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arXiv 2022年

作者： Zhu, Xiutao Chen, Yaojun Gerbner, Dániel Győri, Ervin Karim, Hilal Hama Department of Mathematics Nanjing University Nanjing210093 China Alfréd Rényi Institute of Mathematics Budapest Hungary Department of Computer Science and Information Theory Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Budapest Hungary

The generalized Turán number ex(n, Ks, H) is the maximum number of complete graph Ks in an H-free graph on n vertices. Let Fk be the friendship graph consisting of k triangles. Erdős and Sós (1976) determined the value of ex(n, K3, F2). Alon and Shikhelman (2016) proved that ex(n, K3, Fk) ≤ (9k−15)(k+ 1)n. In this paper, by using a method developed by Chung and Frankl in hypergraph theory, we determine the exact value of ex(n, K3, Fk) and the extremal graph for any Fk when n ≥ 4k3 Copyright © 2022, The Authors. All rights reserved.

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Predictive Analytics for Hospital Readmissions Using Logistic Regression and IoT Sensor Data

Predictive Analytics for Hospital Readmissions Using Logisti...

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International Conference on Energy, Power and Environment: Towards Sustainable Growth (ICEPE)

作者： Kiruthiga B Arshadh Ariff Mohamed Abuthahir Riazulhameed Rajapriya. M R. Sarasu N. Mohankumar A. Kasthuri Department of Management Studies SRM Valliammai Engineering College Chennai Tamil Nadu India Blackstraw Technologies Pvt Ltd Chennai Tamil Nadu India Department of Management Studies Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai Tamil Nadu India Department of Spatial Informatics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India Symbiosis Institute of Technology (SIT) Symbiosis International (Deemed University) Nagpur Maharashtra India Department of Computer Science and Engineering Vinayaka Mission's Kirupananda Variyar Engineering College Inayaka Mission's Research Foundation (DU) Salem Tamil Nadu India

ISBN: (数字)9798350379297

ISBN: (纸本)9798350379303

Hospital readmissions affect healthcare systems globally, increasing costs and morbidity. Readmissions must be predicted and prevented to improve patient outcomes and save healthcare costs. This research leverages the Internet of Things (IoT) sensor data and Logistic Regression (LR) to reduce hospital readmissions using predictive analytics. Patient health data from IoT devices during and after hospitalization is used in the paper. Heart rate, blood pressure, and oxygen saturation are constantly monitored. LR is used to examine this dataset and create a prediction model. The LR algorithm trains us to recognize IoT sensor data patterns and correlations that indicate readmission risks. Our methodology provides developed risk estimates incorporating patient-specific parameters, including age, multiple illnesses, and medical history. The temporal data permits dynamic predictions, considering patient health changes over time. This research detected hospital readmission risk with promising accuracy. These predictions allow healthcare practitioners to proactively intervene and deliver targeted treatments, including prescription modifications, lifestyle advice, and follow-up consultations to decrease readmission. This proactive strategy may improve patient outcomes and save healthcare expenses.

关键词： Logistic regression Costs Hospitals Transforms Predictive models Internet of Things Predictive analytics

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Deep Neural Network Trained Punjabi Children Speech Recognition System Using Kaldi Toolkit 5

Deep Neural Network Trained Punjabi Children Speech Recognit...

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5th IEEE International Conference on Computing Communication and Automation, ICCCA 2020

作者： Taniya Bhardwaj, Vivek Kadyan, Virender Chitkara University Institute of Engineering and Technology Chitkara University Punjab India University of Petroleum and Energy Studies School of Computer Science Department of Informatics Dehradun India

ISBN: (纸本)9781728163246

Despite the number of developed Automatic Speech Recognition (ASR) systems for different languages, still no work has been done on children's speech of Punjabi language. Due to the unavailability of children's speech corpus for Punjabi Language, it is a challenging task to collect speech data. In our current work, efforts have been made to collect Punjabi children's speech corpus and build Children ASR system for Indian regional Punjabi language. The recognition rate of ASR systems is observed to be improved drastically by the emergence of Deep Neural Networks (DNN). In our work, the DNN acoustic model has been implemented by varying number of hidden layers. Approximately four hours of Punjabi children's speech corpus has been collected and several experiments have been performed using the DNN modeling technique. Experimental results have revealed that the system has attained 87% accuracy. © 2020 IEEE.

关键词： Acoustic Modeling

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Development of Robust Automatic Speech Recognition System for Children's using Kaldi Toolkit 2

Development of Robust Automatic Speech Recognition System fo...

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2nd International Conference on Inventive Research in Computing Applications, ICIRCA 2020

作者： Bhardwaj, Vivek Bala, Sashi Kadyan, Virender Kukreja, Vinay Chitkara University Institute of Engineering and Technology Chitkara University Punjab India School of Computer Science University of Petroleum and Energy Studies Department of Informatics Dehradun India

ISBN: (纸本)9781728153742

In this paper, the Punjabi children speech recognition system is developed using Subspace Gaussian mixture models (SGMM) acoustic modeling techniques. Initially, the system is dependent upon Mel-frequency cepstral coefficients (MFCC) approach for controlling the temporal variations in the input speech signals. Here, SGMM is integrated with HMM to measure the efficiency of each state which carries the information of a short-windowed frame. For handling the children speaker acoustic variations speaker adaptive training (SAT), based on vocal-tract length normalization and feature space maximum likelihood linear regression is adopted. Kaldi and open-source speech recognition toolkit is used to develop the Robust Automatic Speech Recognition (ASR) System for Punjabi Children's speech. S GMM accumulate the frame coefficients and their posterior probabilities and pass these probabilities to HMM which systematically fit the frame and output have resulted from HMM states. Therefore, the achievement of SGMM has gotten a large performance margin in Punjabi children speech recognition. A remarkable depletion in the word error rate (WER) was noticed using SGMM by varying the feature dimensions. The developed children ASR system obtained a recognition accuracy of 83.66% while tested by varying the feature dimensions to 12. © 2020 IEEE.

关键词： Acoustic Modeling

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Photonic Frequency Space Simulation of Tight-Binding Lattices Using Integrated LNOI Ring Resonators

Photonic Frequency Space Simulation of Tight-Binding Lattice...

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Pacific Rim Conference on Lasers and Electro-Optics (CLEO/Pacific Rim)

作者： Armandas Balčytis Hiep Dinh Tomoki Ozawa Yasutomo Ota Toshihiko Baba Satoshi Iwamoto Arnan Mitchell Thach G. Nguyen Integrated Photonics and Applications Centre RMIT University Melbourne VIC Australia Advanced Institute for Materials Research Tohoku University Sendai Japan Department of Applied Physics and Physico-Informatics Keio University Yokohama Japan Department of Electrical and Computer Engineering Yokohama National University Hodogaya-ku Yokohama Japan Research Center for Advanced Science and Technology The University of Tokyo Meguro-ku Tokyo Japan

We use electro-optically modulated ring cavities, integrated on thin-film lithium niobate, to model frequency dimension tight-binding lattices with versatile connectivity. Inter-mode coupling range, strength, and hopp... 详细信息

ISBN: (数字)9798350372076

ISBN: (纸本)9798350372083

关键词： Frequency modulation Lithium niobate Resonant frequency Lattices Electro-optic modulators Ring lasers Laser modes

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Performance Analysis for Molecular Communication Under Feedback Channel Using Multipath and Single Path Technique

SSRN

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SSRN 2022年

作者： Ningthoujam, Sanjit Chingkheinganba, Tekcham Chakraborty, Swarnendu Kumar Elngar, Ahmed A. Chakrabarti, Prasun Chakrabarti, Tulika Praveen, S. Phani Gupta, Amit Margala, Martin School of Computer Science and Engineering VIT University Andhra Pradesh 522237 India BSNL Dimapur797112 India Dept. of Computer Science and Engineering National Institute of Technology Arunachal Pradesh 791112 India Faculty of Computers and Information Techno India NJR Institute of Technology India Department of Chemistry Sir Padampat Singhania University Rajasthan Udaipur313601 India Prasad V Potluri Siddhartha Institute of Technology Andhra Pradesh 520007 India Department of ECE Narasaraopeta Engineering College Andhra Pradesh Narasaraopeta522601 India Computer Science School of Computing and Informatics University of Louisiana United States

Nanomachines that can run tasks and molecular communication (MC) for interconnecting nanomachines have been made possible by advances in nanotechnology. Different techniques of Automatic Repeat Request (ARQ) protocols have been devised in MC for acquiring the necessary molecules, although the retransmission of duplicate copies requires special attention. This work presents a diffusion-based MC with a feedback loop to improve MC performance. Based on the received ACK(s) or NACK(s), the Channel state determines if the state is good (G) or bad (B), and then single path or multipath procedures are used to the ‘G' and ‘B' states. The results of the MATLAB simulation illustrate how the systems compare in terms of communication rate, the possibility of complete transmission of the desired molecules, and energy consumption. When the channel state is bad, the multipath approach performs better, but when the channel state is perfect in MC, the single path strategy performs better. © 2022, The Authors. All rights reserved.

关键词： Molecules

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A Lightweight Approach to Real-Time Speaker Diarization: From Audio Toward Audio-Visual Data Streams

SSRN

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SSRN 2023年

作者： Kynych, Frantisek Cerva, Petr Zdansky, Jindrich Svendsen, Torbjørn Salvi, Giampiero Faculty of Mechatronics Informatics and Interdisciplinary Studies Technical University of Liberec Studentska 2 Liberec461 17 Czech Republic Department of Electronic Systems Norwegian University of Science and Technology Torgarden TrondheimNO-7491 Norway KTH Royal Institute of Technology School of Electrical Engineering and Computer Science Brinellvägen 8 StockholmSE-100 44 Sweden

This manuscript deals with the task of real-time speaker diarization (SD) for stream-wise data processing. Therefore, in contrast to most of the existing papers, it considers not only the accuracy but also the computational demands of individual investigated methods. We first propose a new lightweight scheme allowing us to perform speaker diarization of streamed audio data. Our approach utilizes a modified residual network with squeeze-and-excitation blocks (SE-ResNet-34) to extract speaker embeddings in an optimized way using cached buffers. These embeddings are subsequently used for voice activity detection (VAD) and block-online k-means clustering with a look-ahead *** described scheme yields results similar to the reference offline system while operating solely on a CPU with a low real-time factor (RTF) below 0.1 and a constant latency of around 5.5 seconds. In the next part of the work, our research moves toward much more demanding and complex real-time processing of audio-visual data *** this purpose, we extend the above-mentioned scheme for audio data processing by adding an audio-video module. This module utilizes SyncNet combined with visual embeddings for identity tracking. Our resulting multi-modal SD framework then combines the outputs from audio and audio-video modules by using a new overlap-based fusion strategy. It yields diarization error rates that are competitive with the existing state-of-the-art offline audio-visual methods while allowing us to process various audio-video streams, e.g., from internet or TV broadcasts, in real-time and with the same latency as for audio data processing. © 2023, The Authors. All rights reserved.

关键词： Embeddings

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Quantum communications feasibility tests over a UK-Ireland 224-km undersea link

arXiv

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arXiv 2023年

作者： Amies-King, Ben Schatz, Karolina P. Duan, Haofan Biswas, Ayan Bailey, Jack Felvinti, Adrian Winward, Jaimes Dixon, Mike Minder, Mariella Kumar, Rupesh Albosh, Sophie Lucamarini, Marco School of Physics Engineering & Technology York Centre for Quantum Technologies Institute for Safe Autonomy University of York YorkYO10 5FT United Kingdom euNetworks Fiber UK Limited 5 Churchill Place LondonE14 5HU United Kingdom Department of Electrical Engineering Computer Engineering and Informatics Cyprus University of Technology Limassol3036 Cyprus

The future quantum internet will leverage existing communication infrastructures, including deployed optical fibre networks, to enable novel applications that outperform current information technology. In this scenario, we perform a feasibility study of quantum communications over an industrial 224 km submarine optical fibre link deployed between Southport in the United Kingdom (UK) and Portrane in the Republic of Ireland (IE). With a characterisation of phase drift, polarisation stability and arrival time of entangled photons, we demonstrate the suitability of the link to enable international UK-IE quantum communications for the first time. © 2023, CC BY.

关键词： Quantum communication

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A deep transfer learning-based edge computing method for home health monitoring

arXiv

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arXiv 2021年

作者： Sufian, Abu You, Changsheng Dong, Mianxiong Department of Computer Science University of Gour Banga Malda India Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore Department of Sciences and Informatics Muroran Institute of Technology Hokkaido Japan

The health-care gets huge stress in a pandemic or epidemic situation. Some diseases such as COVID-19 that causes a pandemic is highly spreadable from an infected person to others. Therefore, providing health services at home for noncritical infected patients with isolation shall assist to mitigate this kind of stress. In addition, this practice is also very useful for monitoring the health-related activities of elders who live at home. The home health monitoring, a continuous monitoring of a patient or elder at home using visual sensors is one such non-intrusive sub-area of health services at home. In this article, we propose a transfer learning-based edge computing method for home health monitoring. Specifically, a pre-trained convolutional neural network-based model can leverage edge devices with a small amount of ground-labeled data and fine-tuning method to train the model. Therefore, on-site computing of visual data captured by RGB, depth, or thermal sensor could be possible in an affordable way. As a result, raw data captured by these types of sensors is not required to be sent outside from home. Therefore, privacy, security, and bandwidth scarcity shall not be issues. Moreover, real-time computing for the above-mentioned purposes shall be possible in an economical way. © 2021, CC BY-NC-ND.

关键词： computer vision

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Resource Slicing Strategy for Services Co-Existence in Wireless Train Communication Network

Resource Slicing Strategy for Services Co-Existence in Wirel...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Qiao Ren Siyu Lin Yuanxuan Li Shichao Li Linghe Kong Shahid Mumtaz Bo Ai School of Electronic and Information Engineering Beijing Jiaotong University Beijing China Locomotive and Car Research Institute China Academy of Railway Science Beijing China School of Information and Communication Guilin University of Electronic Technology Guilin China Information Systems Technology and Design Pillar Singapore University of Technology and Design Singapore Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Department of Applied Informatics Silesian University of Technology Akademicka Gliwice Poland Department of Engineering Nottingham Trent University Nottingham UK

Wireless train communication network (WLTCN) is a promising technology for intelligent rail vehicles. It is responsible for bearer of train control services (TCS) and passenger information services (PIS), with the latter mainly referring to multimedia services. The two services have notably different quality of service (QoS) requirements from traditional telecommunication services. To realize multiple services co-existence bearer with different quality of service (QoS) requirements in a single network, we propose a radio access network (RAN) slicing framework to fully utilize the bandwidth resource within a WLTCN in this paper. Based on the characteristics of TCS and PIS, the communications models for the two services are proposed. Next, the slicing strategy problem is formulated as the system bandwidth minimization problem, and then it is transformed into an equivalent problem as the non-convexity. We proposed a dual-decomposition based bandwidth allocation (DBA) algorithm to derive the closed-form expressions for the optimal resource allocation. Simulation results show that the proposed slicing strategy enables WLTCN to meet the QoS requirements for TCS and PIS with minimal bandwidth consumption.

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