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international Symposium on Digital Forensic and Security (ISDFS)

作者： Andrew Johnson Richard Ward Faculty of Computing Engineering and Mathematics University of South Wales Pontypridd Wales

ISBN: (数字)9781728169392

ISBN: (纸本)9781728169408

this paper presents a `Unified Side Channel Attack Model' (USCA-M). the USCA-M model is compiled by the research undertaken of side-channel attacks (SCAs) from published journal articles and conference papers between 2015-2019. the research found that SCAs can be categorised into three main areas: SCA types, SCA methods and SCA techniques. By using this categorisation as a foundation, the USCA-M was compiled. USCA-M has three main contributions to the research field:1.A unified model that can categorize present and future SCA vulnerabilities and exploit techniques found.2.A reference point for organisations to be able to identify and place a found SCA within a common or unified *** decomposition of SCA methods and techniques into identifiable components to assist in the defence of SCAs, such as code pattern recognition.

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Spectral Efficiency for Multi-pair Massive MIMO Two-Way Relay Networks with Hybrid Processing 8th

Spectral Efficiency for Multi-pair Massive MIMO Two-Way Rela...

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8th international conference on Communications, Signal Processing, and Systems, CSPS 2019

作者： Wang, Hongyan Li, Zhengquan Xue, Xiaomei Li, Baolong Liu, Yang Wu, Guilu Wu, Qiong Graduate School of Engineering Nagasaki University Nagasaki852-8521 Japan Jiangsu Provincial Engineering Laboratory of Pattern Recognition and Computational Intelligence Jiangnan University Wuxi214122 China National Mobile Communication Research Laboratory Southeast University Nanjing210096 China

ISBN: (纸本)9789811394089

In millimeter wave (mm-wave) communication systems, large antenna array can be employed for higher data rates. Hybrid digital and analogue beamforming design is adopted to reduce the digital signal processing (DSP) power consumption and the circuitry complexity. In this paper, we investigate the multi-pair massive MIMO two-way relay networks with hybrid processing architecture. Furthermore, the power scaling scheme is also considered. We got some conclusions that when the number of antennas at relay station M goes huge, the asymptotic spectral efficiency can be obtained. We also compared three cases of power scaling schemes and obtained the optimal case specially when M tends to considerable large. We can draw the conclusion that when, the Case 2 (only the transmit power of users scaled by M in power scaling schemes) is the optimal case compared with the other two cases. Finally, the Monte-Carlo is employed to demonstrate the validity of analytical results. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Spectrum efficiency

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House Rent Prediction Based on Joint Model 19

House Rent Prediction Based on Joint Model

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Proceedings of the 2019 8th international conference on computing and pattern recognition

作者： Kun Zhang LingCong Shen Ningning Liu School of Information Technology and Management University of International Business and Economics

ISBN: (纸本)9781450376570

With the development of the house leasing market, the house rents of several large cities in China have experienced rapid growth due to the increasing demand. In this paper, we focus on investigating various machine learning approaches to predict the house rent. Firstly, we not only have investigated different rent-related features including community condition, location, traffic and house condition, but also have employed various prediction models including XGBoost, LightGBM and CatBoost algorithms. Based on these, we proposed a joint model, which is a combination of above three models by linear weighting learned from least square method. Our best model ranks in top3% in the public Data Castle competition, which proves the joint model can effectively improve the accuracy and stability of the rent prediction compared to other prediction models.

关键词： CatBoost House Rent LightGBM Joint Model Prediction XGBoost

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PON: Proposal Optimization Network for Temporal Action Proposal Generation 16th

PON: Proposal Optimization Network for Temporal Action Propo...

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16th international conference on Intelligent computing, ICIC 2020

作者： Peng, Xiaoxiao Du, Jixiang Zhang, Hongbo Department of Computer Science and Technology Huaqiao University Quanzhou China Fujian Key Laboratory of Big Data Intelligence and Security Huaqiao University Quanzhou China Xiamen Key Laboratory of Computer Vision and Pattern Recognition Huaqiao University Quanzhou China

ISBN: (纸本)9783030607951

Temporal action localization is a challenging task in video understanding. Although great progress has been made in temporal action localization, the most advanced methods still have the problem of sharp performance degradation when an action proposal generated. Most methods use sliding windows method or simply group frames according to frame-level scores. these methods are not enough to provide accurate action boundary and maintain reasonable temporal structure. In order to solve these problems, we propose a novel proposal optimization network to generate start score, end score, action score and regression score, and then remove the redundancy by NMS algorithm. In the proposed method, we introduce a metric loss function to maintain the temporal structure of action proposal in the training process. To verify the effectiveness of the proposed method, we have made comparative experiments on ActivityNet-1.3 dataset respectively, and the proposed method has surpassed some of the state-of-the-art methods on the dataset. © 2020, Springer Nature Switzerland AG.

关键词： Passive optical networks

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Systematic Design of Approximate Adder Using Significance Based Gate-Level Pruning (SGLP) for Image Processing Application 8th

Systematic Design of Approximate Adder Using Significance Ba...

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8th international conference on pattern recognition and Machine Intelligence (PReMI)

作者： Jena, Sisir Kumar Biswas, Santosh Deka, Jatindra Kumar Indian Inst Technol Guwahati Dept CSE Gauhati India

ISBN: (纸本)9783030348724;9783030348717

Approximate computing techniques emerged as a novel design paradigm that utilizes the error-resilience property of many applications and helps in reducing the power and area consumption with an expense of loss in accuracy of the result. In this paper, we introduce Significance-based gate-level pruning (SGLP) technique to design an approximate adder circuit whose accuracy can be controlled using an Error-threshold provided by the application user. All previous method are nonsystematic and conceptually different from each other. those methods can either apply to a chain-based adder (adders made up of a chain of full adders, e.g., Ripple Carry Adder) or unchain-based adder (e.g., Kogge-Stone Adder) but not both. SGLP follows a systematic approach to generate an approximate version of a Full Adder which is later used to produce multi-bit adder. By using the SGLP method, we can also realize an approximate variant of an unchained adder. this characteristic makes the SGLP more superior than the previous methods. To check the quality and reliability, we have tested our approach using a DCT architecture for image processing particularly image compression and found that our result is acceptable to human perception-behavior on image clarity.

关键词： Approximate computing Approximate circuit design Approximate adder Low power design Gate-level pruning

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Low-Complexity Channel Estimation Method Based on ISSOR-PCG for Massive MIMO Systems 8th

Low-Complexity Channel Estimation Method Based on ISSOR-PCG ...

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8th international conference on Communications, Signal Processing, and Systems, CSPS 2019

作者： Zhou, Cheng Li, Zhengquan Wu, Qiong Liu, Yang Li, Baolong Wu, Guilu Zhao, Xiaoqing Jiangsu Provincial Engineering Laboratory of Pattern Recognition and Computational Intelligence Jiangnan University Wuxi214122 China National Mobile Communication Research Laboratory Southeast University Nanjing210096 China Department of Electronic Engineering Tsinghua University Beijing100084 China The National Key Laboratory of millimeter wave Southeast University Nanjing210096 China

ISBN: (纸本)9789811394089

With the boost of the quantity of antennas at the base station (BS) in massive multiple-input multiple-output (MIMO) systems, the channel capacity and spectral efficiency are also increased. Conventional channel estimation method, such as the classical minimum mean square error (MMSE), which involves the matrix inversion in large size with enormous computational complexity, especially in massive MIMO systems due to large antenna arrays. To degrade the complexity caused by the inversion of the matrix, a low-complexity channel estimation scheme is proposed based on the improved symmetric successive over relaxation preconditioned conjugate gradient (ISSOR-PCG) method to avoid computing the matrix inversion directly. A simple way is also introduced to address the optimal relaxation parameter for the proposed scheme, by utilizing the channel asymptotic orthogonality in massive MIMO systems. Analysis shows that the proposed channel estimator is able to degrade the complexity effectively compared with MMSE channel estimator. Simulation results illustrate that the proposed scheme can obtain near-optimal performance to the classical MMSE estimation method and outperforms other baseline schemes with increased number of iterations. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Mean square error

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An ETL pattern for log configuration and analysis 4

An ETL pattern for log configuration and analysis

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4th international conference on Big Data Analytics, Data Mining and Computational Intelligence 2019, BigDaCI 2019 and the 8th international conference on theory and Practice in Modern computing 2019, TPMC 2019

作者： Oliveira, Bruno Oliveira, Óscar Matos, Telmo Santos, Vasco Belo, Orlando CIICESI School of Management and Technology Porto Polytechnic Felgueiras Portugal ALGORITMI R and D Centre University of Minho Campus de Gualtar Braga Portugal

ISBN: (纸本)9789898533920

In many scenarios, such as the ones related to Data Warehousing Extract-Transform-Load (ETL) processes, logging techniques are usually applied for capturing event metrics across system levels for system auditing and system recovery. the diversity of strategies and architectures of the toolset used to support the ETL implementation introduces another layer of complexity, both for system development and audit. Although a valuable system diagnosis resource for the development team, logging is generally underestimated, being used only when the system reveals unexpected behaviours and not to drive the ETL system evolution. We believe that the use of logs for steering ETL development and maintenance can improve significantly global system quality. However, this approach is only effective if flexible and efficient logging systems exist. In this paper, we describe a Log pattern used in a pattern-oriented approach for ETL systems development, which provides a configurable and flexible component for using to drive ETL development and maintenance phases. © Multi conference on Computer Science and Information Systems, MCCSIS 2019. All rights reserved.

关键词： Data warehouses

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QIBDS Net: A Quantum-Inspired Bi-Directional Self-supervised Neural Network Architecture for Automatic Brain MR Image Segmentation 8th

QIBDS Net: A Quantum-Inspired Bi-Directional Self-supervised...

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8th international conference on pattern recognition and Machine Intelligence (PReMI)

作者： Konar, Debanjan Bhattacharyya, Siddhartha Panigrahi, Bijaya Ketan Sikkim Manipal Univ Sikkim Manipal Inst Technol Dept Comp Sci & Engn Majitar Sikkim India RCC Inst Informat Technol Dept Informat Technol Kolkata India Indian Inst Technol Dept Elect Engn New Delhi India

ISBN: (纸本)9783030348724;9783030348717

A Quantum-Inspired Bidirectional Self-Organizing Neural Network (QIBDS Net) architecture operated by Quantum-Inspired Multi-level Sigmoidal (QIMUSIG) activation function suitable for fully automatic segmentation of T1-weighted contrast enhanced (T1-CE) MR images, is proposed in real time. the QIBDS Net architecture comprises input, intermediate and output layers of neurons represented as qubits and inter-connected by second order neighborhood based topology. the inter-connections between the intermediate and output layers are effected by means of counter propagation of quantum states without any training or external supervision. Quantum observation is carried out at the end to obtain the segmented tumor from the superposition of quantum states. the proposed self-supervised network architecture has been tested on T1-CE MR images from publicly available data sets and is found to be very efficient while compared with other state of the art techniques.

关键词： Quantum computing QBDSONN SOFM CNN

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Acoustic Scene Classification by Enhanced High-Frequency Weak Signal Characteristic Spectrum 19

Acoustic Scene Classification by Enhanced High-Frequency Wea...

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Proceedings of the 2019 8th international conference on computing and pattern recognition

作者： Wenjie Hao Lasheng Zhao Qiang Zhang Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University

ISBN: (纸本)9781450376570

In the acoustic scene classification task, the method of using mel-spectrogram to express the acoustic scene information is widely applied. However, mel-spectrogram has defects and it ignores important information about some acoustic scenes. the paper improves the mel-spectrogram and its generation algorithm. Including: I. For the sensitivity of the acoustic scene to high-frequency acoustic signals, the paper changes the filter design method of Mel Frequency Cepstrum Coefficient (MFCC). this method preserves more high frequency information by applying the equal-height triangular filter banks and increasing the number of the filters. II. Based on the previous step, an enhancement algorithm is proposed for the problem of the lack of high-frequency weak signals in the characteristic spectrum. the algorithm performs nonlinear mapping on the mel-spectrogram, which makes the transformed high-frequency weak signal feature information more obvious. the algorithm is verified by DCASE 2018 acoustic scene classification dataset and LITIS ROUEN dataset. the experimental results demonstrate the effectiveness of the proposed algorithm.

关键词： MFCC weak signal feature extraction Acoustic scene classification

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Symmetry prior for epipolar consistency

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international JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY 2019年第9期14卷 1541-1551页

作者： Preuhs, Alexander Maier, Andreas Manhart, Michael Kowarschik, Markus Hoppe, Elisabeth Fotouhi, Javad Navab, Nassir Unberath, Mathias Friedrich Alexander Univ Erlangen Nurnberg Pattern Recognit Lab Erlangen Germany Siemens Healthcare GmbH Forchheim Germany Johns Hopkins Univ Dept Comp Sci Baltimore MD 21218 USA

Purpose For a perfectly plane symmetric object, we can find two views-mirrored at the plane of symmetry-that will yield the exact same image of that object. In consequence, having one image of a plane symmetric object and a calibrated camera, we automatically have a second, virtual image of that object if the 3-D location of the symmetry plane is known. Methods We propose a method for estimating the symmetry plane from a set of projection images as the solution of a consistency maximization based on epipolar consistency. With the known symmetry plane, we can exploit symmetry to estimate in-plane motion by introducing the X-trajectory that can be acquired with a conventional short-scan trajectory by simply tilting the acquisition plane relative to the plane of symmetry. Results We inspect the symmetry plane estimation on a real scan of an anthropomorphic human head phantom and show the robustness using a synthetic dataset. Further, we demonstrate the advantage of the proposed method for estimating in-plane motion using the acquired projection data. Conclusion Symmetry breakers in the human body are widely used for the detection of tumors or strokes. We provide a fast estimation of the symmetry plane, robust to outliers, by computing it directly from a set of projections. Further, by coupling the symmetry prior with epipolar consistency, we overcome inherent limitations in the estimation of in-plane motion.

关键词： Symmetry Consistency conditions Cone-beam CT Motion compensation Data completeness Tomographic reconstruction

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