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Computational Data Analysis, Prediction and Forecast of Health Disaster: A Machine Learning Approach 8

Computational Data Analysis, Prediction and Forecast of Heal...

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8th international conference on Smart Structures and systems, ICSSS 2022

作者： Sivaranjani, Govindarajan Gopirajan, P.V. Gowdham, C. Abitha, A. Ravindhar, N.V. Saveetha University Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Sustainable Engineering Chennai India Department of Computer Science and Engineering Chennai India Hindustan Institute of Technology and Science Department of Computer Science and Engineering Chennai India Karpaga Vinayga College of Engineering and Technology Department of Electronics and Communication Engineering Tamil Nadu India

ISBN: (纸本)9781665497619

Objective of this study is to analyse the effectiveness of social distancing in reducing the risk of COVID-19, taking Spain as an example. Also, to study the influence of advanced enforcement of social distancing in Spain against the actual date of 14th March 2020. Computational models were developed (with Python programming) using data collected by web crawling using RCrawl using R-programming. the model predicted total cases and total deaths under the given conditions of advanced social distancing in 6 previous dates. Also, this model made a forecast of total cases and total deaths for the month of May. Results suggested that by 15th May 2020, the total cases may reach 337672. If the lockdown was imposed 6 days earlier the cases would be a mere 43083 only. Also, the total deaths will be reduced 82% effectively if the lockdown was imposed 6 days earlier. It can be concluded from the results, that enforcement of social distancing at the earlier stage of any pandemic disease spread is the only effective way to reduce the risk and contain the disaster. © 2022 IEEE.

关键词： COVID-19 Analytical models Pandemics Computational modeling Human factors Predictive models Market research

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A Distributed Secondary Control for Autonomous AC Microgrid Based on Photovoltaic and Energy Storage systems 14th

A Distributed Secondary Control for Autonomous AC Microgrid ...

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14th international conference of the IMACS TC1 Committee, ELECTRIMACS 2022

作者： Ouoba, Sidlawendé V. M. Houari, Azeddine Machmoum, Mohamed IREENA – Nantes Université Saint Nazaire France

ISBN: (纸本)9783031248368

In this paper, a distributed control is proposed for Distributed Energy Storage systems (DESSs) and Renewable Energy Sources (RESs) power management in islanded Microgrid (MG). the power management strategy is designed to maintain generation/consumption balance, to ensure State of Charge (SoC) balancing of the DESSs and MG frequency/voltage (f & V) regulation. A fully distributed control without leader-follower strategy is used to manage the power flow between renewable generators, energy storage and consumption (critical and non-critical loads), to balance the SoC of the DESSs and to restore the frequency and voltage to their nominal value only thanks to low bandwidth communication. the strategy framework of the power management set the islanded MG in 04 operations modes (normal mode, PV active power curtailment mode and load shedding and reconnection mode) in order to provide a high quality and reliable power source in the islanded MG. A MATLAB/Simulink simulation is performed with a system of two Batteries Energy Storage systems (BESSs), three loads (a critical/variable load and two non-critical/constant loads) and photovoltaic (PV) generator, in order to verify the effectiveness and the resilience of the proposed power management method in several operation modes. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Electric load flow

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Quality Analysis of Preprocessing Techniques for De-noising and Enhancement of Fundus Images to Detect Diabetic Retinopathy 15th

Quality Analysis of Preprocessing Techniques for De-noising ...

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15th international conference on Soft Computing and Pattern Recognition, SoCPaR 2023 and 14th World Congress on Nature and Biologically Inspired Computing, NaBIC 2023

作者： thomas, Neetha Merin Jerome, S. Albert Department of Electronics and Communication Engineering Noorul Islam Centre for Higher Education Tamil Nadu Kumaracoil India Department of Biomedical Engineering Noorul Islam Centre for Higher Education Tamil Nadu Kumaracoil India

ISBN: (纸本)9783031810794

Image preprocessing involves improving image quality by removing irrelevant image data, making images suitable for various applications. Diabetes is a global condition that can cause noticeable microvascular complications in the retinal eye, such as diabetic retinopathy and macular edema, significant causes of worldwide vision loss. Retinal fundus images are commonly used in clinics for recognizing and evaluating diabetic retinopathy (DR). Raw medical images often contain irrelevant and undesired elements that can lead to inaccurate results. To eliminate these unwanted components, appropriate preprocessing techniques should be applied to enhance perception before specifically identifying infections. this study introduces an algorithm designed for the enhancement of fundus images by addressing noise removal and contrast enhancement. By combining various filters and employing Contrast Limited Adaptive Histogram Equalization (CLAHE), the algorithm aims to effectively address these issues in color fundus images. the evaluation of the proposed method’s effectiveness is carried out using diverse performance parameters such as Peak Signal to Noise Ratio (PSNR), Mean Absolute Error (MAE), Mean Square Error (MSE), and Structural Similarity Index Measure (SSIM). the method proposed showed improvement in PSNR when a combination of filters was used. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Image denoising

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An Implementation of Job Running Backup Function in User-PC Computing System 4

An Implementation of Job Running Backup Function in User-PC ...

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4th international conference on Computer communication and the Internet, ICCCI 2022

作者： Htet, Hein Funabiki, Nobuo Kamoyedji, Ariel Zhou, Xudong Xiang, Xu Sugawara, Shinji Kao, Wen-Chung Okayama University Department of Information and Communication Systems Okayama Japan Chiba Institute of Technology Department of Information and Communication Systems Narashino Japan National Taiwan Normal University Department of Electrical Engineering Taipei Taiwan

ISBN: (数字)9781665469920

ISBN: (纸本)9781665469920

As a low-cost and high-performance distributed computing platform, we have studied the User-PC Computing (UPC) system based on the master-worker model. Docker container technology is adopted to run various application programs or jobs on heterogeneous PC environments for workers. Some jobs, such as physics simulations and neural networks, require long CPU time, which increases the probability of failure of running workers. the automatic backup of the job running state and migration to other worker will be essential to reduce the job completion delay. In this paper, we implement the job running backup function in the UPC system. Checkpoint-Restore in Userspace (CRIU) is periodically applied to capture the job running state of the running job at a worker. When the master detects the failure, it automatically migrates the job to another worker. To evaluate the function, we conducted experiments using the testbed UPC system with 14 jobs and six workers of different specifications, and confirmed that the proposal successfully resumes the job running from the interrupted point at another worker. © 2022 IEEE.

关键词： Application programs

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TISSA: A Web-based Helpdesk Support System for Tertiary Institutions with Knowledge-based Management and Ticket Forecasting using Time Series Methods 14

TISSA: A Web-based Helpdesk Support System for Tertiary Inst...

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14th IEEE international conference on Humanoid, Nanotechnology, Information Technology, communication and Control, Environment, and Management, HNICEM 2022

作者： Alcober, Geliza Marie I. Rubio, Alexis John M. Lazaro, Joan P. Mangaba, Joel B. Balmeo, Henry Dyke A. Revano, Teodoro F. FEU - Institute of Technology College of Computer Studies and Multimedia Arts P. Paredes St. Sampaloc Manila Philippines University of the East College of Computer Studies and Systems 2219 C.M. Recto Avenue Brgy. 404 Zone 41 Sampaloc Manila Philippines

ISBN: (纸本)9781665464932

this project aims to aid students, teachers, and even non-teaching staff in terms of managing technological inquiries and maintaining communication to perform academic-related transactions by developing Tissa - a web-based helpdesk support system for tertiary institutions that integrates various time series analysis techniques in forecasting the estimated number of tickets to be filed by the stakeholders based on historical records. Specifically, it explores the effects of developing a dedicated ticket management system that incorporates both analytics and enhanced user experience to the users' satisfaction, especially in a tertiary school setting. A total of 62 respondents were selected through purposive sampling. these respondents helped in evaluating the system's overall quality based on the ISO/IEC 25010 software quality model. the respondents' evaluation of the system's overall quality received an above-average score which means that the system passed the testing in terms of system requirements. the results gathered also suggest that 95.2% of the respondents agree that the inclusion of data visualization serves as valuable insights in performing strategic business decisions. Additionally, the system's user experience evaluation received the highest mean score of 4.82. the results for exponential smoothing yielded an 88% accuracy, linear regression was 80% accurate, simple moving techniques had an 85% accuracy rate, and 84% for the weighted moving average, which suggest that techniques used in this study can be considered reliable for future references. © 2022 IEEE.

关键词： Forecasting

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Multimodal Medical Image Registration Using Constraint Least Squares 15th

Multimodal Medical Image Registration Using Constraint Least...

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15th international conference on Soft Computing and Pattern Recognition, SoCPaR 2023 and 14th World Congress on Nature and Biologically Inspired Computing, NaBIC 2023

作者： Nagarathna, P. Jeelani, Azra Tirumala Vasu, G. Fiza, Samreen Kubra, Afreen Department of Computer Science and Engineering Nitte Meenakshi Institute of Technology Karnataka Bengaluru560064 India Department of Electronics and Communication Engineering Presidency University Karnataka Bangalore560064 India

ISBN: (纸本)9783031810794

Multimodal image registration finds widespread use in medical image analysis because of its usefulness in bringing together seemingly disparate sets of information from several imaging modalities. the major issue associated with image registration is that an algorithm works efficiently only for a given modality. In order to tackle this issue, we have proposed a novel multimodal image registration algorithm using Constrained Least Squares (CLS) that works for multiple medical modalities. the entire procedure of registration is based on the stipulation that the source and template images do not differ in zoom level but do differ in rotation and translation effects in the complex domain. To reduce the impact of noise and other inhomogeneities, a weight matrix is developed using prior knowledge of the local properties in the images. the least squares method is used to select the closed form solution to register the transformed image by estimating the displacement and rotation parameters. Many medical image registration algorithms have the limitation of quantitative analysis which we have addressed through Information Ratio (IR), Mutual Information Ratio (MIR), Lower bound Information Ratio (LIR), and Lower bound Mutual Information Ratio (LMIR). © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Image correlation

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Improved IQ imbalance compensation algorithm in faster-than-Nyquist coherent optical communication systems 14

Improved IQ imbalance compensation algorithm in faster-than-...

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14th international conference on Information Optics and Photonics, CIOP 2023

作者： Yang, Tao Zhao, Jing Cao, Fengyu Xia, Gaizun Yao, Naixin Liu, Liman Beijing100876 China Future Network Research Department China Unicom Research Institution Beijing100048 China School of Information and Communication Engineering BUPT Beijing100876 China

ISBN: (纸本)9781510671744

In order to solve the problem that the severe inter-symbol interference (ISI) introduced by faster-than-Nyquist (FTN) strong filtering leads to the degradation of the equalization capability of the traditional receiver side (Rx) IQ imbalance compensation, a two-stage Rx IQ imbalance compensation algorithm is designed and demonstrated in this paper. the algorithm uses a time domain equalizer based on the decision directed-least mean square (DD-LMS) algorithm cascaded with a 4×2 frequency domain (FD) equalizer based on the radius directed equalization (RDE) algorithm, which can effectively improve the compensation range compared to using only a conventional 4×2 FD equalizer based on the RDE algorithm. 128Gbaud-FTN-PM-16QAM system simulation results show that with an acceleration factor as low as 0.85, the designed algorithm has a 14.3%, 100% and 40% improvement in the compensation range of Rx IQ amplitude, phase and skew imbalance compared to using only the 4×2 FD equalizer based on the RDE algorithm. the results validate the performance improvement of the proposed algorithm. © 2023 SPIE.

关键词： Frequency domain analysis

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A Framework for Recommending Products to Solve Cold Starts Problem Using FP Growth Algorithm 15th

A Framework for Recommending Products to Solve Cold Starts P...

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15th international conference on Soft Computing and Pattern Recognition, SoCPaR 2023 and 14th World Congress on Nature and Biologically Inspired Computing, NaBIC 2023

作者： Dani, Virendra Bhati, Nisha Nagar, Sneha Mandloi, Ayesha Matkar, Mayank Department of Computer Science and Engineering Shri Vaishnav Vidyapeeth Vishwavidyalaya Indore India Department of Computer Science and Engineering Medicaps University Indore India Department of Electronics and Communication Engineering Indore Institute of Science & Technology Indore India Department of Computer Science and Engineering SKITM-Technical Campus Indore India

ISBN: (纸本)9783031889912

Different product characteristics and consumer expectations must be analyzed when making a product or service recommendation based on use. However, if all types of knowledge are inaccessible, this is known as the clod start problem in a recommendation system. To explain and address the issue of cold start, this paper suggests a structure for user experience-based product recommendation. As a result, this paper introduces a four-phase recommendation scheme. In the first step, site usage data is preprocessed and used to make product recommendations. the frequent pattern-based recommendation is performed in the next step. the decision is made in the third process based on the user's current search (user click streams) and related user habits seen in network access logs. In addition, the final recommendation is based on filtering the results obtained in the third step, as well as the product or service's cost, brand, and social review. the results show that the prediction is accurate and precise. Furthermore, compared result of proposed system to traditional system using Apriori Algorithm. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Apriori cold start problem Data Mining frequent pattern k-NN Prediction Recommendation System Web Log

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AI-driven Real-time System for Land Surveillance and Reconnaissance 2022

AI-driven Real-time System for Land Surveillance and Reconna...

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14th international conference on Contemporary Computing, IC3 2022

作者： Shahnoor, Shaikh F. Suthar, Kishanlal Kumar, Ravi Rathore, Manish Biradar, Rajashekhar C. Cholachgudda, Kartik School of Electronics and Communication Engineering Reva University Bengaluru India

ISBN: (纸本)9781450396752

Detection of threat elements during dangerous land missions such as rescue operations, bomb disposal, surveillance and reconnaissance using an unmanned ground vehicle (UGV) plays a significant role in technological warfare. Accurate and rapid detection of enemy arsenal and threats can help better plan and deploy military armaments while greatly reducing human casualty and economic losses. Unmanned ground systems with good maneuverability, superior wireless communication, and powerful multi-sensor and data processing capabilities can significantly advantage over the enemies. One of the key data processing tasks, i.e., land-warfare threat detection, is developed and tested in this paper. the goal is to identify and differentiate between threats in a warfare scenario. Four such threats have been defined and used to develop the detection algorithm for the study: soldiers, tanks, tents, and helicopters. Different object detection algorithms (ODAs) such as Single Shot Detector (SSD), CenterNet and Faster R-CNN based on pre-trained Convolutional Neural networks were tested and compared. COCO evaluation metrics were used as performance parameters to evaluate each detection algorithm on the different threats selected. the results show that CenterNet ODA performs better in evaluation and inference when compared to other ODAs, obtaining the highest mean Average Precision of 85.89% and 93.75%, respectively, at 0.5 IoU with Resent101 V1 CNN architecture. the best trade-off between all performance parameters was obtained again using CenterNet Resent101 V1 FPN. the inference was tested on a Raspberry Pi-based UGV streamed data. It was concluded that such systems have a key role in future warfare with a strong communication system and a lighter version of ODA. Further, researchers and engineers can use the work achieved in this paper to develop robust detection and data processing models and incorporate it into various applications and domains. © 2022 ACM.

关键词： Real time systems

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Observation Interval Analysis for Faster-than-Nyquist Signals Coherent Detection with Decision Feedback 21st

Observation Interval Analysis for Faster-Than-Nyquist Signal...

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21st international conference on Next Generation Teletraffic and Wired/Wireless Advanced networks and systems, NEW2AN 2021 and 14th conference on Internet of things and Smart Spaces, ruSMART 2021

作者： Lavrenyuk, Ilya Makarov, Sergey Xue, Wei Peter the Great St. Petersburg Polytechnic University St. Petersburg Russia College of Information and Communication Engineering Harbin Engineering University Harbin China

ISBN: (纸本)9783030977764

the method of transmitting signals above the Nyquist limit seems to be promising in terms of increasing bandwidth efficiency, but its practical application is limited by the complexity of the implementation of receiver devices, which should apply complex detection algorithms to eliminate the negative effect of intersymbol interference in the signal. In this paper, we consider a simple algorithm of elementwise detection with decision feedback and its modification, which makes it possible to increase the detection BER performance without increasing the computational complexity. the modification involves the optimization on observation interval to minimize the interference of subsequent signals during detection procedures. © 2022, Springer Nature Switzerland AG.

关键词： Intersymbol interference

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