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Private Continuous Survival Analysis with Distributed Multi-Site Data

Private Continuous Survival Analysis with Distributed Multi-...

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IEEE International Conference on Big Data

作者： Luca Bonomi Marilyn Lionts Liyue Fan Dept. Biomedical Informatics Vanderbilt University Medical Center Nashville TN Dept. Computer Science Vanderbilt University Nashville TN College of Computing and Informatics University of North Carolina Charlotte NC

Effective disease surveillance systems require large-scale epidemiological data to improve health outcomes and quality of care for the general population. As data may be limited within a single site, multi-site data (e.g., from a number of local/regional health systems) need to be considered. Leveraging distributed data across multiple sites for epidemiological analysis poses significant challenges. Due to the sensitive nature of epidemiological data, it is imperative to design distributed solutions that provide strong privacy protections. Current privacy solutions often assume a central site, which is responsible for aggregating the distributed data and applying privacy protection before sharing the results (e.g., aggregation via secure primitives and differential privacy for sharing aggregate results). However, identifying such a central site may be difficult in practice and relying on a central site may introduce potential vulnerabilities (e.g., single point of failure). Furthermore, to support clinical interventions and inform policy decisions in a timely manner, epidemiological analysis need to reflect dynamic changes in the data. Yet, existing distributed privacy-protecting approaches were largely designed for static data (e.g., one-time data sharing) and cannot fulfill dynamic data requirements. In this work, we propose a privacy-protecting approach that supports the sharing of dynamic epidemiological analysis and provides strong privacy protection in a decentralized manner. We apply our solution in continuous survival analysis using the Kaplan-Meier estimation model while providing differential privacy protection. Our evaluations on a real dataset containing COVID-19 cases show that our method provides highly usable results.

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AI Powered Screening Aid for Dyslexic Children in Tamil

AI Powered Screening Aid for Dyslexic Children in Tamil

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2023 International Conference on Advances in Intelligent Computing and Applications, AICAPS 2023

作者： Banumathi, K. Sudhasadasivam, G. Banurekha, B. Shahana, N. Vaishnavi, K. Psg Vishnugranthi School for Special Children Coimbatore India Psg College of Technology Dept. Computer Science and Engg Coimbatore India Psg College of Technology Dept of Biomedical Engg Coimbatore India

ISBN: (纸本)9798350333817

Dyslexia is a learning disorder characterized with a difficulty in learning due to impairment of the left hemisphere of the brain associated with processing. In India, the incidence of dyslexia is believed to be around 15%. Literacy is the foundation of all learning and hence, identifying dyslexia at an early age is critical. The appropriate age to identify dyslexia is between 5 and 8 years since early detection can nurture corrective measures. Identifying dyslexia at this age will also prevent future school drop outs. The major challenge in detecting dyslexia among children at an early age includes lack of awareness among school teachers and parents. The absence of simple standardized screening and assessment tools in regional languages makes the task more difficult. A Smartphone application to screen dyslexia offers the advantages of universal use and standardization. However, primary school educators feel the need to have screening apps in regional languages (like Tamil), as most of the communication in local population is using regional language. In this research work, a Smartphone based screening application for dyslexia is developed in Tamil. The app consists of questions that cover the areas of general qualities, health & personality, unique talents, speech & hearing skills, visual acuity& reading skills, writing & motor skills, mathematical ability and memory & cognitive skills. The app was created utilizing the expertise of special educators and following regional practices. The app generates visualizations and provides scoring on the severity level of dyslexia for the user. The report can be downloaded and printed. Then the dataset is subjected to training with five different machine learning algorithms and results are compared by their report of classification and error rates. © 2023 IEEE.

关键词： Audition

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Challenges of Integrating Blockchain Technology into Educational Institutions

Challenges of Integrating Blockchain Technology into Educati...

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International Symposium on Networks, computers and Communications (ISNCC)

作者： Abbas Hussein Ali Uraz YavanoğLu Dept. Of Computer Science Graduate School of Informatics Gazi University Ankara Turkey Dept. of Computer Engineering Faculty of Engineering Gazi University Ankara Turkey

ISBN: (数字)9798350364910

ISBN: (纸本)9798350364927

The latest advancements in blockchain technology have significantly influenced several sectors, such as banking, healthcare, and supply chain networks. Because of its distinct attributes, like decentralization, trustworthiness, and security, this technology has recently been employed in the field of education. While the blockchain is bright, several problems, such as legal, immutability, and scalability questions, continue to hinder its adoption in education. In this paper, we look at educational application system in terms of blockchain-based solutions that have been created for educational purposes, as well as the potential challenges of blockchain technology in the field of education.

关键词： computers Law Scalability Education Supply chains Medical services Blockchains Stakeholders Security Guidelines

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An Iterated Local Search Algorithm for Commuting Bus Routing Problem with Latest Arrival Time Constraint

An Iterated Local Search Algorithm for Commuting Bus Routing...

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2022 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2022

作者： Hashimoto, H. Hu, Y. Sugiura, T. Takada, Y. Yagiura, M. Tokyo University of Marine Science and Technology Dept. Logistics and Information Engineering Tokyo Japan Tokyo University of Science Dept. Applied Mathematics Tokyo Japan Nagoya University Graduate School of Information Science Dept. Computer Science and Mathematical Informatics Nagoya Japan

ISBN: (数字)9781665486873

ISBN: (纸本)9781665486873

Given a set of bus stops and a set of employees, the commuting bus routing problem with latest arrival time constraint (CBRP-LATC) aims to determine routes of buses to carry every employee from the company to one of the bus stops at which he/she wants to get off. Each employee walks to his/her destination after getting off the bus and has a desired time when he/she wants to arrive there, which is called the latest arrival time. The objective is to find a set of routes with the minimum total traveling cost that covers all employees' destinations under bus capacity and latest arrival time constraints. We propose an iterated local search algorithm in which we use two kinds of neighborhood operations called set-del/1-ins and VRP-OPT∗. The set-del/1ins operation consists of three neighborhood operations, setdel, 1-ins and set-del-ins to remove or assign employees from or to a bus route. The VRP-OPT∗ is a local search algorithm to improve the distances of routes based on four neighborhood operations, 2-opt, 2-opt∗, relocate and cross-exchange. Computational results show the effectiveness of the two neighborhood operations. © 2022 IEEE.

关键词： Personnel

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Topic Modeling Using Latent Dirichlet Allocation Method Based On Child Anecdotal Record Data

Topic Modeling Using Latent Dirichlet Allocation Method Base...

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science and Information Technology in Smart Administration (ICSINTESA), International Conference of

作者： Rasio Fernandis Daniel Swanjaya Risky Aswi Ramadhani Patmi Kasih Julian Sahertian Dept. Informatics Engineering Faculty of Engineering and Computer Science Universitas Nusantara PGRI Kediri Kediri

ISBN: (数字)9798350376111

ISBN: (纸本)9798350376128

Kindergarten education has a very important role in shaping the foundation of child development. For parents, see reports on the achievement of children’s development at school through the results of each semester’s assessment. The process of preparing teacher assessments uses 4 types of assessments, one of which is anecdotal record assessment. However, teachers experience problems in analyzing the topics in children’s anecdotal notes so that the results become less clear. In addition, it is still done manually so it takes a long time to analyze. Assessment of children’s anecdotal notes is an assessment in the form of a record of events that occur to children while at school. Anecdotal notes are in the form of text data, therefore this research aims to find out the topics in children’s anecdotal notes data by utilizing topic modeling using the Latent Dirichlet Allocation (LDA) method. The children’s anecdotal notes data is used as one dataset with a total of 276 collected directly from YBPK Sidorejo Kindergarten, after which data preprocessing is carried out in the form of case folding, remove punctuation, tokenizing, stopwords, and stemming. In the LDA topic modeling research using the Gensim library, 5 experiments were carried out by determining the number of different iterations, and displaying a range of 2-10 topics for each experiment. Analysis and evaluation using coherence score to determine the optimal number of topics by looking at the highest coherence score value in the experiment conducted. The analysis results in 3 topics with a coherence score of 0.4704 and 40 iterations or passes.

关键词： Analytical models Data preprocessing Education Coherence Libraries Data models Resource management Information technology

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Optical Evanescent Field for Direct Observation of Sub-100nm Particle Motion on Glass Surface 1

Optical Evanescent Field for Direct Observation of Sub-100nm...

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1st International Conference on Robotics, Engineering, science, and Technology, RESTCON 2024

作者： Khajornrungruang, Panart Permpatdechakul, Thitipat Suzuki, Keisuke Blattler, Aran Terayama, Yutaka Goto, Daiki Phaisalpanumas, Pipat Bun-Athuek, Natthaphon Phunopas, Amornphun Kyushu Institute of Technology Iizuka-Shi Mechanical Science and Technology Division Dept. of Intelligent and Control System Faculty of Computer Science and Systems Engineering Fukuoka Japan Kyushu Institute of Technology Iizuka-Shi Mechanical Information Science and Technology Division Dept. of Interdisciplinary Informatics Graduate School of Computer Science and Systems Engineering Fukuoka Japan King Mongkut's University of Technology North Bangkok Bangsue Faculty of Engineering Dept. of Production and Robotics Engineering Bangkok Thailand Kyushu Institute of Technology Iizuka-Shi Mechanical Science and Technology Course Dept. of Intelligent and Control System Graduate School of Computer Science and Systems Engineering Fukuoka Japan King Mongkut's University of Technology North Bangkok Bangsue Faculty of Engineering Dept. of Industiral Engineering Bangkok Thailand King Mongkut's University of Technology North Bangkok Bangsue College of Industrial Technology Dept. of Mechanical Engineering Technology Bangkok Thailand

ISBN: (纸本)9798350348842

To directly investigate the dynamic nanoscale phenomenon on the surface being processed in wet conditions such as precision polishing, and cleaning in semiconductor industrial, an optical method for visualization and observation of each sub-100 nm sized particle that is moving on an interface such as a silica glass surface by applying an evanescent field have been proposing. Subsequently, we developed an experimental apparatus equipped with an optical microscopy system for verifying the moving particle observation method in a laboratory scale. This article introduces some experimentally direct observation results of duplicated wet processes. © 2024 IEEE.

关键词： Visualization

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Blockchain-Based Medical Image Processing Mechanism 4

Blockchain-Based Medical Image Processing Mechanism

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4th International Conference on Cybernetics, Cognition and Machine Learning Applications, ICCCMLA 2022

作者： Berwer, Rajiv Kumar Indora, Sanjeev Atal, Dinesh Kumar Deenbandhu Chhotu Ram University of Science and Technology Dept. of Computer Science and Engineering Murthal Sonipat India Deenbandhu Chhotu Ram University of Science and Technology Dept. of Biomedical Engineering Murthal Sonipat India

ISBN: (数字)9781665462464

ISBN: (纸本)9781665462464

Blockchain is an emerging technology that provides privacy and security to the user data, ultimately leading to user trust. This paper consists of basic key features of blockchain technology, various kinds of blockchain technology, basic blockchain technology, and the use of a cryptographic function. The blockchain uses a cryptographic hash function that converts an arbitrary size into a fixed-length example: MD5, SHA-256, etc., and proof-of-work to validate the block creation. The blockchain is a decentralized architecture with various applications, such as sharing medical data in healthcare, voting mechanism, personal identity security, supply chain, and cross-border transactions. Blockchain is not limited to only digital currency examples: Bitcoin (BTC), but also has massive applications in the medical field and health sector. The paper's primary purpose is to explore the current work of blockchain in a medical image. Blockchain deals with the privacy and security issues in transmitting, storing or retrieving medical photos. © 2022 IEEE.

关键词： Blockchain

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A Land Evaluation Support System using Aerial Images and Land Data for Land Use Classification 12

A Land Evaluation Support System using Aerial Images and Lan...

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12th IEEE Global Conference on Consumer Electronics, GCCE 2023

作者： Tu, Yunhao Urata, Mayu Endo, Mamoru Yasuda, Takami Shimazaki, Hirokazu Kimura, Tomoyuki Chubu University Dept. of Computer Science Kasugai Japan Nagoya University Graduate School of Informatics Nagoya Japan Japan Appraisal System Inc System Development Department Nagoya Japan

ISBN: (纸本)9798350340181

Fixed asset tax, which is determined based on land use, is an important and valuable revenue source for local governments in Japan. Local government staff spend a lot of time and effort in conducting field surveys to confirm land use. Therefore, we have been developing a support system for automatic land use determination in local governments using aerial images and land data. This paper improves on our previous study in three ways. Firstly, we use a transformer-based deep learning model to improve the performance of the proposed system. Secondly, we added more classification tasks and introduced the classification of solar panels to apply to the work in local governments. Thirdly. we verified the effect of time lag in data collection by comparing the differences in the data used. This study aims to improve the efficiency and accuracy of land evaluation work, as well as to reduce the burden on staff by developing the land evaluation support system. The results confirm that the system is effective in supporting land evaluation work in local governments. © 2023 IEEE.

关键词： Economics

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EffiSegNet: Gastrointestinal Polyp Segmentation through a Pre-Trained EfficientNet-based Network with a Simplified Decoder 46

EffiSegNet: Gastrointestinal Polyp Segmentation through a Pr...

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46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2024

作者： Vezakis, Ioannis A. Georgas, Konstantinos Fotiadis, Dimitrios Matsopoulos, George K. Tecreando B.V. Amsterdam Netherlands National Technical University of Athens Biomedical Engineering Laboratory School of Electrical and Computer Engineering Athens Greece University of Ioannina Dept. of Materials Science and Engineering Ioannina Greece

ISBN: (纸本)9798350371499

This work introduces EffiSegNet, a novel segmentation framework leveraging transfer learning with a pre-trained Convolutional Neural Network (CNN) classifier as its backbone. Deviating from traditional architectures with a symmetric U-shape, EffiSegNet simplifies the decoder and utilizes full-scale feature fusion to minimize computational cost and the number of parameters. We evaluated our model on the gastrointestinal polyp segmentation task using the publicly available Kvasir-SEG dataset, achieving state-of-the-art results. Specifically, the EffiSegNet-B4 network variant achieved an F 1 score of 0.9552, mean Dice (mDice) 0.9483, mean Intersection over Union (mIoU) 0.9056, Precision 0.9679, and Recall 0.9429 with a pre-trained backbone - to the best of our knowledge, the highest reported scores in the literature for this dataset. Additional training from scratch also demonstrated exceptional performance compared to previous work, achieving an F 1 score of 0.9286, mDice 0.9207, mIoU 0.8668, Precision 0.9311 and Recall 0.9262. These results underscore the importance of a well-designed encoder in image segmentation networks and the effectiveness of transfer learning approaches. © 2024 IEEE.

关键词： Semantic Segmentation

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Comparison of 2D SURE and 3D CT imaging of cortical vessels in a rat kidney

Comparison of 2D SURE and 3D CT imaging of cortical vessels ...

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2023 IEEE International Ultrasonics Symposium, IUS 2023

作者： Hansen, Lauge Naur Kjer, Hans Martin Amin-Naji, Mostafa Panduro, Nathalie Sarup Sørensen, Charlotte Mehlin Gundlach, Carsten Dahl, Anders Bjorholm Jensen, Jørgen Arendt Technical University of Denmark Dept. of Health Technology Kgs. Lyngby Denmark Technical University of Denmark Dept. of Applied Mathematics and Computer Science Kgs. Lyngby Denmark University of Copenhagen Dept. of Biomedical Sciences Copenhagen Denmark Technical University of Denmark Dept. of Physics Kgs. Lyngby Denmark

ISBN: (纸本)9798350346459

SUper-Resolution ultrasound imaging using the Erythrocytes (SURE) can visualize blood vessels at about 25 to 50 μm resolution, but validation is required to assess how accurately the vasculature and its morphology are represented. Previous work compared ultrasound imaging to maximum intensity projections (MIP) of micro-CT volumes at an insufficient voxel size of 22.6 μm. Here, a 5 μm voxel size micro-CT volume of a cortical region in an excised rat kidney was acquired to test the hypothesis that blood vessels down to 50 μm in diameter are detected with SURE imaging. For the micro-CT volume, the blood vessels were segmented by an intensity threshold, and local thickness estimates were computed using expanding spheres within the segmentation mask. An affine registration between the SURE image and the micro-CT volume was manually defined, and a MIP of the micro-CT volume across 2 mm from the ultrasound imaging plane was computed for vessels with diameter estimates greater than 50 μm. The SURE image depicts 12 cortical radial vessels with high intensities and 9 dimmer cortical radial vessels. Notably, the 12 high intensity vessels are also depicted in the micro-CT projection, but 5 cortical radial vessels and 2 arcuate blood vessels are only visible in the SURE image. Of the faintly depicted cortical radial vessels, 5 vessels are not readily matched to vessels in the micro-CT projection. On the other hand, the micro-CT projection contains 6 cortical radial vessel segments and 2 arcuate blood vessels not depicted in the SURE image. These discrepancies in the comparison may arise from the challenging registration of the ultrasound focus beam and the micro-CT volume that is complicated further by the different states of the imaged tissue. Despite these challenges, SURE depicts most vessels at least down to 50 μm and even resolves parallel vessels not visible in the micro-CT projection, thus highlighting its clinical potential. © 2023 IEEE.

关键词： Blood vessels

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