In the competitive retail industry of the digital era,data-driven insights into gender-specific customer behavior are essential.They support the optimization of store performance,layout design,product placement,and ta...In the competitive retail industry of the digital era,data-driven insights into gender-specific customer behavior are essential.They support the optimization of store performance,layout design,product placement,and targeted marketing.However,existing computer vision solutions often rely on facial recognition to gather such insights,raising significant privacy and ethical concerns.To address these issues,this paper presents a privacypreserving customer analytics system through two key strategies.First,we deploy a deep learning framework using YOLOv9s,trained on the RCA-TVGender dataset.Cameras are positioned perpendicular to observation areas to reduce facial visibility while maintaining accurate gender classification.Second,we apply AES-128 encryption to customer position data,ensuring secure access and regulatory compliance.Our system achieved overall performance,with 81.5%mAP@50,77.7%precision,and 75.7%recall.Moreover,a 90-min observational study confirmed the system’s ability to generate privacy-protected heatmaps revealing distinct behavioral patterns between male and female customers.For instance,women spent more time in certain areas and showed interest in different products.These results confirm the system’s effectiveness in enabling personalized layout and marketing strategies without compromising privacy.展开更多
RETRACTION:P.Goyal and R.Malviya,“Challenges and Opportunities of Big Data Analytics in Healthcare,”Health Care Science 2,no.5(2023):328-338,https://doi.org/10.1002/hcs2.66.The above article,published online on 4 Oc...RETRACTION:P.Goyal and R.Malviya,“Challenges and Opportunities of Big Data Analytics in Healthcare,”Health Care Science 2,no.5(2023):328-338,https://doi.org/10.1002/hcs2.66.The above article,published online on 4 October 2023 in Wiley Online Library(wileyonlinelibrary.com),has been retracted by agreement between the journal Editor-in-Chief,Zongjiu Zhang;Tsinghua University Press;and John Wiley&Sons Ltd.展开更多
This study evaluates the use of predictive analytics to forecast customer turnover in subscription-based Services in order to develop a predictive model to help small and medium-sized enterprises manage customer churn...This study evaluates the use of predictive analytics to forecast customer turnover in subscription-based Services in order to develop a predictive model to help small and medium-sized enterprises manage customer churn in the face of digital disruption.The research uses a quantitative approach focusing on empirical customer data to accurately predict buying trends and adapt marketing techniques.Demand forecasts in the health sector are important,as in every sector.In particular,the material forecast and stock forecasting of the purchasing unit of hospitals are among the areas that receive significant attention.Four classifiers(Random Forest,Logistic Regression,Gradient Boosting and XGBoost)are trained and evaluated using various performance indicators as part of a systematic approach involving Kaggle data collection,preparation and model selection.The results show excellent accuracy in predicting customer attrition,but there are limitations in precision and recall,indicating room for improvement.Confusion matrices provide information about the performance of each classifier,allowing for continuous improvement of predictive analytics techniques.Ethical concerns are rigorously addressed throughout the work process to guarantee appropriate data and machine learning methodologies.The proposals emphasize the proactive use of predictive analytics to identify at-risk customers and implement targeted retention strategies.Incorporating new data sources,improving customer experience,and utilizing collaborative churn management methods are recommended to increase forecast accuracy and business outcomes.Finally,this research provides important insights into the usefulness of predictive analytics for customer churn forecasting as well as practical recommendations for businesses seeking to increase customer retention and reduce churn risk.By leveraging empirical research findings and implementing ethical and rigorous churn control strategies,businesses can achieve long-term success in today’s changing market environment.展开更多
为了应对乌克兰持续不断的战争带来的严峻挑战,EOS Data Analytics推出了“收获希望”计划,该计划旨在关注席卷乌克兰农业部门的危机。这个综合网页设有一张交互式地图,展示了2021—2024年乌克兰主要作物的历史和预测产量。此外,该倡议...为了应对乌克兰持续不断的战争带来的严峻挑战,EOS Data Analytics推出了“收获希望”计划,该计划旨在关注席卷乌克兰农业部门的危机。这个综合网页设有一张交互式地图,展示了2021—2024年乌克兰主要作物的历史和预测产量。此外,该倡议还介绍了乌克兰农业的现状及其对全球粮食安全的影响。出于支持乌克兰农民的承诺,该公司将在2024年向他们免费提供EOSDA作物监测服务,作为“收获希望”计划的一部分。该平台将帮助农民克服逆境,并确保乌克兰农业部门的可持续未来。展开更多
The rapid development and increased installed capacity of new energy sources such as wind and solar power pose new challenges for power grid fault diagnosis.This paper presents an innovative framework,the Intelligent ...The rapid development and increased installed capacity of new energy sources such as wind and solar power pose new challenges for power grid fault diagnosis.This paper presents an innovative framework,the Intelligent Power Stability and Scheduling(IPSS)System,which is designed to enhance the safety,stability,and economic efficiency of power systems,particularly those integrated with green energy sources.The IPSS System is distinguished by its integration of a CNN-Transformer predictive model,which leverages the strengths of Convolutional Neural Networks(CNN)for local feature extraction and Transformer architecture for global dependency modeling,offering significant potential in power safety diagnostics.TheIPSS System optimizes the economic and stability objectives of the power grid through an improved Zebra Algorithm,which aims tominimize operational costs and grid instability.Theperformance of the predictive model is comprehensively evaluated using key metrics such as Root Mean Square Error(RMSE),Mean Absolute Percentage Error(MAPE),and Coefficient of Determination(R2).Experimental results demonstrate the superiority of the CNN-Transformer model,with the lowest RMSE and MAE values of 0.0063 and 0.00421,respectively,on the training set,and an R2 value approaching 1,at 0.99635,indicating minimal prediction error and strong data interpretability.On the test set,the model maintains its excellence with the lowest RMSE and MAE values of 0.009 and 0.00673,respectively,and an R2 value of 0.97233.The IPSS System outperforms other models in terms of prediction accuracy and explanatory power and validates its effectiveness in economic and stability analysis through comparative studies with other optimization algorithms.The system’s efficacy is further supported by experimental results,highlighting the proposed scheme’s capability to reduce operational costs and enhance system stability,making it a valuable contribution to the field of green energy systems.展开更多
Strong seismic excitation and fault dislocation are likely to occur simultaneously in high-intensity seismic zones,causing severe damage to tunnels crossing active fault zones.This paper aims to develop a novel analyt...Strong seismic excitation and fault dislocation are likely to occur simultaneously in high-intensity seismic zones,causing severe damage to tunnels crossing active fault zones.This paper aims to develop a novel analytical solution to determine the longitudinal mechanical responses of tunnels subjected to the combined effects of seismic waves and strike-slip faulting.Adopting the elastic springbeam model,the seismic waves are modelled as shear horizontal(SH)waves and the fault dislocation follows an S-shaped pattern;the superposition principle for free-fielddisplacements caused by both effects is assumed.In addition,the transmission and reflectionof seismic waves at the fault-rock geological interface and the tangential contact conditions at the tunnel-rock interface are considered.The analytical model is validated against numerical simulations,confirmingits accuracy in calculating tunnel responses.Moreover,a parametric study is conducted to evaluate the impact of key factors,including fault displacement,fault zone width,fault dip angle,earthquake frequency,rock conditions,tunnel lining stiffness,and tangential contact conditions,on tunnel responses.Compared with each effect alone,the combined effects of seismic waves and strike-slip faulting significantlychange the tunnel deformation and internal forces,leading to increased tunnel responses,especially within the fault zone and near the fault-rock interfaces.Depending on specificparameters,tunnel responses can be classifiedinto seismic-dominated,faulting-dominated,and seismic-faulting coupled responses on the basis of the relative contributions of each effect.The proposed analytical solution can be applied to quickly predict the longitudinal mechanical behaviour of tunnels under such combined effects in engineering applications.展开更多
Does traditional Chinese economic thought possess genuine analytical rigor?This question lies at the heart of any serious evaluation of its theoretical value and historical significance.It also matters for understandi...Does traditional Chinese economic thought possess genuine analytical rigor?This question lies at the heart of any serious evaluation of its theoretical value and historical significance.It also matters for understanding how best to preserve,build on its remarkable achievements,and develop its intellectual legacy.Critics such as Schumpeter and Taylor have long argued that the economic reasoning found in ancient China cannot compare with that of classical Greece or medieval Europe.Yet this view often reflects the narrow assumptions of mainstream economics,defining analysis almost entirely in terms of market exchange.As a result,it tends to overlook traditions built around statecraft,governance,and the management of economic order.A careful re-examination and Sino-Western comparative analysis of key thinkers-including Mencius,Guanzi,and Sima Qian-tells a different story.Rooted in China’s distinctive cultural and philosophical heritage,traditional Chinese economic thought not only contains the analytical dimensions(as defined by Schumpeter)but also displays a broader and more diverse set of economic reasoning.Notably,its systematic depth and intellectual precision were,in many respects,remarkably advanced.Therefore,advancing the construction of a Chinese school of economics in the new era under the framework of the“Second Integration”,i.e.,integrating the basic tenets of Marxism with China’s fine traditional culture,should,and indeed can draw essential insights from this analytical tradition.展开更多
Ganmai Dazao Decoction,originating from“Jin Gui Yao Lue”(Synopsis of the Golden Chamber),is a classical prescription for treating visceral agitation.Composed of three medicinal and edible substances-licorice(Gancao)...Ganmai Dazao Decoction,originating from“Jin Gui Yao Lue”(Synopsis of the Golden Chamber),is a classical prescription for treating visceral agitation.Composed of three medicinal and edible substances-licorice(Gancao),wheat(Xiaomai),and jujube(Dazao),it functions to nourish the heart and calm the mind,harmonize the middle burner and regulate Qi,and alleviate urgency and restlessness.As its clinical application has expanded from traditional emotional disorders to neurological,endocrine,and various psychosomatic diseases,establishing a scientifically precise quality control system and deeply elucidating its pharmacodynamic material basis and mechanism of action have become critical tasks.Modern analytical methods,typified by chromatography,spectroscopy,and their hyphenated techniques,with their high sensitivity,high resolution,and powerful substance characterization capabilities,have become the core driving force for standardizing the quality control and modernizing the clinical application research of this formula.This paper systematically reviews the progress of the aforementioned analytical techniques and chemometrics in interpreting the chemical composition,establishing fingerprint profiles,controlling process quality,and researching the pharmacodynamic material basis of Ganmai Dazao Decoction.Furthermore,it discusses integrated approaches combining analytical techniques with pharmacology and clinical medicine to reveal mechanisms of action and explore therapeutic biomarkers.Finally,it provides an outlook on future directions and challenges,including technological integration and innovation,standardization of whole-process quality control systems,and evidence-based research aimed at internationalization.展开更多
Rotational computed laminography(CL)has broad application potential in three-dimensional imaging of plate-like objects because it only requires X-rays to pass through the tested object in the thickness direction durin...Rotational computed laminography(CL)has broad application potential in three-dimensional imaging of plate-like objects because it only requires X-rays to pass through the tested object in the thickness direction during the imaging process.In this study,a rectangular cross-section field-of-view rotational CL(RC-CL)is proposed for circuit board imaging.Compared to other rotational CL systems,the field of view is the largest and most suitable for rectangular circuit boards.Meanwhile,as the imaging geometry of RC-CL is significantly different from that of cone-beam CT,the Feldkamp-Davis-Kress(FDK)reconstruction algorithm cannot be used directly.However,transferring the projection data to fit into the CBCT geometry using two-dimensional interpolation introduces interpolation errors.Therefore,an FDK-type analytical reconstruction algorithm applicable to RC-CL was developed.The effectiveness of the method was validated through numerical experiments,and the influence of the tilt angle on the reconstruction results was analyzed.Finally,the RC-CL technique was applied to real defect detection research on circuit boards.展开更多
This paper focuses on facilitating state-of-the-art applications of big data analytics(BDA) architectures and infrastructures to telecommunications(telecom) industrial sector.Telecom companies are dealing with terabyt...This paper focuses on facilitating state-of-the-art applications of big data analytics(BDA) architectures and infrastructures to telecommunications(telecom) industrial sector.Telecom companies are dealing with terabytes to petabytes of data on a daily basis. Io T applications in telecom are further contributing to this data deluge. Recent advances in BDA have exposed new opportunities to get actionable insights from telecom big data. These benefits and the fast-changing BDA technology landscape make it important to investigate existing BDA applications to telecom sector. For this, we initially determine published research on BDA applications to telecom through a systematic literature review through which we filter 38 articles and categorize them in frameworks, use cases, literature reviews, white papers and experimental validations. We also discuss the benefits and challenges mentioned in these articles. We find that experiments are all proof of concepts(POC) on a severely limited BDA technology stack(as compared to the available technology stack), i.e.,we did not find any work focusing on full-fledged BDA implementation in an operational telecom environment. To facilitate these applications at research-level, we propose a state-of-the-art lambda architecture for BDA pipeline implementation(called Lambda Tel) based completely on open source BDA technologies and the standard Python language, along with relevant guidelines.We discovered only one research paper which presented a relatively-limited lambda architecture using the proprietary AWS cloud infrastructure. We believe Lambda Tel presents a clear roadmap for telecom industry practitioners to implement and enhance BDA applications in their enterprises.展开更多
文摘In the competitive retail industry of the digital era,data-driven insights into gender-specific customer behavior are essential.They support the optimization of store performance,layout design,product placement,and targeted marketing.However,existing computer vision solutions often rely on facial recognition to gather such insights,raising significant privacy and ethical concerns.To address these issues,this paper presents a privacypreserving customer analytics system through two key strategies.First,we deploy a deep learning framework using YOLOv9s,trained on the RCA-TVGender dataset.Cameras are positioned perpendicular to observation areas to reduce facial visibility while maintaining accurate gender classification.Second,we apply AES-128 encryption to customer position data,ensuring secure access and regulatory compliance.Our system achieved overall performance,with 81.5%mAP@50,77.7%precision,and 75.7%recall.Moreover,a 90-min observational study confirmed the system’s ability to generate privacy-protected heatmaps revealing distinct behavioral patterns between male and female customers.For instance,women spent more time in certain areas and showed interest in different products.These results confirm the system’s effectiveness in enabling personalized layout and marketing strategies without compromising privacy.
文摘RETRACTION:P.Goyal and R.Malviya,“Challenges and Opportunities of Big Data Analytics in Healthcare,”Health Care Science 2,no.5(2023):328-338,https://doi.org/10.1002/hcs2.66.The above article,published online on 4 October 2023 in Wiley Online Library(wileyonlinelibrary.com),has been retracted by agreement between the journal Editor-in-Chief,Zongjiu Zhang;Tsinghua University Press;and John Wiley&Sons Ltd.
文摘This study evaluates the use of predictive analytics to forecast customer turnover in subscription-based Services in order to develop a predictive model to help small and medium-sized enterprises manage customer churn in the face of digital disruption.The research uses a quantitative approach focusing on empirical customer data to accurately predict buying trends and adapt marketing techniques.Demand forecasts in the health sector are important,as in every sector.In particular,the material forecast and stock forecasting of the purchasing unit of hospitals are among the areas that receive significant attention.Four classifiers(Random Forest,Logistic Regression,Gradient Boosting and XGBoost)are trained and evaluated using various performance indicators as part of a systematic approach involving Kaggle data collection,preparation and model selection.The results show excellent accuracy in predicting customer attrition,but there are limitations in precision and recall,indicating room for improvement.Confusion matrices provide information about the performance of each classifier,allowing for continuous improvement of predictive analytics techniques.Ethical concerns are rigorously addressed throughout the work process to guarantee appropriate data and machine learning methodologies.The proposals emphasize the proactive use of predictive analytics to identify at-risk customers and implement targeted retention strategies.Incorporating new data sources,improving customer experience,and utilizing collaborative churn management methods are recommended to increase forecast accuracy and business outcomes.Finally,this research provides important insights into the usefulness of predictive analytics for customer churn forecasting as well as practical recommendations for businesses seeking to increase customer retention and reduce churn risk.By leveraging empirical research findings and implementing ethical and rigorous churn control strategies,businesses can achieve long-term success in today’s changing market environment.
文摘为了应对乌克兰持续不断的战争带来的严峻挑战,EOS Data Analytics推出了“收获希望”计划,该计划旨在关注席卷乌克兰农业部门的危机。这个综合网页设有一张交互式地图,展示了2021—2024年乌克兰主要作物的历史和预测产量。此外,该倡议还介绍了乌克兰农业的现状及其对全球粮食安全的影响。出于支持乌克兰农民的承诺,该公司将在2024年向他们免费提供EOSDA作物监测服务,作为“收获希望”计划的一部分。该平台将帮助农民克服逆境,并确保乌克兰农业部门的可持续未来。
基金The research project,“Research on Power Safety Assisted Decision System Based on Large Language Models”(Project Number:JSDL24051414020001)acknowledges with gratitude the financial and logistical support it has received.
文摘The rapid development and increased installed capacity of new energy sources such as wind and solar power pose new challenges for power grid fault diagnosis.This paper presents an innovative framework,the Intelligent Power Stability and Scheduling(IPSS)System,which is designed to enhance the safety,stability,and economic efficiency of power systems,particularly those integrated with green energy sources.The IPSS System is distinguished by its integration of a CNN-Transformer predictive model,which leverages the strengths of Convolutional Neural Networks(CNN)for local feature extraction and Transformer architecture for global dependency modeling,offering significant potential in power safety diagnostics.TheIPSS System optimizes the economic and stability objectives of the power grid through an improved Zebra Algorithm,which aims tominimize operational costs and grid instability.Theperformance of the predictive model is comprehensively evaluated using key metrics such as Root Mean Square Error(RMSE),Mean Absolute Percentage Error(MAPE),and Coefficient of Determination(R2).Experimental results demonstrate the superiority of the CNN-Transformer model,with the lowest RMSE and MAE values of 0.0063 and 0.00421,respectively,on the training set,and an R2 value approaching 1,at 0.99635,indicating minimal prediction error and strong data interpretability.On the test set,the model maintains its excellence with the lowest RMSE and MAE values of 0.009 and 0.00673,respectively,and an R2 value of 0.97233.The IPSS System outperforms other models in terms of prediction accuracy and explanatory power and validates its effectiveness in economic and stability analysis through comparative studies with other optimization algorithms.The system’s efficacy is further supported by experimental results,highlighting the proposed scheme’s capability to reduce operational costs and enhance system stability,making it a valuable contribution to the field of green energy systems.
基金supported by the National Natural Science Foundation of China(No.41941018)Shanghai Gaofeng Discipline Construction Funding.
文摘Strong seismic excitation and fault dislocation are likely to occur simultaneously in high-intensity seismic zones,causing severe damage to tunnels crossing active fault zones.This paper aims to develop a novel analytical solution to determine the longitudinal mechanical responses of tunnels subjected to the combined effects of seismic waves and strike-slip faulting.Adopting the elastic springbeam model,the seismic waves are modelled as shear horizontal(SH)waves and the fault dislocation follows an S-shaped pattern;the superposition principle for free-fielddisplacements caused by both effects is assumed.In addition,the transmission and reflectionof seismic waves at the fault-rock geological interface and the tangential contact conditions at the tunnel-rock interface are considered.The analytical model is validated against numerical simulations,confirmingits accuracy in calculating tunnel responses.Moreover,a parametric study is conducted to evaluate the impact of key factors,including fault displacement,fault zone width,fault dip angle,earthquake frequency,rock conditions,tunnel lining stiffness,and tangential contact conditions,on tunnel responses.Compared with each effect alone,the combined effects of seismic waves and strike-slip faulting significantlychange the tunnel deformation and internal forces,leading to increased tunnel responses,especially within the fault zone and near the fault-rock interfaces.Depending on specificparameters,tunnel responses can be classifiedinto seismic-dominated,faulting-dominated,and seismic-faulting coupled responses on the basis of the relative contributions of each effect.The proposed analytical solution can be applied to quickly predict the longitudinal mechanical behaviour of tunnels under such combined effects in engineering applications.
基金supported by the National Social Science Fund of China(NSSFC):NSSFC Major Project“Exploration and Practice in the Development of Chinese Economics Since the Modern Era”(Grant No.17ZDA034)NSSFC Key Project“The Status and Value of Traditional Chinese Economic Thought”(Grant No.17AJL006)NSSFC General Project“The Transformation and Evolution of Chinese Economic Thought During the Republican Era”(Grant No.22BJL130).
文摘Does traditional Chinese economic thought possess genuine analytical rigor?This question lies at the heart of any serious evaluation of its theoretical value and historical significance.It also matters for understanding how best to preserve,build on its remarkable achievements,and develop its intellectual legacy.Critics such as Schumpeter and Taylor have long argued that the economic reasoning found in ancient China cannot compare with that of classical Greece or medieval Europe.Yet this view often reflects the narrow assumptions of mainstream economics,defining analysis almost entirely in terms of market exchange.As a result,it tends to overlook traditions built around statecraft,governance,and the management of economic order.A careful re-examination and Sino-Western comparative analysis of key thinkers-including Mencius,Guanzi,and Sima Qian-tells a different story.Rooted in China’s distinctive cultural and philosophical heritage,traditional Chinese economic thought not only contains the analytical dimensions(as defined by Schumpeter)but also displays a broader and more diverse set of economic reasoning.Notably,its systematic depth and intellectual precision were,in many respects,remarkably advanced.Therefore,advancing the construction of a Chinese school of economics in the new era under the framework of the“Second Integration”,i.e.,integrating the basic tenets of Marxism with China’s fine traditional culture,should,and indeed can draw essential insights from this analytical tradition.
文摘Ganmai Dazao Decoction,originating from“Jin Gui Yao Lue”(Synopsis of the Golden Chamber),is a classical prescription for treating visceral agitation.Composed of three medicinal and edible substances-licorice(Gancao),wheat(Xiaomai),and jujube(Dazao),it functions to nourish the heart and calm the mind,harmonize the middle burner and regulate Qi,and alleviate urgency and restlessness.As its clinical application has expanded from traditional emotional disorders to neurological,endocrine,and various psychosomatic diseases,establishing a scientifically precise quality control system and deeply elucidating its pharmacodynamic material basis and mechanism of action have become critical tasks.Modern analytical methods,typified by chromatography,spectroscopy,and their hyphenated techniques,with their high sensitivity,high resolution,and powerful substance characterization capabilities,have become the core driving force for standardizing the quality control and modernizing the clinical application research of this formula.This paper systematically reviews the progress of the aforementioned analytical techniques and chemometrics in interpreting the chemical composition,establishing fingerprint profiles,controlling process quality,and researching the pharmacodynamic material basis of Ganmai Dazao Decoction.Furthermore,it discusses integrated approaches combining analytical techniques with pharmacology and clinical medicine to reveal mechanisms of action and explore therapeutic biomarkers.Finally,it provides an outlook on future directions and challenges,including technological integration and innovation,standardization of whole-process quality control systems,and evidence-based research aimed at internationalization.
基金supported by the National Key Research and Development Program of China(No.2022YFF0607802)。
文摘Rotational computed laminography(CL)has broad application potential in three-dimensional imaging of plate-like objects because it only requires X-rays to pass through the tested object in the thickness direction during the imaging process.In this study,a rectangular cross-section field-of-view rotational CL(RC-CL)is proposed for circuit board imaging.Compared to other rotational CL systems,the field of view is the largest and most suitable for rectangular circuit boards.Meanwhile,as the imaging geometry of RC-CL is significantly different from that of cone-beam CT,the Feldkamp-Davis-Kress(FDK)reconstruction algorithm cannot be used directly.However,transferring the projection data to fit into the CBCT geometry using two-dimensional interpolation introduces interpolation errors.Therefore,an FDK-type analytical reconstruction algorithm applicable to RC-CL was developed.The effectiveness of the method was validated through numerical experiments,and the influence of the tilt angle on the reconstruction results was analyzed.Finally,the RC-CL technique was applied to real defect detection research on circuit boards.
基金supported in part by the Big Data Analytics Laboratory(BDALAB)at the Institute of Business Administration under the research grant approved by the Higher Education Commission of Pakistan(www.hec.gov.pk)the Darbi company(www.darbi.io)
文摘This paper focuses on facilitating state-of-the-art applications of big data analytics(BDA) architectures and infrastructures to telecommunications(telecom) industrial sector.Telecom companies are dealing with terabytes to petabytes of data on a daily basis. Io T applications in telecom are further contributing to this data deluge. Recent advances in BDA have exposed new opportunities to get actionable insights from telecom big data. These benefits and the fast-changing BDA technology landscape make it important to investigate existing BDA applications to telecom sector. For this, we initially determine published research on BDA applications to telecom through a systematic literature review through which we filter 38 articles and categorize them in frameworks, use cases, literature reviews, white papers and experimental validations. We also discuss the benefits and challenges mentioned in these articles. We find that experiments are all proof of concepts(POC) on a severely limited BDA technology stack(as compared to the available technology stack), i.e.,we did not find any work focusing on full-fledged BDA implementation in an operational telecom environment. To facilitate these applications at research-level, we propose a state-of-the-art lambda architecture for BDA pipeline implementation(called Lambda Tel) based completely on open source BDA technologies and the standard Python language, along with relevant guidelines.We discovered only one research paper which presented a relatively-limited lambda architecture using the proprietary AWS cloud infrastructure. We believe Lambda Tel presents a clear roadmap for telecom industry practitioners to implement and enhance BDA applications in their enterprises.
