• Journal of the Korea Academia-Industrial cooperation Society
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• 제20권1호
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• pp.85-95
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• 2019

Recently, studies on the fourth industrial revolution have been actively conducted in the areas of government, business, and academia. Corporate business models that utilize the major agendas of the fourth industrial revolution such as robots, artificial intelligence, Internet of things (IoT), and block chains have been created, and various changes have occurred in not only business, education, and living environments but also in international relations. In this study, we looked at changes in social contribution activities from the perspective of a company facing impacts of the fourth industrial revolution. This study examines the definition and activities of corporate social contribution and how we can contribute to society through corporate activities. 'AT Educom', LG Uplus 'Social Contribution through IoT', KT's anti-infectious disease prevention platform and cases of Intel using IoT. In addition, we have presented what we need to do in the future to promote corporate social contribution activities that will make more meaningful impacts on how corporate social contribution activities will change according to technology development. The first, measuring the performance of corporate social contribution activities needs a standardized methodology and social contribution activities through platform business and ICT should be actively pursued. Lastly, social contribution activities between companies and sectors will increase.

• Journal of Convergence for Information Technology
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• 제11권4호
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• pp.83-101
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• 2021

This study is to investigate, using AHP, what technologies should be applied first to Korean SMEs in order to respond to the 4th industrial revolution and change to a smart enterprise. To this end, technologies related to the 4th industrial revolution and smart factory are synthesized, and the classification criteria of Dae-Hoon Kim et al. (2019) are applied, but additional opinions of experts are collected and related technologies are converted to artificial intelligence (AI), Big Data, and Cloud Computing. As a base technology, mobile, Internet of Things (IoT), block chain as hyper-connected technology, unmanned transportation (autonomous driving), robot, 3D printing, drone as a convergence technology, smart manufacturing and logistics, smart healthcare, smart transportation and smart finance were classified as smart industrial technologies. As a result of confirming the priorities for technical use by AHP analysis and calculating the total weight, manufacturing companies have a high ranking in mobile, artificial intelligence (AI), big data, and robots, while service companies are in big data and robots, artificial intelligence (AI), and smart healthcare are ranked high, and in all companies, it is in the order of big data, artificial intelligence (AI), robot, and mobile. Through this study, it was clearly identified which technologies should be applied first in order to respond to the 4th industrial revolution and change to a smart company.

• International Journal of Computer Science & Network Security
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• 제24권4호
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• pp.163-169
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• 2024

India is a developing nation and has come with comprehensive way in modernizing its reducing poverty, economy and rising living standards for an outsized fragment of its residents. The STEM (Science, Technology, Engineering, and Mathematics) education plays an important role in it. STEM is an educational curriculum that emphasis on the subjects of "science, technology, engineering, and mathematics". In traditional education scenario, these subjects are taught independently, but according to the educational philosophy of STEM that teaches these subjects together in project-based lessons. STEM helps the students in his holistic development. Youth unemployment is the biggest concern due to lack of adequate skills. There is a huge skill gap behind jobless engineers and the question arises how we can prepare engineers for a better tomorrow? Now a day's Industry 4.0 is a new fourth industrial revolution which is an intelligent networking of machines and processes for industry through ICT. It is based upon the usage of cyber-physical systems and Internet of Things (IoT). Industrial revolution does not influence only production but also educational system as well. IoT in academics is a new revolution to the Internet technology, which introduced "Smartness" in the entire IT infrastructure. To improve socio-economic status of the India students must equipped with 21st century digital skills and Universities, colleges must provide individual learning kits to their students which can help them in enhancing their productivity and learning outcomes. The major goal of this paper is to present a low cost, effective learning mechanism for STEM implementation using Raspberry Pi 3+ model (Single board computer) and Node Red open source visual programming tool which is developed by IBM for wiring hardware devices together. These tools are broadly used to provide hands on experience on IoT fundamentals during teaching and learning. This paper elaborates the appropriateness and the practicality of these concepts via an example by implementing a user interface (UI) and Dashboard in Node-RED where dashboard palette is used for demonstration with switch, slider, gauge and Raspberry pi palette is used to connect with GPIO pins present on Raspberry pi board. An LED light is connected with a GPIO pin as an output pin. In this experiment, it is shown that the Node-Red dashboard is accessing on Raspberry pi and via Smartphone as well. In the final step results are shown in an elaborate manner. Conversely, inadequate Programming skills in students are the biggest challenge because without good programming skills there would be no pioneers in engineering, robotics and other areas. Coding plays an important role to increase the level of knowledge on a wide scale and to encourage the interest of students in coding. Today Python language which is Open source and most demanding languages in the industry in order to know data science and algorithms, understanding computer science would not be possible without science, technology, engineering and math. In this paper a small experiment is also done with an LED light via writing source code in python. These tiny experiments are really helpful to encourage the students and give play way to learn these advance technologies. The cost estimation is presented in tabular form for per learning kit provided to the students for Hands on experiments. Some Popular In addition, some Open source tools for experimenting with IoT Technology are described. Students can enrich their knowledge by doing lots of experiments with these freely available software's and this low cost hardware in labs or learning kits provided to them.

• The Journal of Industrial Distribution & Business
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• 제11권6호
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• pp.29-39
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• 2020

Purpose: The purpose of this study is, in the situation where rapid response to the rapidly changing environment is required due to the development of the fourth industrial revolution such as artificial intelligence, virtual reality, and the internet of things, robotics, big data, additive manufacturing, bio-health, sharing economy and in the organizational culture aspiring toward the innovation of a major company, small business and a public institution, to analyze what influence a job-engagement and stress make, and what influence individual's self-efficacy as a moderator mediator makes, and to offer basic data for improving job-engagement and lowering job-stress. Research design, data, and methodology: For doing this, the literature and the empirical studies were combined. Deriving innovation-oriented organizational culture as factors affecting the job engagement and job stress through the literature, and have established hypotheses to verify them. We have collected data of 281 from ex,ecutives and staff-members working in areas including major company, small business and officials (the central government, a local public service, the prosecution, the police, and school). And these data were analyzed by SPSS 23 version. Results: Based on these data, the results of analysis were as follows; First, the innovation-oriented organizational culture which was recognized by organizational members had effect on job-stress. Second, the innovation-oriented organizational culture which was recognized by organizational members influenced job-stress. Third, in the relationship between the innovation-oriented organizational culture and job-engagement, self-efficacy did not influenced job-engagement. Finally, in the relationship between the innovation-oriented organizational culture and job-stress, self-efficacy influenced job-stress. Conclusions: Innovation-oriented organizational culture places importance on the organization's adaptability and flexibility in the external environment, so companies need to establish an innovation-oriented organizational culture favorable to achieving survival and successful innovation, and to develop and disseminate programs of positive and continuous organizations to improve task enthusiasm, reduce task stress, and enhance organizational performance. In the future, it will be necessary to verify the effectiveness of various organizational culture types through comparative analysis with companies that actively maintain an innovation-oriented organizational culture (Google, Kakao, etc.) and companies that prefer hierarchy-oriented organizational culture, relationship-oriented organizational culture, and market-oriented organizational culture.

• Journal of the Korea Convergence Society
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• 제10권3호
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• pp.49-57
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• 2019

The core technology development of the Fourth Industrial Revolution is linked to the development of other core technologies, which will change the industrial structure in the future and create a new smart business model. In this paper, tried to analyze the technology maturity level and analyze the technology maturity. To do this, used technology trend information to investigate and integrate the market, policy, etc. Of core technology of the 4th Industrial Revolution to achieve a comprehensive maturity level. Because technology maturity measures are scored by technology developers, prejudices may be acted upon according to a person's tendency, which may be a subjective evaluation. It is also a measure of the maturity of individual technologies, and thus is not suitable for evaluating the overall system integration perspective. However, it is possible to evaluate the maturity before integrating the core element technologies constituting the whole system and to use it as a means to compare the effect of the whole system and its feasibility and play an important role in the planning of technology development.

• Journal of the Korea Academia-Industrial cooperation Society
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• 제19권11호
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• pp.310-318
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• 2018

Recently, the importance of big data analysis is increasing as a large amount of data is generated by various devices connected to the Internet with the advent of Internet of Things (IoT). Especially, it is necessary to analyze various large-scale IoT streaming sensor data generated in real time and provide various services through new meaningful prediction. This paper proposes a real-time indoor PM10 concentration prediction LSTM model based on streaming data generated from IoT sensor using AWS. We also construct a real-time indoor PM10 concentration prediction service based on the proposed model. Data used in the paper is streaming data collected from the PM10 IoT sensor for 24 hours. This time series data is converted into sequence data consisting of 30 consecutive values from time series data for use as input data of LSTM. The LSTM model is learned through a sliding window process of moving to the immediately adjacent dataset. In order to improve the performance of the model, incremental learning method is applied to the streaming data collected every 24 hours. The linear regression and recurrent neural networks (RNN) models are compared to evaluate the performance of LSTM model. Experimental results show that the proposed LSTM prediction model has 700% improvement over linear regression and 140% improvement over RNN model for its performance level.

• Journal of the Korea Academia-Industrial cooperation Society
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• 제17권9호
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• pp.745-752
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• 2016

In the era of the Internet of Things, where all physical objects are connected to the Internet, we suggest a remote control system using a Raspberry Pi single-board computer with ZigBee, which can turn an indoor light-emitting diode (LED) and a multiple-tap on and off, and with a smart phone can control the brightness of the LED as well as an electronic door lock. By connecting an infrared (IR) transmitter module to the Raspberry Pi, we can control home appliances, such as an air conditioner, and we can also monitor indoor images, indoor temperatures, and illumination by using a smart phone app. We developed a method of finding out IR transmission codes required for remote-controllable appliances with an AVR micro-controller. We suggest a method to remotely open and shut an office door by novating the door lock. The brightness level of an LED (between 0 and 10) can be controlled through a PWM signal generated by an ATmega88 microcontroller. A mutiple-tap is controlled using an ATmega32, a photo-coupler, and a TRIAC. The signals for measured temperature and illumination are converted from analog to digital by using the ATtiny44A microcontroller transmitting to a Raspberry Pi through SPI communication. Then, we connect a camera to the CSI head of the Raspberry Pi. We can turn on the smart multiple-tap for a certain period of time, or we can schedule the multi-tap to turn on at a specific time. To reduce standby power, people usually pull out a power code from multiple-taps or turn off a switch. Our method helps people do the same thing with a smart phone, if they are away from home.

• Journal of Internet Computing and Services
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• 제20권5호
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• pp.105-111
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• 2019

Core technologies that lead the Fourth Industrial Revolution era, such as artificial intelligence, big data, and autonomous driving, are implemented and serviced through the rapid development of computing power and hyper-connected networks based on the Internet of Things. In this paper, we implement two different models for drivable area segmentation in various environment, and propose a better model by comparing the results. The models for drivable area segmentation are using DeepLab V3+ and Mask R-CNN, which have great performances in the field of image segmentation and are used in many studies in autonomous driving technology. For driving information in various environment, we use BDD dataset which provides driving videos and images in various weather conditions and day&night time. The result of two different models shows that Mask R-CNN has higher performance with 68.33% IoU than DeepLab V3+ with 48.97% IoU. In addition, the result of visual inspection of drivable area segmentation on driving image, the accuracy of Mask R-CNN is 83% and DeepLab V3+ is 69%. It indicates Mask R-CNN is more efficient than DeepLab V3+ in drivable area segmentation.

• Journal of Internet Computing and Services
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• 제20권1호
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• pp.17-24
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• 2019

Since the information of $4^{th}$ Industrial Revolution is introduced in WEF (World Economic Forum) in 2016, IoT, AI, Big Data, 5G, Cloud Computing, 3D/4DPrinting, Robotics, Nano Technology, and Bio Engineering have been rapidly developed as business applications as well as technologies themselves. Among the diverse business applications for IoT, wearable devices are recognized as the leading application devices for final customers. This longitudinal study is compared to the results of the 1st study conducted to identify customer needs of activity trackers, and links the identified users' needs with the well-known marketing frame of marketing mix. For this longitudinal study, a survey was applied to university students in June, 2018, and ANOVA were applied for major variables on usable features. Further, potential customer needs were identified and visualized by Word Cloud Technique. According to the analysis results, different from other high tech IT devices, activity trackers have diverse and unique potential needs. The results of this longitudinal study contribute primarily to understand usable features and their changes according to product maturity. It would provide some valuable implications in dynamic manner to activity tracker designers as well as researchers in this arena.

• Journal of the Korean Institute of Gas
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• 제24권5호
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• pp.10-19
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• 2020

Valve leak accidents in petrochemistry plants and gas utilities cause human and property damage. The main reason why happen gas inhalation, poisoning, fire and explosion accidents is gas valve leakage. To prevent gas leakage, inspectors check the facilities in the field. And they are at risk of gas leak accidents. So we applied IoT-based risk assessment, monitoring and automatic control system. It can detect both internal and external gas leakage, do real-time monitoring of industrial valve in the plant by using hybrid sensor. As the new safety management system for industrial valve is developed, it needs method to evaluate device performance and environmental components for the system. This study is about development of method to verify performance of the explosion-proofed hybrid sensing system include gas detector and optical fiber sensor supporting wire and wireless communication.