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Integration of data science with the intelligent IoT(IIoT): Current challenges and future perspectives

Digital Communications and Networks 2025年第2期11卷 280-298页

作者： Inam Ullah Deepak Adhikari Xin Su Francesco Palmieri Celimuge Wu Chang Choi Department of Computer Engineering Gachon University University of Electronic Science and Technology of China College of Information Science and Engineering Hohai University Department of Computer Science University of Salerno Graduate School of Informatics and Engineering The University of Electro-Communications

The Intelligent Internet of Things(IIoT) involves real-world things that communicate or interact with each other through networking technologies by collecting data from these “things” and using intelligent approaches, such as Artificial Intelligence(AI) and machine learning, to make accurate decisions. Data science is the science of dealing with data and its relationships through intelligent approaches. Most state-of-the-art research focuses independently on either data science or IIoT, rather than exploring their integration. Therefore, to address the gap, this article provides a comprehensive survey on the advances and integration of data science with the Intelligent IoT(IIoT) system by classifying the existing IoT-based data science techniques and presenting a summary of various characteristics. The paper analyzes the data science or big data security and privacy features, including network architecture, data protection, and continuous monitoring of data, which face challenges in various IoT-based systems. Extensive insights into IoT data security, privacy, and challenges are visualized in the context of data science for IoT. In addition, this study reveals the current opportunities to enhance data science and IoT market development. The current gap and challenges faced in the integration of data science and IoT are comprehensively presented, followed by the future outlook and possible solutions.

关键词： Data science Internet of things (IoT) Big data Communication systems Networks Security Data science analytics

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Watermarking technique for document images using discrete curvelet transform and discrete cosine transform

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Multimedia Tools and Applications 2024年第40期83卷 87647-87671页

作者： Singh, Balkar Sharma, M.K. Post Graduate Department of Computer Science Gujranwala Guru Nanak Khalsa College Punjab Ludhiana India School of Mathematics Thapar Institute of Engineering and Technology Punjab Patiala India

In this paper, a watermarking technique based on discrete curvelet transform and discrete cosine trans- form is proposed to protect the color document images. The six layers of the document image are created using the Discrete Curvelet Transform (DCuT). The sixth layer is chosen for the embedding process, while the remaining layers are discarded. Discrete Cosine Transform (DCT) is applied on the 8 × 8 blocks of the real part of sixth layer. DCT coefficients from low to medium are selected for the embedding process, excluding the first one. To choose the Direct Current (DC) coefficients of DCT to embed the watermark bits, a zigzag function is used. The same process is applied on the receiver side watermark image is extracted. Since this is a non-blind method, we require both a cover image and a watermarked image. DCT of watermarked image and the cover image are compared to extract the watermark image. The resistivity of the watermarked image against image processing attacks is measured using the Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), Mean Square Error (MSE), Normalization Correlation (NC), Bit Error Rate (BER) and Universal Quality Index (UQI). © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Mean square error

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Alphabet-Level Indian Sign Language Translation to Text Using Hybrid-AO Thresholding with CNN

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Intelligent Automation & Soft Computing 2023年第9期37卷 2567-2582页

作者： Seema Sabharwal Priti Singla Department of Computer Science and Engineering Baba Mastnath UniversityRohtak124001India Department of Computer Science Government Post Graduate College for WomenPanchkula134109India

Sign language is used as a communication medium in the field of trade,defence,and in deaf-mute communities *** the last few decades,research in the domain of translation of sign language has grown and become more *** necessitates the development of a Sign Language Translation System(SLTS)to provide effective communication in different research *** this paper,novel Hybrid Adaptive Gaussian Thresholding with Otsu Algorithm(Hybrid-AO)for image segmentation is proposed for the translation of alphabet-level Indian Sign Language(ISLTS)with a 5-layer Convolution Neural Network(CNN).The focus of this paper is to analyze various image segmentation(Canny Edge Detection,Simple Thresholding,and Hybrid-AO),pooling approaches(Max,Average,and Global Average Pooling),and activation functions(ReLU,Leaky ReLU,and ELU).5-layer CNN with Max pooling,Leaky ReLU activation function,and Hybrid-AO(5MXLR-HAO)have outperformed other *** open-access dataset of ISL alphabets with approx.31 K images of 26 classes have been used to train and test the *** proposed framework has been developed for translating alphabet-level Indian Sign Language into *** proposed framework attains 98.95%training accuracy,98.05%validation accuracy,and 0.0721 training loss and 0.1021 validation loss and the perfor-mance of the proposed system outperforms other existing systems.

关键词： Sign language translation CNN thresholding Indian sign language

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Understanding Brain Network Stimulation for Emotion Analyzing Connectivity Feature Map from Electroencephalography

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International Journal of Advanced computer science and Applications 2025年第4期16卷 542-551页

作者： Maria, Mahfuza Akter Akhand, M.A.H. Kamal, Abdus Samad Department of Computer Science and Engineering Khulna University of Engineering & Technology Khulna9203 Bangladesh Graduate School of Science and Technology Gunma University Kiryu376-8515 Japan

In understanding brain functioning by Electroencephalography (EEG), it is essential to be able to not only identify more active brain areas but also understand connectivity among different areas. The functional and efficient connectivity networks of the brain have been examined in this study by constructing a connectivity feature map (CFM) with four widely used connectivity methods from the Database for Emotion Analysis Using Physiological Signals (DEAP) emotional EEG data to research how this connectivity’s patterns are influenced by emotion. According to the investigation results, emotions are mainly related to the parietal, central, and frontal regions. The parietal region is more responsible for emotion alteration among these three regions. Positive emotions are associated with more direct correlations and dependencies than negative ones. When experiencing negative emotions, the regions of the brain function more synchronously as well as there are less flow of information. Whether direct or inverse, there is less correlation between brain regions in the higher frequency band than in the lower frequency band. Higher frequencies are associated with increased dependence and directed information transfer between brain regions. Generally, the electrodes in the same lobe show stronger connectivity than those in different lobes. At a glance, the present study is a comprehensive analysis to understand brain network stimulation for emotion from EEG, and it significantly differs from the existing emotion recognition studies typically focused on recognition proficiency. © (2025), (science and Information Organization). All rights reserved.

关键词： Emotion Recognition

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Improving free space optics performance using QC-LDPC codes and simplified bit flipping decoding in low visibility conditions

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Optical and Quantum Electronics 2025年第1期57卷 1-18页

作者： Marlina, Lina Pamukti, Brian Liaw, Shien-Kuei Lee, Pei-Jun Kishikawa, Hiroki Graduate Institute of Electro-Optical Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Electronic and Computer Engineering National Taiwan University of Science and Technology Taipei Taiwan Institute of Post-LED Photonics Tokushima University Tokushima Japan

Currently, free space optics (FSO) is the most promising technology for achieving high data transfer over short to medium or even long distances. Thus, FSO provides wireless line-of-sight (LOS) connectivity in the unlicensed spectrum and can be a high-bandwidth wireless alternative in contrast to fiber optic cabling. Moreover, the FSO offers rapid assembly times and significant cost savings. However, atmospheric weather (e.g., fog, rain, and snow) can degrade the FSO performance, especially in low visibility conditions. Therefore, this research aims to improve the FSO performance using quasi-cyclic low-density parity-check (QC-LDPC) codes in low visibility scenarios or thick turbulence conditions. In addition, a simplified bit-flipping (SBF) algorithm was proposed to decode the information by the receiver side to minimize complexity. Subsequently, the FSO system is simulated using a 1550 nm laser at different data rates of 1 to 20 Gbps data rate and 1-Watt transmitted power. This paper was analyzed using different empirical models of atmosphere attenuation, like the Kim, Kruse, and Naboulsi models. This simulation also uses modulation techniques such as on-off keying, phase shift keying, and quadrature amplitude modulation. Moreover, the looping iteration number of SBF could improve the system’s performance. We also consider using a low-cost PIN photodetector for practical implementation. Our simulation results show that QC-LDPC codes can achieve an average bit error rate of 10-9 in lower visibility than uncoded information. Our research has significant implications for enhancing fiber optic performance in adverse atmospheric phenomena. © The Author(s) 2025.

关键词： Quadrature amplitude modulation

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Improving Prediction Efficiency of Machine Learning Models for Cardiovascular Disease in IoST-Based Systems through Hyperparameter Optimization

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computers, Materials & Continua 2024年第9期80卷 3485-3506页

作者： Tajim Md.Niamat Ullah Akhund Waleed M.Al-Nuwaiser Department of Computer Science and Engineering(CSE) Daffodil International UniversityDhaka1216Bangladesh Graduate School of Science and Engineering Saga UniversitySaga8408502Japan Computer Science Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11623Saudi Arabia

This study explores the impact of hyperparameter optimization on machine learning models for predicting cardiovascular disease using data from an IoST(Internet of Sensing Things)*** distinct machine learning approaches were implemented and systematically evaluated before and after hyperparameter *** improvements were observed across various models,with SVM and Neural Networks consistently showing enhanced performance metrics such as F1-Score,recall,and *** study underscores the critical role of tailored hyperparameter tuning in optimizing these models,revealing diverse outcomes among *** Trees and Random Forests exhibited stable performance throughout the *** enhancing accuracy,hyperparameter optimization also led to increased execution *** representations and comprehensive results support the findings,confirming the hypothesis that optimizing parameters can effectively enhance predictive capabilities in cardiovascular *** research contributes to advancing the understanding and application of machine learning in healthcare,particularly in improving predictive accuracy for cardiovascular disease management and intervention strategies.

关键词： Internet of sensing things(IoST) machine learning hyperparameter optimization cardiovascular disease prediction execution time analysis performance analysis wilcoxon signed-rank test

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An Efficient Three-Party Authenticated Key Exchange Procedure Using Chebyshev Chaotic Maps with Client Anonymity

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computers, Materials & Continua 2023年第6期75卷 5337-5353页

作者： Akshaykumar Meshram Monia Hadj Alouane-Turki N.M.Wazalwar Chandrashekhar Meshram Department of Applied Mathematics Yeshwantrao Chavan College of EngineeringNagpur441110MaharashtraIndia Department of Statistics Rashtrasant Tukadoji Maharaj Nagpur UniversityNagpur440033MaharashtraIndia Department of Computer Science College of Computer ScienceKing Khalid UniversityAbhaSaudi Arabia Department of Post Graduate Studies and Research in Mathematics Jaywanti Haksar Government Post-Graduate CollegeCollege of Chhindwara UniversityBetul460001Madhya PradeshIndia

Internet of Things(IoT)applications can be found in various industry areas,including critical infrastructure and healthcare,and IoT is one of several technological *** a result,tens of billions or possibly hundreds of billions of devices will be linked *** smart devices will be able to gather data,process it,and even come to decisions on their *** is the most essential thing in these *** IoT infrastructure,authenticated key exchange systems are crucial for preserving client and data privacy and guaranteeing the security of data-in-transit(e.g.,via client identification and provision of secure communication).It is still challenging to create secure,authenticated key exchange *** majority of the early authenticated key agreement procedure depended on computationally expensive and resource-intensive pairing,hashing,or modular exponentiation *** focus of this paper is to propose an efficient three-party authenticated key exchange procedure(AKEP)using Chebyshev chaotic maps with client anonymity that solves all the problems mentioned *** proposed three-party AKEP is protected from several *** proposed three-party AKEP can be used in practice for mobile communications and pervasive computing applications,according to statistical experiments and low processing *** protect client identification when transferring data over an insecure public network,our three-party AKEP may also offer client ***,the presented procedure offers better security features than the procedures currently available in the literature.

关键词： Client anonymity Chebyshev chaotic maps authenticated key exchange statistical experiment Galois fields

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Body Extension by Using Two Mobile Manipulators

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Cyborg and Bionic Systems 2023年第1期4卷 418-426页

作者： Yusuke Hirao Weiwei Wan Dimitrios Kanoulas Kensuke Harada Graduate School of Engineering Science Osaka UniversityOsakaJapan Department of Computer Science University College LondonLondonUK

This paper presents a remotely operated robotic system that includes two mobile manipulators to extend the functional capabilities of a human *** with previous tele-operation or robotic body extension systems,using two mobile manipulators helps with enlarging the workspace and allowing manipulation of large or long *** system comprises a joystick for controlling the mobile base and robotic gripper,and a motion capture system for controlling the arm *** together enable tele-operated dual-arm and large-space *** the experiments,a human tele-operator controls the two mobile robots to perform tasks such as handover,long object manipulation,and cooperative *** results demonstrated the effectiveness of the proposed system,resulting in extending the human body to a large space while keeping the benefits of having two limbs.

关键词： system Extension enable

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FPGA implementation of low cost and low power chaotic encryption scheme based on a discrete-space chaotic map

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Multimedia Tools and Applications 2025年 1-22页

作者： Moreira Bezerra, João Inácio Machado, Gustavo Iankowski Soares, Rafael Valduga de Almeida Camargo, Vinícius Molter, Alexandre Post Graduate Program in Computer Science Universidade Federal de Pelotas Rio Grande do Sul Pelotas96010610 Brazil Graduate Program in Computer Engineering Universidade Federal de Pelotas Rio Grande do Sul Pelotas96010610 Brazil Post Graduate Program in Mathematical Modeling Universidade Federal de Pelotas Rio Grande do Sul Capão do Leão96160000 Brazil

The exponential growth of the number of devices connected to the Internet and the use of IoT applications increases the amount of data exchange over public channels in low-cost and low-power embedded systems. Images are the most widely shared files, and standard symmetric algorithms such as the Advanced Encryption Standard (AES) are optimized for text but not image encryption. Consequently, new approaches like chaotic encryption have attracted researchers’ interest. Chaotic encryption schemes have been analyzed mostly from a software standpoint, but recent advancements in the field, through the use of discrete chaotic maps, enabled the development of simpler hardware implementations of ciphers with promising reductions in power and cost and increased performance. This work presents the Field-Programmable Gate Array (FPGA) implementation of a simultaneous permutation-diffusion chaotic encryption scheme utilizing a discrete-space chaotic map. The FPGA implementation of the cipher is analyzed considering area, maximum frequency, and power consumption, and comparisons are made with the AES. The proposed algorithm has a satisfactory trade-off between area, power and performance, obtaining a peak throughput 59% higher than state-of-the-art symmetric ciphers in the literature. Thus, the proposed cipher shows that chaotic ciphers are viable for both high-performance and low-power embedded devices. Tests verified the security of the proposed cipher against statistical, differential, brute-force, and chosen plain-text attacks. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Cryptography

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Low Cost Active Learning Framework for Short Answer Scoring 20th

Low Cost Active Learning Framework for Short Answer Scoring

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20th Principle and Practice of Data and Knowledge Acquisition Workshop, PKAW 2024, held in conjunction with the 21st Pacific Rim International Conference on Artificial Intelligence, PRICAI 2024

作者： Hori, Tatsuya Yamauchi, Koichiro Graduate school of Engineering Department of Computer Science Chubu University Kasugai Japan

ISBN: (纸本)9789819600250

Short answer scoring (SAS) that automatically scores learner’ answers based on given rubric. Because SAS uses different rubrics for different prompts, it is necessary to generate training data for each prompt, which is time-consuming and labor-intensive. We propose a human-in-the-loop framework that achieves SAS with a minimal amount of training data through active data creation and efficient training. We fine-tuned the Sentence BERT model with a small dataset by using SetFit (Lewis Tunstall, et al. (2022).) and then apply active learning (AL) to an unlabeled data pool. The grader scores the data selected by AL, creating new training data that are then used to further fine-tune the models. For the experiments, we used six prompts from a Japanese SAS dataset. Our experimental results demonstrate that the proposed method outperforms previous studies in most cases. We also examined the potential challenges when applying this framework in practical scenarios. This framework significantly reduces the graders’ time and effort by enabling automatic scoring with minimal training data. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Active learning

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