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Encapsulation component and Its Incidence into Scientific Software Performance 7th

Encapsulation Component and Its Incidence into Scientific So...

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7th international conference on Science, Technology and Innovation for Society, CITIS 2021

作者： Pizarro-Vasquez, G. Omar Barahona, Felix Botto-Tobar, Miguel Universidad Politécnica Salesiana Guayaquil Ecuador Guayaquil Ecuador Eindhoven University of Technology Eindhoven Netherlands Universidad de Guayaquil Guayaquil Ecuador

ISBN: (纸本)9789811641251

Performance is considered an important feature rather than the application of programming techniques for better software design in most scientific software developers. therefore, the problem arises if the software is developed without considering a specific paradigm or some programming technique when performing maintenance;tasks related to this activity are complicated, since almost no one would understand the source code. the goal of this research is to verify the performance of the software with or without an encapsulation component. An ex-post-facto experimental methodology has been implemented, carrying out a descriptive analysis of the data and then concluding by verifying the hypothesis by means of a robust test. this work was carried out by running algorithms written in the programming language Java by using three data groups in different conditions to analyze their behavior. Results show is that the application of the encapsulation component of the object-oriented paradigm does affect the execution of the scientific software performance. © 2022, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Object oriented programming

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Exploring Attribute-Based Facial Synthesis with generative Adversarial Networks for Enhanced Patient Simulator Systems

Exploring Attribute-Based Facial Synthesis with Generative A...

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Software and System engineering (ICoSSE), international conference on

作者： Tariq Emad Ali Faten Imad Ali Norbert Pataki Alwahab Dhulfiqar Zoltán dept. of Information and Communication Engineering Al-Khwarizmi College of Engineering University of Baghdad Baghdad Iraq dept. of Biomedical Engineering College of Engineering AL-Nahrain University Baghdad Iraq dept. of Programming Languages and Compilers Faculty of Informatics Eötvös Loránd University Budapest Hungary

ISBN: (数字)9798350386592

ISBN: (纸本)9798350386608

Image generation using deep learning generative models has witnessed significant strides in various domains, particularly in scene and object generation. However, the complexities escalate when applied to facial image generation, especially in healthcare scenarios where detailed and realistic depictions are crucial. this paper introduces a pioneering approach to generating lifelike faces with specific attributes, including age, hair color, and gender, leveraging the manipulable latent space of a generative Adversarial Network (GAN). the proposed system not only holds promise for applications such as criminal identification and film production but also showcases practical implications in the healthcare domain. By offering a user-friendly interface for attribute input and face display, the system facilitates healthcare professionals in generating diverse patient avatars for medical training simulations. the implementation utilizes Python, PyTorch, and the CelebA dataset, with the training process conducted on Google Colab for computational efficiency. this work represents a novel intersection of advanced deep learning, human-computer interaction, and real-world healthcare applications, providing a holistic exploration of attribute-driven face synthesis in the medical field.

关键词： Training Deep learning Image synthesis Medical services generative adversarial networks Systems engineering and theory Software

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A three-Stage Guided Learning Occluded Face Restoration Scheme Based on GAN

A Three-Stage Guided Learning Occluded Face Restoration Sche...

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Software engineering and Computer Science (CSECS), international conference on

作者： Xiliang Jiang Bo Xia Xiaoyan Yang Bo Gao Bingkang Liu Wuhan Maritime Communication Research Institute (WMCRI) Wuhan Hubei China

ISBN: (数字)9798331522216

ISBN: (纸本)9798331522223

Facial recognition systems often face challenges with partial occlusions, which hinder feature identification and degrade model performance. Although GAN-based methods have shown promise, their reliance on synthetic datasets limits real-world applicability due to the lack of dataset realism. In this paper, we propose a novel three-stage framework that uses occlusion region prediction, facial component segmentation, and face restoration based on the outputs from the initial stages. this approach effectively handles diverse occlusions and bridges the gap between synthetic and real-world scenarios. Experimental results show the superiority of our method, achieving over 91 % on a similarity measure and outperforming existing methods.

关键词： Accuracy Face recognition Maintenance engineering Logic gates generative adversarial networks Skin Robustness Image restoration Synthetic data Software engineering

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Introducing Green thinking Into CS Bachelor Curriculum 2023

Introducing Green Thinking Into CS Bachelor Curriculum

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28th Annual conference on Innovation and Technology in Computer Science Education (ITiCSE)

作者： Oprescu, Ana Kokken, Ingrid Maat, Kyrian de Geus, Florine Univ Amsterdam Amsterdam Netherlands

ISBN: (纸本)9798400701399

By 2030 greenhouse gas emissions should be reduced by at least 55%. Despite hardware becoming more energy-efficient (Koomey's law), the ever-increasing reliance on computer technology has increased the energy usage due to ICT significantly. In software engineering (SE), there are many choices from programming languages to development patterns that influence energy efficiency. Recent research inspired our work on incorporating energy efficiency into SE education. An international group of researchers formulated initial recommendations for introducing green and sustainable software engineering [4] to students. An EU-US team formulated more refined recommendations for introducing green thinking as modules in existing courses [3]. ICT4S'22 best paper addressed HES eco-anxiety when teaching sustainability [2]. In this work we report on the experience of introducing reflection on energy efficiency into the default requirements of a SE course, and how that influenced students to address energy efficiency in their projects. Out of 8 teams, 7 implemented at least a small energy-efficient component. However, as one group donated to a climate charity in bitcoins, we need more ways to raise awareness.

关键词： project-based software engineering energy efficiency awareness

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Automatically Generating Front-End Source Code Method for Complex Table Structures Based on Vue

Automatically Generating Front-End Source Code Method for Co...

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2023 7th international conference on Electrical, Mechanical and Computer engineering (ICEMCE)

作者： Xiangfei She Beibei Bian School of Computer Technology and Engineering Changchun Institute of Technology Changchun China

In enterprise software development, component-based front-end page technology is becoming increasingly important. However, traditional manual component-based programming is difficult to adapt to increasingly complex enterprise data table structures. this can lead to a large workload and slow down the development process. To address this issue, this paper proposes a method for automatically generating front-end source code for complex table structures based on Vue (AGT-Complex). this method uses hierarchical data structure recognition and expression to identify complex Excel table structures. It then forms a semantic mapping between business data tables and front-end program tables. Finally, it can generate code based on Vue components. Experimental results show that this method is effective and can greatly improve development efficiency. It can be used to develop complex data software with a high degree of automation.

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Monitor the Effectiveness of Cardiovascular Disease Illness Diagnostics Utilizing AI and Supervised Machine Learning Classifiers 7th

Monitor the Effectiveness of Cardiovascular Disease Illness ...

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7th international conference on Information and Communication Technology for Intelligent Systems, ICTIS 2023

作者： Rathod, Dushyantsinh B. Patel, Yesha Jethava, Archana Gohel, Namrata Suthar, Dhruvi Varia, Dhaval Shah, Nirav Barot, Janki Computer Engineering Department Ahmedabad Institute of Technology Gujarat Ahmedabad India Department of CSE GLS Institute of Faculty of Engineering & Technology GLS University Gujarat Ahmedabad India Vishwakarma Government Engineering College Gujarat Ahmedabad India Lambton College Toronto Canada Silver Oak University Gujarat Ahmedabad India

ISBN: (纸本)9789819940394

the heart is a crucial component of all living organisms. Greater thoroughness and precision are required for heart disease diagnosis and prognosis since even a little error may result in serious consequences or even death;there are many heart-related fatalities and the number is growing daily (Kumar et al. in Cardiac disease prediction using data mining algorithm. Springer Nature Singapore, Singapore, 2020). An illness awareness prediction system is a crucial component needed to address this issue. Machine learning is an illustration of AI (artificial intelligence). It is quite helpful for predicting all kinds of occurrences related to natural catastrophes. In this work, utilizing benchmark data sets from Kaggle for training and testing, we assess the efficiency of machine learning algorithms for heart disease prediction (Gupta and Vinayaka in Cardiac arrest disease prediction system using classification algorithms. Springer Nature Singapore, Singapore, 2020), including k-proximal neighbors, decision trees, linear regression, and Random Forest Classifier. the Anaconda (Jupyter) notebook, which includes a range of libraries and header files that make the process quick and easy, is the ideal tool for utilizing Python programming. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Heart

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Color Detection Using Python 7

Color Detection Using Python

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7th IET Smart Cities Symposium, SCS 2023

作者： Bachute, Mrinal Singh, Aditya Kumar, Akash Sahil, Aman Symbiosis International University Maharashtra Pune412308 India

ISBN: (纸本)9781839539831

RGB color detection is a fundamental component of computer vision with a wide range of applications, including image processing, object recognition, industrial automation, and design. this article provides a comprehensive overview of RGB color detection in Python, a popular and versatile programming language, with the aim of accurately identifying and analysing colors in digital images or video streams in a real-time context. this approach uses Python’s powerful libraries and packages, like OpenCV or NumPy, to quickly and easily access and process image data. It uses the RGB color space to represent and detect colors. the process includes getting the image, setting the color threshold, and segmenting the objects to identify and track specific colors in the image or *** experimental results show how powerful and fast the RGB color detection system is. It’s really good at picking up pre-defined colors in different lighting conditions and different color palettes. It’s really useful for tracking objects, recognizing gestures, and sorting colors, so it’s great for research and industry. this research is not only useful for computer vision, but it’s also a great resource for Python developers and researchers who want to use RGB color detection in their projects. It’s a great way to explore and come up with new ideas for color-based apps, and it shows how important color detection is in modern tech and automation. © the Institution of engineering & Technology 2023.

关键词： Industrial research

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Design and Implementation of a Smart Human Posture Monitoring Device Using a Wearable Vest 7

Design and Implementation of a Smart Human Posture Monitorin...

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7th international conference on Advances in Biomedical engineering, ICABME 2023

作者： Daou, Roy Abi Zeid Geha, Elio Aoun, Youssef Hayek, Ali Boercsoek, Josef Olmedo, Jose Javier Serrano Université la Sagesse Biomedical Engineering Department Furn El Chebbak Beirut Lebanon Mart Learning Education and Research Center Chananir Lebanon Lebanese German University Faculty of Public Health Biomedical Technologies Department Jounieh Lebanon University of Applied Science Hamm-Lippstadt Department Lippstadt 2 Hardware Engineering Marker Allee 76-78 Hamm59063 Germany University of Kassel Faculty of Electrical Engineering /Computer Science Department of Computer Architecture and System Programming Germany Universidad Politecnica de Madrid Lab of Bioinstrumentation and Nanomedicine Centro de Tecnologia Biomedica Spain

ISBN: (纸本)9798350325850

Chronic back pain can present a serious health concern, with symptoms that can significantly affect an individual's well-being, mobility, and overall quality of life over an extended period. While chronic back pain may manifest suddenly in some cases, it often develops gradually and persists for weeks, and in untreated cases, it can linger for years. Hence, the utilization of assistive devices such as wearable posture-monitoring vests can offer valuable assistance and guidance to users. this research paper is dedicated to the development of a system for detecting, diagnosing, and correcting poor posture, specifically leaning posture. the vest is designed to provide users with visual, auditory, and tactile cues to help them address this issue, thereby reducing the risk associated with leaning. Additionally, an integrated electrical box has been designed to consolidate all components directly onto the main board in a secure enclosure. this box also displays the daily count of instances where the user has leaned. this system is characterized by its electrical safety, portability, compactness, comfort, and affordability. A comprehensive analysis of the system's performance has been conducted with a meticulous evaluation of accuracy. Each component of the system has undergone successful testing, and the system as a whole is currently in the testing phase. the results of these tests have indicated a lack of faulty errors and have demonstrated outstanding accuracy and detection rates. Over 100 individuals of varying ages, genders, and BMI categories were involved in testing, with each person wearing the device for an average of six hours. the accuracy rate achieved was 98.85%, with an average of 54.35 instances of poor posture detected per participant. © 2023 IEEE.

关键词： Wearable technology

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Short-term power forecasting model of floating photovoltaic - A case study of Huainan floating photovoltaic plant, China 7

Short-term power forecasting model of floating photovoltaic ...

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7th IEEE international conference on Power and Renewable Energy, ICPRE 2022

作者： Bei, YaoPing Yuan, BingQing Cheng, DaLi Liu, Shenzhen Ma, Chao Zhang, Zihao Co. Ltd. Beijing China Solar Power Generation Co. Ltd. Three Gorges Renewable Energy Huainan Huainan China State Key Laboratory of Hydraulic Engineering Simulation and Safety Tianjin University Tianjin China

ISBN: (数字)9781665450638

ISBN: (纸本)9781665450638

Although the development of floating photovoltaic (FPV) in China is rapid, there are few reports on the power generation forecasting of FPV. Based on the monitoring data of the 150MW FPV plant in Huainan, a short-term power forecasting model for FPV plant is proposed in this paper. Firstly, the input variables of deep belief network (DBN) are selected based on the open-source R programming software;then, wavelet transform is used to decompose the power time series into several components with different frequencies, and convolutional neural network (CNN) is used to extract the nonlinear features and invariant structures of each component;finally, the back propagation neural network (BPNN) optimized by genetic algorithm (GA) is used to integrate the outputs of CNN and DBN to obtain the final PV power forecasting value. the simulation results show that the method proposed in this paper can obtain superior forecasting accuracy than other models. © 2022 IEEE.

关键词： Wavelet transforms

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Wi-piga: A personnel-independentmethod for actions recognition based on Wi-Fi 7

Wi-piga: A personnel-independentmethod for actions recogniti...

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7th international conference on Big Data Computing and Communications, BigCom 2021

作者： Hao, Zhanjun Niu, Juan Dang, Xiao-Chao Qiao, Zhiqiang College of Computer Science and Engineering. Northwest Normal University Gansu Province Internet of Things Engineering Research Center Lanzhou China

ISBN: (纸本)9781665442527

In the process of action recognition, due to the difference of channel state information (CSD collected by different experimenters, the identification method can not be Personnel independent. To address this issue, activity recognition method for combining convolutional neural network(CNN) and generative adversarial network(GAN) is put forward. the CSI data of yoga movements are collected, and the CSI data are preprocessed by second-order Butterworth and principal component analysis (PCA) at first. the high-level motion features which are personnel-independent are extracted by the fusion method, and then these motions are classified and recognized At the same time, whether the action is standardis judged. the experimental results show that this method can identify yoga movements successfully and it has nothing to do with people, which is of great significance for family sports guidance and sports experience. © 2021 IEEE.

关键词： Principal component analysis

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