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1st International Conference on Advances in Computational Science and engineering, ICACSE 2020

作者： Sabhanayagam, T. Senthil Kumar, T. Narendra, M. Martin Sahayaraj, J. Department of Software Engineering School of Computing SRM Institute of Science and Technology Tamil Nadu Kattankulathur India Department of Electronics and Communication Engineering Siddharth Institute of Engineering and Technology Andhra Pradesh Puttur India Department of Information Technology CMR Engineering College Telangana Hyderabad India Department of Electronics and Communication Engineering Sri Indu College of Engineering and Technology Telangana Sheriguda India

When technological development progresses, human interference has become less common, and machines are being used for diverse activities and humans' health. Currently, fire misfortunes still keep happenings running, place human life and properties at risk, and find fires impossible to save lives. In these situations, a robot is used to defend human lives, property and the world from the flames. This model is an IoT robot which detects fire. The robot may be told regarding its activity and disabled. An air pump or a fire style carbon dioxide pump small stretches. Medium lengths. The combination of fire and carbon monoxide is identified via the mounted sensors that generate a graph. The research is often valuable for supplying supplementary details health officials inhaled over the quantity of hazardous gas the inhabitants of the impacted region over a span such that adequate steps can be taken to repair the injury. © Published under licence by IOP Publishing Ltd.

关键词： Fires

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Novel Approach of Designing of a Low-Cost Artificial Ventilators 1

Novel Approach of Designing of a Low-Cost Artificial Ventila...

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1st International Conference on Advances in Computational Science and engineering, ICACSE 2020

作者： Narendra, M. Sabhanayagam, T. Martin Sahayaraj, J. Senthil Kumar, T. Department of Information Technology CMR Engineering College Telangana Hyderabad India Department of Software Engineering School of Computing SRM Institute of Science and Technology Tamil Nadu Kattankulathur India Department of Electronics and Communication Engineering Sri Indu College of Engineering and Technology Telangana Sheriguda India Department of Electronics and Communication Engineering Siddharth Institute of Engineering and Technology Andhra Pradesh Puttur India

In addition to expected ventilator scarcity, induced by the disease outbreak of COVID-19, several organizations have Low-cost emergency breathing apparatuses have been developed. Pressure-cycled pneumatic ventilators are some of these devices that are easy to be using. The signaling or alert features are produced but often not included, on industrial ventilators. This article reports a simplified, simple electronic pressure-cycled respirator sensor & alert device that measures theoretically efficient parameters such as strain & respiratory rate & sounds of alarm;when the respirator malfunctions. A signal processing is for low complexity. A set of time-varying recursive envelope trackers are used in the algorithm to Signal control from a wired digital pressure sensor Trachea of the client. Measurements on each specimen such that it can operate on virtually every test on a microcontroller. © Published under licence by IOP Publishing Ltd.

关键词： Microcontrollers

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Integrating GPS and GSM Technologies for Enhanced Women’s Safety: A Fingerprint-Activated Device Approach

Integrating GPS and GSM Technologies for Enhanced Women’s S...

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Automation and Computation (AUTOCOM), International Conference on

作者： Kamred Udham Singh Varun Chaudhary Pradeep Kumar Sharma Pushpendra Kumar Neeraj Varshney Teekam Singh School of Computing Graphic Era Hill University Dehradun India IMS ENGINEERING COLLEGE Ghaziabad India Technical Architect HCL Technologies Noida UP Sr Software Engineer Scanno System Greater Noida Department of Computer Engineering & Applications GLA University Mathura UP India Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun

The creation of a safety system that is based on GPS and is developed exclusively for the health and safety of women via the incorporation of novel elements in order to meet the rising concerns about crimes committed against women. The gadget is capable of contacting authorities, conveying the user’s position via SMS, and generating a loud noise to attract attention. It may be triggered in anticipation of potential danger and can be activated in the event that danger is imminent. In order to guarantee that only authorized users are able to activate the device, the system makes use of fingerprint recognition in a very unique way. Using technologies such as global positioning system (GPS), global system for mobile communications (GSM), and microcontrollers, this study makes a contribution to the continuing efforts to improve the safety of women via technological innovation. It provides a proactive approach to prevent violence against women and save lives. The research emphasizes the significance of combining hardware and software in order to provide a complete safety tool. It also illustrates the vital role that quick support plays and the potential of such gadgets to promote confidence among women in public places.

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Report from Dagstuhl Seminar 21442: Ensuring the Reliability and Robustness of Database Management Systems

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Datenbank-Spektrum 2022年第3期22卷 261-263页

作者： Rigger, Manuel Böhm, Alexander Christakis, Maria Lo, Eric Department of Computer Science National University of Singapore 13 Computing Drive Singapore Singapore Google Germany GmbH ABC-Str. 19 Hamburg Germany Max Planck Institute for Software Systems Paul-Ehrlich Strasse G 26 Kaiserslautern Germany Department of Computer Science and Engineering The Chinese University of Hong Kong Ho Sin-Hang Eng. Building Hong Kong

In November 2021, Dagstuhl seminar 21442 was bringing together researchers and practitioners from various domains such as of databases, automatic testing, and formal methods to build a common ground and to explore possibilities for systematically improving the state of the art in database management system engineering. The outcome of the seminar was a joint understanding of the specific intricacies of building stateful system software, as well as the identification of several areas of future work. In particular, we believe that database system engineering can both be significantly improved by adopting additional verification techniques and testing tools, and can provide important feedback and additional challenges (e.g. related to state management) to neighboring domains. © 2022, Gesellschaft für Informatik e.V. and Springer-Verlag GmbH Germany, part of Springer Nature.

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PI-VIMO: PHYSIOLOGY-INSPIRED ROBUST VITAL SIGN MONITORING USING MMWAVE RADARS

arXiv

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arXiv 2023年

作者： Zhang, Bo Jiang, Boyu Zheng, Rong Zhang, Xiaoping Li, Jun Xu, Qiang Dept. of Computing and Software McMaster University HamiltonON Canada Department of Electrical Computer and Biomedical Engineering Toronto Metropolitan University TorontoON Canada Huawei Human Machine Interaction Lab MarkhamON Canada

Continuous monitoring of human vital signs using non-contact mmWave radars is attractive due to their ability to penetrate garments and operate under different lighting conditions. Unfortunately, most prior research requires subjects to stay at a fixed distance from radar sensors and to remain still during monitoring. These restrictions limit the applications of radar vital sign monitoring in real life scenarios. In this paper, we address these limitations and present Pi-ViMo, a non-contact Physiology-inspired Robust Vital Sign Monitoring system, using mmWave radars. We first derive a multi-scattering point model for the human body, and introduce a coherent combining of multiple scatterings to enhance the quality of estimated chest-wall movements. It enables vital sign estimations of subjects at any location in a radar’s field of view (FoV). We then propose a template matching method to extract human vital signs by adopting physical models of respiration and cardiac activities. The proposed method is capable to separate respiration and heartbeat in the presence of micro-level random body movements (RBM) when a subject is at any location within the field of view of a radar. Experiments in a radar testbed show average respiration rate errors of 6% and heart rate errors of 11.9% for the stationary subjects, and average errors of 13.5% for respiration rate and 13.6% for heart rate for subjects under different RBMs. © 2023, CC BY.

关键词： Errors

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Goal-Modeling Privacy-by-Design Patterns for Supporting GDPR Compliance

Goal-Modeling Privacy-by-Design Patterns for Supporting GDPR...

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18th International Conference on software Technologies, ICSOFT 2023

作者： Al-Obeidallah, Mohammed Ghazi Piras, Luca Iloanugo, Onyinye Mouratidis, Haralambos Alkubaisy, Duaa Dellagiacoma, Daniele Department of Software Engineering Al Ain University Abu Dhabi United Arab Emirates School of Computing Middlesex University London United Kingdom School of Computing Robert Gordon University Aberdeen United Kingdom Institute for Analytics and Data Science University of Essex Colchester United Kingdom College of Applied Studies and Community Service Imam Abdulrahman Bin Faisal University Dammam Saudi Arabia Centre for Secure Intelligent and Usable Systems University of Brighton Brighton United Kingdom

ISBN: (纸本)9789897586651

The introduction of the European General Data Protection Regulation (GDPR) has imposed obligations on organisations collecting data in the EU. This has been beneficial to citizens due to rights reinforcement achieved as data subjects. However, obligations heavily affected organisations, and their privacy requirements analysts, having issues with interpreting and implementing GDPR principles. This paper proposes visual GDPR Patterns supporting analysts through Privacy-by- Design (PbD) and GDPR compliance analysis. In order to achieve that, we extended a requirements modeling tool, SecTro, which is used to assist analysts in creating visual requirements models. Specifically, we extended SecTro with novel visual GDPR patterns representing GDPR principles. We evaluated the patterns in a healthcare case study. The evaluation results suggest that the GDPR patterns can help analysts in PbD modeling analysis, by representing GDPR principles and considering relevant ready-to-use alternatives, towards achieving GDPR compliance. © 2023 by SCITEPRESS-Science and Technology Publications, Lda.

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Inter- and intra-uncertainty based feature aggregation model for semi-supervised histopathology image segmentation

arXiv

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arXiv 2024年

作者： Jin, Qiangguo Cui, Hui Sun, Changming Song, Yang Zheng, Jiangbin Cao, Leilei Wei, Leyi Su, Ran School of Software Northwestern Polytechnical University Shaanxi China Department of Computer Science and Information Technology La Trobe University Melbourne Australia CSIRO Data61 Sydney Australia School of Computer Science and Engineering University of New South Wales Sydney Australia School of Software Shandong University Shandong China School of Computer Software College of Intelligence and Computing Tianjin University Tianjin China

Acquiring pixel-level annotations is often limited in applications such as histology studies that require domain expertise. Various semi-supervised learning approaches have been developed to work with limited ground truth annotations, such as the popular teacher-student models. However, hierarchical prediction uncertainty within the student model (intra-uncertainty) and image prediction uncertainty (inter-uncertainty) have not been fully utilized by existing methods. To address these issues, we first propose a novel inter- and intra-uncertainty regularization method to measure and constrain both inter- and intra-inconsistencies in the teacher-student architecture. We also propose a new two-stage network with pseudo-mask guided feature aggregation (PG-FANet) as the segmentation model. The two-stage structure complements with the uncertainty regularization strategy to avoid introducing extra modules in solving uncertainties and the aggregation mechanisms enable multi-scale and multi-stage feature integration. Comprehensive experimental results over the MoNuSeg and CRAG datasets show that our PG-FANet outperforms other state-of-the-art methods and our semi-supervised learning framework yields competitive performance with a limited amount of labeled data. Copyright © 2024, The Authors. All rights reserved.

关键词： Image segmentation

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The unified perspective of digital transformation and continuous software engineering

The unified perspective of digital transformation and contin...

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software-Intensive Business (IWSiB), IEEE/ACM International Workshop on

作者： Eriks Klotins Einav Peretz-Andersson Software Engineering Research Lab (SERL) Blekinge Institute of Technology Karlskrona Sweden Department of Computing School of Engineering J&#x00F6 nk&#x00F6 ping University J&#x00F6 ping Sweden

ISBN: (纸本)9781665462297

software is a key component of most products, services, industrial processes, and back-office functions. Thus, companies may gain an advantage by establishing fast feedback cycles to improve their software. Continuous software engineering (CI/CD) is being primarily studied as an engineering topic. However, the rest of the organization needs to align and be prepared to utilize the benefits of CI/CD. In this paper, we explore the overlap between CI/CD and digital transformation (DT). We study literature in both areas to develop a map of conditions, mechanisms, and outcomes. As a result, we present a unified perspective of CI/CD and DT. We found that CI/CD can be seen as an implementation of DT in a software organization. DT perspective can help to guide the adoption of CI/CD from an organizational perspective.

关键词： Leadership Digital transformation Conferences Companies software software engineering

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An IT/OT Converged Cyber Range Framework Supporting Ensemble of Large Multimodal Models-Human Teaming and RAG Capability for Bigdata Information Retrieval – 6G Perspective

An IT/OT Converged Cyber Range Framework Supporting Ensemble...

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IEEE Conference on Global Communications (GLOBECOM)

作者： M. Abdur Rahman M. Saiful Islam M. Repon Islam M. Shamim Hossain Selwa Al-Hazzaa Cyber Security and Forensic Computing Department University of Prince Mugrin Medina Saudi Arabia UoL Worldwide University of London London United Kingdom Department of Computer Science and Engineering Khulna University of Engineering & Technology Khulna Bangladesh Department of Software Engineering King Saud University Riyadh Saudi Arabia Digital Innovation Sector King Abdulaziz City for Science and Technology (KACST) Riyadh Saudi Arabia

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

In IT/OT converged enterprise networks, the management of multimodal big data has surpassed human capabilities, presenting critical challenges in business decision-making. This paper introduces an innovative IT/OT Converged Cyber Range Framework, leveraging the power of 6G technology alongside an ensemble of large multimodal models (LMMs) equipped with Retrieval Augmented Generation (RAG) capabilities. Our proposed framework excels at parsing and retrieving information from diverse and massive multimodal datasets in near real-time, driven by the integration of LMMs and human interactions in natural language. The framework's advanced configuration with RAG achieved top performance with an average score of 80.5 across key metrics, including an 86 in answer relevancy and an 88 in faithfulness, while effectively reducing hallucinations to a score of 26. By combining 6G's connectivity with advanced LMM capabilities, we significantly improve the efficiency of automated big data processing and information retrieval, thereby transforming decision-making processes in IT/OT environments. The implementation of our framework, validated through real-life big data sources, and the encouraging test results showcase its effectiveness and transformative potential in managing and utilizing big data far beyond traditional human capabilities.

关键词： 6G mobile communication Measurement Retrieval augmented generation Decision making Natural languages Big Data Information retrieval Real-time systems Multimedia communication Global communication

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Adaptive Fuzzy Neural Network vs. Convolution Neural Network in Classifying COVID-19 from Chest X-rays

Adaptive Fuzzy Neural Network vs. Convolution Neural Network...

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IEEE Globecom Workshops

作者： Mubarak Alrashoud Md Abdur Rahman Department of Software Engineering King Saud University Riyadh Saudi Arabia Cyber Security & Forensic Computing Department University of Prince Mugrin Madinah Saudi Arabia

ISBN: (纸本)9781665459761

Detecting COVID-19 in the early time can save lives and reduce the cost of huge pressure on healthcare centers. Many machine and deep learning models have been proposed by researchers to detect and diagnose COVID-19 based on chest X-rays. However, we need to know which of those models is more effective and efficient. This paper presents a comparative study between adaptive fuzzy neural network (AFNN) and convolutional neural network (CNN) in classifying COVID-19 using chest X-rays. We present the experimental results showing the comparative performance measures with respect to the size of available dataset. We also present the relative advantage of each family of neural network in accuracy, precision, recall, F1score, and the computation time.

关键词： COVID-19 Adaptation models Adaptive systems Neural networks Medical services Fuzzy neural networks Size measurement

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