Anomaly Detection Method Using Feature Reconstruction Based Knowledge Distillation

In recent years,anomaly detection has attracted much attention in industrial production.As traditional anomaly detection methods usually rely on direct comparison of samples,they often ignore the intrinsic relationship between samples,resulting in poor accuracy in recognizing anomalous samples.To address this problem,a knowledge distillation anomaly detection method based on feature reconstruction was proposed in this study.Knowledge distillation was performed after inverting the structure of the teacher-student network to avoid the teacher-student network sharing the same inputs and similar structure.Representability was improved by using feature splicing to unify features at different levels,and the merged features were processed and reconstructed using an improved Transformer.The experimental results show that the proposed method achieves better performance on the MVTec dataset,verifying its effectiveness and feasibility in anomaly detection tasks.This study provides a new idea to improve the accuracy and efficiency of anomaly detection.

A Feature-Based Parametric Product Modeling System in CIMS Environment

This paper proposes an approach of developing the feature based parametric product modeling system which is suitable for integrated engineering design in CIMS environment.The architecture of ZD--MCADII and the characteristics of its each module are introduced in detail. ZD--MCADII’s product data is managed by an object--oriented database management system OSCAR, and the product model is built according to the standard STEP. The product design is established on a unified product model, and all the product data are globally associated in ZD--MCADII. ZD--MCADII provides various design features to facilitate the product design, and supports the integrity of CAD, CAPP and CAM.

Well production optimization using streamline features-based objective function and Bayesian adaptive direct search algorithm

Well production optimization is a complex and time-consuming task in the oilfield development.The combination of reservoir numerical simulator with optimization algorithms is usually used to optimize well production.This method spends most of computing time in objective function evaluation by reservoir numerical simulator which limits its optimization efficiency.To improve optimization efficiency,a well production optimization method using streamline features-based objective function and Bayesian adaptive direct search optimization(BADS)algorithm is established.This new objective function,which represents the water flooding potential,is extracted from streamline features.It only needs to call the streamline simulator to run one time step,instead of calling the simulator to calculate the target value at the end of development,which greatly reduces the running time of the simulator.Then the well production optimization model is established and solved by the BADS algorithm.The feasibility of the new objective function and the efficiency of this optimization method are verified by three examples.Results demonstrate that the new objective function is positively correlated with the cumulative oil production.And the BADS algorithm is superior to other common algorithms in convergence speed,solution stability and optimization accuracy.Besides,this method can significantly accelerate the speed of well production optimization process compared with the objective function calculated by other conventional methods.It can provide a more effective basis for determining the optimal well production for actual oilfield development.

Feature-based and objectoriented product information model for welding structure

Product information model for welding structure plays an important role for the integration of welding CAD/CAPP/CAM. However, existing CAD modeling systems are not capable of providing enough information for subsequent manufacturing activities such as CAPP and CAM. A new design approach using feature technique and object oriented programming method is put forward in this paper in order to create the product information model of welding structure. With this approach, the product information model is able to effectively support computer aided welding process planning, fixturing, assembling, path planning of welding robot and other manufacturing activities. The feature classification and representing scheme of welding structure are discussed. A prototype system is developed based on feature and object oriented programming. Its structure and functions are given in detail.

Product Image Classification Based on Fusion Features

Two key challenges raised by a product images classification system are classification precision and classification time. In some categories, classification precision of the latest techniques, in the product images classification system, is still low. In this paper, we propose a local texture descriptor termed fan refined local binary pattern, which captures more detailed information by integrating the spatial distribution into the local binary pattern feature. We compare our approach with different methods on a subset of product images on Amazon/e Bay and parts of PI100 and experimental results have demonstrated that our proposed approach is superior to the current existing methods. The highest classification precision is increased by 21% and the average classification time is reduced by 2/3.

Exogenous Financing,State-Ownership Features and Enterprises Productivity-An Empirical Analysis on Listed Chinese Manufacturing Enterprises

This study examines how the exogenous financing and state-ownership features affect the enterprises’productivity by observing the financing data of 1,481 Chinese listed enterprises over the period 2001-2016.The result shows that long-term loan has a positive impact on enterprises’productivity.Short-term loan and account payable have a negative impact on enterprises’productivity.Also,we find that state-ownership features have a negative impact on enterprises productivity.Moreover,this paper investigates the relationship between enterprises’productivity and the degree of regional economic development measured by GDP on provincial level.The result shows provincial economic development is positively related to the enterprises productivity.These findings are useful for both related authorities and enterprises for better understanding of the financial channels and constrains in China and the possible solutions to more diversified exogenous financing.

Binary Oriented Feature Selection for Valid Product Derivation in Software Product Line

Software Product Line(SPL)is a group of software-intensive systems that share common and variable resources for developing a particular system.The feature model is a tree-type structure used to manage SPL’s common and variable features with their different relations and problem of Crosstree Constraints(CTC).CTC problems exist in groups of common and variable features among the sub-tree of feature models more diverse in Internet of Things(IoT)devices because different Internet devices and protocols are communicated.Therefore,managing the CTC problem to achieve valid product configuration in IoT-based SPL is more complex,time-consuming,and hard.However,the CTC problem needs to be considered in previously proposed approaches such as Commonality VariabilityModeling of Features(COVAMOF)andGenarch+tool;therefore,invalid products are generated.This research has proposed a novel approach Binary Oriented Feature Selection Crosstree Constraints(BOFS-CTC),to find all possible valid products by selecting the features according to cardinality constraints and cross-tree constraint problems in the featuremodel of SPL.BOFS-CTC removes the invalid products at the early stage of feature selection for the product configuration.Furthermore,this research developed the BOFS-CTC algorithm and applied it to,IoT-based feature models.The findings of this research are that no relationship constraints and CTC violations occur and drive the valid feature product configurations for the application development by removing the invalid product configurations.The accuracy of BOFS-CTC is measured by the integration sampling technique,where different valid product configurations are compared with the product configurations derived by BOFS-CTC and found 100%correct.Using BOFS-CTC eliminates the testing cost and development effort of invalid SPL products.

PRODUCT IMAGE RETRIEVAL BASED ON CO-FEATURES OF THE OBJECT

In this paper, we propose a product image retrieval method based on the object contour corners, image texture and color. The product image mainly highlights the object and its background is very simple. According to these characteristics, we represent the object using its contour, and detect the corners of contour to reduce the number of pixels. Every corner is described using its approximate curvature based on distance. In addition, the Block Difference of Inverse Probabilities (BDIP) and Block Variation of Local Correlation (BVLC) texture features and color moment are extracted from image's HIS color space. Finally, dynamic time warping method is used to match features with different length. In order to demonstrate the effect of the proposed method, we carry out experiments in Mi-crosoft product image database, and compare it with other feature descriptors. The retrieval precision and recall curves show that our method is feasible.

Adaptability Feature's Concept, Modeling and Application in Product Design

The current 3D CAD/CAM system, both research prototypes and commercial systems, based on traditional feature modeling are always hampered by the problems in their complicated modeling and difficult maintaining. This paper introduces a new method for modeling parts by using adaptability feature (AF), by which the consistent relationship among parts and assemblies can be maintained in whole design process. In addition, the design process, can be speeded, time-to-market shortened, and product quality improved. Some essential issues of the strategy are discussed. A system, KMCAD3D, by taking advantages of AF has been developed. It is shown that the method discussed is a feasible and effective way to improve current feature modeling technology.

Feature extraction of search product based on multi-feature fusion-oriented to Chinese online reviews

The increasing Chinese online reviews contain rich product demand information,especially for search products.This study suggests a product feature extraction model from online reviews based on multi-feature fusion named PFEMF(products features extraction based on multi-feature fusion)model.Combining sentence and word characteristics of Chinese online reviews,the model explores the lexical features,frequency features,span features,and semantic similarity features of words.And then,they are fused to identify the features that customers are concerned about most by sequential relationship analysis.The identified product feature provides direction for product innovation and facilitates the product selection for customers.Finally,the study takes iPad Air as an example to prove this model.The results show that the extraction performance of the PFEMF model is superior to the traditional term frequency-inverse document frequency(tf-idf)algorithm,word span algorithm,and semantic similarity algorithm.

A FORMAL REPRESENTATION FOR FEATURE-BASED DESIGN

Feature based design has been regarded as a promising approach for CAD/CAM integration.This paper aims to establish a domain independent representation formalism for feature based design in three aspects: formal representation,design process model and design algorithm.The implementing scheme and formal description of feature taxonomy,feature operator,feature model validation and feature transformation are given in the paper.The feature based design process model suited for either sequencial or concurrent engineering is proposed and its application to product structural design and process plan design is presented. Some general design algorithms for developing feature based design system are also addressed.The proposed scheme provides a formal methodology elementary for feature based design system development and operation in a structural way.

Stylistic Analysis on "Bill's Little Girl":Lexical Features

"Bill's Little Girl " is a prose. This article analysis's its stylistic features of language in the aspects of lexical. While analysis, we can further appreciate its plain and simple language, its natural and fluent manner of writing and its complete discourse, meanwhile we can deeply understand that love is great, father's love is great.

Clinical and Pathological Features of Riedel's Thyroiditis

Objective To evaluate the clinical and pathological features of Riedel's thyroiditis(RT),and current diagnostic and treatment methods for that disease.Methods Five RT cases identified by surgery and pathological examinations at Peking Union Medical College Hospital from 1985 to 2009 were analyzed and compared with the cases reported in the literature in terms of clinical and pathological features.Immunohistochemical staining of kappa and lambda light chains was carried out for RT tissues from all the five patients.Results All the five cases were females,aged 45-55 years.Elevation of serum thyroid autoantibodies was found in only one patient,who had longer disease duration than the others.Pathological examination revealed invasive fibrosclerosis of the thyroid follicles,thyroid capsule,and the surrounding tissues.In RT tissues,the number of cells containing lambda chains was a little higher than those containing kappa chains.Conclusions RT is a rare disease which might be more common in middle-aged females than in other populations.Pathological features include the destruction of thyroid follicle,extension into surrounding tissues by inflammatory cells and fibrous tissues.Immunohistochemical staining of kappa and lambda chains could help diagnose RT.

Enhancing Parkinson’s Disease Prediction Using Machine Learning and Feature Selection Methods

Several millions of people suffer from Parkinson’s disease globally.Parkinson’s affects about 1%of people over 60 and its symptoms increase with age.The voice may be affected and patients experience abnormalities in speech that might not be noticed by listeners,but which could be analyzed using recorded speech signals.With the huge advancements of technology,the medical data has increased dramatically,and therefore,there is a need to apply data mining and machine learning methods to extract new knowledge from this data.Several classification methods were used to analyze medical data sets and diagnostic problems,such as Parkinson’s Disease(PD).In addition,to improve the performance of classification,feature selection methods have been extensively used in many fields.This paper aims to propose a comprehensive approach to enhance the prediction of PD using several machine learning methods with different feature selection methods such as filter-based and wrapper-based.The dataset includes 240 recodes with 46 acoustic features extracted from3 voice recording replications for 80 patients.The experimental results showed improvements when wrapper-based features selection method was used with K-NN classifier with accuracy of 88.33%.The best obtained results were compared with other studies and it was found that this study provides comparable and superior results.

Drainage feature about coalbed methane wells in different hydrogeological conditions in Fanzhuang area

It is an important guarantee to enhance the production of coalbed methane （CBM） and reduce the project invest- ment by finding out the drainage feature about CBM wells in different hydrogeological conditions. Based on the CBM explora- tion and development data on the Fanzhuang block in southeast Qinshui Basin and combined with the seepage principle and lithology on the roof and the bottom coalbed, the mathematical model of integrated permeability was established. By perme- ability experiments of the different lithologies on the roof and the floor within the 20 m range combined with the log curves, the integrated permeability of different lithological combinations were obtained. The starting pressure gradient and permeabi- lity of the roof and the floor for different lithologies was tested by ＂differential pressure-flow method＂. The relationships be- tween the starting pressure gradient and the integrated permeability were obtained. The critical distance of limestone water penetrating into coal reservoirs was calculated. According to the drainage feature of CBM wells combined with the drainage data of some CBM wells, the results show that, when limestone water can penetrate into coal reservoirs, the daily water production is high and the daily gas production is low although there is no gas at the beginning of the drainage process, the CBM wells stop discharging water within 6 months after the gas began to come out, and the gas production is steadily improved. When limestone water can not penetrate into coal reservoirs, the daily water production is low and the daily gas production is high at the beginning of the drainage process, and it almost stops discharging water after some time when the gas come out, the daily gas production increases, and the cumulative water production is much lower.

Diffuse large B-cell lymphoma arising from follicular lymphoma with warthin’s tumor of the parotid gland-immunophenotypic and genetic features: A case report

BACKGROUND Warthin’s tumor(WT)is composed of several cysts that are lined with tall,bilayered oncocytic columnar cells and lymphoid stroma.Within WT,the two components rarely transform into carcinoma or lymphoma,and when it does,carcinoma is the most common type.Approximately 28 cases of lymphoma with WT have been reported,most of which were non-Hodgkin lymphomas,and only a few cases were Hodgkin lymphomas.In the present report,we studied a case of diffuse large B cell lymphoma(DLBCL)arising from follicular lymphoma(FL)with WT in the parotid gland and its immunophenotypic and genetic features.CASE SUMMARY A 67-year-old man presented with a slowly enlarging right cheek mass for 12 years,and the mass began to change in size over a 2-mo time period.Over time,the patient felt mild local pain and right cheek discomfort.His medical history included a hepatitis B virus infection for 20 years and 30 years of smoking.Gross examination of the excised specimen showed a gray-red and gray-white appearance and a soft texture lobulated external surface neoplasm that measured 9 cm×8 cm×7 cm and was well circumscribed by relative normal parotid gland tissue.In cross section,the cut surfaces of the neoplasm were multicystic and had a homogeneous scaly appearance.A small fluid was discovered in the cyst.Bilateral oxyphilic,cuboidal or polygonal epithelium cells and lymphoid intraparenchymal components were observed.Many medium-to large-sized lymphoid cells were observed diffusely in part of the neoplasm,and a few secondary lymphoid follicles were observed at the center or edge of the neoplasm.Immunohistochemical staining showed that the columnar oncocytic cells were positive for AE1/AE3;neoplastic cells located in coarctate follicular were positive for CD20,Pax-5,bcl-2 and bcl-6;and the adjacent diffusely medium-to large-sized lymphoid cells were positive for Pax-5,bcl-6,CD20,MUM-1,bcl-2 and CD79a.The bcl-6(3q27)break-apart rearrangement was observed,and an Epstein Barr virus test was negative in the tumor cells.The patient survived 6 months after being diagnosed without any treatment.CONCLUSION WT-associated lymphoma is a very rare neoplasm in the parotid gland.Most cases are B cell non-Hodgkin lymphomas and involve middle-age and older males.This case highlights the extremely rare association of DLBCL arising from FL with WT and the importance of deliberate evaluation of the WT intraparenchymal stroma.Molecular detection techniques have potential advantages in the diagnosis of lymphoma with WT.

Content Feature Extraction-based Hybrid Recommendation for Mobile Application Services

The number of mobile application services is showing an explosive growth trend,which makes it difficult for users to determine which ones are of interest.Especially,the new mobile application services are emerge continuously,most of them have not be rated when they need to be recommended to users.This is the typical problem of cold start in the field of collaborative filtering recommendation.This problem may makes it difficult for users to locate and acquire the services that they actually want,and the accuracy and novelty of service recommendations are also difficult to satisfy users.To solve this problem,a hybrid recommendation method for mobile application services based on content feature extraction is proposed in this paper.First,the proposed method in this paper extracts service content features through Natural Language Processing technologies such as word segmentation,part-of-speech tagging,and dependency parsing.It improves the accuracy of describing service attributes and the rationality of the method of calculating service similarity.Then,a language representation model called Bidirectional Encoder Representation from Transformers(BERT)is used to vectorize the content feature text,and an improved weighted word mover’s distance algorithm based on Term Frequency-Inverse Document Frequency(TFIDF-WMD)is used to calculate the similarity of mobile application services.Finally,the recommendation process is completed by combining the item-based collaborative filtering recommendation algorithm.The experimental results show that by using the proposed hybrid recommendation method presented in this paper,the cold start problem is alleviated to a certain extent,and the accuracy of the recommendation result has been significantly improved.

A WEIGHTED FEATURE REDUCTION METHOD FOR POWER SPECTRA OF RADAR HRRPS

Feature reduction is a key process in pattern recognition. This paper deals with the feature reduction methods for a time-shift invariant feature, power spectrum, in Radar Automatic Target Recognition (RATR) using High-Resolution Range Profiles (HRRPs). Several existing feature reduction methods in pattern recognition are analyzed, and a weighted feature reduction method based on Fisher's Discriminant Ratio (FDR) is proposed in this paper. According to the characteristics of radar HRRP target recognition, this proposed method searches the optimal weight vector for power spectra of HRRPs by means of an iterative algorithm, and thus reduces feature dimensionality. Compared with the method of using raw power spectra and some existing feature reduction methods, the weighted feature reduction method can not only reduce feature dimensionality, but also improve recognition performance with low computation complexity. In the recognition experiments based on measured data, the proposed method is robust to different test data and achieves good recognition results.

Robust Speech Recognition System Using Conventional and Hybrid Features of MFCC,LPCC,PLP,RASTA-PLP and Hidden Markov Model Classifier in Noisy Conditions

In recent years, the accuracy of speech recognition (SR) has been one of the most active areas of research. Despite that SR systems are working reasonably well in quiet conditions, they still suffer severe performance degradation in noisy conditions or distorted channels. It is necessary to search for more robust feature extraction methods to gain better performance in adverse conditions. This paper investigates the performance of conventional and new hybrid speech feature extraction algorithms of Mel Frequency Cepstrum Coefficient (MFCC), Linear Prediction Coding Coefficient (LPCC), perceptual linear production (PLP), and RASTA-PLP in noisy conditions through using multivariate Hidden Markov Model (HMM) classifier. The behavior of the proposal system is evaluated using TIDIGIT human voice dataset corpora, recorded from 208 different adult speakers in both training and testing process. The theoretical basis for speech processing and classifier procedures were presented, and the recognition results were obtained based on word recognition rate.

Feature Technology in Product Modeling

A unified feature definition is proposed.Feature is form-concentrated,and can be used to model product func- tionalities,assembly relations,and part geometries.The feature model is given and a feature classification is introduced including functional,assembly,structural,and manufacturing features.A prototype modeling system is developed in Pro/ENGINEER that can define the assembly and user-defined form features.