Human resource management has begun to conduct information technology to enhance the efficiency of human resource work.The research objectives are:(1)Does the implementation of human resource management information sy...Human resource management has begun to conduct information technology to enhance the efficiency of human resource work.The research objectives are:(1)Does the implementation of human resource management information system enhance work efficiency?(2)What are key factors to influence the implementation of human resource management information system?This research adopts case study with in-depth interviews at W University of Science and Technology.The interviewees of this study were mainly one director and four staffs working at the Department of Human Resource.The research results show that the system quality is acceptable and the system security is perfect.All users have consistent opinions on the bad quality of information and they spend more time to check the data at work.The system use frequency of each user is different,mainly depending on the content of their work.Users who are used less have higher user satisfaction in human resource management information system.Most users perceive that the personal benefit is increased,and feel that this system can enhance personal benefits and improve the organization benefits for personnel management.展开更多
We advance here a novel methodology for robust intelligent biometric information management with inferences and predictions made using randomness and complexity concepts. Intelligence refers to learning, adap- tation,...We advance here a novel methodology for robust intelligent biometric information management with inferences and predictions made using randomness and complexity concepts. Intelligence refers to learning, adap- tation, and functionality, and robustness refers to the ability to handle incomplete and/or corrupt adversarial information, on one side, and image and or device variability, on the other side. The proposed methodology is model-free and non-parametric. It draws support from discriminative methods using likelihood ratios to link at the conceptual level biometrics and forensics. It further links, at the modeling and implementation level, the Bayesian framework, statistical learning theory (SLT) using transduction and semi-supervised lea- rning, and Information Theory (IY) using mutual information. The key concepts supporting the proposed methodology are a) local estimation to facilitate learning and prediction using both labeled and unlabeled data;b) similarity metrics using regularity of patterns, randomness deficiency, and Kolmogorov complexity (similar to MDL) using strangeness/typicality and ranking p-values;and c) the Cover – Hart theorem on the asymptotical performance of k-nearest neighbors approaching the optimal Bayes error. Several topics on biometric inference and prediction related to 1) multi-level and multi-layer data fusion including quality and multi-modal biometrics;2) score normalization and revision theory;3) face selection and tracking;and 4) identity management, are described here using an integrated approach that includes transduction and boosting for ranking and sequential fusion/aggregation, respectively, on one side, and active learning and change/ outlier/intrusion detection realized using information gain and martingale, respectively, on the other side. The methodology proposed can be mapped to additional types of information beyond biometrics.展开更多
European Community policy concerning water is placing increasing demands on the acquisition of information about the quality of aquatic environments. The cost of this information has led to a reflection on the rationa...European Community policy concerning water is placing increasing demands on the acquisition of information about the quality of aquatic environments. The cost of this information has led to a reflection on the rationalization of monitoring networks and, therefore, on the economic value of information produced by these networks. The aim of this article is to contribute to this reflection. To do so, we used the Bayesian framework to define the value of additional information in relation to the following three parameters: initial assumptions (prior probabilities) on the states of nature, costs linked to a poor decision (error costs) and accuracy of additional information. We then analyzed the impact of these parameters on this value, particularly the combined role of prior probabilities and error costs that increased or decreased the value of information depending on the initial uncertainty level. We then illustrated the results using a case study of a stream in the Bas-Rhin department in France.展开更多
Global concerns toward environmental issues have induced growing demand for new approaches in the construction because of its considerable impact on the environment and use of natural resources. Through using construc...Global concerns toward environmental issues have induced growing demand for new approaches in the construction because of its considerable impact on the environment and use of natural resources. Through using construction sustainability tools, methods and techniques, a greener design can be applied during various building phases. In this connection, it is argued that the analytical and integrated models applied by Building Information Modelling (BIM) may also facilitate this process to be performed more efficiently. BIM and construction sustainability are quite different initiatives, but both have received much attention in recent years in the architecture, engineering and construction (AEC) industry. A rigorous analysis of the interactions between them implies that a synergy exists which, if properly it is understood that can be helpful to reduce the environmental impacts of the AEC industry. A BIM-based design model can contribute to sustainability through its three main dimensions which are environmental, economic and social. In this paper, by reviewing the existing literature on BIM and construction sustainability and using a matrix to analyze construction sustainability dimensions and BIM functionalities a number of interactions have been discussed. It can be concluded that despite there are many improvements in implementation of BIM in environmental and economic aspects of sustainability, its potential impact on social dimension has not been explicitly explored hence further studies need to be undertaken in this area.展开更多
Lack of trust has been an ongoing issue for decades in construction quality management,hindering the improvement of quality performance.The development of mutual trust depends on immutable,traceable,and transparent co...Lack of trust has been an ongoing issue for decades in construction quality management,hindering the improvement of quality performance.The development of mutual trust depends on immutable,traceable,and transparent construction quality information records.However,current information technologies cannot meet the requirements.To address the challenge,this study explores a blockchain-based framework for construction quality information management,which extends applications of blockchain in the domain of construction quality management.A consortium blockchain system is designed to support construction quality management in which participants’information permissions and lifecycle are discussed.Additionally,this study presents in detail the consensus process that aims to address the problem of information fraud.The automated compliance checking based on smart contracts is presented as well,aiming to assure that construction products meet regulation requirements.Finally,an example of the consortium blockchain network is visualized to validate the feasibility of blockchain-based construction quality information management.The research shows that blockchain can facilitate mutual trust in construction quality management by providing distributed,encrypted,and secure information records and supporting automated compliance checking of construction quality.展开更多
文摘Human resource management has begun to conduct information technology to enhance the efficiency of human resource work.The research objectives are:(1)Does the implementation of human resource management information system enhance work efficiency?(2)What are key factors to influence the implementation of human resource management information system?This research adopts case study with in-depth interviews at W University of Science and Technology.The interviewees of this study were mainly one director and four staffs working at the Department of Human Resource.The research results show that the system quality is acceptable and the system security is perfect.All users have consistent opinions on the bad quality of information and they spend more time to check the data at work.The system use frequency of each user is different,mainly depending on the content of their work.Users who are used less have higher user satisfaction in human resource management information system.Most users perceive that the personal benefit is increased,and feel that this system can enhance personal benefits and improve the organization benefits for personnel management.
文摘We advance here a novel methodology for robust intelligent biometric information management with inferences and predictions made using randomness and complexity concepts. Intelligence refers to learning, adap- tation, and functionality, and robustness refers to the ability to handle incomplete and/or corrupt adversarial information, on one side, and image and or device variability, on the other side. The proposed methodology is model-free and non-parametric. It draws support from discriminative methods using likelihood ratios to link at the conceptual level biometrics and forensics. It further links, at the modeling and implementation level, the Bayesian framework, statistical learning theory (SLT) using transduction and semi-supervised lea- rning, and Information Theory (IY) using mutual information. The key concepts supporting the proposed methodology are a) local estimation to facilitate learning and prediction using both labeled and unlabeled data;b) similarity metrics using regularity of patterns, randomness deficiency, and Kolmogorov complexity (similar to MDL) using strangeness/typicality and ranking p-values;and c) the Cover – Hart theorem on the asymptotical performance of k-nearest neighbors approaching the optimal Bayes error. Several topics on biometric inference and prediction related to 1) multi-level and multi-layer data fusion including quality and multi-modal biometrics;2) score normalization and revision theory;3) face selection and tracking;and 4) identity management, are described here using an integrated approach that includes transduction and boosting for ranking and sequential fusion/aggregation, respectively, on one side, and active learning and change/ outlier/intrusion detection realized using information gain and martingale, respectively, on the other side. The methodology proposed can be mapped to additional types of information beyond biometrics.
文摘European Community policy concerning water is placing increasing demands on the acquisition of information about the quality of aquatic environments. The cost of this information has led to a reflection on the rationalization of monitoring networks and, therefore, on the economic value of information produced by these networks. The aim of this article is to contribute to this reflection. To do so, we used the Bayesian framework to define the value of additional information in relation to the following three parameters: initial assumptions (prior probabilities) on the states of nature, costs linked to a poor decision (error costs) and accuracy of additional information. We then analyzed the impact of these parameters on this value, particularly the combined role of prior probabilities and error costs that increased or decreased the value of information depending on the initial uncertainty level. We then illustrated the results using a case study of a stream in the Bas-Rhin department in France.
文摘Global concerns toward environmental issues have induced growing demand for new approaches in the construction because of its considerable impact on the environment and use of natural resources. Through using construction sustainability tools, methods and techniques, a greener design can be applied during various building phases. In this connection, it is argued that the analytical and integrated models applied by Building Information Modelling (BIM) may also facilitate this process to be performed more efficiently. BIM and construction sustainability are quite different initiatives, but both have received much attention in recent years in the architecture, engineering and construction (AEC) industry. A rigorous analysis of the interactions between them implies that a synergy exists which, if properly it is understood that can be helpful to reduce the environmental impacts of the AEC industry. A BIM-based design model can contribute to sustainability through its three main dimensions which are environmental, economic and social. In this paper, by reviewing the existing literature on BIM and construction sustainability and using a matrix to analyze construction sustainability dimensions and BIM functionalities a number of interactions have been discussed. It can be concluded that despite there are many improvements in implementation of BIM in environmental and economic aspects of sustainability, its potential impact on social dimension has not been explicitly explored hence further studies need to be undertaken in this area.
基金the National Natural Science Foundation of China(Grant Nos.71732001,51878311,and 51978302).
文摘Lack of trust has been an ongoing issue for decades in construction quality management,hindering the improvement of quality performance.The development of mutual trust depends on immutable,traceable,and transparent construction quality information records.However,current information technologies cannot meet the requirements.To address the challenge,this study explores a blockchain-based framework for construction quality information management,which extends applications of blockchain in the domain of construction quality management.A consortium blockchain system is designed to support construction quality management in which participants’information permissions and lifecycle are discussed.Additionally,this study presents in detail the consensus process that aims to address the problem of information fraud.The automated compliance checking based on smart contracts is presented as well,aiming to assure that construction products meet regulation requirements.Finally,an example of the consortium blockchain network is visualized to validate the feasibility of blockchain-based construction quality information management.The research shows that blockchain can facilitate mutual trust in construction quality management by providing distributed,encrypted,and secure information records and supporting automated compliance checking of construction quality.
