• KIPS Transactions on Software and Data Engineering
• /
• v.8 no.6
• /
• pp.243-250
• /
• 2019

Because of a moving UAV has a lot of potential/kinetic energy, if the UAV falls to the ground, it may have a lot of impact. Because this can lead to human casualities, in this paper, the population density area on the UAV flight path is defined as a dangerous area. The conventional UAV path flight was a passive form in which a UAV moved in accordance with a path preset by a user before the flight. Some UAVs include safety features such as a obstacle avoidance system during flight. Still, it is difficult to respond to changes in the real-time flight environment. Using public Big Data for UAV path flight can improve response to real-time flight environment changes by enabling detection of dangerous areas and avoidance of the areas. Therefore, in this paper, we propose a method to detect and avoid dangerous areas for UAVs by utilizing the Big Data collected in real-time. If the routh is designated according to the destination by the proposed method, the dangerous area is determined in real-time and the flight is made to the optimal bypass path. In further research, we will study ways to increase the quality satisfaction of the images acquired by flying under the avoidance flight plan.

• The Journal of Bigdata
• /
• v.6 no.1
• /
• pp.23-35
• /
• 2021

In the era of the 4th industrial revolution, smart factories have received great attention, where production and manufacturing technology and ICT converge. With the development of IoT technology and big data, automation of production systems has become possible. In the advanced manufacturing industry, production systems are subject to unscheduled performance degradation and downtime, and there is a demand to reduce safety risks by detecting and reparing potential errors as soon as possible. This study designs a model based on supervised and unsupervised learning for detecting anomalies. The accuracy of XGBoost, LightGBM, and CNN models was compared as a supervised learning analysis method. Through the evaluation index based on the confusion matrix, it was confirmed that LightGBM is most predictive (97%). In addition, as an unsupervised learning analysis method, MD, AE, and LSTM-AE models were constructed. Comparing three unsupervised learning analysis methods, the LSTM-AE model detected 75% of anomalies and showed the best performance. This study aims to contribute to the advancement of the smart factory by combining supervised and unsupervised learning techniques to accurately diagnose equipment failures and predict when abnormal situations occur, thereby laying the foundation for preemptive responses to abnormal situations. do.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.27 no.4
• /
• pp.465-473
• /
• 2021

Since the past, ships have hoisted national flags as a means of indicating their nationality. Both domestically and internationally, laws and conventions related to the nationality and hoisting of the flag have been enacted because it is significant that the nationality of a ship is a matter of the jurisdiction of the ship. Nevertheless, there are differences in domestic and international regulations related to the hoisting of the flag of a ship, and if the flag is not hoisted irrespective of the intention, there may be a difference in interpretation as to whether or not the ship will be regarded unconditionally as a stateless ship. However, there is no disagreement locally or abroad about the necessity of indicating the nationality of ships. Therefore, I would like to propose a method to indicate and confirm the nationality of the ship by using wireless communication equipment with hoisting the flag as the only way to express its nationality, reflecting the situation of the era such as high-speed, larger and unmanned ship. Representatively, the method utilizes the automatic identification system(AIS), which is one of the equipment legally installed in the ship, and includes the ship's nationality in its information. If the nationality information is included in the AIS, nationality can be identified earlier and even from a distance, and there will not be instances of nationality not being identified because the flag is not hoisted or the flag is damaged. In addition, it is expected that the problem of nationality indication can be solved even when vessels are unmanned in future.

• Journal of the Korean Applied Science and Technology
• /
• v.38 no.1
• /
• pp.241-262
• /
• 2021

This paper reviewed the necessity of a information and communication technology (ICT)-based smart livestock system as a development strategy for the animal life industry in the future. It also predicted the trends of livestock and animal food until 2050, 30 years later. Worldwide, livestock raising and consumption of animal food are rapidly changing in response to population growth, aging, reduction of agriculture population, urbanization, and income growth. Climate change can change the environment and livestock's productivity and reproductive efficiencies. Livestock production can lead to increased greenhouse gas emissions, land degradation, water pollution, animal welfare, and human health problems. To solve these issues, there is a need for a preemptive future response strategy to respond to climate change, improve productivity, animal welfare, and nutritional quality of animal foods, and prevent animal diseases using ICT-based smart livestock system fused with the 4th industrial revolution in various aspects of the animal life industry. The animal life industry of the future needs to integrate automation to improve sustainability and production efficiency. In the digital age, intelligent precision animal feeding with IoT (internet of things) and big data, ICT-based smart livestock system can collect, process, and analyze data from various sources in the animal life industry. It is composed of a digital system that can precisely remote control environmental parameters inside and outside the animal husbandry. The ICT-based smart livestock system can also be used for monitoring animal behavior and welfare, and feeding management of livestock using sensing technology for remote control through the Internet and mobile phones. It can be helpful in the collection, storage, retrieval, and dissemination of a wide range of information that farmers need. It can provide new information services to farmers.

• Journal of Practical Engineering Education
• /
• v.14 no.1
• /
• pp.61-74
• /
• 2022

Recently, youth unemployment, especially the unemployment problem of university graduates, has emerged as a social problem. Unemployment of university graduates is both a pan-national issue and a university-level issue, and each university is making many efforts to increase the employment rate of graduates. In this study, we present a model that predicts employment availability of D-university graduates by utilizing Machine Learning. The variables used were analyzed using up to 138 personal information, admission information, bachelor's information, etc., but in order to reflect them in the future curriculum, only the data after admission works effectively, so by department / student. The proposal was limited to the recommended ability to improve the separate employment rate. In other words, since admission grades are indicators that cannot be improved due to individual efforts after enrollment, they were used to improve the degree of prediction of employment rate. In this research, we implemented a employment prediction model through analysis of the core ability of D-University, which reflects the university's philosophy, goals, human resources awards, etc., and machined the impact of the introduction of a new core ability prediction model on actual employment. Use learning to evaluate. Carried out. It is significant to establish a basis for improving the employment rate by applying the results of future research to the establishment of curriculums by department and guidance for student careers.

• KIPS Transactions on Computer and Communication Systems
• /
• v.12 no.8
• /
• pp.253-262
• /
• 2023

E-voting is a concept that includes actions such as kiosk voting at a designated place and internet voting at an unspecified place, and has emerged to alleviate the problem of consuming a lot of resources and costs when conducting offline voting. Using E-voting has many advantages over existing voting systems, such as increased efficiency in voting and ballot counting, reduced costs, increased voting rate, and reduced errors. However, centralized E-voting has not received attention in public elections and voting on corporate agendas because the results of voting cannot be trusted due to concerns about data forgery and modulation and hacking by others. In order to solve this problem, recently, by designing an E-voting system using blockchain, research has been actively conducted to supplement concepts lacking in existing E-voting, such as increasing the reliability of voting information and securing transparency. In this paper, we proposed an electronic voting system that introduced hybrid blockchain that uses public and private blockchains in convergence. A hybrid blockchain can solve the problem of slow transaction processing speed, expensive fee by using a private blockchain, and can supplement for the lack of transparency and data integrity of transactions through a public blockchain. In addition, the proposed system is implemented as BaaS to ensure the ease of type conversion and scalability of blockchain and to provide powerful computing power. BaaS is an abbreviation of Blockchain as a Service, which is one of the cloud computing technologies and means a service that provides a blockchain platform ans software through the internet. In this paper, in order to evaluate the feasibility, the proposed system and domestic and foreign electronic voting-related studies are compared and analyzed in terms of blockchain type, anonymity, verification process, smart contract, performance, and scalability.

• KIPS Transactions on Computer and Communication Systems
• /
• v.12 no.2
• /
• pp.77-84
• /
• 2023

Dengue virus transmission is a viral infection disease between humans and Aedes mosquitoes. Dengue is ubiquitous throughout the tropics and subtropical zones, where 1/3 of the global population live. The weather in Korea is also changing to subtropical weather, resulting in increased vulnerable Korean population to dengue virus transmission. It is important to control and prevent the dengue risk with track-recording & monitoring system. It is also required to have the control system to treat and monitor dengue patients with various cases such as regions, ages, genders according to the track-record of the disease. In this paper, we developed a Dengue Control & Prevention System, which can monitor and control dengue outbreaks in real-time with in-vitro diagnostic devices. Dengue Control & Prevention System is composed of in-vitro diagnostic device, which is a fluorescent immunoassay, and real-time monitoring system. In the future, we expect that our Dengue Control & Prevention System can be upgraded to have various disease information from Korea Disease Control and Prevention Agency for government policies and diseases control in Korea.

• KIPS Transactions on Computer and Communication Systems
• /
• v.11 no.3
• /
• pp.73-82
• /
• 2022

Auto-scaling is one of the most important functions for cloud computing technology. Even if the number of users or service requests is explosively increased or decreased, system resources and service instances can be appropriately expanded or reduced to provide services suitable for the situation and it can improves stability and cost-effectiveness. However, since the policy is performed based on a single metric data at the time of monitoring a specific system resource, there is a problem that the service is already affected or the service instance that is actually needed cannot be managed in detail. To solve this problem, in this paper, we propose a method to predict system resource and service response time using a multivariate time series analysis model and establish an auto-scaling policy based on this. To verify this, implement it as a custom scheduler in the Kubernetes environment and compare it with the Kubernetes default auto-scaling method through experiments. The proposed method utilizes predictive data based on the impact between system resources and response time to preemptively execute auto-scaling for expected situations, thereby securing system stability and providing as much as necessary within the scope of not degrading service quality. It shows results that allow you to manage instances in detail.

• Information Systems Review
• /
• v.24 no.2
• /
• pp.1-20
• /
• 2022

Researchers are making contradictory claims through the concept of superstars and long tails about how the development of IT technology affects demand distribution. Unlike previous studies that focused on changes in demand from a macro point of view, this study explored whether the relationship between a company's marketing activities and consumer response differs depending on the product location (i.e., superstar vs. long tail) from a micro point of view. Based on the marketing mix framework, hypotheses were developed based on the relevant literature. In the case of empirical analysis, 2,835 daily data from 63 Korean films were tested using the quantile regression method. As a result of the analysis, it was found that the influence of marketing mix factors on sales varies depending on the location of the product. Specifically, the appeal breadth of the film and the effect of owned media are enhanced in superstar products, and the effect of acquisition media in long-tail products is enhanced and the negative effects of competition are mitigated. Unlike previous studies that focused on macroscopic changes in demand distribution, this study suggested marketing activities suitable for practitioners through microscopic analysis.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.17 no.6
• /
• pp.151-160
• /
• 2017

Among the methods of developing tourist spots and culture as the experience contents, it is a common method to display high-quality video images on a large display, and it is necessary to make a special difference between the participant's active participation and the visual experience in other regions. In this paper, using the single molecular OLED and active type, the regional tourist spots blend transparent OLED dual-layer display systems with the extended image implementation and augmented interaction techniques to give the participants a real-world experience, such as directing to new experiences and beautiful sights. In this paper, additional images and UI layers are applied to the layers of the images to allow visitors to experience sightseeing information, weather, maps, accommodations, festivals and photo materials with image. In addition to the dual-layer system, it also added a multi-display system that additionally has one vertical 55-inch display on each side, adding to the experience the immersive experience and interface interlocking fun. By using transparent OLED, dual layer panel and 3-channel Multi-image playback technique, the augmented type experience contents which can experience the local attractions in Jeollanamdo province in Korea at all time without any limitation of time and space were developed.