine. This research will present a collecting data method from the digital shadow of CNC system where a complete set of parameters hierarchically structured and transmit the whole set of these parameters through the OPC UA server to production data collection cloud for performing subsequent analyzing, forecasting the state of technological equipment and performing simulation procedures. © 2023 IEEE.

关键词： Data acquisition

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Collection and Storage of Technological Data in Multi-Channel CNC Processing Using a Non-Relational Database and Node-RED

Collection and Storage of Technological Data in Multi-Channe...

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2023 International Russian Automation Conference, RusAutoCon 2023

作者： Martinov, Georgi Polyakov, Kirill Moscow State University of Technology "STANKIN" Department of Computer-Architecture Control Systems Moscow Russia

ISBN: (纸本)9798350345551

This article contemplates the problem of collecting and storing technological data during multichannel and multi - coordinate machining on CNC machines obtained using the OPC UA protocol and applying Node-RED open-source instrumentation. A structural model of obtaining, visualizing and storing technological data in multichannel and multi - coordinate machining is proposed in this research. The necessary nodes for Collection and storage of technological data in multi-channel CNC processing are implemented and configured. The researchers illustrated practical aspects of building a system for collecting and storing technological data in multichannel machining using the OPC UA protocol and applying Node-RED open-source tools and a non-relational MongoDB database. © 2023 IEEE.

关键词： Digital storage

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An Approach to the Production of Prototype Printed Circuit Boards on Bench-Type Machine with the CNC System

An Approach to the Production of Prototype Printed Circuit B...

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2023 International Russian Smart Industry Conference, SmartIndustryCon 2023

作者： Martinov, Georgi Martemianova, Natalia Moscow State University of Technology "STANKIN" Department of Computer-Architecture Control Systems Moscow Russia

ISBN: (纸本)9781665464291

The paper considers the problems of manufacturing prototypes of printed circuit boards on bench-Type milling machines that require the prompt production of a small batch and correction, if it's necessary. We used modern tools from third-party manufacturers for the preparation of production and processing of single-and double-layer printed circuit boards on bench-Type CNC machines. A technique is proposed that formalizes the process of preparing and verifying part programs and manufacturing printed circuit boards. The methodology was tested and an example of manufacturing a prototype of a printed circuit board for a voltage regulator on a machine with an "AxiOMA Control"CNC system was illustrated. © 2023 IEEE.

关键词： Printed circuit boards

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Impact of Mixed-Precision: A Way to Accelerate Data-Driven Forest Fire Spread Systems 23rd

Impact of Mixed-Precision: A Way to Accelerate Data-Driven...

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23rd International Conference on Computational Science, ICCS 2023

作者： Carrillo, Carlos Margalef, Tomás Espinosa, Antonio Cortés, Ana Computer Architecture and Operating Systems Department Universitat Autónoma de Barcelona Barcelona Spain

ISBN: (纸本)9783031360206

Every year, forest fires burn thousands of hectares of forest around the world and cause significant damage to the economy and people from the affected zone. For that reason, computational fire spread models arise as useful tools to minimize the impact of wildfires. It is well known that part of the forest fire forecast error comes from the uncertainty in the input data required by the models. Different strategies have been developed to reduce the impact of this input-data uncertainty during the last few years. One of these strategies consists of introducing a data-driven calibration stage where the input parameters are adjusted according to the actual evolution of the fire using an evolutionary scheme. In particular, the approach described in this work consists of a Genetic Algorithm (GA). This calibration strategy is computationally intensive and time-consuming. In the case of natural hazards, it is necessary to maintain a balance between accuracy and time needed to calibrate the input parameters. Most scientific codes have over-engineered the numerical precision required to obtain reliable results. In this paper, we propose to use a mixed-precision methodology to accelerate the calibration of the input parameters involved in forest fire spread prediction without sacrificing the accuracy of the forecast. The proposed scheme has been tested on a real fire. The results have led us to conclude that using the mixed-precision approach does not compromise the quality of the result provided by the forest fire spread simulator and can also speed up the whole evolutionary prediction system. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Calibration

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The Practice of Using a SoftPLC to Control the Electromechanical Units of a Training Turning Machine

The Practice of Using a SoftPLC to Control the Electromechan...

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2023 International Conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2023

作者： Martinov, Georgi Nikishechkin, Petr A. Moscow State University of Technology Stankin Department of Computer-Architecture Control Systems Moscow Russia

ISBN: (纸本)9781665475952

The process of developing a PLC program for controlling the electromechanical units of modern machine tools with computer numerical control (CNC) has been formalized. The architecture of a two-computer CNC system with an integrated SoftPLC is given and the specifics of using the touch operator panel and virtual machine panel are considered. A set of libraries developed in the FBD (Functional Block Diagram) language for controlling the electrical automation units of a turning machine is proposed. An example of controlling the electric automation of a training lathe via the high-speed EtherCAT field bus using relatively inexpensive third-party solutions for servo drives and I/O modules that provide the required accuracy and speed is given. © 2023 IEEE.

关键词： Lathes

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