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Towards an integration management maturity 49

Towards an integration management maturity

引用

49th Euromicro Conference on Software engineering and Advanced Applications, SEAA 2023

作者： Hyrynsalmi, Sonja M. Olsson, Helena Holmstrom Bosch, Jan Lut University Dept. Software Engineering Lahti Finland Malmö University Dept. Computer Science and Media Technology Malmö Sweden Chalmers University of Technology Dept. Computer Science and Engineering Göteborg Sweden

ISBN: (纸本)9798350342352

As industries continue to digitize at a rapid pace, the number of integrations, the connections between different digital systems, is increasing. As a consequence, integration management is becoming increasingly difficult, leading to scalability, stability, and system outage problems that directly affect company performance. For that reason the modern integration management platforms have emerged to offer efficient management of the growing number of integrations, as well as a new way to handle, enrich, and utilize data both inside and outside *** research involved interviews with 20 software vendor professionals and 20 clients who had recently undergone an integration platform project. The study identified key drivers behind integration management projects and recognized different maturity levels in integration management. The results revealed that more mature companies are utilizing modern integration platforms to support their digital transformation. The study also highlighted the growing importance of data management and utilization in integration *** address these findings, a maturity model was developed to help companies evaluate their current integration management status and find ways to progress in their integration management. © 2023 IEEE.

关键词： Integration

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AttRes-UNet: A Dual-Model Approach for Brain Tumor Segmentation 4

AttRes-UNet: A Dual-Model Approach for Brain Tumor Segmentat...

引用

4th International Conference on Advancement in Electronics and Communication engineering, AECE 2024

作者： Kolekar, Samruddhi Maheshkumar Yadav, Agnesh Chandra Yadav, Suchita Dash, Daba Prasad Thaper Institue of Engineering and Technology Dept. Electrical Engineering Patiala India India Instite of Technology Patna Dept. Electrical Engineering Patna India Bennett University Dept. of Computer Science and Engineering Gr. Noida India

ISBN: (纸本)9798350364729

Accurate segmentation of brain tumors in MRI images is crucial for diagnosis, treatment planning, and disease monitoring. Traditional manual segmentation methods are time- consuming and prone to variability, while standard deep learning architectures such as U-Net face challenges in capturing the complex, heterogeneous structures of brain tumors. In this study, we proposed AttRes-UNet, a novel dual-model architecture combining Attention U-Net and Residual U-Net to enhance segmentation accuracy. Attention Gates allow the model to focus on critical tumor regions, while Residual Blocks improve deep feature learning, enabling the model to handle diverse tumor morphologies with greater precision. We evaluated the model using the BraTS 2021 dataset, achieving high performance with an accuracy of 0.996, a dice coefficient of 0.8340, and an Intersection over Union of 0.8210. These results demonstrate the effectiveness of AttRes-UNet in improving segmentation accuracy, making it a valuable tool for automated brain tumor delineation, ultimately reducing manual workload and improving clinical outcomes. © 2024 IEEE.

关键词： Magnetic resonance imaging

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Enhanced Driver Stress Prediction from Multiple Biosignals via CNN Encoder-Decoder Model 46

Enhanced Driver Stress Prediction from Multiple Biosignals v...

引用

46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Singh Roha, Vishal Gaber Gendy, Maggie Ezzat Pavan, Kaveti Deserno, Thomas M. Ganapathy, Nagarajan Yuce, Mehmet R. Monash University Dept. of Electrical & Computer Systems Melbourne Australia Indian Institute of Technology Hyderabad Dept. of Biomedical Engineering Hyderabad India Technical University of Braunschweig Plri Lab for Medical Informatics Brunswick Germany

ISBN: (纸本)9798350371499

In this work, we present PhysioFuseNet, a novel framework designed to enhance driver stress state classification. PhysioFuseNet integrates a CNN-based encoder-decoder model with multimodal biosignal fusion. Using a driving simulator, different multimodal signals were acquired, namely electrocardiography, electrodermal activity, photoplethysmography, and respiration rate from (N = 25) healthy subjects. The experiment is of 35 minutes duration and contains different stress states (baseline (5 minutes), while normal, cognitive, and emotional sessions for 10 minutes). Multimodal features are extracted and employed in an encoder-decoder network. Extracted encoder features are combined through intermediate fusion and fed to support vector machine (SVM) and random forest (RF) classifiers. Experimental results demonstrate the efficacy of our approach, outperforming previous methods by achieving accuracies of 0.95 and 0.94 for SVM and RF, respectively. Notably, the framework excels in classifying emotional and cognitive stress states. In summary, the proposed framework could be useful in stress assessment in real-time and clinical conditions. © 2024 IEEE.

关键词： Photoplethysmography

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Dynamic Checkpointing: Fault Tolerance in High-Performance Computing 3

Dynamic Checkpointing: Fault Tolerance in High-Performance C...

引用

3rd International Conference on Communication, Control, and Intelligent Systems, CCIS 2024

作者： Bhowmik, Biswajit Verma, Tushar Dineshbhai, Navdeep Dadhania Reddy, Manideep Raya Vsrs Girish, K.K. National Institute of Technology Karnataka Maharshi Sushrut Cas Lab Brics Laboratory Dept. of Computer Science and Engineering Mangalore India National Institute of Technology Karnataka Maharshi Kanad Qc Lab Brics Laboratory Dept. of Computer Science and Engineering Mangalore India National Institute of Technology Karnataka Ishwarchandra Vidyasagar Ait Lab Brics Laboratory Dept. of Computer Science and Engineering Mangalore India

ISBN: (纸本)9798331528201

Parallel computing has become a cornerstone of modern computational systems, enabling the rapid processing of complex tasks by utilizing multiple processors simultaneously. However, the efficiency and reliability of these systems can be significantly compromised by inherent challenges such as hardware failures, communication delays, and uneven workload distribution. These issues not only slow down computations but also threaten the dependability of applications reliant on parallel processing. To address these challenges, researchers have developed strategies like dynamic checkpointing and load balancing, which are crucial for enhancing fault tolerance and optimizing performance. Dynamic checkpointing periodically saves the computational state, allowing for recovery from failures without significant data loss, while load balancing ensures that tasks are evenly distributed across processors, preventing bottlenecks and underutilization of resources. By integrating these mechanisms, this paper proposes a robust framework that improves the reliability and efficiency of parallel systems, particularly in high-performance computing environments where the ability to handle large-scale data processing with minimal downtime is critical. © 2024 IEEE.

关键词： Parallel processing systems

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Enhancing Deepfake Image Detection with Deep Convolutional Neural Networks

Enhancing Deepfake Image Detection with Deep Convolutional N...

引用

2023 Annual International Conference on Emerging Research Areas: International Conference on Intelligent Systems, AICERA/ICIS 2023

作者： Bhamare, Siddharth Bhamare, Shreeraj Watumull Institue of Technology Computer Engineering Dept. Ulhasnagar India School of Computer Engineering Coep Technological University Pune India

ISBN: (纸本)9798350303452

The availability of image editing software such as Adobe Photoshop or GIMP has made picture alteration so widespread these days. Finding these phony photos is a must for exposing image-based cyber crimes. Due to its ubiquity, images produced with a digital camera or smartphone are typically saved in the JPEG format. The 8×8 pixel-sized, independently compressed mage grids used by the JPEG technique are used. Images that haven't been altered have a comparable inaccuracy level. Due to a similar number of faults throughout the whole image, each block should degrade at roughly the same rate during resaving operations. Error Level Analysis was used to determine that the compression ratio of the false image was different from the actual images. © 2023 IEEE.

关键词： Image enhancement

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Exploratory Testing of Software Product Linesusing Distance Metrics

Exploratory Testing of Software Product Linesusing Distance ...

引用

2023 International Conference on Computational Intelligence and Sustainable engineering Solution, CISES 2023

作者： Saini, Ashish Kumar, Satendra Kumar, Raj Kumar, Mukesh Kumari, Amrita Quantum University Dept. of Computer Science and Engineering Roorkee India Moradabad Institute of Technology Dept. of Computer Science and Engineering Moradabad India Gurukula Kangri Deemed to Be University Dept. of Computer Science Haridwar India Quantum University Dept. of Mechanical Engineering Roorkee India

ISBN: (纸本)9798350323917

Quality is very important in any software product, so that the customer trusts the efficiency of the product. The quality or validity of a product is measured by its testing. The test measures the quality of a product as well as shows the validity of the product. For example, testing and measuring the validity of a product in a single software system is not easy. Similarly, the software product line, which produces many different products of the same family at once, makes it even more difficult to check their validity and quality. Several techniques and models have been proposed to test the validity of the software line products and to ascertain the quality. In the same direction, we also propose a method for testing the products of software product line. The proposed method isbased on the distance between the features of the product (Desired and Original). We have used the proposed technique on product line with less features and found that the method presented gives fast and better results than traditional methods. © 2023 IEEE.

关键词： Software testing

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Voltage Sag Investigation for Induction Motor Startup in Distribution Systems using Solid State Transformer 15

Voltage Sag Investigation for Induction Motor Startup in Dis...

引用

15th International Renewable Energy Congress, IREC 2025

作者： Ghambirlou, Khaled Abosnina, Adel Ali Moschopoulos, Gerry Western University Dept. Electrical and Computer Engineering London Canada College of Electrical and Electronics Technology Benghazi Libya

ISBN: (纸本)9798331516772

Dealing with voltage sags during motor startup is crucial because they can delay power restoration and lead to widespread failures for industrial loads and distribution systems. A novel approach is introduced to investigate voltage sag in distribution networks using solid-state transformers (SSTs) instead of traditional ones. The induction motor startup model is employed to simulate voltage sags, accurately representing the characteristics influenced by conventional industrial loads. The inherent capabilities of SSTs are leveraged to mitigate these voltage sag issues effectively. This study focuses on analyzing voltage sags caused by the activation of induction motors in power systems, with particular emphasis on SST technology, which actively regulates voltage during motor starting by controlling reactive power. The selected distribution system is implemented and tested using MATLAB/Simulink. The results will be compared with previous research on voltage sag during motor startup, demonstrating the improvements and effectiveness of using SSTs in managing power quality issues. This study emphasizes the potential of SSTs to improve the stability and reliability of power systems during the challenging conditions of motor startup. © 2025 IEEE.

关键词： Distribution transformers

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Steganalysis on Dual-Layer Security of Messages Using Steganography and Cryptography 15

Steganalysis on Dual-Layer Security of Messages Using Stegan...

引用

15th International Conference on Information technology and Electrical engineering, ICITEE 2023

作者： Shamsi, Zeba Saha, Anish Kumar Patgiri, Ripon Singh, Khoirom Motilal Singh, Laiphrakpam Dolendro National Institute of Technology Dept. of Computer Science and Engineering Assam Silchar788010 India Indian Institute of Information Technology Dept. of Computer Science and Engineering Manipur Senapati795002 India

ISBN: (纸本)9798350304466

Recently, Bansal et al. proposed a dual-layer message security technique using steganography and cryptography. An index table maps each text data to an index point and an elliptic curve point. The text data are encrypted using elliptic curve cryptography, and the corresponding index values are embedded in a cover image using the Least Significant Bit Inversion technique. The proposed paper breaks the security of the key exchange technique in the Bansal et al. method and the secret text is extracted. © 2023 IEEE.

关键词： Steganography

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Evaluating Machine Learning Methods for Bangla Text Emotion Analysis

Evaluating Machine Learning Methods for Bangla Text Emotion ...

引用

2024 Asia Pacific Conference on Innovation in technology, APCIT 2024

作者： Akter, Tahmina Akter, Mst. Sharmin Mahmud, Tanjim Islam, Dilshad Hossain, Mohammad Shahadat Andersson, Karl Port City International University Dept. of Computer Science and Engineering Chittagong Bangladesh Rangamati Science and Technology University Dept. of Computer Science and Engineering Rangamati4500 Bangladesh Chattogram Veterinary and Animal Sciences University Dept. of Physical and Mathematical Sciences Bangladesh University of Chittagong Dept. of Computer Science and Engineering Chittagong4331 Bangladesh Luleå University of Technology Cybersecurity Laboratory Luleå97187 Sweden

ISBN: (纸本)9798350361537

Text-based emotion identification goes beyond simple sentiment analysis by capturing emotions in a more nuanced way, akin to shades of gray rather than just positive or negative sentiments. This paper details our experiments with emotion analysis on Bangla text. We collected a corpus of user comments from various social media groups discussing socioeconomic and political topics to identify six emotions: sadness, disgust, surprise, fear, anger, and joy. We evaluated the performance of four widely used machine learning algorithms - RF, DT, k-NN, and SVM - alongside three popular deep learning algorithms - CNNs, LSTM, and Transformer Learning - using TF-IDF feature extraction and word embedding techniques. The results showed that among the machine learning algorithms, DT, RF, k-NN, and SVM achieved accuracy scores of 82%, 84%, 73%, and 83%, respectively. In contrast, the deep learning models CNN and LSTM both achieved higher performance with an accuracy of 85% and 86% respectively. These findings highlight the effectiveness of traditional ML and DL approaches in detecting emotions from Bangla social media texts, indicating significant potential for further advancements in this area. © 2024 IEEE.

关键词： Contrastive Learning

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Traffic Volume Prediction Based on Weather Parameters 2

Traffic Volume Prediction Based on Weather Parameters

引用

2nd IEEE International Conference for Women in Innovation, technology and Entrepreneurship, ICWITE 2024

作者： Kendre, Harshvardhan Karmarkar, Mandar Karadbhajne, Harsh Kamtalwar, Neha Marathe, Abha Vishwakarma Institute of Technology Computer Engineering Department Pune India Vishwakarma Institute of Technology Dept. of e & Tc Engineering Pune India

ISBN: (纸本)9798350383287

With increase in number of vehicles, traffic congestion is on rise. It leads to a multitude of problems in urban areas. Commuters experience unpredictable travel times, resulting in delays, stress, and inefficiency. Inadequate planning and resource allocation hinder traffic management efforts, leading to congestion, increased accident risks, and reduced overall transportation system performance. A way to deal with these problems is predicting the flow of traffic and understanding patterns according to different urban areas. Existing research on traffic volume prediction has predominantly overlooked the influence of weather parameters, despite their potential impact. This paper fills this research gap by focusing on the integration of weather parameters into traffic volume prediction models and shedding light on the relationship among weather and traffic dynamics. The prediction algorithms employed in our study include Decision Trees, XGboost, Support Vector Machine and Random Forest are compared using prediction parameters including Mean Squared Error, Mean Absolute Error, Root Mean Squared Error, and R-square. After analyzing each Algorithm, the SVM algorithm arrives to be the best fit for predicting traffic volume on weather conditions. © 2024 IEEE.

关键词： Traffic congestion

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