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Enhancing Document Summarization with Machine Learning Approaches for Single and Multiple Documents 8th

Enhancing Document Summarization with Machine Learning Appro...

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8th international conference on Information and Communication Technology for Intelligent Systems, ICTIS 2024

作者： Deshmukh, Gopal B. Takale, Dattatray G. Gawali, Piyush P. Kashid, Shraddha S. Mahalle, Parikshit N. Sule, Bipin Patil, Sambhaji A. Lahve, Ramesh Department of Computer Engineering Vishwakarma Institute of Information Technology SPPU Pune Pune India Department of Computer Engineering MIT ADT University Pune India Department of AI & DS Vishwakarma Institute of Information Technology SPPU Pune Pune India and Humanities Vishwakarma Institute of Technology Pune India E&TC PGM College of Engineering Pune Wagholi India Department of Information Technology Anantrao Pawar COE Pune SPPU Pune Pune India

ISBN: (纸本)9789819766802

the purpose of this research paper is to enhance the effectiveness of document summarization by integrating advanced deep learning methodologies into the process. In this study, neural networks, attention mechanisms, transformer-based models, and attention mechanisms are investigated in light of both single and multiple document scenarios. this paper provides valuable insights into how well these approaches work in producing concise and informative summaries by conducting comprehensive experiments and evaluations. As part of this paper, an innovative approach is introduced to document summarization by combining the strengths of Ensemble RNNs and Long Short-Term Memory (LSTM) networks. Having to summarize multiple documents at the same time is challenging. A nuanced approach is required to accomplish this task. the proposed method utilizes the power of RNN-LSTM networks in order to capture long-range dependencies and contextual information and then enhances this data by utilizing Ensemble techniques so that summarizing performance is improved. To demonstrate our approach's effectiveness, we conduct comprehensive experiments and evaluations on a variety of datasets. According to the results of this study, the Ensemble LSTM-based hybrid summarization technique achieves superior results when compared to individual LSTM models, setting a new standard in document summarization for single or multiple documents. In addition to contributing significantly to the advancement of document summarization, this research provides valuable insights for practical applications in information retrieval and knowledge extraction that could be applied in the future. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Natural language processing systems

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Scalable SubXPCA on a Distributed Platform applied to Classification of Hyperspectral Images

Scalable SubXPCA on a Distributed Platform Applied to Classi...

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conference on Information and Communication Technology (CICT)

作者： Bogolu Rupa Atul Negi School of Computer and Information Sciences University of Hyderabad Department of Computer Science and Engineering Vardhaman College of Engineering Hyderabad Telangana India

ISBN: (数字)9798331531539

ISBN: (纸本)9798331531546

the exponential growth of technological advancements in satellite and airborne remote sensing is giving rise to large volumes of high-dimensional hyperspectral image data. Apache Spark is one of the most popular, extensively used and open-source distributed processing frameworks, which is proven effective in processing large volumes of remotely sensed hyperspectral images in a time-efficient manner. Open-source distributed processing frameworks have proven effective in processing large volumes of remotely sensed hyperspectral images quickly and efficiently. While computational power has been increasing, the rate of data accumulation is more than the processing capabilities. therefore, more efficient algorithms such as dimensionality reduction are needed to process and get accurate performance for the application. this paper proposes an efficient and parallel spectral dimensionality reduction approach based on feature partitioning principal component analysis called scalable SubXPCA. We implemented scalable SubXPCA on a spark cluster distributed environment. We compared scalable SubXPCA against other distributed feature partitioning and various non-feature partitioning dimensionality reduction methods. Our experiments on different real and synthetic datasets of hyperspectral images confirm that SubXPCA classification performance is not only better than its competitors but also that the running time of SubXPCA is better in distributed processing than serial processing. As the size of the hyperspectral image dataset increased, SubXPCA showed a speed up factor of 5.7× and more in the spark cluster compared to the serial version.

关键词： Dimensionality reduction Distributed processing Accuracy Satellites Partitioning algorithms Information and communication technology Sparks Hyperspectral imaging Principal component analysis Synthetic data

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P-ODA: A Fast and Robust parallel Ommatidia Detection Algorithm for High-throughput Insect Ommatidia Detection

P-ODA: A Fast and Robust Parallel Ommatidia Detection Algori...

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Advanced Algorithms and Control Engineering (ICAACE), international conference on

作者： Wentao Zhu Chaofan Zhang Tianhao Zhang Zhenyu Gao Siqin Ge Yong Liu Anhui Institute of Optics and Fine Mechanics Hefei Institutes of Physical Science Chinese Academy of Sciences University of Science and Technology of China Anhui China Anhui Institute of Optics and Fine Mechanics Hefei Institutes of Physical Science Chinese Academy of Sciences Anhui China Key Laboratory of Animal Biodiversity Conservation and Integrated Pest Management Institute of Zoology Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China Key Laboratory of Animal Biodiversity Conservation and Integrated Pest Management Institute of Zoology Chinese Academy of Sciences Beijing China

ISBN: (数字)9798331535087

ISBN: (纸本)9798331535094

the automatic detection and analysis of ommatidia, the fundamental visual units of insect compound eyes, is vital for advancing biological research and understanding insect vision. Compound eyes, with their multi-lens structure, provide a broad field of view and high visual resolution. Researchers typically obtain ommatidia structures through CT imaging of insect compound eyes. However, processing these high-resolution 3D images requires significant computational resources due to the complexity and scale of the data. Existing methods struggle with inefficiency and poor robustness, particularly when dealing with large and complex datasets. To overcome these challenges, we introduce a groundbreaking framework, P-ODA, for fast and robust ommatidia detection by integrating parallel computing into the CT image analysis insect compound eyes. By harnessing the power of both Graphics processing Units (GPUs) with Compute Unified Device Architecture (CUDA) and multicore Central processing Units (CPUs), we present a novel approach to enhance the Ommatidia Detection Algorithm (ODA). Our method efficiently processes large-scale datasets and demonstrates unprecedented scalability. We offer two independent implementations: one utilizing CUDA for GPU acceleration, and another leveraging Python's multicore CPU capabilities. Experimental results show that P-ODA dramatically improves execution time and scalability over traditional ODA methods. Moreover, the system is designed for ease of use with a Linux graphical interface. this innovative framework sets the stage for the next generation of biological dataset processing and hybrid parallel computing systems.

关键词： Visualization Insects Computed tomography Scalability Graphics processing units parallel processing Biology Central processing Unit Compounds Detection algorithms

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Validation of a High-Precision Phase Synchronization Approach for Bi-Static SARs through Universal Electronic Measuring Instruments

Validation of a High-Precision Phase Synchronization Approac...

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international conference on Vision, Image and Signal processing (ICVISP)

作者： Guangshen Wang Peng Zhou Zhenhua Zhang College of Oceanography and Space Informatics China University of Petroleum (East China) Qingdao China School of Astronautics Beihang University Peking China

ISBN: (数字)9798331541460

ISBN: (纸本)9798331541477

Bistatic synthetic aperture radar (BiSAR) system faces significant phase synchronization challenges due to its distributed platform. this paper theoretically analyzes the working principle of a bidirectional synchronization link and proposes a method for extracting compensation phase using the single frequency continuous wave signals. A high-precision phase synchronization compensation algorithm is applied in imaging simulations to compare results under different frequency source conditions, verifying the algorithm's accuracy. Finally, a bistatic SAR phase synchronization system is constructed with universal electronic instruments, and phase synchronization experiments using single frequency continuous wave signals are conducted. Experimental results demonstrate that the system effectively verifies phase synchronization accuracy, providing valuable references for subsequent engineering design.

关键词： Accuracy Phase measurement Satellites Instruments Signal processing algorithms Signal processing Frequency measurement Synchronization Frequency synchronization Synthetic aperture radar

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Implementation of A High Speed Layout parallel Prefix Adder for Design Applications

Implementation of A High Speed Layout Parallel Prefix Adder ...

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international conference of Electronics, Communication and Aerospace Technology (ICECA)

作者： D. V. N. Bharathi Y. Varthamanan Electronics and Communication Engineering Sathyabama Institute of Science and Technology Chennai Tamil Nadu India

ISBN: (数字)9798350367904

ISBN: (纸本)9798350367911

One of the essential components of applications like signal processing, adders play a crucial role. Integrated circuits are the main technology used in the modern world, and adder modules are required. the arithmetic operationmost often used in digital systems is binary addition. Reliability depends heavily on the efficiency of its *** the digital adder could be made more efficient, it would handle binary operations much better. A microprocessor’s minimum clock cycle time is defined by the speed of its adder. the overall performance of the system is always determined by combining the adders power dissipation, speed, and area. Carry propagation is a performance problem with the addition operation that affects its speed. As a result, VLSI (Very Large-Scale Integration) has been continually focusing on speed increase while reducing covered area. A parallel prefix adder’s speed is the primary consideration when choosing between a ripple carry adder and our preferred alternative. For both latency and coverage area, the best adders in use right now are PPAs, or parallel prefix adders. they are hence the recommended option given the larger number of high-performance adders. An efficient layout parallel prefix adder has been developed and is now accessible to use in design applications. the area (number of LUTs), delay (ns), power, and speed of the suggested designs is better compared to RCA & CLA adders.

关键词： Digital systems Layout Very large scale integration Signal processing Generators Delays Table lookup Power dissipation Integrated circuit reliability Adders

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ECSCDA: An efficient system for analyzing contents of Computer Science Courses 8

ECSCDA: An efficient system for analyzing contents of Comput...

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8th international conference on Advanced Informatics: Concepts, theory, and Application, ICAICTA 2021

作者： Kamlangpuech, Peerapon Amphawan, Komate Burapha University Computational Innovation Laboratory Faculty of Informatics Chonburi20131 Thailand

ISBN: (纸本)9781665417433

this paper aims to introduce a new efficient system, called eCSCDA, to efficient analyze Computer Science (CS) course description. the primary task of the system is to identify similar (and dissimilar) contents amount two (or a group of) CS course descriptions which can help to know similar and different focuses on important contents to teach to students. Moreover, it can help to check for integrity and quality and to set up a standard of teaching contents of the course. In eCSCDA, text processing procedure is newly rearranged and developed. Besides, the linguistic rules and their derivation are newly updated and applied to extracted important keywords. Moreover, two synonym corpuses, terminology and word synonyms, are recently designed and collected to consider synonyms of the keywords hidden in the course descriptions. Last, to efficiently identify similar contents, two new matching techniques, sub-keyword and semantic matching techniques, are designed and applied together with exact and subset (superset) matching methods. Experiments were conducted on CS course contents gathered from nine thai Universities to examine the effectiveness of our proposed system in comparison with previous system and related methodologies. From the results, it shows that eCSCDA is efficient to analyze the course contents and outperforms other related systems in various terms e.g. percentage of similar contents, precision, recall and F-measure, respectively. © 2021 IEEE.

关键词： Text processing

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Classification of Transient Power Quality Disturbances Based on Digital Image processing Techniques

Classification of Transient Power Quality Disturbances Based...

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IEEE international conference on Power and Power and Renewable Energy (ICPRE)

作者： Feng Guo Jian Li Xu Xu Yizhi Zhu Xiaoyuan Luo Wangkai Qian State Grid Zhejiang Electric Power Co. Ltd. Taizhou China Taizhou Power Supply Company State Grid Zhejiang Electric Power Co. Ltd. Taizhou China School of Electrical Engineering Nanjing Institute of Technology Nanjing China

With the advancement of technology and the transformation of energy systems, electrical energy has become an essential part of various industries. In modern active distribution networks, there have been new trends in the structure of distribution networks and loads. the sensitivity of devices has increased, and issues related to voltage oscillations and voltage sag have become increasingly important in terms of power quality. therefore, improving power grid quality requires rapid and efficient classification and detection of various disturbances. To achieve accurate classification and identification of disturbance signals, digital image processing methods such as gamma correction, edge detection, and local extremum analysis can be used. By extracting the morphological characteristics of disturbance signals, effective classification and recognition of disturbance types can be achieved. Subsequently, normalization processing is applied to the power quality disturbance data, generating new grayscale images. Analysis of experimental data indicates that the improved method for transient power quality disturbance classification has higher accuracy, making it a feasible and efficient approach.

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the AC-DC-AC Converter Design for parallel Asynchronous Generator Based Microhydro Power Plants 8

The AC-DC-AC Converter Design for Parallel Asynchronous Gene...

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8th international conference on Electrical Engineering, Computer Science and Informatics (EECSI)

作者： Marwanto, Arief Irmawanto, Rudi Haddin, Muhamad Rosyadi, Marwan Univ Islam Sultan Agung UNISSULA Post Grad Dept Elect Engn Semarang Indonesia Univ Muhammadiyah Surabaya UM Surabaya Fac Engn Elect Engn Dept Surabaya Indonesia Kitami Inst Technol Elect & Eletron Engn Dept Kitami Hokkaido Japan

ISBN: (纸本)9786236264201;9786236264195

the use of micro hydro energy for electricity generation in Indonesia is currently increasing along with the launch of the energy independence village program which continues to grow in several regions. In this study, the design and analysis of AC-DC-AC converter is applied to asynchronous/induction generators connected in parallel with 50-kW Micro Hydro Power Plant. the AC-DC-AC converter consists of a Generator Side Converter (GSC) and a Load Side Converter (LSC) which are installed back to back via the DC-Link network. the effectiveness and dynamic characteristics of the controller design were evaluated and analyzed through simulation using the PSCAD program. Simulation analysis is divided into 2 fault scenarios, namely: (1) Analysis of small disturbances in the form of changes in load and generator rotation differences, and (2) Analysis of large disturbances due to short circuits in the transmission network. the results show that the control system is able to stabilize and regulate the flow of power against changes in load and permanent disturbances.

关键词： Micro hydro plant Asynchronous Generator AC-DC-AC Converter dynamic analysis

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RFNet: A Refinement Network for Semantic Segmentation 26

RFNet: A Refinement Network for Semantic Segmentation

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26th international conference on Pattern Recognition / 8th international Workshop on Image Mining - theory and Applications (IMTA)

作者： Zhu, Guilin Wang, Runmin Han, Chang Liu, Yingying Ding, Yajun Liu, Minghao Liu, Li Sang, Nong Hunan Normal Univ Coll Informat Sci & Engn Changsha 410081 Peoples R China Wuhan Business Univ Lab Control & Applicat Technol Robot Wuhan 430056 Peoples R China Natl Univ Def Technol Sch Syst Engn Changsha 410000 Peoples R China Huazhong Univ Sci & Technol Sch Artif Intelligence & Automat Wuhan 430074 Peoples R China

ISBN: (数字)9781665490627

ISBN: (纸本)9781665490627

As one of the basic tasks of computer vision, semantic segmentation is widely used in many fields, e.g., medical images parsing, scene parsing, autonomous driving, etc. In the current mainstream approaches, downsampling or patching operation is required to ensure that the GPU memory is not overloaded for dealing with the high-resolution input images. However, the corresponding cost is the lack of details in the final segmentation map. In this work, we proposed RFNet, a refinement network which resolves the lack of detailed information in coarse predictions by fusing the coarse predictions and the fine predictions gained by fine input image patches. there are three key characteristics: (i) designing a spatial information extraction module which can efficiently process information in coarse and fine feature maps at spatial level. (ii) proposing an auxiliaryfusion information branch calculated from the prediction maps, which contribute to refine predictions. (iii) designing a boundary auxiliary loss function in the training process, which makes the model pay more attention to those pixels belonging to the boundary of objects. We show the superiority of the proposed RFNet on the Cityscapes dataset, the experimental results illustrate that ours RFNet performance outperforms other state-of-the-art approaches with low computation consumption. the codes will be available at: https://***/zhu-gl-ux/RFNet.

关键词： Training Image color analysis Semantic segmentation Image edge detection Memory management Graphics processing units Predictive models

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A VLSI Architecture for MQ Arithmetic Encoder Supporting three-Context parallel processing

A VLSI Architecture for MQ Arithmetic Encoder Supporting Thr...

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international conference on Vision, Image and Signal processing (ICVISP)

作者： Peijun Ma Cong Yao Jiangyi Shi Gongzhi Zhao Xidian University Xi'an China

ISBN: (数字)9798331541460

ISBN: (纸本)9798331541477

JPEG2000 is a popular still image compression standard, which has excellent compression performance in the field of still image compression. At present, it is widely believed that MQ arithmetic encoder has become the most critical speed bottleneck of JPEG2000 algorithm due to the restriction of the serial execution mode of the algorithm itself. the MQ encoding is serial in nature, which is due to the high dependence between adjacent Cx-D pairs which severely affects its processing speed. In order to solve this problem, this paper proposes a multi-context MQ coding hardware architecture based on a partially parallel coding strategy. this architecture can process up to three Cx-D pairs in one clock cycle, which greatly improves the processing speed of the MQ arithmetic encoder under the existing architecture. In terms of overall performance, the encoder designed in this paper can process 2.64 Cx-D pairs per cycle on average, and 743.16 Cx-D pairs per second under TSMC90nm technology. the architecture is only 208399.66 units in area while achieving high throughput. the proposed MQ encoder provides a useful reference for hardware implementation of high performance algorithmic encoders in JPEG2000 and other image compression standards. At the same time, we comprehensively analyze the possible output scenarios of multi-bytecode streams caused by multi-context processing, and propose a processing structure based on additional pipeline, which greatly reduces the number of module fan-out and FIFOs.

关键词： Image coding Transform coding Voltage Very large scale integration throughput Libraries Hardware Environmental factors Standards Arithmetic

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