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An Effective Approach to Speech-Based Email Assistance for Visually Impaired People

An Effective Approach to Speech-Based Email Assistance for V...

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international conference on Trends in Electronics and Informatics (ICEI)

作者： Henwyn Shan Antony. S Sherin Eliyas Department of Computer Application Hindustan Institute of Technology and Science Chennai India

ISBN: (数字)9798331544607

ISBN: (纸本)9798331544614

the Speech-based Email Assistant aims to promote digital inclusivity for the blind by allowing email operations to be done hands-free via voice commands. the system is capable of uninterrupted use without any visual input, using the OpenAI Whisper model for converting speech to text and the Google Text-to-Speech (GTTS) package for providing auditory feedback. the application allows for creating, sending, retrieving, managing mailboxes, and summarizing email messages, thus providing basic Natural Language processing (NLP) functions. Voice input is in live mode through PyAudio, and emails are sent over secure channels using SMTP and IMAP for email operations. Voice authentication alongside SHA-256 hashing is applied to enhance security, providing protection against unauthorized access while ensuring user privacy. this research aims to develop a voice-based email assistant that is user-friendly, efficient, and secure, thus promoting the digitally inclusive training of visually impaired users.

关键词： Training Visualization Authentication Natural language processing Electronic mail Text to speech Security Speech processing Usability Speech to text

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Migrate On-Premises Real-Time Data Analytics Jobs Into the Cloud 8

Migrate On-Premises Real-Time Data Analytics Jobs Into the C...

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8th IEEE international conference on Data Science and Advanced Analytics (DSAA)

作者： Wu, Huijun Qian, Xiaoyao Crowell, Hulya Pamukcu Singh, Tushar Shulman, Aleks Bhimani, Prashil Maloo, Abhishek Tang, Chunxu Li, Yao Zhang, Lu Ulherr, Chris Twitter Inc San Francisco CA 94103 USA

ISBN: (纸本)9781665420990

Twitter's data platform team is serving a large number of real-time analytics jobs, powering a wide range of data science use cases, from aggregations over time to spam detection. these analytics jobs constitute a crucial step in Twitter's data science infrastructure. As a key part of Twitter's "partly cloudy" strategy, real-time data analytics jobs are being migrated from on-premises into the cloud. We would like to share our migration approach and findings in this paper. the jobs to be migrated vary but follow common patterns, including the "read-modify-write store" and "lambda architecture" patterns. Both patterns can be migrated to the Beam data model in general ways. Besides job patterns, the job IOs are handled by replicating or proxying between on-premises and the cloud. Tests are applied in two phases through monitoring metrics and control tests. A case study demonstrates the business impact of migration. Finally, we discuss lessons learned.

关键词： real-time data processing on-premises cloud migration

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Quantum Annealing to Solve the Unrelated parallel Machine Scheduling Problem 1

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14th international conference on parallel processing and applied mathematics, PPAM 2022

作者： Orts, Francisco Puertas, Antonio M. Garzón, Ester M. Ortega, Gloria Informatics Department University of Almería ceiA3 Almería Spain Department of Chemistry and Physics University of Almería ceiA3 Almería Spain

ISBN: (数字)9783031304453

ISBN: (纸本)9783031304446

Quantum computing has emerged in recent years as an alternative to classical computing, which could improve the latter in solving some types of problems. One of the quantum programming models, Adiabatic Quantum Computing, has been successfully used to solve problems such as graph partitioning, traffic routing and task scheduling. Specifically, in this paper we focus on the scheduling on unrelated parallel machines problem. It is a workload-balancing problem where the processing time of any procedure executed on any of the available processing elements is known. Here, the problem is expressed as Quadratic Unconstrained Binary Optimisation, which can be subsequently solved using quantum annealers. the quantum nonlinear programming framework discussed in this work consists of three steps: quadratic approximation of cost function, binary representation of parameter space, and solving the resulting Quadratic Unconstrained Binary Optimisation. One of the novelties in tackling this problem has been to compact the model bearing in mind the repetitions of each task, to make it possible to solve larger scheduling problems. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Cost functions

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A Configurable Detector Based on Layered Belief Propagation for Massive MIMO Detection

A Configurable Detector Based on Layered Belief Propagation ...

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international conference on Integrated Circuits and Microsystems (ICICM)

作者： Rui Gao Houren Ji Wenyue Zhou Xiaohu You Chuan Zhang Lab of Efficient Architectures for Digital-communication and Signal-processing (LEADS) National Mobile Communications Research Laboratory Southeast University Nanjing China Purple Mountain Laboratories Nanjing China

Massive multiple-input multiple-output (MIMO) detection plays a prominent role in the field of wireless communication. And with this trend, message passing detection (MPD) attracts a great attention since its advantages of high throughput and low complexity between distinct detection algorithms. Among various MPD algorithms, Gaussian approximate interference belief propagation (GAI-BP) detection can exhibit excellent convergence and performance in the different scenarios. However, its hardware design should be more efficient and flexible further. this paper proposes a novel semi-parallel hardware architecture for GAI-BP detection, aimed at improving its configurability using a layer scheduling scheme. through this scheme, the proposed detector achieves a gain of 0.65 dB when compared to the original algorithm, while simultaneously accommodating multi-antenna radios through the proposed hardware design.

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A Ship Trajectory Prediction Model Based on ECA-BiGRU

A Ship Trajectory Prediction Model Based on ECA-BiGRU

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IEEE international conference on Big Data Analysis (ICBDA)

作者： Shenghui Yang Siyuan Chen Chenshen Liu Mengqian Li Mouye Wang Jinlong Wang China Academy of Electronics and Information Technology Beijing China

It is essential to forecast the ship’s next track with the ship’s historical track and real-time motion status information to ensure safe navigation. With the large-scale application of the Chinese satellite navigation system Beidou, the total management of ship trajectory is feasible, and its data sequence characteristics are more robust. this thesis proposes an ECA-BIGRU vessel track forecast model based on Beidou vessel sequence data using the BIGRU model and makes a preliminary track forecast. then it uses the ECA attention mechanism to optimize BiGRU. the measurement results of 112 ships running continuously for 20 days show that this dissertation proposes higher real-time performance and more accurate ship trajectory prediction in this dissertation than the ordinary BiGRU and LSTM algorithms, and it has significant application value.

关键词： Tracking Computational modeling Predictive models parallel processing Prediction algorithms Satellite navigation systems Real-time systems

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FITC & TRITC Spot Detection and Analysis at BCL2 Gene Locus as Follicular Lymphoma Marker on 2D Digital Tissue Slides and 3D Serial Sections

FITC & TRITC Spot Detection and Analysis at BCL2 Gene Locus ...

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IEEE international conference on Intelligent Engineering Systems (INES)

作者： Marianna Dimitrova Kucarov Annamária Csizmadia Béla Molnár Miklos Kozlovszky Doctoral School of Applied Informatics and Applied Mathematics BioTech Óbuda University 3DHistech Ltd Budapest Hungary Doctoral School of Pathological Sciences Semmelweis University Budapest Hungary 3DHistech Ltd Budapest Hungary John von Neumann Faculty of Informatics Óbuda University Hungary Medical Device Research Group LPDS Inst. for Computer Science and Control (SZTAKI) Hungarian Research Network (HUN-REN)

ISBN: (数字)9798350367591

ISBN: (纸本)9798350367607

We aimed to automate the detection and measurement of chromosomal rearrangements at the BCL2 locus located on chromosome 18q21 in order to further refine the BCL2 based therapeutic strategies for follicular lyphoma and speed up its diagnostics. the implementation was carried out using fluorescence in situ hybridization, PANNORAMIC MIDI II fluorescence slide scanner, and digital image processing techniques. the method provides visualization of the evaluated digital tissue slides for 2D and 3D serial sections as well.

关键词： Visualization three-dimensional displays Digital images Scattering Manuals Fluorescence parallel processing

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Building Edge Detection Technology from Remote Sensing Image Based on NSCT and Tensor Voting 8

Building Edge Detection Technology from Remote Sensing Image...

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2024 8th international conference on Machine Vision and Information Technology, CMVIT 2024

作者： Wu, Yingbin Zhao, Peng Zhou, Mingquan Geng, Shengling Zhang, Dan School of Computer Science Qinghai Normal University Qinghai Xining China School of Mathematics and Information Technology Yuncheng University Shanxi Yuncheng China State Key Laboratory of Tibetan Intelligent Information Processing and Application Qinghai Xining China

An edge detection technology based on the combination of non-downsampling contour wave transform (NSCT) and tensor voting is proposed, which aims to obtain more accurate and detailed edge information of buildings in remote sensing images. Firstly, NSCT is used for image decomposition to obtain the subband frequency information of different scales and angles. then, position encoding is performed on these subband coefficients to obtain second-order symmetric tensors at the corresponding positions. Tensors of different scales and angles at the same position are weighted and summed to complete feature fusion. Finally, the edge features of the image are obtained based on tensor voting theory. the experimental results show that compared to common edge detection technologies, such as Canny, Fast Edge (Fast edge detection using structured forests) and HED (Holistically-Nested Edge Detection), our method can more accurately and intensively reflect the boundaries of buildings and the edge information of roofs, providing better support for the analysis of building types and architectural styles. Compared to the HED method, which is based on deep learning, our method improves PSNR and SSIM metrics by 0.98 and 0.03, respectively. © Published under licence by IOP Publishing Ltd.

关键词： Edge detection

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Training a neural network to observe the assembly mode of parallel robots

Training a neural network to observe the assembly mode of pa...

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Mechanical Engineering and Robotics Research (ICMERR), international conference on

作者： Adrián Peidró Antonio Manuel García-Pérez Paula Mollá-Santamaría Marc Fabregat-Jaén Óscar Reinoso Instituto de Investigación en Ingeniería de Elche (I3E) Miguel Hernández University Elche 03202 Spain Instituto de Investigación en Ingeniería de Elche (I3E) Valencian Graduate School and Research Network for AI

parallel robots have different solutions to their forward kinematic problem, i.e., their gripper can adopt different possible positions that are compatible with the displacements of the actuated joints. It is necessary to know the position of the gripper to control parallel robots in the operational space. However, usually, only these joint displacements are measured, which results in the indetermination of which of these possible positions is the one actually adopted by the gripper. Previous methods require redundant sensors to measure directly the position of the gripper or the displacements of passive joints. In this paper we propose to estimate the position of the gripper by solving the observability problem of parallel robots regarded as nonlinear dynamical systems. By taking the position coordinates of the gripper as states of the system, it is possible to reconstruct these states from the signals of inputs (control forces) and outputs (displacements of actuated joints) of the system. To that end, we propose a feedforward neural network to perform as the state observer, and we train it using thousands of trajectories. the proposed neural observer is tested on a simulated 2RPR parallel robot, and it is found that, combined with a refinement post-processing based on Newton-Raphson’s iterative method to solve the forward kinematics, the proposed method is able to exactly reconstruct the position of the gripper if the robot starts to move far from Type 2 singularities, at which different solutions merge.

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Conception of a Mixed Reality Eyesight Training System Based on the parallel Robot 8

Conception of a Mixed Reality Eyesight Training System Based...

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8th IEEE international conference on Problems of Infocommunications, Science and Technology, PIC S and T 2021

作者： Selivanova, Karina Kostin, Denys Tymkovych, Maksym Kharkiv National University of Radio Electronics Department of Biomedical Engineering Kharkiv Ukraine

ISBN: (纸本)9781665406826

Diseases of the human visual system occupy a significant part of the total number of illnesses. Exercising the motor muscles of the eyes is one of the most effective methods of combating certain diseases of the human visual system. the paper considers the concept of a mixed reality training system using a parallel mechanism for vision training tasks. the block diagram of the system is given, its main components are described (including input unit, control unit, reprojection unit, sensor unit), as well as the principle of its operation. the full-scale assembling of the parallel manipulator has been accomplished. Other mechanisms can also be used as a manipulator. the elements of such a system were tested, namely, the registration of depth information, segmentation of the significant planes, etc. Based on this, environmental modeling was carried out. the proposed concept of a mixed reality simulator can be widely applied in various medical institutions. © 2021 IEEE.

关键词： Mixed reality

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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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