The Journal of The Korea Institute of Intelligent Transport Systems
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v.18
no.1
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pp.43-55
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2019
Smart phone based navigation applications are very useful in everyday life. Cost-effective and user friendly navigation can be provided to the user by many applications available in market. Using the Smart phone these navigation applications provide accurate navigation for outdoor locations. But providing an accurate navigation underground space such as subway station is still a challenge. It is hence more convenient and appropriate for mobility services if the visitors could simply view the guidance of the subway station on their mobile phone, wherever and whenever it is needed. This study develops a algorithm for indoor navigation with the help of Augmented Reality(AR) and QR marker code from the entrance to the train platform for users. This indoor navigation uses AR and QR maker codes for two purposes: to provide the user link to the subway station location and to provide the current guidance details to the user. This Smart phone algorithm that uses a smart phone optical tool to decode the QR marker to determine the location information and provide guidance to the AR without indoor Maps. This algorithm also provides a module to guide mobility vulnerable to the Barrier Free route to destination.
The purpose of this study was to analyze landslide susceptibility in the Pyeongchang area using Weight of Evidence (WOE) and Evidential Belief Function (EBF) as probability models and Artificial Neural Networks (ANN) as a machine learning model in a geographic information system (GIS). This study examined the widespread shallow landslides triggered by heavy rainfall during Typhoon Ewiniar in 2006, which caused serious property damage and significant loss of life. For the landslide susceptibility mapping, 3,955 landslide occurrences were detected using aerial photographs, and environmental spatial data such as terrain, geology, soil, forest, and land use were collected and constructed in a spatial database. Seventeen factors that could affect landsliding were extracted from the spatial database. All landslides were randomly separated into two datasets, a training set (50%) and validation set (50%), to establish and validate the EBF, WOE, and ANN models. According to the validation results of the area under the curve (AUC) method, the accuracy was 74.73%, 75.03%, and 70.87% for WOE, EBF, and ANN, respectively. The EBF model had the highest accuracy. However, all models had predictive accuracy exceeding 70%, the level that is effective for landslide susceptibility mapping. These models can be applied to predict landslide susceptibility in an area where landslides have not occurred previously based on the relationships between landslide and environmental factors. This susceptibility map can help reduce landslide risk, provide guidance for policy and land use development, and save time and expense for landslide hazard prevention. In the future, more generalized models should be developed by applying landslide susceptibility mapping in various areas.
This study is aimed at suggesting information about technical choices for designing LED camping lights based on emotional lighting contents of integrated IOT and design areas which take a central role in creation and knowledge based industries and the procedure for materializing them. 'i-Light,' a portable LED camping light, is 'connected lighting' connecting men, space and emotion and a smart camping light based on IOT and emotional lighting contents. 'i-Light' has two functions. One is about lighting for adjusting color and color temperature naturally and the other is about safety for detecting harmful gases. 'i-Light' also has various emotional functions for experiencing interaction and taste of light. For the purpose, portable LED camping lights were designed, first of all, and then a highly color rendering/full-color lighting module, a smart sensor module and an IOT device platform were developed. In addition, efforts were made to establish detailed data about emotional lighting contents and to develop a Web application based on them. Finally, prototypes of portable LED camping lights were made to get a test bench and usability evaluation from related organizations. According to the results, all of 12 developed emotional lighting contents and three IOT safety sensors were suitable and prototypes were satisfactory. This paper will suggest a direction about actual technical choices for development of contents and products integrating artificial intelligence and big data and about the procedure for materializing them.
The quality of service delivery by governments to their citizens is a subject of concern in the contemporary society. E-governance is a critical aspect that is transforming government operation and service delivery to citizens and other bodies through application of information technology. This research explores the state of e-governing focusing on nations that are developing with special attention to Pakistan. The difficulties and benefits encountered are identified. The results are vital for implementers of e-governing systems in these countries. The methodology applied entails a secondary research that involves analysis and synthesis of literature relating the research topic. The results reveal that Pakistan has made incredible steps in setting up e-governance systems with growth in internet use and access of data from a digital platform. The findings reveal that e-government is associated with multiple benefits including enhanced quality of services, cost efficiency in service provision, enhance transparency and elimination of corruption, provide the basis for eradication of poverty, boost economic stability of a country, and provide room for direct democracy. The research also found that developing countries experience challenges in form of financial constraints, poor ICT infrastructure, illiteracy on e-government, political consensus constraints, legal obstacles, social and cultural constraints. E-government has the capability to transform the quality of governance provided by governments, and policymakers and implementers should address the constraints that act as a hindrance to its implementation.
Journal of the Korea Academia-Industrial cooperation Society
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v.20
no.7
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pp.520-527
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2019
In this study, the technical level and competence of Chungbuk region manufactures were diagnosed and implications for efficiency improvement of cooperation with local universities were derived. The results are as follow. First, in Chungbuk area, 75% of the skilled workers are medium-skilled and high skilled workers. And the life cycle of production products was found to have entered middle/old age. In addition, the industries were overestimating its technology capabilities, including marketing and sales technology, and management technology. Therefore, local universities should develop differentiated program such as technology transfer and commercialization support so that companies can nurture new industries and it is necessary to improve understanding of reality and future prediction ability through various education and seminars. Second, universities in Chungbuk province have failed to meet the practical demands of industry by providing general educational programs such as lifelong education curriculum, rather than the practical training required by industry. First of all, industries needed the practical training programs such as human resource empowerment, technical education and workers' retraining for local industry development. In addition, industries were expected to provide relevant knowledge and infrastructure such as testing, analysis, participation in technology development such as commissioning and joint research. Therefore, universities should prepare customized Industry-Academia Cooperation Programs through industry demand survey in planning. Also, it is necessary to establish various connection points with industry to ensure that industry-academia cooperation will continue and achieve results. Third, the technology of the industries in Chungbuk province was found to be very unrelated to the next generation regional strategic industries. This is not shared vision between industry and local government, Industry-Academia Cooperation Programs will serve as a platform to organize various community entities. Universities will be able to play a key role in between industries and local governments.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.14
no.2
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pp.105-118
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2019
New manufactural innovation was generated with combination with Do It Yourself(DIY) culture and Information and Communication Technology(ICT). It led people to make their creative idea in real things and share them. This social movement has been called as 'Maker' culture. As maker culture was developed, the places named 'Makerspace' with high-tech equipment and sharing environment have been widely spread and gotten spotlight. Futhermore, makerspaces have been diffused rapidly in Korea; because of its importance for the fourth industrial revolution. However, the operation of makerspaces is not matured as much as its popularity, so problems occurred in operating aspects. The number of related studies is not enough to foster domestic maker culture in Korea. Of that, studies on operation of makerspaces were limited and the quantity of survey sample was insufficient. Therefore, firstly, in this study, operation elements of makerspaces were extracted by literature review. And, survey for examining the extracted elements was conducted to four policy makers and researchers, four makerspace operators and four makers. Final survey was carried out by Importance-Performance Analysis(IPA) method to fifty recipients composed of policy makers and researchers, operators, and makers. In result, importance located above performance in every elements and in-depth interview was followed to understand domestic surroundings and suggest way to invigorate makerspaces in Korea. The suggestion shows as follows. First, online and offline platform for makers should be expanded; second, makerspace should connect private sponsorship with makers or their projects; third, policy direction has to be improved from venturing business to diffusion of maker culture; fourth, basic maker education should be enlarged.
KIPS Transactions on Computer and Communication Systems
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v.10
no.10
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pp.285-290
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2021
In the medical field, disease diagnosis and prediction research using artificial intelligence technology is being actively conducted. It is being released as a variety of products for disease diagnosis and prediction, which are most widely used in the application of artificial intelligence technology based on medical images. Artificial intelligence is being applied to diagnose diseases, to classify diseases into benign and malignant, and to separate disease regions for use in identification or reading according to the risk of disease. Recently, in connection with cloud technology, its utility as a service product is increasing. Among the diseases dealt with in this paper, liver disease is a disease with very high risk because it is difficult to diagnose early due to the lack of pain. Artificial intelligence technology was introduced based on medical images as a non-invasive diagnostic method for diagnosing these diseases. We describe the development of a web service to help the most meaningful clinical reading of liver cirrhosis patients. Then, it shows the web service process and shows the operation screen of each process and the final result screen. It is expected that the proposed service will be able to diagnose liver cirrhosis at an early stage and help patients recover through rapid treatment.
In this study, the status of damage by subterranean termites and their management according to the region and type of domestic wooden cultural properties were identified. This was based on the survey reports of agencies conducting regular nationwide and regional monitoring of subterranean termites. In addition, using geographical information system (GIS) based on the survey contents, a map was constructed of termite infestation and its progress on 2,805 wooden cultural properties that were surveyed nationwide. Based on the map produced, a total of 486 cases of termite infestation were confirmed in wooden cultural properties during 2018-2019, of which 143 cases (approximately 29.4%) were confirmed to be owing to the invasion of termites in the ground and infestation of wood materials. A web platform and an application using a mapping application program interface were created to increase accessibility to the investigated damage status data. The methods employed by each institution for investigating and monitoring the invasion of termites in the ground included the use of detection dogs, visual observation, installation of wood specimens made of pine, and microwave equipment. However, it was confirmed that monitoring and survey methods were not applied to determine the territorial range of the subterranean termite colonies. Accordingly, the use of dyeing and mark-release-recapture methods were deemed necessary to understand the current status, such as calculating the scope of the target wooden cultural property, when monitoring subterranean termite colonies.
The purpose of this study is to analyze the effect of the height and insole height upon landing on the lower limb joint angle and muscle activity during maximum ground repulsion in young men. For a male in their twenties, a landing motion was performed with a force plate on a 40cm-high platform by wearing one of 0, 3, 5cm polyurethane insoles per week for a total of 3 weeks. During the landing motion, the joint angle of the lower extremities and the muscle activity of the rectus femoris, biceps femoris, anterior tibialis and calf muscles were measured during the maximum ground repulsion. In order to compare the changes in the joint angle and muscle activity of the lower limbs according to the height of the insole, a one-way ANOVA with repetitive factors was performed. As a result of the analysis of the lower limb joint angle, the higher the height of the insole affected the angle of the left ankle joint. As a result of the muscle activity analysis, the higher the height of the insole affected the right anterior tibialis muscle and biceps femoris. It is thought that it is possible to protect the body when landing through sufficient muscle strength increase of the lower limb muscles. As the angle of the affected muscle and lower limb joint may be different depending on the type of insole, it is considered necessary to study it.
KIPS Transactions on Computer and Communication Systems
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v.9
no.12
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pp.291-306
/
2020
Nowadays, Data-Network-AI (DNA)-based intelligent services and applications have become a reality to provide a new dimension of services that improve the quality of life and productivity of businesses. Artificial intelligence (AI) can enhance the value of IoT data (data collected by IoT devices). The internet of things (IoT) promotes the learning and intelligence capability of AI. To extract insights from massive volume IoT data in real-time using deep learning, processing capability needs to happen in the IoT end devices where data is generated. However, deep learning requires a significant number of computational resources that may not be available at the IoT end devices. Such problems have been addressed by transporting bulks of data from the IoT end devices to the cloud datacenters for processing. But transferring IoT big data to the cloud incurs prohibitively high transmission delay and privacy issues which are a major concern. Edge computing, where distributed computing nodes are placed close to the IoT end devices, is a viable solution to meet the high computation and low-latency requirements and to preserve the privacy of users. This paper provides a comprehensive review of the current state of leveraging deep learning within edge computing to unleash the potential of IoT big data generated from IoT end devices. We believe that the revision will have a contribution to the development of DNA-based intelligent services and applications. It describes the different distributed training and inference architectures of deep learning models across multiple nodes of the edge computing platform. It also provides the different privacy-preserving approaches of deep learning on the edge computing environment and the various application domains where deep learning on the network edge can be useful. Finally, it discusses open issues and challenges leveraging deep learning within edge computing.
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