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A systematic approach in load disaggregation utilizing a multi-stage classification algorithm for consumerelectrical appliances classification

Chuan Choong YANG, Chit Siang SOH, Vooi Voon YAP

《能源前沿（英文）》 2019年第13卷第2期页码 386-398 doi: 10.1007/s11708-017-0497-z

摘要： The potential to save energy in existing consumer electrical appliances is very high. One of the ways to achieve energy saving and improve energy use awareness is to recognize the energy consumption of individual electrical appliances. To recognize the energy consumption of consumer electrical appliances, the load disaggregation methodology is utilized. Non-intrusive appliance load monitoring (NIALM) is a load disaggregation methodology that disaggregates the sum of power consumption in a single point into the power consumption of individual electrical appliances. In this study, load disaggregation is performed through voltage and current waveform, known as the - trajectory. The classification algorithm performs cropping and image pyramid reduction of the - trajectory plot template images before utilizing the principal component analysis (PCA) and the -nearest neighbor ( -NN) algorithm. The novelty of this paper is to establish a systematic approach of load disaggregation through - trajectory-based load signature images by utilizing a multi-stage classification algorithm methodology. The contribution of this paper is in utilizing the “ -value,” the number of closest data points to the nearest neighbor, in the -NN algorithm to be effective in classification of electrical appliances. The results of the multi-stage classification algorithm implementation have been discussed and the idea on future work has also been proposed.

关键词： load disaggregation voltage-current (V-I) trajectory multi-stage classification algorithm principal component analysis (PCA) k-nearest neighbor (k-NN)

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Classifying multiclass relationships between ASes using graph convolutional network

《工程管理前沿（英文）》页码 653-667 doi: 10.1007/s42524-022-0217-1

摘要： Precisely understanding the business relationships between autonomous systems (ASes) is essential for studying the Internet structure. To date, many inference algorithms, which mainly focus on peer-to-peer (P2P) and provider-to-customer (P2C) binary classification, have been proposed to classify the AS relationships and have achieved excellent results. However, business-based sibling relationships and structure-based exchange relationships have become an increasingly nonnegligible part of the Internet market in recent years. Existing algorithms are often difficult to infer due to the high similarity of these relationships to P2P or P2C relationships. In this study, we focus on multiclassification of AS relationship for the first time. We first summarize the differences between AS relationships under the structural and attribute features, and the reasons why multiclass relationships are difficult to be inferred. We then introduce new features and propose a graph convolutional network (GCN) framework, AS-GCN, to solve this multiclassification problem under complex scenes. The proposed framework considers the global network structure and local link features concurrently. Experiments on real Internet topological data validate the effectiveness of our method, that is, AS-GCN. The proposed method achieves comparable results on the binary classification task and outperforms a series of baselines on the more difficult multiclassification task, with an overall metrics above 95%.

关键词： autonomous system multiclass relationship graph convolutional network classification algorithm Internet topology

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Development of a new method for RMR and Q classification method to optimize support system in tunneling

Asghar RAHMATI,Lohrasb FARAMARZI,Manouchehr SANEI

《结构与土木工程前沿（英文）》 2014年第8卷第4期页码 448-455 doi: 10.1007/s11709-014-0262-x

摘要： Rock mass classification system is very suitable for various engineering design and stability analysis. classification method is confirmed by Japan Highway Public Corporation that this method can figure out either strength or deformability of rock mass, further appropriating the amount of rock bolts, thickness of shotcrete, and size of pitch of steel ribs just after the blasting procedure. Based on these advantages of method, in this study, according to data of five deep and long tunnels in Iran, two equations for estimating the value of method from and classification systems were developed. These equations as a new method were able to optimize the support system for and classification systems. From classification and its application in these case studies, it is pointed out that the method for the design of support systems in underground working is more reliable than the and classification systems.

关键词： JH classification Q and RMR classification new method

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Molecular classification and precision therapy of cancer: immune checkpoint inhibitors

null

《医学前沿（英文）》 2018年第12卷第2期页码 229-235 doi: 10.1007/s11684-017-0581-0

摘要：

On May 23, 2017, the US Food and Drug Administration (FDA) approved a treatment for cancer patients with positive microsatellite instability-high (MSI-H) markers or mismatch repair deficient (dMMR) markers. This approach is the first approved tumor treatment using a common biomarker rather than specified tumor locations in the body. FDA previously approved Keytruda for treatment of several types of malignancies, such as metastatic melanoma, metastatic non-small-cell lung cancer, recurrent or metastatic head and neck cancer, refractory Hodgkin lymphoma, and urothelial carcinoma, all of which carry positive programmed death-1/programmed death-ligand 1 biomarkers. Therefore, indications of Keytruda significantly expanded. Several types of malignancies are disclosed by MSI-H status due to dMMR and characterized by increased neoantigen load, which elicits intense host immune response in tumor microenvironment, including portions of colorectal and gastric carcinomas. Currently, biomarker-based patient selection remains a challenge. Pathologists play important roles in evaluating histology and biomarker results and establishing detection methods. Taking gastric cancer as an example, its molecular classification is built on genome abnormalities, but it lacks acceptable clinical characteristics. Pathologists are expected to act as “genetic interpreters” or “genetic translators” and build a link between molecular subtypes with tumor histological features. Subsequently, by using their findings, oncologists will carry out targeted therapy based on molecular classification.

关键词： molecular classification precision medicine pembrolizumab PD-1/PD-L1 MSI-H

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An approach for mechanical fault classification based on generalized discriminant analysis

LI Wei-hua, SHI Tie-lin, YANG Shu-zi

《机械工程前沿（英文）》 2006年第1卷第3期页码 292-298 doi: 10.1007/s11465-006-0022-2

摘要： To deal with pattern classification of complicated mechanical faults, an approach to multi-faults classification based on generalized discriminant analysis is presented. Compared with linear discriminant analysis (LDA), generalized discriminant analysis (GDA), one of nonlinear discriminant analysis methods, is more suitable for classifying the linear non-separable problem. The connection and difference between KPCA (Kernel Principal Component Analysis) and GDA is discussed. KPCA is good at detection of machine abnormality while GDA performs well in multi-faults classification based on the collection of historical faults symptoms. When the proposed method is applied to air compressor condition classification and gear fault classification, an excellent performance in complicated multi-faults classification is presented.

关键词： generalized discriminant non-separable abnormality classification multi-faults classification

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EAI-oriented information classification code system in manufacturing enterprises

WANG Junbiao, DENG Hu, JIANG Jianjun, YANG Binghong, WANG Bailing

《机械工程前沿（英文）》 2008年第3卷第1期页码 81-85 doi: 10.1007/s11465-008-0011-8

摘要： Although the traditional information classification coding system in manufacturing enterprises (MEs) emphasizes the construction of code standards, it lacks the management of the code creation, code data transmission and so on. According to the demands of enterprise application integration (EAI) in manufacturing enterprises, an enterprise application integration oriented information classification code system (EAIO-ICCS) is proposed. EAIO-ICCS expands the connotation of the information classification code system and assures the identity of the codes in manufacturing enterprises with unified management of codes at the view of its lifecycle.

关键词： EAI EAIO-ICCS management classification connotation

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Fault classification and reconfiguration of distribution systems using equivalent capacity margin method

K. Sathish KUMAR, T. JAYABARATHI

《能源前沿（英文）》 2012年第6卷第4期页码 394-402 doi: 10.1007/s11708-012-0211-0

摘要： This paper investigates the capability of support vector machines (SVM) for prediction of fault classification and the use of the concept of equivalent capacity margin (ECM) for restoration of the power system. The SVM, as a novel type of machine learning based on statistical learning theory, achieves good generalization ability by adopting a structural risk minimization (SRM) induction principle aimed at minimizing a bound on the generalization error of a model rather than the minimization of the error on the training data only. Here, the SVM has been used as a classification. The inputs of the SVM model are power and voltage values. An equation has been developed for the prediction of the fault in the power system based on the developed SVM model. The next steps of this paper are the restoration and reconfiguration by using the ECM concept, the development of a code, and the testing of the results with various load outages, which have been executed for a 12 load system.

关键词： support vector machines (SVM) structural risk minimization (SRM) equivalent capacity margin (ECM) restoration fault classification

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UsingKinect for real-time emotion recognition via facial expressions

Qi-rong MAO,Xin-yu PAN,Yong-zhao ZHAN,Xiang-jun SHEN

《信息与电子工程前沿（英文）》 2015年第16卷第4期页码 272-282 doi: 10.1631/FITEE.1400209

摘要： Emotion recognition via facial expressions (ERFE) has attracted a great deal of interest with recent advances in artificial intelligence and pattern recognition. Most studies are based on 2D images, and their performance is usually computationally expensive. In this paper, we propose a real-time emotion recognition approach based on both 2D and 3D facial expression features captured by Kinect sensors. To capture the deformation of the 3D mesh during facial expression, we combine the features of animation units (AUs) and feature point positions (FPPs) tracked by Kinect. A fusion algorithm based on improved emotional profiles (IEPs) and maximum confidence is proposed to recognize emotions with these real-time facial expression features. Experiments on both an emotion dataset and a real-time video show the superior performance of our method.

关键词： Kinect Emotion recognition Facial expression Real-time classification Fusion algorithm Support vector machine (SVM)

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Progress on molecular biomarkers and classification of malignant gliomas

null

《医学前沿（英文）》 2013年第7卷第2期页码 150-156 doi: 10.1007/s11684-013-0267-1

摘要：

Gliomas are the most common primary intracranial tumors in adults. Anaplastic gliomas (WHO grade III) and glioblastomas (WHO grade IV) represent the major groups of malignant gliomas in the brain. Several diagnostic, predictive, and prognostic biomarkers for malignant gliomas have been reported over the last few decades, and these markers have made great contributions to the accuracy of diagnosis, therapeutic decision making, and prognosis of patients. However, heterogeneity in patient outcomes may still be observed, which highlights the insufficiency of a classification system based purely on histopathology. Great efforts have been made to incorporate new information about the molecular landscape of gliomas into novel classifications that may potentially guide treatment. In this review, we summarize three distinctive biomarkers, three most commonly altered pathways, and three classifications based on microarray data in malignant gliomas.

关键词： malignant glioma molecular biomarker IDH1 MGMT molecular classification

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Multiclass classification based on a deep convolutional

Ying CAI,Meng-long YANG,Jun LI

《信息与电子工程前沿（英文）》 2015年第16卷第11期页码 930-939 doi: 10.1631/FITEE.1500125

摘要： Head pose estimation has been considered an important and challenging task in computer vision. In this paper we propose a novel method to estimate head pose based on a deep convolutional neural network (DCNN) for 2D face images. We design an effective and simple method to roughly crop the face from the input image, maintaining the individual-relative facial features ratio. The method can be used in various poses. Then two convolutional neural networks are set up to train the head pose classifier and then compared with each other. The simpler one has six layers. It performs well on seven yaw poses but is somewhat unsatisfactory when mixed in two pitch poses. The other has eight layers and more pixels in input layers. It has better performance on more poses and more training samples. Before training the network, two reasonable strategies including shift and zoom are executed to prepare training samples. Finally, feature extraction filters are optimized together with the weight of the classification component through training, to minimize the classification error. Our method has been evaluated on the CAS-PEAL-R1, CMU PIE, and CUBIC FacePix databases. It has better performance than state-of-the-art methods for head pose estimation.

关键词： Head pose estimation Deep convolutional neural network Multiclass classification

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Modular design of typical rigid links in parallel kinematic machines: Classification and topology optimization

Xinjun LIU, Xiang CHEN, Zhidong LI

《机械工程前沿（英文）》 2012年第7卷第2期页码 199-209 doi: 10.1007/s11465-012-0315-6

摘要：

Due to the demand of reconfigurable system in parallel kinematic machines (PKMs), modular design technology is significant and necessary. However, in earlier research, the core joint modules have been concerned about rather than the customized link modules. The modular design to the typical customized links from the point of seeking optimal structures with best mechanical performances is analyzed and processed in two steps: classification and optimization. Firstly, a brief introduction to the current research status and the aims of this paper are outlined. And then, how the typical customized links classified is proposed. Next, the technology method and the iterative formula derivation process of topology optimization are described in detail. Finally, calculation models for each group of classified ones are set up and their optimal structures are achieved through topology optimization technique. The results provide useful references for reconfigurable and modular design in engineering cases.

关键词： parallel kinematic machines (PKMs) modular design classification topology optimization and improved Guide-Weight method

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Arthrogryposis multiplex congenita: classification, diagnosis, perioperative care, and anesthesia

null

《医学前沿（英文）》 2017年第11卷第1期页码 48-52 doi: 10.1007/s11684-017-0500-4

摘要：

Arthrogryposis multiplex congenita (AMC) is a rare disorder characterized by non-progressive, multiple contractures. In addition to affected extremities, patients may also present microstomia, decreased temporomandibular joint mobility. Although the etiology of AMC is unclear, any factor that decreases fetal movement is responsible for AMC. Thus, accurate diagnosis and classification are crucial to the appropriate treatment of AMC. The development of ultrasound technology has enabled prenatal diagnosis. Very early treatment is favorable, and multidisciplinary treatment is necessary to improve the function of AMC patients. Most patients require surgery to release contracture and reconstruct joints. However, perioperative care is challenging, and difficult airway is the first concern of anesthesiologists. Postoperative pulmonary complications are common and regional anesthesia is recommended for postoperative analgesia. This review on AMC is intended for anesthesiologists. Thus, we discuss the treatment and perioperative management of patients undergoing surgery, as well as the diagnosis and classification of AMC.

关键词： arthrogryposis amyoplasia distal arthrogryposis anesthesia

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Molecular classification and molecular targeted therapy of cancer

null

《医学前沿（英文）》 2013年第7卷第2期页码 147-149 doi: 10.1007/s11684-013-0274-2

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Fine-grained P2P traffic classification by simply counting flows

Jie HE,Yue-xiang YANG,Yong QIAO,Wen-ping DENG

《信息与电子工程前沿（英文）》 2015年第16卷第5期页码 391-403 doi: 10.1631/FITEE.1400267

摘要： The continuous emerging of peer-to-peer (P2P) applications enriches resource sharing by networks, but it also brings about many challenges to network management. Therefore, P2P applications monitoring, in particular, P2P traffic classification, is becoming increasingly important. In this paper, we propose a novel approach for accurate P2P traffic classification at a fine-grained level. Our approach relies only on counting some special flows that are appearing frequently and steadily in the traffic generated by specific P2P applications. In contrast to existing methods, the main contribution of our approach can be summarized as the following two aspects. Firstly, it can achieve a high classification accuracy by exploiting only several generic properties of flows rather than complicated features and sophisticated techniques. Secondly, it can work well even if the classification target is running with other high bandwidth-consuming applications, outperforming most existing host-based approaches, which are incapable of dealing with this situation. We evaluated the performance of our approach on a real-world trace. Experimental results show that P2P applications can be classified with a true positive rate higher than 97.22% and a false positive rate lower than 2.78%.

关键词： Traffic classification Peer-to-peer (P2P) Fine-grained Host-based

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Terrain classification and adaptive locomotion for a hexapod robot Qingzhui

Yue ZHAO, Feng GAO, Qiao SUN, Yunpeng YIN

《机械工程前沿（英文）》 2021年第16卷第2期页码 271-284 doi: 10.1007/s11465-020-0623-1

摘要： Legged robots have potential advantages in mobility compared with wheeled robots in outdoor environments. The knowledge of various ground properties and adaptive locomotion based on different surface materials plays an important role in improving the stability of legged robots. A terrain classification and adaptive locomotion method for a hexapod robot named Qingzhui is proposed in this paper. First, a force-based terrain classification method is suggested. Ground contact force is calculated by collecting joint torques and inertial measurement unit information. Ground substrates are classified with the feature vector extracted from the collected data using the support vector machine algorithm. Then, an adaptive locomotion on different ground properties is proposed. The dynamic alternating tripod trotting gait is developed to control the robot, and the parameters of active compliance control change with the terrain. Finally, the method is integrated on a hexapod robot and tested by real experiments. Our method is shown effective for the hexapod robot to walk on concrete, wood, grass, and foam. The strategies and experimental results can be a valuable reference for other legged robots applied in outdoor environments.

关键词： terrain classification hexapod robot legged robot adaptive locomotion gait control