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16th ACM International Conference on Mobile Systems, Applications, and Services,MobiSys 2018

作者： Yang, Qiang Fu, Hongrui Zou, Yongpan Wu, Kaishun College of Computer Science and Software Engineering Shenzhen University China

ISBN: (纸本)9781450357203

Recently, tiny smart devices have become increasingly popular in our lives because of their neat features and stylish appearance. However, their small form factors, especially screens, make it inconvenient for users to enter texts with conventional methods such as soft keyboards, which need a fairly large screen. To address this problem, we propose a novel texts-input system, called EchoType, with which users can enter texts with a finger writing in the air. EchoType makes use of acoustic sensors (i.e., microphone and speaker) to sense finger gestures and infer texts based on mapping relation between gestures and basic letters. We take a step to enable users to input texts with acoustic signals. Compared with existing approaches, EchoType enjoys merits of low hardware requirements and high scalability to different mobile devices. © 2018 Copyright held by the owner/author(s).

关键词： Acoustic waves

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Research on Green Energy Saving ECO Intelligent System engineering Cycle

Research on Green Energy Saving ECO Intelligent System Engin...

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2020 International Conference on Green Energy, Environment and Sustainable Development, GEESD 2020

作者： Chen, Jue-Jia Wu, Shinn-Dar Chen, Dong-Yan Li, Jie Huang, Ta-Wei Software Engineering Department of Computer Science Neusoft Institute Guangdong Guangdong Province Foshan528225 China School of Chemistry and Materials Engineering Huizhou University Huizhou Guangdong516007 China USA Saint Paul's College and DePaul University 115 College Drive LawrencevilleVA23868 United States Royal Global Business Center Legaspi Village Makati City Metro Manila1229 Philippines South China Agricultural University Tianhe District Guangzhou510642 China Department of Information Management and Engineering Neusoft Institute Guangdong Guangdong Province Foshan528225 China

With the improvement of living standards, the national coverage of heaters is also higher. From the original only the northern part of the installation of heating devices, to the south of the central area has also installed heaters, and even some people in the southern area installed heaters. With the increase in sales volume and fierce competition, companies need to reform and innovate products to meet the higher requirements of customers for energy-saving effects, comfort and safety. The design of the heater involves theories of structure, integrated circuit, program algorithm, aerodynamics, heat transfer and so on. Due to the technical level and cost constraints of enterprises, few companies can produce safe, energy-saving, moisturizing and comfortable heaters suitable for the public. In this study, the green energy-saving circulating heater of ECO intelligent system adopts the incremental ECO processing algorithm, with the single-chip STC89C52 as the main control chip system, combined with the peripheral STC89C52 temperature data acquisition, HIH-3010 humidity data collector, A/D Conversion module, keyboard settings, LCD1602 liquid crystal display and other circuit modules. This design realizes the temperature value that the heater provides the user with the optimum indoor temperature value and sets the heating according to the user's needs. When the set temperature value is reached or the temperature is high, the controller will control the heating element to reduce power or automatically power off to achieve safe power saving effect. © Published under licence by IOP Publishing Ltd.

关键词： Intelligent systems

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Mobility-Aware Dynamic Taxi Ridesharing

Mobility-Aware Dynamic Taxi Ridesharing

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International Conference on Data engineering

作者： Zhidan Liu Zengyang Gong Jiangzhou Li Kaishun Wu Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ) Shenzhen University P. R. China College of Computer Science and Software Engineering Shenzhen University P R. China

ISBN: (数字)9781728129037

ISBN: (纸本)9781728129044

Taxi ridesharing becomes promising and attractive because of the wide availability of taxis in a city and tremendous benefits of ridesharing, e.g., alleviating traffic congestion and reducing energy consumption. Existing taxi ridesharing schemes, however, are not efficient and practical, due to they simply match ride requests and taxis based on partial trip information and omit the offline passengers, who hail a taxi at roadside with no explicit requests to the system. In this paper, we consider the mobility-aware taxi ridesharing problem, and present mT- Share to address these limitations. mT-Share fully exploits the mobility information of ride requests and taxis to achieve efficient indexing of taxis/requests and better passenger-taxi matching, while still satisfying the constraints on passengers' deadlines and taxis' capacities. Specifically, mT-Share indexes taxis and ride requests with both geographical information and travel directions, and supports the shortest path based routing and probabilistic routing to serve both online and offline ride requests. Extensive experiments with a large real-world taxi dataset demonstrate the efficiency and effectiveness of mT-Share, which can response each ride request in milliseconds and with a moderate detour cost. Compared to state-of-the-art methods, mT-Share serves 42% and 62% more ride requests in peak and non-peak hours, respectively.

关键词： Public transportation Schedules Routing Urban areas Trajectory Roads Indexing

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Verifying Arithmetic in Cryptographic C Programs

Verifying Arithmetic in Cryptographic C Programs

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IEEE International Conference on Automated software engineering (ASE)

作者： Jiaxiang Liu Xiaomu Shi Ming-Hsien Tsai Bow-Yaw Wang Bo-Yin Yang College of Computer Science and Software Engineering Shenzhen University Academia Sinica Institute of Information Science

Cryptographic primitives are ubiquitous for modern security. The correctness of their implementations is crucial to resist malicious attacks. Typical arithmetic computation of these C programs contains large numbers of non-linear operations, hence is challenging existing automatic C verification tools. We present an automated approach to verify cryptographic C programs. Our approach successfully verifies C implementations of various arithmetic operations used in NIST P-224, P-256, P-521 and Curve25519 in OpenSSL. During verification, we expose a bug and a few anomalies that have been existing for a long time. They have been reported to and confirmed by the OpenSSL community. Our results establish the functional correctness of these C implementations for the first time.

关键词： Reactive power Tools computer bugs Elliptic curve cryptography NIST

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Research on Key Technologies of Topology Control in Mobile Predictive Ad Hoc Networks

Research on Key Technologies of Topology Control in Mobile P...

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Wireless Communications and Smart Grid (ICWCSG), 2020 International Conference on

作者： Li Jiang San Quan Ke Le Zhang South china institute of Software Engineering Gu Guangzhou China Guangzhou Yide Trading Co. Ltd China College of Computer Science Inner Mongolia University Hohhot Inner Mongolia China

ISBN: (数字)9781728198200

ISBN: (纸本)9781728198217

Mobile Ad Hoc network is composed of a group of nodes equipped with wireless communication devices and networking capabilities, which does not need any infrastructure. Compared with the traditional wireless network, the mobile Ad Hoc network is a self constructed, self-organized and self managed network without any centralized infrastructure. The reliability of mobile Ad Hoc network can be improved from the aspects of transmission control, routing protocol, topology control, etc. in this paper, an Ad Hoc network topology control model is proposed. Considering the main objectives of topology control, an Ad Hoc network is designed according to the related network model. the related factors of topology control are synthetically measured, and a key algorithm of topology control is designed by using OPNET The network modeling and simulation tools verify the reliability of the algorithm, reduce the energy consumption of the network, have better end-to-end transmission performance, and effectively enhance the reliability of mobile Ad Hoc network. It improves the ability of mobile prediction and guarantees the connectivity and service quality of the network.

关键词： Topology Network topology Ad hoc networks Conferences Wireless communication Smart grids Quality of service

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A Gait Recognition Method Based on the Combination of Human Body Posture and Human Body Contour

A Gait Recognition Method Based on the Combination of Human ...

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作者： Yue Ma Chenghao Wei Hao Long Key Laboratory of Impression Evidence Examination and Identification Technology(Criminal Investigation Police University of China) Ministry of Public Security Big Data Institute College of Computer Science and Software EngineeringShenzhen University

Aiming at the issues that affect the gait recognition, such as outfit changes and carryon-objects during gait recognition, this paper proposes a gait recognition method based on the improved GaitSet network, which relies on the fusion of human posture and human contour. This method introduces key points of human posture, and improves the precision of human contour extraction by introducing the key points of human posture. At the same time, the human posture map composed of the key points of human posture is used as the synchronous attribute of the contour map to extract gait features. Because key points focus on the inherent walking characteristics of human body, they are not affected by the external information such as clothing and carrying objects. Combined with the rich gait change attributes of human contour, it can effectively improve the accuracy and robustness of the gait recognition model. In scenes of human body wearing coats, our experimental results show that the accuracy of the proposed method in CASIA-B gait data set and self-built database can reach over 73.5% accuracy.

关键词： A Gait Recognition Method Based on the Combination of Human Body Posture and Human Body Contour

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iLGaCo: Incremental Learning of Gait Covariate Factors

iLGaCo: Incremental Learning of Gait Covariate Factors

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IEEE International Joint Conference on Biometrics (IJCB)

作者： Zihao Mu Francisco M. Castro Manuel J. Marín-Jiménez Nicolás Guil Yan-Ran Li Shiqi Yu College of Computer Science and Software Engineering Shenzhen University China University of Málaga Spain University of Córdoba Spain Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS) China Southern University of Science and Technology China

ISBN: (数字)9781728191867

ISBN: (纸本)9781728191874

Gait is a popular biometric pattern used for identifying people based on their way of walking. Traditionally, gait recognition approaches based on deep learning are trained using the whole training dataset. In fact, if new data (classes, view-points, walking conditions, etc.) need to be included, it is necessary to re-train again the model with old and new data samples. In this paper, we propose iLGaCo, the first incremental learning approach of covariate factors for gait recognition, where the deep model can be updated with new information without re-training it from scratch by using the whole dataset. Instead, our approach performs a shorter training process with the new data and a small subset of previous samples. This way, our model learns new information while retaining previous knowledge. We evaluate iLGaCo on CASIA-B dataset in two incremental ways: adding new view-points and adding new walking conditions. In both cases, our results are close to the classical `training-from-scratch' approach, obtaining a marginal drop in accuracy ranging from 0.2% to 1.2%, what shows the efficacy of our approach. In addition, the comparison of iLGaCo with other incremental learning methods, such as LwF and iCarl, shows a significant improvement in accuracy, between 6% and 15% depending on the experiment.

关键词： Training Gait recognition Adaptation models Feature extraction Legged locomotion Task analysis Biological system modeling

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Research and Implementation of Anti-occlusion Algorithm for Vehicle Detection in Video Data 16th

Research and Implementation of Anti-occlusion Algorithm for ...

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16th Web Information Systems and Applications Conference, WISA 2019

作者： Wu, Yongqi Zhou, Zhichao Yao, Lan Yu, Minghe Yan, Yongming College of Computer Science and Engineering Northeastern University Shenyang110819 China College of Software Northeastern University Shenyang110819 China Department of Video Big Data DIXN Technology Co. Ltd. Shenyang110004 China

ISBN: (纸本)9783030309510

Object detection is an important branch of image processing and computer vision, which has become a hot research issue in recent years. Accurate target detection in a video is the foundation of intelligent surveillance system. Since the background scenario is dynamic and even especially complicated when vehicles occlude, the target detection accuracy is declined. Therefore, based on the bounding box regression algorithm, this paper constructs adjacent punishment mechanism to make the bounding box clear off other objects. The proposal weak confidence suppression is leveraged for the robustness of the detector when occlusion happens. Experiments show that the proposed method outperforms traditional methods on three different datasets. © 2019, Springer Nature Switzerland AG.

关键词： Object detection

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A semi-supervised approach of graph-based with local and global consistency

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International Journal of Information Technology and Management 2019年第2-3期18卷 243-255页

作者： Zhang, Yihao Wen, Junhao Liu, Zhi Zhu, Changpeng College of Computer Science and Engineering Chongqing University of Technology Chongqing400054 China College of Software Engineering Chongqing University Chongqing400030 China

An approach of graph-based semi-supervised learning is proposed that consider the local and global consistency of data. Like most graph-based semi-supervised learning, the algorithm mainly focused on two key issues: the graph construction and the manifold regularisation framework. In the graph construction, these labelled and unlabelled data are represented as vertices encoding edges weights with the similarity of instances, which means that not only the local geometry information but also the class information are utilised. In manifold regularisation framework, the cost function contains two terms of smoothness constraint and fitting constraint, it is sufficiently smooth with respect to the intrinsic structure revealed by known labelled and unlabelled instances. Specifically, we design the algorithm that uses the normalised Laplacian eigenvectors, which ensure the cost function can converge to closed form expression and then, we provide the convergence proof. Experimental results on various datasets and entity relationship classification show that the proposed algorithm mostly outperforms the popular classification algorithm. Copyright © 2019 Inderscience Enterprises Ltd.

关键词： Cost functions

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Development of a machine-learning system to classify lung CT scan images into normal/COVID-19 class

arXiv

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arXiv 2020年

作者： Kadry, Seifedine Rajinikanth, Venkatesan Rho, Seungmin Raja, Nadaradjane Sri Madhava Rao, Vaddi Seshagiri Thanaraj, Krishnan Palani Department of Mathematics and Computer Science Faculty of Science Beirut Arab University Lebanon Department of Electronics and Instrumentation Engineering St. Joseph’s College of Engineering Chennai600119 India Department of Software Sejong University Seoul05006 Korea Republic of Department of Mechanical Engineering St. Joseph’s College of Engineering Chennai600 119 India

Recently, the lung infection due to Coronavirus Disease (COVID-19) affected a large human group worldwide and the assessment of the infection rate in the lung is essential for treatment planning. This research aims to propose a Machine-Learning-System (MLS) to detect the COVID-19 infection using the CT scan Slices (CTS). This MLS implements a sequence of methods, such as multi-thresholding, image separation using threshold filter, feature-extraction, feature-selection, feature-fusion and classification. The initial part implements the Chaotic-Bat-Algorithm and Kapur’s Entropy (CBA+KE) thresholding to enhance the CTS. The threshold filter separates the image into two segments based on a chosen threshold ‘Th’. The texture features of these images are extracted, refined and selected using the chosen procedures. Finally, a two-class classifier system is implemented to categorize the chosen CTS (n=500 with a pixel dimension of 512x512x1) into normal/COVID-19 group. In this work, the classifiers, such as Naive Bayes (NB), k-Nearest Neighbors (KNN), Decision Tree (DT), Random Forest (RF) and Support Vector Machine with linear kernel (SVM) are implemented and the classification task is performed using various feature vectors. The experimental outcome of the SVM with Fused-Feature-Vector (FFV) helped to attain a detection accuracy of 89.80%. Copyright © 2020, The Authors. All rights reserved.

关键词： Feature extraction

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