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Landslides are one of the main geological disasters in the riparian zone of the Three Gorges Reservoir Area (TGRA) in China, causing massive losses in terms of industrial and agricultural production and people's lives and property. Due to the difficulty of data collection and lack of facade information, the remote sensing methods currently used for landslide mapping and detection are insufficient. The current landslide information acquisition method is mainly based on visual interpretation and automatic computer classification from aerial orthophotographs, which is subjective and time-consuming and yields low accuracy. New shipborne photogrammetry has unique advantages in small and steep slope landslide detection. In recent years, the deep learning technology represented by convolutional neural networks (CNNs) exhibits more powerful feature learning ability in image recognition than traditional machine learning technology. Meanwhile, transfer learning can make the network suitable for small datasets through fine-tuning, which could transfer the parameters of the pretrained model to the new model in a certain way, thereby increasing the learning efficiency of the model. In this paper, the training of multiple deep learning models is realized through transfer learning, and automatic identification of landslides based on shipborne images is achieved through decision-level fusion. The experimental results show that through the integration of decision-level fusion and transfer learning, it performs well in the classification of landslides based on shipborne images. [ABSTRACT FROM AUTHOR]

This paper evaluates the efficiency of Chinese vehicle manufacturing with different products for the period January to December 31st, 1993. It utilizes actual data rather than data modified by utilizing methods that can deal with zeros in the outputs. The paper thus highlights the fundamental role of zeros in DEA analysis, and derives a special calculation method which can decrease the dimension for computer implementation. The paper also illustrates the importance of the use of Assurance Regions (AR) and their application. [ABSTRACT FROM AUTHOR]

This paper addresses key barriers to implementing a clinical information system (CIS) in a Hong Kong nursing home setting, from a healthcare specific socio-technical perspective. Data was collected through field observations ( n = 12) and semi-structured individual interviews ( n = 18) of CIS stakeholders in a Hong Kong nursing home, and analyzed using the immersion/crystallization approach. Complex interactions relevant to our case were contextualized and interpreted within the perspective of the Sittig-Singh Healthcare Socio-Technical Framework (HSTF). Three broad clusters of implementation barriers from the eight HSTF dimensions were identified: (a) Infrastructure-based barriers, which relate to conflict between government regulations and system functional needs of users; lack of financial support; inconsistency between workflow, work policy, and procedures; and inadequacy of hardware-software infrastructural and technical support; (b) Process-based barriers, which relate to mismatch between the technology, existing work practice and workflow, and communication; low system speed, accessibility, and stability; deficient computer literacy; more experience in health care profession; clinical content inadequacy and unavailability; as well as poor system usefulness and user interface design; and (c) Outcome-based barriers, which relate to the lack of measurement and monitoring of system effectiveness. Two additional dimensions underlining the importance of the ability of a CIS to change are proposed to extend the Sittig-Singh HSTF. First, advocacy would promote the articulation and influence of changes in the system and subsequent outcomes by CIS stakeholders, and second, adaptability would ensure the ability of the system to adjust to emerging needs. The broad set of discovered implementation shortcomings expands prior research on why CIS can fail in nursing home settings. Moreover, our investigation offers a knowledge base and recommendations that can serve as a guide for future implementation strategies and policies in CIS initiatives. [ABSTRACT FROM AUTHOR]

Received wisdom views political humor, viz. egao, in the Chinese cyber public sphere as a form of resistance. This study creates and tests a framework that best conceptualizes how different functions of egao are connected with one another: to analyze the patterns of ties that link the different facets of the phenomenon together. The study contends that by framing egao within network society theory, we can appreciate its fluidity and better understand its online ubiquity. Analysis of survey data suggests that it is not the content solely but the networked practice of egao that dictates its true function. Namely, the networked practices of netizens (Internet citizens) have a formative relationship with their perceptions of, and interactions with, egao. The connectivity netizens feel from engaging in the practice often supersedes its content, in terms of value to cyber culture. [ABSTRACT FROM AUTHOR]