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"Semantic studies of the Biblical Hebrew verb "whole" have been influenced by those of its most invoked nominal form "whole". In this volume Andrew Chin Hei Leong shows that the concepts of balance, alliance, and completeness form the basic semantic structure of "whole". Previous studies on "whole" employed either historical or textual methodology, which has been dominant in biblical lexical studies. In addition to these methods, in Leong develops a systematic semantic methodology from Cognitive Semantics and Frame Semantics, to demonstrate that it is balance, rather than completeness, that is the most central concept in holding the semantic network together"--
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Information and communication technologies (ICTs) are highly associated with the study of e-government, and many scholars believe that within the coming decades, government operation and policy decision-making cannot persist without the use of ICTs (Van Dijk, 2018). This thesis aims to generate a conceptual framework of the behavioral factors that could contribute to the acceleration of the implementation of e-government services in Macao SAR. Rather than regarding e-government services as a goal to be realized in traditional practice through evaluating the outcome, a process-oriented study was conducted. The e-government services are regarded as advanced tools in the 21st century to transform Macao into a smart city. The design of the process-oriented approach and the comparative study of four groups of Macao citizens' behavioral intentions are solidly supported by the research gaps identified in the literature review of e-government studies in an international perspective and the actual context of local Macao studies. Under the framework of the Theory of Planned Behavior (Ajzen, 1985, 1991), the behavioral factors of the general public and civil servants are investigated through a qualitative approach, and the findings are triangulated from various aspects. Firstly, a systematic literature review of TPB was conducted thoroughly to better understand the current study of e-government around the world. Secondly, a content and thematic analysis of the official documents and articles from local press media and research institutes related to the topic of e-government services was carried out to demonstrate a more comprehensive picture of the current problems of implementing iv and adopting e-services in Macao SAR. Observations in some government premises that provided e-services and 40 in-depth interviews were conducted to generate detailed and first-hand data. Key issues were extracted from the interviewees’ narratives and daily actual usages. Different conceptual models for different age groups and civil servant group were formed. Special attention was paid to analyzing the "hard-to-reach" groups' behavioral intentions. Research limitations identified from the previous literature were overcome partially in this study too. After comparing the similarities and differences, a new conceptual model of significant behavioral factors that affect the behavioral intentions in adopting e-government services was built. Results and findings from the analysis could be used to develop effective interventions by the government policymakers in responding to the behavioral change of the general public in the aspect of e-government services acceptance and adoption
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Confucian education is best captured by the programme described in the Great Learning. Education is presented first as the process of self-cultivation for the sake of developing virtuous character. Self-cultivation then ...
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Convolutional neural network (CNN) model based on deep learning has excellent performance for target detection. However, the detection effect is poor when the object is circular or tubular because most of the existing object detection methods are based on the traditional rectangular box to detect and recognize objects. To solve the problem, we propose the circular representation structure and RepVGG module on the basis of CenterNet and expand the network prediction structure, thus proposing a high-precision and high-efficiency lightweight circular object detection method RebarDet. Specifically, circular tubular type objects will be optimized by replacing the traditional rectangular box with a circular box. Second, we improve the resolution of the network feature map and the upper limit of the number of objects detected in a single detect to achieve the expansion of the network prediction structure, optimized for the dense phenomenon that often occurs in circular tubular objects. Finally, the multibranch topology of RepVGG is introduced to sum the feature information extracted by different convolution modules, which improves the ability of the convolution module to extract information. We conducted extensive experiments on rebar datasets and used AB-Score as a new evaluation method to evaluate RebarDet. The experimental results show that RebarDet can achieve a detection accuracy of up to 0.8114 and a model inference speed of 6.9 fps while maintaining a moderate amount of parameters, which is superior to other mainstream object detection models and verifies the effectiveness of our proposed method. At the same time, RebarDet’s high precision detection of round tubular objects facilitates enterprise intelligent manufacturing processes.
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