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Computer Science on Philosophy Perspective 1

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13th Computer Science Online Conference

作者： Nasution, Mahyuddin K. M. Univ Sumatera Utara Comp Sci Program Study Fac Comp Sci & Informat Technol Medan 20155 Sumatera Utara Indonesia

ISBN: (数字)9783031705182

ISBN: (纸本)9783031705175;9783031705182

This paper reveals the relationship between computer science and philosophy. With the aim of stating a picture of the development of computer science from a philosophical perspective, which requires concepts base on philosophy, namely language and logic in expressing the ontology of computer science into a definition. Language and logic become a forum for developing computer science through a methodology that is epistemologically appropriate to a culture or country. This relationship shows a variety of support for the development of computer science.

关键词： Ontology language logic definition epistemology methodology natural law

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Learning Module for Visually-Challenged Children in the Post-covid World 8th

Learning Module for Visually-Challenged Children in the Post...

引用

8th Smart Trends in Computing and Communications (SmartCom)

作者： Sunidhi, C. S. Kumar, Tarun PES Univ Bangalore 560085 Karnataka India Indian Inst Sci CPDM Bangalore Karnataka India

ISBN: (纸本)9789819713127;9789819713134

This study aims to develop a smart learning module for visually-challenged children in the post-covid world to provide sufficient educational resources and in-person support. A thorough case study is conducted, followed by ethnographic research and empathy-based design techniques. A smart learning device-with a Braille-type face for visually-challenged children-is designed with accessibility and inclusivity in mind, incorporating features and functions that make it easier for the visually-challenged to access new information, connect with others, and learn together. The device uses advanced technology and is composed of two main parts, six Braille keys and a tactile representation of texts, which allows users to access and read information. This device is also integrated with a smartphone application that would be used by sighted teachers (or individual) to send and receive information, track the students' progress and responses, and conduct virtual exams. Text-to-Braille and Braille-to-text conversion is done via the application to make it easier for both users. The proposed solution will not only help the visually-challenged children to cope with new learning methods but also provide a better learning experience.

关键词： Visually-challenged Covid-19 Learning module Braille Smart device

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Automatic Instance Segmentation Labeling of Road Sign Image from Bounding Box Data 9th

Automatic Instance Segmentation Labeling of Road Sign Image ...

引用

9th International Congress on Information and Communication Technology (ICICT)

作者： Manongga, William Eric Chen, Rung-Ching Chaoyang Univ Technol Dept Informat Management Taichung Taiwan

ISBN: (纸本)9789819735617;9789819735624

The rising popularity of artificial intelligence can be attributed to the amazing capabilities of supervised learning. This training method requires a vast amount of data to train the model. In computer vision, many datasets are publicly available for image classification and object detection tasks. However, the number of datasets available for image instance segmentation tasks could be improved, which shows how resource-intensive and complex the image labeling process is. Since many available image datasets are labeled for object detection, the preliminary task before instance segmentation, we propose a novel method for automatically labeling road marking signs based on bounding box-labeled data in this paper. Our method combines several image processing techniques to get the image labeled, for instance, segmentation. Tested on the Taiwan Road Marking Sign Dataset (TRMSD), our method can label more than 60% of the images. We are significantly cutting the time needed to label the images manually.

关键词： Image labeling Automatic labeling Image segmentation

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Evaluating Data Informativeness and Information Usefulness to Address the User's Information Needs 13th

Evaluating Data Informativeness and Information Usefulness t...

引用

13th Computer Science Online Conference

作者： Vicentiy, A. V. Kola Sci Ctr RAS Putilov Inst Informat & Math Modeling 24A Fersman St Apatity 184209 Russia Arctic Univ Apat Branch Murmansk Lesnaya St 29 Apatity 184209 Russia

ISBN: (纸本)9783031705946;9783031705953

Assessing the informativeness of data and the usefulness of information are relevant problems for user-oriented information systems. Currently, there are various approaches to solve these problems. This paper examines the possibility of applying quantitative approaches to assess the informativeness of data and usefulness of information. The paper analyses syntactic, semantic and pragmatic approaches to meet the information needs of the user. The analysis shows that the methods for estimating the quantity of information, which belong to the syntactic approach, cannot be effectively applied to assess the informativeness of data and the usefulness of information. These methods can only be used as auxiliary methods. The methods that belong to the semantic and pragmatic approach assess the meaning of information messages and therefore can be effectively used in user-centred information systems. It is noted that usefulness is a subjective characteristic of information and depends on the knowledge the user already possesses. The user's knowledge is described using a thesaurus. Therefore, the most promising methods for assessing the level of satisfaction of the user's information needs, are methods that allow taking into account the user's thesaurus.

关键词： Data Informativeness User's Information Needs User Mental Model Information Usefulness Quantitative Methods Pragmatic Approach Thesaurus User Modeling Human-Computer Interaction

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Performance Optimization in Agro-Vision by Assessing the Impact of Data Normalization and Standardization on Deep Learning Models 4th

Performance Optimization in Agro-Vision by Assessing the Imp...

引用

4th International Conference on Digital Technologies and Applications (ICDTA)

作者： Zarrouk, Yassine Bourhaleb, Mohammed Rahmoune, Mohammed Hachami, Khalid Hamdaoui, Hajar Al Kaddouri, Hanae Mohammed First Univ ENSAO LaRSA Oujda Morocco Mohammed First Univ LAPABE FSO Oujda Morocco Mohammed First Univ ENSAO SmartICT Oujda Morocco

ISBN: (纸本)9783031686740;9783031686757

Potato late blight is one of the commonserious diseases, caused by Phytophthora infestans, with major risks for agriculture production and food supply. This study addresses this challenge by critically evaluating the effect of normalization, image-wise standardization, and dataset-wise standardization preprocessing techniques on a YOLOv8m model designed for blight detection. The reported results of the normalization show it remains robust for generalization, especially in the case of unseen data with an mAP50 of 99.4%. At the same time, imagewise standardization still is an acceptable alternative with an mAP50 of 73.3%. Dataset-wise standardization is reported to showlesser efficacy in newdata scenarios resulting in 21.7% of mAP50. The YOLOv8m has a compact and streamlined architecture that projects preprocessing to be a core factor in disease detection, paving the way for further advances in precision agriculture.

关键词： Deep learning Crop disease detection Image preprocessing techniques Performance Optimization

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A New Obstacle Detection Approach for Railway Transit Using Cooperative Deep Learning Models 1

引用

International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Aydin, Ilhan Sener, Taha Kubilay Firat Univ Dept Comp Engn TR-23119 Elazig Turkiye

ISBN: (数字)9783031700187

ISBN: (纸本)9783031700170;9783031700187

In railway lines, the safety of the line and the line surroundings is of great importance for the operation of the train. An obstacle around the line causes accidents in railway transportation and endangers line safety. Ensuring a safe operating condition for the train and warning the driver early is an important need in this respect. Although deep learning-based object detection methods are recommended for detecting obstacles in the rail and surrounding objects, distance detection is not performed in these methods. In distance detection studies, additional cameras and sensors are needed. In this study, it is aimed to detect the rail and surrounding objects with a two-stage network. The first network determines the rail and its surroundings by performing semantic segmentation in real time. Then, if there is an obstacle in the segmented rail area, the distance of the obstacle will be estimated with a deep convolutional regression network. The modified Unet model will be used for segmentation. RailSem19 dataset is used to segment the railway and its surroundings. The object around railway is detected by using YoloV8 object detection model. The ZoeDepth model is activated only when there is an obstacle and the distance of the obstacle is measured. For this purpose, the network is trained on the KITI dataset and the distances of the images detected during the testing phase are determined.

关键词： Railway intrusion detection deep learning segmentation object detection

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How Do NoSQL Databases Handle Variety of Big Data? 9th

How Do NoSQL Databases Handle Variety of Big Data?

引用

9th International Congress on Information and Communication Technology (ICICT)

作者： Vagner, Aniko Univ Debrecen Fac Informat Dept Informat Technol Debrecen Hungary

ISBN: (纸本)9789819735556;9789819735563

Many research papers and books say that NoSQL databases were born to support big data and it is a well-known big data tool. Like the three V's of volume, variety, and velocity, numerous aspects describe dig data. This paper's primary objective is to investigate how NoSQL databases handle the variety of data, namely binary unstructured data, which is typically media assets like picture, audio, and video files. We chose the NoSQL databases based on the DB engines ranking, the first database from each NoSQL type: MongoDB, Redis, Cassandra, and Neo4j.

关键词： NoSQL databases Big data Variety

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A Structure for Forecasting Stomach Cancer Using Deep Learning and Advanced Tongue Characteristics 1

引用

8th Smart Trends in Computing and Communications (SmartCom)

作者： Reddy, D. Lakshmi Narayana Mahaveerakannan, R. Kumar, Santosh Kumaran, J. Chenni Bhanurangarao, M. Anantha Lakshmi Inst Technol & Sci Dept Comp Sci & Engn Anantapur Andhra Pradesh India Saveetha Inst Med & Tech Sci Saveetha Sch Engn Dept Comp Sci & Engn Chennai Tamil Nadu India ERA Univ Dept Comp Sci Lucknow Uttar Pradesh India

ISBN: (数字)9789819713134

ISBN: (纸本)9789819713127;9789819713134

The global health problem of gastric cancer has significantly impacted people's daily lives. Early detection and rapid treatment of stomach cancer patients considerably contribute in protecting human health. Routine gastric cancer tests, however, are time-consuming and run the risk of consequences. The performance of the current tongue segmentation algorithms in a typical context is good. Tongue segmentation is quickly completed in an open environment using a revolutionary deep neural network tongue segmentation technique that is appropriate for mobile devices. Given that the images taken by this device also include non-tongue areas, a special deep neural network was used to segment the tongue in order to reduce interference with feature extraction. Intelligent tongue diagnosis requires accurate tongue picture segmentation. In this manner, linkages between the nine recovered tongue traits and the disease as well as statistical and deep learning approaches were used to construct a forecast structure to predict gastric cancer. The experimental results demonstrated the suggested framework's 93.6% accuracy rate for threat detection. A method for investigating the connections between cancer of the stomach and tongue traits is provided by a structure to forecast gastric cancer that was developed by fusing statistics and deep learning approaches. With the use of this framework, early identification of stomach cancer is considerably simpler.

关键词： Novel deep neural network Non-intrusive deep learning Tongue characteristics And prediction structure for stomach cancer

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Investment Decision Making Using Fuzzy Logic and Ahp 10th

Investment Decision Making Using Fuzzy Logic and Ahp

引用

International Conference on New Technologies, Development and Application - Advanced Production Processes and Intelligent systems

作者： Ribeiro, Lucas Matheus Oliveira, Selma Regina M. Fluminense Fed Univ Volta Redonda RJ Brazil

ISBN: (纸本)9783031662706;9783031662713

The purpose of this article is to provide an application of a fuzzy logic model in conjunction with AHP to mitigate the uncertainty associated with the economic-financial analysis of companies in the cyclical consumption sector in Brazil, expanding the scope of accounting information, and helping managers in making investment decisions. Experts have judged companies based on indicators from specialized literature. Fuzzy logic was used to manage with the valuation of the uncertainty and the AHP method was used to rank companies based on Liquidity, Indebtedness and Profitability criteria. This approach provides a tool to assist managers in decision making. The interpretation of indicators through the fuzzy inference system and selection of alternatives is capable of providing decision support, dealing with the uncertainty of the decision-making process. This work contributes with knowledge in decision-making support systems. This research brings significant contributions: (i) it improves the quality of information under uncertainties and unpredictability;as is the case with investment decisions;and (ii) sheds light on managers and stakeholders in their economic-financial decision-making journeys;and (iii) signals the prominence of intelligent systems to support complex decisions. It is recommended to collect data from more experts in judging the criteria of importance.

关键词： Decision-making investments uncertainties framework fuzzy-logic AHP cyclic consumer sector in Brazil

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Towards a Healthcare 4.0 Vocabulary: A Patent-Based Approach 1

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11st World Conference on Information systems and Technologies (WorldCIST)

作者： Loiotile, Annamaria Demarinis De Nicolo, Francesco Agrimi, Adriana Conti, Giuseppe Amoroso, Nicola Bellotti, Roberto Univ Bari Aldo Moro Dipartimento Interateneo Fis I-70126 Bari Italy Politecn Bari Dipartimento Ingn Elettr Informaz I-70125 Bari Italy Univ Bari Aldo Moro Direz Ric Terza Missione & Int I-70125 Bari Italy Netval Network Valorizzaz Ric Univ Lecce Italy Univ Bari Aldo Moro Dipartimento Farm Sci Farmaco I-70125 Bari Italy

ISBN: (数字)9783031456510

ISBN: (纸本)9783031456503;9783031456510

In modern knowledge economies, intellectual property assets are both engines of development and drivers of social transition. One of the most widely used approaches to identifying promising emerging technologies, record the direction of technological development and R&D activities and forecast innovation is patent analysis. The paper analyses the patent information available in the Knowledge-Share (KS) platform, an Italian patents database, first by using Natural Language Processing and clustering techniques, and then, by means of a complex network analysis on the most frequent words, focuses the analysis on those clusters inherent to health in order to investigate the technologies used and their applications to the Healthcare 4.0 domain. The paper aims to a first attempt of formulating a vocabulary of Healthcare 4.0 based on the patents produced by the most important Italian universities and research centers.

关键词： Patent analysis Healthcare 4.0 Natural Language Processing Clustering Complex network

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