Earticle

The environment refers to what is surrounded by something during human life. This environment is related to the way humans live, and presents various problems on how to perceive the surrounding environment and how the behaviors that constitute the environment support the elements necessary for human life. Humans have an interest in the supportability of the environment as the interrelationship increases as humans perceive and understand the environment and accept the factors supported by the environment. In space, human movement starts from one space to the next and exchanges stimuli and reactions with the environment until reaching a target point. These human movements start with subjective judgment and during gait movement, the spatial environment surrounding humans becomes a collection of information necessary for humans and gives stimulation. will do. In this process, in particular, humans move along the movement path through movement in space and go through displacement perception and psychological changes, and recognize a series of spatial continuity. An image of thinking is formed[1]. In this process, spatial experience is perceived through the process of filtering by the senses in the real space, and the result of cognition is added through the process of subjective change accompanied by memory and knowledge, resulting in human movement. As such, the spatial search behavior begins with a series of perceptual and cognitive behaviors that arise in the process of human beings trying to read meaning from objects in the environment. Here, cognition includes the psychological process of sorting out and judging what the information is in the process of reading the meaning of the external environment, conditions, and material composition, and perception is the process of accepting information as the first step. It can be said to be the cognitive ability to read the meaning of the environment given to humans. Therefore, if we can grasp the perception of space while moving and human behavior as a response to perception, it will be possible to predict how to grasp it from a human point of view in a space that does not exist. Modern people have the theme of reminiscing dog-friendly hotels for the healing of petloss syndrome, and this thesis attempts to approach the life of companions.

In the era of the pandemic, the importance of a wireless LAN environment has become increasingly important, especially as the era of smart working and non-face-to-face education has become a universal and daily routine. Smartphones, tablets, laptops, PCs, smart watches, and wearable devices, collective referred to as wireless terminals, can be accessed anytime and anywhere through the internet, allowing for consistent and constant access to offices, factories, warehouses, shopping malls, railways, hotels, hospitals, schools, logistics centers, airports, exhibition halls, etc. This sort of access is currently being used in roads, parks, traditional markets, and ports. Since the release of the IEEE 802.11 Legacy Standard in 1997, Wi-Fi technology has been continuously supplemented and revised, and the standard has been continuously developed. In the era of smart working, the importance of efficient wireless deployment and scientific design has become more important. The importance of wireless in the smart factory, in the metaverse era, in the era of pursuing work and life that transcend time and space by using AR, VR, MR, and XR, it is more urgent to solve the shadow area of Wi-Fi. Through this study, we intend to verify the wireless failure problem of the xr training center and suggest improvement measures.

The aim of this study is to investigate the relationship between the object ability, basic movement ability, and mathematical ability of young children. Next, through this study, the influence of young children’s object manipulation ability and basic movement ability on mathematical ability was investigated. The subjects of this study were 80 children aged 5 years old. As a research tool, the non-mobile movement and mobile movement, the basic movement development test scale, and the young children’s picture-mathematical ability test scale were used. This survey was conducted from October 2018 to January 2019. For data analysis, correlation analysis and hierarchical multiple regression analysis were performed using the spss program. As a result of the study, it was found that there was a significant positive correlation between the non-mobile ability, movement ability, object manipulation ability and mathematical ability of young children. It was found that young children’s ability to manipulate objects and non-movement abilities had positive effect on their mathematical abilities. The movement ability of young children had both negative and positive effects on mathematical ability, but it was not found to be statistically significant. This study is meaningful in that it investigated the effects of non-mobile movement, mobile movement ability, and object manipulation ability, which are sub-capabilities of basic movement ability, which had not been investigated so far, on the mathematical ability of young children.

Korea is facing a number difficulties arising from rising housing prices. As ‘housing’ takes the lion’s share in personal assets, many difficulties are expected to arise from fluctuating housing prices. The purpose of this study is creating housing price prediction model to prevent such risks and induce reasonable real estate purchases. This study made many attempts for understanding real estate instability and creating appropriate housing price prediction model. This study predicted and validated housing prices by using the LSTM technique - a type of Artificial Intelligence deep learning technology. LSTM is a network in which cell state and hidden state are recursively calculated in a structure which added cell state, which is conveyor belt role, to the existing RNN’s hidden state. The real sale prices of apartments in autonomous districts ranging from January 2006 to December 2019 were collected through the Ministry of Land, Infrastructure, and Transport’s real sale price open system and basic apartment and commercial district information were collected through the Public Data Portal and the Seoul Metropolitan City Data. The collected real sale price data were scaled based on monthly average sale price and a total of 168 data were organized by preprocessing respective data based on address. In order to predict prices, the LSTM implementation process was conducted by setting training period as 29 months (April 2015 to August 2017), validation period as 13 months (September 2017 to September 2018), and test period as 13 months (December 2018 to December 2019) according to time series data set. As a result of this study for predicting ‘prices’, there have been the following results. Firstly, this study obtained 76 percent of prediction similarity. We tried to design a prediction model of real estate transaction price with the LSTM Model based on AI and Bigdata. The final prediction model was created by collecting time series data, which identified the fact that 76 percent model can be made. This validated that predicting rate of return through the LSTM method can gain reliability.

After extracting the calcium component from the KR slag and the converter slag using ammonium chloride solution, the extract was reacted with carbon dioxide to synthesize precipitated calcium carbonate (PCC). In order to understand the effect of ultrasonic waves on calcium extraction from slags and calcium carbonate synthesis, the efficiency of calcium carbonate synthesis according to the with or without of ultrasonic waves was analyzed. The synthetic efficiency of PCC was investigated according to various experimental conditions, and the synthesized calcium carbonate was analyzed using XRD and SEM. In both slags, the amount of PCC decreased as the reaction temperature increased. The pH at the end of the experiment capable of synthesizing the maximum PCC in the carbonation reaction was 7 (irradiated with ultrasound) and 8 (irradiated without ultrasound), respectively. Because the pH of the extraction filtrate is different when irradiated with or without ultrasound, the pH was adjusted to 9 by injecting an additive (10 M NaOH) before the carbonation experiment, and then the experiment was performed. When calcium was extracted from KR slag, the crystal phase appeared as calcite regardless of the pH at the end of the experiment. However, when calcium was extracted from the converter slag and the pH was set to 7 at the end of the experiment, the crystal phase of PCC appeared as a mixture of calcite and vaterite.

COVID-19 is a crisis with numerous casualties. The World Health Organization (WHO) has declared the use of masks as an essential safety measure during the COVID-19 pandemic. Therefore, whether or not to wear a mask is an important issue when entering and exiting public places and institutions. However, this makes face recognition a very difficult task because certain parts of the face are hidden. As a result, face identification and identity verification in the access system became difficult. In this paper, we propose a system that can detect masked face using transfer learning of Yolov5s and recognize the user using transfer learning of Facenet. Transfer learning preforms by changing the learning rate, epoch, and batch size, their results are evaluated, and the best model is selected as representative model. It has been confirmed that the proposed model is good at detecting masked face and masked face recognition.

Occupational safety accidents are caused by various factors, and it is difficult to predict when and why they occur, and it is directly related to the lives of workers, so the interest in safety accidents is increasing every year. Therefore, in order to reduce safety accidents at industrial fields, workers are required to wear personal protective equipment. In this paper, we proposes a method to automatically check whether workers are wearing safety helmets among the protective equipment in the industrial field. It detects whether or not the helmet is worn using YOLOv5, a computer vision-based deep learning object detection algorithm. We transfer learning the s model among Yolov5 models with different learning rates and epochs, evaluate the performance, and select the optimal model. The selected model showed a performance of 0.959 mAP.

The smart tourism service provides services such as travel planning and tour guides to tourists using key technologies of the 4th industrial revolution, such as the Internet of Things, communication infrastructure, big data, artificial intelligence, AR/VR, and drones. We are developing smart tourism services such as recommended travel products, my travel itinerary, tourism information, and chatbots for tourists through the smart tourism app. In this paper, we develop a smart tourism service system that provides real-time location-based tourism information and weather information to tourists. The smart tourism service system consists of a smart tourism app, a smart tourism information system, and an IoT data collection device. The smart tourism information system receives weather information from the IoT data collection device installed in the tourist destination. The location-based smart tourism service is provided as a smart tourism app in the smart tourism information system according to the Beacon’s UUID in the IoT data collection device. The smart tourism information system stores the Beacon’s UUIDs received from tourists and provides a safe hiking service for tourists.