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检索条件"任意字段=7th International Conference on Computing in Engineering and Technology, ICCET 2022"

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SpMV Algorithm Based on MPI+HIP Hybrid Model 7

SpMV Algorithm Based on MPI+HIP Hybrid Model

引用

7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Bo, Mengyu Liu, Yaqu Yue, Yuanyuan Shang, Jiandong Han, Pu Zhang, Yi Zhengzhou University School of Information Engineering Zhengzhou450000 China Zhengzhou University National Supercomputing Center in Zhengzhou Zhengzhou450000 China

ISBN: (纸本)9781665478571

SpMV(Sparse matrix-vector multiplication) plays an important role in the fields of scientific research and engineering, but its non-merged memory access and load imbalance cause worse performance when dealing with very large-scale sparse matrices. In view of the above problems, this paper proposes a SpMV algorithm of MPI+HIP hybrid model based on the DCU accelerator, which uses on-chip high-speed storage space at a fine-grained level to reduce the hidden access latency to global memory. through the warp reduction, the barriers of implicit synchronization and thread synchronization logic are reduced. the MPI is used at the coarse-grained level to partition the ultra-large-scale sparse matrix in behavioral units, and computational tasks are assigned to processes on the corresponding DCUs for accelerated processing. Experimental results show that, compared with the SpMV algorithm in the hipSPARSE library, the SpMV algorithm of the hybrid programming model achieves an increase of speedup from 4.34 to 6.44, which significantly improves the parallel efficiency. © 2022 IEEE.

关键词： Matrix algebra

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Implementation of One Data-based Lecturer Profile Information System for Key Performance Indicator Monitoring 7

Implementation of One Data-based Lecturer Profile Informatio...

引用

7th international conference on Informatics and computing, ICIC 2022

作者： Septama, Hery Dian Komarudin, Muhamad Wintoro, Puput Budi Pratama, Mahendra Yulianti, Titin Sulistiono, Wahyu Eko University of Lampung Department of Electrical Engineering and Infomatics Bandar Lampung Indonesia

ISBN: (纸本)9798350345711

the Key Performance Indicators (KPI) released by the Indonesian Ministry of Education, Culture, Research, and technology in 2021 are a new performance indicator for state universities that are concerned with output-based. It consists of 8 indicators that focus on the quality of university graduates, the quality of the lecturer, the quality of the curriculum, and learning. these papers focus on developing an integrated lecturer information profile with the university's one data database and the ministry's integrated human resource information system. the information focused on KPI 3 and KPI 4 to measure lecturer quality. the development process is presented using extreme programming (XP) methodology. the results show that all user stories are fulfilled and tested successfully. © 2022 IEEE.

关键词： Information systems

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Diagnosis of Pneumonia using Image Recognition Techniques 7

Diagnosis of Pneumonia using Image Recognition Techniques

引用

7th international conference on Intelligent computing and Control Systems, ICICCS 2023

作者： Sangeetha, S. Suruthika, S. Keerthika, S. Vinitha, S. Sugunadevi, M. Kongunadu College of Engineering and Technology Department of IT Tamil Nadu Trichy India

ISBN: (纸本)9798350397253

Pneumonia is a severe and fatal disease caused by viral or bacterial sepsis in human lungs. Early detection of pneumonia is critical for successful treatment. Deep learning algorithms that use many layers to interpret a boundary of data have obtained the best results in a variety of disciplines, particularly in the documenting and sorting of various diseases. As a result, there is an increasing need to design and develop a pneumonia detection system by using deep learning methods with an ability to evaluate chest CT-scan imageries and aid in the pneumonia exposure process. the proposed framework contains three phases: feature extraction, image classification, and image pre-processing. As a consequence, the projected Compared to other deep-learning models that have already been trained, such as (ResNet 50) and SVM, pneumonia diagnosis using the CNN model performed better in terms of accuracy and reliability. As a result, the efficient performance of the proposed Convolutional Neural Network centred pneumonia perception model in every parameter can provide valuable assistance to patients' care and reduce the human error rates. © 2023 IEEE.

关键词： Convolutional neural networks

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Comparative Analysis of Techniques for Big-data Performance Testing 7

Comparative Analysis of Techniques for Big-data Performance ...

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7th international conference on Parallel, Distributed and Grid computing, PDGC 2022

作者： Hasanpuri, Vijay Diwaker, Chander University Institute of Engineering and Technology Kurukshetra University Department of Computer Science and Engineering Kurukshetra India

ISBN: (纸本)9781665454018

Big data has become the primary objective for any area or department on the globe, including government, healthcare, and industrial sectors. Every day, a large amount of big data is generated, and information is added based on the three characteristics of big data. Handling massive amounts of data with traditional methods has become a significant challenge. To test large amount of duplicate data is very challenging task for researchers. Big data performance testing has great promise for obtaining more optimised solutions. Better performance saves time and money while also producing more optimised results. this paper makes an attempt to present several performance testing approaches. Furthermore, we compare the performance testing techniques and analyse the performance improvement factors. Finally, various tools for performance testing of big data, such as Apache Jmeter, Apache Drill, LoadRunner, WebLoad, YCSB etc., are also compared with various parameters such as domain applicability, scripting interface etc., and tools are suggested to improve overall performance. © 2022 IEEE.

关键词： Big data

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Web based Payment Tracking and Accounting Application 7

Web based Payment Tracking and Accounting Application

引用

7th international conference on Intelligent computing and Control Systems, ICICCS 2023

作者： Baibhav, Jayesh Ghatak, Jyotishman Mayan, J. Albert Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350397253

the Payment Tracking System (PTS) is a sophisticated web-based platform designed for proficiently tracking and managing payments from various vendors. It serves as a centralized hub for consolidating payment requests from the accounts department to upper management, thereby ensuring timely delivery of supplier payments through the implementation of integrated best practices for managing operations and services. the system boasts advanced Transaction Management functionality such as Invoice Generation and Payment Reminders, providing unparalleled visibility, insight, isolation, and swift resolution of payment-related issues for any type of organization by delivering the necessary information in a timely manner to the user. In today's fast-paced business environment, managing invoicing and chasing payments from clients can be a challenging task. this innovative application offers a solution to this problem by providing businesses with the capability to track payments from clients and gain valuable insights into their earnings. the system not only facilitates the creation, sending, and receiving of invoices, but also generates automated follow-up reminders for overdue payments. By utilizing this application, clients can also avoid incurring late fees © 2023 IEEE.

关键词： Websites

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Parameter Estimation of Frequency-hopping Signal and Simulation Based on Kernel Function Design 7

Parameter Estimation of Frequency-hopping Signal and Simulat...

引用

7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Mi, Wenhui Wang, Hongbin Guo, Daoxing Yang, Lei Army Engineering University of Pla College of Communication Engineering Nanjing China

ISBN: (纸本)9781665478571

One of the most prevalent spread spectrum techniques is frequency hopping. Once implemented, it will dramatically enhance the difficulty of communication confrontation because to its high anti-interference ability, low probability of interception, and ease of networking. In the crowded environment of modern electronic warfare, it is critical to predict the parameters of frequency hopping signals and provide prior knowledge to jammers. To begin, the distribution properties of the frequency hopping signal in the fuzzy domain are completely leveraged to create a novel bilinear time-frequency distribution kernel function based on the existing nonlinear time-frequency approach. Second, entropy measurement theory is introduced to optimize the kernel function parameters, filter the cross-interference items to reduce interference, and keep the self-term as long as possible. Finally, the procedure of estimating the frequency hopping signal parameter is completely designed. the experimental results suggest that the kernel function proposed in this study is capable of accurately estimating signal properties in a -6 dB environment. the improved kernel function can provide larger performance benefits under the same information entropy conditions. © 2022 IEEE.

关键词： Frequency hopping

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Sentiment Classification of Visitors in Yogyakarta Palace using Support Vector Machine 7

Sentiment Classification of Visitors in Yogyakarta Palace us...

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7th international conference on Informatics and computing, ICIC 2022

作者： Damariati, Cahva Rani, Fadia Riyadi, Slamet Beng, Gan Kok Universitas Muhammadiyah Yogyakarta Department of Information Technology Yogyakarta Indonesia Universiti Kebangsaan Malaysia Department of Electrical and Electronic Engineering Bangi43600 Malaysia

ISBN: (纸本)9798350345711

Yogyakarta is one of Indonesia's most popular tourist destinations with its Yogyakarta Palace 'Keraton'. Trip Advisor, one of the most extensive traveller guides, provides visitor reviews about the Keraton. Since the review is very important for Keraton management and was not analyzed yet, this research aims to classify the visitor sentiment on Keraton using the Support Vector Machine (SVM) method. the research method involved collecting comments from the website, preprocessing, including data cleaning, tokenizing, transforming, and stopwords filtering, as well as classifying the sentiment as positive and negative. this study showed that the SVM could classify the sentiment with 75.79% accuracy. © 2022 IEEE.

关键词： Support vector machines

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IRNet: An Improved RetinaNet Model for Face Detection 7

IRNet: An Improved RetinaNet Model for Face Detection

引用

7th international conference on Image, Vision and computing, ICIVC 2022

作者： Jiang, Chenchen Ma, Hongbing Li, Liangliang Xinjiang University College of Information Science and Engineering Urumqi830046 China Tsinghua University Department of Electronic Engineering Beijing100084 China

ISBN: (数字)9781665467346

ISBN: (纸本)9781665467346

the current face detection methods mainly focus on overlaying network layers to improve the detection accuracy. However, in practical applications, these huge models cannot achieve the real-time detection. In order to solve the aforementioned problems, an improved RetinaNet (IRNet) model for face detection is proposed. In the field of face detection, feature fusion module is a common method to solve multi-scale detection problems. In this paper, a new feature fusion module N-FPN is introduced. the N-FPN module has been proven to improve detection accuracy. We design experiments to select the appropriate weight decay parameters. the IRNet finally achieves 91.77%, 89.26%, and 76.59% detection results on Easy, Medium, and Hard datasets of Wider Face, respectively. In addition, the IRNet obtained better detection results than RetinaNet on the FDDB dataset. © 2022 IEEE.

关键词： Face recognition

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IoT Based Continuous Glucose Monitoring: An Insight into Current Trends and Limitations 7

IoT Based Continuous Glucose Monitoring: An Insight into Cur...

引用

2023 7th international conference On computing, Communication, Control And Automation, ICCUBEA 2023

作者： Kalia, Surkiti Ahmed, Suhaib Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798350304268

In order to remotely access patient data and continuously monitor their blood glucose levels, patients can now use the Internet of things (loT) and continuous glucose monitoring (CGM) as a potential strategy for managing diabetes. the purpose of this review is to evaluate the effectiveness of CGM with loT as a diabetes management tool and to look into the benefits, limitations, and challenges of using CGM with loT in the treatment of diabetes with an emphasis on recent studies. Studies that evaluated the effectiveness of CGM with loT for controlling diabetes were included in the review. the study found that CGM plus loT is an effective diabetes management tool. Increased time spent in the target glucose range, a reduction in hypoglycemia, and improved glycemic control have all been associated with the use of CGM with loT. Additionally, it has been shown that CGM combined with loT's remote patient data access enhances patient outcomes and lowers healthcare costs. Costs and technological challenges, however, may limit the adoption of CGM with loT. It is also concluded that more research is needed to determine the long-term cost- and efficacy of CGM with loT in controlling diabetes. © 2023 IEEE.

关键词： CGM Diabetes loT Medical Care

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Camouflaged Object Detection with Discriminative Information Attention and Cross-level Feature Fusion 7

Camouflaged Object Detection with Discriminative Information...

引用

7th international conference on Image, Vision and computing, ICIVC 2022

作者： Li, Xinyue Li, Lin Jiang, Shiyao Yang, Miao Qi, Lin Ocean University of China Faculty of Information Science and Engineering Qingdao China

ISBN: (数字)9781665467346

ISBN: (纸本)9781665467346

Camouflaged object detection (COD) aims to accurately locate and segment objects that blend in with surroundings, which is a challenging task due to the inconspicuous appearance and boundary. In this paper, we propose a novel Discriminative Information Attention and Cross-level Feature Fusion Network (DACF-Net) for camouflaged object detection. Specifically, we introduce a Discriminative Information Attention Module (DIAM) and a Context Enriched Module(CEM) to exploit and extract representative and contextual information. A Cross-level Feature Aggregation Module (CFAM) is utilized to suppress feature redundancies and exploit more complementary information. Extensive quantitative and qualitative experiments indicate that the proposed method has superior performance in explaining the camouflage prediction. © 2022 IEEE.

关键词： Object detection

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