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Fraud detection within bankcard enrollment on mobile device based payment using machine learning None

Hao ZHOU, Hong-feng CHAI, Mao-lin QIU

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 12,   Pages 1537-1545 doi: 10.1631/FITEE.1800580

Abstract: technologies has induced a dramatic increase in mobile payments as well as concomitant mobile transaction fraudstep of mobile transactions, bankcard enrollment on mobile devices has become the primary target of fraudAlthough no immediate financial loss is incurred after a fraud attempt, subsequent fraudulent transactionscan be quickly executed and could easily deceive the fraud detection systems if the fraud attempt succeedsThe results and framework are adopted and absorbed into a new design for a mobile payment fraud detectionsystem

Keywords： Fraud detection     Mobile payment     Bankcard enrollment     Mobile device based     GBDT     XGBoost    

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FinBrain 2.0: when finance meets trustworthy AI Review

Jun ZHOU, Chaochao CHEN, Longfei LI, Zhiqiang ZHANG, Xiaolin ZHENG

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 12,   Pages 1747-1764 doi: 10.1631/FITEE.2200039

Abstract: Artificial intelligence (AI) has accelerated the advancement of financial services by identifying hidden patterns from data to improve the quality of financial decisions. However, in addition to commonly desired attributes, such as model accuracy, financial services demand trustworthy AI with properties that have not been adequately realized. These properties of trustworthy AI are interpretability, fairness and inclusiveness, robustness and security, and privacy protection. Here, we review the recent progress and limitations of applying AI to various areas of financial services, including , , , personalized services, and regulatory technology. Based on these progress and limitations, we introduce FinBrain 2.0, a research framework toward trustworthy AI. We argue that we are still a long way from having a truly trustworthy AI in financial services and call for the communities of AI and financial industry to join in this effort.

Keywords： Artificial intelligence in finance     Trustworthy artificial intelligence     Risk management     Fraud detection    

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Usability perceptions and beliefs about smart thermostats by chi-square test, signal detection theory, and fuzzy detection theory in regions of Mexico

Pedro PONCE, Therese PEFFER, Arturo MOLINA

Frontiers in Energy 2019, Volume 13, Issue 3,   Pages 522-538 doi: 10.1007/s11708-018-0562-2

Abstract: This paper proposes the use of a signal detection theory (SDT), fuzzy detection theory (FDT), and chi-square

Keywords： thermostats     perceptions     beliefs     signal detection theory (SDT)     fuzzy signal detection theory (FSDT)     chi-square    

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Advances in airborne microorganisms detection using biosensors: A critical review

Frontiers of Environmental Science & Engineering 2021, Volume 15, Issue 3, doi: 10.1007/s11783-021-1420-8

Abstract: In recent years, the detection technology for airborne microorganisms has developed rapidly; it can be

Keywords： Biosensor     Airborne microorganisms     Microbiological detection technology    

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Recent advances in SERS detection of perchlorate

Jumin Hao, Xiaoguang Meng

Frontiers of Chemical Science and Engineering 2017, Volume 11, Issue 3,   Pages 448-464 doi: 10.1007/s11705-017-1611-9

Abstract: Development of novel detection methods for perchlorate with the potential for field use has been an urgentperchlorate in water and other media with an emphasis on the development of SERS substrates for perchlorate detection

Keywords： perchlorate     SERS     detection     substrate     modification     nanostructure    

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A fast antibiotic detection method for simplified pretreatment through spectra-based machine learning

Frontiers of Environmental Science & Engineering 2022, Volume 16, Issue 3, doi: 10.1007/s11783-021-1472-9

Abstract:

• A spectral machine learning approach is proposed for predicting mixed antibiotic.

Keywords： Antibiotic contamination     Spectral detection     Machine learning    

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Development of Pulsed Radiation Detection Technology

Ouyang Xiaoping

Strategic Study of CAE 2008, Volume 10, Issue 4,   Pages 44-55

Abstract: Pulse radiation detection has found its various applications in scientific researches, including nuclearThese diagnostic techniques and their relative detection systems, the design principle, the parameters

Keywords： fission reaction     fusion reaction     pulse radiation detection     detecting system     neutron detection     gamma-raydetection    

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Edge detection of steel plates at high temperature using image measurement

Qiong Zhou, Qi An

Frontiers of Mechanical Engineering 2009, Volume 4, Issue 1,   Pages 77-82 doi: 10.1007/s11465-009-0013-1

Abstract: An edge detection method for the measurement of steel plate’s thermal expansion is proposed in this paperFirst, images are picked up by an imaging system; a method of regional edge detection based on grayscales

Keywords： thermal expansion     image measurement     edge detection     image calibration    

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Machine vision-based automatic fruit quality detection and grading

Frontiers of Agricultural Science and Engineering doi: 10.15302/J-FASE-2023532

Abstract:

● A machine vision-based prototype system was developed for fruit grading.

Keywords： Computer and machine vision     convolution neural network     deep learning     defective fruit detection     fruit    

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Experimental and numerical study on microcrack detection using contact nonlinear acoustics

Xiaojia CHEN, Yuanlin WANG

Frontiers of Structural and Civil Engineering 2009, Volume 3, Issue 2,   Pages 137-141 doi: 10.1007/s11709-009-0028-z

Abstract: This paper introduces a non-classical nonlinear acoustic theory for microcrack detection in materialsconcentrates on the experimental and numerical verification of the effectivity of contact nonlinear acoustic detection

Keywords： microcrack detection     contact nonlinearity     numerical analysis    

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Digital image correlation-based structural state detection through deep learning

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 1,   Pages 45-56 doi: 10.1007/s11709-021-0777-x

Abstract: CNN can extract the structural state information from the vibration signals and classify them; 2) the detection

Keywords： structural state detection     deep learning     digital image correlation     vibration signal     steel frame    

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Damage detection in beam-like structures using static shear energy redistribution

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 12,   Pages 1552-1564 doi: 10.1007/s11709-022-0903-4

Abstract: Another advantage of the proposed approach is that damage detection can be performed without establishing

Keywords： damage detection     beam structure     strain energy     static displacement variation     energy damage index    

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Fast detection algorithm for cracks on tunnel linings based on deep semantic segmentation

Frontiers of Structural and Civil Engineering 2023, Volume 17, Issue 5,   Pages 732-744 doi: 10.1007/s11709-023-0965-y

Abstract: The proposed method addresses the low accuracy of tunnel crack segmentation and the slow detection speed

Keywords： tunnel engineering     crack segmentation     fast detection     DeepLabv3+     feature fusion     attention mechanism    

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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: In this study, the effect of defect length on the MF examination for corrosion detection of bridge cables

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

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Image-based fall detection and classification of a user with a walking support system

Sajjad TAGHVAEI, Kazuhiro KOSUGE

Frontiers of Mechanical Engineering 2018, Volume 13, Issue 3,   Pages 427-441 doi: 10.1007/s11465-017-0465-7

Abstract: show that the algorithm can be adapted to the new user’s motion pattern within 40 s, with a fall detectionThe proposed method can be implemented to other abnormality detection/classification applications that

Keywords： fall detection     walking support     hidden Markov model     multivariate analysis    

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Title Author Date Type Operation

Fraud detection within bankcard enrollment on mobile device based payment using machine learning

Hao ZHOU, Hong-feng CHAI, Mao-lin QIU

Journal Article

FinBrain 2.0: when finance meets trustworthy AI

Jun ZHOU, Chaochao CHEN, Longfei LI, Zhiqiang ZHANG, Xiaolin ZHENG

Journal Article

Usability perceptions and beliefs about smart thermostats by chi-square test, signal detection theory, and fuzzy detection theory in regions of Mexico

Pedro PONCE, Therese PEFFER, Arturo MOLINA

Journal Article

Advances in airborne microorganisms detection using biosensors: A critical review

Journal Article

Recent advances in SERS detection of perchlorate

Jumin Hao, Xiaoguang Meng

Journal Article

A fast antibiotic detection method for simplified pretreatment through spectra-based machine learning

Journal Article

Development of Pulsed Radiation Detection Technology

Ouyang Xiaoping

Journal Article

Edge detection of steel plates at high temperature using image measurement

Qiong Zhou, Qi An

Journal Article

Machine vision-based automatic fruit quality detection and grading

Journal Article

Experimental and numerical study on microcrack detection using contact nonlinear acoustics

Xiaojia CHEN, Yuanlin WANG

Journal Article

Digital image correlation-based structural state detection through deep learning

Journal Article

Damage detection in beam-like structures using static shear energy redistribution

Journal Article

Fast detection algorithm for cracks on tunnel linings based on deep semantic segmentation

Journal Article

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

Qiwei ZHANG, Rongya XIN

Journal Article

Image-based fall detection and classification of a user with a walking support system

Sajjad TAGHVAEI, Kazuhiro KOSUGE

Journal Article