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International Conference on Artificial Intelligence, Blockchain, Computing and Security, ICABCS 2023

作者： Archana, K. Kareem, Z.H. Al-Farhani, Liwa H. Bagyalakshmi, K. Jenvi, Ignatia K. Majella Kumar, Ashok Department of Computer Engineering Pimpri Chinchwad College of Engineering and Research Maharashtra Pune India Medical Instrumentation Techniques Engineering Department Al-Mustaqbal University College Babylon Iraq System Analysis Control and Information Processing dep Academy of Engineering RUDN University Moscow Russia Sri Ranganathar Institute of Engineering and Technology Coimbatore India Mathematics Department Saveetha School of Engineering SIMATS Saveetha Nagar Chennai India Department of Computer Science Banasthali Vidyapith Rajasthan Banasthali India

ISBN: (纸本)9781032669663

One of the most critical problems facing the blockchain technology industry right now is how to protect the privacy of users’ data on the blockchain in a way that is both effective and cheap. Based on the Pedersen commitment and the Schnorr protocol, this study comes up with a secure multi-party computing protocol (BPLSM). By making the structure of the protocol and doing formal proof calculations, it has been shown that the protocol can be used in the blockchain network to combine private messages for efficient signing while keeping people’s identities secret. Furthermore, by looking at the nature and security of the protocol, it is also possible to find that the BPLSM protocol on the blockchain has a low cost of computing and a high level of information secrecy. Furthermore, it was found that the BPLSM protocol takes less time to check than the current mainstream BLS signature in a simple multi-party transaction with a fixed number of participants. © 2024 The Author(s).

关键词： Blockchain

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Sentiment Analysis in Indonesian Trading using Lexicon-based and Support Vector Machine

Sentiment Analysis in Indonesian Trading using Lexicon-based...

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2023 International Conference on computer Science, Information Technology and engineering, ICCoSITE 2023

作者： Oetama, Raymond Sunardi Yanfi, Yanfi Ikhsan Assiddiq Up, Masagus M. Muhamad Isa, Sani Universitas Multimedia Nusantara Information System DepartmentFaculty of Engineering and Informatics Jakarta Indonesia Bina Nusantara University BINUS Graduate Program Computer Science School of Computer Science Computer Science Department Jakarta Indonesia Bina Nusantara University BINUS Graduate Program Computer Science Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798350320954

Many individuals now trade online utilizing trading software in the digital world. Binomo is one of Indonesia's most popular trading platforms. This is because some influencers made several promises to Binomo customers. Since many customers were deceived, this case became quite popular. This study was executed to see how Indonesians felt about the Binomo application after the case went viral. The solution taken was in the form of sentiment analysis because there had been no previous research on sentiment analysis that discussed the Binomo case. The data was scanned using Netlytic tools, a cloud-based text and social network analyzer capable of identifying any talks on social media sites such as Twitter. The sentiment analysis of Binomo trading tweets by using the Multi-Perspective Question Answering lexicon utilized the KNIME tool. But unfortunately, the accuracy of sentiment analysis results is low. Furthermore, the Support Vector Machine technique is also being conducted. The Term Frequency-Inverse Document Frequency method is applied to perform feature extraction whilst the chi-square approach is utilized to identify features that are thought to be useful for inclusion in the classification process and to exclude features that are irrelevant to the target class. The obtained accuracy is 86%. The study proposes that words from the algorithm's outputs can be utilized to improve the quality of sentiment analysis using the lexicon. As an outcome of the algorithm, positive and negative terms are added to the lexicon, increasing the accuracy of sentiment analysis using the new vocabulary from 58.984% to 71.146%. © 2023 IEEE.

关键词： Support vector machines

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BuildingMap-GAN: A Map Translator From Road to Building Footprint 3

BuildingMap-GAN: A Map Translator From Road to Building Foot...

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3rd International Conference on Internet of Things and Smart City, IoTSC 2023

作者： Wei, Jing Zuo, Zejun Yang, Lin Yang, Ruolin School of Computer Science China University of Geosciences Wuhan China National Engineering Research Center of Geographic Information System China University of Geosciences Wuhan China

ISBN: (纸本)9781510666375

Building footprint information is crucial for urban-related applications. Due to the rapid growth of the number and types of community-level buildings, the completeness and coverage of building footprint data at the community level are lagging. Efficiently and accurately generating community-level building footprint maps for the update of community electronic maps, post-disaster assessment, navigation services, etc. is an urgent and challenging task. To fill the data gaps of community-level building footprint with high accuracy, we design a building map translator named BuildingMap-GAN that is configured with a novel generator: MACU-Net. It has multi-scale connections with channel attention and asymmetric convolution blocks (ACB), which are used for fully capturing the spatial structure information of buildings and roads. An experiment is conducted on real-world community dataset in Wuhan, China, in which the street network data of 700 communities were used for training and the street network data of 42 communities were used for verification. Compared with the two baseline models, F1 scores are improved by 6.7% and 4.5%, respectively, and IoU values increase by 5.0% and 3.2%, respectively. Our model can generate refined building footprint data with higher precision and is closer to the real building distribution. © 2023 SPIE.

关键词： Generative adversarial networks

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UWB Channel Modeling and Simulation with Continuous Frequency Response

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China Communications 2022年第11期19卷 88-98页

作者： Kai Mao Qiuming Zhu Xijuan Ye Ruirui Feng Fuqiao Duan Yang Miao Maozhong Song The Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space College of Electronic and Information EngineeringNanjing University of Aeronautics and AstronauticsNanjing 211106China The Radio Systems Faculty of Electrical Engineering Computer Science and Mathematics(EEMCS)University of Twentethe Netherlands

Ultra-wideband(UWB)technology is a prospective technology for high-rate transmission and accurate localization in the future communication ***-of-art channel modeling approaches usually divide the UWB channel into several sub-band channels and model them *** considering frequency-dependent channel parameters,a novel analytical UWB channel model with continuous frequency response is *** composite effect of all frequency components within the UWB channel on the channel impulse response(CIR)of delay domain is derived based on the continuous channel transfer function(CTF)of frequency *** this basis,a closed-form simulation model for UWB channels and geometry-based parameter calculation method are developed,which can guarantee the continuity of channel characteristics on the frequency domain and greatly reduce the simulation ***,the proposed method is applied to generate UWB channel with 2 GHz bandwidth at sub-6GHz and millimeter wave(mmWave)bands,*** channel measurements are also carried out to validate the proposed *** simulated CIR and power gain are shown to be in good agreement with the measurement ***,the comparison results of power gain and Doppler power spectral density(DPSD)show that the proposed UWB channel model Received:Apr.23,2022 Revised:Jun.09,2022 Editor:Wei Fan achieves a good balance between the simulation accuracy and efficiency.

关键词： ultra-wideband(UWB)channel continuous frequency response frequency-dependent channel parameters simulation model channel measurement

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Fixed-Time Sliding Mode Fault-Tolerant Consensus Control for Second-Order Multi-Agent system with Actuator Fault 41

Fixed-Time Sliding Mode Fault-Tolerant Consensus Control for...

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第41届中国控制会议

作者： Jing Wang Yi-ming Fang Jian-xiong Li Kun-da Li Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Engineering Research Center of the Ministry of Education for Intelligent Control System and Intelligent Equipment

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Aiming at the problems of immeasurable leader state and actuator fault for second-order multi-agent system(MAS),the distributed robust sliding mode fault-tolerant control method based on fixed-time state observer(FTSO) is adopted to realize the fixed time fault-tolerant consensus tracking control for the *** MAS is under the undirected communication *** actuator fault is including partial loss of effectiveness(PLOE) fault and bias ***,a fixed time state observer is designed for each follower to obtain the state information of the ***,for followers with actuator faults,the distributed fixed-time robust sliding mode fault-tolerant controller is designed to realize fault-tolerant consensus tracking ***,the Lyapunov stability theorem is used to prove that the observation error and the consensus control error converge to zero in a ***,the effectiveness of the designed FTSO and fixed-time robust sliding mode fault-tolerant control algorithm is verified by numerical simulation.

关键词： fixed-time state observer fixed-time fault-tolerant control multi-agent systems consensus tracking control

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TransFeatEx: a NLP pipeline for feature extraction

TransFeatEx: a NLP pipeline for feature extraction

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Joint of REFSQ-2023 Workshops, Doctoral Symposium, Posters and Tools Track and Journal Early Feedback, REFSQ-JP 2023

作者： Gállego, Agustí Motger, Quim Franch, Xavier Marco, Jordi Department of Service and Information System Engineering Universitat Politècnica de Catalunya Spain Department of Computer Science Universitat Politècnica de Catalunya Spain

Mobile app stores provide centralized access to a large data set of mobile app related natural language textual data, including developer’s documentation (e.g., descriptions, changelogs) and user-generated data (e.g., user reviews). Motivated by this context, multiple studies have focused on data-driven elicitation processes for the automatic extraction of the set of features exposed by a catalogue of applications and the inferred, extended knowledge that can be derived from this information. Moreover, with the emerging and generalization of large language models, traditional linguistic-based approaches can be significantly improved by the potential of the knowledge embedded in this kind of models. In this paper, we present TransFeatEx, a NLP-based feature extraction pipeline that combines the use of a RoBERTa-based model with the application of consolidated syntactic and semantic techniques. The pipeline is designed as a customizable, standalone service to be used either as a playground, experimentation tool or as a software component to be embedded into a third-party software system for batch-processing large document corpora. An example of a demo plan is showcased here: https://***/gfFyi_i_uTw. © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Feature extraction

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EEG based stress classification by using difference plots of variational modes and machine learning

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Journal of Ambient Intelligence and Humanized Computing 2023年第12期14卷 16347-16360页

作者： Salankar, Nilima Qaisar, Saeed Mian School of Computer Science University of Petroleum and Energy Studies Dehradun India Persistent System Limited IT Park Maharashtra Nagpur India Department of Electrical and Computer Engineering EFfat University Jeddah22332 Saudi Arabia Communication and Signal Processing Lab Energy and Technology Research Center Effat University Jeddah22332 Saudi Arabia

The recent trend in healthcare is to use the automated biomedical signals processing for an augmented and precise diagnosis. In this context, an original approach is presented for categorization of stress and non-stress classes by processing the multichannel Electroencephalogram (EEG) signals. The EEG signals are decomposed by using the "Empirical Mode Decomposition" (EMD) and "Variational Mode Decomposition" (VMD), respectively render the "Intrinsic Mode Functions" (IMFs) and Modes. The Second Order Difference Plots (SODPs) are traced for each IMF and Mode. Shapes of SODPs are used to discriminate the two intended categories. The feature space includes areas, Central Tendency Measures (CTMs) and means of SODPs. It is derived from first 7 IMFs and Modes. The identification of stress and non-stress categories is performed by using the robust machine learning algorithms namely, the Support Vector Machine (SVM), Boosting with Random Forest (RF) and Multilayer Perceptron Neural Network (MLPNN). The applicability is tested by using a publicly available EEG signals dataset, recorded during mental arithmetic test. A detailed evaluation is carried out at the subset, individual channel and lobes wise. Noteworthy highest accuracies of subset wise 99.89%, channel wise 98.89% and lobe wise 99.99% are obtained respectively. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Empirical mode decomposition

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F-CNN: Faster CNN Exploiting Data Re-Use with Statistical Analysis 5

F-CNN: Faster CNN Exploiting Data Re-Use with Statistical An...

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5th IEEE International Conference on Artificial Intelligence Circuits and systems, AICAS 2023

作者： Alantali, Fatmah Halawani, Yasmin Mohammad, Baker Al-Qutayri, Mahmoud Khalifa University System-on-Chip Lab Electrical Engineering and Computer Science Department Abu Dhabi United Arab Emirates University of Dubai College of Engineering & Information Technology Dubai United Arab Emirates

ISBN: (纸本)9798350332674

Many of the current edge computing devices need efficient implementation of Artificial Intelligence (AI) applications due to strict latency, security and power requirements. Nonetheless, such devices, face various challenges when executing AI applications due to their limited computing and energy resources. In particular, Convolutional Neural Networks (CNN) is a popular machine learning method that derives a high-level function from being trained on various visual input examples. This paper contributes to enabling the use of CNN on resource-constrained devices offline, where a trade-off between accuracy, running time and power efficiency is verified. The paper investigates the use of minimum pre-processing methods of input data to identify nonessential computations in the convolutional layers. In this work, Spatial locality of input data is considered along with an efficient pre-processing method to mitigate the accuracy loss caused by the computational re-use approach. This technique was tested on LeNet and CIFAR-10 structures and was responsible for 1.9% and 1.6% accuracy loss while reducing the processing time by 38.3% and 20.9% and reducing the energy by 38.3%, and 20.7%, respectively. The models were deployed and verified on Raspberry Pi 4 B platform using the MATLAB coder to measure time and energy. © 2023 IEEE.

关键词： Convolution

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Novel MEMS-IMU/Wi-Fi integrated indoor pedestrian location algorithm

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Harbin Gongcheng Daxue Xuebao/Journal of Harbin engineering University 2025年第3期46卷 609-617页

作者： Zhu, Minghong Yu, Fei Jin, Ming Liu, Juan Wang, Zhenpeng Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo315211 China College of Mathematical Sciences Harbin Engineering University Harbin150001 China System Engineering Institute of Sichuan Aerospace Chengdu610100 China

A novel integration strategy for accurately estimating pedestrian location has been developed by combining microelectromechanical systems-inertial measurement units (MEMS-IMUs) and Wi-Fi data. This approach enables the effective use of MEMS-IMU devices in smartphones. The research work included: establishing a position estimation model relative to the reference coordinate system based on the pedestrian dead reckoning algorithm;directly using the output of the gyroscope in the IMU as the original observation value, and adopting the Wi-Fi position data at a fixed frequency for system correction, then designing the extended Kalman filter algorithm to estimate the real-time position coordinates of pedestrians;creating the motion trajectory of pedestrians and verifying the effectiveness and feasibility of the algorithm by collecting the data of mobile phone sensors and wireless signal access point. The results show that when using integrated MEMS-IMU and Wi-Fi positioning, the position error becomes significantly smaller than that of IMU-only positioning. The findings also indicate that Wi-Fi information can assist MEMS inertial sensors to more accurately complete indoor pedestrian navigation and positioning tasks. © 2025 Editorial Board of Journal of Harbin engineering. All rights reserved.

关键词： Extended Kalman filters

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An Efficient Schema Transformation Technique for Data Migration from Relational to Column-Oriented Databases

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computer systems Science & engineering 2022年第12期43卷 1175-1188页

作者： Norwini Zaidi Iskandar Ishak Fatimah Sidi Lilly Suriani Affendey System Development and Engineering Center Universiti Sains Islam Malaysia71800Negeri SembilanMalaysia Faculty of Computer Science and Information Technology Universiti Putra MalaysiaUPM Serdang43400SelangorMalaysia

Data transformation is the core process in migrating database from relational database to NoSQL database such as column-oriented database. However,there is no standard guideline for data transformation from relational database toNoSQL database. A number of schema transformation techniques have been proposed to improve data transformation process and resulted better query processingtime when compared to the relational database query processing time. However,these approaches produced redundant tables in the resulted schema that in turnconsume large unnecessary storage size and produce high query processing timedue to the generated schema with redundant column families in the transformedcolumn-oriented database. In this paper, an efficient data transformation techniquefrom relational database to column-oriented database is proposed. The proposedschema transformation technique is based on the combination of denormalizationapproach, data access pattern and multiple-nested schema. In order to validate theproposed work, the proposed technique is implemented by transforming data fromMySQL database to MongoDB database. A benchmark transformation techniqueis also performed in which the query processing time and the storage size arecompared. Based on the experimental results, the proposed transformation technique showed significant improvement in terms query processing time and storagespace usage due to the reduced number of column families in the column-orienteddatabase.

关键词： Data migration data transformation column-oriented database relational database big data

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