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SinhaLearn: NLP, CNN, and OCR Based Data Driven Approach for Enhancing Sinhala Proficiency of Grade 5 Scholarship Students

SinhaLearn: NLP, CNN, and OCR Based Data Driven Approach for...

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Moratuwa Engineering Research conference (MERCon)

作者： Juliana V Francis Yasiru L Bellanavithana Thisal K Pulasinghe Rashmika D Silva Samadhi Rathnayake Supipi V Karunathilaka Department of Computer Science Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (数字)9798331529048

ISBN: (纸本)9798331529055

The Sinhala language, deeply rooted in Pali and Sanskrit, holds immense cultural significance for the Sinhalese community in Sri Lanka. However, its intricate morphology and diglossic nature, where written and spoken forms diverge, pose significant challenges. In response, we present “SinhaLearn” an automated system designed specifically to enhance Sinhala language proficiency for the Grade 5 Scholarship examination domain. Our system leverages advanced Natural Language processing algorithms, optical Character Recognition technology, Convolutional Neural Networks, and Part-ofSpeech tagging. Key functionalities include Sinhala Handwriting Capturing and Recognition, real-time error detection and correction in spelling and grammar within Sinhala Present Tense sentences, simplified explanations for complex Sinhala vocabulary aligned with the Grade 5 curriculum, and automated assessment of handwritten responses with instant feedback and scoring. Notably, informed by a comprehensive literature review, our research has made significant improvements by blending rule-based methods with hybrid components, effectively addressing critical gaps in the field. While existing systems often concentrate on singular functionalities such as spelling analysis, grammar analysis, dictionary functions, or content display, our “SinhaLearn” system provides a holistic solution by integrating these aspects. This comprehensive approach sets a new benchmark for automated systems in Sinhala language proficiency.

关键词： Vocabulary Handwriting recognition Scholarships optical character recognition Morphology Tagging Real-time systems Grammar Convolutional neural networks Global communication

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Carrier Phase Recovery Estimation algorithms in optical Coherent QPSK Communication System

Carrier Phase Recovery Estimation Algorithms in Optical Cohe...

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2021 International conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2021

作者： Lalu, Wilver Alvarez, Bryril Cruz, Christian Dela Lauan, Lea Trinos, Jerico Yanza, Ralph Anthony Weng, Cheong Hao Tan, Gerhard Cruz, John Dela Polytechnic University of the Philippines Sta. MesaManila Philippines Technical University of Munich Germany

ISBN: (纸本)9781665425032

Increased data rate demand, driven by various Internet applications exponential growth of electronics processing speeds were drivers behind this coherent optical communication. optical Fiber sends out pulses of light to transmit information from one place to another. When relaying signals over long distances, light is just meant to allow mechanically coded signals to be visible to one another. Pulses of light can carry information by modulating electromagnetic carriers. Presence of Laser phase noise (LPN), induced by the signal transmission as well as by the local oscillator (local oscillator phase noise), causes fluctuation in intensity and laser output electrical field deviations that leads to degraded Signal-To-Noise Ratio (SNR). In a Coherent transmission system, it is unavoidable to suffer from these phase noise problems which is quite common to experience. Thus, carrier phase recovery (CPR) method is used in coherent systems where LPN is present. In this research, evaluation of relationship between the symbol error rate (SER) and input power in two different carrier phase recovery estimate (CPE) algorithms in optical coherent QPSK optical communication system were studied. As a result, based on the simulations done we can conclude that pilot-Aided feedforward recovery is the best algorithm in terms of SER over input power for the two algorithms. © 2021 IEEE.

关键词： Quadrature phase shift keying

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An IoT-based Deep Belief Network in Intrusion Detection System using Butterfly Optimization

An IoT-based Deep Belief Network in Intrusion Detection Syst...

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International conference on Communications and Signal processing

作者： Aswathy K Cherian M. Vaidhehi M Arshey Serin V Simpson J Briskilal Astitva Singh Department of Computing Technologies SRM Institute of Science and Technology Kattankulathur Chennai India Department of AI & DS SCMS School of Engineering and Technology Ernakulam Kerala Department of Computer Science and Technology Madanapalle Institute of Technology & Science Madanapalle Chittoor Andhra Pradesh India

ISBN: (数字)9798350353068

ISBN: (纸本)9798350353075

Rapid technological advancements in the communication and internet industries have led to a huge increase in network scale and data volume. Network security is having a hard time identifying attacks as new threats are being created. Additionally, you can’t overlook the possibility of unauthorized users trying to attack the network in various methods. Numerous technologies, such as an intrusion detection system, can be utilized to protect the network from potential threats (IDS). The collecting and dissemination of data by Internet-connected devices is referred to as the “Internet of Things” (IoT). There are now more privacy and security problems due to the proliferation of Internet connections and the introduction of new technologies like the Internet of Things (IoT). IoT incursions are becoming increasingly complex and numerous as a result of the proliferation of connected devices. Companies are boosting their investment in research and development in order to better detect these threats. In this research, Deep Belief Network (DBN) and Butterfly Optimization Algorithm (BOA) Intrusion Detection systems (IDS) are proposed for detecting Io T network assaults. In order to minimize information leakage on the test data, the UNSW-NB15 dataset was normalized using the Absolute Maximum Scaling (AMS) approach in the first stage of this study process. This dataset contains a mixture of current assaults and typical network traffic, categorized into nine different attack types. The next step was to use Principal Component Analysis to reduce the dimensionality (PCA). Last but not least, results showed that DBN-BOA was superior to other IoT intrusion detection systems in terms of accuracy and speed.

关键词： Intrusion detection Training data Signal processing algorithms Telecommunication traffic Network security Data models Internet of Things

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Design of A Distributed Intrusion Detection System for Streaming Data in IoT Environments

Design of A Distributed Intrusion Detection System for Strea...

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International conference on Optimization and Applications (ICOA)

作者： Souad Atbib Chaimae Saadi Habiba Chaoui Advanced Systems Engineering Laboratory (ISA) National School of Applied Sciences Kenitra Morocco Laboratory of Systems Analysis Information Processing and Industrial Management (LASTIMI) EST Salé University Mohamed V Salé Morocco

Nowadays, IoT devices produce a large amount of streaming data that requires real-time analysis to ensure its security. Traditional security solutions are no longer sufficient to counter recent IoT attacks and to analyze the huge amount of data. In recent years, intrusion detection systems have been the subject of much research to evaluate their performance in detecting intrusions in IoT, especially since they are based on Artificial Intelligence and allow real-time intrusion detection. In this paper, we present the architecture of an intrusion detection system for streaming data analysis. We implemented our IDS in a Fog computing architecture and developed using Apache Spark. We applied several machine-learning algorithms to the NF-ToN-IoT-v2 dataset, and the results were promising.

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Decision Transformer for IRS-Assisted systems with Diffusion-Driven Generative Channels

Decision Transformer for IRS-Assisted Systems with Diffusion...

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IEEE International conference on Communications in China (ICCC)

作者： Jie Zhang Jun Li Zhe Wang Yu Han Long Shi Bin Cao School of Electronic and Optical Engineering Nanjing University of Science and Technology Nanjing China School of Information Science and Engineering Southeast University Nanjing China School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China National Mobile Communications Research Laboratory Southeast University Nanjing China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798350378412

ISBN: (纸本)9798350378429

In this paper, we propose a novel diffusion-decision transformer (D2T) architecture to optimize the beamforming strategies for intelligent reflecting surface (IRS)-assisted multiple-input single-output (MISO) communication systems. The first challenge lies in the expensive computation cost to recover the real-time channel state information (CSI) from the received pilot signals, which usually requires prior knowledge of the channel distributions. To reduce the channel estimation complexity, we adopt a diffusion model to automatically learn the mapping between the received pilot signals and channel matrices in a model-free manner. The second challenge is that, the traditional optimization or reinforcement learning (RL) algorithms cannot guarantee the optimality of the beamforming policies once the channel distribution changes, and it is costly to resolve the optimized strategies. To enhance the generality of the decision models over varying channel distributions, we propose an offline pre-training and online fine-tuning decision transformer (DT) framework, wherein we first pre-train the DT offline with the data samples collected by the RL algorithms under diverse channel distributions, and then fine-tune the DT online with few-shot samples under a new channel distribution for a generalization purpose. Simulation results demonstrate that, compared with retraining RL algorithms, the proposed D2T algorithm boosts the convergence speed by 3 times with only a few samples from the new channel distribution while enhancing the average user data rate by 6%.

关键词： Array signal processing Simulation Channel estimation Reinforcement learning MISO communication Transformers Diffusion models

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Mail Sorting Vehicle System Based on Visible Light Control 2021

Mail Sorting Vehicle System Based on Visible Light Control

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2nd International conference on Artificial Intelligence and information systems (ICAIIS )

作者： Wei, Shuyi Xing, Dongyuan Zhang, Lilong Zhang, Xiuxia North Minzu Univ Sch Elect & Informat Engn Yinchuan Ningxia Peoples R China Xi An Jiao Tong Univ Sch Mech Engn Xian Peoples R China

ISBN: (纸本)9781450390200

With the development of optical communication technology, it's application was more and more extensive. Researchers had proposed a new type of optical communication technology, which connected the high-speed internet wire device to LED lighting device, LED as a signal generator was used for indoor wireless access to the local area network, using the light emitted by the LED as the carrier wave, the drive circuit modulated the network data to the visible light emitted by LED. LED was switched on and off at a frequency that the human eye couldn't perceive, and a light pulse signal carrying information was sent out, the light signal of LED was sent out with an electrical signal. After transmission through atmospheric channel, the receiving end converts the optical pulse signal into electrical pulse signal through diode and other photosensitive devices, and then the original transmission information of demodulation ended through circuit processing, so as to realize the function of communication. In this paper the design of a mail sorting vehicle system based on visible light control was introduced. The principle was this new type of optical communication technology. The mail sorting vehicle system controlled by LED visible light consists of four parts: visible light communication system, light-controlled mail car system, server and client. It could make the logistics sorting and handling system more intelligent and modern, for managers, enterprises, units to provided better decision-making and management basis.

关键词： optical communication mail sorting LED lighting

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PACE: pacing operator learning to accurate optical field simulation for complicated photonic devices 24

PACE: pacing operator learning to accurate optical field sim...

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Proceedings of the 38th International conference on Neural information processing systems

作者： Hanqing Zhu Wenyan Cong Guojin Chen Shupeng Ning Ray T. Chen Jiaqi Gu David Z. Pan The University of Texas at Austin Arizona State University

ISBN: (纸本)9798331314385

Electromagnetic field simulation is central to designing, optimizing, and validating photonic devices and circuits. However, costly computation associated with numerical simulation poses a significant bottleneck, hindering scalability and turnaround time in the photonic circuit design process. Neural operators offer a promising alternative, but existing SOTA approaches,NeurOLight, struggle with predicting high-fidelity fields for real-world complicated photonic devices, with the best reported 0.38 normalized mean absolute error in NeurOLight. The interplays of highly complex light-matter interaction, e.g., scattering and resonance, sensitivity to local structure details, non-uniform learning complexity for full-domain simulation, and rich frequency information, contribute to the failure of existing neural PDE solvers. In this work, we boost the prediction fidelity to an unprecedented level for simulating complex photonic devices with a novel operator design driven by the above challenges. We propose a novel cross-axis factorized PACE operator with a strong long-distance modeling capacity to connect the full-domain complex field pattern with local device structures. Inspired by human learning, we further divide and conquer the simulation task for extremely hard cases into two progressively easy tasks, with a first-stage model learning an initial solution refined by a second model. On various complicated photonic device benchmarks, we demonstrate one sole PACE model is capable of achieving 73% lower error with 50% fewer parameters compared with various recent ML for PDE solvers. The two-stage setup further advances high-fidelity simulation for even more intricate cases. In terms of runtime, PACE demonstrates 154-577x and 11.8-12x simulation speedup over numerical solver using scipy or highly-optimized pardiso solver, respectively. We open sourced the code and complicated optical device dataset at https://***/zhuhanqing/PACE-Light.

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Experimental verification of EGN model in 11-THz C+L broadband 400G real-time transmission with digital sub-carrier multiplexing 13

Experimental verification of EGN model in 11-THz C+L broadba...

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13th International conference on information Optics and Photonics, CIOP 2022

作者： Tang, Rui Zhao, Xin Chen, Huan Du, Yuting Shi, Hu Feng, Zhenhua China Academy of Information and Communication Technology Beijing100191 China State Key Laboratory of Mobile Network and Mobile Multimedia Technology and WDM System Department of ZTE Corporation Wuhan430223 China

ISBN: (纸本)9781510660632

To support high-quality network plan, reliable operation and efficient service provisioning, the quality of transmission estimation (QoT-E) tool, which predicts the penalty of transmission impairments, is highly required. Among these channel impairments, non-linear-interference noise (NLIN) in high-speed, large-capacity and long-reach transmission systems with advanced modulation formats and powerful digital signal processing (DSP) algorithms is complex and difficult to be accurately estimated, thus an precise and practical model of NLIN is desperately desired as one of the key components for QoT-E. Nowadays, 400Gb/s/ch combined with multi-band transmission has become a research hotspot achieving larger capacity without deploying new fibers. However, in this multi-band scenario, the interaction of NLIN with the stimulated Raman scattering (SRS) must be properly considered. In this paper, an equivalent attenuation coefficient assisted enhanced Gaussian noise (EGN) model which considers the impact of SRS on the nonlinear interference in C+L band, is proposed and experimentally verified. The real-time experiments of 400Gb/s/ch transmission system in 11-THz C+L band over 14x75 km G.652 and 14x100 km G.654E fiber links are carried out using coherent transponders modulated with 91.6 GBaud digital sub-carrier multiplexing (DSCM) based probabilistic constellation shaping (PCS) 16QAM format, achieving a net spectral efficiency of 4 bit/s/Hz. The experimental results show that the maximum deviation of NLI induced OSNR penalty at different frequencies across the whole C+L band is found to be less than 0.22 dB. This work could potentially provide an effective and accurate tool for QoT-E estimation in broadband C+L or even multiband systems, paving the way for intelligent management and control of high-capacity and flexible optical networks. © 2022 SPIE.

关键词： Stimulated Raman scattering

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Multi-resistant Bacterial Infection Surveillance using a Graph Database with Spatio-temporal information 14

Multi-resistant Bacterial Infection Surveillance using a Gra...

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14th International Joint conference on Biomedical Engineering systems and Technologies (BIOSTEC) / 14th Int Conf on Bio-inspired systems and Signal processing (BIOSIGNALS) / 14th Int Conf on Biomedical Electronics and devices (BIOdevices)

作者： Pujante, Lorena Campos, Manuel Juarez, Jose M. Canovas-Segura, Bernardo Morales, Antonio Univ Murcia Fac Comp Sci AIKE Res Grp Murcia Spain Int Res Inst Murcia Spain Murcian Biohlth Inst IMIB Arrixaca Murcia Spain

ISBN: (纸本)9789897584909

Some of epidemiologists' efforts in dealing with multi-resistant bacterial infections acquired in healthcare settings focus on tracing patient's activities, carrying out a contact analysis, and identifying the main risk factors that lead the appearance of these infections. Most contact analysis studies assume information is stored in conventional relational databases. To date, little attention has been paid to other storage paradigms. This paper explores the potential of graph databases to establish the complex relations required to compute contact analysis. We discuss the advances in modelling of the temporal and the spatial information of the Electronic Health Record that has to be introduced in the graph database. In this position paper we propose three points for discussion: advances in formal modelling, specific algorithms for graph analysis, and visualisation tools.

关键词： Graph Analytics Graph Database Epidemiology Infection Surveillance

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GPU-based real-time estimation of phase and delay of PCAL signal

GPU-based real-time estimation of phase and delay of PCAL si...

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Signal, information and Data processing (ICSIDP), IEEE International conference on

作者： Xue Jian Li Hong Ma Yi Wen Jiao Yu Xin Wang Yu Ke Song Hao Feng Qi Min Chen Department of Electronic and Optical Engineering Key Laboratory of Intelligent Space TTC&O Space Engineering University Beijing China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

In order to meet the requirement of high-efficiency phase delay estimation of PCAL signal in the digital baseband converter (DBBC) equipment link for deep space measurement and control, we propose a GPU-based PCAL signal phase delay estimation method with parallel computing technology, combining the method with FFT and FFT to solve the problem of low computational efficiency in the traditional PCAL signal phase delay estimation method based on the fast Fourier transform (FFT), and then propose a graphics processing unit(GPU)-based PCAL signal phase delay estimation method with parallel computing technology. Firstly, to address the problem of low computational efficiency in the traditional fast Fourier transform (FFT)-based phase delay estimation of PCAL signals, a GPU-based phase delay estimation method for PCAL signals is proposed by combining this method with parallel computing technology. Experimental validation of the method is carried out, and a large number of experimental results show that the GPU-based PCAL signal phase delay estimation method improves the acceleration ratio by at least one order of magnitude, and realizes the real-time estimation of the phase delay of PCAL signals with bandwidths of 32 MHz or less, signal intervals of 1 MHz, and quantization bit number of 8 bit. In addition, the designed real-time system is also applicable to the link calibration of other inverter devices.

关键词： Phased arrays Fast Fourier transforms Phase estimation Graphics processing units Delay estimation Life estimation Parallel processing Real-time systems Calibration Computational efficiency

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