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Safety can be defined as being maintained or reduced to a level below which the possibility of human or physical harm can be tolerated through continuous identification of risks and safety risk management. FAA, EASA, IATA and Boeing, major organizations that conduct research and analysis for aviation safety around the world, report that about 70 percent of aviation accidents are caused by human factors, which have led to a surge in interest in human factors-induced accident prevention activities around the world. As part of this purpose, the FAA in the U.S. is raising awareness among aviation workers by publicizing the 12 human errors (Boeing, 2016), which account for the largest part of aviation accidents under the theme of Dirty Dozen, to prevent aviation accidents. Therefore, based on the domestic helicopter accidents reported to the Air Railroad Accident Investigation Committee from 2007 until recently, this study aims to use HFACS to extract human factors for the six recent helicopter accidents in Korea, analyze the extracted human factors in conjunction with the Dirty Dozen concept, and then present measures to prevent accidents by item

This paper proposed the design of a new window signage system architecture, which utilized a window of a building, with attached LED for visible light communication. In this paper, the proposed method using the LED strip to transmit light data and receive the data through a HMD with a smart device camera. The LED strip attached to the existing building window, as a part of semi-transparent signage. Semi-transparent signage based on a controllable LED strip-modules and attached to the window used to provide entertainment contents and the information service to people through optical camera communication (OCC) as well. Also, this work suggests using the camera supplied Head Mounted Device (HMD) as an OCC receiver. The LED attached window signage system structure described in this paper can be utilized in various buildings infrastructure like house, shopping areas, industrial building, etc.

In the fifth generation (5G) and beyond 5G (B5G) mobile communication, non-orthogonal multiple access (NOMA) has attracted great attention due to higher spectral efficiency and massive connectivity. We investigate the impacts of the channel estimation errors on the bit-error rate (BER) of NOMA, especially with the single-user decoding (SUD) receiver, which does not perform successive interference cancellation (SIC), in contrast to the conventional SIC NOMA scheme. First, an analytical expression of the BER for SUD NOMA with channel estimation errors is derived. Then, it is demonstrated that the BER performance degrades severely up to the power allocation less than about 20%. Additionally, we show that for the fixed power allocation of 10% in such power allocation range, the signal-to-noise (SNR) loss owing to channel estimation errors is about 5 dB. As a consequence, the channel estimation error should be considered for the design of the SUD NOMA scheme

There are many airline customer evaluation data, but they are insufficient in terms of predicting customer satisfaction in practice. In particular, they are generally insufficient in case of verification of data value and development of a customer satisfaction prediction model based on customer evaluation data. In this paper, airline customer satisfaction analysis is conducted through an experiment of correlation analysis between customer evaluation data provided by Google's Kaggle. The difference in accuracy varied according to the three types, which are the overall variables, the top 4 and top 8 variables with the highest correlation. To build an airline customer satisfaction prediction model, they are applied to three classification algorithms of Random Forest, SVM, DNN and conduct a classification experiment. They are divided into training data and verification data by 7:3. As a result, the DNN model showed the lowest accuracy at 86.4%, while the SVM model at 89% and the Random Forest model at 95.7% showed the highest accuracy and performance.

Nowadays, distributed mobility management (DMM) approaches have been widely adopted to address the limitations of centralized architectural methods to support seamless data transmission schemes in wireless sensor networks. This paper deals with the end-to-end (E2E) integration of Network Mobility (NEMO) basic support protocol in distributed wireless sensor network systems in structural health and environmental monitoring of social overhead capital (SOC) public infrastructures such as bridges, national highways, tunnels, and railroads. The proposed scheme takes advantage of the features of both the NEMO basic support protocol and partially distributed network-based DMM framework in providing seamless data transmission and robust mobility support. The E2E seamless data transmission scheme allows mobile users to roam from fixed-point network access locations and mobile platforms (i.e., vehicles such as cars, buses, and trains) without disconnecting its current sessions (i.e., seamless handover).

YouTube, the online video streaming platform, has become popular and influential around the globe. Due to the development of science and technology, people without expertise in filming can now easily produce their videos with unique content. Many people are more eager to become a popular YouTube creator because they can earn money by placing commercials or Products in Placement (PPL) in their video clips. However, it is yet unknown what genres of YouTube videos are popular. YouTube creators have their channels where they upload videos of a certain type of genre. This study investigates video genres of the top 250 YouTube channels in English-speaking countries (United States, Canada, United Kingdom, and Australia) using Social Blade, which is a research website. The ranking is set based on the number of times people watched a video (“Video Views”). We handsomely analyze popular genres of the channels and also the YouTube ecosystem, and it will be meaningful for today’s new media era.

Researchers recognized air pollution changes causing diseases and difficulties in living due to environmental pollution following various human activities, and have studied how to avoid fine dust harmful to the human respiratory system to be healthy. To this end, Arduino is used to equip fine dust level sensors in drones to measure the fine dust levels, visualize the measurements with LED indicator colors depending on the measurements to inform users of the danger of fine dust, and use the benefits of drones to specify dangerous fine dust zones and measure the fine dust levels. Users can see the changes depending on the fine dust levels in real time with the LED indicators. This will contributes to measuring fine dust levels easily in dangerous areas. Mission Planner (ArduPilot) is used to set up the GPS of drone, and store the data from the dust sensor as contents. This study aims to establish a method for improving the environment to measure fine dust levels with drones with LED indicators for fine dust, and reduce fine dust.

This study aims to apply Arduino and 3D printing technology considered as a key subject in the age of 4th industrial revolution which is a step 1 for customizing and applying the process of production by chemical molding companies producing environment-friendly biodegradable packaging materials to the 3D printing teaching in universities. Step 3 is applied to IoT for Arduino application, and 3D printing technology is also used on the basis of teaching creative integrated human resource. Integration of Arduino with 3D printers is based on the assumption that middle- and high-school students can learn it step by step to higher levels and university students majoring or not majoring in computing science can also have computing skills for solving 3D printing-based problems. For IoT application in this study, the 3D printing technology is applied to the external shape of products for producing an Arduino-based lighting fixture. The applied 3D printing technology is further extended to teaching modeling of producing packaging materials by chemical product molding companies in the age of 4th industrial revolution.

As mobile device usage time increases thanks to the development of information and communication alongside the increase in the spread of smartphones, mobile shopping has become a common trend. While mobile shopping has the advantage of saving both time and money, it may also result in dissatisfaction with product differences after purchase. For online clothing shopping malls, in particular, if the size does not match after purchase, it is difficult for customers to return or exchange the goods. To address this problem, some mobile apparel shipping malls offer a virtual fitting service and a size comparison function; however, the number of such malls remains low. In this paper, a usability evaluation was performed on a mobile apparel shopping mall that provides a size comparison function. The three apps selected for evaluation have different size input methods, and a slightly different method of providing results after comparing the user's dimensions with the dimensions of the clothes to be purchased. In this paper, the evaluators were asked to select clothes at the shopping mall and perform the task of deciding the size of the clothes to be purchased through their own measurements and comparison while also evaluating the effectiveness, meaning, and satisfaction of the apps. Based on the analysis of the results, this paper aims to produce an improvement plan and help design the size comparison UI (User Interface) in the future.

Traffic accidents due to excessive speed frequently occur in places where traffic signal controllers are installed, places where sharp curves exist, or places where the traffic signal cycle does not match the current time. These traffic accidents cause economic loss due to the destruction of road facilities and structures, and cause a big problem of increasing the number of traffic accident deaths. When a traffic accident occurs, leaving a tire mark before or after a car crash, pre-collision speed of the car is calculated using the law of conservation of momentum or the skid mark formula. In the skip skid mark generated in ABS brake vehicles and the comb-shaped yaw mark generated by tire trace caused by lateral sliding, there is a difference of 30-40% in the reliability of the vehicle speed calculated by the smite mark. In this paper, we propose an algorithm that can improve the calculation reliability in vehicle speed by using skid marks in order to compensate for this problem. In addition, we present an intelligent speed calculation algorithm for traffic safety and a computer simulation in order to prevent traffic accidents by estimating the speed of a vehicle, using Skid marks, Yaw marks, and ABS brake characteristics and fuzzy rules.

A recent study to determine the fall is focused on analyzing fall motions using a recurrent neural network (RNN), and uses a deep learning approach to get good results for detecting human poses in 2D from a mono color image. In this paper, we investigated the improved detection method to estimate the position of the head and shoulder key points and the acceleration of position change using the skeletal key points information extracted using PoseNet from the image obtained from the 2D RGB low-cost camera, and to increase the accuracy of the fall judgment. In particular, we propose a fall detection method based on the characteristics of post-fall posture in the fall motion analysis method and on the velocity of human body skeleton key points change as well as the ratio change of body bounding box’s width and height. The public data set was used to extract human skeletal features and to train deep learning, GRU, and as a result of an experiment to find a feature extraction method that can achieve high classification accuracy, the proposed method showed a 99.8% success rate in detecting falls more effectively than the conventional primitive skeletal data use method.

Shipyards are potential environments for using IoT services, sensor networks, and delay tolerant networks. Simulations of those services and networks strongly rely on human mobility models. Results obtained with an unrealistic model may not reflect the true performance of applications, protocols, and algorithms in a shipyard. A lot of synthetic models for human movements have been studied but most of them are generic and focus on the daily movements of humans on city scales. Nevertheless, workers in shipyards have unique movement characteristics such as movement speed, pause time, and attractions places. For instance, workers usually move to some places, where they work, and rarely move to other places in the factory. Movement characteristics of workers not only depend on workers but also on tasks, which they do. For instance, workers, who paint ships, have similar movement speed and pause time. Hence, in this paper, human movements in shipyards are studied. We propose a new human mobility model called the human mobility mode in shipyards (MIS). In MIS, workers are classified into multiple types. Movement characteristics of a worker are similar to other workers in the same type. Based on the visiting probability, workers have some places, where they frequently visits, and some places, where they rarely visit. We analyze real mobility traces and studie to achieve human movement characteristics from real traces. The results show that MIS provides a well-match to the movement characteristic from real traces.

One of the key features of a mobile crowd-sensing (MCS) system is task allocation, which aims to recruit workers efficiently to carry out the tasks. Due to various constraints of the tasks (such as specific sensor requirement and a probabilistic guarantee of task completion) and workers heterogeneity, the task allocation become challenging. This assignment problem becomes more intractable because of the deadline of the tasks and a lot of possible task completion order or moving path of workers since a worker may perform multiple tasks and need to physically visit the tasks venues to complete the tasks. Therefore, in this paper, a hybrid search algorithm for task allocation called HST is proposed to address the problem, which employ a traveling salesman problem heuristic to find the task completion order. HST is developed based on the tabu search algorithm and exploits the premature convergence avoiding concepts from the genetic algorithm and simulated annealing. The experimental results verify that our proposed scheme outperforms the existing methods while satisfying given constraints.

As a decrease in labor became a serious issue in the manufacturing industry, smart factory technology, which combines IT and the manufacturing business, began to attract attention as a solution. In this study, we have designed and implemented a real-time remote management system for smart factories, which is connected to an IoT sensor and gateway, for plastic manufacturing plants. By implementing the REST API in which an IoT sensor and smart gateway can communicate, the system enabled the data measured from the IoT sensor and equipment status data to the real-time monitoring system through the gateway. Also, a web-based management dashboard enabled remote monitoring and control of the equipment and raw material processing status. A comparative analysis experiment was conducted on the suggested system for the difference in processing speed based on equipment and measurement data number change. The experiment confirmed that saving equipment measurement data using cache mechanisim offered faster processing speed. Through the result our works can provide the basic framework to factory which need implement remote management system.

After the THAAD crisis, Goyang city's Global Medical Service performance is showing a sharp decline compared to other cities and provinces. In particular, the contraction of participants who can create policy outcomes such as Medical Institutions and Attracting companies has emerged as the biggest problem. Therefore, Goyang City wanted to derive effective marketing policies and establish marketing policies according to their priorities in order to prevent the deaths of the future patient visitor market as well as performance. In order to examine such policy needs more closely, this paper reviewed the Global Medical Service policies of Goyang City based on AHP analysis, and derived a ranking of 28 major policies and preferred policies for each participant. In the future, Goyang City is expected to derive major policy effects by applying the results of this study to the establishment of marketing policies through customized policies for each medical institution type and Patient attraction company.

In this paper, we presented a simple hologram recording set for learners to broaden their program choices and experience holographic techniques with lifelong education programs. In order to obtain quality 3D images, the quality of light sources and recording mediums, which are the main elements of hologram recording, must be good. In addition, due to the characteristics of the hologram, the ambient vibrations shall be minimized for accurate interference pattern recording. The simple hologram recording set presented in this paper has not significantly restricted in space and location, and anyone can easily experience it at a reasonable price compared to the existing hologram production method. Also, it can make two different type of hologram (transmission and reflection) for providing easy access to recording and reconstruction of the hologram. Experiments have shown that holographic manufacturing practices are a very useful way to educate the public on optics and photonics technologies.

The Corona 19 pandemic is bringing a big change in the fields of politics, economy, society, culture, environment, ecosystem, science and technology, and business management activities and advertising. Therefore, in this study, after the Corona 19 pandemic, we predicted how the characteristics of future advertising and the types of future advertising will change . and we studied countermeasures. We used, a method of analyzing related literature and the Delphi Survey method predicting the future, as a research method. As expert Panel, the subject of the Delphi technique survey, we recruited 30 experts in the field of advertising and future fields with professional insight. We study to predict how the characteristics of future advertising and the types of future advertising will change according to changes in the advertising environment such as social changes, business changes, and consumer changes after the Corona 19 pandemic. In order to cope with these changes in future advertising, it is necessary to actively prepare the advertising industry and advertising experts. Therefore, we suggested countermeasures so that the advertising industry and advertising experts can understand and respond for future advertising changes.

This study investigated learners' perceptions of using self-generated listening materials based on Text to Speech. After taking an online training session to learn how to make listening materials for extensive listening practice outside the classroom, the learners were engaged in practice with self-generated listening materials for 10 weeks in a self-directed way. The results show that a majority of the learners found the TTS-based listening materials helpful to reduce anxiety toward listening and enhance self-confidence and motivation, with a positive effect on improving their listening ability. The learners’ general satisfaction can be attributed to some beneficial features of TTS-based listening material, including freedom to choose what they want to learn, convenient accessibility to the material, availability of various native speakers' voices, and novelty of digital tools. This suggests that TTS-based digital listening materials can be a useful educational tool to support learners’ self-directed listening practice outside the classroom in EFL settings.

We study empirically analyzed the final 216 copies of the responses from SME organization members in Seoul and Gyeonggi regions using statistical programs of SPSS24.0 and AMOS 24.0. In other words, the effect of job satisfaction on the organizational culture and job environment characteristics perceived by members of the organization, and the relationship between job satisfaction and job performance is shown as follows. First, the organizational culture of consensus, development, hierarchy, and rationality was statistically significant in job satisfaction. Therefore, the hypothetical one-man organizational culture was adopted by showing a positive (+) effect on job satisfaction. Second, job environment characteristics such as autonomy in job performance, compensation system, physical environment, and human environment had a positive effect on job satisfaction. That is, the job environment characteristics of hypothesis 2 were adopted as a positive (+) influence relationship on organizational satisfaction. Third, job satisfaction was expressed as a positive (+) influence relationship with job performance, so hypothesis 3 was adopted. As a result of this study, the higher the organizational member's perception of organizational culture and job environment characteristics is, the higher the job satisfaction is, and the improvement in job satisfaction is meaningful in that it provides theoretical and practical implications that indicate job performance.

Video streaming application such as YouTube is one of the most popular mobile applications. To adjust the quality of video for available network bandwidth, a streaming server provides multiple representations of video of which bit rate has different bandwidth requirements. A streaming client utilizes an adaptive bit rate scheme to select a proper video representation that the network can support. The download behavior of video streaming client player is governed by several parameters such as maximum buffer size. Especially, the size of the maximum playback buffer in the client player can greatly affect the user experience. To tackle this problem, in this paper, we propose the maximum buffer size optimization according to available network bandwidth and buffer status. Our simulation study shows that our proposed buffer size optimization scheme successfully mitigates playback stalls while preserving the similar quality of streaming video compared to existing ABR schemes.

In this study, we present the difference in thoracic reposition sense in young people (24.00 ±2.20 years old) with and without habitual slouched posture in two target positions of half flexion and half extension. People with habitual slouched posture (n = 20; 11 men and 9 women) and people without slouched posture (n = 20; 10 men and 10 women) were recruited from three universities. Thoracic spine (T-spine) repositioning errors were measured in two target positions (half flexion and half extension). People with habitual slouched posture showed significantly higher thoracic repositioning error in the extension target position than did people without slouched posture (P<0.05). There was no difference in repositioning error in the flexion target position between the two groups (P>0.05). In conclusion, people with habitual slouched posture show lower T-spine repositioning sense in extension than do people without slouched posture. A rehabilitation program to treat habitual slouched posture, such as postural correction education, should be implemented for individuals with decreased position sense of the T-spine.

Security threats are increasing with interest due to the mass spread of smart devices, and vulnerabilities in developed applications are being exposed while mobile malicious codes are spreading. The government and companies provide various applications for the public, and for reliability and security of applications, security checks are required during application development. In this paper, among the security threats that can occur in the mobile service environment, we set up the vulnerability analysis items to respond to security threats when developing Android-based applications. Based on the set analysis items, vulnerability analysis was performed by examining three applications of public institutions and private companies currently operating as mobile applications. As a result of application security checks used by three public institutions and companies, authority management and open module stability management were well managed. However, it was confirmed that many security vulnerabilities were found in input value verification, outside transmit data management, and data management. It is believed that it will contribute to improving the safety of mobile applications through the case of vulnerability analysis for Android application security.

Purpose: This study aimed to review the recent scientific literature regarding nursing care of arteriovenous fistula (AVF) for the patients with Chronic Renal Failure (CRF) undergoing hemodialysis. Methods: An integrative review was conducted and articles were searched from Cochrane library, Medline, PubMed, Science direct and CINAHL databases by using the terms “nursing”, ‘Chronic Renal Failure’, ‘Haemodialysis’, renal failure’, ‘or ‘AV Fistula’ nursing care’, ‘self-care’. The inclusion criteria were articles published in English in the year of 2015-2020 with availability of free full text. Reviewed data were carefully analyzed and charted regard to the nursing care of the patient with AVF. Results: 12 articles papers met the inclusion criteria. Three themes were derived from the data: (a) Intervention (b). Patient and nurse education (c) KPA Assessment of (Knowledge, Practice and Attitude) Conclusions: This review indicates the challenges that nursing care of AVF patients undergoing hemodialysis. The identified themes can be used in the development of more effective educational- programs. Future studies should focus on the development and evaluation of educational programs that include these selected themes.

In this study, we tried to explore the actual direction for the play culture by looking at the social perception of the change of play culture due to the Corona 19 using big data analysis. For this research, we used Textom, a website specializing in collecting big data, and collected 10,216 data using keywords of "Corona + Play," "Play Culture" and "Leisure" from January 19, 2020 to September 30, 2020, when the first confirmed case of Corona 19 occurred in Korea on various portal sites at home and abroad. The results of this paper showed that the social perception of the play culture in Corona 19 was 51.61%, not much different from the negative image of 48.15%. It is necessary to develop a play culture program that can identify people's various desires and emotions under the premise that situations similar to the current With Corona period and Corona19 can occur at any time, and find mental and physical stability and vitality in unstable situations. In addition, the results of this study can be used as basic data for the development of play culture policies or programs, with the significance that this study helped vitalize big data utilization research in the fields of play, leisure, and culture.

The era of the 4th industrial revolution is a complex environment in which the cyber world and the physical world are integrated and interacted. In order to successfully implement and be sustainable the 4th industrial revolution of hyper-connectivity, hyper-convergence, and hyper-intelligence, not only the technological aspects that implemented digitalization but also the social aspects must be recognized and dealt with as important. There are socio-technical systems and socio-technical systems theory as concepts that describe systems involving complex interactions between the environmental aspects of human, mechanical and tissue systems. This study confirmed how the Socio-technical System was applied in the research literature for the last 10 years through machine learning-based analysis. Eight clusters were derived by performing co-occurrence keywords network analysis, and 13 research topics were derived and analyzed by performing a structural topic model. This study provides consensus and insight on the social and technological perspectives necessary for the sustainability of the 4th industrial revolution.

We studied on the design of a sprinkler control system that communicates with the administrator's mobile through a wireless communication network and a sprinkler unit that sprays water on the vegetation area. This sprinkler control system consists of a communication module that receives an operation signal for the operation of the sprinkler unit from the administrator's mobile, and a control module that controls the sprinkler unit according to the operation signal received through the communication module. It is also designed to control sprinkler units by measuring temperature, humidity, light intensities, vibration and field images in the vegetation area in real time through sensors and camera for each of them and comparing them with established limit criteria. The sprinkler allows the administrator to control the sprinkler more easily because the administrator operates the sprinkler through the mobile from a distance, and emergency situations occur and can respond quickly.

The purpose of this paper is to establish an IoT-based big data platform that can check the space and form analysis in various play cultures of children. Therefore, to this end, in order to understand the healthy play culture of children, we are going to build a big data platform that allows IoT and smart devices to work together to collect data. Therefore, the goal of this study is to develop a big data platform linked to IoT first in order to collect data related to observation of children's mobile movements. Using the developed big data platform, children's play culture can be checked anywhere through observation and intuitive UI design, quick information can be automatically collected and real-time feedback, data collected through repeaters can be aggregated and analyzed, and systematic database can be utilized in the form of big data.

In order to maximize the production of landscape plants in optimal condition while coexisting with the environment in terms of precision agriculture, quick and accurate information gathering of the internal environmental elements of the growing container is necessary. This may depend on the accuracy of the positioning of numerous sensors connected to landscape plants cultivating system (LPCS) in containers. Thus, this paper presents a method for estimating the location of the sensors related to cultivation environment connected to LPCS by measuring the received signal strength (RSS) or time of arrival TOA received between oneself and adjacent sensors. The Small sensors connected to the LPCS of container are known for their locations, but the remaining locations must be estimated. For this in the paper, Rao-Cramer limits and maximum likelihood estimators are derived from Gaussian models and lognormal models for TOA and RSS measurements, respectively. As a result, this study suggests that both RSS and TOA range measurements can produce estimates of the exact locations of the cultivation environment sensors within the wireless sensor network related to the LPCS.

Given the recent pace of development and expansion of Artificial Intelligence (AI) technology, the influence and ripple effects of AI technology on the whole of our lives will be very large and spread rapidly. The National Artificial Intelligence R&D Strategy, published in 2019, emphasizes the importance of artificial intelligence education for K-12 students. It also mentions STEM education, AI convergence curriculum, and budget for supporting the development of teaching materials and tools. However, it is necessary to create a new type of curriculum at a time when artificial intelligence curriculum has never existed before. With many attempts and discussions going very fast in all countries on almost the same starting line. Also, there is no suitable professor for K-12 students, and it is difficult to make K-12 students understand the concept of AI. In particular, it is difficult to teach elementary school students through professional programming in AI education. It is also difficult to learn tools that can teach AI concepts. In this paper, we propose an educational model for elementary school students to improve their understanding of AI through play or experience. This an experiential education model that combineds exploratory learning and discovery learning using multi-intelligence and the PLAY teaching-learning model to undertand the importance of data training or data required for AI education. This educational model is designed to learn how a computer that knows only binary numbers through UA recognizes images. Through code.org, students were trained to learn AI robots and configured to understand data bias like play. In addition, by learning images directly on a computer through TeachableMachine, a tool capable of supervised learning, to understand the concept of dataset, learning process, and accuracy, and proposed the process of AI inference.

This study has a purpose to analyze quantitatively whether ICT industry provides the qualitative indicator of employment to attract excellent human resources. We investigate the relationships of labor market conditions among ICT manufacturing, non-ICT manufacturing, ICT services, non-ICT services. Therefore, the quantitative and qualitative indicators of employment (wages, working hours, admission and turnover, involuntary retirement, and the duration years of job) are analyzed for the ICT industry and IT workers. In order to quantitatively analyze qualitative indicators such as employment status and longevity, we used employment statistics. In order to compensate for the limitations of employment insurance data, the comparison analysis with the survey data of economically active population of the National Statistical Office was conducted. As a result of this research, ICT service industry has to improve the working conditions of employees and establish an ecosystem for a lifelong career base to grow as a specialist, need to pursue an investigation for ICT worker career shift, and promote standard labor contracts. In addition, protection of employees, ICT-related job vision and social respect have to be perused.