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Enhancing Dental Diagnosis through Automated Detection of Teeth Diseases in Panoramic Radiographs

Enhancing Dental Diagnosis through Automated Detection of Te...

引用

2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Rawashdeh, Majdi Bdair, Tariq Salhi, DhaiEddine Al-Yamamah University Software Engineering Dept. Riyadh Saudi Arabia Psut Business Information Technology Dept. Amman Jordan Psut Data Science Dept. Amman Jordan

ISBN: (纸本)9798350351255

Edge learning has shown promising solutions to address diseases by exploiting edge computing capabilities. On the other hand, the analysis of dental radiographs is a crucial step in clinical routine practice since the dentist must evaluate tooth-related issues throughout the clinical diagnosis. Further, errors in manual human analysis may lead to false predictions. Fortunately, the automated approach for identifying and categorizing dental issues can help in the early diagnosis of diseases and prevent tooth loss. This paper aims to create a model that may offer a second viewpoint and simplify dental diagnosis for dentists. The proposed method utilizes state-of-the-art deep learning architecture for object detection. It provides panoramic teeth radiograph images to the proposed network to detect four teeth diseases: conservative (fillings and crowns), implant, RCT (root canal treatment), and bridges. After data preprocessing and augmentation, our framework is used to detect the above teeth diseases with high detection quality and accuracy with mAP and F1-score at 0.902 and 0.86, respectively. © 2024 IEEE.

关键词： Diseases

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Analyzing Cyberbullying Word Distribution Across Social Media to Develop Lexicon Dictionary 2

Analyzing Cyberbullying Word Distribution Across Social Medi...

引用

2nd IEEE International Conference on Networks, Multimedia and information technology, NMITCON 2024

作者： Sahana, V. Anil Kumar, K.M. Jss Academy of Technical Education Dept. of Information Science and Engineering Bengaluru560060 India Jss Science and Technology University Dept. of Computer Science and Engineering Mysuru570006 India

ISBN: (纸本)9798350372892

Social media platforms have become essential tools for communication, collaboration, and exchanging information, ideas, and knowledge among users worldwide. Despite their benefits, the anonymity offered by these platforms has unfortunately led to a rise in hate speech and cyberbullying, causing concern across the globe. This issue has drawn the attention of researchers and scholars now focused on devising methods for automatically detecting cyberaggression and hate speech. The goal is to mitigate these harmful behaviors and create safer online environments [1]. This study specifically aims to identify and analyze the usage of cyberbullying language within the English Tweet corpus, focusing on distinguishing between bullying and non-bullying language. This research contributes to developing more effective cyberbullying detection models by examining the frequency and patterns of cyberbullying words. These findings are vital for enhancing the efficacy of cyberbullying detection on social networks in future research efforts. The conclusions of the experiments indicate that the SVM achieved the highest average accuracy, approximately 84 %. © 2024 IEEE.

关键词： Anonymity

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End-To-End Knowledge Graph Construction and Reasoning Using Path Based Metrics 1

End-To-End Knowledge Graph Construction and Reasoning Using ...

引用

1st IEEE International Conference on Advances in Computing, Communication and Networking, ICAC2N 2024

作者： Shejole, Rohit Dofe, Sanket Shejole, Prachi Veermata Jijabai Technological Institute Dept. of Electrical Engineering Mumbai India Veermata Jijabai Technological Institute Dept. of Computer Engineering and Information Technology Mumbai India D.Y. Patil College of Engineering Dept. of Mechanical Engineering Pune India

ISBN: (纸本)9798350356816

The schema-less nature of knowledge graphs has led to their widespread adoption. It makes it possible for knowledge graphs to expand without interruption and to add new entities and relationships as needed. Knowledge graphs are now an effective tool for providing textual data with semantics and representing knowledge as a labelled directed graph. Every item, entity, and user are represented as nodes in a knowledge graph, which is then created by connecting the nodes that communicate with one another through edges. Knowledge graphs can hold a variety of more comprehensive types of information and have a wealth of natural semantics. Its mode of expression is similar to that of natural language. Nevertheless, there is still no accepted definition or format for expressing knowledge graphs. © 2024 IEEE.

关键词： Knowledge graph

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From Pixels to Prognosis: Exploring Convolutional Neural Networks for Cassava Leaf Disease Diagnosis 21

From Pixels to Prognosis: Exploring Convolutional Neural Net...

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21st OITS International Conference on information technology, OCIT 2023

作者： Pai, Abhishek Raotole, Atharv Shirodkar, Sailee Bose, Samprit Kolekar, Maheshkumar H. SPIT Mumbai Dept. of Information Technology Mumbai India IIT Patna Dept. of Electrical Engineering Patna India

ISBN: (纸本)9798350358230

Cassava is a major crop in many areas, but it is susceptible to a number of illnesses that can have a terrible impact on crop productivity and food security. For successful disease treatment and prevention, these diseases must be accurately and quickly detected. In this paper, we suggest a deep learning-based approach for diagnosing cassava leaf disease. We create a modified convolutional neural network architecture for feature extraction and classification that includes parallel pathways, multiple convolutions, max pooling, and global average pooling. Cassava leaf images from a large dataset, including both healthy leaves and several disease kinds, are used to train the model. Through extensive experimentation and evaluation, the proposed model demonstrates high accuracy and robust performance in classifying cassava leaf diseases. The proposed model has also achieved a training accuracy of 98.54%, validation accuracy of 97.84% and a testing accuracy of 98.08%. The suggested approach has enormous potential to aid farmers and researchers in early disease diagnosis, enabling prompt treatments and efficient crop management. Utilising cutting-edge technology to solve current problems and enhance sustainable agricultural practices is important, as demonstrated by the application of deep learning techniques in agriculture. © 2023 IEEE.

关键词： Diseases

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Filtering in Projection-based Integrators for Improved Phase Characteristics 63

Filtering in Projection-based Integrators for Improved Phase...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Chu, Hoang Van Den Eijnden, S.J.A.M. Heertjes, M.F. Heemels, W.P.M.H. Eindhoven University of Technology Control Systems Technology Section Dept. Mechanical Engineering Netherlands Asml Mechatronics & Measurements Systems Veldhoven Netherlands

ISBN: (纸本)9798350316339

Projection-based integrators are effectively employed in high-precision systems with growing industrial success. By utilizing a projection operator, the resulting projection-based integrator keeps its input-output pair within a designated sector set, leading to unique freedom in control design that can be directly translated into performance benefits. This paper aims to enhance projection-based integrators by incorporating well-crafted linear filters directly into its structure, resulting in a new class of projected integrators that includes the earlier ones, such as the hybrid-integrator gain systems (HIGS), as special cases. The extra design freedom in the form of two filters in the input paths to the projection operator and the internal dynamics allows the controller to break away from the inherent limitations of a linear control design. The enhanced performance properties of the proposed structure are formally demonstrated through i) a describing function analysis, ii) mitigation of the gain-loss problem (occurring in, e.g., HIGS), and iii) numerical case studies showcasing improved time-domain properties. The describing function analysis is supported by rigorously showing incremental properties of the new filtered projection-based integrators, thereby guaranteeing the steady-state responses to be unique and asymptotically stable. © 2024 IEEE.

关键词： Describing functions

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Sentiment Analysis of Tweets on the Russia-Ukraine War 4

Sentiment Analysis of Tweets on the Russia-Ukraine War

引用

4th International Conference on Advanced Research in Computing, ICARC 2024

作者： Pathinayake, Nilani Kulatileke, Lasitha Hettiarachchi, Chethana Yapa, Sachira Ahangama, Supunmali University of Sri Jayewardenepura Dept. of Mechanical Engineering Sri Lanka University of Kelaniya Dept. of Industrial Management Sri Lanka University of Moratuwa Dept. of Information Technology Sri Lanka

ISBN: (纸本)9798350384864

This study aims to mine public opinion on the X platform using sentiment analysis concerning the Russia-Ukraine war. The study seeks to address the contradiction in recent reports regarding public sentiment toward the conflict between Russia and Ukraine. The analysis used both supervised and unsupervised learning approaches. Under supervised learning, both BOW and TF-IDF features were used through CountVectorizer together with logistic regression and support vector machine to predict sentiments. TextBlob, SentiWordNet, AFINN, and VADER were used under unsupervised learning to measure subjectivity and polarity in the text data. The study found that public opinion supports Russia resulting in the majority of pro-Russia tweets. Even though public opinion about Russian leader, Putin is negative, his name is the most trending name on the X platform regarding this topic. On the other hand, even though tweets are slightly skewed towards supporting Russia the general sentiment on war is negative. The outcome of this analysis could significantly impact decision-making in political conflicts in general. The findings highlighted the impact of leader-centric influence on social media platforms in shaping public opinion. The results also showed that influential figures or leaders can strategically utilize social media to amplify their narratives during a conflict situation, though it contradicts public opinion. The study contributes by addressing the contradictions in recent reports and providing an understanding of public sentiment towards the Russia-Ukraine war on the X platform. It highlighted the complexity of public opinions by differentiating tweets between pro-Russia and pro-Ukraine sentiments regarding the war addressing few limitations in prior studies. © 2024 IEEE.

关键词： Sentiment analysis

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EFFECTIVE GRAYSCALE LASER LITHOGRAPHY FOR LARGE AREA 2.5D STRUCTURES 23

EFFECTIVE GRAYSCALE LASER LITHOGRAPHY FOR LARGE AREA 2.5D ST...

引用

23rd Slovak-Czech-Polish Optical Conference on Wave and Quantum Aspects of Contemporary Optics

作者： Zdurienčík, M. Jandura, D. Pudiš, Dušan University of Žilina Univerzitna 8215/1 01026 Žilina SlovakiaDept. of Physics Faculty of Electrical Engineering and Information Technology

ISBN: (数字)9781510688094

ISBN: (纸本)9781510688087

In the field of optical diffraction elements, laser lithography has an important role in the preparation of 2- and 2.5 dimensional microstructures in polymer materials. Rapid prototyping in the process of manufacturing such fine structures is key to boosting research of photonic components and devices. Standard direct laser writing (DLW) lithography process allows to create only on very small scales, limited by the construction of used setup. Using extremely fine and precise manipulation, we are creating these structures on relatively large surfaces in tens of millimeters squared. The latest results show that we can create structures with complex topography by manipulating height gradient of structures with exposure dose modulation, also known as grayscale lithography. This device can speed up of the preparation and expand the area of structure in single-step process. © 2025 SPIE.

关键词： Photonic devices

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The Image of Tourist Attraction in Bali Based on Big Data Analytics and Sentiment Analysis

The Image of Tourist Attraction in Bali Based on Big Data An...

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2023 International Conference on Smart-Green technology in Electrical and information Systems, ICSGTEIS 2023

作者： Saraswati, Ni Wayan Sumartini Ketut Gede Darma Putra, I. Sudarma, Made Made Sukarsa, I. Udayana University Dept. of Engineering Science Denpasar Indonesia Udayana University Dept. of Information Technology Denpasar Indonesia

ISBN: (纸本)9798350382822

Tourism development is currently very rapid due to advances in information technology. The growth of various digital tourism platforms makes it easy to obtain tourism information. Almost every time tourists leave traces of their travel experiences on digital platforms, one of them is a review. Until now, the review is only greatly beneficial to prospective tourists in terms of supporting decision-making about the consumption of tourism products and services to minimize the risk of failure. This research analyzed large amounts of reviews, known as big data, to benefit stakeholders. This research aimed to describe the image of Bali tourism that originated from tourist attraction reviews on TripAdvisor. Sentiment analysis was carried out using the Vader Lexicon method to obtain the image clarified using term frequency, bigrams, and topic-based trigrams. The analysis obtained several positive images of tourist attractions in Bali, including beautiful beaches, amazing temples, and friendly locals. Meanwhile, we recommend improvements to several negative images that we found such as dirty tourist objects, plastic waste, and disturbances from hawkers in order to get a better image of Bali tourism. © 2023 IEEE.

关键词： Big data

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Measures of Organizational Process Performance in the Capability Maturity Model Integration 24

Measures of Organizational Process Performance in the Capabi...

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24th International Arab Conference on information technology, ACIT 2023

作者： Al-Ghuwairi, Abdel-Rahman Al-Fraihat, Dimah Sharrab, Yousef Kittaneh, Ahmed Ali, Ahmed Alsarhan, Ayoub Alkhalidy, Muhsen The Hashemite University Faculty of Prince Al-Hussein Bin Abdallah Ii for Information Technology Dept. of Software Engineering Jordan Isra University Faculty of Information Technology Dept. of Software Engineering Jordan Isra University Faculty of Information Technology Dept. of Artificial Intelligence and Data Science Jordan The Hashemite University Faculty of Prince Al-Hussein Bin Abdallah Ii for Information Technology Dept. of Cyber Security Jordan The Hashemite University Faculty of Prince Al-Hussein Bin Abdallah Ii for Information Technology Dept. of Information Technology Jordan

ISBN: (纸本)9798350384307

The Capability Maturity Model Integration (CMMI) is widely utilized by organizations to facilitate process improvement. Among its 22 process areas, this paper focuses on the Organizational Process Performance (OPP) area, which assesses the effectiveness of a process. Specifically, this study examines one goal (establishing performance baselines and models) and two practices (establishing quality and process performance objectives and selecting processes within OPP. To measure these practices, the Goal Questions Metrics (GQM) approach is employed. Data was collected using a questionnaire, and the defined measures are validated quantitatively. 250 responses were used for analysis. The results obtained indicate that implementing the defined measures in companies would be beneficial for achieving high-quality processes in OPP and advancing the maturity level of CMMI. © 2023 IEEE.

关键词： Goal Questions Metrics (GQM) Software Quality, Organizational Process Performance, Capability Maturity Model Integration, CMMI

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Integrating Robotic Process Automation (RPA) with AI and ML for Efficient Banking Operations 2

Integrating Robotic Process Automation (RPA) with AI and ML ...

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2nd International Conference on Advances in Computation, Communication and information technology, ICAICCIT 2024

作者： Mohammed, Abubakar Syed, Waheeduddin Khadri Reddy, Janamolla Kavitha Jiwani, Nasmin Suganyadevi Dept. of Information Technology University of the Cumberlands HoustonTX United States Dept. of Information Technology University of the Cumberlands SomervilleNJ United States University of the Cumberlands - IT HillsboroughNJ United States Dept. of Information Technology University of The Cumberlands WilliamsburgKY United States Department of ECE Sri Eshwar College of Engineering Coimbatore641202 India

ISBN: (纸本)9798331541217

Integrating robotic method automation (RPA) with artificial intelligence (AI) and device getting to know (ML) has revolutionized the banking enterprise, permitting extra green and correct operations. RPA technology automates repetitive responsibilities, even as AI algorithms offer sensible selection-making competencies, and ML algorithms constantly learn and enhance from statistics. Collectively, they create a powerful synergy that improves client reports, reduces fees, and streamlines techniques. RPA can deal with high-quantity, rule-based duties, which include statistics entry and report processing, liberating human employees to focus on greater complicated and price-added sports. AI and ML can analyze significant amounts of information and offer valuable insights for fraud detection, danger evaluation, and customized guidelines for clients. This integration saves time, reduces blunders charges, and allows for better resource allocation, in the end leading to improved performance and cost-effectiveness in banking operations. © 2024 IEEE.

关键词： Cost effectiveness

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