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Artificial Fish Swarm Algorithm for Mining High Utility Itemsets 12th

Artificial Fish Swarm Algorithm for Mining High Utility Item...

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12th international conference on advances in Swarm Intelligence, ICSI 2021

作者： Song, Wei Li, Junya Huang, Chaomin School of Information Science and Technology North China University of Technology Beijing100144 China

ISBN: (纸本)9783030788100

the discovery of high utility itemsets (HUIs) is an attractive topic in data mining. Because of its high computational cost, using heuristic methods is a promising approach to rapidly discovering sufficient HUIs. the artificial fish swarm algorithm is a heuristic method with many applications. Except the current position, artificial fish do not record additional previous information, as other related methods do. this is consistent with the HUI mining problem: that the results are not always distributed around a few extreme points. thus, we study HUI mining from the perspective of the artificial fish swarm algorithm, and propose an HUI mining algorithm called HUIM-AF. We model the HUI mining problem with three behaviors of artificial fish: follow, swarm, and prey. We explain the HUIM-AF algorithm and compare it with two related algorithms on four publicly available datasets. the experimental results show that HUIM-AF can discover more HUIs than the existing algorithms, with comparable efficiency. © 2021, Springer Nature Switzerland AG.

关键词： Heuristic methods

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Study of PSO Optimized BP Neural Network and Smith Predictor for MOCVD Temperature Control in 7nm 5G Chip Process 6th

Study of PSO Optimized BP Neural Network and Smith Predictor...

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6th international conference on Advanced Intelligent Systems and Informatics, AISI 2020

作者： Chang, Kuo-Chi Zhou, Yu-Wen Wang, Hsiao-Chuan Lin, Yuh-Chung Chu, Kai-Chun Hsu, Tsui-Lien Pan, Jeng-Shyang School of Information Science and Engineering Fujian University of Technology Fuzhou China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China Institute of Environmental Engineering National Taiwan University Taipei Taiwan Department of Business Management Fujian University of Technology Fuzhou China Institute of Construction Engineering and Management National Central University Taoyuan Taiwan College of Computer Science and Engineering Shandong University of Science and Technology Shandong China College of Mechanical and Electrical Engineering National Taipei University of Technology Taipei Taiwan

ISBN: (纸本)9783030586683

the key industries of information technology in the semiconductor integrated circuit industry will have an important role after 2020, In the third generation of advanced semiconductor of 7nm 5G chips GaN is be used, MOCVD is a key technology for preparing high-quality communication semiconductor crystals. this study proposes PID controller of PSO and BP neural network algorithm to improve the control ability of MOCVD temperature. From the research results, it is found that the method proposed in this study adopts the PSO and BP neural network intelligent PID algorithm controller with Smith predictor, which has better dynamic performance, and the value from 150 to 500s is stable from 0 to 1 no vibration, any overshoot and short adjustment time, ideal control. © 2021, the Editor(s) (if applicable) and the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Controllers

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Number theoretic Transform: Generalization, Optimization, Concrete Analysis and Applications 16th

Number Theoretic Transform: Generalization, Optimization, Co...

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16th international conference on Information Security and Cryptology, Inscrypt 2020

作者： Liang, Zhichuang Shen, Shiyu Shi, Yuantao Sun, Dongni Zhang, Chongxuan Zhang, Guoyun Zhao, Yunlei Zhao, Zhixiang School of Computer Science Fudan University Shanghai China School of Mathematical Sciences Fudan University Shanghai China State Key Laboratory of Integrated Services Networks Xidian University Xi’an China Department of Applied Mathematics Reading Academy Nanjing University of Information Science and Technology Nanjing China

ISBN: (纸本)9783030718510

Number theoretic transform (NTT) is a basic mathematic operation, and is particularly fundamental to the practical implementations of cryptographic algorithms based on lattices with algebraic structures. In this work, we make a systematic and comprehensive study of NTT and its variants. We first review the NTT technique and the recent advances raised in the implementations of practical lattice-based cryptography. We clarify the relationship of some existing NTT variants, and prove their computational equivalence. We then make the generalizations of NTT, analyze their exact computational complexity, and derive the optimal bounds. Finally, we show the applications of our results to some prominent practical lattice-based algorithms. © 2021, Springer Nature Switzerland AG.

关键词： Cryptography

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Anonymous Fine-Grained User Access Control Scheme for Internet of things Architecture 5th

Anonymous Fine-Grained User Access Control Scheme for Intern...

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5th international conference on Mathematics and Computing, ICMC 2019

作者： Banerjee, Soumya Odelu, Vanga Das, Ashok Kumar Chattopadhyay, Samiran Giri, Debasis Department of Information Technology Jadavpur University Salt Lake CityKolkata700 098 India Department of Computer Science and Information Systems Birla Institute of Technology and Science Pilani Hyderabad Campus Hyderabad500 078 India Center for Security Theory and Algorithmic Research International Institute of Information Technology Hyderabad500 032 India Department of Information Technology Maulana Abul Kalam Azad University of Technology Kolkata700064 India

ISBN: (纸本)9789811554100

With the rapid growth of wireless technology, Internet of things (IoT) became very popular in both industrial as well as consumer product domains. While there is a lot of available platforms and technologies for IoT, the access control issue is often overlooked in the IoT security research. An effective access control depends on the proper user authentication mechanism. thus, access control in this scenario is an emerging and challenging problem in the IoT environment. In this paper, we design an anonymous fine-grained user access control mechanism for IoT architecture. In the proposed scheme, the user authentication is performed by the smart device node based on the user attributes, which enables fine-grained access control over the authorized data. We utilize the widely accepted formal verification tool, called the Automated Validation of Internet Security Protocols and Applications (AVISPA), to formally prove the security of the proposed scheme. Additionally, we also provide a detailed informal security analysis of the scheme. Finally, we perform a simulation study using the broadly used NS3 network simulator to show the practical impact on the proposed scheme on various network parameters. © 2021, the Editor(s) (if applicable) and the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Internet of things

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Pixel Based Adversarial Attacks on Convolutional Neural Network Models 4th

Pixel Based Adversarial Attacks on Convolutional Neural Netw...

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4th IFIP TC 12 international conference on Computational Intelligence in Data science, ICCIDS 2021

作者： Srinivasan, Kavitha Jello Raveendran, Priyadarshini Suresh, Varun Anna Sundaram, Nithya Rathna Department of Computer Science and Engineering Sri Sivasubramaniya Nadar College of Engineering Kalavakkam603 110 India

ISBN: (纸本)9783030925994

Deep Neural Networks (DNN) has found their applications in the real time, for example, facial recognition for security in ATMs and self-driving cars. A major security threat to DNN is through adversarial attacks. An adversarial sample is an image that has been changed in such a way that it is imperceptible to human eye but causes the image to be misclassified by a Convolutional Neural Networks (CNN). the objective of this research work is to devise pixel based algorithms for adversarial attacks on images. For validating the algorithms, untargeted attack is performed on MNIST and CIFAR-10 dataset using techniques such as edge detection, Gradient weighted Class Activation Mapping (GRAD-CAM) and noise addition whereas targeted attack is performed on MNIST dataset using Saliency maps. these adversarial images thus generated are then passed to a CNN model and the misclassification results are analyzed. From the analysis, it has been inferred that it is easier to fool CNNs using untargeted attacks than the targeted attacks. Also, grayscale images (MNIST) are preferred to generate robust adversarial examples compared to colored images (CIFAR-10). © 2021, IFIP international Federation for Information Processing.

关键词： Neural network models

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the Impact of Wechat Red Packet Feature at Achieving Users Satisfaction and Loyalty: Wechat Users in China 12th

The Impact of Wechat Red Packet Feature at Achieving Users S...

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12th international conference on advances in Swarm Intelligence, ICSI 2021

作者： Sleiman, Kamal Abubker Abrahim Juanli, Lan Cai, Xiangyu Yubo, Wang Hongzhen, Lei Liu, Ru School of Economics and Management Yan’an University Yan’an716000 China International School of Business Shaanxi Normal University Xi’an710062 China Xian University of Finance and Economics Xi’an Changan District710062 China

ISBN: (纸本)9783030788100

WeChat has become an essential social media platform in China. this research investigates the importance of the WeChat Red packet as a motivator at achieving user’s satisfaction and loyalty in China. To investigate its impact, and factors that attribute to its popularity and acceptability, we extended technology acceptance model (TAM), in addition to the main model factors, "perceived usefulness and perceived ease of use" our proposed model include, perceived trust, perceived security, and perceived entertainment. the questionnaire was designed, and SPSS was used for the analysis. the research results provide insight into how WeChat Red Packet can motivate users and build their satisfaction to improve their loyalty which in turn increases WeChat users’. these results have future implication and practice for research. © 2021, Springer Nature Switzerland AG.

关键词： Social networking (online)

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three Dimensional Wireframe Model of Medical and Complex Images Using Cellular Logic Array Processing Techniques 12th

Three Dimensional Wireframe Model of Medical and Complex Ima...

引用

12th international conference on Soft Computing and Pattern Recognition, SoCPaR 2020 and 16th international conference on Information Assurance and Security, IAS 2020

作者： Rani, Shilpa Lakhwani, Kamlesh Kumar, Sandeep School of Computer Science and Engineering Lovely Professional University Phagwara India Sreyas Institute of Engineering and Technology Hyderabad India

ISBN: (纸本)9783030736880

the main aim of computer vision is to provide the representation of images which is helpful for a better understanding of Two Dimensional and three-dimensional world. Considering this, in this paper we proposed a method called cellular logic array processing for three Dimensional wireframe representation of 3D images. this approach detects the junctions, straight lines, curves, depth of the 3D image and constructs the 3D wireframe model for the given dataset. the proposed algorithm has been evaluated on example-based Synthesis of 3D Object Arrangements dataset, PASCAL 3D+ dataset, and our own medical images dataset. the time complexity of the proposed method is O(n3r3) + O(n3) and the Average processing time is 1.12 s. the number of passes required for converting an input image into a wireframe model is one that is less than the other methods. the proposed method is simpler and has better accuracy compared to other wireframe based methods. © 2021, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Medical imaging

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Hard-Mining Loss Based Convolutional Neural Network for Face Recognition 1

引用

5th international conference on computer Vision and Image Processing, CVIP 2020

作者： Srivastava, Yash Murali, Vaishnav Dubey, Shiv Ram Computer Vision Group Indian Institute of Information Technology Sri City Chittoor Andhra Pradesh India

ISBN: (数字)9789811611032

ISBN: (纸本)9789811611025

Face Recognition is one of the prominent problems in the computer vision domain. Witnessing advances in deep learning, significant work has been observed in face recognition, which touched upon various parts of the recognition framework like Convolutional Neural Network (CNN), Layers, Loss functions, etc. Various loss functions such as Cross-Entropy, Angular-Softmax and ArcFace have been introduced to learn the weights of network for face recognition. However, these loss functions do not give high priority to the hard samples as compared to the easy samples. Moreover, their learning process is biased due to a number of easy examples compared to hard examples. In this paper, we address this issue by considering hard examples with more priority. In order to do so, We propose a Hard-Mining loss by increasing the loss for harder examples and decreasing the loss for easy examples. the proposed concept is generic and can be used with any existing loss function. We test the Hard-Mining loss with different losses such as Cross-Entropy, Angular-Softmax and ArcFace. the proposed Hard-Mining loss is tested over widely used Labeled Faces in the Wild (LFW) and YouTube Faces (YTF) datasets. the training is performed over CASIA-WebFace and MS-Celeb-1M datasets. We use the residual network (i.e., ResNet18) for the experimental analysis. the experimental results suggest that the performance of existing loss functions is boosted when used in the framework of the proposed Hard-Mining loss. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Face recognition

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Developing a Framework for Acquisition and Analysis of Speeches 4th

Developing a Framework for Acquisition and Analysis of Speec...

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4th international conference on Advanced Computing and Intelligent Engineering, ICACIE 2019

作者： Hossain, Md. Billal Arefin, Mohammad Shamsul Habib, Mohammad Ashfak Department of Computer Science & Engineering Chittagong University of Engineering & Technology Chattogram4349 Bangladesh

ISBN: (纸本)9789811565830

Speech plays a vital role for human communication. Proper delivery of speech can enable a person to connect with a large number of people. Nowadays, a lot of valuable speeches are being provided by many popular people throughout the world and it will be very helpful if important information can be extracted from those speeches by analyzing them. An automatic speech-to-text converter can facilitate the task of speech analysis. there have been carried out a lot of works for the conversion of speech to text in the last few decades. this paper presents a framework for the acquisition of speech along with the location of the speaker and then conversion of that speech into text. We have worked with speeches containing three different languages. To evaluate our framework, we collected speeches from several locations and the result shows that the framework can be used for efficient collection and analysis of the speeches. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Tracking (position)

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A Cell Tracking Method with Deep Learning Mitosis Detection in Microscopy Images 12th

A Cell Tracking Method with Deep Learning Mitosis Detection ...

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12th international conference on advances in Swarm Intelligence, ICSI 2021

作者： Wu, Di Xu, Benlian Lu, Mingli Shi, Jian Li, Zhen Guan, Fei Yang, Zhicheng School of Electrical and Power Engineering China University of Mining and Technology Xuzhou China School of Mechanical Engineering Changshu Institute of Technology Changshu China School of Electrical and Automatic Engineering Changshu Institute of Technology Changshu China

ISBN: (纸本)9783030788100

Cell motion analysis plays an important role in biomedical fields such as disease diagnosis and drug development. A crucial step in quantifying cell dynamics is to detect mitosis, which is the process that a mother cell divided into two daughter cells. To gain an accurate analysis of multiple cells, a deep framework combining U-net and convolution LSTM is proposed to simultaneously segment cells and detect mitosis, in which the spatiotemporal information of image sequences is fully utilized to predict the locations of cell and the occurrence of mitosis. With the obtained cell segmentation and mitotic event, a particle filter based tracking method is proposed to estimate individual state of cells, in which a two-step data association strategy is developed to handle the mitotic assignment. Simulation results are presented to show that the proposed method has favorable performance and can track cells effectively with mitosis. © 2021, Springer Nature Switzerland AG.

关键词： Image segmentation

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