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Network analysis and Throughput Estimation for MmWave Communication in an Autonomous vehicle 14

Network Analysis and Throughput Estimation for MmWave Commun...

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14th International conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Shravan, M. Sneha, B. Peroumal, vijayakumar Vellore Institute of Technology Chennai School of Electronics Engineering Chennai India

ISBN: (纸本)9798350335095

vehicular communication has numerous advantageous features including autonomy safety, communication skills with other vehicle or pedestrian or an infrastructure. mmWave communication in a type of wireless communication which comes under the 5th generation of wireless communication (5G), hat uses high frequencies ranges from 30 to 300 GHz, which is mainly known for its high data rates and very low latency. In this paper, using mmWave technology, how it can be used to communicate in a limited spectral boundary and pass the information to the neighboring vehicles for enhancements of vehicular safety. At present, the most common sensor used in vehicles is automotive radars and visual cameras and ultrasonic sensors. The major challenge associated with these sensors are limited sensing range (360 degree of view, low-light situation, communication with the infrastructure, etc.) and the limited ability to share the crucial situation with the neighboring cars. The vehicle connectivity has two potential benefits - firstly, if a suitable carrier frequency is chosen then cars can communicate in non-line-of sight conditions. Secondly, if a higher bandwidth is implemented, it can increase the data rate transmission between the vehicles, by which an "Intelligent connected autonomous vehicle"(ICAvs) can be created. The major advantage of the ICAvs is that they can work independently and train themselves in avoiding vehicle accidents caused by human errors. The simulation was illustrated with the help "Network Simulator -3"(NS-3) in ubuntu software. Five scenarios are taken, explain the possible v2v communication between the vehicles. The carrier frequency taken for consideration in 70GHz and a bandwidth of 100 GHz. The throughput was also calculated using NetSim tool by varying the distance between the base station and user equipment. © 2023 IEEE.

关键词： Autonomous vehicles

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Uncertainty Inspired Autism Spectrum Disorder Screening 26th

Uncertainty Inspired Autism Spectrum Disorder Screening

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26th International conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)

作者： Zhang, Ying Huang, Yaping Qi, Jiansong Zhang, Sihui Tian, Mei Tian, Yi Beijing Jiaotong Univ Beijing Key Lab Traff Data Anal & Min Beijing Peoples R China

ISBN: (纸本)9783031439032;9783031439049

People with autism spectrum disorder (ASD) show distinguishing preferences for specific visual stimuli compared to typically developed (TD) individuals, opening the door for objective and quantitative screening by eye-tracking data analysis. However, existing eye-tracking-based ASD screening approaches often assume that there are no individual differences and that all stimuli contribute equally to the prediction of an ASD. Consequently, a fixed number of images are usually selected by a pre-defined strategy for further training and testing, ignoring the distinct characteristics of various subjects viewing the same image. To address the aforementioned difficulties, we propose a novel Uncertainty-inspired ASD Screening Network (UASN) that dynamically modifies the contribution of each stimulus viewed by different subjects. Specifically, we estimate the uncertainty of each stimulus by considering the variation between the subject's fixation map and the ones of the two clinical groups (i.e., ASD and TD) and further utilize it for weighting the training loss. Besides, to reduce the diagnosis time, instead of the shuffle-appeared mode of image viewing, we propose an uncertainty-based personalized diagnosis method to dynamically rank the viewing images according to the preferences of different subjects, which can achieve high prediction accuracy with only a small set of images. Experiments demonstrate the superior performance of our proposed UASN.

关键词： ASD Screening Eye-tracking data Uncertainty

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8th International conference on Modelling and Development of Intelligent Systems, MDIS 2022

8th International Conference on Modelling and Development of...

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8th International conference on Modelling and Development of Intelligent Systems, MDIS 2022

ISBN: (纸本)9783031270338

The proceedings contain 21 papers. The special focus in this conference is on Modelling and Development of Intelligent Systems. The topics include: Morphology of Convolutional Neural Network with Diagonalized Pooling;challenges and Opportunities in Deep Learning Driven Fashion Design and Textiles Patterns Development;feature Selection and Extreme Learning Machine Tuning by Hybrid Sand Cat Optimization Algorithm for Diabetes Classification;Enriching SQL-Driven data exploration with Different Machine Learning Models;analytical Solution of the Simplest Entropiece Inversion Problem;latent Semantic Structure in Malicious Programs;innovative Lattice Sequences Based on Component by Component Construction Method for Multidimensional Sensitivity analysis;on an Optimization of the Lattice Sequence for the Multidimensional Integrals Connected with Bayesian Statistics;numerical Optimization Identification of a Keller-Segel Model for Thermoregulation in Honey Bee Colonies in Winter;gaze Tracking: A Survey of Devices, Libraries and Applications;gradient Optimization in Reconstruction of the Diffusion Coefficient in a Time Fractional Integro-Differential Equation of Pollution in Porous Media;Flash Flood Simulation Between Slănic and vărbilău Rivers in vărbilău village, Prahova County, Romania, Using Hydraulic Modeling and GIS Techniques;group Decision-Making Involving Competence of Experts in Relation to Evaluation Criteria: Case Study for e-Commerce Platform Selection;Transparency and Traceability for AI-Based Defect Detection in PCB Production;tasks Management Using Modern Devices;a Method for Target Localization by Multistatic Radars;Intrusion Detection by XGBoost Model Tuned by Improved Social Network Search Algorithm;bridging the Resource Gap in Cross-Lingual Embedding Space;classification of Microstructure Images of Metals Using Transfer Learning.

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Emotion Recognition in Tweets using Optimized Ensemble Classifiers 7

Emotion Recognition in Tweets using Optimized Ensemble Class...

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7th International conference on Communication and Electronics Systems, ICCES 2022

作者： Kavitha, D.N.S.B. Reddy, P.v.G.D. Prasad Rao, K. venkata Andhra University Department of Computer Science and Systems Engineering Visakhapatnam India

ISBN: (数字)9781665496346

ISBN: (纸本)9781665496346

The development of superior recognition/ classification techniques is essential for real-time Natural Language Processing (NLP) applications. Sentiment analysis (SA) is a task of NLP that aims to extract the sentiments/ opinions of the people from texts. In addition, very recent SA techniques start to integrate the data from text, speech, and other modalities such as visual data. Effective computing techniques and SA techniques are the two keys to the development of Artificial Intelligence (AI) such as human computer interaction. This article presents the investigations on sentiment classification of political tweets about an individual on Twitter using optimized Ensemble classifier under different training rates. From the analysis done through simulation, it is noted that Ensemble Classifier (EC) provides better classification accuracy than that of traditional machine learning (ML) classifiers. © 2022 IEEE.

关键词： Human computer interaction

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QeNoBi: A System for QuErying and miNing Behavioral Patterns 37

QeNoBi: A System for QuErying and miNing Behavioral Patterns

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37th IEEE International conference on data Engineering (IEEE ICDE)

作者： Chibah, Abdelouahab Amer-Yahia, Sihem Berti-Equille, Laure Univ Grenoble Alpes CNRS St Martin Dheres France IRD ESPACE DEV Montpellier France

ISBN: (纸本)9781728191843

We demonstrate QeNoBi, a system for mining and querying customer behavioral patterns. QeNoBi combines an interactive visual interface, on-demand mining, and efficient top-k processing, to provide the exploration of customer behavior over time. QeNoBi relies on two distinct data models: a customer-centric graph that represents customers with similar purchasing behaviors and is annotated with a change algebra to reflect their behavior evolution, and product-centric time series that reflect the evolution of customer purchases over time. Users can query both representations along three dimensions: shape (the sketched trend of the behavior), scope (the set of customers/products of interest), and time granularity. QeNoBi provides a holistic behavior exploration capability by allowing users to seamlessly switch between customer-centric and product-centric views in a coordinated manner, thereby catering to various needs. A demonstration of QeNoBi is available at https://***/2HlcO3S.

关键词： visualization Shape Algebra conferences Time series analysis Switches Market research

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Optimizing Feature Extraction for Website visuals: A Comparative Study of AlexNet and Inception v3

Optimizing Feature Extraction for Website Visuals: A Compara...

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International conference on Cyber and IT Service Management (CITSM)

作者： Arif Mu'amar Wahid Taqwa Hariguna Giat Karyono Magister of Computer Science Universitas Amikom Purwokerto Purwokerto Indonesia Magister of Computer Science and Information System Department Universitas Amikom Purwokerto Purwokerto Indonesia Magister of Computer Science and Informatics Department Universitas Amikom Purwokerto Purwokerto Indonesia

ISBN: (数字)9798331528799

ISBN: (纸本)9798331528805

This study investigates the feature extraction capabilities of two prominent convolutional neural network (CNN) architectures, Inception v3 and AlexNet, in the context of website visuals. With the growing need for automated visual data analysis on the web, effective feature extraction is critical for tasks such as image classification, object detection, and visual content analysis. Inception v3 and AlexNet were selected due to their distinct architectural approaches and widespread use in various computer vision applications. The research employed a controlled experimental design, utilizing a dataset of website visuals collected from platforms like Themeforest. data preprocessing included image resizing, normalization, and augmentation techniques to enhance model robustness. Both models were fine-tuned on the specific dataset to adapt their pretrained weights from ImageNet to the unique characteristics of website visuals. Performance metrics were used to evaluate the models' effectiveness, including precision, recall, F1 score, Mean Average Precision (MAP), and Normalized Discounted Cumulative Gain (NDCG). Results indicated that AlexNet outperformed Inception v3 in precision (0.7062 vs. 0.6860) and recall (0.5914 vs. 0.0506), highlighting its efficiency and suitability for more straightforward feature extraction tasks with lower computational costs. In contrast, Inception v3 exhibited superior potential in capturing complex visual patterns but struggled with computational efficiency, as evidenced by its significantly longer inference time (222.9552 seconds compared to 63.2978 seconds for AlexNet). The findings underscore the importance of model selection based on specific application requirements, such as prioritizing speed or depth of feature extraction. Recommendations for practitioners include leveraging AlexNet for resource-constrained environments and opting for Inception v3 when handling complex, multi-scale visual data. Future research could explore additional

关键词： Measurement visualization Adaptation models Computational modeling Computer architecture Feature extraction Robustness data models Computational efficiency Convolutional neural networks

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Design of a University Book Push System Based on Big data 23

Design of a University Book Push System Based on Big Data

引用

Proceedings of the 2023 4th International conference on Computer Science and Management Technology

作者： Liqiang Sheng Hui Xia Xiangquan Li School of Information Engineering Jingdezhen University China

ISBN: (纸本)9798400709517

In response to the existing university book recommendation systems that mostly recommend readers based on library resources and lack exploration of recommended books, this paper proposes a system service architecture that accurately pushes both readers and libraries simultaneously. The system is designed using technologies such as web spiders, big data, NLP, and visual analysis. The system integrates reader data entry, web crawler, user profile, book similarity measurement, and intelligent push functions. Book managers can use the system to push books accurately and discover recommended books. The system fully utilizes book attribute data and reader attribute data, avoiding common cold start issues in recommendation systems, and providing support for improving the service level of the library and scientifically allocating collection resources.

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EmoGeoCity: Interactive visual exploration of City’s Historical and Cultural Evolution Based on Emotional Geography

EmoGeoCity: Interactive Visual Exploration of City’s Histor...

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Pacific (formerly Asia-Pacific APvIS) visualization Symposium

作者： Yutong Yang Yinuo Liu Qishuo Bai Tianyi Zhou Ziduo Ye Xiaoju Dong SJTU Paris Elite Institute of Technology Shanghai Jiao Tong University China Department of Computer Science and Engineering Shanghai Jiao Tong University China School of Design Shanghai Jiao Tong University China

ISBN: (数字)9798350393804

ISBN: (纸本)9798350393811

A city’s history and culture studies involves understanding the literary works and historical events that have shaped the city’s identity. Increased availability of quantitative historical data has provided new opportunities. Taking Nanjing as an example, this paper proposes EmoGeoCity, a visual analytics system to study a city’s cultural and historical evolution, through the use of digital humanities methods and emotional geography. The system incorporates sentiment analysis into historical research to quantify the emotional content of works and synthesize an overall emotion trend within a specific location. A dynamic emotional map, integrating locations, works, and events, enables a macroscopic observation of city emotions over time. An emotional polyline is designed to provide a microscopic interpretation of the emotion trend of a single location. exploration through the system reveals the evolution of the city from an emotional geographic perspective, which gives insights for humanities researchers studying a city’s history and literature, as well as for the general public interested in gaining knowledge on historical sites. Case and user studies illustrate the effectiveness and usability of our system.

关键词： Sentiment analysis visual analytics Microscopy Urban areas Knowledge graphs Market research History

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Clover Connections: visualising Character Dynamics in Novels for Non-Experts 23

Clover Connections: Visualising Character Dynamics in Novels...

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Proceedings of the 35th Australian Computer-Human Interaction conference

作者： Natalie House Andrew Johnston University of Technology Sydney Australia

ISBN: (纸本)9798400717079

Many literature enthusiasts join communities to discuss their favourite fictional characters and novels, but meaningful insights may be slow to achieve and share when attempting to recall or verify the textual basis of their personal perspectives. Information visualisations can present text-derived data to make its summarisation and exploration both accessible and intuitive, yet visualisations of literary works are mostly tailored to expert workflows. This design study addresses this gap, comprehensively detailing our process of uncovering the tasks, data, and visual design requirements to implement Clover Connections, a visualisation of text-derived data for non-experts. Its layout features clover-shaped glyphs, storylines, and arcs to visually represent and connect temporal, social and personal data on characters in novels, which we demonstrate using datasets built from two popular novels. A formative user evaluation study with non-expert participants showed Clover Connections supports multiple general character analysis tasks, and provided qualitative insights that encourage future work.

关键词： design study fictional characters non-expert users storyline visualisation text data abstraction visual encodings

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Harnessing Energy of M-ary Hopfield Neural Network for Connectionist Temporal Sequence Decoding 1

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9th International conference on Mining Intelligence and Knowledge exploration, MIKE 2021

作者： Ladwani, vandana M. Ramasubramanian, v. International Institute of Information Technology - Bangalore Bangalore India PES University Bangalore India

ISBN: (数字)9783031215179

ISBN: (纸本)9783031215162

Sequence decoding is the core component of systems that deal with sequence alignment problems like continuous speech recognition, visual scene labelling, multimedia storage and retrieval. In this paper, we address the problem of connectionist temporal sequence decoding in the context of movie sequence data. We present a novel decoding algorithm and associated system which harnesses the energy of an extended M-ary Hopfield Neural Network (MHNN) to decode movie sequence data. This is a first of its kind approach using the Hopfield associative memory based connectionist framework to solve the sequence alignment problem. We demonstrate with experiments the robustness of the proposed algorithm and system to handle temporal variability of the input sequence which is very crucial for connectionist sequence decoding system. © 2022, Springer Nature Switzerland AG.

关键词： Decoding

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