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2024 Cognitive Models and Artificial Intelligence Conference, AICCONF 2024

作者： Acikalin, Utku Umur Caskurlu, Bugra Abul, Osman Department of Computer Engineering TOBB University of Economics and Technology Ankara Turkey Department of Computer Science College of Computing and Informatics University of Sharjah Sharjah United Arab Emirates

ISBN: (纸本)9798400716928

Wireless Sensor Networks (WSNs) play a crucial role in various domains, from commercial to military, enabling precise monitoring of environmental and other conditions. However, the transmission of sensitive data in WSNs poses security challenges, particularly concerning eavesdropping attacks. While cryptographic methods offer protection, they often incur high energy costs, making them impractical for battery-powered WSNs. Our problem formulation, based on graph theory, reduces to the Secluded Paths problem for which no polynomial solution yet to known. Motivated by the challenge of reducing the eavesdropping risk through intelligent routing, we propose a scalable optimization approach using heuristics and local search techniques. We present a solution framework, followed by an experimental evaluation to demonstrate its efficacy. This paper contributes to the advancement of secure and efficient data transmission in WSNs. © 2024 ACM.

关键词： Sensitive data

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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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Enhanced Lightweight Facial Emotion Recognition Systems for Visually Impaired People 12

Enhanced Lightweight Facial Emotion Recognition Systems for ...

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12th IEEE Conference on Systems, Process and Control, ICSPC 2024

作者： Shehada, Dina Turky, Ayad Rabie, Tamer Hussain, Abir University of Dubai College of Engineering and IT Dubai United Arab Emirates University of Sharjah College of Engineering Department of Electrical Engineering Sharjah United Arab Emirates University of Sharjah College of Computing & Informatics Department of Computer Science Sharjah United Arab Emirates University of Sharjah College of Computing & Informatics Department of Computer Engineering Sharjah United Arab Emirates

ISBN: (纸本)9798350391398

Facial expressions are a vital component of human communication, conveying emotional information that enhances the social experience. However, for individuals with visual impairments, perceiving and interpreting facial expressions can be challenging, hindering their ability to engage fully in social interactions. This paper presents an enhanced facial emotion recognition system specifically designed to aid visually impaired individuals. Two enhanced approaches for facial emotion recognition systems are proposed. The first approach consolidates negative emotions (anger, fear, sadness, disgust) into a single class, while the second approach incorporates diverse training datasets from real-world environments. The negative emotion consolidation approach achieved 90.9% and 94.7% accuracy on the FER2013 and CK+ datasets, respectively. While, the diverse dataset integration approach achieved 84.9% and 70.6% accuracy on FER2013 and CK+ datasets, respectively. This is a significant improvement when benchmarked with other approaches available in the literature. The feasibility of the enhanced proposed systems as assistive technology for the visually impaired indicated its ability to be applied in real-world applications. © 2024 IEEE.

关键词： Assistive technology

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Neural End-to-End Coreference Resolution using Morphological Information 6

Neural End-to-End Coreference Resolution using Morphological...

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CRAC Shared Task on Multilingual Coreference Resolution at 6th Workshop on Computational Models of Reference, Anaphora and Coreference, CRAC 2023

作者： Arslan, Tugba Pamay Acar, Kutay Eryigit, Gulsen ITÜ NLP Research Group Department of AI&Data Engineering Faculty of Computer&Informatics Istanbul Technical University Turkey ITÜ NLP Research Group Department of Computer Engineering Faculty of Computer&Informatics Istanbul Technical University Turkey

ISBN: (纸本)9781955917025

In morphologically rich languages, words consist of morphemes containing deeper information in morphology, and thus such languages may necessitate the use of morpheme-level representations as well as word representations. This study introduces a neural multilingual end-to-end coreference resolution system by incorporating morphological information in transformer-based word embeddings on the baseline model. This proposed model participated in the Sixth Workshop on Computational Models of Reference, Anaphora and Coreference (CRAC 2023). Including morphological information explicitly into the coreference resolution improves the performance, especially in morphologically rich languages (e.g., Catalan, Hungarian, and Turkish). The introduced model outperforms the baseline system by 2.57 percentage points on average by obtaining 59.53% CoNLL F-score. © CRAC 2023. All Rights Reserved.

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The Threshold of Existence of δ-Temporal Cliques in Random Simple Temporal Graphs 20th

The Threshold of Existence of δ-Temporal Cliques in Rand...

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20th International Symposium on Algorithmics of Wireless Networks, ALGOWIN 2024

作者： Mertzios, George B. Nikoletseas, Sotiris Raptopoulos, Christoforos Spirakis, Paul G. Department of Computer Science Durham University Durham United Kingdom Computer Engineering and Informatics Department University of Patras Patras Greece Department of Mathematics University of Patras Patras Greece Department of Computer Science University of Liverpool Liverpool United Kingdom

ISBN: (纸本)9783031745799

We consider random simple temporal graphs in which every edge of the complete graph Kn appears once within the time interval [0, 1] independently and uniformly at random. Our main result is a sharp threshold on the size of any maximum δ-clique (namely a clique with edges appearing at most δ apart within [0, 1]) in random instances of this model, for any constant δ. In particular, using the probabilistic method, we prove that the size of a maximum δ-clique is approximately 2lognlog1δ with high probability (whp). We note that, even though the random simple temporal graph contains Θ(n2) overlapping δ-windows, which (when viewed separately) correspond to different random instances of the Erdős-Rényi random graphs model, the size of the maximum δ-clique in the former model and the maximum clique size of the latter are approximately the same. Furthermore, we show that the minimum interval containing a δ-clique is δ-o(δ) whp. We use this result to show that any polynomial time algorithm for δ-Temporal Clique is unlikely to have very large probability of success. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： probabilistic method Simple random temporal graph δ-temporal clique

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A Low-Cost Real-Time Cyber Physical System for Overcoming Excess Braking Issues In Race Cars 12

A Low-Cost Real-Time Cyber Physical System for Overcoming Ex...

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

作者： Samaras, V. Tatas, K. Lontos, A. Frederick University Department of Electrical Engineering Computer Engineering and Informatics Nicosia Cyprus Frederick University Department of Mechanical Engineering Nicosia Cyprus

ISBN: (纸本)9798350321074

This paper presents the development of proof of concept for a low-cost, real-time Cyber Physical System (CPS)/IoT that deals with observed excess braking issues in Formula Student (FS) race cars. The goal is to utilize telemetry aspects through a smart monitoring system under the FS low budget competition restrictions, with low-cost materials, open-source software, Long Range wireless communication (LoRa) and cloud services. The paper also introduces an algorithm for implementing an adaptive sampling rate based on the proximity of monitored parameters to warning levels to minimize unnecessary data transmission. The system prototype was tested under realistic driving conditions, obtaining useful preliminary data that can be used to guide both driving behavior and future vehicle design. The results demonstrate that the proposed approach can be useful for the race team in FS conditions and may be possible to expand it to other similar driving scenarios outside FS. © 2023 IEEE.

关键词： Cyber Physical System

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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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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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Realizing Predictive Maintenance in Production Machinery Through Low-Cost IIoT Framework and Anomaly Detection: A Case Study in a Real-World Manufacturing Environment 19

Realizing Predictive Maintenance in Production Machinery Thr...

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19th Annual International Conference on Distributed Computing in Smart Systems and the Internet of Things, DCOSS-IoT 2023

作者： Filios, Gabriel Karatzas, Stylianos Krousarlis, Marios Nikoletseas, Sotiris Panagiotou, Stefanos H. Spirakis, Paul University of Patras Computer Engineering and Informatics Department Greece Greece University of Patras Civil Engineering Department Greece University of Liverpool Department of Computer Science United Kingdom

ISBN: (纸本)9798350346497

Digital transformation and predictive maintenance are still some of the key challenges faced by the industrial sector as it moves towards Industry 4.0. However, the lack of resources, experienced personnel, and the absence of digital-savvy culture in manufacturing companies, often hinder the adoption of the required technologies. In this context, maintenance is a required process to ensure the smooth and continuous operation of the production, but to this day, engineers are still required to physically inspect equipment on site. By applying digital technologies, a predictive maintenance framework will enable the industry to maximize the life of the equipment and to act on time in order to prevent failures and thus reduce costs and optimize maintenance efficiency. In this effort, integrating such technologies and the required modern computing devices for monitoring legacy industrial equipment remains a challenge. Therefore, in this paper, we present a low-cost IIoT system for an AI-based predictive maintenance of machinery in a real-world industrial environment. In specific, a data collection system, consisting of a Raspberry Pi device and several sensors (namely, an accelerometer, temperature sensors and a microphone), was designed and developed. The collected data was then utilized to feed a deep-learning LSTM-autoencoder model for anomaly detection through a semi-supervised learning approach. Despite the small amount of data collected, the model is able to effectively detect anomalies. Finally, ways in which the existing system can be improved are proposed. © 2023 IEEE.

关键词： Internet of things

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Real-Time-Based Blood Wastage Management Using IoT and Blockchain Technology

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SN computer Science 2024年第3期5卷 310页

作者： Kumar, Ajay Chatterjee, Indranath Pallavi Sharma, Komal Thakur, Muskan Department of Computer Science and Informatics Central University of Himachal Pradesh Dharamshala India Department of Computer Engineering Tongmyong University Busan South Korea Department of Computing and Mathematics Manchester Metropolitan University Manchester United Kingdom

The rapid shift in population density increased the need for blood in medical treatments, emphasizing the importance of appropriate blood supply chain management. Most countries have institutions that run centralized blood management information networks. However, these centralized solutions are limited as they do not provide complete blood information. In the healthcare industry, supply chains are crucial, ranging from the prompt delivery of vital medications to patients to the traceability of these medications. To address the limitations of current systems, we recommend the use of Blockchain technology to offer real-time information on donors and patients. The primary advantage of Blockchain is that information is secure and less susceptible to tampering. The blood supply chain uses private Blockchain solutions, ideal for commercial transactions due to the limited number of participants, who are both rapid and trustworthy. This article also explores how the Internet of Things (IoT) can be used to store blood information in QR codes. These codes, attached to blood packets, provide easy access to critical data such as blood group, cell count, etc. The proposed method aims to reduce blood waste, facilitate real-time identification of suitable donors, and improve the distribution of blood units to all needed locations. Ultimately, implementing this approach will be beneficial for both donors and patients. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd 2024.

关键词： Blockchain Internet of Things Smart contracts Supply chain

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