Locating Power and Decision-Making： Social Production of Space in Juiz de Fora, Brazil

This paper aims to discuss how the shaping of a city, Juiz de Fora, in Brazil, has resulted from the power of location of some social agents and from their disputes on the production of space. First, it introduces the concept of social production of space, emphasizing the role of social agents in urban processes. Then, it presents specific aspects of the history of Juiz de Fora＂ its origins and how social agents and forces have played a significant role in shaping the built environment of the city--specially represented by main streets of the city. The paper studies how the social agents, with their different visions and goals, have influenced the process of formation and development of the city. This demonstrates the complexity of the existing relationships between the built environment and the social context that is specific to the city. Different urban forces fight for city spaces, construct and modify its territory so that their needs are fulfilled. Their strength, their experiences and efforts, and their ideas of a city are inscribed in urban landscapes; in similar ways, these are revealed by the city paths we follow here.

Convolutional Neural Network Model for Fire Detection in Real-Time Environment

Disasters such as conflagration,toxic smoke,harmful gas or chemical leakage,and many other catastrophes in the industrial environment caused by hazardous distance from the peril are frequent.The calamities are causing massive fiscal and human life casualties.However,Wireless Sensors Network-based adroit monitoring and early warning of these dangerous incidents will hamper fiscal and social fiasco.The authors have proposed an early fire detection system uses machine and/or deep learning algorithms.The article presents an Intelligent Industrial Monitoring System(IIMS)and introduces an Industrial Smart Social Agent(ISSA)in the Industrial SIoT(ISIoT)paradigm.The proffered ISSA empowers smart surveillance objects to communicate autonomously with other devices.Every Industrial IoT(IIoT)entity gets authorization from the ISSA to interact and work together to improve surveillance in any industrial context.The ISSA uses machine and deep learning algorithms for fire-related incident detection in the industrial environment.The authors have modeled a Convolutional Neural Network(CNN)and compared it with the four existing models named,FireNet,Deep FireNet,Deep FireNet V2,and Efficient Net for identifying the fire.To train our model,we used fire images and smoke sensor datasets.The image dataset contains fire,smoke,and no fire images.For evaluation,the proposed and existing models have been tested on the same.According to the comparative analysis,our CNN model outperforms other state-of-the-art models significantly.

What Preteen Girls Learn About Gender Roles From Celebrities

A face-to-face qualitative interview study was conducted to examine the perceived gender roles and gender identities among 10 to 12 years old girls in Hong Kong. Sixteen girls aged 10 to 12 were asked to take pictures from the media they consumed that illustrated ＂What girls or women should or should not be; and what girls or women should or should not do＂. Analysis of interviews and images captured found that celebrities and characters in popular media play a significant role in socializing preadolescent girls on gender roles and gender identity formation. Celebrities and media characters that caught the interviewees＇ attention were mainly female adult entertainers and media characters. Girls showed admiration of specific talents and personalities of the celebrities and media characters. They paid much attention to the private lives of the celebrities. They learned from celebrities and media characters that certain behaviors were not acceptable in the social arena.