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Smart City Surveillance: Survey on Current Status and Future Trends 14

Smart City Surveillance: Survey on Current Status and Future...

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14th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2023

作者： Neyaz, Hera Paul, Hrituparna Srivastava, Anima Singh, Shiksha Dept. of Computer Science and Engineering Shambhunath Institute of Engineering and Technology India

This paper presents a comprehensive survey on surveillance and security aspects of a smart city. Multiple dimensions of a smart city surveillance system have been discussed. The current trends and methodologies are thoroughly researched and presented. The algorithms of novel methods are reviewed along with analytics and methodologies. Impact of XAI in the smart city surveillance is discussed. Advantages and disadvantages of current infrastructures have been included in the broad literature survey. Lastly, the challenges and future trends are conferred to. © Grenze Scientific Society, 2023.

关键词： Smart city

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Breakpoint Estimation Using Age-Based SIR Model on COVID -19 Epidemic in Bangladesh 5

Breakpoint Estimation Using Age-Based SIR Model on COVID -19...

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5th International Conference on Sustainable Technologies for Industry 5.0, STI 2023

作者： Roy, Tonushree Masud, Md Abdul Hossain, Mohammad Jamal Samsuzzaman, Md. Hossen, Md. Showrov Jannath, Nahary Pstu Dept of Computer Science and Information Technology Dhaka Bangladesh Pstu Dept of Computer and Communication Engineering Dhaka Bangladesh

ISBN: (纸本)9798350394290

COVID-19 has disrupted the harmonic rhythm of civilized societies worldwide, including Bangladesh. The impact of this all-encompassing pandemic situation has spread across the globe and has also affected Bangladesh. COVID-19 prediction and breakpoint estimation have garnered significant attention for facilitating the recovery of a normal and healthy life. The SIR (Susceptible-Infected-Removed/Recovered) model is a widely-used epidemiological model employed for breakpoint estimation and prediction. Breakpoint estimation represents the point at which the curve reaches its highest peak position. In this study, we propose a variant of the SIR model, specifically an age-based SIR model, to estimate the breakpoint of the COVID-19 pandemic in Bangladesh. Our approach considers the age distribution of the population, recognizing its significant impact on disease spread and mortality rates. We focus on the effectiveness of age-specific contamination and treatment efforts to assess their role in combating the pandemic. To examine the impact of age categories, we compare results across selected groups based on different population factors. The findings indicate that middle-aged people are the most vulnerable group. Consequently, we excluded the less vulnerable groups and estimated the breakpoint using data from the most vulnerable age groups. The results from the age-based SIR model demonstrate a minimization of the gap between the predicted model and actual data points. Thus, the selected age groups exhibit better performance compared to considering all populations. This prediction serves to raise awareness among people, helping them understand the severity of this pandemic. © 2023 IEEE.

关键词： COVID-19

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HAC-Bchain: A Secure and Scalable Blockchain-Shard Based E-Voting System

HAC-Bchain: A Secure and Scalable Blockchain-Shard Based E-V...

引用

2023 IEEE Technology and engineering Management Conference - Asia Pacific, TEMSCON-ASPAC 2023

作者： Joni, Sohel Ahmed Rahat, Rabiul Tasnin, Nishat Ghose, Partho Gaur, Loveleen Bangladesh University of Business and Technology Dept of Computer Science and Engineering Bangladesh Taylorâs University School of Computer Science Malaysia

ISBN: (纸本)9798350384659

Voting is a fundamental right of citizens in a democratic country and crucial for any thriving democracy. Reliable voting systems are essential for free and fair elections in the modern era. Biometric Electronic Voting Machines (EVMs) address many issues with paper-ballot systems, but their closed-source nature undermines voter trust. Traditional election systems are also vulnerable to cyberattacks. In this paper, we propose a hybrid blockchain-based electronic voting system (HAC-Bchain) to address the limitations of conventional e-voting systems and ensure a secure, auditable, tamper-proof, transparent, and privacy-preserving voting process. A scripting system for our blockchain facilitates a limited set of predefined operations for each layer, which helps authoritative figures to manage the election securely. We also combine a category-based sharding mechanism with the HAC-Bchain hybrid approach to create more data-concentrated shards, which improves scalability, performance, and data availability. Furthermore, we compare and discuss the performance and efficiency of different sharding configurations. Our experiments shed new light on the overall security, performance, and scalability of blockchain-based evoting systems. © 2023 IEEE.

关键词： Blockchain

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RTBERT: A Transformer Based Approach for Improved Rumor Classification from Tweet 26

RTBERT: A Transformer Based Approach for Improved Rumor Clas...

引用

26th International Conference on computer and Information Technology, ICCIT 2023

作者： Dipto, Shakib Mahmud Kamal Sagor, Mostofa Rozario, Anatte Saad, Sahal Bin Department of Computer Science and Engineering Dhaka Bangladesh Dept. of CSE Dhaka Bangladesh Primeasia University Department of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350359015

In an era where both the general public and established news outlets increasingly rely on social media for real-time information, the abundance of rumors offers a huge difficulty. False information can have far-reaching implications, affecting individuals, communities, and even entire countries. To address this issue, a low-cost, self-regulating, and forward-thinking rumor detection technique is required. This research performs an intensive analysis of the performance of three robust machine learning algorithms, including XGBoost, SVM, and Random Forest, as well as two deep learning-based transformers, namely BERT and DistilBert. In this research, the models are trained and evaluated on a combined dataset comprising data from Twitter15 and Twitter16 datasets. Support Vector Machine (SVM) and Random Forest exhibit the best accuracy among classical machine learning models, reaching 89.05%. In comparison, among the transformer-based deep learning models, BERT achieves the best accuracy of 90.20%. In conclusion, the learning-based transformers beat its competitors in terms of accuracy, recall, precision, and F-measure, proving its efficacy in minimizing the detrimental impact of rumors on people, communities, and society as a whole. © 2023 IEEE.

关键词： BERT DistilBERT Rumors Transformer Tweet Twitter

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Comparative Study on Extractive Summarization Using Sentence Ranking Algorithm and Text Ranking Algorithm

Comparative Study on Extractive Summarization Using Sentence...

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2023 International Conference on Power, Instrumentation, Control and Computing, PICC 2023

作者： Majeed, Mansoora Kala, M.T. Government Engineering College Dept. of Computer Science and Engineering Thrissur India

ISBN: (纸本)9798350334463

It is possible to create an accurate and succinct summary using a method called automatic text summarising. Before creating the necessary summary sentences, the machine learning algorithms may be trained to understand documents and recognise the portions that transmit crucial facts and information. Abstractive text summa- rization and Extractive text summarization are its two methods. An extractive text summarization refers to the process of removing significant text from a text document or source manuscript. Deep learning techniques are used to train an abstractive text summarizer, which then generates new phrases and keywords based on the content of the original text. The process of acquiring and assimilation of the knowledge from numerous sources takes time. Automatic text summary is used to speed up the process of finding and consuming pertinent information. An extractive text summarising technique chooses crucial phrases, sentences, and other parts of the original text and concatenates them into a compressed form. The extractive text summarization produces grammatically correct sentences. The project is to develop a model that demonstrates extractive text summarization using sentence ranking and text rank algorithm. It shows that the text rank algorithm does a remarkable performance to extractive text summarization. Using a sentence ranking algorithm, extractive summaries are created that rate sentences according to their weights. In order to create a high-quality summary of the input document and store the summary as audio, the input document's highly scored sentences are extracted. A non-supervised, extractive text summarising method is called TextRank. While calculating the value of words and phrases in a document, the TextRank algorithm looks at how they relate to one another. According on how important the words are in each phrase, it then assigns a score to each one. The summary is formed using the algorithm's choice of the most crucial phrases. © 2023 IE

关键词： Deep learning

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Detection of Cataracts from Retinal Fundus Image Using Ensemble Machine Learning Approach

Detection of Cataracts from Retinal Fundus Image Using Ensem...

引用

2023 International Conference on Next-Generation Computing, IoT and Machine Learning, NCIM 2023

作者： Hasan, Md. Nahid Hossain, Md. Ali Rajshahi University of Engineering and Technology Dept. of Computer Science and Engineering Bangladesh

ISBN: (纸本)9798350316001

Cataract is a common eye condition that causes clouding of the eye's natural lens, resulting in blurry vision and it is very common in older ages people. However, it can also occur in younger aged people due to various genetical effects, diabetes, smoking, and prolonged exposure to sunlight. Cataracts can be treated through surgery to remove the clouded lens and replaced by an artificial one, which can significantly improve the vision. This problem can be reduced through early detection, regular eye examinations etc. In this research, a Contrast Limited Histogram Equalization (CLAHE) of retinal fundus images is applied for a better presentation of the above cataract effects. These improved images are fed to a machine learning-based model for effective detection. Finally, the ensembling of the proposed machine learning-based classifiers is performed for the accurate detection of cataracts. The proposed model was tested experimentally on a real dataset and achieves excellent performance with accuracy, precision, and recall scores of 99.67%, 100%, and 99.25%, respectively which outperform the baseline methods. The robustness of the proposed ensemble model is evaluated through 5-fold cross-validation and achieved an average accuracy of 99.6%. The implementation code can be accessed from the GitHub repository: https://***/nahid-tech/cataract-detection. © 2023 IEEE.

关键词： Image enhancement

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An IoT-Based Health Care Solution: A Smart Medical Box 4

An IoT-Based Health Care Solution: A Smart Medical Box

引用

4th Asia Service sciences and Software engineering Conference, ASSE 2023

作者： Khan, Adib Mahamud Kabir, Raihan Sudha, Nigar Sultana Ahmed, Nadeem Watanobe, Yutaka Islam, Md Rashedul Dept. of Computer Science and Engineering University of Asia Pacific Dhaka1216 Bangladesh Dept. of Computer Science and Engineering University of Aizu Aizuwakamatsu Fukushima Japan

ISBN: (纸本)9798400708534

IoT in healthcare is intended to keep people safe and healthy, with the primary goal of lowering healthcare costs and reducing the involvement of caregivers in the coming years. This research proposes a smart IoT-based health- care system, which includes an intelligent medical box connected to a mobile app for continuous health monitoring. Patients can get regular health care with the help of this medical box with a dedicated app and web server. The proposed system helps the patients to check their heart rate, temperature, and oxygen level, all using just one device. It provides an easy way for the user to do this checkup by themselves without any help from caregivers or even doctors. Moreover, the proposed system assists the patients in taking the proper medicinal drugs in due time with an SMS and buzzer alarm. It additionally creates a clean verbal exchange between medical doctors and patients rather than bodily contact. The proposed system can be accessed through an app that stores all the detailed health reports about the patient. Doctors can easily check the patient's report and can change the prescriptions based on the condition of the reports, if necessary. This box also consists of an emergency button that the user can use in case of any emergency to notify their respective caregivers immediately. © 2023 ACM.

关键词： Electrocardiograms

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UHI Web Application: Empowering Healthcare with Disease Prediction for Seamless Doctor Consultations 4

UHI Web Application: Empowering Healthcare with Disease Pred...

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4th IEEE Global Conference for Advancement in Technology, GCAT 2023

作者： Vardhan, Nunna Harsha Rajesh, M. Vishal Matcha, V.R.S. Reddy, Sathi Ravi Shankar Chowdary, Verelli Nivas Dept. of Computer Science Engineering Amrita School of Engineering Bangalore India

ISBN: (纸本)9798350305258

The large amount of data generated by hospitals is helping machine learning algorithms to generate accurate solutions. This data includes information about treatment, diagnosis, and medications. This valuable information can be used to create automated solutions. The Indian government is planning to introduce a technology like the United Payment Interface (UPI) in the healthcare sector. This technology is called the United Health Interface (UHI). The UHI aims to consolidate various healthcare services, such as the storage of patients' health records, management of blood banks, provision of hospitals' information, doctors' details, bed availability, medical insurance services, and more. Our goal is to develop a similar system where all these services can be accessed through a single account. The UHI is an advanced technology that has revolutionized the healthcare industry. It offers numerous benefits to both patients and healthcare providers. One of the most significant advantages of UHI is the seamless sharing of patient information across different healthcare providers and institutions. This means that doctors, nurses, and other healthcare professionals can easily access patient data, regardless of their location, and make informed decisions regarding treatment. The online doctor appointment system has also revolutionized healthcare. It offers several advantages for patients and healthcare providers alike. These advantages include convenience, time savings, improved access to healthcare, reduced costs, and enhanced patient management. Therefore, our aim is to develop a web application that consolidates all healthcare services under one platform, significantly improving our lives. Here are some additional details about the UHI and the online doctor appointment system, The UHI is a network of open protocols that enable the interoperability of health services. This means that patients' health records can be shared securely and easily between different healthcare provi

关键词： Disease prediction Gradient Boosting Classifier Random Forest Symptoms Unified health interface

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UAV-based Firefighting by Multi-agent Reinforcement Learning 13

UAV-based Firefighting by Multi-agent Reinforcement Learning

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13th International Conference on computer and Knowledge engineering, ICCKE 2023

作者： Tanha, Reza Shami Hooshmand, Mohsen Afsharchi, Mohsen Dept. Computer Science and It Zanjan Iran University of Zanjan Dept. Electrical and Computer Engineering Zanjan Iran

ISBN: (纸本)9798350330151

Wildfire in the forest leads to a huge amount of financial and human losses. That is it causes damage to the forest and the life of firefighters. To reduce the amount of such damage, unmanned aerial vehicles are among the best options to do the job of firefighting. Their orchestration of effective fire extinguishing is a must and essential. This work proposes a multi-agent reinforcement learning method using an actor-critic structure to extinguish the fire. While the learning is centralized, their execution is decentralized. Moreover, we define two models of fire spreading based on the discrete-time Markov process. The results show that the proposed method outperforms the state-of-the-art methods. © 2023 IEEE.

关键词： Reinforcement learning

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A Model of Factors Influencing the Adoption and Utilization of E-Government Services in KSA (MFIAUEGS) 3

A Model of Factors Influencing the Adoption and Utilization ...

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3rd International Conference on Computing and Information Technology, ICCIT 2023

作者： Almasabe, Dulqader Ludi, Stephanie Aborokbah, Majed University of North Texas Computer Science and Engineering Dept Denton United States University of Tabut Computer Science Dept Tabuk Saudi Arabia

ISBN: (纸本)9798350321487

This research demonstrates a proposal for a model of factors influencing the adoption and utilization of e-government services in Saudi Arabia (MIFEGSAU). This model was developed by combining factors from different well-known models and theories along with technical factors within the Technology Acceptance Model. This research focused on understanding and analyzing the factors taking e-government acceptance and implementation among all public members, particularly those with visual impairments. By Integrating motivational and technological factors recognized in the literature, hypotheses have been created to be studied and tested with Saudi citizens through a questionnaire survey and interviews. © 2023 IEEE.

关键词： e-government

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