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4th International Conference on Control, Artificial Intelligence, Robotics and Optimization, ICCAIRO 2023

作者： Kounalakis, Nikolaos Kalykakis, Emmanouil Kosmopoulos, Dimitrios Fasoulas, John Sfakiotakis, Michael Heraklion Greece University of Patras Dept. of Computer Engineering and Informatics Patras Greece

ISBN: (纸本)9798350300918

We present an integrated framework for intelligent automated plant monitoring, towards early disease and pest detection in greenhouse tomato crops. The framework combines the use of a robotic mobile platform to autonomously collect multi-spectral images of the plants, with a tool that utilizes Faster R-CNN to detect regions that signify the presence of a disease or pest. The robot is based on a modified mobile vertical mast lift platform, and integrates a 6-dof robotic arm that is used to position the plant imaging multi-spectral camera. The robot can navigate autonomously inside the greenhouse via a magnetic guidance sensor. Results from a series of experiments demonstrate the validity and effectiveness of the implemented framework. © 2023 IEEE.

关键词： Machine learning

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An approach for measuring spatial similarity among COVID-19 epicenters

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Geo-Spatial Information Science 2023年第3期26卷 496-513页

作者： Neda Kaffash Charandabi Abolghasem Sadeghi-Niaraki Soo-Mi Choi Tamer Abuhmed Geomatic Department Marand Technical FacultyUniversity of TabrizTabrizIran Department of Computer Science and Engineering and Convergence Engineering for Intelligent Drone Sejong UniversitySeoulSouth Korea College of Computing and Informatics Sungkyunkwan UniversitySuwonSouth Korea

Most countries and territories worldwide are affected by coronavirus disease 2019(COVID-19),and some cities have become known as epicenters owing to high *** of the changeable and unknown nature of the virus,managers of different cities could learn from the experiences of cities that have been successful in controlling COVID-19 instead of wasting time exploring different *** would be even more beneficial if they analyzed the experiences of similar *** similarity of such cities could be examined within a geographic information system based on various *** study investigated the similarities among eight cities-Wuhan,Tehran,Bergamo,Madrid,Paris,Daegu,New York,and Berlin-in terms of the COVID-19 situation(target)in these locations based on proximity factors,weather,and demographic ***,the factor and target layers were prepared,and then similar cities were identified using a similarity model and different distance *** results were aggregated using the Copeland method because of the different outcomes for each *** most similar city was identified for each selected city,and its similarity level was determined based on these *** results suggested the following pairs of similar cities:Wuhan-Berlin,Tehran-Berlin,Daegu-Wuhan,Bergamo-Madrid,Paris-Madrid,and New York-Paris based on COVID-19 related data up to 15 April 2020(target T1),and Daegu-Wuhan,Tehran-Madrid,Bergamo-Paris,Berlin-Paris,and New York-Madrid up to 8 December 2021(target T2)with a minimum and maximum similarity rate of 82.85%and 92.36%,*** similar cities,the most similar factors among the proximity criteria are the distance from bus and metro stations;among weather,the criteria are humidity and pressure;and among demographics,the criteria are male and female population ratios,literacy ratio,and death ratio from asthma and cancer,with a minimum and maximum difference of 0%and 64.94%,*** addition,according to the rando

关键词： COVID-19 GIS spatial similarity environmental factors demographic factors

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Knowledge augmented significant language model-based chatbot for explainable diabetes mellitus prediction 19

Knowledge augmented significant language model-based chatbot...

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19th International Conference on Ubiquitous Information Management and Communication, IMCOM 2025

作者： Elfayoumi, Mazen AbouElazm, Mohamed Mohamed, Omar Abuhmed, Tamer El-Sappagh, Shaker Faculty of Computer Science and Engineering Galala University Egypt Faculty of Computer Science Goldsmith UOL United Kingdom College of Computing and Informatics Sungkyunkwan University Korea Republic of

ISBN: (纸本)9798331507817

This study proposes an innovative diabetes prediction chatbot that utilizes large language models (LLMs) to determine the likelihood of diabetes based on specific patient inputs. Unlike conventional machine learning models and in addition to providing precise, individualized, robust prediction of diabetes augmented by the percentage of its confidence, this chatbot provides detailed text-based explanations for its individual predictions and enhances user’s understanding by retrieving and presenting similar cases using case-based reasoning techniques. Utilizing key health indicators such as hypertension status, heart disease presence, smoking history, BMI, HbA1c level, and blood glucose levels, the chatbot not only predicts the presence of diabetes but also educates users about the underlying reasons for each prediction. The system's explanation module promotes transparency and trust in the predictive process. The proposed architecture integrates the retrieval augmented generation (RAG) technique with prompt engineering across multiple LLMs, including Llama 3.1, GPT-3.5, and Gemma2. This approach augments the chatbot’s responses with contextually relevant data from similar past cases, thereby enhancing both relevance and accuracy. Furthermore, RAG minimizes LLM hallucinations while enhancing them with up-to-date, precise, personalized medical information. The objective of this chatbot is to offer healthcare professionals and patients a dependable, educational instrument for early detection of diabetes supported by transparent AI principles. This will have a positive effect on preventative healthcare measures. © 2025 IEEE.

关键词： Prediction models

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Smart Road Damage Survey System Using Machine Vision and IoT Technology 3

Smart Road Damage Survey System Using Machine Vision and IoT...

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3rd International Conference on Intelligent Cybernetics Technology and Applications, ICICyTA 2023

作者： Mutijarsa, Kusprasapta Alunjati, Figo Agil Hidayat, Fadhil Kurnia, Ranna Arsyad, Zulkifli School of Electrical Engineering and Informatics Bandung Indonesia National Institute of Technology Department of Civil Engineering Bandung Indonesia Bandung State Polytechnic Department of Computer and Informatics Engineering Bandung Indonesia

ISBN: (纸本)9798350394559

Road is an essential transportation infrastructure to move people and goods to support economic prosperity. The efficiency, safety, security, and comfort of people have significant consequences by damage and defects on the road surface. A good-condition road ensures the land traffic runs well. This research is a collaboration between the Bandung Institute of Technology and the Department of Public Works and Spatial Planning of West Java Province to develop a smart system for road damage surveys. The system was built by leveraging machine vision and IoT technologies to improve the performance of the road survey activities. The previous road damage detection, classification method, and pavement condition index (IKP) computation were performed semi-automatically. The proposed survey system developed in this work uses the Canny edge Detection algorithm and MobileNet V2 architecture to detect road defects automatically. The pavement condition index computation also improved by using the interpolation reduction factor. The system is designed into a four-layer architecture that consists of several functions and modules, i.e., the sensor system that includes a vision sensor, GPS and odometry, a hardware embedded system using a microcontroller, and machine learning to process the road condition image automatically, and a dashboard application to reveal the road condition on map. The performance resulted in accuracy, precision, recall, and F-score of the road damage detection are 54.5%, 24.2%, 78.9%, and 37%, respectively. © 2023 IEEE.

关键词： computer vision

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The Using of Mixed Reality Technology for Digital Transformation in Tourism 10

The Using of Mixed Reality Technology for Digital Transforma...

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10th International Conference on ICT for Smart Society, ICISS 2023

作者： Tresnawati, Dewi Latifah, Ayu Mahpudin, Indra Pratama, Vitradisa Sukoco, Agus Prihatmanto, Ary Setijadi Informatics Institut Teknologi Garut Department of Computer Science Garut Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Department of Computer Science Informatics Universitas Bandar Lampung Garut Indonesia

ISBN: (纸本)9798350339543

The tourism industry in Indonesia experienced a decrease in the number of tourist visits that occurred at the end of 2020. This was due to the outbreak of the COVID-19 outbreak that occurred at the end of January 2020. Apart from having an impact on decreasing the number of foreign tourist visits, it also had an impact on domestic tourists or local tourists. especially Bandung residents who are reluctant to travel because they are worried about the spread. Bandung has several popular tourist destinations such as history, culinary, fashion, handicrafts, arts, and interesting amusement parks to visit. One of them is Gedung Sate. For this reason, media promotion is needed to attract tourists to Bandung. The purpose of this research is to implement mixed reality technology that can be used to support tourism. This study uses the multimedia development life cycle which consists of six stages, namely concept, design, material collection, assembly, testing, and distribution. The results of this study are mixed reality application prototypes as promotional media for tourist attractions in Bandung that can be used by domestic and foreign tourists. Additionally, by using mixed reality technology as a promotional tool for Bandung's tourism sites, users may interact with 3D objects in real-time, making the information offered more engaging and dynamic. © 2023 IEEE.

关键词： Life cycle

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Performance Analysis of the Edge-Preservation based Normalized Convolution for Medical Image Enhancement and Noise Reduction 3

Performance Analysis of the Edge-Preservation based Normaliz...

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3rd IEEE International Biomedical Instrumentation and Technology Conference, IBITeC 2023

作者： Marjuni, Aris Nurhayati, Oky Dwi Universitas Dian Nuswantoro Faculty of Computer Science Department of Informatics Engineering Semarang Indonesia

ISBN: (纸本)9798350302424

Acquired medical images often contain noise due to various factors that affect image quality. The noisy image indicates the presence of inappropriate information or loss of original information due to changes in the pixel values. For diagnosis purposes, the acquired or noisy medical image needs to be reconstructed to obtain an enhanced image or denoised image for a better decision. One of the techniques to enhance or reduce the noise can be performed by normalized convolution to interpolate the change of pixels in the original image. This paper is presented to investigate the feasibility of the normalized convolution filter to enhance and reduce medical image noise. The study was performed through experiments using several types of medical images, namely Brain MRI, Breast Ultrasound, Chest X-ray, Retinal OCT, Mammogram, and RSNA Bone Age images. Experimental results show that the normalized convolution could produce an enhanced image with sharper contrast. In the image enhancement, the enhanced image obtained by this filter achieves 41.12 dB on the PSNR average. In the medical image denoising, the normalized convolution could produce better visual quality to reduce the Gaussian, Salt & Pepper, Poisson, and Speckle with PSNR averages are 28.43dB, 32.82dB, 32.49dB, and 29.30dB. This method also outperforms basic image denoising filters, such as Imbox, Wiener, and Median Filterings. Hence, this filter could be used as an alternative for medical image preprocessing, such as image enhancement and noise reduction. © 2023 IEEE.

关键词： Image enhancement

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Detection and Classification of Cardiac Arrhythmia from Photoplethysmography Signal

Detection and Classification of Cardiac Arrhythmia from Phot...

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2023 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2023

作者： Dewantara, Bima Sena Bayu Sari, Dewi Mutiara Fahmi, Ahmad Nur Politeknik Elektronika Negeri Surabaya Dept. of Informatics and Computer Engineering Surabaya Indonesia

ISBN: (纸本)9798350319040

This paper presents the development of an application for classifying cardiac arrhythmia by utilizing photoplethys-mography sensor signals. The Photoplethysmography (PPG) sensor is used as a reader for the cardiovascular system by measuring changes in blood volume in the skin tissue. The PPG sensor captures electrical signals originating from the reflected light source due to changes in blood flow during heart activity. After going through the preprocessing stage, the signals are then extracted into several features that will be classified using the Random Forest algorithm. The results from the Random Forest algorithm will provide a diagnosis based on the detection of arrhythmia. Based on the experimental results, the accuracy achieved using the method and dataset is 72%. The accuracy of the system testing using the smartwatch under normal heart conditions is 88.88%. © 2023 IEEE.

关键词： Photoplethysmography

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A Game Theoretic Approach to Enhance DCF Performance in Full Duplex Ad-hoc WLANs 12

A Game Theoretic Approach to Enhance DCF Performance in Full...

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12th International Conference on Modern Circuits and Systems Technologies, MOCAST 2023

作者： Politis, Anastasios C. Anastassiu, Hristos T. Hilas, Constantinos S. International Hellenic University Informatics and Telecommunications Engineering Dept. of Computer Serres Greece

ISBN: (纸本)9798350321074

Physical Full Duplex (FD) operation in WLANs is a promising technology aiming at substituting the traditional Half Duplex (HD) functionality. An increased performance is expected which, theoretically, can be expressed as a double increase in system throughput. However, due to the initial design of the basic access method in WLANs, known as Distributed Coordination Function (DCF), this performance boost is poorly exhibited. Game theory is an invaluable tool to model the performance of Medium Access Control (MAC) protocols used in WLANs. In this paper, we exploit game theory to propose a simple enhancement to the DCF access method, in order to increase the benefit received when the FD capability is enabled in ad-hoc WLANs. © 2023 IEEE.

关键词： Game theory

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To Split or not to Split? A Simulation Study on the Network Convergence Duration of Multi-Area OSPF 46

To Split or not to Split? A Simulation Study on the Network ...

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46th International Conference on Telecommunications and Signal Processing, TSP 2023

作者： Sachinidis, Theofilos Politis, Anastasios C. Hilas, Constantinos S. International Hellenic University Dept. of Computer Informatics and Telecommunications Engineering Serres Greece

ISBN: (纸本)9798350303964

Internetworks with a large number of routing devices that utilise the Open Shortest Path First (OSPF) routing protocol, benefit greatly if they are designed in a hierarchical manner. The multi-area feature of OSPF leads to reduced network overhead, low processing and memory requirements and smaller routing tables. This, however, comes at the cost of increased configuration complexity, especially at the Area Border Routers. The threshold after which splitting the OSPF domain into multiple areas, is an ongoing debate among network administrators. A well known rule-of-thumb is recommended by large vendors of networking devices setting that threshold to 50 routing devices. The objective of this preliminary work is to investigate that threshold by conducting a simulation-based study using the OPNET network simulation tool. To assess the network performance, we select the network convergence duration as the quantitative Key Performance Indicator (KPI) of our study. Results indicate that the above mentioned threshold does not appear to be appropriate and a revision of that empirical rule should be considered. © 2023 IEEE.

关键词： Routing protocols

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XLM-RoBERTa Model for Key Information Extraction on Military Document 10

XLM-RoBERTa Model for Key Information Extraction on Military...

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10th International Conference on ICT for Smart Society, ICISS 2023

作者： Rachmadi, Muhammad Faza Ilmanuddiin Shalahuddin, Salman Permana, Heru Setijohatmo, Urip Teguh Hutahaean, Jonner Politeknik Negeri Bandung Department of Computer and Informatics Engineering Bandung Indonesia Bandung Indonesia

ISBN: (纸本)9798350339543

Key Information Extraction (KIE) is the process of extracting important data in a text or an image, such as the content of a military document. One popular method for performing KIE is by utilizing pattern matching with Regular Expression on texts from documents. However, this method is not efficient due to the fixed nature of RegEx, where we need an exclusive RegEx rule to extract certain data entities. To solve this flexibility issue, a deep learning method with Named Entity Recognition (NER) has been proposed. NER is applied to the scanned document using a transformer-based model called XLM-RoBERTa. This model has been chosen for the development of the KIE module as it supports Indonesian and has demonstrated good accuracy in previous studies. The model has been trained on a military document dataset in the Indonesian language, achieving an f1-score of 86.55%. This method has also been proven to be flexible, as the model can extract the same entities across different document types. © 2023 IEEE.

关键词： Pattern matching

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