A New High-Precision and Lightweight Detection Model for Illegal Construction Objects Based on Deep Learning

Illegal construction has caused serious harm around the world. However, current methods are difficult to detect illegal construction activities in time, and the calculation complexity and the parameters of them are large. To solve these challenges, a new and unique detection method is proposed, which detects objects related to illegal buildings in time to discover illegal construction activities. Meanwhile, a new dataset and a high-precision and lightweight detector are proposed. The proposed detector is based on the algorithm You Only Look Once (YOLOv4). The use of DenseNet as the backbone of YDHNet enables better feature transfer and reuse, improves detection accuracy, and reduces computational costs. Meanwhile, depthwise separable convolution is employed to lightweight the neck and head to further reduce computational costs. Furthermore, H-swish is utilized to enhance non-linear feature extraction and improve detection accuracy. Experimental results illustrate that YDHNet realizes a mean average precision of 89.60% on the proposed dataset, which is 3.78% higher than YOLOv4. The computational cost and parameter count of YDHNet are 26.22 GFLOPs and 16.18 MB, respectively. Compared to YOLOv4 and other detectors, YDHNet not only has lower computational costs and higher detection accuracy, but also timely identifies illegal construction objects and automatically detects illegal construction activities.

Construction and application of an assessment index system for evalu ating the eco-community’s sustainability

An assessment index system including environment, socio-culture, economy and technology was established for evaluating environmental construction level of community （objective construction）, and questionnaire was designed according to paper review for evaluating residential satisfaction （subjective satisfaction）. The index system was divided into four layers： system （A）, subsystems （B）, categories （C）, and indicators （D）, and in total of 38 indicators was established. The Xihe community, affiliated to Nanfen district, Benxi City, Liaoning Province, China was selected as a case study. Results indicated that the community sustainability index related to objective environmental construction was 0.4355 and was classified as class Ⅲ （moderate）; the community sustainability index related to the residential satisfaction was 0.4255, belonging to class Ⅲ. In conclusion, the sustainability of Xihe community was moderate and needed to be improved. Residential satisfaction was lower than objective environmental construction. The assessment index system established in this study is able to reflect the comprehensive sustainability of community and can be used to evaluate other similar communities＇ sustainability.

Language Transfer Evidence in the Acquisition of Double Object Construction by Chinese EFL Learners

Based on the theory of language transfer in second language acquisition, this study explored the dynamic acquisition of English double object construction by Chinese EFL learners through comparative analysis. Altogether 120 subjects participated in this experiment and were required to take the proofreading exercise in limited time. The experimental results showed that Chinese EFL learners at different levels of proficiency acquired the core subclass of double object construction better than peripheral ones;meanwhile, learners at higher levels of proficiency outperformed those at lower levels, especially in the peripheral types. Relevant theoretical interpretations were given thereafter to the above research findings, with the hope to shed some light on the learning of double object construction by Chinese EFL learners.

Construction of Vertical Wind Profile from Satellite-Derived Winds for Objective Analysis of Wind Field

During summer Monex-79, a variety of observing systems viz. research ships, research aircrafts, constant pressure balloons and geostationary satellite etc. were deployed, besides the regular conventional observations. The purpose of these additional systems was to make the best possible data for the studies on various aspects of monsoon circulation. The present study is aimed at the construction of vertical wind profile using cloud motion vectors obtained from GOES (I-O) satellite and to examine whether the constructed wind profiles improves the representation of the monsoon system, flow pattern etc. in the objective analysis. For this purpose, climatological normals of the wind field are considered as the initial guess and the objective analyses of the wind field are made with, first using only data from conventional observations over land areas, subsequently including the constructed winds from cloud motion vectors. These analyses are then compared with the standard analyses of wind field obtained from Quick Look Atlas by T. N. Krishnamurti et al. (1979).It is inferred that satellite estimated mean wind profiles show good agreement with the mean wind profiles of the research ships with RMS errors less than 5 mps below 500 hPa and less than 8 mps above 500 hPa. It is further inferred that the inclusion of constructed winds shows a positive impact on the objective analysis and improvement is seen to be more marked in the data-sparse region of the Arabian sea. Analyses which include the constructed winds show better agreement with the standard analysis, than the analyses obtained using only conventional winds. Thus, results of our study suggest that the wind profiles constructed using cloud motion vectors are of potential use in objective analysis to depict the major circulation features over the Indian region.

IoT in Building Process:A Literature Review

The pervasive diffusion of digital technologies opened up to new concepts in managing and monitoring the processes occurring in our society.Information and Communication Technologies(ICTs)become enabling tools to rethink our way of living,consuming and producing goods and services.Among these,the Internet of Things(IoT)represents the disruptive technology that may redefine the stages of the building process to meet renewed environmental challenges.This new technological paradigm imports in the Architecture,Engineering and Construction(AEC)sector new and not-tectonic instances.In this context,the paper maps the experiences related to the use of IoT for managing the building process.Through a systematic literature review,the article highlights the potential benefits generable by a widespread integration of IoT in the AEC sector.In particular,the article has three purposes:defining the IoT infrastructure for its proper application in the AEC sector;identifying IoT main application domains;investigating the integration modalities.

The Unlikely Objects of 吃（Chi）

Drawing on cognitive linguistic theories, this study investigates the various meanings of the Chinese verb 吃（chi） and the types of objects that it takes. It is concluded that the many meanings of吃 are organized in a radial network, with the primary meaning at the center and extended meanings at the periphery and that extended meanings are derived from, and thus can be traced back to, the primary meaning. This study also suggests that the productivity of the 吃 ＋ object construction is affected by the meaning of 吃, the interpretation of its objects, as well as social and linguistic convention.

Monthly Monetary Planning for China via Applying Method of Constructing Objective Function

Many economic problems can be formulated as optimization problems. Econometricians have long devoted their efforts to construct the econometric equation systems, while the corresponding objective functions receive few attentions. In recent twenty years, some techniques to construct the objective functions with economic implications have been developed, which might have a potential in economic decision-making. In the paper we app1y the method of constructing objective function to design an optimization model for monthly monetary planning of China. The real monthly data from l991 to l999 are used to evaluate the monthly economic situation. Our empirical experiment shows that the model gives a good short-term forecasting.