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arXiv 2020年

作者： Nkenyereye, Lewis Islam, S.M. Riazul Hossain, Mahmud Abdullah-Al-Wadud, M. Alamri, Atif Department of Computer and Information Security Sejong University Seoul05006 Korea Republic of Department of Computer Science and Engineering Sejong University Seoul05006 Korea Republic of Department of Computer Science University of Alabama at Birmingham AL35294 United States Department of Software Engineering King Saud University Riyadh11543 Saudi Arabia

The Internet of Medical Things (IoMT) offers an infrastructure made of smart medical equipment and software applications for health services. Through the internet, the IoMT is capable of providing remote medical diagnosis and timely health services. The patients can use their smart devices to create, store and share their electronic health records (EHR) with a variety of medical personnel including medical doctors and nurses. However, unless the underlying commination within IoMT is secured, malicious users can intercept, modify and even delete the sensitive EHR data of patients. Patients also lose full control of their EHR since most health services within IoMT are constructed under a centralized platform outsourced in the cloud. Therefore, it is appealing to design a decentralized, auditable and secure EHR system that guarantees absolute access control for the patients while ensuring privacy and security. Using the features of blockchain including decentralization, auditability and immutability, we propose a secure EHR framework which is mainly maintained by the medical centers. In this framework, the patients’ EHR data are encrypted and stored in the servers of medical institutions while the corresponding hash values are kept on the blockchain. We make use of security primitives to offer authentication, integrity and confidentiality of EHR data while access control and immutability is guaranteed by the blockchain technology. The security analysis and performance evaluation of the proposed framework confirms its efficiency. © 2020, CC-BY.

关键词： Access control

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An improved smith-waterman algorithm based on spark parallelization

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International Journal Bioautomation 2019年第1期23卷 117-129页

作者： Liu, Yanfeng Li, Leixiao Gao, Jing College of Data Science and Application Inner Mongolia University of Technology Hohhot010080 China College of Computer and Information Engineering Inner Mongolia Agricultural University Hohhot010018 China Inner Mongolia Autonomous Region Engineering Technology Research Center of Big Data Based Software Service Inner Mongolia University of Technology Hohhot010080 China

This paper proposes the design and the implementation of a Spark parallelization plan for improving the Smith-Waterman (SW) algorithm, named the Spark-OSW algorithm. Then, the Spark-OSW was verified through accuracy, performance and acceleration tests. The results show that the proposed algorithm achieved 100% accuracy, ran much faster than the SW, and performed well in cluster environment. The research findings shed important new light on the database search for gene sequences. © 2019 INT. J. Bioautomation.

关键词： Search engines

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RETRACTED ARTICLE: Automatically human action recognition (HAR) with view variation from skeleton means of adaptive transformer network

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Soft Computing 2023年第2期28卷 485-485页

作者： Mehmood, Faisal Chen, Enqing Abbas, Touqeer Akbar, Muhammad Azeem Khan, Arif Ali School of Electrical and Information Engineering Zhengzhou University Zhengzhou China Henan Xintong Intelligent IOT Co. Ltd. No.1-303 Intersection of Ruyun Road and Meihe Road Zhengzhou China Department of Computer Science and Technology Beijing University of Chemical Technology Beijing China Department of Software Engineering LUT University Lahti Finland M3S Empirical Software Engineering Research Unit University of Oulu Oulu Finland

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A unified end-to-end framework for efficient deep image compression

arXiv

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arXiv 2020年

作者： Liu, Jiaheng Lu, Guo Hu, Zhihao Xu, Dong School of Computer Science and Engineering Beihang University Beijing China Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China School of Software Beihang University Beijing China School of Electrical and Information Engineering University of Sydney NSW2006 Australia

Image compression is a widely used technique to reduce the spatial redundancy in images. Recently, learning based image compression has achieved significant progress by using the powerful representation ability from neural networks. However, the current state-of-the-art learning based image compression methods suffer from the huge computational complexity, which limits their capacity for practical applications. In this paper, we propose a unified framework called Efficient Deep Image Compression (EDIC) based on three new technologies, including a channel attention module, a Gaussian mixture model and a decoder-side enhancement module. Specifically, we design an auto-encoder style network for learning based image compression. To improve the coding efficiency, we exploit the channel relationship between latent representations by using the channel attention module. Besides, the Gaussian mixture model is introduced for the entropy model and improves the accuracy for bitrate estimation. Furthermore, we introduce the decoder-side enhancement module to further improve image compression performance. Our EDIC method can also be readily incorporated with the Deep Video Compression (DVC) framework [1] to further improve the video compression performance. Simultaneously, our EDIC method boosts the coding performance significantly while bringing slightly increased computational complexity. More importantly, experimental results demonstrate that the proposed approach outperforms the current state-of-the-art image compression methods and is up to more than 150 times faster in terms of decoding speed when compared with Minnen's method [2]. The proposed framework also successfully improves the performance of the recent deep video compression system DVC [1]. Copyright © 2020, The Authors. All rights reserved.

关键词： Complex networks

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High-rate and high-capacity measurement-deviceindependent quantum key distribution with Fibonacci matrix coding in free space

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science China(information sciences) 2018年第6期61卷 227-237页

作者： Hong LAI Mingxing LUO Josef PIEPRZYK Jun ZHANG Lei PAN Mehmet A.ORGUN School of Computer and Information Science and Centre for Research and Innovation in Software Engineering (RISE) Southwest University Information Security and National Computing Grid Laboratory School of Information Science and TechnologySouthwest Jiaotong University School of Electrical Engineering and Computer Science Queensland University of Technology Institute of Computer Science Polish Academy of Sciences School of Information Technology Deakin University Department of Computing Macquarie University Faculty of Information Technology Macau University of Science and Technology

This paper proposes a high-rate and high-capacity measurement-device-independent quantum key distribution(MDI-QKD) protocol with Fibonacci-valued and Lucas-valued orbital angular momentum(OAM) entangled states in free space. In the existing MDI-OAM-QKD protocols, the main encoding algorithm handles encoded numbers in a bit-by-bit manner. To design a fast encoding algorithm, we introduce a Fibonacci matrix coding algorithm, by which, encoded numbers are separated into segments longer than one bit. By doing so, when compared to the existing MDI-OAM-QKD protocols, the new protocol can effectively increase the key rate and the coding capacity. This is because Fibonacci sequences are used in preparing OAM entangled states, reducing the misattribution errors(which slow down the execution cycle of the entire QKD) in QKD protocols. Moreover, our protocol keeps the data blocks as small as possible, so as to have more blocks in a given time interval. Most importantly, our proposed protocol can distill multiple Fibonacci key matrices from the same block of data, thus reducing the statistical fluctuations in the sample and increasing the final QKD rate. Last but not the least, the sender and the receiver can omit classical information exchange and bit flipping in the secure key distillation stage.

关键词： measurement-device-independent quantum key distribution Fibonacci-matrix coding free space orbital angular momentum bit flipping misattribution errors

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Discovery of time profiled temporal patterns 19

Discovery of time profiled temporal patterns

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5th International Conference on engineering and MIS, ICEMIS 2019

作者： Radhakrishna, Vangipuram Aljawarneh, Shadi Kumar, P.V. Janaki, Vinjamuri Cheruvu, Aravind Information Technology Dept VNR VJIET Hyderabad India Software Engg Dept JUST Jordan Computer Science and Engg Dept Acharya Institute of Technology Bangalore India Computer Science and Engg Dept Vaagdevi College of Engineering Warangal India

ISBN: (纸本)9781450372121

Finding temporal association patterns from temporal dataset is addressed in a wider perspective in the existing literature. Discovering time profiled temporal patterns is addressed in our previous research works which includes proposing new support estimation techniques, similarity measures for computing similarity between temporal patterns. Most measures proposed in our previous research are for Gaussian space. Our previous research proposed z-space dissimilarity measures SRIHASS and KRISHNA SUDARSANA. Following these two measures, there have been no z-space measures that are proposed in literature. This paper proposes a new similarity measure for determining similarity between temporal patterns in z-space. © 2019 Association for Computing Machinery. All rights reserved.

关键词： Z-score computational complexity support temporal pattern novel approach similarity computation

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Correction to “Performance Evaluation of LoRaWAN for Green Internet of Things”

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IEEE Access 2022年 10卷 125400-125400页

作者： Zulfiqar Ali Shagufta Henna Adnan Akhunzada Mohsin Raza Sung Won Kim Department of Software Engineering Bahria University Islamabad Pakistan Department of Computer Science Bahria University Islamabad Pakistan Telecommunications Software and Systems Group (TSSG) Waterford Institute of Technology (WIT) Waterford Ireland Department of Computer Science COMSATS University Islamabad Islamabad Pakistan Department of Design Engineering and Mathematics Middlesex University London London U.K Department of Information and Communication Engineering Yeungnam University Gyeongsan South Korea

In the above article [1] , we want to change the affiliation of the first author to “Department of software engineering, Bahria University, Islamabad, 46000, Pakistan” and add a new affiliation for the second author, which is “Department of computer science, Bahria University, Islamabad, 46000, Pakistan.” The first author (ZULFIQAR ALI; zulfijobs@***) is a Ph.D. student at Bahria University Islamabad, Pakistan, and the second author (SHAGUFTA HENNA; shaguftahenna@***) is his Ph.D. Supervisor.

关键词： Performance evaluation computer science Internet of Things software engineering

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Age-Aware Query Evaluation for Big Data Analytics in Mobile Edge Clouds

Age-Aware Query Evaluation for Big Data Analytics in Mobile ...

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IEEE International Conference on High Performance Computing and Communications (HPCC)

作者： Qiufen Xia Wenhao Ren Mingchu Li Jiankang Ren International School of Information Science and Engineering Dalian University of Technology Dalian China School of Software Dalian University of Technology Dalian China School of Computer Science and Technology Dalian University of Technology Dalian China

ISBN: (纸本)9781728176499;9781728176505

The advancement of 5G technology and extensive usage of smart devices have led to a deluge of data. It is invaluable to analyze such big data by issuing queries to derive real-time business insights for better, smarter and fact-based decisions. Timely big data analytics are crucial in many service domains, thus the age of data (AoD) required by queries is emerging as a novel metric that measures the freshness of data and evaluates the quality of data analytics. Traditional big data analytics that are performed in remote clouds cannot satisfy the AoD requirements of queries, due to the congested core networks and long transmission latency between users and clouds. The technique of mobile edge computing (MEC) is expected to reduce the age and guarantee the timeliness of queries for big data analytics, by processing data at edge cloudlets close to users. In this paper, we investigate a problem of age-aware query evaluation for big data analytics in a mobile edge cloud network. We first formulate the problem with certain data processing latency as an Integer Linear Program (ILP). We then develop an online learning algorithm for the problem with uncertain data processing latency. We finally evaluate the performance of proposed algorithms against existing studies by simulations and testbed implementations. Evaluation results show that the proposed algorithms outperform existing works by achieving 20% lower AoD.

关键词： Measurement Data analysis Query processing High performance computing Conferences Big Data Real-time systems

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Superpixel segmentation based on spatially constrained subspace clustering

arXiv

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arXiv 2020年

作者： Li, Hua Jia, Yuheng Cong, Runmin Wu, Wenhui Kwong, Sam Chen, Chuanbo School of Software Engineering Huazhong University of Science and Technology Wuhan430074 China Department of Computer Science City University of Hong Kong Kowloon Hong Kong School of Computer Science and Engineering Southeast University Nanjing211189 China Institute of Information Science Beijing Jiaotong University Beijing100044 China Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing Jiaotong University Beijing100044 China College of Electronics and Information Engineering Shenzhen University Shenzhen518060 China Department of Computer Science City University of Hong Kong Kowloon Hong Kong City University of Hong Kong Shenzhen Research Institute Shenzhen518057 China School of Software Engineering Huazhong University of Science and Technology Wuhan430074 China

Superpixel segmentation aims at dividing the input image into some representative regions containing pixels with similar and consistent intrinsic properties, without any prior knowledge about the shape and size of each superpixel. In this paper, to alleviate the limitation of superpixel segmentation applied in practical industrial tasks that detailed boundaries are difficult to be kept, we regard each representative region with independent semantic information as a subspace, and correspondingly formulate superpixel segmentation as a subspace clustering problem to preserve more detailed content boundaries. We show that a simple integration of superpixel segmentation with the conventional subspace clustering does not effectively work due to the spatial correlation of the pixels within a superpixel, which may lead to boundary confusion and segmentation error when the correlation is ignored. Consequently, we devise a spatial regularization and propose a novel convex locality-constrained subspace clustering model that is able to constrain the spatial adjacent pixels with similar attributes to be clustered into a superpixel and generate the content-aware superpixels with more detailed boundaries. Finally, the proposed model is solved by an efficient alternating direction method of multipliers (ADMM) solver. Experiments on different standard datasets demonstrate that the proposed method achieves superior performance both quantitatively and qualitatively compared with some state-of-the-art methods. © 2020, CC BY-NC-ND.

关键词： Clustering algorithms

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A mobile application for crowdsourced road condition monitoring 4

A mobile application for crowdsourced road condition monitor...

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4th International Conference on information Technology Research, ICITR 2019

作者： Kumara Thilakarathna, Thusithanjana Kavinda Perera, Hasith E Jayaweera, H H E Sri Lanka Institute of Information Technology Faculty of Computing Department of Computer Science and Software Engineering Malabe Sri Lanka University of Colombo Department of Physics Colombo 03 Sri Lanka

ISBN: (纸本)9781728161990

An Android App has been developed to measure geo-tagged vehicle-induced vibrations with the use of the built-in accelerometer of a mobile phone. The architecture of the app is designed in such a way that it can be published as a crowdsourced vehicle-induced vibration measurement data collection app. A simple calibration method has been developed to calibrate each individual axis of the accelerometer to get rid of imperfections within the three axes. The system is evaluated for extracting data of vibrations for a known system (simple pendulum) and the same system was tested for vehicle induced-vibration capturing. The results produced from the system during the test run correctly classified different road conditions. Once the crowdsourced data is available, a more statistically significant prediction could be performed. © 2019 IEEE.

关键词： Accelerometers

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