• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.35-40
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• 2021

People counting data is crucial for most business owners, since they can derive meaningful information about customers movement within their businesses. For example, owners of the supermarkets can increase or decrease the number of checkouts counters depending on number of occupants. Also, it has many applications in smart buildings, too. Where it can be used as a smart controller to control heating and cooling systems depending on a number of occupants in each room. There are advanced technologies like camera-based people counting system, which can give more accurate counting result. But they are expensive, hard to deploy and privacy invasive. In this paper, we propose a method and a hardware sensor for counting people passing through a passage or an entrance using IR Infrared sensors. Proposed sensor operates at low voltage, so low power consumption ensure long duration on batteries. Moreover, we propose a new method that distinguishes human body and other objects. Proposed method is inexpensive, easy to install and most importantly, it is real-time. The evaluation of our proposed method showed that when counting people passing one by one without overlapping, recall was 96% and when people carrying handbag like objects, the precision was 88%. Our proposed method outperforms IR Infrared based people counting systems in term of counting accuracy.

• Journal of Advanced Navigation Technology
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• v.27 no.5
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• pp.610-620
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• 2023

The interest in the aircraft interior market is gradually growing due to technological development based on the 4th industrial revolution and competition for airlines to attract customers, and as part of that, Cabin Display System (CDS) for FAA Part.25 civil aircraft is being developed in Korea. The CDS is a system that provides various multimedia services to passengers by utilizing Flexible and Transparent Organic Light Emitting Diodes (OLED) with Integrated Display Processing Module (IDPM). This paper presents a new method for efficient Data Load Process of large-sized files and deals with their implementation and performance. The results of this study are expected to be applied to Data Load Process development of avionics that require reliable large-capacity file transmission along with reducing the costs of development compared to existing ARINC-615A.

• Journal of Advanced Navigation Technology
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• v.28 no.1
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• pp.15-20
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• 2024

The utilization of small unmanned aerial vehicles (UAVs) has expanded into both military and civilian domains, increasing the necessity for research to ensure operational safety and the efficient utilization of airspace. In this study, the calculation of minimum separation distances for the safe operation of small UAVs at low altitudes was conducted. The determination of minimum separation distances requires a comprehensive analysis of the total system errors associated with small UAVs, necessitating sensitivity analysis to identify key factors contributing to flight technology errors. Flight data for small UAVs were acquired by integrating the control system of an actual small UAV with a flight simulation program. Based on this data, operational scenarios for small UAVs were established, and the minimum separation distances for each scenario were calculated. This research contributes to proposing methods for utilizing calculated minimum separation distances as crucial parameters for ensuring the safe operation of small unmanned aerial vehicles in real-world scenarios.

• Journal of the Korea Computer Graphics Society
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• v.30 no.4
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• pp.1-10
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• 2024

In the fields of computer animation and robotics, reaching a destination while avoiding obstacles has always been a difficult task. Moreover, generating appropriate motions while planning a route is even more challenging. Recently, academic circles are actively conducting research to generate character motions by modifying and utilizing VAE (Variational Auto-Encoder), a data-based generation model. Based on this, in this study, the latent space of the MVAE model is learned using a reinforcement learning method[1]. With the policy learned in this way, the character can arrive its destination while avoiding both static and dynamic obstacles with natural motions. The character can easily avoid obstacles moving in random directions, and it is experimentally shown that the performance is improved, and the learning time is greatly reduced compared to existing approach.

• The KIPS Transactions:PartA
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• v.11A no.4
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• pp.243-250
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• 2004

Monitoring is used to see if a real-time system provides a service on time. Generally, monitoring for real-time focuses on investigating the current status of a real-time system. To support a stable performance of a real-time system, it should have not only a function to see the current status of real-time process but also a function to predict executions of real-time processes, however. The legacy prediction model has some limitation to apply it to a real-time monitoring. First, it performs a static prediction after a real-time process finished. Second, it needs a statistical pre-analysis before a prediction. Third, transition probability and data about clustering is not based on the current data. We propose the execution prediction model based on learning algorithm to solve these problems and apply it to real-time monitoring. This model gets rid of unnecessary pre-processing and supports a precise prediction based on current data. In addition, this supports multi-level prediction by a trend analysis of past execution data. Most of all, We designed the model to support dynamic prediction which is performed within a real-time process' execution. The results from some experiments show that the judgment accuracy is greater than 80% if the size of a training set is set to over 10, and, in the case of the multi-level prediction, that the prediction difference of the multi-level prediction is minimized if the number of execution is bigger than the size of a training set. The execution prediction model proposed in this model has some limitation that the model used the most simplest learning algorithm and that it didn't consider the multi-regional space model managing CPU, memory and I/O data. The execution prediction model based on a learning algorithm proposed in this paper is used in some areas related to real-time monitoring and control.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.1-8
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• 2020

Air ducts installed for ventilation inside buildings accumulate contaminants during their service life. Robots are installed to clean the air duct at low cost, but they are still not fully automated and depend on manpower. In this study, an intersection detection algorithm for autonomous driving was applied to an air duct cleaning robot. Autonomous driving of the robot was achieved by calculating the distance and angle between the extracted point and the center point through the intersection detection algorithm from the camera image mounted on the robot. The training data consisted of CAD images of the duct interior as well as the cross-point coordinates and angles between the two boundary lines. The deep learning-based CNN model was applied as a detection algorithm. For training, the cross-point coordinates were obtained from CAD images. The accuracy was determined based on the differences in the actual and predicted areas and distances. A cleaning robot prototype was designed, consisting of a frame, a Raspberry Pi computer, a control unit and a drive unit. The algorithm was validated by video imagery of the robot in operation. The algorithm can be applied to vehicles operating in similar environments.

• The KIPS Transactions:PartD
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• v.12D no.3 s.99
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• pp.461-470
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• 2005

This paper suggests a new policy for consolidating a company's profits by segregating the clients using the contents service and allocating the media server's resources distinctively by clusters using the cluster analysis method of CRM, which is mainly applied to marketing. In this case, CRM refers to the strategy of consolidating a company's profits by efficiently managing the clients, providing them with a more effective, personalized service, and managing the resources more effectively. For the realization of a new service policy, this paper analyzes the level of contribution $vis-\acute{a}-vis$ the clients' service pattern (total number of visits to the homepage, service type, service usage period, total payment, average service period, service charge per homepage visit) and profits through the cluster analysis of clients' data applying the K-Means Method. Clients were grouped into 4 clusters according to the contribution level in terms of profits. Likewise, the CRFA (Client Request Filtering algorithm) was suggested per cluster to allocate media server resources. CRFA issues approval within the resource limit of the cluster where the client belongs. In addition, to evaluate the efficiency of CRFA within the Client/Server environment the acceptance rate per class was determined, and an evaluation experiment on network traffic was conducted before and after applying CRFA. The results of the experiments showed that the application of CRFA led to the decrease in network expenses and growth of the acceptance rate of clients belonging to the cluster as well as the significant increase in the profits of the company.

• Geophysics and Geophysical Exploration
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• v.23 no.3
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• pp.208-214
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• 2020

In this study, we have developed a drone magnetic exploration system (proto-type) using a fluxgate magnetic sensor. Hardware of the system consists of a fluxgate magnetometer, an inertial measurement unit (IMU), a GPS, and a communication module. And we have developed monitoring software, which enables it to transmit the measured data to the ground control system (GCS) in real time. The measured magnetic data are finally saved as 1 Hz data after passing through a notch filter and a band-pass filter. For verification of this system, a preliminary test was conducted to check the magnetic responses of a magnetic object first, then the field test was carried out in two iron mines. We tested the developed system on the field test in Pocheon, Gyeonggi and Jeongseon, Gangwon. The magnetic data from the developed drone system was very similar to those from unmanned airship system developed by Korea Institute of Geoscience and Mineral Resources (KIGAM). As a result, preliminary experiment and field test have demonstrated that this system is applicable for outdoor aeromagnetic exploration. It requires more studies to improve filter function and instrument performance to minimize noise in the future.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.1
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• pp.39-47
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• 2005

The range of hardware implementation increases in communication systems as high-speed processing is required for high data rate. In the broadband wireless access (BWA) system based on IEEE standard 802.16 the functions of higher part in the MAC layer to Provide data needed for generating MAC PDU are implemented in software, and the tasks from formatting MAC PDUs by using those data to transmitting the messages in a modem are implemented in hardware. In this paper, the interface hardware for efficient message exchange between MAC and PHY layers in the BWA system is designed. The hardware performs the following functions including those of the transmission convergence(TC) sublayer; (1) formatting TC PDU(Protocol data unit) from/to MAC PDU, (2) Reed-solomon(RS) encoding/decoding, and (3) resolving DL MAP and UL MAP, so that it controls transmission slot and uplink and downlink traffic according to the modulation scheme of burst profile. Also, it provides various control signal for PHY modem. In addition, the truncated binary exponential backoff (TBEB) algorithm is implemented in a subscriber station to avoid collision on contention-based transmission of messages. The VLSI architecture performing all these functions is implemented and verified in VHDL.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.828-835
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• 2019

An artificial rainfall system is used widely as a research tool for generating model experiment data. Artificial rainfall devices have been used in many studies, but studies of the rainfall distribution are not considered as important issues. To simulate various rainfall characteristics, it should be possible to simulate from low to high intensity, and the homogeneity of the rainfall distribution should be ensured. In this study, the maximum rainfall intensity was set to 130mm/hr and controlled by 10mm/hr. In addition, the aim was to secure a uniform coefficient value of 80% or more. To this end, rainfall tests were performed according to the nozzle type, diameter, position, and pump pressure. The rainfall test showed that the circular nozzle was suitable, and the nozzle size was 1.9mm and 1.4mm. The optimal pump pressure was found to be 3~6kg/㎠. The rainfall intensity tended to increase linearly with increasing pump pressure. Based on the rainfall test results, a rainfall control manual was produced with variables, such as pump pressure, nozzle type, and number of nozzles. As a result of rainfall verification, rainfall intensity showed a 3.1% error with a uniformity coefficient of 86%.