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3rd International Conference on Artificial Intelligence For Internet of Things, AIIoT 2024

作者： Roshan Ahmed, N. Shridevi, S. Vellore Institute of Technology School of Computer Science and Engineering Chennai India Vellore Institute of Technology Center for Advanced Data Science Chennai India

ISBN: (纸本)9798350372120

Text-based Statistical steganography is one of the most non-human detectable methods of embedding hidden messages in plain text format which is useful in concealing information. Steganalysis is its counter, the process of detecting if a text has any encrypted data in it. This paper applies quantum computing to create DeepKet Embedding, which optimizes the space requirements for word embeddings similar to Word2Vec. DeepKet is benchmarked against existing embedding layers and a significant size reduction is achieved while maintaining accuracy for steganalysis. © 2024 IEEE.

关键词： Embeddings

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Realizing n-type CdSb with promising thermoelectric performance

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Journal of Materials science & Technology 2023年第13期144卷 54-61页

作者： Peng Zhao Honghao Yao Shizhen Zhi Xiaojing Ma Zuoxu Wu Yijie Liu Xinyu Wang Li Yin Zongwei Zhang Shuaihang Hou Xiaodong Wang Siliang Chen Chen Chen Xi Lin Haoliang Liu Xingjun Liu Feng Cao Qian Zhang Jun Mao School of Materials Science and Engineering and Institute of Materials Genome&Big DataHarbin Institute of Technology(Shenzhen)Shenzhen 518055China School of Science Harbin Institute of Technology(Shenzhen)Shenzhen 518055China State Key Laboratory of Advanced Welding and Joining Harbin Institute of TechnologyHarbin 150001China

Realizing high performance in both n-type and p-type materials is essential for designing efficient ther-moelectric ***,the doping bottleneck is often encountered,i.e.,only one type of conduction can be *** one example,p-type CdSb with high thermoelectric performance has been discovered for several decades,while its n-type counterpart has rarely been *** this work,the calculated band structure of CdSb demonstrates that the valley degeneracy is as large as ten for the conduction band,and it is only two for the valence ***,the n-type CdSb can potentially realize an ex-ceptional thermoelectric ***,the n-type conduction has been successfully real-ized by tuning the stoichiometry of *** further doping indium at the Cd site,an improved room-temperature electron concentration has been *** modeling predicts an optimal electron con-centration of∼2.0×1019 cm−3,which is higher than the current experimental ***,future optimization of the n-type CdSb should mainly focus on identifying practical approaches to optimize the electron concentration.

关键词： Thermoelectric materials n-type CdSb Indium doping Band degeneracy

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Angle-uniform parallel coordinates

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Computational Visual Media 2023年第3期9卷 495-512页

作者： Kaiyi Zhang Liang Zhou Lu Chen Shitong He Daniel Weiskopf Yunhai Wang School of Computer Science and Technology Shandong UniversityQingdao 266237China National Institute of Health Data Science Peking UniversityBeijing 100191China Visualization Research Center(VISUS) University of Stuttgart70569 StuttgartGermany

We present angle-uniform parallel coordinates,a data-independent technique that deforms the image plane of parallel coordinates so that the angles of linear relationships between two variables are linearly mapped along the horizontal axis of the parallel coordinates *** being a common method for visualizing multidimensional data,parallel coordinates are ineffective for revealing positive correlations since the associated parallel coordinates points of such structures may be located at infinity in the image plane and the asymmetric encoding of negative and positive correlations may lead to unreliable *** address this issue,we introduce a transformation that bounds all points horizontally using an angleuniform mapping and shrinks them vertically in a structure-preserving fashion;polygonal lines become smooth curves and a symmetric representation of data correlations is *** further propose a combined subsampling and density visualization approach to reduce visual clutter caused by *** method enables accurate visual pattern interpretation of data correlations,and its data-independent nature makes it applicable to all multidimensional *** usefulness of our method is demonstrated using examples of synthetic and real-world datasets.

关键词： parallel coordinates multidimensional data deformation correlations

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Adversarial Machine Learning for Social Good: Reframing the Adversary as an Ally

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第9期5卷 4322-4343页

作者： Al-Maliki, Shawqi Qayyum, Adnan Ali, Hassan Abdallah, Mohamed Qadir, Junaid Hoang, Dinh Thai Niyato, Dusit Al-Fuqaha, Ala Division College of Science and Engineering Doha34110 Qatar Information Technology University Lahore54000 Pakistan University of New South Wales Sydney Sydney2052 Australia Qatar University Department of Computer Science and Engineering College of Engineering Doha34110 Qatar University of Technology Sydney School of Electrical and Data Engineering Sydney2052 Australia Nanyang Technological University College of Computing and Data Science 639798 Singapore

Deep neural networks (DNNs) have been the driving force behind many of the recent advances in machine learning. However, research has shown that DNNs are vulnerable to adversarial examples - input samples that have been perturbed to force DNN-based models to make errors. As a result, adversarial machine learning (AdvML) has gained a lot of attention, and researchers have investigated these vulnerabilities in various settings and modalities. In addition, DNNs have also been found to incorporate embedded bias and often produce unexplainable predictions, which can result in antisocial AI applications. The emergence of new AI technologies that leverage large language models (LLMs), such as ChatGPT and GPT-4, increases the risk of producing antisocial applications at scale. AdvML for social good (AdvML4G) is an emerging field that repurposes the AdvML bug to invent prosocial applications. Regulators, practitioners, and researchers should collaborate to encourage the development of prosocial applications and hinder the development of antisocial ones. In this work, we provide the first comprehensive review of the emerging field of AdvML4G. This paper encompasses a taxonomy that highlights the emergence of AdvML4G, a discussion of the differences and similarities between AdvML4G and AdvML, a taxonomy covering social good-related concepts and aspects, an exploration of the motivations behind the emergence of AdvML4G at the intersection of ML4G and AdvML, and an extensive summary of the works that utilize AdvML4G as an auxiliary tool for innovating prosocial applications. Finally, we elaborate upon various challenges and open research issues that require significant attention from the research community. © 2020 IEEE.

关键词： Taxonomies

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Internet of Things IoMT data Aggregation Using Machine Learning 2

Internet of Things IoMT Data Aggregation Using Machine Learn...

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2nd IEEE International Conference on Device Intelligence, computing and Communication Technologies, DICCT 2024

作者： Pulabaigari, Lakshmi Sagar Sivakumar, C. School of Computing Mohan Babu University Dept. of Computer Science and Engineering Andhra Pradesh Tirupati India School of Computing Mohan Babu University Dept. of Data Science Andhra Pradesh Tirupati India

ISBN: (纸本)9798350372847

The Internet of Things (IoT) has revolutionized the way data is handled and collected, allowing for large amounts of information to be revolutionized quickly and efficiently. This has paved the way for Machine Learning (ML) applications to be used on IoT datasets, such as 10MT data aggregation. This paper discusses the use of a ML approach for aggregation 10MT data in order to better understand trends and classify patterns in various sectors that would otherwise go undetected. It discusses the benefits and challenges of such a system, and how it could be used to improve the efficiency of industrial operations. It stresses the importance of data integrity in this process, as wrong or incomplete datasets can significantly reduce the accuracy and reliability of the results obtained. Furthermore, it discusses the need for suitable ML algorithms and models, such as clustering and random forest, to be applied to the collected data in order to produce robust and meaningful output. It observes the security and privacy challenges associated with such ML-based 10MT data aggregation systems, and the potential solutions available. © 2024 IEEE.

关键词： Internet of things

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Multi-scale feature fusion for facial expression recognition

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Neural computing and Applications 2025年第17期37卷 11399-11420页

作者： Guo, Jiatao Peng, Junjie Huang, Yansong Chen, Gan Cai, Zesu Tan, Shuhua School of Computer Engineering and Science Shanghai University Shanghai China Shanghai Institute for Advanced Communication and Data Science Shanghai University Shanghai China School of Computer Science and Technology Harbin Institute of Technology Harbin China National Engineering Laboratory for Logistics Information Technology YTO Express Co. Ltd. Shanghai China

As an important computer vision task that can be used in many areas, facial expression recognition (FER) has been widely studied which much progress has been obtained especially when deep learning (DL) approaches have been introduced in FER. However, existing methods are restricted to extracting localized information or utilizing attention mechanism to focus on the region most relevant to the emotion, possibly resulting in errors in facial expression interpretation. Moreover, the inconsistency of image sizes in the wild FER datasets further increases the difficulty of the FER task. To address these issues, we propose a multi-scale feature fusion (MSFF) for FER. Specifically, our method first extracts features from facial images using multi-scale feature extraction to obtain rich multi-dimensional information. Meanwhile, extensive feature extraction at different scales is achieved by expanding the receptive field of the model, which provides the basis for more detailed analysis of facial expressions. Eventually, features at different scales are fused to enhance their synergistic effect. Subsequently, the adaptive extraction of comprehensive and valuable information from the fused features is performed, optimizing the performance of expression recognition. Extensive experimental results demonstrate that the proposed method outperforms the state-of-the-art methods on in-the-wild datasets. It is promising for FER in realistic and complex scenarios. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Feature extraction

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Indoor Navigation Using Ultra Wide Band

Indoor Navigation Using Ultra Wide Band

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2023 Intelligent computing and Control for Engineering and Business Systems, ICCEBS 2023

作者： Divya, B. Veeramakali, T. Revathi, S. Harisharajan, R.R. Adhirooban, D. Ebishdon, G.V. Sri Sai Ram Institute of Technology Dept of Computer Science and Engineering India School of Computing Srm Institute of Science and Technology Dept of Data Science and Business Systems Tamilnadu Kattankulathur India

ISBN: (纸本)9798350394580

Indoor positioning is a significant and intriguing topic in navigation systems that present numerous use cases for investigation. Researchers are exploring technologies capable of providing accurate locations in indoor spaces where GNSS positioning systems are ineffective. In the numerous solutions available for indoor location services, Ultra-wideband (UWB) technology was chosen for its ability to provide high-precision positioning information for multiple points in real-time. This paper presents a UWB indoor positioning system that utilizes time of flight (TOF) algorithm. At times, time difference of arrival (TDOA) algorithms compute range measurements, this facilitates the trans-receiver (TAG) plane position algorithm's location determination. UWB technology was chosen because it is the latest technology available on Android 12 and further also offers high accuracy, resistance to interference and minimal signal reflection from walls. UltraWide Band(UWB) localization encounters various obstacles, such as multipath distortions, additional signal delays, time discrepancies in clocks, signal interference, and the computational resources necessary to determine the user's location. © 2023 IEEE.

关键词： Indoor Positioning System(IPS) Time of Flight(TOF) Ultra Wide Band(UWB)

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SYSTEM THINKING MEETS data science/ENGINEERING 67

SYSTEM THINKING MEETS DATA SCIENCE/ENGINEERING

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67th Annual Meeting of the International Society for the Systems sciences, ISSS 2023

作者： Malele, Vusumuzi Unit for Data Science and Computing School of Computer Science and Information Systems North-West University Vanderbijlpark Campus South Africa

ISBN: (纸本)9781713893455

With the advent of data 3.0 and analytics 3.0, system thinkers are in the position to provide a bigger picture in data science and data engineering. In the data life cycle, a system thinking approach emphasises data-driven decision-making. A System Thinker approaches problem-solving by viewing the problems as part of a wider, data-resourced and dynamic system, and a data Practitioner supports the data life cycle by collecting, transforming, and analyzing data, and communicating results to inform and guide decision-making. This paper uses explanatory research and a pragmatic case study approach to look at the (i) What is the role of system thinking and data science/engineering skill in data-driven decision-making or organisation? (ii) Does the combination of system thinking and data science/engineering give rise to a new discipline? (iii) What are the skills needed in this new discipline? The research shows that the system thinking skills in the data life cycle are important. System thinkers meet data practitioners to provide a bigger picture of data-driven decision-making. The latter ascertains the position of a system thinker in any industrial revolution (i.e. industry 4.0. and industry 5.0). Furthermore, a data-System Thinker is proposed as a new career field. © Copyright, Author (Creative Commons), 2023.

关键词： Systems thinking

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A novel approach for image retrieval in remote sensing using vision-language-based image caption generation

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Multimedia Tools and Applications 2025年第6期84卷 2985-3014页

作者： Yadav, Prem Shanker Tyagi, Dinesh Kumar Vipparthi, Santosh Kumar Department of Computer Science and Engineering Malaviya National Institute of Technology Rajasthan Jaipur302017 India School of Artificial Intelligence and Data Engineering Indian Institute of Technology Ropar Punjab Rupnagar140001 India

Recent advancements in satellite technologies have resulted in the emergence of Remote Sensing (RS) images. Hence, the primary imperative research domain is designing a precise retrieval model for retrieving the most pertinent images based on the query. Present Remote Sensing Image Retrieval (RSIR) systems use visual descriptors to characterize the primitives (such as various land-cover types) that are visible in the images. However, the visual descriptors are inadequate for defining the complicated content of RS images. To solve this problem, a new model is devised for image retrieval based on image captions. The goal is to generate textual illustrations with captions to define relations amongst objects precisely. Here, image captioning is attained based on the vision-language pre-training model. The image captions are utilized for generating features like term frequency-inverse document frequency (TF-IDF), length of text, and Bag of Words. Meanwhile, query text is utilized wherein features like TF-IDF, text length, and Bag of Words are obtained. The similarity between query text features and the image captions features has been computed on the basis of a hybrid similarity measure wherein weights are tuned with the proposed Honey Badger Political Optimizer (HBPO) to retrieve the image. The proposed HBPO provided enhanced efficiency with elevated precision of 93.3%, recall of 93.7%, F1-score of 93.5%, and Recall-Oriented Understudy for Gisting Evaluation (ROUGE) of 0.441. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Visual languages

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Benchmark experiment on slab^(238)U with D-T neutrons for validation of evaluated nuclear data

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Nuclear science and Techniques 2024年第2期35卷 145-159页

作者： Yan-Yan Ding Yang-Bo Nie Yue Zhang Zhi-Jie Hu Qi Zhao Huan-Yu Zhang Kuo-Zhi Xu Shi-Yu Zhang Xin-Yi Pan Chang-Lin Lan Jie Ren Xi-Chao Ruan Key Laboratory of Nuclear Data China Institute of Atomic EnergyBeijing 102413China School of Nuclear Science and Technology Lanzhou UniversityLanzhou 730000China Institute of Fluid Physics China Academy of Engineering PhysicsMianyang 62100China

A benchmark experiment on^(238)U slab samples was conducted using a deuterium-tritium neutron source at the China institute of Atomic *** leakage neutron spectra within energy levels of 0.8-16 MeV at 60°and 120°were measured using the time-of-flight *** samples were prepared as rectangular slabs with a 30 cm square base and thicknesses of 3,6,and 9 *** leakage neutron spectra were also calculated using the MCNP-4C program based on the latest evaluated files of^(238)U evaluated neutron data from CENDL-3.2,ENDF/B-Ⅷ.0,JENDL-5.0,and *** on the comparison,the deficiencies and improvements in^(238)U evaluated nuclear data were *** results showed the following.(1)The calculated results for CENDL-3.2 significantly overestimated the measurements in the energy interval of elastic scattering at 60°and 120°.(2)The calculated results of CENDL-3.2 overestimated the measurements in the energy interval of inelastic scattering at 120°.(3)The calculated results for CENDL-3.2 significantly overestimated the measurements in the 3-8.5 MeV energy interval at 60°and 120°.(4)The calculated results with JENDL-5.0 were generally consistent with the measurement results.

关键词： Leakage neutron spectra Uranium D-T neutron source Evaluated nuclear data

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