Delegating revocations and authorizations in collaborative business environments

Efficient collaboration allows organizations and individuals to improve the efficiency and quality of their business activities. Delegations, as a significant approach, may occur as workflow collaborations, supply chain collaborations, or collaborative commerce. Role-based delegation models have been used as flexible and efficient access management for collaborative business environments. Delegation revocations can provide significant functionalities for the models in business environments when the delegated roles or permissions are required to get back. However, problems may arise in the revocation process when one user delegates user U a role and another user delegates U a negative authorization of the role. This paper aims to analyse various role-based delegation revocation features through examples. Revocations are categorized in four dimensions: Dependency, Resilience, Propagation and Dominance. According to these dimensions, sixteen types of revocations exist for specific requests in collaborative business environments: DependentWeakLocalDelete, Dependent WeakLocalNegative, DependentWeakGlobalDelete, DependentWeakGlobalNegative, IndependentWeak LocalDelete, IndependentWeakLocalNegative, Inde pendentWeakGlobalDelete, IndependentWeakGlobal Negative, and so on. We present revocation delegating models, and then discuss user delegation authorization and the impact of revocation operations. Finally, comparisons with other related work are discussed

Effects of anesthesia on conventional and speckle tracking echocardiographic parameters in a mouse model of pressure overload

Genetically‑modified mice are widely applied in cardiovascular studies as model organisms. Echocardiography is a key tool for evaluating cardiac and hemodynamic functions in mice. The present study aimed to examine the effects of isoflurane (ISF) on conventional and speckle tracking echocardiography (STE) parameters under healthy and pathological conditions using a murine model of pressure overload. In addition, the optimal dose of ISF in the process of echocardiographic measurement, with minimum cardiac contraction depression, was investigated. Conventional echocardiographic and STE examinations were performed on 38 adult C57BL/6 male mice. The mice were divided into the following three groups: The sham (n=15); mild thoracic aortic banding (TAB; n=15); and severe TAB (n=8) groups. ISF was administered under deep anesthesia (DA; 1‑2% ISF), light anesthesia (LA; 0.5‑1% ISF) and immediately prior to the mice waking up (awake; 0‑0.5% ISF). Conventional echocardiographic parameters were preserved within the sham and mild TAB groups (P>0.05 for each parameter) under LA and awake conditions. However, under DA conditions, the majority of these parameters were reduced compared with the LA and awake conditions (P<0.05). In the severe TAB group, conventional echocardiographic parameters remained constant under LA, DA and awake conditions. STE parameters in the groups remained similar between the LA and awake conditions, but were significantly reduced under DA conditions. Therefore, conventional echocardiography and STE may be performed using LA induced with low doses of ISF, under various pathological conditions without affecting cardiac function

Matrix model for web page community construction

The World Wide Web is now a huge information source with its own characteristics. In most cases, traditional database-based technologies are no longer suitable for web information processing and management. For effectively processing and managing web. information, it is necessary to reveal intrinsic relationships/structures among concerned web information objects such as web pages. In this work, a set of web pages that has its own intrinsic structure is called a web page community. This paper proposes a matrix model to describe relationships among concerned web pages. Based on this model, intrinsic relationships among pages could be revealed, and in turn a web page community could be constructed. The issues that are related to this model in its application are deeply investigated and studied. Some applications based on this model are presented, which demonstrate the potential of this matrix model in different kinds of web page community construction and information processing.<br /

On incremental global update support in cooperative database systems

OzGateway is a cooperative database system designed for integrating heterogeneous existing information systems into an interoperable environment. It also aims to provide a gatewway for legacy information system migration. This paper summarises the problems and results of multidatabase transaction management research. In supporting global updates in OzGateway in an evolutionary way, we introduce a classification of multidatabase transactions and discuss the problems in each category. The architecture of OzGateway and the design of the global transaction manager and servers are presented

Set-Based Adaptive Distributed Differential Evolution for Anonymity-Driven Database Fragmentation

By breaking sensitive associations between attributes, database fragmentation can protect the privacy of outsourced data storage. Database fragmentation algorithms need prior knowledge of sensitive associations in the tackled database and set it as the optimization objective. Thus, the effectiveness of these algorithms is limited by prior knowledge. Inspired by the anonymity degree measurement in anonymity techniques such as k-anonymity, an anonymity-driven database fragmentation problem is defined in this paper. For this problem, a set-based adaptive distributed differential evolution (S-ADDE) algorithm is proposed. S-ADDE adopts an island model to maintain population diversity. Two set-based operators, i.e., set-based mutation and set-based crossover, are designed in which the continuous domain in the traditional differential evolution is transferred to the discrete domain in the anonymity-driven database fragmentation problem. Moreover, in the set-based mutation operator, each individual’s mutation strategy is adaptively selected according to the performance. The experimental results demonstrate that the proposed S-ADDE is significantly better than the compared approaches. The effectiveness of the proposed operators is verified

Electrooxidation of Hydrogen on Ni-Organic Metal Complex Catalysts in Acidic Media for PEMFCs

Novel organic metal complexes with N2O2 coordination structure which showed high hydrogen oxidation reaction were synthesized. The catalytic activity was found to strongly depend on the heat-treatment temperature and the structural properties

A heterogeneous graph-based semi-supervised learning framework for access control decision-making

For modern information systems, robust access control mechanisms are vital in safeguarding data integrity and ensuring the entire system’s security. This paper proposes a novel semi-supervised learning framework that leverages heterogeneous graph neural network-based embedding to encapsulate both the intricate relationships within the organizational structure and interactions between users and resources. Unlike existing methods focusing solely on individual user and resource attributes, our approach embeds organizational and operational interrelationships into the hidden layer node embeddings. These embeddings are learned from a self-supervised link prediction task based on a constructed access control heterogeneous graph via a heterogeneous graph neural network. Subsequently, the learned node embeddings, along with the original node features, serve as inputs for a supervised access control decision-making task, facilitating the construction of a machine-learning access control model. Experimental results on the open-sourced Amazon access control dataset demonstrate that our proposed framework outperforms models using original or manually extracted graph-based features from previous works. The prepossessed data and codes are available on GitHub,facilitating reproducibility and further research endeavors