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A software defect prediction method with metric compensation based on feature selection and transfer Research Article

Jinfu CHEN, Xiaoli WANG, Saihua CAI, Jiaping XU, Jingyi CHEN, Haibo CHEN,caisaih@ujs.edu.cn

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 5,   Pages 715-731 doi: 10.1631/FITEE.2100468

Abstract: redundant features in the model training process will affect the training efficiency and thus decrease the predictiongreatly from project to project due to the development environment and other factors, resulting in lower predictionaccuracy when the model achieves cross-project prediction.

Keywords： Defect prediction     Feature selection     Transfer learning     Metric compensation    

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Afeature selection approach based on a similarity measure for software defect prediction Article

Qiao YU, Shu-juan JIANG, Rong-cun WANG, Hong-yang WANG

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 11,   Pages 1744-1753 doi: 10.1631/FITEE.1601322

Abstract: Software defect prediction is aimed to find potential defects based on historical data and software featuresthe class, we present a feature selection approach based on a similarity measure (SM) for software defectprediction.

Keywords： Software defect prediction     Feature selection     Similarity measure     Feature weights     Feature ranking list    

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Acoustic fault signal extraction via the line-defect phononic crystals

Frontiers of Mechanical Engineering 2022, Volume 17, Issue 1,   Pages 10-10 doi: 10.1007/s11465-021-0666-y

Abstract: In this paper, 2D line-defect phononic crystals (PCs) consisting of periodic acrylic tubes with slitThe defect band, namely, the formed resonance band of line-defect PCs enables the incident acoustic waveThe effectiveness of weak harmonic and periodic impulse signal detection via line-defect PCs are investigatedAll the numerical and experimental results indicate that line-defect PCs can be well used for extracting

Keywords： phononic crystals     line-defect     fault signal extraction     acoustic enhancement    

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Research progress of defect-engineered UiO-66(Zr) MOFs for photocatalytic hydrogen production

Frontiers in Energy 2021, Volume 15, Issue 3,   Pages 656-666 doi: 10.1007/s11708-021-0765-9

Abstract: In recent years, defect-engineered Zr-based UiO-66 metal-organic frameworks (UiO-66(Zr) metal-organicIt is extremely challenging to introduce defect sites in the synthesis of MOFs to regulate the physicochemicalrecent research results of synthesis methods, characterization technologies, and application fields of defect-engineered

Keywords： defect engineering     metal-organic frameworks     UiO-66     photocatalysis    

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The defect-length effect in corrosion detection with magnetic method for bridge cables

Qiwei ZHANG, Rongya XIN

Frontiers of Structural and Civil Engineering 2018, Volume 12, Issue 4,   Pages 662-671 doi: 10.1007/s11709-018-0512-4

Abstract: The magnetic flux (MF) examination shows great potential to detect the corrosion defect, or loss of metallicAn LMA defect in steel cables can be measured accurately when it is longer than a certain length.In this study, the effect of defect length on the MF examination for corrosion detection of bridge cablesAn original analytical model to quantify the influence of defect length is proposed based on the equivalentThen, MF examination experiments are performed on a series of cable models with different defect lengths

Keywords： bridge cable     corrosion detection     defect length     MF examination     quantitative evaluation    

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Single-electromagnet levitation for density measurement and defect detection

Yuhan JIA, Peng ZHAO, Jun XIE, Xuechun ZHANG, Hongwei ZHOU, Jianzhong FU

Frontiers of Mechanical Engineering 2021, Volume 16, Issue 1,   Pages 186-195 doi: 10.1007/s11465-020-0608-0

Abstract: single-electromagnet levitation device has a large measuring range and can realize accurate density measurement and defect

Keywords： single-electromagnet     electromagnetic levitation     density measurement     defect detection    

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Statistical analysis of recombination properties of the boron-oxygen defect in p-type Czochralski silicon

Nitin NAMPALLI,Tsun Hang FUNG,Stuart WENHAM,Brett HALLAM,Malcolm ABBOTT

Frontiers in Energy 2017, Volume 11, Issue 1,   Pages 4-22 doi: 10.1007/s11708-016-0442-6

Abstract: lifetime spectroscopy to the study of carrier-induced degradation ascribed to the boron-oxygen (BO) defectresults demonstrate that the capture cross section ratio associated with the donor level of the BO defectFor the data set studied here, it was also found that illumination used to form the defect caused minoralone and is likely related to the acceptor level of the BO defect.While specific to the BO defect, this study has implications for the use of lifetime spectroscopy to

Keywords： Czochralski silicon     boron-oxygen defect     injection dependent lifetime spectroscopy     goodness-of-fit     repeatability    

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Study on Defect Detection Technology for Bridge Deck Pavements

Guo Chengchao,Xu Pengfei and Cui Can

Strategic Study of CAE 2017, Volume 19, Issue 6,   Pages 38-43 doi: 10.15302/J-SSCAE-2017.06.006

Abstract:

The bridge deck is the most vulnerable part of a bridge during its entire life cycle. The deck pavement is often adversely affected by improper construction methods, the aging of concrete, and corrosion of steel bars. This then has an adverse effect on the structure and overall performance of the bridge. Therefore, it is necessary to determined defects related to the bridge deck and to conduct relevant quality evaluations. This article describes the mechanism, application methods, and testing equipment of four mainstream nondestructive testing technologies used worldwide: ground penetrating radar, half-cell potential, impact echo, and infrared thermography. The use of one or more of these methods can accurately assess the deterioration of the bridge deck and make a rapid, nondestructive evaluation, which provides technical support for rapid detection and accurate evaluation of the deck situation, leading to reduced structural defects and an extended bridge life cycle.

Keywords： bridge deck pavement     defect     nondestructive testing    

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Effect of cavity defect on the triaxial mechanical properties of high-performance concrete

Yanbin ZHANG; Zhe WANG; Mingyu FENG

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 5,   Pages 600-614 doi: 10.1007/s11709-022-0821-5

Abstract: The stress concentration of pipe structure or cavity defect has a great effect on the mechanical properties

Keywords： high-performance concrete     cavity     conventional triaxial compression     pressurized liquid     modified power-law criterion    

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Construction of defect-containing UiO-66/MoSe heterojunctions with superior photocatalytic performance

Frontiers of Chemical Science and Engineering 2023, Volume 17, Issue 4,   Pages 449-459 doi: 10.1007/s11705-022-2226-3

Abstract: Metal–organic frameworks are recognized as promising multifunctional materials, especially metal–organic framework-based photocatalysts, which are considered to be ideal photocatalytic materials. Herein, a new type of UiO-66/MoSe2 composite was prepared using the solvothermal method. The optimum composite was selected by adjusting the mass ratio of UiO-66 and MoSe2. X-ray diffraction analysis showed that the mass ratio influenced the crystal plane exposure rate of the composite, which may have affected its photocatalytic performance. The composite is composed of ultra-thin flower-like MoSe2 that wrapped around cubic UiO-66, a structure that increases the abundance of active sites for reactions and is more conducive to the separation of carriers. The photocatalytic properties of the composite were evaluated by measuring the degradation rate of Rhodamine B and the catalyst’s ability to reduce Cr(VI)-containing wastewater under visible light irradiation. Rhodamine B was decolorized completely in 120 min, and most of the Cr(VI) was reduced within 150 min. The photochemical mechanism of the complex was studied in detail. The existence of Mo6+ and oxygen vacancies, in addition to the Z-type heterojunction promote the separation of electrons and holes, which enhances the photocatalytic effect.

Keywords： UiO-66/MoSe2     photocatalysis     dye-containing wastewater     heavy metal wastewater     oxygen vacancies    

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Spatial prediction of soil contamination based on machine learning: a review

Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 8, doi: 10.1007/s11783-023-1693-1

Abstract:

● A review of machine learning (ML) for spatial prediction of soil

Keywords： Soil contamination     Machine learning     Prediction     Spatial distribution    

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Hybrid deep learning model for risk prediction of fracture in patients with diabetes and osteoporosis

Frontiers of Medicine 2022, Volume 16, Issue 3,   Pages 496-506 doi: 10.1007/s11684-021-0828-7

Abstract: The fracture risk of patients with diabetes is higher than those of patients without diabetes due to hyperglycemia, usage of diabetes drugs, changes in insulin levels, and excretion, and this risk begins as early as adolescence. Many factors including demographic data (such as age, height, weight, and gender), medical history (such as smoking, drinking, and menopause), and examination (such as bone mineral density, blood routine, and urine routine) may be related to bone metabolism in patients with diabetes. However, most of the existing methods are qualitative assessments and do not consider the interactions of the physiological factors of humans. In addition, the fracture risk of patients with diabetes and osteoporosis has not been further studied previously. In this paper, a hybrid model combining XGBoost with deep neural network is used to predict the fracture risk of patients with diabetes and osteoporosis, and investigate the effect of patients’ physiological factors on fracture risk. A total of 147 raw input features are considered in our model. The presented model is compared with several benchmarks based on various metrics to prove its effectiveness. Moreover, the top 18 influencing factors of fracture risks of patients with diabetes are determined.

Keywords： XGBoost     deep neural network     healthcare     risk prediction    

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Detection for transverse corner cracks of steel plates’ surface using wavelet

Qiong ZHOU, Qi AN

Frontiers of Mechanical Engineering 2009, Volume 4, Issue 2,   Pages 224-227 doi: 10.1007/s11465-009-0017-x

Abstract: An algorithm is presented for detecting transverse corner cracks at a steel plate surface using wavelet transform. According to characteristics of transverse corner crack images, the wavelet transform is used for the multi-scale analysis of detecting the image edges and disintegrating the image into four directions at the same time. The proper threshold value is chosen to segment the image into vertical components to obtain the final detection result. The experiment shows that transverse corner cracks of steel plates can be more effectively extracted by the proposed method than the other two common methods.

Keywords： transverse corner cracks     defect detection     multi-scales wavelet analysis    

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Position-varying surface roughness prediction method considering compensated acceleration in milling

Frontiers of Mechanical Engineering 2021, Volume 16, Issue 4,   Pages 855-867 doi: 10.1007/s11465-021-0649-z

Abstract: Aiming at surface roughness prediction in the machining process, this paper proposes a position-varyingsurface roughness prediction method based on compensated acceleration by using regression analysis.i>R-square proving the effectiveness of the filtering features, is selected as the input of the predictionMoreover, the prediction curve matches and agrees well with the actual surface state, which verifies

Keywords： surface roughness prediction     compensated acceleration     milling     thin-walled workpiece    

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Improved prediction of pile bending moment and deflection due to adjacent braced excavation

Frontiers of Structural and Civil Engineering doi: 10.1007/s11709-023-0961-2

Abstract: Deep excavations in dense urban areas have caused damage to nearby existing structures in numerous past construction cases. Proper assessment is crucial in the initial design stages. This study develops equations to predict the existing pile bending moment and deflection produced by adjacent braced excavations. Influential parameters (i.e., the excavation geometry, diaphragm wall thickness, pile geometry, strength and small-strain stiffness of the soil, and soft clay thickness) were considered and employed in the developed equations. It is practically unfeasible to obtain measurement data; hence, artificial data for the bending moment and deflection of existing piles were produced from well-calibrated numerical analyses of hypothetical cases, using the three-dimensional finite element method. The developed equations were established through a multiple linear regression analysis of the artificial data, using the transformation technique. In addition, the three-dimensional nature of the excavation work was characterized by considering the excavation corner effect, using the plane strain ratio parameter. The estimation results of the developed equations can provide satisfactory pile bending moment and deflection data and are more accurate than those found in previous studies.

Keywords： pile responses     excavation     prediction     deflection     bending moments    

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Title Author Date Type Operation

A software defect prediction method with metric compensation based on feature selection and transfer

Jinfu CHEN, Xiaoli WANG, Saihua CAI, Jiaping XU, Jingyi CHEN, Haibo CHEN,caisaih@ujs.edu.cn

Journal Article

Afeature selection approach based on a similarity measure for software defect prediction

Qiao YU, Shu-juan JIANG, Rong-cun WANG, Hong-yang WANG

Journal Article

Acoustic fault signal extraction via the line-defect phononic crystals

Journal Article

Research progress of defect-engineered UiO-66(Zr) MOFs for photocatalytic hydrogen production

Journal Article

The defect-length effect in corrosion detection with magnetic method for bridge cables

Qiwei ZHANG, Rongya XIN

Journal Article

Single-electromagnet levitation for density measurement and defect detection

Yuhan JIA, Peng ZHAO, Jun XIE, Xuechun ZHANG, Hongwei ZHOU, Jianzhong FU

Journal Article

Statistical analysis of recombination properties of the boron-oxygen defect in p-type Czochralski silicon

Nitin NAMPALLI,Tsun Hang FUNG,Stuart WENHAM,Brett HALLAM,Malcolm ABBOTT

Journal Article

Study on Defect Detection Technology for Bridge Deck Pavements

Guo Chengchao,Xu Pengfei and Cui Can

Journal Article

Effect of cavity defect on the triaxial mechanical properties of high-performance concrete

Yanbin ZHANG; Zhe WANG; Mingyu FENG

Journal Article

Construction of defect-containing UiO-66/MoSe heterojunctions with superior photocatalytic performance

Journal Article

Spatial prediction of soil contamination based on machine learning: a review

Journal Article

Hybrid deep learning model for risk prediction of fracture in patients with diabetes and osteoporosis

Journal Article

Detection for transverse corner cracks of steel plates’ surface using wavelet

Qiong ZHOU, Qi AN

Journal Article

Position-varying surface roughness prediction method considering compensated acceleration in milling

Journal Article

Improved prediction of pile bending moment and deflection due to adjacent braced excavation

Journal Article