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Received signal strength based indoor positioning algorithm using advanced clustering and kernel ridge regression Research Articles

Yanfen Le, Hena Zhang, Weibin Shi, Heng Yao,leyanfen@usst.edu.cn,hyao@usst.edu.cn

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 6,   Pages 827-838 doi: 10.1631/FITEE.2000093

Abstract: We propose a novel algorithm based on the . The proposed algorithm can be divided into three steps, an offline phase at which an (AC) strategy is used, an online phase of approximate localization at which is used, and an online phase of precise localization with . Specifically, after offline fingerprint collection and similarity measurement, we employ an AC strategy based on the -medoids clustering algorithm using additional reference points that are geographically located at the outer cluster boundary to enrich the data of each cluster. During the approximate localization, RSS measurements are compared with the cluster radio maps to determine to which cluster the target most likely belongs. Both the Euclidean distance of the RSSs and the Hamming distance of the coverage vectors between the observations and training records are explored for . Then, a kernel-based ridge regression method is used to obtain the ultimate positioning of the target. The performance of the proposed algorithm is evaluated in two typical indoor environments, and compared with those of state-of-the-art algorithms. The experimental results demonstrate the effectiveness and advantages of the proposed algorithm in terms of positioning accuracy and complexity.

Keywords： 室内定位；接收信号强度（RSS）指纹；核岭回归；簇匹配；改进型分簇    

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A new method of rock-explosive matching in drilling and blasting based on reasonable control of the crushed zone

LengZhendong,LuWenbo,YanPeng, ChenMing,Hu Yingguo

Strategic Study of CAE 2014, Volume 16, Issue 11,   Pages 28-35

Abstract:

Reasonable rock-explosive matching is of great important to the enhancing of explosive energy effective utilization and the improving of rock fragmentation effect. The traditionally emphasized method of acoustic impedance matching is not reasonable. Starting from the blasting breakage mechanism, a new method of rock-explosive matching in drilling and blasting is proposed. The new approach chooses explosive parameters by reasonable control of the size of crushed zone under the condition of fully fragmentation between adjacent balstholes. This method can intuitively reflect the blasting fragmentation effect and energy effective utilization, which is easy to implement. Also, a modified model is developed, with the combination of adjacent blastholes explosion load taken into account. As a result, explosive parameters for different grades of rock are given in full coupling on-site mixed explosive charge under different project objectives.

Keywords： drilling and blasting     crushed zone     rock-explosive matching     acoustic impedance matching    

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The research of connectivity-credibility restricted clustering algorithm in wireless sensor networks

Yu Jiming,Sun Yamin,Lei Yanjing,Yang Yuwang

Strategic Study of CAE 2010, Volume 12, Issue 9,   Pages 73-77

Abstract:

This paper proposed a speeding clustering algorithm of connectivity-credibility constrained random dispose which based on some other clustering algorithms. Simulation shows that this algorithm can get large cover of clustering, logical distributing and good stability. Comparing to the lowerst-ID clustering and highest-connectivity clustering algorithm, the algorithm can get less number of cluster-heads, more logical clustering, good communication between nodes and cluster-heads, steady networks, reduce communication cost of rebuilding, and can balance network's energy consume, prolong the networks life.

Keywords： wireless sensor networks     connectivity-credibility     clustering algorithm    

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Radio propagation measurement and cluster-based analysis for millimeter-wave cellular systems in dense urban environments

Peize Zhang, Haiming Wang, Wei Hong,pzzhang@seu.edu.cn,hmwang@seu.edu.cn,weihong@seu.edu.cn

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 4,   Pages 471-487 doi: 10.1631/FITEE.2000489

Abstract: The deployment of millimeter-wave (mmWave) cellular systems in dense urban environments with an acceptable coverage and cost-efficient transmission scheme is essential for the rollout of fifth-generation and beyond technology. In this paper, cluster-based analysis of mmWave channel characteristics in two typical dense urban environments is performed. First, radio campaigns are conducted in two identified mmWave bands of 28 and 39 GHz in a central business district and a dense residential area. The custom-designed channel sounder supports high-efficiency directional scanning sounding, which helps collect sufficient data for statistical channel modeling. Next, using an improved auto- algorithm, multipath clusters and their scattering sources are identified. An appropriate measure for inter- and intra-cluster characteristics is provided, which includes the cluster number, the Ricean -factor, root-mean-squared (RMS) delay spread, RMS angular spread, and their correlations. Comparisons of these parameters across two mmWave bands for both line-of-sight (LoS) and non-light-of-sight (NLoS) links are given. To shed light on the blockage effects, detailed analysis of the propagation mechanisms corresponding to each NLoS cluster is provided, including reflection from exterior walls and over building corners and rooftops. Finally, the results show that the cluster-based analysis takes full advantage of mmWave beamspace channel characteristics and has further implications for the design and deployment of mmWave wireless networks.

Keywords： 毫米波通信；分簇；绕射；多路通道；传播测量    

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Featurematching using quasi-conformalmaps Article

Chun-xue WANG, Li-gang LIU

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 5,   Pages 644-657 doi: 10.1631/FITEE.1500411

Abstract: We present a fully automatic method for finding geometrically consistent correspondences while discarding outliers from the candidate point matches in two images. Given a set of candidate matches provided by scale-invariant feature transform (SIFT) descriptors, which may contain many outliers, our goal is to select a subset of these matches retaining much more geometric information constructed by a mapping searched in the space of all diffeomorphisms. This problem can be formulated as a constrained optimization involving both the Beltrami coefficient (BC) term and quasi-conformal map, and solved by an efficient iterative algorithm based on the variable splitting method. In each iteration, we solve two subproblems, namely a linear system and linearly constrained convex quadratic programming. Our algorithm is simple and robust to outliers. We show that our algorithm enables producing more correct correspondences experimentally compared with state-of-the-art approaches.

Keywords： Feature correspondence     Quasi-conformal map     Splitting method    

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Study on channcl resolution matching algorithm for HY-2 satellite

Huang Lei,Zhou Wu,Li Yanmin

Strategic Study of CAE 2014, Volume 16, Issue 6,   Pages 65-69

Abstract:

Accuracy Satellite Scanning Microwave Radiometer ocean parameters retrieval need brightness temperature of multiple channel from same area and identical resolution. Due to the limitation of spaceborne radiometer antenna design and feedhorn arrangement, each channel has different resolution and observation position, this will increase the ocean parameter retrieval error. Based on the HY-2 Scanning microwave radiometer antenna pattern and imaging geometry, we simulate the ground footprint form different channel, use Backu-Gilbert(BG) algorithm produce a single composite sample at a particular location and with a particular spatial weighting pattern from combination of the adjacent measurements, the low frequency 6.6GHz is set as the reference channel. The result showed that the matching with resolution decreasing could simulate the real instrument observation without introducing noise.

Keywords： scanning microwave radiometer     HY-2     resolution matching     Backus-Gilbert algorithm    

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A algorithm for binocular stereo matching in the presence of specular reflections

Lu Sijun,Tang Zhenmin,Guo Longyuan,Lu Ali

Strategic Study of CAE 2010, Volume 12, Issue 1,   Pages 56-60

Abstract:

Traditional stereo correspondence algorithms rely heavily on the Lambertian model of diffuse reflectance. While this diffuse assumption is generally valid for most part of an image, processing of regions that contain specular reflections can result in severe matching errors. In this paper, we address the problem of binocular stereo dense matching in the presence of specular reflections by introducing a novel correspondence measurement which is robust to the specular reflections. Accurate depth can be estimated for both diffuse and specular regions. Unlike the previous works which seek to eliminate or avoid specular reflections using image preprocessing or multibaseline stereo, our approach works in its presence. Experiments demonstrate the effectiveness and robustness of our approach.

Keywords： stereo matching     diffuse reflection     specular reflection     chromaticity    

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Towards adaptable and tunable cloud-based map-matching strategy for GPS trajectories Article

Aftab Ahmed CHANDIO,Nikos TZIRITAS,Fan ZHANG,Ling YIN,Cheng-Zhong XU

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 12,   Pages 1305-1319 doi: 10.1631/FITEE.1600027

Abstract: Smart cities have given a significant impetus to manage traffic and use transport networks in an intelligent way. For the above reason, intelligent transportation systems (ITSs) and location-based services (LBSs) have become an interesting research area over the last years. Due to the rapid increase of data volume within the transportation domain, cloud environment is of paramount importance for storing, accessing, handling, and processing such huge amounts of data. A large part of data within the transportation domain is produced in the form of Global Positioning System (GPS) data. Such a kind of data is usually infrequent and noisy and achieving the quality of real-time transport applications based on GPS is a difficult task. The map-matching process, which is responsible for the accurate alignment of observed GPS positions onto a road network, plays a pivotal role in many ITS applications. Regarding accuracy, the performance of a map-matching strategy is based on the shortest path between two con-secutive observed GPS positions. On the other extreme, processing shortest path queries (SPQs) incurs high computational cost. Current map-matching techniques are approached with a fixed number of parameters, i.e., the number of candidate points (NCP) and error circle radius (ECR), which may lead to uncertainty when identifying road segments and either low-accurate results or a large number of SPQs. Moreover, due to the sampling error, GPS data with a high-sampling period (i.e., less than 10 s) typically contains extraneous datum, which also incurs an extra number of SPQs. Due to the high computation cost incurred by SPQs, current map-matching strategies are not suitable for real-time processing. In this paper, we propose real-time map-matching (called RT-MM), which is a fully adaptive map-matching strategy based on cloud to address the key challenge of SPQs in a map-matching process for real-time GPS trajectories. The evaluation of our approach against state-of-the-art approaches is per-formed through simulations based on both synthetic and real-world datasets.

Keywords： Map-matching     GPS trajectories     Tuning-based     Cloud computing     Bulk synchronous parallel    

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A Weighted Block-matching Criterion for the Hardware Implementation of Motion Estimators

Zhang Xia,Zheng Nanning,Zhang Guanglie,Wu Yong,Wang Shaorui,Xu Weipu

Strategic Study of CAE 2002, Volume 4, Issue 1,   Pages 47-53

Abstract:

In all kinds of digital video processing algorithms, motion compensated algorithm can acquire perfect performance because the motion information in the video signal has been considered. The hardware implementation of the motion estimator is the core of the various motion compensated digital video processings, which will be applied in real systems. Block-matching motion estimating algorithm is widely used in real system because of its low computing complication, easy realization and high call frequency of the block-matching criterion in the hardware systems. A new criterion called weighted minimized maximum error is proposed in this paper. This criterion can reduce the complexity of the motion estimator, decrease the area of the hardware and increase the speed of the hardware. On the other hand, the criterion is suitable to be applied to the recursive searching strategy which has an inherent weakness called error propagation.

Keywords： video processing     motion compensation     motion estimation     block-matching criterion    

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A knowledge push technology based on applicable probability matching and multidimensional context driving None

Shu-you ZHANG, Ye GU, Xiao-jian LIU, Jian-rong TAN

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 2,   Pages 235-245 doi: 10.1631/FITEE.1700763

Abstract: Actively pushing design knowledge to designers in the design process, what we call ‘knowledge push’, can help im-prove the efficiency and quality of intelligent product design. A knowledge push technology usually includes matching of related knowledge and proper pushing of matching results. Existing approaches on knowledge matching commonly have a lack of intel-ligence. Also, the pushing of matching results is less personalized. In this paper, we propose a knowledge push technology based on applicable probability matching and multidimensional context driving. By building a training sample set, including knowledge description vectors, case feature vectors, and the mapping Boolean matrix, two probability values, application and non-application, were calculated via a Bayesian theorem to describe the matching degree between knowledge and content. The push results were defined by the comparison between two probability values. The hierarchical design content models were built to filter the knowledge in push results. The rules of personalized knowledge push were sorted by multidimensional contexts, which include design knowledge, design context, design content, and the designer. A knowledge push system based on intellectualized design of CNC machine tools was used to confirm the feasibility of the proposed technology in engineering applications.

Keywords： Product design     Knowledge push     Applicable probability matching     Multidimensional context     Personalization    

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Improved Matching Algorithms for Linear Face Class Model

Fu Yun,Zheng Nanning

Strategic Study of CAE 2005, Volume 7, Issue 2,   Pages 47-56

Abstract:

An advanced matching technique for linear face class model is proposed, which can solve the problem of detailed controlling and robust iteration for the realistic facial modeling. A new method——Dynamic Gaussian Pyramid Analysis (DGPA), which combines Non-Uniform Sampling (NUS) method and Multi-Resolution Analysis, is presented. Integrating the PS Sampling and the Cluster Random Sampling, the distribution of the sampled points in each level images of the Gaussian pyramid is adjusted dynamically. In coarse-to-fine scheme, the minimization algorithm is used to compute the near global optimal solution that may fit to yield accurate model matching. Dynamic adjusting the boundary of the sampling cluster area and the resampling ratio, the detailed representations are effectively controlled, and the model creation is quite robust. An improved Stochastic Gradient Descent (SGD) algorithm based on the Correlative Disturbance (CD) and Adaptive Learning Rate (ALR) is exploited to accelerate iteration convergence and compute valid model parameters. With the examples of MPI Caucasian Face and AI&R Asian Face databases, experimental results in subjective evaluation and objective evaluation demonstrate the advanced model matching technique.

Keywords： facial modeling     model matching     stochastic gradient descent     non-uniform sampling     multiresolution analysis    

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Improving the reconstruction efficiency of sparsity adaptive matching pursuit based on the Wilkinsonmatrix None

Rasha SHOITAN, Zaki NOSSAIR, I. I. IBRAHIM, Ahmed TOBAL

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 4,   Pages 503-512 doi: 10.1631/FITEE.1601588

Abstract: Sparsity adaptive matching pursuit (SAMP) is a greedy reconstruction algorithm for compressive sensing signals. SAMP reconstructs signals without prior information of sparsity and presents better reconstruction performance for noisy signals compared to other greedy algorithms. However, SAMP still suffers from relatively poor reconstruction quality especially at high compression ratios. In the proposed research, the Wilkinson matrix is used as a sensing matrix to improve the reconstruction quality and to increase the compression ratio of the SAMP technique. Furthermore, the idea of block compressive sensing (BCS) is combined with the SAMP technique to improve the performance of the SAMP technique. Numerous simulations have been conducted to evaluate the proposed BCS-SAMP technique and to compare its results with those of several compressed sensing techniques. Simulation results show that the proposed BCS-SAMP technique improves the reconstruction quality by up to six decibels (dB) relative to the conventional SAMP technique. In addition, the reconstruction quality of the proposed BCS-SAMP is highly comparable to that of iterative techniques. Moreover, the computation time of the proposed BCS-SAMP is less than that of the iterative techniques, especially at lower measurement fractions.

Keywords： Block compressive sensing     Sparsity adaptive matching pursuit     Greedy algorithm     Wilkinson matrix    

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A knowledge matching approach based on multi-classification radial basis function neural network for knowledge push system Research Articles

Shu-you Zhang, Ye Gu, Guo-dong Yi, Zi-li Wang,zsy@zju.edu.cn,me_guye@zju.edu.cn,ygd@zju.edu.cn,ziliwang@zju.edu.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 7,   Pages 963-1118 doi: 10.1631/FITEE.1900057

Abstract: We present an exploratory study to improve the performance of a in . We focus on the domain of , where traditional matching algorithms need repeated calculations that result in a long response time and where accuracy needs to be improved. The goal of our approach is to meet designers’ knowledge demands with a quick response and quality service in the . To improve the previous work, two methods are investigated to augment the limited training set in practical operations, namely, oscillating the feature weight and revising the case feature in the case feature vectors. In addition, we propose a multi-classification radial basis function neural network that can match the knowledge from the knowledge base once and ensure the accuracy of pushing results. We apply our approach using the training set in the design of guides by computer numerical control machine tools for training and testing, and the results demonstrate the benefit of the . Moreover, experimental results reveal that our approach outperforms other matching approaches.

Keywords： Product design     Knowledge push system     Augmented training set     Multi-classification neural network     Knowledge matching    

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Three-dimensional face point cloud hole-filling algorithm based on binocular stereo matching and a B-spline Research Articles

Yuan HUANG, Feipeng DA,whhbb@163.com

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 3,   Pages 398-408 doi: 10.1631/FITEE.2000508

Abstract: When obtaining three-dimensional (3D) face point cloud data based on structured light, factors related to the environment, occlusion, and illumination intensity lead to holes in the collected data, which affect subsequent recognition. In this study, we propose a hole-filling method based on stereo-matching technology combined with a . The algorithm uses phase information acquired during raster projection to locate holes in the point cloud, simultaneously extracting boundary point cloud sets. By registering the face point cloud data using the stereo-matching algorithm and the data collected using the raster projection method, some supplementary information points can be obtained at the holes. The shape of the curve can then be roughly described by a few key points, and the control points are put into the hole area as key points for iterative calculation of surface reconstruction. Simulations using smooth ceramic cups and human face models showed that our model can accurately reproduce details and accurately restore complex shapes on the test surfaces. Simulation results indicated the robustness of the method, which is able to fill holes on complex areas such as the inner side of the nose without a prior model. This approach also effectively supplements the hole information, and the patched point cloud is closer to the original data. This method could be used across a wide range of applications requiring accurate facial recognition.

Keywords： Three-dimensional (3D) point cloud     Hole filling     Stereo matching     B-spline    

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A General Strategy for Efficiently Constructing Multifunctional Cluster Fillers Using a Three-Fluid Nozzle Spray Drying Technique for Dental Restoration Article

Dan-Lei Yang, Dan Wang, Hao Niu, Rui-Li Wang, Mei Liu, Fei-Min Zhang, Jie-Xin Wang, Mei-Fang Zhu

Engineering 2022, Volume 8, Issue 1,   Pages 138-147 doi: 10.1016/j.eng.2021.08.001

Abstract:

Multifunctional fillers are greatly required for dental resin composites (DRCs). In this work, a spray dryer with a three-fluid nozzle was applied for the first time to construct high-performance complex nanoparticle clusters (CNCs) consisting of different functional nanofillers for dental restoration. The application of a three-fluid nozzle can effectively avoid the aggregation of different nanoparticles with opposite zeta potentials before the spray drying process in order to construct regularly shaped CNCs. For a SiO2–ZrO2 binary system, the SiO2–ZrO2 CNCs constructed using a three-fluid nozzle maintained their excellent mechanical properties ((133.3 ± 4.7) MPa, (8.8 ± 0.5) GPa, (371.1 ± 13.3) MPa, and (64.5 ± 0.7) HV for flexural strength, flexural modulus, compressive strength, and hardness of DRCs, respectively), despite the introduction of ZrO2 nanoparticles, whereas their counterparts constructed using a two-fluid nozzle showed significantly decreased mechanical properties. Furthermore, heat treatment of the SiO2–ZrO2 CNCs significantly improved the mechanical properties and radiopacity of the DRCs. The DRCs containing over 10% mass fraction ZrO2 nanoparticles can meet the requirement for radiopaque fillers. More importantly, this method can be expanded to ternary or quaternary systems. DRCs filled with SiO2–ZrO2–ZnO CNCs with a ratio of 56:10:4 displayed high antibacterial activity (antibacterial ratio > 99%) in addition to excellent mechanical properties and radiopacity. Thus, the three-fluid nozzle spray drying technique holds great potential for the efficient construction of multifunctional cluster fillers for DRCs.

Keywords： Multifunctional cluster fillers     Three-fluid nozzle spray drying     Mechanical properties     Antibacterial activity     Radiopacity     Dental resin composites    

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Title Author Date Type Operation

Received signal strength based indoor positioning algorithm using advanced clustering and kernel ridge regression

Yanfen Le, Hena Zhang, Weibin Shi, Heng Yao,leyanfen@usst.edu.cn,hyao@usst.edu.cn

Journal Article

A new method of rock-explosive matching in drilling and blasting based on reasonable control of the crushed zone

LengZhendong,LuWenbo,YanPeng, ChenMing,Hu Yingguo

Journal Article

The research of connectivity-credibility restricted clustering algorithm in wireless sensor networks

Yu Jiming,Sun Yamin,Lei Yanjing,Yang Yuwang

Journal Article

Radio propagation measurement and cluster-based analysis for millimeter-wave cellular systems in dense urban environments

Peize Zhang, Haiming Wang, Wei Hong,pzzhang@seu.edu.cn,hmwang@seu.edu.cn,weihong@seu.edu.cn

Journal Article

Featurematching using quasi-conformalmaps

Chun-xue WANG, Li-gang LIU

Journal Article

Study on channcl resolution matching algorithm for HY-2 satellite

Huang Lei,Zhou Wu,Li Yanmin

Journal Article

A algorithm for binocular stereo matching in the presence of specular reflections

Lu Sijun,Tang Zhenmin,Guo Longyuan,Lu Ali

Journal Article

Towards adaptable and tunable cloud-based map-matching strategy for GPS trajectories

Aftab Ahmed CHANDIO,Nikos TZIRITAS,Fan ZHANG,Ling YIN,Cheng-Zhong XU

Journal Article

A Weighted Block-matching Criterion for the Hardware Implementation of Motion Estimators

Zhang Xia,Zheng Nanning,Zhang Guanglie,Wu Yong,Wang Shaorui,Xu Weipu

Journal Article

A knowledge push technology based on applicable probability matching and multidimensional context driving

Shu-you ZHANG, Ye GU, Xiao-jian LIU, Jian-rong TAN

Journal Article

Improved Matching Algorithms for Linear Face Class Model

Fu Yun,Zheng Nanning

Journal Article

Improving the reconstruction efficiency of sparsity adaptive matching pursuit based on the Wilkinsonmatrix

Rasha SHOITAN, Zaki NOSSAIR, I. I. IBRAHIM, Ahmed TOBAL

Journal Article

A knowledge matching approach based on multi-classification radial basis function neural network for knowledge push system

Shu-you Zhang, Ye Gu, Guo-dong Yi, Zi-li Wang,zsy@zju.edu.cn,me_guye@zju.edu.cn,ygd@zju.edu.cn,ziliwang@zju.edu.cn

Journal Article

Three-dimensional face point cloud hole-filling algorithm based on binocular stereo matching and a B-spline

Yuan HUANG, Feipeng DA,whhbb@163.com

Journal Article

A General Strategy for Efficiently Constructing Multifunctional Cluster Fillers Using a Three-Fluid Nozzle Spray Drying Technique for Dental Restoration

Dan-Lei Yang, Dan Wang, Hao Niu, Rui-Li Wang, Mei Liu, Fei-Min Zhang, Jie-Xin Wang, Mei-Fang Zhu

Journal Article