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42nd International Conference on Conceptual Modeling: ER Forum, 7th Symposium on Conceptual Modeling Education, SCME 2023, Project Exhibitions, Posters and Demos, and Doctoral Consortium, ER-Companion 2023

作者： Hausler, Dominique Klettke, Meike Störl, Uta University of Regensburg Data Engineering Group Faculty of Informatics and Data Science Bajuwarenstrasse 4 Regensburg93053 Germany University of Hagen Chair of Databases and Information Systems Faculty of Mathematics and Computer Science Universitätsstrasse 1 Hagen58084 Germany

In this article, we present an evolution language for graph databases and a method to realize evolution operations on graph databases and their schema. Graph database management systems like Neo4j can be used for different scenarios: they can store graphs where no semantic constraints are checked. It is also possible to use them to store graphs where the structure of nodes and relationships is regular, for example, because the nodes and relationships of a graph have been generated by an application. In the latter case, these structures may change, that means they can undergo evolution. Currently, there is no established evolutionary language for graphs. However, evolution operations (such as add, rename, delete, merge, copy, split and move) have already been developed for other database models. In this article, we will not only use the established evolution operations but additionally extend the operations appropriated. After analyzing evolution operators explicitly in the context of graph databases, we also created a new graph-specific operation: transform. Moreover, we suggest an evolution language to graph data and show how it can be executed on the graph database schema as well as on the instances (i.e. the graphs themselves). In doing so, some operations can be implemented native based on Cypher, others non-native using the APOC library for Neo4j. © 2023 CEUR-WS. All rights reserved.

关键词： evolution graph databases evolution graph evolution language graph schema description

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Text recognition on images using pre-trained CNN

arXiv

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arXiv 2023年

作者： Rizky, Afgani Fajar Yudistira, Novanto Santoso, Edy Department of Informatics Engineering Faculty of Computer Science University of Brawijaya Malang Indonesia

A text on an image often stores important information and directly carries high level semantics, makes it as important source of information and become a very active research topic. Many studies have shown that the use of CNN-based neural networks is quite effective and accurate for image classification which is the basis of text recognition. It can also be more enhanced by using transfer learning from pre-trained model trained on ImageNet dataset as an initial weight. In this research, the recognition is trained by using Chars74K dataset and the best model results then tested on some samples of IIIT-5K-Dataset. The research results showed that the best accuracy is the model that trained using VGG-16 architecture applied with image transformation of rotation 15°, image scale of 0.9, and the application of gaussian blur effect. The research model has an accuracy of 97.94% for validation data, 98.16% for test data, and 95.62% for the test data from IIIT-5K-Dataset. Based on these results, it can be concluded that pre-trained CNN can produce good accuracy for text recognition, and the model architecture that used in this study can be used as reference material in the development of text detection systems in the future. © 2023, CC BY-SA.

关键词： Semantics

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Compression through extraction of learned parameters from images in de-correlated image space

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Iran Journal of computer Science 2024年第2期7卷 259-277页

作者： Hasnat, Abul Halder, Santanu Bhattacharjee, Debotosh Government College of Engineering and Textile Technology West Bengal Berhampore India Government College of Engineering and Leather Technology West Bengal Kolkata India Computer Science and Engineering Jadavpur University Kolkata 700032 India Center for Basic and Applied Science Faculty of Informatics and Management University of Hradec Kralove Rokitanskeho 62 Hradec Kralove 500 03 Czech Republic

Image compression is a class of algorithms that reduces the storage space requirement for a digital image. Lossy image compression techniques achieve higher compression but the visual quality of the decompressed image is degraded many times. Decompressed images lose their visual appeal due to compression artifacts. These compression artifacts are introduced due to the quantization step of the compression phase. We developed a lossy image compression technique that works on the spatial domain and de-correlated color model. For the luminance channel compression, the modified Vector Quantization method is used. In the case of chrominance channels, a feature vector is built for each pixel using the neighborhood statistics and cluster information of the pixel. For all the pixels of the image, using these feature vectors, a training dataset is formed. For the training of an artificial neural network (ANN), a feature vector of a pixel is used as the input and its respective chrominance value is used as the target output. Two training datasets are used to train two ANNs separately—one for the Cb channel and one for the Cr channel. These two trained ANNs are stored as the compressed form for the chrominance channels. During the decompression process, first, the luminance channel is reconstructed. Later, for each chrominance channel, the respective trained ANN predicts the chrominance values for each pixel. Thus, the whole image is reconstructed. The method has been tested on the benchmark images and also color images from the UCID v.2 database. The experimental result shows that the method successfully avoids the blocking artifacts in the reconstructed images. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： JPEG JPEG2000 Lossy image compression Neighborhood Statistics PSNR SSIM Vector quantization

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An Enhanced Deep Learning Method for Skin Cancer Detection and Classification

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computers, Materials & Continua 2022年第10期73卷 1109-1123页

作者： Mohamed W.Abo El-Soud Tarek Gaber Mohamed Tahoun Abdullah Alourani Department of Computer Science and Information College of Science in ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia Faculty of Computers and Informatics Suez Canal UniversityIsmailia41522Egypt School of Science Engineeringand EnvironmentUniversity of SalfordUK

The prevalence of melanoma skin cancer has increased in recent *** greatest risk from melanoma is its ability to broadly spread throughout the body by means of lymphatic vessels and ***,the early diagnosis of melanoma is a key factor in improving the prognosis of the *** learning makes it possible to design and develop intelligent systems that can be used in detecting and classifying skin lesions from visible-light *** systems can provide early and accurate diagnoses of melanoma and other types of skin *** paper proposes a new method which can be used for both skin lesion segmentation and classification *** solution makes use of Convolutional neural networks(CNN)with the architecture two-dimensional(Conv2D)using three phases:feature extraction,classification and *** proposed method is mainly designed for skin cancer detection and *** the public dataset International Skin Imaging Collaboration(ISIC),the impact of the proposed segmentation method on the performance of the classification accuracy was *** obtained results showed that the proposed skin cancer detection and classification method had a good performance with an accuracy of 94%,sensitivity of 92%and specificity of 96%.Also comparing with the related work using the same dataset,i.e.,ISIC,showed a better performance of the proposed method.

关键词： Convolution neural networks activation function separable convolution 2D batch normalization max pooling classification

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Aspect Level Songs Rating Based Upon Reviews in English

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computers, Materials & Continua 2023年第2期74卷 2589-2605页

作者： Muhammad Aasim Qureshi Muhammad Asif Saira Anwar Umar Shaukat Atta-ur-Rahman Muhammad Adnan Khan Amir Mosavi Department of Computer Science Bahria University Lahore54000Pakistan Lahore Institute of Science and Technology Lahore 54792Pakistan Department of Multidisciplinary Engineering Texas A&M UniversityCollege Station77843USA Department of Computer Science College of Computer Science and Information Technology(CCSIT)Imam Abdulrahman Bin Faisal University(IAU)P.O.Box 1982Dammam 31441Saudi Arabia Department of Software Gachon UniversitySeongnam13120Korea John von Neumann Faculty of Informatics Obuda UniversityBudapest1034Hungary Institute of Information Engineering Automation and MathematicsSlovak University of Technology in BratislavaBratislava81107Slovakia Faculty of Civil Engineering TU-DresdenDresden01062Germany

With the advancements in internet facilities,people are more inclined towards the use of online *** service providers shelve their items for *** users post their feedbacks,reviews,ratings,*** the use of the *** enormous increase in these reviews has raised the need for an automated system to analyze these reviews to rate these *** Analysis(SA)is a technique that performs such decision *** research targets the ranking and rating through sentiment analysis of these reviews,on different *** a case study,Songs are opted to design and test the decision *** aspects of songs namely music,lyrics,song,voice and video are *** the reason,reviews of 20 songs are scraped from YouTube,pre-processed and formed a *** machine learning algorithms—Naïve Bayes(NB),Gradient Boost Tree,Logistic Regression LR,K-Nearest Neighbors(KNN)and Artificial Neural Network(ANN)are *** performed the best with 74.99%*** are validated using K-Fold.

关键词： Machine learning natural language processing songs reviews:sentiment analysis songs rating aspect level sentiment analysis reviews analysis text classification music

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Hijaiyah Letter Learning Education Game for Children with Cerebral Palsy Elementary School Level Using Dance Pad Media

Hijaiyah Letter Learning Education Game for Children with Ce...

引用

International Conference on informatics and Computing (ICIC)

作者： Endah Sudarmilah Ainayah Syifa Hendri Devi Afriyantari Puspa Putri Wiwien Dinar Pratisti Fatah Yasin Al Irsyadi Ika Safitri Windiarti Informatics Engineering Department Faculty of Communication and Informatics University Muhammadiyah Surakarta Surakarta Indonesia Psychology Department Faculty of Psychology University Muhammadiyah Surakarta Surakarta Indonesia Computer Science Department Engineering Faculty Universitas Muhammadiyah Palangkaraya Indonesia

ISBN: (数字)9798331517601

ISBN: (纸本)9798331517618

Children with special needs cerebral palsy are children who have movement disorders, muscle tone, or posture caused by damage to the immature and developing brain. The learning method for children with cerebral palsy is different from normal children in general. The learning method used must adhere to the same principles, namely interesting, easy to accept and remember, and must be adapted to the ability to control motion. One method that can be used in the learning process of children with cerebral palsy is using game media. This study aims to design and create an educational game for learning hijaiyah letters that are tailored to the needs and motor training of Cerebral Palsy children. The research was conducted at the MI Muhammadiyah PK Kartasura School with the needs of the school as the main reference. This game is developed using 2D Game engine as the main application in making games and a dance pad as a liaison between the game and the controller. The design of this game uses the SDLC (System Development Life Cycle) method with the Waterfall model and is tested using the black box testing method and the SUS (System Usability Scale) method. The expected result of this research is an educational game that is easy to play by children with Cerebral Palsy in the light category, very interesting, can be used to train children’s motor skills, and can be used by teachers as an interactive and fun learning medium. Based on the black box testing, it shows that the game is running as expected, moreover the SUS testing got 70,625 score which was included in the Good category.

关键词： Learning systems Training Cerebral palsy Humanities Games Media Muscles Motors Usability Testing

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A Multivocal Review of MLOps Practices, Challenges and Open Issues

arXiv

引用

arXiv 2024年

作者： Eken, Beyza Pallewatta, Samodha Tran, Nguyen Khoi Tosun, Ayse Babar, Muhammad Ali Faculty of Computer and Information Sciences Sakarya University Turkey CREST - The Centre for Research on Engineering Software Technology The University of Adelaide Australia Faculty of Computer and Informatics Engineering Istanbul Technical University Turkey

With the increasing trend of Machine Learning (ML) enabled software applications, the paradigm of ML Operations (MLOps) has gained tremendous attention of researchers and practitioners. MLOps encompasses the practices and technologies for streamlining the resources and monitoring needs of operationalizing ML models. Software development practitioners need access to the detailed and easily understandable knowledge of MLOps workflows, practices, challenges and solutions to effectively and efficiently support the adoption of MLOps. Whilst the academic and industry literature on the MLOps has been growing rapidly, there have been relatively a few attempts at systematically synthesizing and analyzing the vast amount of existing literature of MLOps for improving ease of access and understanding. We conducted a Multivocal Literature Review (MLR) of 150 relevant academic studies and 48 gray literature to provide a comprehensive body of knowledge on MLOps. Through this MLR, we identified the emerging MLOps practices, adoption challenges and solutions related to various areas, including development and operation of complex pipelines, managing production at scale, managing artifacts, and ensuring quality, security, governance, and ethical aspects. We also report the socio-technical aspect of MLOps relating to diverse roles involved and collaboration practices across them through the MLOps lifecycle. We assert that this MLR provides valuable insights to researchers and practitioners seeking to navigate the rapidly evolving landscape of MLOps. We also identify the open issues that need to be addressed in order to advance the current state-of-the-art of MLOps. Copyright © 2024, The Authors. All rights reserved.

关键词： Machine learning

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CONCEPT OF DELIVERY SYSTEM IN THE SMART CITY ENVIRONMENT

arXiv

引用

arXiv 2023年

作者： Špitálová, Zuzana Leontiev, Oliver Harmaňoš, Patrik Institute of Computer Engineering and Applied Informatics Faculty of Informatics and Information Technology Slovak University of Technology Bratislava Slovakia

Regarding to the smart city infrastructures, there is a demand for big data processing and its further usage. This data can be gained by various means. There are many IoT devices in the city, which can communicate and share the information about the environment which they are situated in. Moreover every personal mobile device can also participate in this process and help to gain data via various applications. Every app provides the useful data, enabling the location and data sharing. This data can be further processed and used for improving the city infrastructure, transport or other services. We designed the system for shared delivery process, which can help to achieve the described situation. It consists of frontend and backend part. The frontend part, multiplatform mobile app, represents the graphical interface and the backend part represents the database for the gained data. © 2023, CC0.

关键词： Smart city

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Towards Designing a Low-Cost Humanoid Robot with Flex Sensors-Based Movement*

Towards Designing a Low-Cost Humanoid Robot with Flex Sensor...

引用

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Muhammad H. Al Omoush Sameer Kishore Tracey Mehigan Faculty of Engineering and Computing Dublin City University Dublin Ireland Department of Computer Engineering and Informatics Middlesex University Dubai UAE

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Humanoid robots have potential applications across diverse sectors, including education, healthcare, and customer service. This paper presents a project on designing and building a low-cost humanoid robot equipped with a flex sensor-based movement mechanism, highlighting its compatibility with Raspberry Pi and microcontrollers such as Arduino Uno and Nano. The project aims to investigate the robot's relevance and effectiveness within educational settings to showcase how a low-cost humanoid robot can potentially support the United Nations' fourth Sustainable Development Goal (UN SDG4) by improving access to quality education through innovative robotics solutions. The robot was tested in a cycle two school (covering Grades 5 to 8 (ages 10 to 13)) in Dubai, United Arab Emirates. It was integrated into math, science, and design technology classes to assess its functionality and efficiency. Surveys conducted among students and teachers showed a high level of acceptance towards the robot, with over 85% of respondents expressing positive attitudes about its presence and interaction in the classroom. However, teachers and students provided feedback concerning the robot's shape, capabilities, and movement mechanism. Teachers also appreciated the robot's alignment with the UN SDG4, stating its capability to support students learning and engagement. The authors highlighted the robot's potential to assist students with sensory challenges, such as hearing and vision impairments, and learning difficulties like dyslexia while emphasizing their commitment to enhancing its accessibility features for a more inclusive learning environment.

关键词： Surveys Flexible printed circuits Shape Microcontrollers Education Visual impairment Humanoid robots Robot sensing systems Sustainable development Robots

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The Development of a Glove-like Controller Interface for VR applications 14

The Development of a Glove-like Controller Interface for VR ...

引用

14th ACM SIGMM Workshop on Immersive Mixed and Virtual Environment Systems, MMVE 2022

作者： Salgado, Eduardo Pereira Salgado, Eurico Marques Salgado, Débora Pereira Rodrigues, Thiago Braga Faculty of Computer Science Federal University of Uberlândia Uberlândia Brazil Faculty of Mechanical Engineering Federal University of Uberlândia Uberlândia Brazil Faculty of Engineering & Informatics Technological University of the Shannon Athlone Ireland Department Computer and Software Engineering Technological University of the Shannon Athlone Ireland

ISBN: (纸本)9781450393829

Smart gloves are wearable interfaces which provide detection of movements and gestures, kinesthetic, and even tactile feedback. These capabilities are important for immersive applications as it can bring more realistic features. The presented paper shows a concept of a working in progress application of a smart glove. The proposed hardware uses resistive flexible and electromagnets sensors to provide tactile and haptic feedback to be used in immersive applications such as the ones that use Virtual Reality (VR). The project will be done in a way that can provide user-centric requirement such as: the glove must be lightweight, comfortable, adjustable to different hands and finger shapes, and low cost to be manufactured. The intend is to use this glove as part of a biggest framework and immersive application. © 2022 ACM.

关键词： Wearable sensors

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