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17th IEEE International Conference on Signal Processing, ICSP 2024

作者： Wang, Junfeng Cui, Yue Zhou, Mingzhang Sun, Haixin Liu, Lanjun Zhang, Ailing Tianjin University of Technology School of Integrated Circuit Science and Engineering Tianjin300384 China Mnr Key Laboratory of Southeast Coast Marine Information Intelligent Perception and Application China Tianjin Normal University College of Computer and Information Engineering Tianjin300387 China Xiamen University School of Information Science and Engineering Xiamen361005 China Ocean University of China College of Engineering Qingdao266100 China

ISBN: (纸本)9798350387384

Detecting the status of autonomous underwater vehicle, referred to hereinafter as an underwater target, is fundamental for successfully fulfilling cognition tasks or improving communication quality. In this article, we present a thorough study over the passive detection issue for multiple underwater targets emitting the linear frequency modulation signals. Specifically, hypothesis testing model, which comprises the signals received at the underwater detection node including periodic emission signals from the targets and additive noise, is firstly proposed for the practical scenarios. Then, the detection scheme has been investigated. Among this scheme, the behavior of the signals emitted by the underwater targets has been analyzed;and the primary aiming of the detection procedure, i.e., decision rule and its performance, has also been discussed and derived for the aforementioned scenarios. Towards the end, to confirm the advantages of our proposed studies, numerical simulation examples are carried out to examine the performance under different conditions. © 2024 IEEE.

关键词： Signal modulation

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Analysis of Feedback and Customer Satisfaction Parameters for Hospitality Industry-A Technology Intervention

Analysis of Feedback and Customer Satisfaction Parameters fo...

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2024 International Conference on Smart Devices, ICSD 2024

作者： Ramnarayan Yamsani, Nagendar Joshi, Girija Shankar Singh, Jasjit Nautiyal, Kshitij Kumar, Gaurav Uttaranchal University UIT CSE Department Dehradun India SR University School of Computer Science and Artificial Intelligence Warangal India Uttaranchal University Uttaranchal School of Computing Sciences Uttarakhand Dehradun India Concordia University Masters in Mechanical Engineering Canada Dev Bhoomi Uttarakhand University Dehradun India

ISBN: (纸本)9798350394412

Technologies are the patronage for the sustainable development and growth in the field of hospitality industry. Today's hotel visitors are accustomed to using remote keyless entry to open and lock their vehicles, placing food orders directly from a smartphone app, and using the technology to switch on the needful thing, add something to their shopping list, or to on the Television and music also. Many of these visitors also anticipate having the same frictionless experience while staying at hotels. Prior studies tended to be preoccupied with technological service innovation, leaving human-related service innovation relatively unexplored. TBSI (Technology Based Service and Innovation) can be examine in this study to develop the sustainable application and system can have the stronger role for the customer satisfaction and delight. For the hospitality business to flourish and grow quickly in the future, we now also need to know what the customers are saying. In this study, we focus on technology and how it may help the hotel sector grow based on client input. © 2024 IEEE.

关键词： Sales

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Tensor Graph Convolutional Network for Dynamic Graph Representation Learning 7

Tensor Graph Convolutional Network for Dynamic Graph Represe...

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7th International Symposium on Autonomous Systems, ISAS 2024

作者： Wang, Ling Yuan, Ye The School of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing400065 China The Chongqing Key Laboratory of Big Data and Intelligent Computing Chongqing Engineering Research Center of Big Data Application For Smart Cities Chongqing Institute of Green and Intelligent Technology Chinese Academy of Sciences Chongqing400714 China College of Computer and Information Science Southwest University Chongqing400715 China

ISBN: (纸本)9798350363173

Dynamic graphs (DG) represent evolving interactions between entities in various real-world scenarios. Many existing DG representation learning models employ a combination of graph convolutional networks and sequence neural networks to capture spatial-temporal dependencies. However, this hybrid approach often fails to effectively capture the spatial-temporal continuity inherent in DGs. In this paper, we propose a novel approach called the Tensor Graph Convolutional Network (TGCN) to learn DG representations within a unified convolution framework based on tensor products. Our approach is founded on two key principles: (a) representing DG information in tensor form, and (b) leveraging tensor product operations to design a graph convolutional network that simultaneously models spatial and temporal features. Experimental results on three real-world DG datasets demonstrate that our proposed model achieves state-of-the-art performance. © 2024 IEEE.

关键词： Tensors

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ABID: Attention-Based Bengali Image Description 3rd

ABID: Attention-Based Bengali Image Description

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3rd International Conference on Communication, Devices and Computing, ICCDC 2021

作者： Das, Bidyut Sekh, Arif Ahmed Majumder, Mukta Phadikar, Santanu Department of Information Technology Haldia Institute of Technology Haldia India School of Computer Science and Engineering XIM University Bhubaneswar India Department of Computer Science and Application University of North Bengal Darjeeling India Department of Computer Science and Engineering Maulana Abul Kalam Azad University of Technology West Bengal India

ISBN: (纸本)9789811691539

Image caption or description generation is a fundamental problem of artificial intelligence. It requires both knowledge, natural language processing, and computer vision together. It automatically produces description(s) from an image. The Bengali language is the fifth language spoken widely in the world. It is considered in many areas of research and development. Various established datasets are available in the literature for image caption generation in English since no such standard dataset exists for Bengali. This paper proposes a model for automatic image captioning in the Bengali language. This study uses a Bengali dataset to train the encoder–decoder neural network model. The proposed model trained with two descriptions per image and achieved a 0.67 BLEU-1 score. We expect that a far better result is obtained with a larger and more diverse dataset. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Neural network models

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Improving Search Engine Results Using AI Methods 3

Improving Search Engine Results Using AI Methods

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3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Katariya, Jitendra Kumar Geetha, B. Mahajan, Rupali A. Singh, Manpreet Yadav, Rakesh Kumar Vivek, V. Vivekananda Global University Department of Computer Science & Application Jaipur India Prince Shri Venkateshwara Padmavathy Engineering College Department of Science and Humanities Chennai127 India Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India Chitkara University Institute of Engineering and Technology Chitkara University Centre of Interdisciplinary Research in Business and Technology Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Computer Science and Engineering Karnataka Bangalore India

ISBN: (纸本)9798350319125

This paper examines how artificial Intelligence (AI) algorithms can be used to improve seek engine consequences. It outlines key terms, demanding situations, and opportunities related to AI -based totally search engine optimization. initial studies shows that AI-based totally tactics display promising ability to increase accuracy and relevancy in search engine consequences. AI strategies such as natural language processing (NLP), system getting to know (ML), and sentiment analysis are explored in element. additionally, the paper compares current answers that rent AI algorithms to conventional search engines and evaluates their performance, scalability, and applicability. ultimately, the paper discusses the destiny outlook of AI in seo and its potential implications for web users, corporations, and seeks engine developers. © 2023 IEEE.

关键词： algorithms developers engine potential strategies

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Predictive Sleep Disorder Modelling: Using Machine Learning with Lifestyle and Sleep Health Data

Predictive Sleep Disorder Modelling: Using Machine Learning ...

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Advances in Computing, Communication and Applied Informatics (ACCAI), International Conference on

作者： Mukesh Kumar Bilal Ahmed Hari Mohan Mishra Amit Kumar Jha Pushpendra Kumar Sikarwal Sahil Rampal Department of Computer Science and Engineering Chandigarh Group of Colleges Jhanjeri Mohali Punjab India School of Computer Application Lovely Professional University Phagwara Punjab India Department of Computer Science and Engineering JECRC university Jaipur Rajasthan India

ISBN: (数字)9798350389449

ISBN: (纸本)9798350389456

The Sleep Health and Lifestyle dataset was analyzed using different Machine Learning (ML) techniques in the study. The dataset contains information about a variety of sleeping patterns, health concerns, and lifestyle choices. The study incorporated various classification algorithms, including Light Gradient Boosting Machine (LGBM), AdaBoost, Random Forest (RF), Extra Trees, k-Neighbours Networks (k-NNs), Logistic Regression (LR), Gaussian Naive Bayes (GNB), and Gradient Boosting (GB).The results indicated that the GB classifier effectively and reliably predicted sleep-related disorders with a notable degree of precision. Furthermore, we acquired substantial comprehension of the variables that influence sleep disorders by analysing class distribution, and correlations, visualising categorical data, and conducting bivariate analysis. In essence, it highlights the effectiveness of ML approaches in precisely identifying sleep problems through the analysis of many lifestyle and health attributes. Other implemented approaches also provide some useful insights into the elements that contribute to sleep difficulties.

关键词： Correlation Computational modeling Null value Boosting Sleep apnea Data models Bayes methods

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BERT in Cognition for Learner

BERT in Cognition for Learner

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International Conference on Computing and Networking Technology (ICCNT)

作者： Souvik Ganguly Priyanka Chatterjee Kailash Pati Mandal School of Computer Science Inspiria Knowledge Campus Siliguri India Master in Computer Application Dr. B.C. Roy Engineering College Durgapur India Computer Science and Engineering National Institute of Technology Durgapur India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Profound subject knowledge is necessary for education to spark creative or formative projects and boost individual’s dynamism. Acquiring a magnificent education is crucial because it permits us to live completely, make wise decisions, and overcome obstacles in life. A learner’s academic journey is continued in early education, which also permits them to become more adept at discriminating between inequity and fairness and equips them for a broader spectrum of activities in higher education. Alongside superficial constraints like threats or financial crises, learners must compose a plethora of delightful and demanding activities in addition to their studies. Therefore, learners can experience moments of cognitive disorientation and progressively acquire cognitive ailments such as stress or depression, to name a couple. Thus, this research suggests a novel Bi-directional Encoder Representations from Transformer (BERT) method for ascertaining learners’ cognitive declines. This research utilizes the BERT-Base architecture, and the hyper-tuning of the hyperparameters is carried out by the innovative Tweaked Shuffled Frog Leaping Algorithm technique. Although there is a high need for language models these days, there are currently no specific language models that can reliably specify a learner’s cognitive deficits according to psychological inqueries. Thus, this work offers a novel strategy known as CogniBERT in response to this. Our approach confounds some of the weaknesses of the BERT methodology by choosing the right scaling factors during training. In terms of training, validation, and testing accuracies, the experimental result surpasses the other approaches, obtaining $\mathbf{9 9. 5 6 \%}, 98.97 \%$, and $99.29 \%$, respectively, when the suggested method is contrasted with a few state-of-the-art methods.

关键词： Training Psychology Bidirectional control Human factors computer architecture Depression Transformers Encoding Cognition Testing

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IoT based Smart wheelchair For Disabled Person

IoT based Smart wheelchair For Disabled Person

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Electrical Electronics and Computing Technologies (ICEECT), International Conference on

作者： Lalit Kumar Ajay Shriram Kushwaha Kartikeya Sherawat Zishan Siddique Department of Computer Application School of Computer Science & Engineering IILM University Greater Noida Uttar Pradesh India Department of Computer Science & Applications Sharda School of Enginering & Technology Sharda University Greater Noida Uttar Pradesh India

ISBN: (数字)9798350378092

ISBN: (纸本)9798350378108

Smart wheelchairs are revolutionizing mobility for disabled individuals, offering enhanced independence and improved quality of life. These advanced devices incorporate cutting-edge technologies like obstacle avoidance systems, voice control, and self-navigation capabilities, transforming the traditional wheelchair into an intelligent mobility solution. Obstacle avoidance systems utilize sensors to detect and avoid obstacles, ensuring safe navigation in complex environments. Voice control enables users to operate the wheelchair hands-free, providing greater convenience and control. Self-navigation capabilities allow the wheelchair to autonomously navigate to pre-programmed destinations, reducing user burden and enhancing independence. Smart wheelchairs also offer connectivity features, enabling remote monitoring and control by caregivers. This provides an added layer of safety and support for users, ensuring timely assistance when needed. The integration of these advanced technologies into smart wheelchairs is transforming mobility for disabled individuals, empowering them with greater independence, safety, and control over their movement. As smart wheelchair technology continues to evolve, the possibilities for enhanced mobility and improved quality of life for disabled individuals are limitless.

关键词： computer vision Three-dimensional displays Navigation Wheelchairs Speech recognition Software Safety Older adults Collision avoidance Intelligent sensors

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Personalized Confederation Training for Smart Iot Systems: A Cloud - Delivered Structure

Personalized Confederation Training for Smart Iot Systems: A...

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Advance Computing and Innovative Technologies in engineering (ICACITE), International Conference on

作者： Jitendra Kumar Katariya Nivesh Department of Computer Science Engineering Vivekananda Global University Department of Master of Computer Application Chandigarh School of Business Jhanjeri

The Internet of Things (IoT) has significantly impacted many facets of contemporary life, and several sophisticated IoT applications and services are already being developed. Recently, the concept of federated learning has been proposed in order to train a globally shared model on IoT devices utilising a large number of user-generated data samples while stopping data leak. Due to the widespread heterogeneities in device, statistics, and model in complex IoT contexts, traditional federated learning is not suitable for instant implementation. In this paper, we present a cloud-edge architecture for intelligent IoT applications that includes a customised federated learning framework. To address the heterogeneity worries in IoT conditions, we examine imaginative altered united learning calculations that could diminish the unfortunate results brought about by heterogeneities in various aspects. The advantages of edge registering empower smart IoT applications to meet the models for high handling pace and low inertness. At long last, we give a contextual investigation of human movement recognition in light of Web of Things to show the advantages of customisable combined learning for intelligent IoT applications.

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Isolated word-based spoken dialogue system using odia phones

Recent Advances in Computer Science and Communications

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Recent Advances in computer science and Communications 2021年第6期14卷 1912-1918页

作者： Swain, Basanta K. Mohanty, Sanghamitra Chowdhary, Chiranji L. Department of Computer Science & Engineering Government College of Engineering Kalahandi Bhawanipatna766002 India Department of Computer Science & Application Utkal University Bhubaneswar751004 India School of Information Technology and Engineering VIT University Vellore Tamil Nadu 632014 India

Aims: To develop Spoken Dialogue System in Indian language with Voice response and voice based biometric feature Background: Most of research works in spoken dialogue system are carried out in U.S. and Eu-rope and currently, few government funding projects on spoken dialogue system (SDS) are carried out in Indian academic institutes. Objective: We have tried to use our developed spoken language system to eliminate the desktop clutter. It is very normal tendency of computer users to place the most frequently used files, fold-ers, applications shortcuts on their computer’s desktop. Cluttering of desktop not only slows down the productivity of computer but also looks very messy and very difficult to find files as well. Therefore, we tried to use the spoken dialogue system to eliminate the desktop clutters in painless manner and the services are provided to the computer users by opening the files, folders and frequently used application of users in spoken command mode with voice response. Methods: In this research article, we have attempted to utilize an Indian spoken language for communication with spoken dialogue system. We have adopted a statistical machine learning algorithm called Hidden Markov Model for development of speech recognition engine. The speaker verification module is developed using fuzzy c-means algorithm. Speech synthesis is carried out using diphone corpus. Results: The speaker verification module has yielded satisfactory results with average accuracy of 66.2% using FCM algorithm. It is also seen that fundamental frequency and formant frequency car-ry the distinctive characteristics of speaker verification over Indian spoken language. The vital module of SDS i.e. speech recognition engine is developed by using HMM, a statistical algorithm. It is observed that word accuracy of ASR engine is 78.22 % and 62.31 % for seen and unseen users respectively. The voice response is given to the user in terms of synthesized speech. The audio quality of synthesiz

关键词： Hidden Markov models

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