Traditional anomaly detection methods often assume that data points are independent or exhibit regularly structured relationships,as in Euclidean data such as time series or image grids.However,real-world data frequen...Traditional anomaly detection methods often assume that data points are independent or exhibit regularly structured relationships,as in Euclidean data such as time series or image grids.However,real-world data frequently involve irregular,interconnected structures,requiring a shift toward non-Euclidean approaches.This study introduces a novel anomaly detection framework designed to handle non-Euclidean data by modeling transactions as graph signals.By leveraging graph convolution filters,we extract meaningful connection strengths that capture relational dependencies often overlooked in traditional methods.Utilizing the Graph Convolutional Networks(GCN)framework,we integrate graph-based embeddings with conventional anomaly detection models,enhancing performance through relational insights.Ourmethod is validated on European credit card transaction data,demonstrating its effectiveness in detecting fraudulent transactions,particularly thosewith subtle patterns that evade traditional,amountbased detection techniques.The results highlight the advantages of incorporating temporal and structural dependencies into fraud detection,showcasing the robustness and applicability of our approach in complex,real-world scenarios.展开更多
为解决C语言数据类型在支持后下载应用的片上操作系统(COS)中无法完全满足应用程序数据的存储特性和安全需求的问题,分析了Java Card和C语言数据类型的属性,提出了一种基于 C 语言扩展的应用程序数据类型体系。根据数据分类,重点阐述了...为解决C语言数据类型在支持后下载应用的片上操作系统(COS)中无法完全满足应用程序数据的存储特性和安全需求的问题,分析了Java Card和C语言数据类型的属性,提出了一种基于 C 语言扩展的应用程序数据类型体系。根据数据分类,重点阐述了4种模块数据类型和5种应用数据类型。测试结果表明,该数据类型体系满足了COS应用程序数据的需求,有效提升了内存利用率和应用执行性能,为COS虚拟机运行时环境提供了高效的数据模型。展开更多
GERON Card Clothing(Jiangsu)Co.,Ltd.was founded in 1987 and is a professional textile carding equipment enterprise integrating research,production and sales.The production and sales of carding equipment have been lead...GERON Card Clothing(Jiangsu)Co.,Ltd.was founded in 1987 and is a professional textile carding equipment enterprise integrating research,production and sales.The production and sales of carding equipment have been leading the industry for many years.Our products include metallic card clothing,flat-top,stationary flat,circular comb and combing roller.Our brands include TYRION,Blue Diamond,Diamond,Pioneer and Lance.We provide customers with the most advanced carding solutions.展开更多
Train Mass Rapid Transit(MRT)was put into service in 1987,and has since been augmented by and linked to the Light Rapid Transit.Combined,you can often get you within walking distance of most destinations.The maps on t...Train Mass Rapid Transit(MRT)was put into service in 1987,and has since been augmented by and linked to the Light Rapid Transit.Combined,you can often get you within walking distance of most destinations.The maps on the metro system are easy to read,complete with English version.You can easily purchase an EZ-Link card or a NETS Flashpay Card(stored value cards)at all MRT stations and bus interchange.展开更多
In the workshop of Guangshan White Shark Card Clothing Co.,Ltd.,precision machines are meticulously crafting the tips of card clothing with millimeter-level accuracy.These seemingly tiny textile accessories play a cru...In the workshop of Guangshan White Shark Card Clothing Co.,Ltd.,precision machines are meticulously crafting the tips of card clothing with millimeter-level accuracy.These seemingly tiny textile accessories play a crucial role in the global cotton and chemical fiber industry chains.As China's textile industry encounters trade barriers in the process of globalization,this company specializing in card clothing manufacturing is striving to explore a differentiated path in overseas markets.展开更多
Last Monday,on my way to school,I found a wallet on the ground.I picked up it①and opened it.There was some money,a student ID card and a few photos in it.I thought the owner must be very worried.
Operating out of Shanghai,Brujas Textile Tech(Shanghai)Co.,Ltd.(“Brujas”)is a wholly owned subsidiary of Guangshan White Shark Card Clothing Co.,Ltd.(“White Shark”)tasked with providing international trade service...Operating out of Shanghai,Brujas Textile Tech(Shanghai)Co.,Ltd.(“Brujas”)is a wholly owned subsidiary of Guangshan White Shark Card Clothing Co.,Ltd.(“White Shark”)tasked with providing international trade services to support its parent company's global operations.Whereas White Shark,as the parent company founded in 1962,is the manufacture facilities located in Xinyang,Henan Province.Brujas was founded in 1908 by the Brujas family in Terrassa,Spain.In 2008,White Shark integrated Brujas brand into its production and added European experience and knowledge that continues in the production today.This enables White Shark and Brujas to provide customers with the best,personalized carding solutions.White Shark and Brujas service 8700 clients in over 40 countries globally.The main products of the company include but not limited to:metallic card clothing,flat tops,stationary flat,circular comb,combing roller,cleaning fillet,raising fillet,flexible fillet etc.,and they are widely used in the areas of cotton spinning,non-woven materials,wool and linen spinning.展开更多
Reducing the risk of fraud in credit card transactions is crucial for the competitiveness of companies,especially in Latin American countries.This study aims to establish measures for preventing and detecting fraud in...Reducing the risk of fraud in credit card transactions is crucial for the competitiveness of companies,especially in Latin American countries.This study aims to establish measures for preventing and detecting fraud in the use of credit cards in shops through analytical methods(data mining,machine learning and artificial intelligence).To achieve this objective,the study employs a predictive methodology using descriptive and exploratory statistics and frequency,frequency&monetary(RFM)classification techniques,differentiating between SMEs and large businesses via cluster analysis and supervised models.A dataset of 221,292 card records from a Latin American merchant payment gateway for the year 2022 is used.For fraud alerts,the classification model has been selected for small and medium–sized merchants,and the multilayer perceptron(MLP)neural network has been selected for large merchants.Random forest or Gini decision tree models have been selected as backup models for retraining.For the detection of punctual fraud patterns,the K-means and partitioning around medoids(PAM)models have been selected,depending on the type of trade.The results revealed that the application of the identified models would have prevented between 48 and 85%of fraud transactions,depending on the trade size.Despite the promising results,continuous updating is recommended,as fraudsters frequently implement new fraud techniques.展开更多
胱天蛋白募集域蛋白9(caspase recruitment domain-containg protein 9,CARD9)是先天免疫系统中一种重要的信号转导分子,在抗真菌下游发挥着非常重要的作用。同时,随着研究的深入,学者们发现CARD9蛋白与多种免疫性疾病具有高度的相关性...胱天蛋白募集域蛋白9(caspase recruitment domain-containg protein 9,CARD9)是先天免疫系统中一种重要的信号转导分子,在抗真菌下游发挥着非常重要的作用。同时,随着研究的深入,学者们发现CARD9蛋白与多种免疫性疾病具有高度的相关性。CARD9存在着自抑制形态以及复杂的正、负调控途径,这些都影响着机体下游的免疫应答强度。因此,了解CARD9的调控途径至关重要。CARD9的激活途径在真菌识别的背景下,尤其是CLR通路中得到了最透彻的研究。该文总结了在C型凝集素受体-CARD9-NF-κB通路上,CARD9的自抑制形态的维持和解除,以及正、负调控途径如何影响CARD9的激活,以帮助更好地理解CARD9缺陷患者免疫系统异常反应的原理,从而促进CARD9缺陷患者获得更佳的治疗。展开更多
Digital twin can simulate and monitor the state and behavior of physical entities in the real world,helping enterprises to better understand and manage real-world physical systems,improve production efficiency,reduce ...Digital twin can simulate and monitor the state and behavior of physical entities in the real world,helping enterprises to better understand and manage real-world physical systems,improve production efficiency,reduce costs,and improve safety and reliability.In this paper,we use GTS motion control card and Unity engine to build a digital twin system,and control a virtual industrial automation handling platform including two screw servo axes and multiple sensors through the physical GTS motion control card.The control card program controls the motion of the virtual model through transmission control protocol(TCP)communication,and the virtual model system feeds back the signal to the control card program to achieve the virtual and real synchronous digital twin effect.The digital twin system uses Unity engine to create a highly realistic virtual environment,and can run on multi-platform terminals.展开更多
Credit card fraud is one of the primary sources of operational risk in banks,and accurate prediction of fraudulent credit card transactions is essential to minimize banks’economic losses.Two key issues are faced in c...Credit card fraud is one of the primary sources of operational risk in banks,and accurate prediction of fraudulent credit card transactions is essential to minimize banks’economic losses.Two key issues are faced in credit card fraud detection research,i.e.,data category imbalance and data drift.However,the oversampling algorithm used in current research suffers from excessive noise,and the Long Short-Term Memory Network(LSTM)based temporal model suffers from gradient dispersion,which can lead to loss of model performance.To address the above problems,a credit card fraud detection method based on Random Forest-Wasserstein Generative Adversarial NetworkTemporal Convolutional Network(RF-WGAN-TCN)is proposed.First,the credit card data is preprocessed,the feature importance scores are calculated by Random Forest(RF),the features with lower importance are eliminated,and then the remaining features are standardized.Second,the Wasserstein Distance Improvement Generative Adversarial Network(GAN)is introduced to construct the Wasserstein Generative Adversarial Network(WGAN),the preprocessed data is input into the WGAN,and under the mutual game training of generator and discriminator,the fraud samples that meet the target distribution are obtained.Finally,the temporal convolutional network(TCN)is utilized to extract the long-time dependencies,and the classification results are output through the Softmax layer.Experimental results on the European cardholder dataset show that the method proposed in the paper achieves 91.96%,98.22%,and 81.95%in F1-Score,Area Under Curve(AUC),and Area Under the Precision-Recall Curve(AUPRC)metrics,respectively,and has higher prediction accuracy and classification performance compared with existing mainstream methods.展开更多
基金supported by the National Research Foundation of Korea(NRF)funded by the Korea government(RS-2023-00249743)Additionally,this research was supported by the Global-Learning&Academic Research Institution for Master’s,PhD Students,and Postdocs(LAMP)Program of the National Research Foundation of Korea(NRF)grant funded by the Ministry of Education(RS-2024-00443714)This research was also supported by the“Research Base Construction Fund Support Program”funded by Jeonbuk National University in 2025.
文摘Traditional anomaly detection methods often assume that data points are independent or exhibit regularly structured relationships,as in Euclidean data such as time series or image grids.However,real-world data frequently involve irregular,interconnected structures,requiring a shift toward non-Euclidean approaches.This study introduces a novel anomaly detection framework designed to handle non-Euclidean data by modeling transactions as graph signals.By leveraging graph convolution filters,we extract meaningful connection strengths that capture relational dependencies often overlooked in traditional methods.Utilizing the Graph Convolutional Networks(GCN)framework,we integrate graph-based embeddings with conventional anomaly detection models,enhancing performance through relational insights.Ourmethod is validated on European credit card transaction data,demonstrating its effectiveness in detecting fraudulent transactions,particularly thosewith subtle patterns that evade traditional,amountbased detection techniques.The results highlight the advantages of incorporating temporal and structural dependencies into fraud detection,showcasing the robustness and applicability of our approach in complex,real-world scenarios.
文摘为解决C语言数据类型在支持后下载应用的片上操作系统(COS)中无法完全满足应用程序数据的存储特性和安全需求的问题,分析了Java Card和C语言数据类型的属性,提出了一种基于 C 语言扩展的应用程序数据类型体系。根据数据分类,重点阐述了4种模块数据类型和5种应用数据类型。测试结果表明,该数据类型体系满足了COS应用程序数据的需求,有效提升了内存利用率和应用执行性能,为COS虚拟机运行时环境提供了高效的数据模型。
文摘GERON Card Clothing(Jiangsu)Co.,Ltd.was founded in 1987 and is a professional textile carding equipment enterprise integrating research,production and sales.The production and sales of carding equipment have been leading the industry for many years.Our products include metallic card clothing,flat-top,stationary flat,circular comb and combing roller.Our brands include TYRION,Blue Diamond,Diamond,Pioneer and Lance.We provide customers with the most advanced carding solutions.
文摘Train Mass Rapid Transit(MRT)was put into service in 1987,and has since been augmented by and linked to the Light Rapid Transit.Combined,you can often get you within walking distance of most destinations.The maps on the metro system are easy to read,complete with English version.You can easily purchase an EZ-Link card or a NETS Flashpay Card(stored value cards)at all MRT stations and bus interchange.
文摘In the workshop of Guangshan White Shark Card Clothing Co.,Ltd.,precision machines are meticulously crafting the tips of card clothing with millimeter-level accuracy.These seemingly tiny textile accessories play a crucial role in the global cotton and chemical fiber industry chains.As China's textile industry encounters trade barriers in the process of globalization,this company specializing in card clothing manufacturing is striving to explore a differentiated path in overseas markets.
文摘Last Monday,on my way to school,I found a wallet on the ground.I picked up it①and opened it.There was some money,a student ID card and a few photos in it.I thought the owner must be very worried.
文摘Operating out of Shanghai,Brujas Textile Tech(Shanghai)Co.,Ltd.(“Brujas”)is a wholly owned subsidiary of Guangshan White Shark Card Clothing Co.,Ltd.(“White Shark”)tasked with providing international trade services to support its parent company's global operations.Whereas White Shark,as the parent company founded in 1962,is the manufacture facilities located in Xinyang,Henan Province.Brujas was founded in 1908 by the Brujas family in Terrassa,Spain.In 2008,White Shark integrated Brujas brand into its production and added European experience and knowledge that continues in the production today.This enables White Shark and Brujas to provide customers with the best,personalized carding solutions.White Shark and Brujas service 8700 clients in over 40 countries globally.The main products of the company include but not limited to:metallic card clothing,flat tops,stationary flat,circular comb,combing roller,cleaning fillet,raising fillet,flexible fillet etc.,and they are widely used in the areas of cotton spinning,non-woven materials,wool and linen spinning.
基金supported by project Finance for all(F4A),funded by the"Institución Gran Duque de Alba"and"Diputación provincial deávila"under the grant 3364/2022.
文摘Reducing the risk of fraud in credit card transactions is crucial for the competitiveness of companies,especially in Latin American countries.This study aims to establish measures for preventing and detecting fraud in the use of credit cards in shops through analytical methods(data mining,machine learning and artificial intelligence).To achieve this objective,the study employs a predictive methodology using descriptive and exploratory statistics and frequency,frequency&monetary(RFM)classification techniques,differentiating between SMEs and large businesses via cluster analysis and supervised models.A dataset of 221,292 card records from a Latin American merchant payment gateway for the year 2022 is used.For fraud alerts,the classification model has been selected for small and medium–sized merchants,and the multilayer perceptron(MLP)neural network has been selected for large merchants.Random forest or Gini decision tree models have been selected as backup models for retraining.For the detection of punctual fraud patterns,the K-means and partitioning around medoids(PAM)models have been selected,depending on the type of trade.The results revealed that the application of the identified models would have prevented between 48 and 85%of fraud transactions,depending on the trade size.Despite the promising results,continuous updating is recommended,as fraudsters frequently implement new fraud techniques.
文摘胱天蛋白募集域蛋白9(caspase recruitment domain-containg protein 9,CARD9)是先天免疫系统中一种重要的信号转导分子,在抗真菌下游发挥着非常重要的作用。同时,随着研究的深入,学者们发现CARD9蛋白与多种免疫性疾病具有高度的相关性。CARD9存在着自抑制形态以及复杂的正、负调控途径,这些都影响着机体下游的免疫应答强度。因此,了解CARD9的调控途径至关重要。CARD9的激活途径在真菌识别的背景下,尤其是CLR通路中得到了最透彻的研究。该文总结了在C型凝集素受体-CARD9-NF-κB通路上,CARD9的自抑制形态的维持和解除,以及正、负调控途径如何影响CARD9的激活,以帮助更好地理解CARD9缺陷患者免疫系统异常反应的原理,从而促进CARD9缺陷患者获得更佳的治疗。
基金Research Startup Project of Shenzhen Polytechnic University“Research and Development of High-Speed and High-Resolution 2D/3D Combined Vision Sensor”(Project No.6022312003K).
文摘Digital twin can simulate and monitor the state and behavior of physical entities in the real world,helping enterprises to better understand and manage real-world physical systems,improve production efficiency,reduce costs,and improve safety and reliability.In this paper,we use GTS motion control card and Unity engine to build a digital twin system,and control a virtual industrial automation handling platform including two screw servo axes and multiple sensors through the physical GTS motion control card.The control card program controls the motion of the virtual model through transmission control protocol(TCP)communication,and the virtual model system feeds back the signal to the control card program to achieve the virtual and real synchronous digital twin effect.The digital twin system uses Unity engine to create a highly realistic virtual environment,and can run on multi-platform terminals.
基金supported by the National Natural Science Foundation of China under Grant No.62466001the Talent Plan Project of Fuzhou City of Jiangxi Province of China under the Grant No.2021ED008+1 种基金the Opening Project of Jiangxi Key Laboratory of Cybersecurity Intelligent Perception under the Grant No.JKLCIP202202the Priority Unveiled Marshalling Project of Fuzhou City of Jiangxi Province of China under the Grant No.2023JBB026.
文摘Credit card fraud is one of the primary sources of operational risk in banks,and accurate prediction of fraudulent credit card transactions is essential to minimize banks’economic losses.Two key issues are faced in credit card fraud detection research,i.e.,data category imbalance and data drift.However,the oversampling algorithm used in current research suffers from excessive noise,and the Long Short-Term Memory Network(LSTM)based temporal model suffers from gradient dispersion,which can lead to loss of model performance.To address the above problems,a credit card fraud detection method based on Random Forest-Wasserstein Generative Adversarial NetworkTemporal Convolutional Network(RF-WGAN-TCN)is proposed.First,the credit card data is preprocessed,the feature importance scores are calculated by Random Forest(RF),the features with lower importance are eliminated,and then the remaining features are standardized.Second,the Wasserstein Distance Improvement Generative Adversarial Network(GAN)is introduced to construct the Wasserstein Generative Adversarial Network(WGAN),the preprocessed data is input into the WGAN,and under the mutual game training of generator and discriminator,the fraud samples that meet the target distribution are obtained.Finally,the temporal convolutional network(TCN)is utilized to extract the long-time dependencies,and the classification results are output through the Softmax layer.Experimental results on the European cardholder dataset show that the method proposed in the paper achieves 91.96%,98.22%,and 81.95%in F1-Score,Area Under Curve(AUC),and Area Under the Precision-Recall Curve(AUPRC)metrics,respectively,and has higher prediction accuracy and classification performance compared with existing mainstream methods.
