• KIPS Transactions on Software and Data Engineering
• /
• v.4 no.10
• /
• pp.447-454
• /
• 2015

This paper proposes geographical name denoising by machine learning of event detection based on twitter. Recently, the increasing number of smart phone users are leading the growing user of SNS. Especially, the functions of short message (less than 140 words) and follow service make twitter has the power of conveying and diffusing the information more quickly. These characteristics and mobile optimised feature make twitter has fast information conveying speed, which can play a role of conveying disasters or events. Related research used the individuals of twitter user as the sensor of event detection to detect events that occur in reality. This research employed geographical name as the keyword by using the characteristic that an event occurs in a specific place. However, it ignored the denoising of relationship between geographical name and homograph, it became an important factor to lower the accuracy of event detection. In this paper, we used removing and forecasting, these two method to applied denoising technique. First after processing the filtering step by using noise related database building, we have determined the existence of geographical name by using the Naive Bayesian classification. Finally by using the experimental data, we earned the probability value of machine learning. On the basis of forecast technique which is proposed in this paper, the reliability of the need for denoising technique has turned out to be 89.6%.

• KIPS Transactions on Computer and Communication Systems
• /
• v.3 no.10
• /
• pp.337-350
• /
• 2014

Internet-of-Things(IoT) is the computing paradigm converged with different technologies, where diverse devices are connected via the wireless network, acquire environmental information from their equipped sensors, and are actuated. IoT applications provide smart services to users by interacting with multiple devices connected to the network. IoT devices provide the simple set of the information and also offer smart services by collaborating with other devices. That is, IoT applications always interact with IoT devices which are becoming very popular at a fast pace. However, due to this fact, developing IoT application results in unconventional technical challenges which have not been observed in typical software applications. Moreover, since IoT computing has its own characteristics which are distinguished from other former paradigms such as embedded computing and mobile computing, IoT applications also reveal their own technical challenges. Therefore, we analyze technical challenges occurring in developing IoT applications and present effective solutions to overcome the challenges. To verify identified issues and presented solutions, we present the result of performing a case study of developing an IoT application. Through the case study, we verify how the unconventional technical issues are raised in a real domain and analyze effectiveness of applying the solutions to the application.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.22 no.1
• /
• pp.140-153
• /
• 2019

Cloase-range image information from drones and ground-based camera has been frequently used in the field of disaster mitigation with 3D modeling and mapping. In addition, the utilization of virtual reality(VR) is being increased by implementing realistic 3D models with the VR technology simulating disaster circumstances in large scale. In this paper, we created a VR training program by extracting realistic 3D models from close-range images from unmanned aircraft and digital camera on hand and observed several issues occurring during the implementation and the effectiveness in the case of a VR application in training for disaster mitigation. First of all, we built up a scenario of disaster and created 3D models after image processing with the close-range imagery. The 3D models were imported into Unity, a software for creation of augmented/virtual reality, as a background for android-based mobile phones and VR environment was created with C#-based script language. The generated virtual reality includes a scenario in which the trainer moves to a safe place along the evacuation route in the event of a disaster, and it was considered that the successful training can be obtained with virtual reality. In addition, the training through the virtual reality has advantages relative to actual evacuation training in terms of cost, space and time efficiencies.

• The Journal of the Convergence on Culture Technology
• /
• v.5 no.1
• /
• pp.401-407
• /
• 2019

SDN(Softeware Defined Networking) has emerged to address the rapidly growing demand for cloud computing and to support network virtualization services. Therefor many companies and organizations have taken SDN as a next-generation network technology. However, unlike the wired network where the SDN is originally designed, the SDN in the wireless network has a restriction that it can not provide the mobility of the node. In this paper, we extended existing openflow protocol of SDN and developed SDN-based network platform, which enables the SDN controller to manage the radio resources of its network and support the mobility of the nodes. The mobility support function of this paper has the advantage that a node in the network can move using its two or more wireless interfaces by using the radio resource management function of the SDN controller. In order to test the functions implemented in this paper, we measured parameters related to various transmission performance according to various mobile experiments, and compared parameters related to performance using one wireless interface and two interfaces. The SDN-based network platform proposed in this paper is expected to be able to monitor the resources of wireless networks and support the mobility of nodes in the SDN environment.

• KIPS Transactions on Software and Data Engineering
• /
• v.11 no.3
• /
• pp.141-148
• /
• 2022

Recently, reinforcement learning combined with deep neural network technology has achieved remarkable success in various fields such as board games such as Go and chess, computer games such as Atari and StartCraft, and robot object manipulation tasks. However, such deep reinforcement learning describes states, actions, and policies in vector representation. Therefore, the existing deep reinforcement learning has some limitations in generality and interpretability of the learned policy, and it is difficult to effectively incorporate domain knowledge into policy learning. On the other hand, dNL-RRL, a new relational reinforcement learning framework proposed to solve these problems, uses a kind of vector representation for sensor input data and lower-level motion control as in the existing deep reinforcement learning. However, for states, actions, and learned policies, It uses a relational representation with logic predicates and rules. In this paper, we present dNL-RRL-based policy learning for transportation mobile robots in a manufacturing environment. In particular, this study proposes a effective method to utilize the prior domain knowledge of human experts to improve the efficiency of relational reinforcement learning. Through various experiments, we demonstrate the performance improvement of the relational reinforcement learning by using domain knowledge as proposed in this paper.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.28 no.4
• /
• pp.601-609
• /
• 2022

Jack-up drilling rigs are mobile offshore platforms widely used in the offshore oil and gas exploration industry. These are independent, three-legged, self-elevating units with a cantilevered drilling facility for drilling and production. A typical jack-up rig includes a triangular hull, a tower derrick, a cantilever, a jackcase, living quarters and legs which comprise three-chord, open-truss, X-braced structure with a spudcan. Generally, jack-up rigs can only operate in water depths ranging from 130m to 170m. Recently, there has been an increasing demand for jack-up rigs for operating at deeper water levels and harsher environmental conditions such as waves, currents and wind loads. All static and dynamic loads are supported through legs in the jack-up mode. The most important issue by society is to secure the safety of the leg structure against collision that causes large instantaneous impact energy. In this study, nonlinear FE -analysis and verification of the requirement against collision for 35MJ recommended by DNV was performed using LS-Dyna software. The colliding ship used a 7,500ton of shore supply vessel, and five scenarios of collisions were selected. From the results, all conditions do not satisfy the class requirement of 35MJ. The loading conditions associated with chord collision are reasonable collision energy of 15M and brace collisions are 6MJ. Therefore, it can be confirmed that the identical collision criteria by DNV need to be modified based on collision scenarios and colliding members.

• The Journal of Korean Academy of Prosthodontics
• /
• v.60 no.3
• /
• pp.276-282
• /
• 2022

Close communication between clinicians and dental technicians is an important factor in providing successful prostheses. The exchange of opinions with laboratories has mainly been in the form of written prescriptions and a photos, but it has been reported that information transmission may be limited. Currently, as digital technology-based prosthesis fabrication is common, 3D image objects can be stored on the web and can be easily viewed through a mobile web browser. In this article, we introduce cases where the design of the prosthesis was improved by designing the prosthesis using CAD software and reviewing the prosthesis designed with the clinical side through a web viewer. Through this protocol, it was possible to improve the occlusal surface and crown contour, the opposing teeth condition, the size of the gingival embrasure, and the shape of pontic. The process of sharing, discussing, and modifying the prosthesis design with the clinician and technician through a web viewer contributes to reflecting the diversity of oral conditions and individualized needs, thereby helping to make functional and esthetic prostheses.

• Therapeutic Science for Rehabilitation
• /
• v.12 no.3
• /
• pp.7-18
• /
• 2023

Objective : This study aimed to confirm the research characteristics by analyzing the literature that applied the school readiness programs for children with disabilities. Methods : Studies were collected from the PubMed, Embase, Web of Science, and Research Information Sharing Service databases. The key terms were "School readiness" AND ("Occupational Therapy" OR "Rehabilitation") in English and Korean. Total eight articles were selected through the selection and exclusion criteria. Results : The programs included multi-type training, motor skill training, parent training, and mobile application training. The providers were psychologists, occupational therapists, physical therapists, speech pathologists, community workers, educators, and the psychologists who conducted most of the research. The program factors can be classified into academic function, motor function, social function, parental training, and others. Academic and social functions accounted for the largest proportion of the respondents. The intervention improved multiple skills, literacy, parenting skills, and gross fine motor function. Conclusion : This study aimed to provide basic data for school-based occupational therapy by analyzing school readiness programs for children with disabilities. Recently, interest in and research on school readiness has increased. Occupational therapists should also establish their roles in the field of school-related rehabilitation and provide various school-based occupational therapies.

• Journal of Korea Entertainment Industry Association
• /
• v.13 no.1
• /
• pp.25-34
• /
• 2019

The purpose of this study is to develop a mobile app for mental health self care of university student. User centered design is a research design that applies the subject's needs assessment, analysis, design, development, evaluation, modification and supplement to suit the subjects. In order to manage the mental health of university students, they consisted of four main areas of mental health problems: drinking, sleeping, depression, and stress. It is designed to enable self test content, analysis and notification of inspection results, and management plan for current status of each area. Based on this, I developed an Android based mental health self-care Application. The subject can enter his or her mental health status data to explain the normal or risk level for each result, and the subject can then select the appropriate intervention method that he or she can perform. In addition, we developed a mental health self care calendar that can display the present status of each of the four areas on a day by day basis, and the current status can be expressed in an integrated manner through animations and status bars. The purpose of this study was to develop a mental health self-care app that can be improved by continuous and improved programs.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.141-143
• /
• 2022

This paper presented a new technology to identify traffic violations of motorbike riders by detecting the traffic signal using You Only Look Once (YOLO) object detection. The hardware module that is mounted on the front of the motorbike consists of Raspberry Pi with a camera to run the YOLO object detection, a GPS module to acquire the motorcycle's coordinate, and a LoRa communication module to send the data to a cloud DB. The main goal of the software is to determine whether a motorbike has violated a traffic signal. This paper proposes a function to recognize the red traffic signal colour with its movement inside the camera angle and determine that the traffic signal violation happens if the traffic signal is moving to the right direction (the rider turns left) or moving to the top direction (the riders goes straight). Furthermore, if a motorbike rider is violated the signal, the rider's personal information (name, mobile phone number, etc), the snapshot of the violation situation, rider's location, and date/time will be sent to a cloud DB. The violation information will be delivered to the driver's smartphone as a push notification and the local police station to be used for issuing violation tickets, which is expected to prevent motorbike riders from violating traffic signals.