This paper proposes a novel hybrid fraud detection framework that integrates multi-stage feature selection,unsupervised clustering,and ensemble learning to improve classification performance in financial transaction m...This paper proposes a novel hybrid fraud detection framework that integrates multi-stage feature selection,unsupervised clustering,and ensemble learning to improve classification performance in financial transaction monitoring systems.The framework is structured into three core layers:(1)feature selection using Recursive Feature Elimination(RFE),Principal Component Analysis(PCA),and Mutual Information(MI)to reduce dimensionality and enhance input relevance;(2)anomaly detection through unsupervised clustering using K-Means,Density-Based Spatial Clustering(DBSCAN),and Hierarchical Clustering to flag suspicious patterns in unlabeled data;and(3)final classification using a voting-based hybrid ensemble of Support Vector Machine(SVM),Random Forest(RF),and Gradient Boosting Classifier(GBC).The experimental evaluation is conducted on a synthetically generated dataset comprising one million financial transactions,with 5% labelled as fraudulent,simulating realistic fraud rates and behavioural features,including transaction time,origin,amount,and geo-location.The proposed model demonstrated a significant improvement over baseline classifiers,achieving an accuracy of 99%,a precision of 99%,a recall of 97%,and an F1-score of 99%.Compared to individual models,it yielded a 9% gain in overall detection accuracy.It reduced the false positive rate to below 3.5%,thereby minimising the operational costs associated with manually reviewing false alerts.The model’s interpretability is enhanced by the integration of Shapley Additive Explanations(SHAP)values for feature importance,supporting transparency and regulatory auditability.These results affirm the practical relevance of the proposed system for deployment in real-time fraud detection scenarios such as credit card transactions,mobile banking,and cross-border payments.The study also highlights future directions,including the deployment of lightweight models and the integration of multimodal data for scalable fraud analytics.展开更多
In the evolving landscape of software engineering, Microservice Architecture (MSA) has emerged as a transformative approach, facilitating enhanced scalability, agility, and independent service deployment. This systema...In the evolving landscape of software engineering, Microservice Architecture (MSA) has emerged as a transformative approach, facilitating enhanced scalability, agility, and independent service deployment. This systematic literature review (SLR) explores the current state of distributed transaction management within MSA, focusing on the unique challenges, strategies, and technologies utilized in this domain. By synthesizing findings from 16 primary studies selected based on rigorous criteria, the review identifies key trends and best practices for maintaining data consistency and integrity across microservices. This SLR provides a comprehensive understanding of the complexities associated with distributed transactions in MSA, offering actionable insights and potential research directions for software architects, developers, and researchers.展开更多
Since its inception in 2009,Bitcoin has become and is currently the most successful and widely used cryptocurrency.It introduced blockchain technology,which allows transactions that transfer funds between users to tak...Since its inception in 2009,Bitcoin has become and is currently the most successful and widely used cryptocurrency.It introduced blockchain technology,which allows transactions that transfer funds between users to take place online,in an immutable manner.No real-world identities are needed or stored in the blockchain.At the same time,all transactions are publicly available and auditable,making Bitcoin a pseudo-anonymous ledger of transactions.The volume of transactions that are broadcast on a daily basis is considerably large.We propose a set of features that can be extracted from transaction data.Using this,we apply a data processing pipeline to ultimately cluster transactions via a k-means clustering algorithm,according to the transaction properties.Finally,according to these properties,we are able to characterize these clusters and the transactions they include.Our work mainly differentiates from previous studies in that it applies an unsupervised learning method to cluster transactions instead of addresses.Using the novel features we introduce,our work classifies transactions in multiple clusters,while previous studies only attempt binary classification.Results indicate that most transactions fall into a cluster that can be described as common user transactions.Other clusters include transactions made by online exchanges and lending services,those relating to mining activities as well as smaller clusters,one of which contains possibly illicit or fraudulent transactions.We evaluated our results against an online database of addresses that belong to known actors,such as online exchanges,and found that our results generally agree with them,which enhances the validity of our methods.展开更多
Foreign-funded overseas industrial parks(OIPs)are crucial for attracting foreign investment and promoting globalization in developing countries.However,large-scale land acquisition for these parks generates conflicts ...Foreign-funded overseas industrial parks(OIPs)are crucial for attracting foreign investment and promoting globalization in developing countries.However,large-scale land acquisition for these parks generates conflicts between developers and local stakeholders,increasing development costs.A qualitative multicase study was conducted in this study to analyze the land transaction trajectories of China's OIPs.Four OIPs were selected to reveal the underlying mechanisms from the perspectives of institutional arrangements,governance mechanisms,and enterprise heterogeneity.The findings indicate that in host countries with insufficient institutional development,local governments are more inclined to directly engage in OIP land acquisition.High-level intergovernmental mechanisms facilitate land acquisition processes,although their efficacy depends largely on administrative power allocation across parks in host countries.The results also indicate that enterprise characteristics significantly influence land acquisition,where microscale private enterprises lacking political connections often employ low-cost,bottom-up strategies by leveraging international experience.In summary,policy-makers in developing countries should prioritize enhancing OIP governance to mitigate transaction costs,promote diversified land supply,and optimize land allocation.By depicting China's OIP land acquisition processes,this study deepens the academic understanding of OIP governance in developing countries and related international land transactions,offering practical OIP management insights for governments in both host and parent countries.展开更多
The rapid growth of blockchain and Decentralized Finance(DeFi)has introduced new challenges and vulnerabilities that threaten the integrity and efficiency of the ecosystem.This study identifies critical issues such as...The rapid growth of blockchain and Decentralized Finance(DeFi)has introduced new challenges and vulnerabilities that threaten the integrity and efficiency of the ecosystem.This study identifies critical issues such as Transaction Order Dependence(TOD),Blockchain Extractable Value(BEV),and Transaction Importance Diversity(TID),which collectively undermine the fairness and security of DeFi systems.BEV-related activities,including sandwich attacks,liquidations,transaction replay etc.have emerged as significant threats,collectively generating$540.54 million in losses over 32 months across 11,289 addresses,involving 49,691 cryptocurrencies and 60,830 on-chain markets.These attacks exploit transaction mechanics to manipulate asset prices and extract value at the expense of other participants,with sandwich attacks being particularly impactful.Additionally,the growing adoption of blockchain in traditional finance highlights the challenge of TID,wherein high transaction volumes can strain systems and compromise time-sensitive operations.To address these pressing issues,we propose a novel Distributed Transaction Sequencing Strategy(DTSS)that integrates forking mechanisms with an Analytic Hierarchy Process(AHP)to enforce fair and transparent transaction ordering in a decentralized manner.Our approach is further enhanced by an optimization framework and the introduction of a Normalized Allocation Disparity Metric(NADM)that ensures optimal parameter selection for transaction prioritization.Experimental evaluations demonstrated that the DTSS effectively mitigated BEV risks,enhanced transaction fairness,and significantly improved the security and transparency of DeFi ecosystems.展开更多
P2P trading is driving the decentralization of the electricity market,the autonomy and privacy requirements of prosumers may intro-duce safety risks such as voltage violations.Existing security management methods base...P2P trading is driving the decentralization of the electricity market,the autonomy and privacy requirements of prosumers may intro-duce safety risks such as voltage violations.Existing security management methods based on price guidance may face unsolvable situa-tions in trading scenarios and have difficulty assessing the impact of P2P transactions on voltage security.To this end,this paper proposes a novel distribution system operator(DSO)-prosumers bi-level optimization framework incorporating the dynamic operating envelope(DOE)and risk coefficient-based network usage charge(RC-NUC).In the upper-level,the DOE is employed for dynamic voltage man-agement to prevent violations while the RC-NUC further guides prosumers to engage in grid-friendly transactions.The lower-level decen-tralized market enables prosumers to optimize trading decisions autonomously.Only price signals and energy quantities are exchanged between the two levels,ensuring the privacy of both parties.Additionally,an alternating direction method of multipliers(ADMM)with adaptive penalty factor is introduced to improve computational efficiency.Case studies on a modified IEEE 33-bus system demonstrate that the proposed method reduces voltage violation risks by 18.31%and enhances trading efficiency by 32.3%.These results highlight the feasibility and effectiveness of the approach in advancing secure and efficient distributed energy transactions.展开更多
Blockchain platform swith the unique characteristics of anonymity,decentralization,and transparency of their transactions,which are faced with abnormal activities such as money laundering,phishing scams,and fraudulent...Blockchain platform swith the unique characteristics of anonymity,decentralization,and transparency of their transactions,which are faced with abnormal activities such as money laundering,phishing scams,and fraudulent behavior,posing a serious threat to account asset security.For these potential security risks,this paper proposes a hybrid neural network detection method(HNND)that learns multiple types of account features and enhances fusion information among them to effectively detect abnormal transaction behaviors in the blockchain.In HNND,the Temporal Transaction Graph Attention Network(T2GAT)is first designed to learn biased aggregation representation of multi-attribute transactions among nodes,which can capture key temporal information from node neighborhood transactions.Then,the Graph Convolutional Network(GCN)is adopted which captures abstract structural features of the transaction network.Further,the Stacked Denoising Autoencode(SDA)is developed to achieve adaptive fusion of thses features from different modules.Moreover,the SDA enhances robustness and generalization ability of node representation,leading to higher binary classification accuracy in detecting abnormal behaviors of blockchain accounts.Evaluations on a real-world abnormal transaction dataset demonstrate great advantages of the proposed HNND method over other compared methods.展开更多
The global wave of digitalization has accelerated the process of corporate digital transformation,placing higher demands on financial and accounting management.Since then,accounting work has shifted from the tradition...The global wave of digitalization has accelerated the process of corporate digital transformation,placing higher demands on financial and accounting management.Since then,accounting work has shifted from the traditional transactional model to a modern value management-oriented model,leading to a transformation of accounting functions.As corporate managers,they must advance their work proactively,empower the modernization and innovation of financial accounting with digital technology,and transition to management accounting to ensure enterprises keep pace with the times.Therefore,this paper explores the current status of corporate financial and accounting work amid the digital wave,identifies the challenges in the transformation of accounting from transactional to value management-oriented,and finally proposes several feasible and effective improvement strategies,aiming to provide more references for relevant practitioners.展开更多
Low data encryption efficiency and inadequate security are two issues with the current blockchain cross-chain transaction protection schemes.To address these issues,a blockchain cross-chain transaction protection sche...Low data encryption efficiency and inadequate security are two issues with the current blockchain cross-chain transaction protection schemes.To address these issues,a blockchain cross-chain transaction protection scheme based on Fully Homomorphic Encryption(FHE)is proposed.In the proposed scheme,the functional relationship is established by Box-Muller,Discrete Gaussian Distribution Function(DGDF)and Uniform Random Distribution Func-tion(URDF)are used to improve the security and efficiency of key generation.Subsequently,the data preprocessing function is introduced to perform cleaning,deduplication,and normalization operations on the transaction data of multi-key signature,and it is classified into interactive data and asset data,so as to perform different homomorphic operations in the FHE encryption stage.Ultimately,in the FHE encryption stage,homomorphic multiplication and homomorphic addition are used targeted for the interactive data and asset data,thereby reducing the computational complexity and enhancing the FHE encryption efficiency.The significance of the proposed scheme is proved by experimental results:Firstly,the multi-key generation function and its specific sampling method and transformation ensure the security and efficiency of key generation.Data preprocessing can also accelerate the FHE encryption process by eliminating invalid data and redundancy,so the FHE encryption efficiency is significantly improved.Secondly,the FHE encryption method based on discrete logarithm problem enhances the security of transaction data and can effectively resist multiple attacks.In addition,the preprocessed data also has good performance in capacity storage.The proposed scheme has significant impacts on key indicators such as encryption efficiency and security,it provides a new reference for blockchain cross-chain transaction protection technology and has an important impact on the security improvement of various cross-chain transaction data.展开更多
Bilateral electric power contract is settled based on contract output curve. This paper considered the bilateral transactions execution, new energy accommodation, power grid security and generation economy, considerin...Bilateral electric power contract is settled based on contract output curve. This paper considered the bilateral transactions execution, new energy accommodation, power grid security and generation economy, considering the executive priority of different power components to establish a multi-objective coordination unit commitment model. Through an example to verify the effectiveness of the model in promoting wind power consumption, guaranteeing trade execution, and improving power generation efficiency, and analyzed the interactions to each other among the factors of wind power, trading and blocking. According to the results, when wind power causes reverse power flow in the congestion line, it will promote the implementation of contracts, the influence of wind power accommodation to trade execution should be analyzed combined with the grid block, the results can provide reference for wind power planning.展开更多
Privilege user is needed to manage the commercial transactions, but a super-administrator may have monopolize power and cause serious security problem. Relied on trusted computing technology, a privilege separation me...Privilege user is needed to manage the commercial transactions, but a super-administrator may have monopolize power and cause serious security problem. Relied on trusted computing technology, a privilege separation method is proposed to satisfy the security management requirement for information systems. It authorizes the system privilege to three different managers, and none of it can be interfered by others. Process algebra Communication Sequential Processes is used to model the three powers mechanism, and safety effect is analyzed and compared.展开更多
Market construction Overview In 2009, the electric power market expanded continuously. New installed capacity put into production within the coverage of the State Grid Corporation
This paper proposes to use the related party transactions’(RPT)budget completion ratio(BCR)as indicator of RPT’s execution quality.This paper studies BCR by defining budget ceiling through RPTs announcement and comp...This paper proposes to use the related party transactions’(RPT)budget completion ratio(BCR)as indicator of RPT’s execution quality.This paper studies BCR by defining budget ceiling through RPTs announcement and comparing the amount disclosed in annual report as budget execution result.Through statistical analysis of 285 RPT announcements,we classify RPT’s BCR into four benchmark grades.This paper sums up the BCR of RPT from the samples,and deduces moral obligation and moral judgement curve(OJ curve)in terms of BCR.OJ curve is the real dynamic equilibrium after the struggle agency problems.From our statistical results,we verified that Weitzman’s ratchet effect exists in the budget formulation of RPTs,and it is a solid proof of Weitzman’s ratchet effect applied to real business scenarios.The empirical results show ratchet effect exists in BCR of RPTs before and after the change from GEM board listing to main board listing in Hong Kong(Transfer).This paper also finds that it is significant to find the estimated actual amount in the coming year through the budget completion ratio(BCR)of RPT from last year.This paper is a pioneer to examine the execution quality of RPT by the means of(i)Weitzman’s Truth Inducing Model,(ii)BCR,and(iii)SGR as well as(iv)estimated actual amount.展开更多
To safeguard the interests of transacting parties,non-repudiation mechanisms need to assure fairness and timeliness.The non-repudiation service currently implemented usually does not consider the requirement of fairne...To safeguard the interests of transacting parties,non-repudiation mechanisms need to assure fairness and timeliness.The non-repudiation service currently implemented usually does not consider the requirement of fairness and the fair non-repudiation protocols to date can not be suitably applied in real environment due to its complex interaction.This paper discusses the transaction-oriented non-repudiation requirement for Web services transaction,analyzes the constraints of the traditional model for the available fair non-repudiation protocols and designs a new Online-TTP fair non-repudiation protocol.The new protocol provides a fair non-repudiation solution to secure Web services transactions and can be embedded into a single Web service call.The protocol adopts evidence chained to decreasing the overhead of evidence verification and management and alleviates the overhead of certificate revocation checking and time-stamp generation for signatures.The protocol has strong fairness,timeliness,efficiency and practicability.展开更多
With the introduction of the“dual carbon”goal and the continuous promotion of low-carbon development,the integrated energy system(IES)has gradually become an effective way to save energy and reduce emissions.This st...With the introduction of the“dual carbon”goal and the continuous promotion of low-carbon development,the integrated energy system(IES)has gradually become an effective way to save energy and reduce emissions.This study proposes a low-carbon economic optimization scheduling model for an IES that considers carbon trading costs.With the goal of minimizing the total operating cost of the IES and considering the transferable and curtailable characteristics of the electric and thermal flexible loads,an optimal scheduling model of the IES that considers the cost of carbon trading and flexible loads on the user side was established.The role of flexible loads in improving the economy of an energy system was investigated using examples,and the rationality and effectiveness of the study were verified through a comparative analysis of different scenarios.The results showed that the total cost of the system in different scenarios was reduced by 18.04%,9.1%,3.35%,and 7.03%,respectively,whereas the total carbon emissions of the system were reduced by 65.28%,20.63%,3.85%,and 18.03%,respectively,when the carbon trading cost and demand-side flexible electric and thermal load responses were considered simultaneously.Flexible electrical and thermal loads did not have the same impact on the system performance.In the analyzed case,the total cost and carbon emissions of the system when only the flexible electrical load response was considered were lower than those when only the flexible thermal load response was taken into account.Photovoltaics have an excess of carbon trading credits and can profit from selling them,whereas other devices have an excess of carbon trading and need to buy carbon credits.展开更多
Transactions of Nanjing University of Aeronautics&Astronautics (TNUAA) is a bimonthly journal facing international academic community. Emphasizing prompt and effective dissemination of key data and new scientific ...Transactions of Nanjing University of Aeronautics&Astronautics (TNUAA) is a bimonthly journal facing international academic community. Emphasizing prompt and effective dissemination of key data and new scientific insights, TNUAA offers publication of new experimental and theoretical papers bearing on applications to all branches of aeronautics, astronautics and civil aviation.展开更多
Transactions of Nanjing University of Aeronautics & Astronautics (TNUAA) is a bimonthly journal facing international academic community.Emphasizing prompt and effective dissemination of key data and new scientific...Transactions of Nanjing University of Aeronautics & Astronautics (TNUAA) is a bimonthly journal facing international academic community.Emphasizing prompt and effective dissemination of key data and new scientific insights,TNUAA offers publication of new experimental and theoretical papers bearing on applications to all branches of aeronautics,astronautics and civil aviation.展开更多
基金funded by the Deanship of Scientific Research,Vice Presidency for Graduate Studies and Scientific Research,King Faisal University,Saudi Arabia[Grant No.KFU241683].
文摘This paper proposes a novel hybrid fraud detection framework that integrates multi-stage feature selection,unsupervised clustering,and ensemble learning to improve classification performance in financial transaction monitoring systems.The framework is structured into three core layers:(1)feature selection using Recursive Feature Elimination(RFE),Principal Component Analysis(PCA),and Mutual Information(MI)to reduce dimensionality and enhance input relevance;(2)anomaly detection through unsupervised clustering using K-Means,Density-Based Spatial Clustering(DBSCAN),and Hierarchical Clustering to flag suspicious patterns in unlabeled data;and(3)final classification using a voting-based hybrid ensemble of Support Vector Machine(SVM),Random Forest(RF),and Gradient Boosting Classifier(GBC).The experimental evaluation is conducted on a synthetically generated dataset comprising one million financial transactions,with 5% labelled as fraudulent,simulating realistic fraud rates and behavioural features,including transaction time,origin,amount,and geo-location.The proposed model demonstrated a significant improvement over baseline classifiers,achieving an accuracy of 99%,a precision of 99%,a recall of 97%,and an F1-score of 99%.Compared to individual models,it yielded a 9% gain in overall detection accuracy.It reduced the false positive rate to below 3.5%,thereby minimising the operational costs associated with manually reviewing false alerts.The model’s interpretability is enhanced by the integration of Shapley Additive Explanations(SHAP)values for feature importance,supporting transparency and regulatory auditability.These results affirm the practical relevance of the proposed system for deployment in real-time fraud detection scenarios such as credit card transactions,mobile banking,and cross-border payments.The study also highlights future directions,including the deployment of lightweight models and the integration of multimodal data for scalable fraud analytics.
文摘In the evolving landscape of software engineering, Microservice Architecture (MSA) has emerged as a transformative approach, facilitating enhanced scalability, agility, and independent service deployment. This systematic literature review (SLR) explores the current state of distributed transaction management within MSA, focusing on the unique challenges, strategies, and technologies utilized in this domain. By synthesizing findings from 16 primary studies selected based on rigorous criteria, the review identifies key trends and best practices for maintaining data consistency and integrity across microservices. This SLR provides a comprehensive understanding of the complexities associated with distributed transactions in MSA, offering actionable insights and potential research directions for software architects, developers, and researchers.
基金co-financed by the European Union Horizon Europe Research and Innovation Programme under Grant Agreements No.101058174 and No 101091895.
文摘Since its inception in 2009,Bitcoin has become and is currently the most successful and widely used cryptocurrency.It introduced blockchain technology,which allows transactions that transfer funds between users to take place online,in an immutable manner.No real-world identities are needed or stored in the blockchain.At the same time,all transactions are publicly available and auditable,making Bitcoin a pseudo-anonymous ledger of transactions.The volume of transactions that are broadcast on a daily basis is considerably large.We propose a set of features that can be extracted from transaction data.Using this,we apply a data processing pipeline to ultimately cluster transactions via a k-means clustering algorithm,according to the transaction properties.Finally,according to these properties,we are able to characterize these clusters and the transactions they include.Our work mainly differentiates from previous studies in that it applies an unsupervised learning method to cluster transactions instead of addresses.Using the novel features we introduce,our work classifies transactions in multiple clusters,while previous studies only attempt binary classification.Results indicate that most transactions fall into a cluster that can be described as common user transactions.Other clusters include transactions made by online exchanges and lending services,those relating to mining activities as well as smaller clusters,one of which contains possibly illicit or fraudulent transactions.We evaluated our results against an online database of addresses that belong to known actors,such as online exchanges,and found that our results generally agree with them,which enhances the validity of our methods.
基金Philosophy and Social Science Planning Projects in Yunnan Province,No.QN202428China Postdoctoral Science Foundation,No.2024M752918。
文摘Foreign-funded overseas industrial parks(OIPs)are crucial for attracting foreign investment and promoting globalization in developing countries.However,large-scale land acquisition for these parks generates conflicts between developers and local stakeholders,increasing development costs.A qualitative multicase study was conducted in this study to analyze the land transaction trajectories of China's OIPs.Four OIPs were selected to reveal the underlying mechanisms from the perspectives of institutional arrangements,governance mechanisms,and enterprise heterogeneity.The findings indicate that in host countries with insufficient institutional development,local governments are more inclined to directly engage in OIP land acquisition.High-level intergovernmental mechanisms facilitate land acquisition processes,although their efficacy depends largely on administrative power allocation across parks in host countries.The results also indicate that enterprise characteristics significantly influence land acquisition,where microscale private enterprises lacking political connections often employ low-cost,bottom-up strategies by leveraging international experience.In summary,policy-makers in developing countries should prioritize enhancing OIP governance to mitigate transaction costs,promote diversified land supply,and optimize land allocation.By depicting China's OIP land acquisition processes,this study deepens the academic understanding of OIP governance in developing countries and related international land transactions,offering practical OIP management insights for governments in both host and parent countries.
基金funded by the University of Macao(file no.MYRG2022-00162-FST and MYRG2019-00136-FST).
文摘The rapid growth of blockchain and Decentralized Finance(DeFi)has introduced new challenges and vulnerabilities that threaten the integrity and efficiency of the ecosystem.This study identifies critical issues such as Transaction Order Dependence(TOD),Blockchain Extractable Value(BEV),and Transaction Importance Diversity(TID),which collectively undermine the fairness and security of DeFi systems.BEV-related activities,including sandwich attacks,liquidations,transaction replay etc.have emerged as significant threats,collectively generating$540.54 million in losses over 32 months across 11,289 addresses,involving 49,691 cryptocurrencies and 60,830 on-chain markets.These attacks exploit transaction mechanics to manipulate asset prices and extract value at the expense of other participants,with sandwich attacks being particularly impactful.Additionally,the growing adoption of blockchain in traditional finance highlights the challenge of TID,wherein high transaction volumes can strain systems and compromise time-sensitive operations.To address these pressing issues,we propose a novel Distributed Transaction Sequencing Strategy(DTSS)that integrates forking mechanisms with an Analytic Hierarchy Process(AHP)to enforce fair and transparent transaction ordering in a decentralized manner.Our approach is further enhanced by an optimization framework and the introduction of a Normalized Allocation Disparity Metric(NADM)that ensures optimal parameter selection for transaction prioritization.Experimental evaluations demonstrated that the DTSS effectively mitigated BEV risks,enhanced transaction fairness,and significantly improved the security and transparency of DeFi ecosystems.
文摘P2P trading is driving the decentralization of the electricity market,the autonomy and privacy requirements of prosumers may intro-duce safety risks such as voltage violations.Existing security management methods based on price guidance may face unsolvable situa-tions in trading scenarios and have difficulty assessing the impact of P2P transactions on voltage security.To this end,this paper proposes a novel distribution system operator(DSO)-prosumers bi-level optimization framework incorporating the dynamic operating envelope(DOE)and risk coefficient-based network usage charge(RC-NUC).In the upper-level,the DOE is employed for dynamic voltage man-agement to prevent violations while the RC-NUC further guides prosumers to engage in grid-friendly transactions.The lower-level decen-tralized market enables prosumers to optimize trading decisions autonomously.Only price signals and energy quantities are exchanged between the two levels,ensuring the privacy of both parties.Additionally,an alternating direction method of multipliers(ADMM)with adaptive penalty factor is introduced to improve computational efficiency.Case studies on a modified IEEE 33-bus system demonstrate that the proposed method reduces voltage violation risks by 18.31%and enhances trading efficiency by 32.3%.These results highlight the feasibility and effectiveness of the approach in advancing secure and efficient distributed energy transactions.
文摘Blockchain platform swith the unique characteristics of anonymity,decentralization,and transparency of their transactions,which are faced with abnormal activities such as money laundering,phishing scams,and fraudulent behavior,posing a serious threat to account asset security.For these potential security risks,this paper proposes a hybrid neural network detection method(HNND)that learns multiple types of account features and enhances fusion information among them to effectively detect abnormal transaction behaviors in the blockchain.In HNND,the Temporal Transaction Graph Attention Network(T2GAT)is first designed to learn biased aggregation representation of multi-attribute transactions among nodes,which can capture key temporal information from node neighborhood transactions.Then,the Graph Convolutional Network(GCN)is adopted which captures abstract structural features of the transaction network.Further,the Stacked Denoising Autoencode(SDA)is developed to achieve adaptive fusion of thses features from different modules.Moreover,the SDA enhances robustness and generalization ability of node representation,leading to higher binary classification accuracy in detecting abnormal behaviors of blockchain accounts.Evaluations on a real-world abnormal transaction dataset demonstrate great advantages of the proposed HNND method over other compared methods.
文摘The global wave of digitalization has accelerated the process of corporate digital transformation,placing higher demands on financial and accounting management.Since then,accounting work has shifted from the traditional transactional model to a modern value management-oriented model,leading to a transformation of accounting functions.As corporate managers,they must advance their work proactively,empower the modernization and innovation of financial accounting with digital technology,and transition to management accounting to ensure enterprises keep pace with the times.Therefore,this paper explores the current status of corporate financial and accounting work amid the digital wave,identifies the challenges in the transformation of accounting from transactional to value management-oriented,and finally proposes several feasible and effective improvement strategies,aiming to provide more references for relevant practitioners.
文摘Low data encryption efficiency and inadequate security are two issues with the current blockchain cross-chain transaction protection schemes.To address these issues,a blockchain cross-chain transaction protection scheme based on Fully Homomorphic Encryption(FHE)is proposed.In the proposed scheme,the functional relationship is established by Box-Muller,Discrete Gaussian Distribution Function(DGDF)and Uniform Random Distribution Func-tion(URDF)are used to improve the security and efficiency of key generation.Subsequently,the data preprocessing function is introduced to perform cleaning,deduplication,and normalization operations on the transaction data of multi-key signature,and it is classified into interactive data and asset data,so as to perform different homomorphic operations in the FHE encryption stage.Ultimately,in the FHE encryption stage,homomorphic multiplication and homomorphic addition are used targeted for the interactive data and asset data,thereby reducing the computational complexity and enhancing the FHE encryption efficiency.The significance of the proposed scheme is proved by experimental results:Firstly,the multi-key generation function and its specific sampling method and transformation ensure the security and efficiency of key generation.Data preprocessing can also accelerate the FHE encryption process by eliminating invalid data and redundancy,so the FHE encryption efficiency is significantly improved.Secondly,the FHE encryption method based on discrete logarithm problem enhances the security of transaction data and can effectively resist multiple attacks.In addition,the preprocessed data also has good performance in capacity storage.The proposed scheme has significant impacts on key indicators such as encryption efficiency and security,it provides a new reference for blockchain cross-chain transaction protection technology and has an important impact on the security improvement of various cross-chain transaction data.
文摘Bilateral electric power contract is settled based on contract output curve. This paper considered the bilateral transactions execution, new energy accommodation, power grid security and generation economy, considering the executive priority of different power components to establish a multi-objective coordination unit commitment model. Through an example to verify the effectiveness of the model in promoting wind power consumption, guaranteeing trade execution, and improving power generation efficiency, and analyzed the interactions to each other among the factors of wind power, trading and blocking. According to the results, when wind power causes reverse power flow in the congestion line, it will promote the implementation of contracts, the influence of wind power accommodation to trade execution should be analyzed combined with the grid block, the results can provide reference for wind power planning.
文摘Privilege user is needed to manage the commercial transactions, but a super-administrator may have monopolize power and cause serious security problem. Relied on trusted computing technology, a privilege separation method is proposed to satisfy the security management requirement for information systems. It authorizes the system privilege to three different managers, and none of it can be interfered by others. Process algebra Communication Sequential Processes is used to model the three powers mechanism, and safety effect is analyzed and compared.
文摘Market construction Overview In 2009, the electric power market expanded continuously. New installed capacity put into production within the coverage of the State Grid Corporation
文摘This paper proposes to use the related party transactions’(RPT)budget completion ratio(BCR)as indicator of RPT’s execution quality.This paper studies BCR by defining budget ceiling through RPTs announcement and comparing the amount disclosed in annual report as budget execution result.Through statistical analysis of 285 RPT announcements,we classify RPT’s BCR into four benchmark grades.This paper sums up the BCR of RPT from the samples,and deduces moral obligation and moral judgement curve(OJ curve)in terms of BCR.OJ curve is the real dynamic equilibrium after the struggle agency problems.From our statistical results,we verified that Weitzman’s ratchet effect exists in the budget formulation of RPTs,and it is a solid proof of Weitzman’s ratchet effect applied to real business scenarios.The empirical results show ratchet effect exists in BCR of RPTs before and after the change from GEM board listing to main board listing in Hong Kong(Transfer).This paper also finds that it is significant to find the estimated actual amount in the coming year through the budget completion ratio(BCR)of RPT from last year.This paper is a pioneer to examine the execution quality of RPT by the means of(i)Weitzman’s Truth Inducing Model,(ii)BCR,and(iii)SGR as well as(iv)estimated actual amount.
基金Supported by the National High Technology Research and Development Program of China (863 Program) (2006AA01Z405)
文摘To safeguard the interests of transacting parties,non-repudiation mechanisms need to assure fairness and timeliness.The non-repudiation service currently implemented usually does not consider the requirement of fairness and the fair non-repudiation protocols to date can not be suitably applied in real environment due to its complex interaction.This paper discusses the transaction-oriented non-repudiation requirement for Web services transaction,analyzes the constraints of the traditional model for the available fair non-repudiation protocols and designs a new Online-TTP fair non-repudiation protocol.The new protocol provides a fair non-repudiation solution to secure Web services transactions and can be embedded into a single Web service call.The protocol adopts evidence chained to decreasing the overhead of evidence verification and management and alleviates the overhead of certificate revocation checking and time-stamp generation for signatures.The protocol has strong fairness,timeliness,efficiency and practicability.
基金supported by State Grid Shanxi Electric Power Company Science and Technology Project“Research on key technologies of carbon tracking and carbon evaluation for new power system”(Grant:520530230005)。
文摘With the introduction of the“dual carbon”goal and the continuous promotion of low-carbon development,the integrated energy system(IES)has gradually become an effective way to save energy and reduce emissions.This study proposes a low-carbon economic optimization scheduling model for an IES that considers carbon trading costs.With the goal of minimizing the total operating cost of the IES and considering the transferable and curtailable characteristics of the electric and thermal flexible loads,an optimal scheduling model of the IES that considers the cost of carbon trading and flexible loads on the user side was established.The role of flexible loads in improving the economy of an energy system was investigated using examples,and the rationality and effectiveness of the study were verified through a comparative analysis of different scenarios.The results showed that the total cost of the system in different scenarios was reduced by 18.04%,9.1%,3.35%,and 7.03%,respectively,whereas the total carbon emissions of the system were reduced by 65.28%,20.63%,3.85%,and 18.03%,respectively,when the carbon trading cost and demand-side flexible electric and thermal load responses were considered simultaneously.Flexible electrical and thermal loads did not have the same impact on the system performance.In the analyzed case,the total cost and carbon emissions of the system when only the flexible electrical load response was considered were lower than those when only the flexible thermal load response was taken into account.Photovoltaics have an excess of carbon trading credits and can profit from selling them,whereas other devices have an excess of carbon trading and need to buy carbon credits.
文摘Transactions of Nanjing University of Aeronautics&Astronautics (TNUAA) is a bimonthly journal facing international academic community. Emphasizing prompt and effective dissemination of key data and new scientific insights, TNUAA offers publication of new experimental and theoretical papers bearing on applications to all branches of aeronautics, astronautics and civil aviation.
文摘Transactions of Nanjing University of Aeronautics & Astronautics (TNUAA) is a bimonthly journal facing international academic community.Emphasizing prompt and effective dissemination of key data and new scientific insights,TNUAA offers publication of new experimental and theoretical papers bearing on applications to all branches of aeronautics,astronautics and civil aviation.
