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Respiratory Sounds Classification by Fusing the Time-Domain and 2D Spectral Features

Respiratory Sounds Classification by Fusing the Time-Domain ...

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IEEE international conference on Bioinformatics and Biomedicine (BIBM)

作者： Gaoyang Dong Jianhong Wang Yufei Shen Mingli Zhang Minghui Zhang Ping Sun School of Information Engineering Nanchang University Nanchang China 1st Affiliated Hospital of Nanchang University Nanchang China

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

Automated respiratory sounds classification is a challenging task. Currently, the most commonly used feature extraction methods in the respiratory sounds classification are based on two-dimensional time-frequency representation, which reflect more information in the frequency domain but usually ignore the key information in the time domain of audio signals. To overcome this limitation, we proposed a novel respiratory sounds classification method that integrates the time-domain and two-dimensional time-frequency representation features of audio signals. Specifically, we first used a Mel encoder to extract the spectral features from the Mel-spectrum and used time domain feature extraction module to capture the time domain features of the original audio signal respectively. Then, we designed co-attention module for efficiently fusing these two different types of features. Finally, we inputted the fused features into the classifier for accurate classification of respiratory sounds. Experimental results on the ICBHI 2017 and SPRSound datasets demonstrate that our method achieved state-of-the-art performance. Specifically, it surpassed previous best results by 1.00% on ICBHI 2017 dataset and exceeded the best results in the four subtasks of SPRSound dataset by 3.01%, 4.89%, 5.70%, and 3.87%, respectively.

关键词： Time-frequency analysis Accuracy Fuses Event detection Feature extraction Time-domain analysis Bioinformatics

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Container-Based Lab-as-a-Service Application 1st

Container-Based Lab-as-a-Service Application

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1st international conference of IoT and its Applications, ICIA2020

作者： Thiruchadai Pandeeswari, S. Padmavathi, S. Sanjaybabu, M. Srilakshmi, S.S. Sabari Priya, K. Department of Information Technology Thiagarajar College of Engineering Tamil Nadu Madurai India

ISBN: (纸本)9789811676369

In most of the Indian engineering and science educational institutions, variety of courses on problem-solving through programming and computer-aided tools are taught. These courses often have theory and practical components. The practical components are conducted in dedicated laboratories equipped with necessary software and tools. students need to work in the respective labs to carry out the exercises. Lab setup with diverse requirements restricts the users to depend on the lab facility. In order to allow the users to access the lab environment beyond the working hours and eliminate the dependency on a particular lab facility, number of solutions leveraging virtualization and cloud services have been provided in the past. However, these approaches have few drawbacks. The virtual images are quite heavy. Though portable, it takes quite sometime to configure the virtual images. Similarly, cloud-based solutions may not be affordable for every institution and given the scale of usage, the cloud services may be expensive. In this paper, we propose a simple container-based solution for providing customized lab environments for the users. Containers are lightweight, portable, and easily configurable when compared to virtual image formats. The proposed container-based solution is presented to the users through a simple web portal that allows users to create required lab environment with few clicks. The container-based lab-as-a-service application presented in this paper incorporates necessary settings to save the changes made on the given image by the user and also allows the user to save and retrieve his customized image as and when required. The users do not require knowledge on Docker commands and do not require to use command-line interface for getting the lab setup ready using containers. The web portal’s UI allows the user to create lab environments without having to worry about the intricacies of tools required for the lab setup and containers. The proposed solution

关键词： Containers

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On Solving the Physicians Scheduling Problem at an Emergency Department: A Case study from Canada 1st

On Solving the Physicians Scheduling Problem at an Emergency...

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1st international conference on Optimization and Data science in Industrial engineering, ODSIE 2023

作者： Yakoubi, Ghada Ahabchane, Chahid Layeb, Safa Bhar LR-OASIS National Engineering School of Tunis University of Tunis El Manar Tunis Tunisia University of Quebec in Abitibi-Temiscamingue Rouyn-NorandaQC Canada Centre Génie Industriel Université Toulouse IMT Mines Albi Albi France

ISBN: (纸本)9783031814549

Emergency departments play a pivotal role in healthcare delivery since they represent the first line in hospitals to face emergency patients. This department is where medical care is provided to patients whose arrival rate is uncertain and a high fluctuation in the daily requirements is presented. Yet, managing its human resources efficiently is imperative to improve the quality of its services and provide the right treatments at the right time. This work aims to establish a schedule for physicians in emergency departments which represents a challenging task as it requires respecting several rules incorporating diverse aspects. The objective of this study is to allocate workdays and shifts to emergency department physicians to align physicians’ productivity with patients’ demands, without decreasing physicians’ preferences, to maximize the number of patients treated at the emergency department. Taking into consideration the stochastic and time-varying patients’ demand, we presented a mathematical programming approach that determines feasible physicians’ schedules respecting the emergency department’s hard requirements, minimizing patients’ coverage violations, along with the violation of physicians’ preferences. A real-life case study was carried out in a public Hospital in Quebec, Canada. Different scenarios were then created to study the effect of each goal on the problem. Afterward, we applied a meta-heuristic solution approach belonging to the iterative evolutionary algorithms with several feature configurations to solve the physicians scheduling problem. The results obtained from the computational study of the several scenarios were discussed as a function of the degree of satisfaction of the goals under which the system operates allowing to conclude the best scenario that generates a one-month schedule respecting all goals without deterioration. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： stochastic systems

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Design and Implementation of Roof Top Solar Panel Cleaner Robot Using IoT 1

Design and Implementation of Roof Top Solar Panel Cleaner Ro...

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1st international conference on Advances in Computational science and engineering, ICACSE 2020

作者： Hema, L.K. Dwibedi, Rajat Kumar Ashwin Kumar, J. Raj, Pulkit Shanmugavel, M. Department of Electronics and Communication Engineering AarupadaiVeedu Institute of Technology Vinayaka Mission's Research Foundation Tamilnadu Paiyanoor India

Fuel is one of the main challenges which the world faces in current situation;water shortage for urban and rural households has been one of the major problems too. Fuel wood and crop residues meet about 60 to 70 percent of the country's electricity demand. Solar energy is a green energy source with an immense potential & light from the sun. The use of electric energy generated by petroleum is important for renewable energy. Solar energy has become a clean energy option and the deployment of solar energy needs to be strengthened. For dusty climates, tropical nations such as India typically use Solar PV panels. On the front side of the frame the dust accumulates and filters the light from the sun. It reduces the ability of the module to produce electricity. If the device is not cleaned for one month, the power output is reduced by 50%. The cleaning device cleans the module via the PIC programming interface. To eliminate the dust in the panel for energy efficiency enhancement. © Published under licence by IOP Publishing Ltd.

关键词： Solar energy

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Job-scheduling Model For an Autonomous Additive Manufacturing: a Case of 3D Food Printing 4

Job-scheduling Model For an Autonomous Additive Manufacturin...

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4th international conference on Industry 4.0 and Smart Manufacturing, ISM 2022

作者： Alghamdy, Mohammed Almutairi, Faisal M. Ahmad, Rafiq Laboratory of Intelligent Manufacturing Design and Automation Department of Mechanical Engineering University of Alberta 9211 116 Street NW EdmontonABT6G 1H9 Canada Epsilon Data Management LLC. Connection Dr IrvingTX75039 United States

Three-dimensional food printing (3DFP) is an emerging application of additive manufacturing (AM) as it offers customized designs, personalized nutrition, simplified and efficient supply chain, and reduced waste. Grouping parts into jobs (batches) and sequencing these jobs (known as job-scheduling) is considered a key operational factor in additive manufacturing (AM). The task of job-scheduling is complex because the number of possible solutions grows exponentially with the number of parts and various constraints has to be considered (e.g., machine's capacity). In the case of 3DFP, scheduling presents a unique challenge since different 3D printed foods have different time constraints depending on material's shelf-life. In this paper, we propose a mathematical optimization model for job-scheduling in 3DFP that minimizes the makespan (total accumulative manufacturing time) and the deadline violation simultaneously. We reformulate the proposed optimization model to the form of mixed-integer linear programming (MILP) and solve in using MILP solver in MATLAB 2022. We demonstrate the effectiveness of the proposed model with a numerical case study. The obtained results show that our algorithm obtains scheduling that significantly reduces the deadline violation while achieving the same production time as the state-of-the-art baseline. © 2022 The Authors. Published by ELSEVIER B.V.

关键词： 3D printing

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Respiratory Sound Classification Based on Swin Transformer

Respiratory Sound Classification Based on Swin Transformer

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IEEE international conference on Signal and Image Processing (ICSIP)

作者： Weiwei Sun Fan Zhang Ping Sun Qishi Hu Jianhong Wang Minghui Zhang Department of Electronic Information Engineering Nanchang University Nanchang China 1st Affiliated Hospital of Nanchang University Nanchang University Nanchang China

Various deep learning (DL) techniques have found application in the respiratory sound classification to effectively alleviate the diagnostic pressure of physicians. However, DL-based respiratory sound classification methods are mostly based on convolutional neural networks (CNN). Due to the inherent locality of convolution operations, CNN generally extracts only local features of 2D spectrogram representations. A respiratory sound has wide frequency bands and long time spans. It is important to obtain both global and local information. To address this problem, we propose a novel Swin Transformer network for respiratory sound classification. Experimental results on the ICBHI2017 dataset demonstrate that the proposed model achieves 77.3% specificity, 41.1% sensitivity, 59.2% ICBHI score and outperforms the state-of-the-art methods.

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A Highly Efficient Intrusion Detection and Packet Tracking Based on Game Theory Approach 1

A Highly Efficient Intrusion Detection and Packet Tracking B...

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1st IEEE international conference on Emerging Trends in Industry 4.0, ETI 4.0 2021

作者： Sadineni, Giribabu Archana, M. Tanguturi, Rama Chaithanya Annamalai University Department of Computer Science and Engineering Tamil Nadu India PACE Institute of Technology and Sciences Department of Computer Science and Engineering Andhra Pradesh India

ISBN: (纸本)9781665422376

Wireless Sensing Networks (WSNs) offer excellent environmental monitoring capabilities and use many interesting applications in advanced network applications. The problem is that the security mechanisms used in wired networks cannot be incorporated directly in WSN due to scarce resources. In this paper, specific measures that need to be taken against across distributed wireless networks, explore some of the approaches to detect attacks, and propose a new game theory-approach in identifying the intrusion detection. Two key elements which are most challenging in mobile and wireless networks, the geo-location of the nodes will change dynamically and security between the nodes is limited and monitoring packet transmission in order to avoid various intrusion methods involved between the nodes and data transmission has to be secured with a guarding mechanism. This paper implements about how to provide advanced authentication schemes for network programming to avoid and reduce intrusion and precautionary measures to be considered in avoiding intrusion detection in advantage of vulnerabilities and attack network and causes failure. The results show that implemented research on sensor network security focuses on the ability to detect third-party intrusion attempts, even if they are attempts to attack even before it has happened If the intruder is detected quickly, appropriate action is taken before any damage occurs or if any data is available made a compromise. © 2021 IEEE.

关键词： Game theory

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Applying a Competency-Based Education Approach for Designing a Unique Interdisciplinary Graduate Program: A Case study for a Systems engineering Program

Applying a Competency-Based Education Approach for Designing...

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2023 ASEE Annual conference and Exposition - The Harbor of engineering: Education for 130 Years, ASEE 2023

作者： Thompson, Amy stuber, Matthew D. Han, Song Dutta, Abhishek Xu, Hongyi Zhou, Shengli Yang, Qian Miao, Fei Bollas, George M. University of Connecticut United States

starting in 2020, ten faculty members of the University of Connecticut's (UConn) Master of engineering program in Advanced Systems engineering applied four existing competency frameworks to define the unique aspects of their professional training program using a competency-based education approach. The four frameworks include the 21st Century Cyber-Physical Systems Education report published by the National Academies Press, the Applied Mathematics at the U.S. Department of Energy report published by Lawrence Livermore National Laboratory, the INCOSE (international Council on Systems engineering) Systems engineering Competency Framework, and the INCOSE Model-Based Enterprise Capabilities Matrix. The purpose of the use of these frameworks and reports was to identify generally desirable competencies that a professional should acquire when training at the graduate level in systems engineering for the development of complex CPS. The competency-based education process included a mapping of previously defined student learning outcomes to competencies defined in the frameworks. This paper explains the systems engineering education program background, competency-based education initiative goals, methods, process, and results. The paper concludes that a tailored approach to graduate education programming, based upon this competency-based education and course assessment method, can be used to differentiate graduate systems engineering programs from each other. The paper also concludes that customized learning, targeting specific systems engineering skillsets, can be achieved by each systems engineering student based upon offering an open and customizable course curriculum. students can use their competency-based learning plans and social-media-recognizable badges to signify their unique systems engineering competencies and learning outcomes achieved either through a four-course Graduate Certificate or a ten-course Master of engineering program offered by UConn. The competency

关键词： Cyber Physical System

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A Data Centre Configurable Data Mining Document Management Information System 1

A Data Centre Configurable Data Mining Document Management I...

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1st international conference on Advances in Computational science and engineering, ICACSE 2020

作者： Gurusubramani, S. Mouleeswaran, S.K. Srinivas, Porandla Aruna, R. Department of Computer Science and Engineering Sri Sairam Engineering College Tamil Nadu Chennai India Department of Computer Science and Engineering Dayananda Sagar University Karnataka Bangalore India Department of Information Technology Malla Reddy Institute of Engineering and Technology Telangana Secunderabad India Department of Computer Science and Engineering Vel Tech Rangaraj Dr.Sagunthala RandD Institute of Science and Technology Tamil Nadu Chennai India

Data extraction is often a dynamic process that can be easily modelled as a workflow for data processing. When massive collections of data have to be evaluated and/or sophisticated data mining algorithms have to be performed, it can take very long to execute data analysis workflows. Effective technologies are also needed to incorporate flexible data collection workflows through the use of cloud-based storage platforms, where data is stored even more regularly. The paper attempts to show how cloud infrastructure is implemented to introduce an optimised framework in which scalable data analyzation workflows can be planned and performed. We explain how the Data Mining Cloud Architecture is built and applied and a data analytics method that incorporates visual workflow vocabulary, parallel to the Virtualized environment. DMCF is developed with a view to simplifying the creation of applications for data mining associated with generic system monitoring schemes that are not created especially for this area, in view of the specifications of actual data mining applications. The effects are a high-level environment that minimises the programming effort with an optimised visual workflow language, allowing the implementation of typical patterns meant to generate and execute data mining application in parallel simple to professional developers. The wall mounted of the workflow, device design and mechanisms of the DMCF are shown. We also address many DMCF-developed data mining business processes and the scalability achieved by running business processes in a cloud environment. © Published under licence by IOP Publishing Ltd.

关键词： Data mining

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An Intelligent Waste Disposal System for Hygienic Society

An Intelligent Waste Disposal System for Hygienic Society

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international conference on Computational science and Technology (ICCst)

作者： G. Puthilibai Deepashri R. Jeyashri R. Devatarika V. Arvind Adithya N. Anurega T.R Department of Chemistry Sri Sairam Engineering College Chennai India Department of EEE Thiagarajar College of Engineering Madurai India Department of EEE Sri Sairam Engineering College Chennai India Bachelor of Medicine and Bachelor of Surgery Muthukumaran Medical College Hospital & Research Institute Chennai India Department of Information Technology Sri Sairam Engineering College Chennai India

ISBN: (纸本)9781665476560

In this overpopulated world, the quantity of garbage generated increases day by day. It is one of the crucial and significant issues faced by the corresponding residential people. Hence the process of waste management comes into play as it is essential to dispose the garbage in periodic manner. If the process is not carried out at stipulated time, it may cause public sanitary issues which consequently affects the health and hygiene of the society. Therefore, it is very much essential to handle the garbage disposal. Nowadays as we see, the garbage bins kept in the residential area overflows as it is not timely discarded. Our proposed system highly contributes to the safe and secure hygiene to the people. This paper describes an intelligent disposal system that employs ultrasonic sensor to detect the level of waste piled in the garbage bin and once it surpasses the threshold limit which we set, an alarm and intimation are issued to alert the municipal authorities. The bin is designed to open when user arrives to throw away the domestic waste. The intelligent bin also provides an opportunity to dispose the waste only into the garbage bin and if any user throws the bin, it is intimated to the use through alarm. The system is built using Deep learning algorithm for ultrasonic sensor to classify whether it is a user came near or it is the garbage thrown outside the bin. As the ultrasonic sensor which we fixed outside detects the presence of user as well as the presence of waste. Hence in order to classify them, we incorporated Deep Learning algorithm using MATLAB which makes the system as an intelligent system and work with increased efficiency.

关键词： Deep learning Codes Scientific computing programming Acoustics Classification algorithms Waste disposal

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