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Novel 3D point set registration method based on regionalized Gaussian process map reconstruction Research

Bo Li, Yu Zhang, Wen-jie Zhao, Ping Li,jameslb20@hotmail.com,zhangyu80@zju.edu.cn,zhaowenjie8@zju.edu.cn,pli@iipc.zju.edu.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 5,   Pages 649-808 doi: 10.1631/FITEE.1900457

Abstract: has been a topic of significant research interest in the field of mobile intelligent unmanned systems. In this paper, we present a novel approach for a three-dimensional scan-to-map . Using (GP) regression, we propose a new type of map representation, based on a regionalized GP map reconstruction algorithm. We combine the predictions and the test locations derived from the GP as the predictive points. In our approach, the correspondence relationships between predictive point pairs are set up naturally, and a rigid transformation is calculated iteratively. The proposed method is implemented and tested on three standard point set datasets. Experimental results show that our method achieves stable performance with regard to accuracy and efficiency, on a par with two standard methods, the iterative closest point algorithm and the normal distribution transform. Our mapping method also provides a compact point-cloud-like map and exhibits low memory consumption.

Keywords： 点集配准；高斯过程；智能无人系统    

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Fast uniform content-based satellite image registration using the scale-invariant feature transform descriptor Article

Hamed BOZORGI, Ali JAFARI

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 8,   Pages 1108-1116 doi: 10.1631/FITEE.1500295

Abstract: Content-based satellite image registration is a difficult issue in the fields of remote sensing and image processing. The difficulty is more significant in the case of matching multisource remote sensing images which suffer from illumination, rotation, and source differences. The scale-invariant feature transform (SIFT) algorithm has been used successfully in satellite image registration problems. Also, many researchers have applied a local SIFT descriptor to improve the image retrieval process. Despite its robustness, this algorithm has some difficulties with the quality and quantity of the extracted local feature points in multisource remote sensing. Furthermore, high dimensionality of the local features extracted by SIFT results in time-consuming computational processes alongside high storage requirements for saving the relevant information, which are important factors in content-based image retrieval (CBIR) applications. In this paper, a novel method is introduced to transform the local SIFT features to global features for multisource remote sensing. The quality and quantity of SIFT local features have been enhanced by applying contrast equalization on images in a pre-processing stage. Considering the local features of each image in the reference database as a separate class, linear discriminant analysis (LDA) is used to transform the local features to global features while reducing dimensionality of the feature space. This will also significantly reduce the computational time and storage required. Applying the trained kernel on verification data and mapping them showed a successful retrieval rate of 91.67% for test feature points.

Keywords： Content-based image retrieval     Feature point distribution     Image registration     Linear discriminant analysis     Remote sensing     Scale-invariant feature transform    

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Multi-View Point-Based Registration for Native Knee Kinematics Measurement with Feature Transfer Learning Article

Cong Wang, Shuaining Xie, Kang Li, Chongyang Wang, Xudong Liu, Liang Zhao, Tsung-Yuan Tsai

Engineering 2021, Volume 7, Issue 6,   Pages 881-888 doi: 10.1016/j.eng.2020.03.016

Abstract:

Deep-learning methods provide a promising approach for measuring in-vivo knee joint motion from fast registration of two-dimensional (2D) to three-dimensional (3D) data with a broad range of capture. However, if there are insufficient data for training, the data-driven approach will fail. We propose a feature-based transfer-learning method to extract features from fluoroscopic images. With three subjects and fewer than 100 pairs of real fluoroscopic images, we achieved a mean registration success rate of up to 40%. The proposed method provides a promising solution, using a learning-based registration method when only a limited number of real fluoroscopic images is available.

Keywords： 2D–3D registration     Machine learning     Domain adaption     Point correspondence    

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Engineering a Coordinatively Unsaturated Au–O–Ti3+ Structure Toward Unprecedented H2 Efficiency for Low-Temperature Propene Epoxidation with H2 and O2 Article

Zhaoning Song, Hao Yan, Juncong Yuan, Hongfei Ma, Jianlin Cao, Yongxiang Wang, Qiang Wang, Chong Peng, Feng Deng, Xiang Feng, De Chen, Chaohe Yang, Yongkang Hu

Engineering 2023, Volume 25, Issue 6,   Pages 144-156 doi: 10.1016/j.eng.2023.01.008

Abstract:

Since 1998, the Au–O–Ti4+ sites of Au/Ti-based catalysts have been widely accepted as the active sites for propene epoxidation with H2 and O2 at a relatively high temperature, although they are limited by poor H2 efficiency. Herein, we demonstrate a novel Au–O–Ti3+ active site aiming at low-temperature propene epoxidation. Notably, this active site results in a sharp shift in the optimum temperature, from 200 to 138 °C, and allows the catalyst to maintain an unprecedented H2 efficiency of 43.6%, a high propylene oxide (PO) selectivity of 90.7%, and a stability of over 100 h. The Au–O–coordinatively unsaturated Ti3+ active site is quantitively constructed by tuning the amount of Si–OH and Bu3NH+ in post-treated silicalite-1 seeds. Through operando ultraviolet–visible (UV–vis) spectroscopy, the dynamic evolution of the Ti–OOH intermediate was investigated. It was found that the Ti–OOH generation rate is higher on Au–O–Ti3+ than on conventional Au–O–Ti4+ sites. Moreover, ammonia temperature-programmed desorption (NH3-TPD) and X-ray photoelectron spectroscopy (XPS) characterizations, together with density-functional theory (DFT) calculations, demonstrated that the coordinatively unsaturated Ti3+ sites promote electron transfer between Au and Ti3+, thereby enhancing the O2 adsorption ability of the catalyst and promoting the in situ formation of H2O2 and the Ti–OOH intermediate, even at a low temperature. The insights and methodology reported here not only shed new light on maximizing H2 efficiency over a coordinatively unsaturated Ti3+ structure of titanium silicate-1 but also open up new opportunities for industrial direct gas-phase propene epoxidation in a low temperature range.

Keywords： Propene epoxidation     H2 efficiency     Au/Ti bifunctional catalysts     Coordinatively unsaturated Ti     Density-functional theory    

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Periodically varied initial offset boosting behaviors in a memristive system with cosine memductance Regular Papers

Mo CHEN, Xue REN, Hua-gan WU, Quan XU, Bo-cheng BAO

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 12,   Pages 1706-1716 doi: 10.1631/FITEE.1900360

Abstract: A four-dimensional memristive system is constructed using a novel ideal memristor with cosine memductance. Due to the special memductance nonlinearity, this memristive system has a line equilibrium set (0, 0, 0, δ) located along the coordinate of the inner state variable of the memristor, whose stability is periodically varied with a change of δ. Nonlinear and one-dimensional initial offset boosting behaviors, which are triggered by not only the initial condition of the memristor but also other two initial conditions, are numerically uncovered. Specifically, a wide variety of coexisting attractors with different positions and topological structures are revealed along the boosting route. Finally, circuit simulations are performed by Power SIMulation (PSIM) to confirm the unique dynamical features.

Keywords： Initial offset boosting     Memristive system     Memductance     Line equilibrium set    

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Quasi-period Changes of the Operational Parameters for Hot Oil Pipelines

Cui Hui

Strategic Study of CAE 2006, Volume 8, Issue 1,   Pages 51-53

Abstract:

Subjected to the annual changes of the air temperature, the quasi-period rules of the operational parameters of the buried hot oil pipelines and the surrounding soil temperature are theoretically presented in this paper. On the basis of large numbers of actual operational data, the rationality of the rules is further validated. In addition, the delay of the operational parameters must be considered in the studies of the saving energy, optimizing operation and economically pigging for hot oil pipelines.

Keywords： hot oil pipeline     air temperature     soil environment     quasi-period    

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The zero-point energy of vibration and the Casimir force

Huang Zhixun

Strategic Study of CAE 2008, Volume 10, Issue 5,   Pages 63-69

Abstract:

Put two metal sheets very close together in vacuum, we'll find they attract each other with a small but measurable force. The explanation for the Casimir effect is that empty space is cracking with zero-point energy(ZPE), a phenomenon arising from quantum theory, and this energy pushes the metal plates together. All scientists agree that such a force does exist, but the trouble is physicists can't agree on what it means for something to be true. Is empty space really fizzing with energy? Perhaps the answer may determine the fate of the universe. A variety of anomalous phenomena in nature or at laboratories could be explained by the Casimir effect and the torsion field theory.

Keywords： zero-point energy     zero-point field     energy of vacuum     Casimir force     theory of torsion field    

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Reinforcement design of anchor blocks for external tendons

Hong Hao,Tong Yuqiang ,He Zhiqi,Liu Zhao

Strategic Study of CAE 2013, Volume 15, Issue 8,   Pages 95-98

Abstract:

Reinforced blocks are common anchorage forms for external tendons. However, there was no mature design method. Through finite element analysis, the paper revealed that the tensile stress concentration was caused by three typical local actions. On this basis, three equations for calculating resultant forces of these local actions were formulated. Thus a quantitative reinforcement design method of anchor blocks was proposed. Finally, an anchor block of the Fourth Nanjing Yangtze River Bridge was presented as a design example to demonstrate the effectiveness and convenience of the proposed method.

Keywords： anchor block     external prestressing     reinforcement design     bursting force     cantilever action     tie-back    

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An anchor-based spectral clustering method None

Qin ZHANG, Guo-qiang ZHONG, Jun-yu DONG

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 11,   Pages 1385-1396 doi: 10.1631/FITEE.1700262

Abstract:

Spectral clustering is one of the most popular and important clustering methods in pattern recognition, machine learning, and data mining. However, its high computational complexity limits it in applications involving truly large-scale datasets. For a clustering problem with n samples, it needs to compute the eigenvectors of the graph Laplacian with O(n3) time complexity. To address this problem, we propose a novel method called anchor-based spectral clustering (ASC) by employing anchor points of data. Specifically, m (m<<n) anchor points are selected from the dataset, which can basically maintain the intrinsic (manifold) structure of the original data. Then a mapping matrix between the original data and the anchors is constructed. More importantly, it is proved that this data-anchor mapping matrix essentially preserves the clustering structure of the data. Based on this mapping matrix, it is easy to approximate the spectral embedding of the original data. The proposed method scales linearly relative to the size of the data but with low degradation of the clustering performance. The proposed method, ASC, is compared to the classical spectral clustering and two state-of-the-art accelerating methods, i.e., power iteration clustering and landmark-based spectral clustering, on 10 real-world applications under three evaluation metrics. Experimental results show that ASC is consistently faster than the classical spectral clustering with comparable clustering performance, and at least comparable with or better than the state-of-the-art methods on both effectiveness and efficiency.

Keywords： Clustering     Spectral clustering     Graph Laplacian     Anchors    

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All Set and Artificial Intelligence

Zhang Jiang,Lin Hua,He Zhongxiong

Strategic Study of CAE 2002, Volume 4, Issue 3,   Pages 40-47

Abstract:

This paper presents a brand new set theory, All Set theory, which is the united set form of the current set theories including crisp set, fuzzy set, extension set, vague set, rough set, set pair analysis, FHW (fuzzy gray matter - element)，FEEC(fuzzy extension economic control) and so on. The operation of the all set is also discussed in detail. A kind of style of the human being' s intelligence can be described by a kind of set form, thus all set is the united form. An all set is comprised of four parts, that is ( A, B, F, J ). A is the universe of the problem discussed. One of the elements in A can be described by an element of B. F is the map from A to B. And J restricts F. From this model, the concept of subjection that is the basic conception of human´s intelligence can be simulated. Hence the wide application of all set theory in the field of artificial intelligence including pattern recognition, clustering, logic, machine learning, intelligent decision, etc. , can be developed. Especially the relation among all set, logic and human intelligence style is illustrated in the paper. The theory of all set can not only unify and summarize the current theories but also provide the primary method for establishing new set theory and new logic.

Keywords： all set     artificial intelligence     set theory     operation     logic    

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A creative concept for designing and simulating quaternary logic gates in quantum-dot cellular automata Research Articles

Alireza Navidi, Reza Sabbaghi-Nadooshan, Massoud Dousti,alireza.navidi@srbiau.ac.ir,r_sabbaghi@iauctb.ac.ir,m_dousti@srbiau.ac.ir

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 11,   Pages 1441-1550 doi: 10.1631/FITEE.2000590

Abstract: New technologies such as have been showing some remarkable characteristics that standard complementary-metal-oxide semiconductor (CMOS) in deep sub-micron cannot afford. Modeling systems and designing multiple-valued logic gates with QCA have advantages that facilitate the design of complicated logic circuits. In this paper, we propose a novel creative concept for . The concept has been set in , the new simulator developed by our team exclusively for QCAs’ quaternary mode. Proposed basic gates such as MIN, MAX, and different types of inverters (SQI, PQI, NQI, and IQI) have been designed and verified by . This study will exemplify how fast and accurately works by its handy set of CAD tools. A 1×4 decoder is presented using our proposed main gates. Preference points such as the minimum delay, area, and complexity have been achieved in this work. QQCA main logic gates are compared with based on carbon nanotube field-effect transistor (CNFET). The results show that the proposed design is more efficient in terms of latency and energy consumption.

Keywords： 量子点细胞自动机（QCA）；四值逻辑；量子点细胞自动模拟器（QCASim）；四值QCA（QQCA）；四值译码器；四值门    

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Change trend and reason analysis of point source pollution load of the Dianchi Lake Basin

He Jia,Xu Xiaomei,Chen Yunbo,Zhang Kunling,Li Yuexun,Li Zhongjie

Strategic Study of CAE 2010, Volume 12, Issue 6,   Pages 75-79

Abstract:

In this paper, yield and reduction of the Dianchi Lake basin point source pollution load of the past 20 years were calculated and the change trend and reasons to it were analyzed. The results indicated that point source wastewater, COD, total nitrogen and total phosphorus discharge from the whole Dianchi Lake basin in 2007 were 26 368 t, 55 913 t, 11 222 t and 1 008 t respectively, and compared to that of 1988, the growth rate of those mentioned above were 73.69 %, 203.27 %, 246.99 % and 301.55 %, among which the growth rate of living pollution were 174.43 %, 296.58 %, 342.90 % and 462.86 % respectively, however the industry pollution has been controlled, the pollution load was decreased by 36.43 %, 6.36 %, 49.24 % and 69.87 %. With the cooperation of 8 sewage treatment plants and 2 pumping stations, from 1993 to 2007, the reduction of COD, total nitrogen and total phosphorus discharged from the Dianchi Lake basin increased from 1 542 t, 177 t and 13 t to 40 581 t, 5 193 t and 637 t, which was the main reason that the environment of the Dianchi Lake stopped worsening. It can be concluded that, living pollution is the main pollutant source, and the major factor to the growth of pollution load in the Dianchi Lake basin.

Keywords： he Dianchi Lake     point source pollution    

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Nanoscale cryptographic architecture design using quantum-dot cellular automata Regular Article

Bikash Debnath, Jadav Chandra Das, Debashis De,dr.debashis.de@gmail.com

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 11,   Pages 1578-1586 doi: 10.1631/FITEE.1800458

Abstract: based on cryptography is a new paradigm in the field of nanotechnology. The overall performance of QCA is high compared to traditional complementary metal-oxide semiconductor (CMOS) technology. To achieve data security during nanocommunication, a cryptography-based application is proposed. The devised circuit encrypts the input data and passes it to an output channel through a cum data path selector, where the data is decrypted back to its original form. The results along with theoretical implication prove the accuracy of the circuit. Power dissipation and circuit complexity of the circuit have been analyzed.

Keywords： 量子点元胞自动机（QCA）；多数决定门密码学；加密；解密；纳米级路由    

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An Intelligent Expert System on Rough Sets

Zeng Huanglin

Strategic Study of CAE 2001, Volume 3, Issue 2,   Pages 47-51

Abstract:

The basic topology, knowledge representation and inductive learning of an intelligent expert system on rough sets are introduced in this paper. Based on the indiscernibility relation of system knowledge expression, a compatible algorithm is proposed to simplify the knowledge expressions and to induce the system decision rules. In order to extract the significant attributes from elementary knowledge and to reduce the dimensions of the system representation, inductive learning is also introduced by means of reasoning the dependency of knowledge between the teacher and the learner.

Keywords： rough sets     intelligent expert system     indiscernibility relation     knowledge expression simplification     decision rules    

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A Method of Constructing Fuzzy Neural Network Based on Rough Set Theory

Huang Xianming,Yi Jikai

Strategic Study of CAE 2004, Volume 6, Issue 4,   Pages 44-50

Abstract:

A new method of constructing fuzzy neural network is presented and Rough set theory is applied to this method. Since Rough set theory has strong numeric analyzing ability and fuzzy neural network has exact function approaching ability, their combination can produce a neural network model with good intelligibility and fast convergence. First, some rules are acquired from given data set by rough set theory. Then, these rules are applied to constructing neural cell numbers and relative parameters in fuzzy neural network. Finally the initial network is trained by BP arithmetic and the whole network design is finished. Also in this paper, an example of nonlinear function approaching is discussed and the feasibility of this method is proved.

Keywords： fuzzy neural network     rough set     acquire rule     function approaching    

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Title Author Date Type Operation

Novel 3D point set registration method based on regionalized Gaussian process map reconstruction

Bo Li, Yu Zhang, Wen-jie Zhao, Ping Li,jameslb20@hotmail.com,zhangyu80@zju.edu.cn,zhaowenjie8@zju.edu.cn,pli@iipc.zju.edu.cn

Journal Article

Fast uniform content-based satellite image registration using the scale-invariant feature transform descriptor

Hamed BOZORGI, Ali JAFARI

Journal Article

Multi-View Point-Based Registration for Native Knee Kinematics Measurement with Feature Transfer Learning

Cong Wang, Shuaining Xie, Kang Li, Chongyang Wang, Xudong Liu, Liang Zhao, Tsung-Yuan Tsai

Journal Article

Engineering a Coordinatively Unsaturated Au–O–Ti3+ Structure Toward Unprecedented H2 Efficiency for Low-Temperature Propene Epoxidation with H2 and O2

Zhaoning Song, Hao Yan, Juncong Yuan, Hongfei Ma, Jianlin Cao, Yongxiang Wang, Qiang Wang, Chong Peng, Feng Deng, Xiang Feng, De Chen, Chaohe Yang, Yongkang Hu

Journal Article

Periodically varied initial offset boosting behaviors in a memristive system with cosine memductance

Mo CHEN, Xue REN, Hua-gan WU, Quan XU, Bo-cheng BAO

Journal Article

Quasi-period Changes of the Operational Parameters for Hot Oil Pipelines

Cui Hui

Journal Article

The zero-point energy of vibration and the Casimir force

Huang Zhixun

Journal Article

Reinforcement design of anchor blocks for external tendons

Hong Hao,Tong Yuqiang ,He Zhiqi,Liu Zhao

Journal Article

An anchor-based spectral clustering method

Qin ZHANG, Guo-qiang ZHONG, Jun-yu DONG

Journal Article

All Set and Artificial Intelligence

Zhang Jiang,Lin Hua,He Zhongxiong

Journal Article

A creative concept for designing and simulating quaternary logic gates in quantum-dot cellular automata

Alireza Navidi, Reza Sabbaghi-Nadooshan, Massoud Dousti,alireza.navidi@srbiau.ac.ir,r_sabbaghi@iauctb.ac.ir,m_dousti@srbiau.ac.ir

Journal Article

Change trend and reason analysis of point source pollution load of the Dianchi Lake Basin

He Jia,Xu Xiaomei,Chen Yunbo,Zhang Kunling,Li Yuexun,Li Zhongjie

Journal Article

Nanoscale cryptographic architecture design using quantum-dot cellular automata

Bikash Debnath, Jadav Chandra Das, Debashis De,dr.debashis.de@gmail.com

Journal Article

An Intelligent Expert System on Rough Sets

Zeng Huanglin

Journal Article

A Method of Constructing Fuzzy Neural Network Based on Rough Set Theory

Huang Xianming,Yi Jikai

Journal Article