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Identification of Risks Related to Passenger Exchange Service in the Water Tram Stop Area on the Example of the Water Tram of the Wroclaw Agglomeration 1

引用

19th Scientific and Technical Conference of the Transport systems Theory and Practice

作者： Skupien, Emilia T. Tubis, Agnieszka A. Rydlewski, Mateusz Wroclaw Univ Sci & Technol Wroclaw Poland

ISBN: (数字)9783031531811

ISBN: (纸本)9783031531804;9783031531811

The paper presents aspects of risks related to the infrastructure of the water tram stop area on the example of the water tram of the Wroclaw Agglomeration. The research area was limited to the passenger exchange service process. To identify the risks, the HFACS (Human Factors Analysis and Classification System) analysis framework was used. Then the city standards for the requirements of the tram and bus stops in Wroclaw and the standards for the infrastructure of the stops of water vessels were analysed. Based on that, the minimum requirements must be met by water tram stops located in the urban agglomeration. These standards are a baseline that must be completed in the design and modification of the current water tram stop.

关键词： water tram risk passenger exchange water tram stop area

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Prototyping IoT Technology Solutions Using LoRaWAN Infrastructure

Prototyping IoT Technology Solutions Using LoRaWAN Infrastru...

引用

International Conference on New Technologies, Development and Application

作者： Hajdar, Amir Konjicija, Samim Univ Sarajevo Inst Geodesy & Geoinformat Patriotskelige 30 Sarajevo 71000 Bosnia & Herceg Univ Sarajevo Fac Elect Engn Kampus Univ Sarajevu Sarajevo 71000 Bosnia & Herceg

ISBN: (纸本)9783031310652;9783031310669

IoT solutions are rapidly finding ways into our lives. They are gaining popularity not only for small scale home applications, but also for large scale industrial applications. We generally have a problem of managing and monitoring multiple devices so we have to automate our processes. This is especially true for large scale industrial applications. In order to learn how this automation can benefit us as well as find potential failures and bottle-necks, we often have to develop p rototypes. These prototypes help us analyze potential problems and further improve our final, most efficient, solutions. The purpose of this paper is to present a prototype developed utilizing Long Range Wide Area Network (LoRaWAN) to communicate with IoT devices that can be used for many different types of home and industrial applications. Typical LoRaWAN architecture will be presented, and use of data collected from a water meter device and a prototype device for measuring air temperature will be demonstrated.

关键词： IoT LoRaWAN prototype MQTT TTN InfluxDB networking

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A Survey and a State-of-the-Art Related to Consensus Mechanisms in Blockchain Technology 2nd

A Survey and a State-of-the-Art Related to Consensus Mechani...

引用

3rd International Conference on Digital Technologies and Applications

作者： Barj, Sara Ouaddah, Aafaf Mezrioui, Abdellatif Natl Inst Posts & Telecommun Rabat Morocco

ISBN: (纸本)9783031298561;9783031298578

Consensus is an essential element of Blockchain technology, as it allows distributed networks to achieve agreement on the state of their shared ledger without the need for a central authority. This is crucial for the security and reliability of the network since it ensures that all nodes have the same copy of the ledger and that the ledger is tamper-proof. Hence, the goal of this paper is to explore and review the most known consensus mechanisms in the wild. In this direction, we start by identifying the types of blockchains and discussing criteria for performing the comparison and the analysis of the studied consensus mechanisms while recalling the Problem of Byzantine Generals. The consensus mechanisms discussed in this paper are mainly those used in public and permissionless blockchains and those used in private and permissioned ones. Finally, we propose a comparison and an analysis of the studied consensus mechanisms, based on the speed and efficiency, validation process and the CAP theorem, to select the best choice for newly designed blockchain platforms.

关键词： Consensus mechanisms Blockchain technologies Consensus mechanism analysis

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Preliminary Study on the Detection of Subtle Variations in Image Sequences for Identifying False Starts in Speedway Racing 1

引用

19th International Conference on Dependability of Computer systems (DepCoS-RELCOMEX)

作者： Krakowian, Jacek Jelen, Lukasz Fdn Support Innovat Res & Dev Grobli 12 Lok 0-211 PL-50421 Wroclaw Poland Wroclaw Univ Sci & Technol Dept Comp Engn Wybrzeze Wyspianskiego 27 PL-50370 Wroclaw Poland

ISBN: (数字)9783031618574

ISBN: (纸本)9783031618567;9783031618574

Computer Vision algorithms have gained significant popularity and prove to be highly beneficial in detecting motion. These methods have proven to be profitable in motor sports especially. This paper presents a preliminary study on image processing, computer vision, and Long Short-Term Memory (LSTM) networks to detect subtle variations in image sequences for identifying false starts in speedway racing. Traditional methods often rely on manual observation, which lacks the precision to capture delicate movements at the start line. The presented methodology utilizes mentioned methods to enhance image quality, computer vision to detect and track racers' positions, and LSTM networks to analyze temporal sequences for movements indicating a false start. Results indicate that the adopted approach outperforms manual false start detection in accuracy and reliability. This advancement not only ensures fairness in speedway racing by providing a more objective detection of false starts but also demonstrates the potential of these technologies for applications requiring the identification of subtle changes in sequences. The efficiency and precision of our method offer promising implications for sports regulations and beyond, advocating for the broader application of technology in similar contexts.

关键词： motion detection speedway false start Gaussian mixture model frame difference Long Short-Term Memory LSTM

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Towards Explainable AI: Relationship Between Twitter Sentiment, User Behaviour, and Bitcoin Price Prediction

Towards Explainable AI: Relationship Between Twitter Sentime...

引用

Intelligent systems Conference (IntelliSys)

作者： Zhu, Qinan Ogunsakin, Rotimi Alliance Manchester Business Sch Booth St West Manchester M15 6PB Lancs England

ISBN: (纸本)9783031477201;9783031477218

Bitcoin prices have been predicted using Twitter sentiments, with results showing relatively low prediction accuracy. Additional external data sources, such as Google Trends, have been used to improve prediction accuracy. However, to the best of our knowledge, no analytical approach has been used to explain why Twitter sentiment is not a good predictor and why additional external data improved predictive model accuracy. Consequently, this paper uses cluster analysis and Shapley Additive Explanations (SHAP) to analyse feature importance and impact on the prediction outcome of the eXtreme Gradient Boosting (XGBoost) model. A combination of Twitter sentiments and user interaction behaviour, such as likes, retweets, and replies, are used as input variables for the XGBoost model and Bitcoin closing prices as the target variable. Our findings indicate that the sentiment score is insufficient because the majority of Bitcoin-related tweets come from Bitcoin enthusiasts whose opinions are unaffected by market fluctuations, and the improved prediction accuracy observed when external data are used in addition to the sentiment score is significant only during price volatility and can be attributed to an increase in the total number of interactions from new sets of users and not the cumulative user behaviour.

关键词： Shapley Additive Explanations Explainable AI Sentiment Analysis Bitcoin

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A Deep Convolutional Neural Network Approach for Plant Leaf Segmentation and Disease Classification in Smart Agriculture

A Deep Convolutional Neural Network Approach for Plant Leaf ...

引用

Computing Conference

作者： Masmoudi, Ilias Lghoul, Rachid Al Akhawayn Univ Ifrane Hassan II Ave Ifrane 53000 Morocco

ISBN: (纸本)9783030801267;9783030801250

This paper concerns an approach for developing a set of tools based on computer vision and deep learning to detect and classify plant diseases in smart agriculture. The main reason that motivated this work is that early detection of plant diseases can help farmers effectively monitor the health of their culture, as well as make the best decision to avoid the spread of the pathogens. In this work, a novel way for training and building a fast and extensible solution to detect plant diseases with images and a convolutional neural network is described. The development of this methodology is achieved in two main steps. The first one introduces Mask R-CNN to give bounding boxes and masks over the area of plant leaves in images. The model is trained on the PlantDoc dataset made of labeled images of leaves with their corresponding bounding boxes. And the second one presents a convolutional neural network that returns the class of the plant. This CNN is trained on the PlantVillage dataset to recognize 38 classes across 14 plant species. Experimental results of the proposed approach show an average accuracy of 76% for leaf segmentation and 83% for disease classification.

关键词： Computer vision Convolutional neural network Segmentation Classification

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Anomaly Detection Using Smartphone Sensors for a Bullying Detection 11th

Anomaly Detection Using Smartphone Sensors for a Bullying De...

引用

11st World Conference on Information systems and Technologies (WorldCIST)

作者： Gattulli, Vincenzo Impedovo, Donato Sarcinella, Lucia Univ Bari Aldo Moro Dipartimento Informat I-70125 Bari Italy

ISBN: (纸本)9783031456503;9783031456510

Anomaly Detection is a fundamental process of detecting a situation different from the ordinary. The followingwork dealswith anomalies in the human behavioral domain while filling out a questionnaire about bullying and cyberbullying. In this work, data obtained from smartphones' sensors (accelerometer, magnetometer, and gyroscope) are analyzed to apply useful Anomaly Detection techniques to detect any abnormal behaviors adopted while filling out the questionnaire implemented in an Android application. Psychology and computer science are merged to analyze and detect any latent patterns within the data set under examination to understand any polarizing content proposed during the use of the app and identify users who exhibit anomalous behaviors, possibly common to classes of users.

关键词： Anomaly Detection Sensors Smartphone Bullying Cyberbullying

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A Conceptual Architecture for Building Intelligent Applications for Cognitive Support in Dementia Care 12th

A Conceptual Architecture for Building Intelligent Applicati...

引用

12th World Conference on Information systems and Technologies (WorldCIST)

作者： Silva, Ana Beatriz dos Santos, Vitor Duarte NOVA Informat Management Sch Lisbon Portugal

ISBN: (纸本)9783031603273;9783031603280

In response to the growing global aging population and the expected rise in dementia cases, this research addresses the critical need for innovative technological solutions in elderly dementia care. With a focus on alleviating the imminent strain on healthcare systems, this study advocates for leveraging technology to create tailored solutions, ranging from user-friendly wearable alarms to the integration of cutting-edge service robots. Emphasizing the importance of patient-centered design, this research aims to discern key factors in cognitive aging care, steering the development and implementation of digital solutions. Beyond proposing an intelligent model for brain aging, this work aspires to transcend academic boundaries by fostering a wider community interest in mental health discourse. Furthermore, it seeks to empower and assist caregivers through the integration of advanced technologies, including AI-driven tools, cognitive screening applications, and remote assessments.

关键词： First Dementia Elderly Digital Solutions Conceptual Architeture Artificial Intelligence

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Design of a Sit to Stand Motion Robotic Assistance Device 7th

Design of a Sit to Stand Motion Robotic Assistance Device

引用

7th International Conference on Green Technology and Sustainable Development

作者： Long Triet Giang Huynh Viet Anh Dung Cai Viet Thang Nguyen Khanh Dien Le Thanh Tung Le Saigon Technol Univ Ho Chi Minh City Vietnam Ho Chi Minh City Univ Technol & Educ Ho Chi Minh City Vietnam Eastern Int Univ Thu Dau Mot Vietnam

ISBN: (纸本)9783031762314;9783031762321

This paper presents the design and the control solution of a "sit - to stand" motion assistance device developed for the purpose of functional rehabilitation of patients after stroke. The device consists of a motorized exoskeleton structure that mimics human lower limb skeleton. The connections between the external mechanical structure and the human lower limb are realized via passive mechanical linkages, allowing the compensation of misalignment between the user's anatomical joints axes and the rigid mechanical axes of the structure. Two linear DC motors are fixed at the knee and ankle levels, providing passive motions / assistance to motion for these joints. The interactive torques between the mechanical structure and the human's limbs are controlled using torque sensors. First experimental results are presented and discussed.

关键词： Lower Limb Exoskeleton Robotic Assistive Device Sit-to-Stand Motion

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Deep Learning Model for Diagnosing the Severity of Diabetic Retinopathy 4th

Deep Learning Model for Diagnosing the Severity of Diabetic ...

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4th Congress on Intelligent systems (CIS)

作者： Nalla, Nikitha Reddy Chellamani, Ganesh Kumar Amrita Vishwa Vidyapeetham Dept Elect & Commun Engn Amrita Sch Engn Chennai India

ISBN: (纸本)9789819990368;9789819990375

Diabetes Mellitus, a condition that affects diabetic individuals, causes diabetic retinopathy. In many nations, it is the leading cause of blindness. A person's likelihood of going blind increases if they have diabetic retinopathy. The failure to properly treat and monitor diabetic retinopathy before it progressed to a severe stage was the root cause of blindness in 90% of instances. In its extreme stages, diabetic retinopathy has no known treatment. However, it can be identified and avoided in its early stages. Consequently, computerized computer diagnosis will help clinicians to find diabetic retinopathy early and more affordably. In health informatics, deep learning is gaining importance. This study uses different deep learning models to create and compare, from which DenseNet169 has been identified as the best deep learning model to categorize the disease into different stages. It may help clinicians to determine the severity of diabetic retinopathy more effectively.

关键词： Deep learning Diabetic retinopathy Image processing Fundus images

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