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arXiv 2021年

作者： Zhao, Yingying Dong, Mingzhi Wang, Yujiang Feng, Da Lv, Qin Dick, Robert P. Li, Dongsheng Lu, Tun Gu, Ning Shang, Li School of Computer Science Fudan University Shanghai China Shanghai Key Laboratory of Data Science Fudan University Shanghai China Shanghai Institute of Intelligent Electronics & Systems Shanghai China Department of Computing Imperial College London London United Kingdom Software Service Company Limited Beijing China University of Colorado Boulder BoulderCO United States Department of Electrical Engineering and Computer Science College of Engineering University of Michigan Ann ArborMI United States Microsoft Research Asia Shanghai China School of Computer Science Fudan University Shanghai China

Deep-learning-based video processing has yielded transformative results in recent years. However, the video analytics pipeline is energy-intensive due to high data rates and reliance on complex inference algorithms, which limits its adoption in energy-constrained applications. Motivated by the observation of high and variable spatial redundancy and temporal dynamics in video data streams, we design and evaluate an adaptive-resolution optimization framework to minimize the energy use of multitask video analytics pipelines. Instead of heuristically tuning the input data resolution of individual tasks, our framework utilizes deep reinforcement learning to dynamically govern the input resolution and computation of the entire video analytics pipeline. By monitoring the impact of varying resolution on the quality of high-dimensional video analytics features, hence the accuracy of video analytics results, the proposed end-to-end optimization framework learns the best non-myopic policy for dynamically controlling the resolution of input video streams to globally optimize energy efficiency. Governed by reinforcement learning, optical flow is incorporated into the framework to minimize unnecessary spatio-temporal redundancy that leads to re-computation, while preserving accuracy. The proposed framework is applied to video instance segmentation which is one of the most challenging computer vision tasks, and achieves better energy efficiency than all baseline methods of similar accuracy on the YouTube-VIS dataset. Copyright © 2021, The Authors. All rights reserved.

关键词： Energy efficiency

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A Blockchain-based Framework for Detecting Malicious Mobile Applications in App Stores

A Blockchain-based Framework for Detecting Malicious Mobile ...

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2019 IEEE Canadian Conference of Electrical and computer engineering, CCECE 2019

作者： Homayoun, Sajad Dehghantanha, Ali Parizi, Reza M. Choo, Kim-Kwang Raymond Department of Computer Engineering and Information Technology Shiraz University of Technology Shiraz Iran School of Computer Science University of Guelph ON Canada Department of Software Engineering and Game Development Kennesaw State University MariettaGA30060 United States Department of Information Systems and Cyber Security Department of Electrical and Computer Engineering University of Texas at San Antonio San AntonioTX78249 United States

ISBN: (纸本)9781728103198

The dramatic growth in smartphone malware shows that malicious program developers are shifting from traditional PC systems to smartphone devices. Therefore, security researchers are also moving towards proposing novel antimalware methods to provide adequate protection. This paper proposes a Blockchain-Based Malware Detection Framework (B2MDF) for detecting malicious mobile applications in mobile applications marketplaces (app stores). The framework consists of two internal and external private blockchains forming a dual private blockchain as well as a consortium blockchain for the final decision. The internal private blockchain stores feature blocks extracted by both static and dynamic feature extractors, while the external blockchain stores detection results as blocks for current versions of applications. B2MDF also shares feature blocks with third parties, and this helps antimalware vendors to provide more accurate solutions. © 2019 IEEE.

关键词： Blockchain

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A Model to Measure the Spread Power of Rumors

arXiv

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arXiv 2020年

作者： Jahanbakhsh-Nagadeh, Zoleikha Feizi-Derakhshi, Mohammad-Reza Ramezani, Majid Akan, Taymaz Asgari-Chenaghlu, Meysam Nikzad–Khasmakhi, Narjes Feizi-Derakhshi, Ali-Reza Ranjbar-Khadivi, Mehrdad Zafarani-Moattar, Elnaz Balafar, Mohammad-Ali Computerized Intelligence Systems Laboratory Department of Computer Engineering University of Tabriz Tabriz Iran Department of Computer Engineering Naghadeh Branch Islamic Azad University Naghadeh Iran Department of Computer Science and Research Branch Islamic Azad University Tehran Iran Department of Software Engineering Istanbul Topkapi University Istanbul Turkey Clinical Informatics Louisiana State University Health Sciences Center Shreveport Shreveport United States Department of Computer Engineering Shabestar Branch Islamic Azad University Shabestar Iran Department of Computer Engineering Tabriz Branch Islamic Azad University Tabriz Iran Department of Computer Engineering University of Tabriz Iran

With technologies that have democratized the production and reproduction of information, a significant portion of daily interacted posts in social media has been infected by rumors. Despite the extensive research on rumor detection and verification, so far, the problem of calculating the spread power of rumors has not been considered. To address this research gap, the present study seeks a model to calculate the Spread Power of Rumor (SPR) as the function of content-based features in two categories: False Rumor (FR) and True Rumor (TR). For this purpose, the theory of Allport and Postman will be adopted, which it claims that importance and ambiguity are the key variables in rumor-mongering and the power of rumor. Totally 42 content features in two categories"importance" (28 features) and"ambiguity" (14 features) are introduced to compute SPR. The proposed model is evaluated on two datasets, Twitter and Telegram. The results showed that (i) the spread power of False Rumor documents is rarely more than True Rumors. (ii) there is a significant difference between the SPR means of two groups False Rumor and True Rumor. (iii) SPR as a criterion can have a positive impact on distinguishing False Rumors and True Rumors. © 2020, CC BY.

关键词： Cell proliferation

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Classification of arrhythmia by using deep learning with 2-d ecg spectral image representation

arXiv

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arXiv 2020年

作者： Ullah, Amin Muhammad Anwar, Syed Bilal, Muhammad Majid Mehmood, Raja Software Engineering Department University of Engineering and Technology Taxila Punjab47050 Pakistan OrlandoFL32816 United States Division of Computer and Electronics Systems Engineering Hankuk University of Foreign Studies Yongin-si17035 Korea Republic of Information and Communication Technology Department School of Electrical and Computer Engineering Xiamen University Malaysia Sepang43900 Malaysia

The electrocardiogram (ECG) is one of the most extensively employed signals used in the diagnosis and prediction of cardiovascular diseases (CVDs). The ECG signals can capture the heart’s rhythmic irregularities, commonly known as arrhythmias. A careful study of ECG signals is crucial for precise diagnoses of patients’ acute and chronic heart conditions. In this study, we propose a two-dimensional (2-D) convolutional neural network (CNN) model for the classification of ECG signals into eight classes;namely, normal beat, premature ventricular contraction beat, paced beat, right bundle branch block beat, left bundle branch block beat, atrial premature contraction beat, ventricular flutter wave beat, and ventricular escape beat. The one-dimensional ECG time series signals are transformed into 2-D spectrograms through short-time Fourier transform. The 2-D CNN model consisting of four convolutional layers and four pooling layers is designed for extracting robust features from the input spectrograms. Our proposed methodology is evaluated on a publicly available MIT-BIH arrhythmia dataset. We achieved a state-of-the-art average classification accuracy of 99.11%, which is better than those of recently reported results in classifying similar types of arrhythmias. The performance is significant in other indices as well, including sensitivity and specificity, which indicates the success of the proposed *** Codes 68T10, 62H30 Copyright © 2020, The Authors. All rights reserved.

关键词： Diseases

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LSTM-Based Channel Prediction for Secure Massive MIMO Communications Under Imperfect CSI

LSTM-Based Channel Prediction for Secure Massive MIMO Commun...

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IEEE International Conference on Communications (ICC)

作者： Tenghui Peng Rongqing Zhang Xiang Cheng Liuqing Yang School of Software Engineering Tongji University Shanghai China State Key Laboratory of Advanced Optical Communication Systems and Networks Peking University Beijing China Department of Electrical and Computer Engineering Colorado State University CO USA

ISBN: (数字)9781728150895

ISBN: (纸本)9781728150901

In recent years, massive multiple-input multiple-output (MIMO) has been regarded as a promising technique in the fifth-generation (5G) communication systems. With the ability of focusing transmission beams on users, massive MIMO has a natural advantage in the field of physical layer security to improve the system secrecy performance. However, in practical mobile systems, the imperfect channel state information (CSI) caused by the channel estimation error and the transmission and processing delay will have a non-negligible impact on the system performance. In this paper, we investigate secure communications in a multi-user massive MIMO-enabled vehicular communication networks. Considering the influence of imperfect CSI on the secrecy performance, we derive a tight asymptotic lower bound of the system secrecy capacity under both perfect and imperfect CSI. Moreover, we further analyze the impact of vehicle speed on the system secrecy performance and propose a channel prediction scheme based on (Long Short-Term Memory) LSTM model to compensate for the negative effects of imperfect CSI, which can improve the system secrecy performance in high mobility scenario. Simulation results show that the imperfect CSI severely reduces the system secrecy capacity, but its negative effects can be effectively alleviated through the designed LSTM-based channel prediction and compensation scheme.

关键词： MIMO communication Channel estimation Precoding Interference Network security Physical layer Antennas

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ER Model Partitioning: Towards Trustworthy Automated systems Development

SSRN

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SSRN 2020年

作者： Pieris, Dhammika Wijegunesekera, M.C. Dias, N.G.J. Department of Human Resource Management Faculty of Commerce and Management Studies University of Kelaniya Sri Lanka Department of Software Engineering Faculty of Computing and Technology University of Kelaniya Sri Lanka Department of Computer Systems Engineering Faculty of Computing and Technology University of Kelaniya Sri Lanka

In database development, a conceptual model is created, in the form of an Entity-relationship(ER) model, and transformed to a relational database schema (RDS) to create the database. However, some important information represented on the ER model may not be transformed and represented on the RDS. This situation causes a loss of information during the transformation process. With a view to preserving information, in our previous study, we standardized the transformation process as a one-to-one and onto mapping from the ER model to the RDS. For this purpose, we modified the ER model and the transformation algorithm resolving some deficiencies existed in them. Since the mapping was established using a few real-world cases as a basis and for verification purposes, a formal-proof is necessary to validate the work. Thus, the ongoing research aiming to create a proof will show how a given ER model can be partitioned into a unique set of segments and use it to represent the ER model itself. How the findings can be used to complete the proof in the future will also be explained. Significance of the research on automating database development, teaching conceptual modeling, and using formal methods will also be discussed. © 2020, The Authors. All rights reserved.

关键词： Mapping

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ER model Partitioning: Towards Trustworthy Automated systems Development

arXiv

引用

arXiv 2020年

关键词： Mapping

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Semantic-Preserving Adversarial Text Attacks

TechRxiv

引用

TechRxiv 2021年

作者： Yang, Xinghao Gong, Yongshun Liu, Weifeng Bailey, James Zhu, Tianqing Tao, Dacheng Liu, Wei The School of Computer Science University of Technology Sydney 15 Broadway UltimoNSW2007 Australia The School of Software Shandong University Jinan China Qingdao266580 China The Department of Computing and Information Systems University of Melbourne Australia The JD Explore Academy China The Digital Science Institute Faculty of Engineering The University of Sydney DarlingtonNSW2008 Australia

Deep learning models are known immensely brittle to adversarial image examples, yet their vulnerability in text classification is insufficiently explored. Existing text adversarial attack strategies can be roughly divided into three categories, i.e., character-level attack, word-level attack, and sentence-level attack. Despite the success brought by recent text attack methods, how to induce misclassification with the minimal text modifications while keeping the lexical correctness, syntactic soundness, and semantic consistency simultaneously is still a challenge. To examine the vulnerability of deep models, we devise a Bigram and Unigram based adaptive Semantic Preservation Optimization (BU-SPO) approach which attacks text documents not only at a unigram word level but also at a bigram level to avoid generating meaningless sentences. We also present a hybrid attack strategy that collects substitution words from both synonyms and sememe candidates, to enrich the potential candidate set. Besides, a Semantic Preservation Optimization (SPO) method is devised to determine the word substitution priority and reduce the perturbation cost. Furthermore, we constraint the SPO with a semantic Filter (dubbed SPOF) to improve the semantic similarity between the input text and the adversarial example. To estimate the effectiveness of our proposed methods, BU-SPO and BU-SPOF, we attack four victim deep learning models trained on three real-world text datasets. Experimental results demonstrate that our approaches accomplish the highest semantics consistency and attack success rates by making the minimal word modifications compared with competitive methods. © 2021, CC BY.

关键词： Semantics

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Mobile Apps Designed for Patients With Polycystic Ovary Syndrome: Content Analysis Using the Mobile App Rating Scale

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Journal of medical Internet research 2025年 27卷 e71118页

作者： Zahra Arabkermani Saeed Barzegari Atefeh Rouhani Nilofar Nahavandi Omer Gibreel Ibrahim Arpaci Department of Paramedicine Amol School of Paramedical Sciences Mazandaran University of Medical Sciences Sari Iran. Student Research Committee Mazandaran University of Medical Sciences Farah Abad Street 1454 Sari 48175 Iran ***. Management Information Systems College of Business Administration Gulf University for Science and Technology Mishref Kuwait. Department of Software Engineering Faculty of Engineering and Natural Sciences Bandirma Onyedi Eylul University Balıkesir Turkey. Department of Computer Science and Engineering College of Informatics Korea University Seoul Republic of Korea.

Background:Digital health interventions, especially mobile apps, have become instrumental in helping women at risk of polycystic ovary syndrome (PCOS), increasing their understanding of the condition, improving self-care, and fostering empowerment. However, their rapid proliferation has brought about significant challenges regarding quality assessment and evidence-based determination. Therefore, establishing reliable quality assessment methods is essential to assist patients with PCOS in identifying effective and trustworthy mobile health tools. Objective:This study was designed to assess the content and quality of mobile apps developed for patients with PCOS using the Mobile App Rating Scale (MARS) to provide insights into their strengths, limitations, and areas needing improvement. Methods:In this descriptive-analytical study conducted in June 2024, a comprehensive search was performed to identify English and Persian mobile apps related to PCOS through the Café Bazaar and Google Play Store platforms, using both direct search methods and auxiliary tools such as AppAgg and AppBrain. Two trained reviewers (AR and NN) independently reviewed the apps using the MARS tool. The interrater reliability was measured using the intraclass correlation coefficient test. The quality of each app was scored across 4 dimensions: engagement, functionality, aesthetics, and information quality. Results:Of the initial 199 apps identified, 15 met the inclusion criteria after screening and updates. The interrater agreement rate was 85%, which is considered acceptable. The apps' overall quality was sufficient, as assessed using the MARS, with a mean score of 3.6 (SD 0.52) of 5. Functionality and aesthetics emerged as the highest-scoring dimensions, highlighting user-friendliness and visual appeal (n=10). In contrast, engagement following information quality received the lowest average score, indicating limited interactivity and gaps in providing evidence-based information. The Ask PCOS app

关键词： Mobile App Rating Scale mobile apps patient satisfaction polycystic ovary syndrome reproductive health

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A modeling and simulation framework for UAVs utilizing 4G-LTE cellular networks

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International Journal of Modeling, Simulation, and Scientific Computing 2018年第5期9卷 108-139页

作者： Shafagh Jafer Stephen Jones Ashok Vardhan Raja Department of Electrical ComputerSoftwareand Systems Engineering Embry-Riddle Aeronautical UniversityDaytona Beach32114 FLUSA

Only a small amount of work has been published on the topic of exploiting existing Long-Term Evolution-Advanced(LTE)cellular communication network infrastructure for Unmanned Aerial Vehicles(UAV)data *** paper documents a modeling and simulation(m&s)framework that has been developed utilizing the powerful OMNeT++simulation tool for assessing the feasibility and effectiveness of this prospect in various UAV *** multiple scenarios,we have studied the data rate requirements for communications between small and medium-sized UAVs and base *** this framework,we have shown that the data rate requirements for the links are within the data throughput achieved by LTE *** developed framework implements a propagation model endorsed by the 3GPP LTE project team and also accurately models the high mobility of *** framework is highly configurable and extensible and boasts of automatic aggregation of results and chart *** outcomes of this research may be utilized by industry for rapidly deploying highly mobile,low-cost UAVs in a wide range of applications and scenarios.

关键词： Unmanned air vehicle communication UAV Data Link OMNET++ 4GLTE modeling and simulation.

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