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A classifier design for micro bubble generators based on deep learning technique

Materials Today: Proceedings 2023年 80卷 2684-2696页

作者： Qaddoori, Ayman S. Saud, Jamila H. Hamad, F.A. Informatics Institute for Postgraduate Studies Iraqi Commission for Computer and Informatics Baghdad Iraq College of Science Mustansiriyah University Baghdad Iraq School of computing Engineering and Digital Technology Teesside University Middlesbrough United Kingdom

This paper aims to study the sizes of bubbles generated by the micro-bubble generator device (MBGs) in the water because of its impact on the dissolved oxygen percentage in the water and we find this in aquaculture where oxygen is important for marine life and in many applications. Where we have designed a classifier for micro-bubbles of different sizes and the effectiveness of the device has been proven in generating bubbles whose size ranges from 20 to 50 and calculating their numbers in the image by converting the image from (RGB) to (HSV), it has proven its effectiveness in maintaining lighting and neglecting color information Which is not important in identifying bubbles in the image, as well as increasing the processing speed, and then finding edges in the image, using canny edge detection, which has proven its great effectiveness in finding weak and strong edges. Where we then used the (Circular Hough Transform) algorithm to identify the tiny bubbles in the image, calculate their average diameter and numbers in the image, and find the overlapping bubbles between them by using (Two Thresholds) one for the edge and the other for the center of the bubble and then making (Segmentation) for these bubbles and inserting them on (Gaussian Normal Distribution) Do not neglect the dark bubbles, because in most cases they are unreal bubbles and may be distortions in the image or reflections in the lighting. And then make (zero paddings) for the extracted images to make them equal in size and avoid the distortion that will happen in the image if another method is used to make all bubbles of equal dimensions to prepare them for classification. And then we calculated the (mean square error) of the resulting bubble images to avoid repeating the same bubble in (datasets). The efficiency of the classifier was calculated by using deep learning technology. Where we built a (Convolution Neural Network) consisting of (15) layers and then we trained these layers on the images resul

关键词： Feature extraction

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Maternal Health Risk Classification - A Comparison between Algorithm Decision Tree and k-Nearest Neighbor (kNN)

Maternal Health Risk Classification - A Comparison between A...

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2023 International Conference on Sustainable Emerging Innovations in engineering and Technology, ICSEIET 2023

作者： Fatmawati, Maylia Novita, Mega Saputro, Nugroho Dwi Chauhan, Alok Singh Nada, Noora Qotrun Sinha, Amit Herlambang, Bambang Agus Gupta, Shruti Universitas Pgri Semarang Faculty of Engineering and Informatics Department of Informatics Semarang Indonesia Universitas Pgri Semarang Postgraduate Program of Science Education Semarang Indonesia School of Computing Science & Engineering Galgotias University Greater Noida India ABES Engineering College Department of Computer Science & Engineering Uttar Pradesh Ghaziabad201009 India

ISBN: (纸本)9798350329186

Maternal health is a critical concern, particularly for individuals who are pregnant and will shape the future generations. However, not all expectant mothers receive tailored attention and care for their unique health needs. Consequently, many mothers face high levels of health risks during pregnancy, highlighting the importance of classifying maternal health risks. Classification can help identify influential factors affecting maternal health and predict risk levels for individual mothers. In the field of data mining, various classification methods exist for analyzing complex datasets. This study focuses on two widely used algorithms: decision tree and k-Nearest Neighbor (kNN). By employing these algorithms, we aim to classify a dataset comprising 1,014 records of maternal health risk levels. Through cross-validation and T-tests, we rigorously evaluate the performance of the decision tree and kNN algorithms in this context. Our findings indicate that the kNN algorithm is more suitable for classifying maternal health risks, achieving a significantly higher accuracy of 71.50% compared to the decision tree algorithm's accuracy of 70.71%. This result establishes the superiority of the kNN algorithm in accurately classifying maternal health risks. These findings have implications for developing targeted interventions and tailored healthcare strategies to mitigate identified risks. © 2023 IEEE.

关键词： Health risks

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A Parallel Steganography Algorithm Using a New Secret Key Generation

A Parallel Steganography Algorithm Using a New Secret Key Ge...

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IEEE Annual Ubiquitous computing, Electronics & Mobile Communication Conference (UEMCON)

作者： Ahmed Imad Hammoodi Al-Jarah Jorge Luis Ortega Arjona Postgraduate in Science and Computing Engineering National Autonomous University of Mexico Mexico City Mexico Mathematics department Science faculty National Autonomous University of Mexico Mexico City Mexico

ISBN: (数字)9798331540906

ISBN: (纸本)9798331540913

Computation has mostly used parallelism for high-performance computation, and multicore processors have gained popularity because they offer better processing time. However, one of the most challenging tasks to achieve is securely exchange confidential data over the network between sender and receiver. The research work in this paper explains how secret key steganography, combined with parallel processing, is utilized to conceal secret data within an image. The proposed algorithm describes and focuses on the generation method of a secret key while merging it with the Least Significant Bit (LSB) algorithm to achieve robustness, as well as parallel computing to improve the processing time in both the encoding/decoding phases. The proposed algorithm adds another layer of security by adding a robustness parameter (secret key), convenient for keeping secret, confidential, and crucial data. Parallel processing, combined with the new method to formulate the secret key is the novelty and strongest attribute of the proposed algorithm. When parallel computing is applied, the process speeds up compared with the same algorithm in the sequential version. The results are compared with the LSB algorithm in terms of the peak signal to noise ratio (PSNR) and mean square error (MSE) values, aspiring to present that the proposed algorithm adds robustness without affecting image imperceptibility.

关键词： Steganography Visualization PSNR Program processors Multicore processing Receivers Parallel processing Mobile communication Robustness Security

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Integrating Deep Learning in Project Management: Improving Efficiency and Effectiveness in Project Planning and Execution 4

Integrating Deep Learning in Project Management: Improving E...

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4th IEEE Asian Conference on Innovation in Technology, ASIANCON 2024

作者： Shukla, Sunil Singh, Jagendra Sahu, Hemant Kanthalia, Shilpa Taufikin Elangovan, Muniyandy Graphic Era Hill University School of Computing Dehradun India Bennett University School of Computer Science Engineering & Technology Greater Noida India Department of Cs & It Udaipur India Faculty of Management Studies Udaipur India Kudus Department of Postgraduate Kudus Indonesia Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Biosciences Chennai India

ISBN: (纸本)9798350354218

The purpose of this research is to explore the use of deep learning technologies, namely the K-Nearest Neighbors model within the textile manufacturing process to test the improvement of the said process. To properly implement the model, we must use real-time data from the process and evaluate the improvement depending on a number of factors: how much does the maintenance cost decrease, how accurate is the inventory management, and how well the program forecasts demand, all of which should lead to an improvement of profit. First, the analysis of the results proved that the implementation of KNN model leads to a significant decrease of maintenance costs: while without the model the reduction was 15%, with it cost maintenance cost a 25% decrease. Second, the usage of a model improves inventory management accuracy: before the use of KNN, it was 85%, while after it rose to 95%. Third, demand forecasting becomes more accurate, as the difference was 75% to the positive without the model and 90% with it. The use of a model improved all aspects, and the most improved was profit: before the implementation of the KNN model, profit was 10%, and it was 40% after, which led to the conclusion that the implementation of deep learning models, namely the KNN model, improves the effectiveness of textile manufacturing process and positively affects the profitability and the production process as a whole. © 2024 IEEE.

关键词： Inventory control

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Maternal Health Risk Classification - A Comparison between Algorithm Decision Tree and k-Nearest Neighbor (kNN)

Maternal Health Risk Classification - A Comparison between A...

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Sustainable Emerging Innovations in engineering and Technology (ICSEIET), International Conference on

作者： Maylia Fatmawati Mega Novita Nugroho Dwi Saputro Alok Singh Chauhan Noora Qotrun Nada Amit Sinha Bambang Agus Herlambang Shruti Gupta Department of Informatics Faculty of Engineering and Informatics Universitas PGRI Semarang Semarang Indonesia Postgraduate Program of Science Education Universitas PGRI Semarang Semarang Indonesia School of Computing Science & Engineering Galgotias University Greater Noida India Department of Computer Science & Engineering ABES Engineering College Ghaziabad Uttar Pradesh India

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ISO X3D 4.0 Audio Graph for web3D applications. Latest trends in declarative 3d sound for the web

ISO X3D 4.0 Audio Graph for web3D applications. Latest trend...

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Immersive and 3D Audio: from Architecture to Automotive (I3DA)

作者： Maria Papadaki Don Brutzman Eftychia Lakka Richard Puk Georgios Daskalakis Athanasios G. Malamos Dept of Electrical and Computer Engineering Hellenic Mediterranean University Heraklion Greece Naval Postgraduate School (NPS) Monterey California USA Faculty of Computing Engineering and Science University of South Wales UK Intelligraphics Inc.

Our work, as 3D Audio Working Group of Web3D Consortium, aims to integrate acoustic properties associated with geometric shapes together with 3D spatial sound and insert this new technology into the X3D v4.0 ISO standard. In this paper we present X3D 4.0 Audio Graph API as it is embedded with all the latest improvements and examples. Moreover, we introduce novel ideas and use cases on how X3D v4.0 may improve immersion experience in Metaverse games, theatre or music performances and concerts. In this paper we introduce new audio components of the X3D standard and we present a case study of a platform that enhances users’ experience in scenarios of live online performances, mainly theater or music concerts, by enriching the realism of the streamed audio through auralization and virtual specialization. Our strong point is that we manage to include all the necessary information inside the scene nodes and combine three technologies that serve different purposes to work harmonically together, allowing multiple people to stream and enjoy the performance as they would in a real theater. We achieve this goal by joining state of the art technologies that involves web3D, teleconferencing and sound. Thus we may encourage community to create new real time applications like virtual theatre or tele-orchestras.

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Graphene's photonic and optoelectronic properties——A review

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Chinese Physics B 2020年第3期29卷 13-35页

作者： A J Wirth-Lima P P Alves-Sousa W Bezerra-Fraga Department of Physics Federal Institute of EducationScience and Technology of Ceara Campus SobralCearaBrazil Postgraduate Program in Electrical Engineering and Computing Federal University of Ceara(U.F.C.)Sobral CearaBrazil

Due to its remarkable electrical and optical properties,graphene continues to receive more and more attention from researchers around the *** excellent advantage of graphene is the possibility of controlling its charge density,and consequently,the management of its conductivity and dielectric constant,among other *** is noteworthy that the control of these properties enables the obtaining of new optical/electronic devices,which would not exist based on conventional ***,to work in this area of science,it is necessary to have a thorough knowledge regarding the electrical/optical properties of *** this review paper,we show these graphene properties very well detailed.

关键词： absorbance conductivity dielecric constant dispersion relation

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Hybrid Optimization of Horizontal Alignments in European Terrains: A Comparative Study 28th

Hybrid Optimization of Horizontal Alignments in European T...

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28th European Conference on Applications of Evolutionary Computation, EvoApplications 2025, held as part of EvoStar 2025

作者： Espeseth, Ane Juříček, Martin Ludwig, Harald Michael Tušar, Tea Center for Computing in Science Education University of Oslo Oslo Norway Faculty of Mechanical Engineering Brno University of Technology Brno Czech Republic Johannes Kepler University Linz Austria Department of Intelligent Systems Jožef Stefan Institute Ljubljana Slovenia Jožef Stefan Postgraduate School Ljubljana Slovenia

ISBN: (纸本)9783031900617

Path planning across terrain is a fundamental challenge in civil engineering, with applications ranging from transportation infrastructure to urban development. Recent advances in computational methods have enabled automated route optimization, particularly in horizontal alignment problems that balance construction costs with terrain constraints. However, standardized comparisons of optimization approaches across diverse geographical contexts remain limited, hindering the development of reliable automated planning systems. Here we show through a systematic comparative study across three European landscapes that A* significantly outperforms RRT* in initial path generation, with better computational efficiency and terrain adaptation, while PSO demonstrates superior optimization capabilities compared to CMA-ES and DE in refining these paths against roadway construction criteria. Through extensive parameter validation, we find these performance advantages remain consistent across different geographical contexts and topographical challenges, with the hybrid A*-PSO approach achieving significantly better results than applying optimization algorithms to straight-line paths alone. These findings provide a comprehensive comparison of key algorithms in infrastructure planning optimization, demonstrating the relative strengths of different approaches in horizontal alignment tasks. This comparative analysis offers practical guidance for algorithm selection while highlighting opportunities for further development through the incorporation of real-world engineering constraints. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Urban growth

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Analysis of the Best Employee Selection Decision Support System Using Analytical Hierarchy Process (AHP) 1

Analysis of the Best Employee Selection Decision Support Sys...

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1st International Conference on Innovation and Application of science and Technology, ICIASTECH 2019

作者： Lia Hananto, April Priyatna, Bayu Fauzi, Ahmad Yuniar Rahman, Aviv Pangestika, Yulia Tukino Faculty of Computing Universiti Teknologi Malaysia Skudai Johor Malaysia Faculty of Technology and Computer Science Universitas Buana Perjuangan Karawang Indonesia Department of Informatics Engineering Universitas Widyagama Malang Indonesia Faculty of Postgraduate Management Computer Indonesia of University Indonesia

The award is given by the company to the best employees always to provide the best performance for companies that carry out duties and obligations in the company. How to give rewards to employees not only for how long they have been working at the company but about the results achieved. The gift can be in the form of salary or inventory from the company. So employees have great loyalty to the company. Decision making to determine the company can do the best employee by assessing the performance that has been done by employees at a specific time. Performance evaluation of Hon Chuan Company is influenced by several criteria, namely discipline, innovation, and responsibility. The support system for the best employee selection method uses the Analytical Hierarchy Process (AHP) method. The decision-making system is carried out to assess choices based on predetermined criteria. AHP method is applied to choose the best prospective employees. The calculation of the AHP method gives the results of the order of importance of criteria, namely discipline level (0.5584), responsibility (0.3196), and innovation (0.1220) and the best employee selection results obtained by Hendra (0.189), Vienna (0.189), Yin (0.145), Paul (0.109), Kandi (0.108), Kusworo (0.101), Bayu (0.088), and Ade Muhidin (0.072). © Published under licence by IOP Publishing Ltd.

关键词： Decision making

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A Machine Learning Model for Augmenting the Media Accessibility for the Disabled People

A Machine Learning Model for Augmenting the Media Accessibil...

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Communication, Security and Artificial Intelligence (ICCSAI), International Conference on

作者： Hari Krishnan Andi S. Senbagam Dilip Kumar Sharma Mayura Shelke N K Senthil Kumar Ramesh Chandra Poonia Centre for Postgraduate Studies Asia Metropolitan University Malaysia Department of Computer Science and Engineering Dhanalakshmi Srinivasan College of Engineering and Technology Mamallapuram Tamil Nandu India Department of Mathematics Jaypee University of Engineering and Technology Guna Madhya Pradesh India Department of Artificial Intelligence and Data Science AISSMS IOIT Pune India Department of Computer Science and Engineering School of Computing Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology (Deemed to be University) Chennai Tamil Nadu India Department of Computer Science CHRIST (Deemed to be University) Delhi-NCR Ghaziabad Uttar Pradesh India

In an era characterized by the proliferation of digital media, the need to efficiently use multimedia content has become paramount. This article discusses an innovative technique called “Fast Captioning (FC)” to improve media accessibility, especially for people with disabilities and others with time restrictions. Modern Machine Learning (ML) algorithms are incorporated into the framework, which speeds up video consumption while maintaining content coherence. The procedure includes extracting complex features like Word2Vec embeddings, part-of-speech tags, named entities, and syntactic relationships. Using annotated data, a ML model is trained to forecast semantic similarity scores between words and frames. The predicted scores seamlessly integrate into equations that calculate similarity, thus enhancing content comprehension. Through this all-encompassing approach, the article offers a comprehensive solution that balances the requirements of contemporary media with the accessibility requirements of people with disabilities, producing a more inclusive digital environment. Machine Learning-based Media Augmentation (ML-MA) has achieved the highest accuracy of 96%, and the captioning is accurate.

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