The capability requirements of the command, control, communication, computing, intelligence, surveillance, reconnaissance （C41SR） systems are full of uncertain and vague information, which makes it difficult to mode...The capability requirements of the command, control, communication, computing, intelligence, surveillance, reconnaissance （C41SR） systems are full of uncertain and vague information, which makes it difficult to model the C41SR architecture. The paper presents an approach to modeling the capability requirements with the fuzzy unified modeling language （UML） and building domain ontologies with fuzzy description logic （DL）. The UML modeling constructs are extended according to the meta model of Depart- ment of Defense Architecture Framework to improve their domain applicability, the fuzzy modeling mechanism is introduced to model the fuzzy efficiency features of capabilities, and the capability requirement models are converted into ontologies formalized in fuzzy DL so that the model consistency and reasonability can be checked with a DL reasoning system. Finally, a case study of C41SR capability requirements model checking is provided to demonstrate the availability and applicability of the method.展开更多
Purpose: This study intends to evaluate the service quality of academic digital libraries(DLs)in China. By utilizing tetra-class model which concentrates on categorizing services according to their contributions to us...Purpose: This study intends to evaluate the service quality of academic digital libraries(DLs)in China. By utilizing tetra-class model which concentrates on categorizing services according to their contributions to user satisfaction, this paper attempts to visually categorize the specific DL service elements to reveal their present performances, and then further explain the categorizing variations among different groups of users to discover the user preference.Design/methodology/approach: This paper carries out a survey to evaluate user experience on 27 typical DL services summarized from our investigations of representative Chinese university DLs. Based on the five-point Likert-type scale evaluation, the users’ attitudes toward specific service element are divided into negative and positive dimensions. Afterwards,a correspondence analysis is applied to calculate the contributions to satisfaction and dissatisfaction of each service element based on tetra-class model. As a result, the DL service elements of Chinese academic libraries are classified into four categories(i.e. Basic, Secondary,Plus, and Key). Finally, we compared the categorizing variations.Findings: The results show that the DL service elements of Chinese academic libraries are all distributed in Basic and Key services regarding information retrieval and informationorganizing; 80% of the interaction services elements are Plus services, while 50% of the Secondary services are information-providing services. The results also reveal that service categorization is obviously influenced by the users’ education background, especially their disciplines. Furthermore, the users who are older, more highly-educated, or studying in higher reputation universities are more likely to evaluate DL services as either critical or useless.Research limitations: Tetra-class model cannot reveal the interplay among the DL service elements. In addition, the user segmentation in our studies is limited to the sample structure.Practical implications: This empirical study focuses on the evaluation of DL services of academic libraries in China, the analyses of their current performances could provide useful reference for the assessment of other types of Chinese DLs. Moreover, the consideration of user characteristics(gender, age, and education background, etc.) in the DL evaluation would help librarians improve DL services to meet the users’ various needs in teaching and doing scientific research.Originality/value: Different from the frequently-used factor analysis which focuses on the relationship among factors and user satisfaction, this paper tries to use and compare element distributions of different user segments while focusing on various service objectives. Factor analysis shows some flaws as used to measure the element with selected indicators, for it ignores the fact that the indicators which measure the same factor would have different degrees of impacts on user satisfaction. However, the tetra-class model can better visually analyze the performance of each DL service element from its contributions to satisfaction and dissatisfaction, which would help librarians to better understand users’ need and offer DL services more efficiently.展开更多
In this paper,we summarize recent progresses made in deep learning based acoustic models and the motivation and insights behind the surveyed techniques.We first discuss models such as recurrent neural networks(RNNs) a...In this paper,we summarize recent progresses made in deep learning based acoustic models and the motivation and insights behind the surveyed techniques.We first discuss models such as recurrent neural networks(RNNs) and convolutional neural networks(CNNs) that can effectively exploit variablelength contextual information,and their various combination with other models.We then describe models that are optimized end-to-end and emphasize on feature representations learned jointly with the rest of the system,the connectionist temporal classification(CTC) criterion,and the attention-based sequenceto-sequence translation model.We further illustrate robustness issues in speech recognition systems,and discuss acoustic model adaptation,speech enhancement and separation,and robust training strategies.We also cover modeling techniques that lead to more efficient decoding and discuss possible future directions in acoustic model research.展开更多
文摘The capability requirements of the command, control, communication, computing, intelligence, surveillance, reconnaissance （C41SR） systems are full of uncertain and vague information, which makes it difficult to model the C41SR architecture. The paper presents an approach to modeling the capability requirements with the fuzzy unified modeling language （UML） and building domain ontologies with fuzzy description logic （DL）. The UML modeling constructs are extended according to the meta model of Depart- ment of Defense Architecture Framework to improve their domain applicability, the fuzzy modeling mechanism is introduced to model the fuzzy efficiency features of capabilities, and the capability requirement models are converted into ontologies formalized in fuzzy DL so that the model consistency and reasonability can be checked with a DL reasoning system. Finally, a case study of C41SR capability requirements model checking is provided to demonstrate the availability and applicability of the method.
基金supported by the National Natural Science Foundation of China (Grant No.:71273197)
文摘Purpose: This study intends to evaluate the service quality of academic digital libraries(DLs)in China. By utilizing tetra-class model which concentrates on categorizing services according to their contributions to user satisfaction, this paper attempts to visually categorize the specific DL service elements to reveal their present performances, and then further explain the categorizing variations among different groups of users to discover the user preference.Design/methodology/approach: This paper carries out a survey to evaluate user experience on 27 typical DL services summarized from our investigations of representative Chinese university DLs. Based on the five-point Likert-type scale evaluation, the users’ attitudes toward specific service element are divided into negative and positive dimensions. Afterwards,a correspondence analysis is applied to calculate the contributions to satisfaction and dissatisfaction of each service element based on tetra-class model. As a result, the DL service elements of Chinese academic libraries are classified into four categories(i.e. Basic, Secondary,Plus, and Key). Finally, we compared the categorizing variations.Findings: The results show that the DL service elements of Chinese academic libraries are all distributed in Basic and Key services regarding information retrieval and informationorganizing; 80% of the interaction services elements are Plus services, while 50% of the Secondary services are information-providing services. The results also reveal that service categorization is obviously influenced by the users’ education background, especially their disciplines. Furthermore, the users who are older, more highly-educated, or studying in higher reputation universities are more likely to evaluate DL services as either critical or useless.Research limitations: Tetra-class model cannot reveal the interplay among the DL service elements. In addition, the user segmentation in our studies is limited to the sample structure.Practical implications: This empirical study focuses on the evaluation of DL services of academic libraries in China, the analyses of their current performances could provide useful reference for the assessment of other types of Chinese DLs. Moreover, the consideration of user characteristics(gender, age, and education background, etc.) in the DL evaluation would help librarians improve DL services to meet the users’ various needs in teaching and doing scientific research.Originality/value: Different from the frequently-used factor analysis which focuses on the relationship among factors and user satisfaction, this paper tries to use and compare element distributions of different user segments while focusing on various service objectives. Factor analysis shows some flaws as used to measure the element with selected indicators, for it ignores the fact that the indicators which measure the same factor would have different degrees of impacts on user satisfaction. However, the tetra-class model can better visually analyze the performance of each DL service element from its contributions to satisfaction and dissatisfaction, which would help librarians to better understand users’ need and offer DL services more efficiently.
文摘In this paper,we summarize recent progresses made in deep learning based acoustic models and the motivation and insights behind the surveyed techniques.We first discuss models such as recurrent neural networks(RNNs) and convolutional neural networks(CNNs) that can effectively exploit variablelength contextual information,and their various combination with other models.We then describe models that are optimized end-to-end and emphasize on feature representations learned jointly with the rest of the system,the connectionist temporal classification(CTC) criterion,and the attention-based sequenceto-sequence translation model.We further illustrate robustness issues in speech recognition systems,and discuss acoustic model adaptation,speech enhancement and separation,and robust training strategies.We also cover modeling techniques that lead to more efficient decoding and discuss possible future directions in acoustic model research.
