安全开发生命周期（SDL，Security Development Lifecycle）的目标有两个：减少安全相关的设计和编码缺陷的数量，降低缺陷的严重性。SDL主要专注于这三个原则的前两项。设计安全意味着从一开始就保证设计和代码是安全的，默认安全是您...安全开发生命周期（SDL，Security Development Lifecycle）的目标有两个：减少安全相关的设计和编码缺陷的数量，降低缺陷的严重性。SDL主要专注于这三个原则的前两项。设计安全意味着从一开始就保证设计和代码是安全的，默认安全是您永远不会重视的。实际上，不可能写出百分之百正确的代码，关于此话题的更多内容见稍后对减少受攻击面的讨论。展开更多
Aqueous Zn batteries are promising candidates for grid-scale renewable energy storage.Foil electrodes have been widely investigated and applied as anode materials for aqueous Zn batteries,however,they suffer from limi...Aqueous Zn batteries are promising candidates for grid-scale renewable energy storage.Foil electrodes have been widely investigated and applied as anode materials for aqueous Zn batteries,however,they suffer from limited surface area and severe interfacial issues including metallic dendrites and corrosion side reactions,limiting the depth of discharge(DOD)of the foil electrode materials.Herein,a low-temperature replacement reaction is utilized to in-situ construct a three-dimensional(3D)corrosion-resistant interface for deeply rechargeable Zn foil electrodes.Specifically,the deliberate low-temperature environment controlled the replacement rate between polycrystalline Zn metal and oxalic acid,producing a Zn foil electrode with distinct 3D corrosion-resistant interface(3DCI-Zn),which differed from conventional two-dimensional(2D)protective structure and showed an order of magnitude higher surface area.Consequently,the 3DCI-Zn electrode exhibited dendrite-free and anticorrosion properties,and achieved stable plating/stripping performance for 1000 h at 10 mA cm^(-2)and 10 mAh cm^(-2)with a remarkable DOD of 79%.After pairing with a MnO2cathode with a high areal capacity of 4.2 mAh cm^(-2),the pouch cells delivered 168 Wh L^(-1)and a capacity retention of 89.7%after 100 cycles with a low negative/positive(N/P)ratio of 3:1.展开更多
The purpose of the research was to assess the impact of Citizen Development activities on digital transformation. The research identified eight categories that contribute to the success of Low-code No-code (LCNC) proj...The purpose of the research was to assess the impact of Citizen Development activities on digital transformation. The research identified eight categories that contribute to the success of Low-code No-code (LCNC) projects: 1) Strategy;2) Infrastructure;3) Technology;4) Processes & Procedures;5) Governance;6) Culture;7) People;8) Goals & Metrics and selected six critical success factors from these categories: 1) Operational Efficiency;2) Time Savings;3) Timeframe to Realize Value;4) Employee Engagement;5) Participation;6) Number of Sponsored Ideas. End users of the digital transformation efforts through Citizen Development were asked to assess the six critical success measures in terms of performance and importance criteria. The research results identified that focus should be applied to improving “Timeframe to Realize Value”, on “Operational Efficiency”, and on “Time Savings” to deliver success.展开更多
The research aims to explore the transition from monolithic Digital Experience Platforms (DXPs) to Microservices-based DXPs, addressing scalability challenges. The study systematically decomposes monolithic structures...The research aims to explore the transition from monolithic Digital Experience Platforms (DXPs) to Microservices-based DXPs, addressing scalability challenges. The study systematically decomposes monolithic structures into Microservices, emphasizing business capability and subdomain decomposition. Concrete insights, challenges, and solutions encountered during this transformation process are presented. The research contributes valuable insights into the challenges and benefits of adopting Microservices in DXPs. Results highlight the importance of architectural patterns and strategic scaling dimensions for improved performance and scalability. The case study on Backbase’s Engagement Banking Platform showcases successful implementation, providing flexibility, integration, and efficient development in the evolving DXP landscape.展开更多
Data storage solutions are a crucial aspect of any application, significantly impacting data management and system performance. This article explores the rationale behind utilizing both SQL and NoSQL databases, addres...Data storage solutions are a crucial aspect of any application, significantly impacting data management and system performance. This article explores the rationale behind utilizing both SQL and NoSQL databases, addressing key questions about when each type is preferable. The background emphasizes the importance of selecting the appropriate database technology to meet specific application requirements. The purpose of this research is to provide a comprehensive guide for choosing between SQL and NoSQL databases based on various factors, including workload characteristics, scalability needs, and consistency requirements. To achieve this, we examine different strategies for implementing SQL and NoSQL databases in large-scale distributed applications and systems. The research method involves a comparative analysis of the features, advantages, and limitations of both database types. We specifically focus on scenarios involving read-heavy versus write-heavy systems and the trade-offs between availability and consistency. The results of this research indicate that SQL databases, with their relational structure and ACID compliance, are ideal for applications requiring complex queries and data integrity. In contrast, NoSQL databases, offering schema flexibility and horizontal scalability, are better suited for managing extensive datasets and high-velocity data ingestion. In conclusion, the selection of a database depends on the specific needs of the application. SQL databases are preferred for transactional systems with complex relationships, while NoSQL databases excel in scenarios demanding flexibility and scalability. The study provides insights into hybrid approaches, leveraging both database types to optimize system performance.展开更多
Knowlege is important for text-related applications.In this paper,we introduce Microsoft Concept Graph,a knowledge graph engine that provides concept tagging APIs to facilitate the understanding of human languages.Mic...Knowlege is important for text-related applications.In this paper,we introduce Microsoft Concept Graph,a knowledge graph engine that provides concept tagging APIs to facilitate the understanding of human languages.Microsoft Concept Graph is built upon Probase,a universal probabilistic taxonomy consisting of instances and concepts mined from the Web.We start by introducing the construction of the knowledge graph through iterative semantic extraction and taxonomy construction procedures,which extract 2.7 million concepts from 1.68 billion Web pages.We then use conceptualization models to represent text in the concept space to empower text-related applications,such as topic search,query recommendation,Web table understanding and Ads relevance.Since the release in 2016,Microsoft Concept Graph has received more than 100,000 pageviews,2 million API calls and 3,000 registered downloads from 50,000 visitors over 64 countries.展开更多
探讨了以大语言模型(large language model,LLM)为代表的大模型(big model)时代人工智能(artificial intelligence,AI)发展面临的新挑战:道德价值观对齐问题.大模型的崛起极大地提升了AI理解、生成和控制信息与内容的能力,从而赋能了丰...探讨了以大语言模型(large language model,LLM)为代表的大模型(big model)时代人工智能(artificial intelligence,AI)发展面临的新挑战:道德价值观对齐问题.大模型的崛起极大地提升了AI理解、生成和控制信息与内容的能力,从而赋能了丰富的下游应用.然而,随着大模型成为与人类生活方方面面深度交融的基础,其内在的道德价值观和潜在的价值倾向对人类社会带来不可预测的风险.首先对大模型面临的风险和挑战进行了梳理,介绍了当下主流的AI伦理准则和大模型的局限性对应的道德问题.随后提出从规范伦理学的角度重新审视近年来不断提出的各类规范性准则,并倡导学界共同协作构建统一的普适性AI道德框架.为进一步探究大模型的道德倾向,基于道德基础理论体系,检验了当下主流大语言模型的道德价值倾向,梳理了现有的大模型对齐算法,总结了大模型在道德价值观对齐上所面临的独特挑战.为解决这些挑战,提出了一种新的针对大模型道德价值观对齐的概念范式,从对齐维度、对齐评测和对齐方法3个方面展望了有潜力的研究方向.最后,倡导以交叉学科为基础,为将来构建符合人类道德观的通用AI迈出了重要一步.展开更多
文摘安全开发生命周期（SDL，Security Development Lifecycle）的目标有两个：减少安全相关的设计和编码缺陷的数量，降低缺陷的严重性。SDL主要专注于这三个原则的前两项。设计安全意味着从一开始就保证设计和代码是安全的，默认安全是您永远不会重视的。实际上，不可能写出百分之百正确的代码，关于此话题的更多内容见稍后对减少受攻击面的讨论。
基金financially supported by the National Natural Science Foundation of China (No.22205068,22109144)the“CUG Scholar”Scientific Research Funds at China University of Geosciences (Wuhan) (Project No.2022118)the Fundamental Research Funds for the Central Universities,China University of Geosciences (Wuhan) (No.162301202673)。
文摘Aqueous Zn batteries are promising candidates for grid-scale renewable energy storage.Foil electrodes have been widely investigated and applied as anode materials for aqueous Zn batteries,however,they suffer from limited surface area and severe interfacial issues including metallic dendrites and corrosion side reactions,limiting the depth of discharge(DOD)of the foil electrode materials.Herein,a low-temperature replacement reaction is utilized to in-situ construct a three-dimensional(3D)corrosion-resistant interface for deeply rechargeable Zn foil electrodes.Specifically,the deliberate low-temperature environment controlled the replacement rate between polycrystalline Zn metal and oxalic acid,producing a Zn foil electrode with distinct 3D corrosion-resistant interface(3DCI-Zn),which differed from conventional two-dimensional(2D)protective structure and showed an order of magnitude higher surface area.Consequently,the 3DCI-Zn electrode exhibited dendrite-free and anticorrosion properties,and achieved stable plating/stripping performance for 1000 h at 10 mA cm^(-2)and 10 mAh cm^(-2)with a remarkable DOD of 79%.After pairing with a MnO2cathode with a high areal capacity of 4.2 mAh cm^(-2),the pouch cells delivered 168 Wh L^(-1)and a capacity retention of 89.7%after 100 cycles with a low negative/positive(N/P)ratio of 3:1.
文摘The purpose of the research was to assess the impact of Citizen Development activities on digital transformation. The research identified eight categories that contribute to the success of Low-code No-code (LCNC) projects: 1) Strategy;2) Infrastructure;3) Technology;4) Processes & Procedures;5) Governance;6) Culture;7) People;8) Goals & Metrics and selected six critical success factors from these categories: 1) Operational Efficiency;2) Time Savings;3) Timeframe to Realize Value;4) Employee Engagement;5) Participation;6) Number of Sponsored Ideas. End users of the digital transformation efforts through Citizen Development were asked to assess the six critical success measures in terms of performance and importance criteria. The research results identified that focus should be applied to improving “Timeframe to Realize Value”, on “Operational Efficiency”, and on “Time Savings” to deliver success.
文摘The research aims to explore the transition from monolithic Digital Experience Platforms (DXPs) to Microservices-based DXPs, addressing scalability challenges. The study systematically decomposes monolithic structures into Microservices, emphasizing business capability and subdomain decomposition. Concrete insights, challenges, and solutions encountered during this transformation process are presented. The research contributes valuable insights into the challenges and benefits of adopting Microservices in DXPs. Results highlight the importance of architectural patterns and strategic scaling dimensions for improved performance and scalability. The case study on Backbase’s Engagement Banking Platform showcases successful implementation, providing flexibility, integration, and efficient development in the evolving DXP landscape.
文摘Data storage solutions are a crucial aspect of any application, significantly impacting data management and system performance. This article explores the rationale behind utilizing both SQL and NoSQL databases, addressing key questions about when each type is preferable. The background emphasizes the importance of selecting the appropriate database technology to meet specific application requirements. The purpose of this research is to provide a comprehensive guide for choosing between SQL and NoSQL databases based on various factors, including workload characteristics, scalability needs, and consistency requirements. To achieve this, we examine different strategies for implementing SQL and NoSQL databases in large-scale distributed applications and systems. The research method involves a comparative analysis of the features, advantages, and limitations of both database types. We specifically focus on scenarios involving read-heavy versus write-heavy systems and the trade-offs between availability and consistency. The results of this research indicate that SQL databases, with their relational structure and ACID compliance, are ideal for applications requiring complex queries and data integrity. In contrast, NoSQL databases, offering schema flexibility and horizontal scalability, are better suited for managing extensive datasets and high-velocity data ingestion. In conclusion, the selection of a database depends on the specific needs of the application. SQL databases are preferred for transactional systems with complex relationships, while NoSQL databases excel in scenarios demanding flexibility and scalability. The study provides insights into hybrid approaches, leveraging both database types to optimize system performance.
文摘Knowlege is important for text-related applications.In this paper,we introduce Microsoft Concept Graph,a knowledge graph engine that provides concept tagging APIs to facilitate the understanding of human languages.Microsoft Concept Graph is built upon Probase,a universal probabilistic taxonomy consisting of instances and concepts mined from the Web.We start by introducing the construction of the knowledge graph through iterative semantic extraction and taxonomy construction procedures,which extract 2.7 million concepts from 1.68 billion Web pages.We then use conceptualization models to represent text in the concept space to empower text-related applications,such as topic search,query recommendation,Web table understanding and Ads relevance.Since the release in 2016,Microsoft Concept Graph has received more than 100,000 pageviews,2 million API calls and 3,000 registered downloads from 50,000 visitors over 64 countries.
文摘探讨了以大语言模型(large language model,LLM)为代表的大模型(big model)时代人工智能(artificial intelligence,AI)发展面临的新挑战:道德价值观对齐问题.大模型的崛起极大地提升了AI理解、生成和控制信息与内容的能力,从而赋能了丰富的下游应用.然而,随着大模型成为与人类生活方方面面深度交融的基础,其内在的道德价值观和潜在的价值倾向对人类社会带来不可预测的风险.首先对大模型面临的风险和挑战进行了梳理,介绍了当下主流的AI伦理准则和大模型的局限性对应的道德问题.随后提出从规范伦理学的角度重新审视近年来不断提出的各类规范性准则,并倡导学界共同协作构建统一的普适性AI道德框架.为进一步探究大模型的道德倾向,基于道德基础理论体系,检验了当下主流大语言模型的道德价值倾向,梳理了现有的大模型对齐算法,总结了大模型在道德价值观对齐上所面临的独特挑战.为解决这些挑战,提出了一种新的针对大模型道德价值观对齐的概念范式,从对齐维度、对齐评测和对齐方法3个方面展望了有潜力的研究方向.最后,倡导以交叉学科为基础,为将来构建符合人类道德观的通用AI迈出了重要一步.
