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A LoRa-mesh based system for marine Social IoT

A LoRa-mesh based system for marine Social IoT

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Consumer Communications and Networking Conference, CCNC IEEE

作者： Tommaso Patriti Silvia Mirri Roberto Girau Dept. of Computer Science and Eng. University of Bologna Bologna Italy

Recently in the world of boats we hear about “smart boats”, or 3.0 connected boats. For many years, technology has entered the world of boats, especially as regards safety, some systems have become mandatory. With the spread of IoT systems, boats could be considered as sources of information for other boats in the same sea area or for the construction of coastal IoT services. In the marine context, measurements of environmental values such as sea water temperature, wave period and height or direction of currents, are carried out using buoys of considerable size and at a great distance from the coast. In this paper we want to present a Social Internet of Things system that allows the distribution of information between boaters and the integration with fixed IoT networks consisting of buoys and coastal stations. A preliminary LoRa mesh communication test is presented showing a stable mesh network in which each node is able to communicate in the sea with a radius of 5 Km.

关键词： Temperature measurement Mesh networks Current measurement Boats Sea measurements Size measurement Social Internet of Things

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BERT Goes to SQL School: Improving Automatic Grading of SQL Statements

BERT Goes to SQL School: Improving Automatic Grading of SQL ...

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computer science, computer eng.neering, & Applied Computing (CSCE), Congress in

作者： Pablo Rivas Donald R. Schwartz Ernesto Quevedo Dept. of Computer Science School of Eng. & Computer Science Baylor University Dept. of Computing Technology School of Computer Science & Math. Marist College

Automated grading of SQL queries is a challeng.ng task due to the complexity of the language and the variety of acceptable solutions for a given problem. In this paper, we propose a novel approach that leverages deep learning with a BERT model to understand the syntax and semantics of SQL statements. By training BERT on a dataset of SQL queries and their corresponding grades, we create a model that can automatically grade new questions accurately. Our experiments demonstrate that the proposed methodology achieves high accuracy and consistency in grading SQL queries, outperforming existing state-of-the-art models. Furthermore, we provide an analysis of the model's explainability, revealing a new capability that can be extremely beneficial for understanding the decision-making process. Overall, our work demonstrates the potential of deep learning with BERT for improving the efficiency and accuracy of SQL query grading.

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A Smart Network Intrusion Detection System for Cyber Security of Industrial IoT

A Smart Network Intrusion Detection System for Cyber Securit...

引用

Intelligent Data science Technologies and Applications (IDSTA), International Conference on

作者： Fadi Alzhouri Hardik Gunjal Preetkumar Patel Ahmad Hammad Dariush Ebrahimi Dept. of Elect. & Computer Eng. Concordia University Montreal Canada Dept. of Computer Science Lakehead University Thunder Bay Canada Dept. of Computer Eng. Kuwait University Kuwait Kuwait

In the industrial sectors, machines and sensors communicate with each other and with the control or central units through the Internet; this forms a network of Industrial devices called the Industrial Internet of Things (IIoT). IIoT is an emerging trend that generates big data which could be vulnerable to cyber-attacks. In the IIoT network, data and control instructions are usually flown through a Supervisory Control and Data Acquisition (SCADA) system. We propose to install a Network Intrusion Detection System (NIDS) between SCADA and IIoT devices to monitor real-time network traffic and detect cyber-attacks. Several deep learning algorithms can be used on a large dataset for intrusion detection. In this paper, we implement and compare three deep learning algorithms, namely, MultiLayer Perceptron (MLP), Fully Connected Deep Neural Network (FCNN), and Convolutional Neural Network (CNN), on two different datasets by varying the number of selec.ed features for classifications using the XGBoost algorithm. The study shows that CNN with XGBoost is superior in its performance over other methods applied to NIDS. Our proposed methodology has proven to be effective regardless of the highly unbalanced dataset.

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Performance Measurement of Distributed Systems via Single-Host Parallel Requesting using (Single, Multi and Pool) Threads 3

Performance Measurement of Distributed Systems via Single-Ho...

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3rd Information Technology to Enhance e-Learning and Other Application, IT-ELA 2022

作者： Jghef, Yousif Sufyan Zeebaree, Subhi R. M. Ageed, Zainab Salih Shukur, Hanan M. College of Engineering Knowledge University Computer Engineering Dept. Erbil Iraq Technical College of Engineering Duhok Polytechnic University Energy Eng. Dept. Duhok Iraq College of Science Nawroz University Computer Science Dept. Duhok Iraq

ISBN: (纸本)9798350334968

Distributed systems and cloud computing are essential in IT (ICT). Scholars have not contemplated merging distributed systems and cloud computing to measure execution time in milliseconds and capacity in gigabytes. Distributed Systems and Cloud Computing Execute Time and Capacity Methodology This title covered two networking types. Multi-scenario distributed networking begins. A TCP socket links a client-server application (Transmission Control Protocol). This example also networks between computers. In another example, Remote Method Invocation Technology (RMI) links subservers to the main server to handle all client inquiries. Second-generation networking involves distributed systems and cloud computing. Google's API downloaded files to my machine and sent them to the main server. Other examples include using numerous computers or a client server software on the same machine. Multi-client and server threads helped the system find correct results. Pool threads were used elsewhere. This thesis examines execution time and file capacity. The system showed how cloud computing affects distributed systems in two ways to apply many scenarios and draw conclusions (execution time and capacity). This project utilizes TCP sockets, RMI, and API. Threads and a hash table software structure were used to load data into the system between the client and the server. © 2022 IEEE.

关键词： Cloud computing

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Shieldmaiden: A maternity and baby care assistance smartphone application with pregnancy detection, healthcare support, baby product purchasing features

Shieldmaiden: A maternity and baby care assistance smartphon...

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Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), IEEE Conference on

作者： Mahfuzulhoq Chowdhury Arupa Barua Suriya Sultana Dept. of Computer Science and Engg. CUET Chittagong Univ. of Eng. And Tech. Bangladesh Department of Computer Science and Engg. CUET Chittagong Univ. of Eng. And Tech. Bangladesh

ISBN: (数字)9798331521691

ISBN: (纸本)9798331521707

A nation’s development and well-being depend on a healthy mother and newborn child. There were no ICT-based smartphone applications with pregnancy detection, health status prediction for the mother and newborn, or online mom and baby goods buying features in previous maternity and infant care-related works. Additionally, they did not offer any support systems for the detection of postpartum depression in women, search for health professionals, ambulances, infant day care centers, caregivers, and clinic search, as well as pregnancy calendars and recommendations, help for maternity-related queries, and emergency messaging features. To resolve these problems, this paper offers a smartphone application for maternity and baby care assistance with pregnancy detection, health status detection, mom and baby item purchase, search for health professionals and clinics, post-partum depression detection, exercise and diet advice, baby day care center search, query assistance, and emergency chat features. According to the app’s merit and impeccability study results, over 62% of reviewers provided spectacular feedback on the app’s suitability.

关键词： Pregnancy Pediatrics Technological innovation Transfer learning Medical services Feature extraction Depression Search problems Method of moments Smart phones

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Deep Learning Approaches for Natural Language Understanding

Deep Learning Approaches for Natural Language Understanding

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Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), IEEE Conference on

作者： Saurabh Pratap Singh Rathore Shristi Chamoli Roy T P Ajith Sundaram Neeraj Varshney Vinod Sharma Dept. of Management & Research ICAPSR New Delhi India Dept. of Management Uttaranchal University Dehradun India Dept. of Computer Science & Eng. TKM College of Engineering Kerala India Dept. of Business Amrita Vishwa Vidyapeetham Kochi India Dept. of Computer Eng. & Applications GLA University Mathura India Dept. of Computer Science Jiwaji University Gwalior India

ISBN: (数字)9798331521691

ISBN: (纸本)9798331521707

Deep learning models have really revolutionized the domain of NLU, enabling robots to understand and process human language with high accuracy. These models, which include neural networks like RNNs, CNNs, and Transformers, are quite efficient in extracting complex verbal patterns and contextual information. Recurrent Neural Networks, including LSTM and GRU, are specially proficient in modeling sequences, sentiment analysis, and language translation. Conversely, CNNs are applicable for sentence classification and the extraction of key phrases. The Transformer architecture, especially with models like BERT and GPT, set new benchmarks for NLU by leveraging self-attention mechanisms to improve context understanding and handle long-range dependencies. Deep learning has really advanced tasks such as text classification, question answering, machine translation, among others, which in fact has pushed the boundaries of what machines can achieve in understanding language.

关键词： Deep learning Training Sentiment analysis Analytical models Technological innovation Accuracy Translation Text categorization Transformers Context modeling

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Special Session: Amplifying Voices Through Animaker Animation: Results from a Longitudinal Study with Latino/a/x eng.neering Students 54

Special Session: Amplifying Voices Through Animaker Animatio...

引用

54th IEEE Frontiers in Education Conference, FIE 2024

作者： Mejia, Joel Alejandro Hernandez, Sofia Paul, Neethu University of Texas at San Antonio Dept. of Biomedical & Chemical Eng. San AntonioTX United States University of Texas at San Antonio Dept. of Computer Science San AntonioTX United States University of Texas at San Antonio Dept. of Int. Learning & Teaching San Antonio United States

ISBN: (纸本)9798350351507

This special session explores the application of Chicana Feminist Epistemology methodologies in eng.neering education research with a focus on Latino/a/x students at Hispanic Serving Institutions. By utilizing Platicas and Testimonios as forms of data and data collection approaches in eng.neering education research, this session aims to foster a more inclusive and empowering research approach while challeng.ng traditional Westernized paradigms. Through the analysis of Animaker videos created from vignettes emerging from these Platicas and Testimonios, participants will have a better understanding of the experiences of Latino/a/x eng.neering students, emphasizing asset-based methodologies and the creation of multimodal artifacts for research purposes. The research approaches presented in this session seek to amplify marginalized voices, promote critical consciousness, and challeng. traditional ways of knowing and doing in eng.neering education research, encouraging attendees to integrate these methodologies into their research and teaching practices effectively to support diverse student populations. © 2024 IEEE.

关键词： Students

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Performance Analysis of Time Series Databases: A Comparison in Cloud and Physical Environments

Performance Analysis of Time Series Databases: A Comparison ...

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Artificial Intelligence and Knowledge eng.neering (AIKE)

作者： Haoming Tong Sunghwan Jeon Yunmook Nah Dept. of Computer Eng. Graduate School Dankook university Yongin-si Korea Dept. of Data Science Graduate School Dankook University Yongin-si Korea Dept. of Computer Eng. Dankook University Yongin-si Korea

ISBN: (数字)9798331517045

ISBN: (纸本)9798331517052

The exponential growth of time-series data presents new challeng.s in time-series data processing. This paper provides a detailed analysis of the performance of InfluxDB, a widely adopted time-series database, in both physical and cloud-based infrastructures. We the Time Series Benchmarking Suite (TSBS) to quantitatively measure write and query performance across a range of dataset sizes. Write performance was assessed in terms of throughput and latency, while query performance focused on response times for the six distinct query types. The experimental results can be used to provide guidance on selec.ion of suitable time-series databases for varied application requirements.

关键词： Databases Scalability Time series analysis Throughput Data processing Size measurement Time measurement Time factors Resource management Reliability

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Automated Road Extraction from Aerial Images: A Generative Approach with W-FuseNet Model

Automated Road Extraction from Aerial Images: A Generative A...

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International Conference on Computing and Networking Technology (ICCNT)

作者： Debendra Muduli Santosh Kumar Sharma Debasish Pradhan Dept. Computer Science and Eng. C.V. Raman Global University Bhubaneshwar India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

This research introduces an automated road extraction model utilizing deep learning techniques for high-resolution aerial imagery. Focused on applications in urban planning, disaster management, and logistics, the study employs convolutional neural networks (CNNs) and a conditional Generative Adversarial Network (cGAN) architecture. The Massachusetts Roads Dataset, comprising 1171 images, is subject to advanced preprocessing techniques, including resizing, concatenation, and normalization. The proposed model features a carefully crafted generator with an encoder-decoder architecture and a modified Pix2pix-based cGAN for semantic segmentation. Inspired by the PatchGAN concept, the discriminator assesses image patches to distinguish real from generated images. A literature survey evaluates methodologies, emphasizing the Road Structure Refined CNN (RSRCNN), generative learning approaches, and the fully convolutional network (FCN) for road extraction. Performance analysis demonstrates the model’s competitive IoU score compared to existing approaches along with accuracy, precision, recall and f1-score. A novel road extraction model using the Massachusetts Roads Dataset is introduced, highlighting WFuseNet architecture and advanced pre-processing techniques.

关键词： Surveys Analytical models Adaptation models Roads Semantic segmentation Urban planning computer architecture Predictive models Convolutional neural networks Remote sensing

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Bridging the Digital Divide: 6G Networks and Enabling Technologies for Ubiquitous Coverage

Bridging the Digital Divide: 6G Networks and Enabling Techno...

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Advanced Telec.mmunication and Networking Technologies (ATNT), IEEE International Conference on

作者： Muhammad Omair Butt Lilatul Ferdouse Waleed Eiaz Dept. of Elect. and Computer Eng. Lakehead University Thunder Bay ON Canada Dept. of Physics and Computer Science Wilfrid Laurier University Waterloo ON Canada

ISBN: (数字)9798350353501

ISBN: (纸本)9798350353518

Sixth-generation (6G) networks are expected to support an exponential increase in connected devices and address critical concerns such as capacity, coverage, and privacy. However, one significant concern is the digital divide, which refers to the difference in accessibility, availability, and usage of communication services between urban and rural areas. The COVID-19 pandemic has emphasized the need for reliable communication services in rural areas for economic inclusion in online education, remote work, and financial services. In this paper, we examine the three levels of the digital divide: coverage, access, and usage, and analyze suitable communication technologies to mitigate coverage issues and achieve ubiquitous service. Moreover, we explore enabling technologies that can help reduce global coverage gaps. Within this context, we provide a case study involving on-demand coverage and computational services provisioning in remote rural areas to demonstrate how such measures can harness the benefits of digital farming. Finally, we conclude the paper and present future research directions.

关键词： 6G mobile communication Privacy Pandemics Rural areas Communications technology Remote working Digital divide Reliability Financial services Farming

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