• Journal of Cadastre & Land InformatiX
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• v.53 no.2
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• pp.5-18
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• 2023

As the development of drones and sensors accelerates, new services and values are created by fusing data acquired from various sensors mounted on drone. However, the construction of spatial information through data fusion is mainly constructed depending on the image, and the quality of data is determined according to the specification and performance of the hardware. In addition, it is difficult to utilize it in the actual field because expensive equipment is required to construct spatial information of high-quality. In this study, super-resolution was performed by applying deep learning to low-resolution images acquired through RGB and THM cameras mounted on a drone, and quantitative evaluation and feature point extraction were performed on the generated high-resolution images. As a result of the experiment, the high-resolution image generated by super-resolution was maintained the characteristics of the original image, and as the resolution was improved, more features could be extracted compared to the original image. Therefore, when generating a high-resolution image by applying a low-resolution image to an super-resolution deep learning model, it is judged to be a new method to construct spatial information of high-quality without being restricted by hardware.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.454-464
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• 2023

This paper proposes a low-power 8-bit asynchronous SAR ADC with a sampling rate of 1 MS/s for sensor node applications. The ADC uses bootstrapped switches to improve linearity and applies a VCM-based CDAC switching technique to reduce the power consumption and area of the DAC. Conventional synchronous SAR ADCs that operate in synchronization with an external clock suffer from high power consumption due to the use of a clock faster than the sampling rate, which can be overcome by using an asynchronous SAR ADC structure that handles internal comparisons in an asynchronous manner. In addition, the SAR logic is designed using dynamic logic circuits to reduce the large digital power consumption that occurs in low resolution ADC designs. The proposed ADC was simulated in a 180-nm CMOS process, and at a 1.8 V supply voltage and a sampling rate of 1 MS/s, it consumed 46.06 𝜇W of power, achieved an SNDR of 49.76 dB and an ENOB of 7.9738 bits, and obtained a FoM of 183.2 fJ/conv-step. The simulated DNL and INL are +0.186/-0.157 LSB and +0.111/-0.169 LSB.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.478-488
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• 2023

This paper investigates the naval application of laser communication as a potential replacement for traditional acoustic wave communication in underwater environments. We developed a laser transceiver using Arduino and MATLAB, conducting a water tank experiment to validate communication feasibility across diverse underwater conditions. In the first experiment, when transmitting data through a laser, the desired message was converted into data and transmitted, received, and confirmed to be converted into the correct message. In the second experiment, the operation of communication in underwater situations was confirmed, and in the third experiment, the intensity of light was measured using the CDS illuminance sensor module and the limits of laser communication were measured and confirmed in various underwater situations. Additionally, MATLAB code was employed to gather data on salinity, water temperature, and water depth for calculating turbidity. Optimal wavelength values (532nm, 633nm, 785nm, 1064nm) corresponding to calculated turbidity levels (5, 20, 55, 180) were determined and presented. The study then focuses on analyzing potential applications in naval tactical communication, remote sensing, and underwater drone control. Finally, we propose measures for overcoming current technological limitations and enhancing performance.

• The Transactions of the Korea Information Processing Society
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• v.13 no.6
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• pp.269-277
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• 2024

With the advancement of modern IT technologies, the operation of autonomous vehicles is becoming a reality, and route planning is essential for this. Generally, route planning involves proposing the shortest path to minimize travel distance and the quickest path to minimize travel time. However, the quality of these routes depends on the topological characteristics of the road network graph. If the connectivity structure of the road network is not rational, there are limits to the performance improvement that routing algorithms can achieve. Real drivers consider psychological factors such as the number of turns, surrounding environment, traffic congestion, and road quality when choosing routes, and they particularly prefer routes with fewer turns. This paper introduces a simple path algorithm that seeks routes with the fewest turns, in addition to the traditional shortest distance and quickest time routes, to evaluate the characteristics of road networks. Using this simple path algorithm, we compare and evaluate the connectivity characteristics of road networks in 20 major cities worldwide. By analyzing these road network characteristics, we can identify the strengths and weaknesses of urban road networks and develop more efficient and safer route planning algorithms. This paper comprehensively examines the quality of road networks and the efficiency of route planning by analyzing and comparing the road network characteristics of each city using the proposed simple path algorithm.

• The Transactions of the Korea Information Processing Society
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• v.13 no.4
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• pp.157-165
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• 2024

The evolution of the Distributed Denial of Service Attack(DDoS Attack) method has increased the difficulty in the detection process. One of the solutions to overcome the problems caused by the limitations of the existing victim-side detection method was the source-side detection technique. However, there was a problem of performance degradation due to network traffic irregularities. In order to solve this problem, research has been conducted to detect attacks using a collaborative network between several nodes based on artificial intelligence. Existing methods have shown limitations, especially in nonlinear traffic environments with high Burstness and jitter. To overcome this problem, this paper presents a collaborative source-side DDoS attack detection technique introduced with an attention mechanism. The proposed method aggregates detection results from multiple sources and assigns weights to each region, and through this, it is possible to effectively detect overall attacks and attacks in specific few areas. In particular, it shows a high detection rate with a low false positive of about 6% and a high detection rate of up to 4.3% in a nonlinear traffic dataset, and it can also confirm improvement in attack detection problems in a small number of regions compared to methods that showed limitations in the existing nonlinear traffic environment.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.21-30
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• 2024

In this paper, we propose a method to build a sample dataset of the features of eight sensor-only facilities built as infrastructure for autonomous cooperative driving. The feature extracted from point cloud data acquired by LiDAR and build them into the sample dataset for recognizing the facilities. In order to build the dataset, eight sensor-only facilities with high-brightness reflector sheets and a sensor acquisition system were developed. To extract the features of facilities located within a certain measurement distance from the acquired point cloud data, a cylindrical projection method was applied to the extracted points after applying DBSCAN method for points and then a modified OTSU method for reflected intensity. Coordinates of 3D points, projected coordinates of 2D, and reflection intensity were set as the features of the facility, and the dataset was built along with labels. In order to check the effectiveness of the facility dataset built based on LiDAR data, a common CNN model was selected and tested after training, showing an accuracy of about 90% or more, confirming the possibility of facility recognition. Through continuous experiments, we will improve the feature extraction algorithm for building the proposed dataset and improve its performance, and develop a dedicated model for recognizing sensor-only facilities for autonomous cooperative driving.

• The Journal of the Acoustical Society of Korea
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• v.25 no.2
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• pp.49-55
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• 2006

Measurement of impact sound insulation of floor, by current Korean Standard KS F 2810-2. is to be made with peak levels over 4 point in a receiving room. But it is often the case that there is inconsistency in results at various receiving points in the receiving room. Such variations obviously have effects on the repeatability and reproducibility of measured data. The result shows that there are even 10 dB deviations in 63Hz octave band frequency range and relatively less variations are occurred in other low frequency ranges. Such variations seems to be coming from modal overlaps of the receiving room. According to current rating method of floor impact sound. KS F 2863-2, that may affect on the single number latins scheme. From the result of tests in this study, there are 2dB to 6dB differences in the sin91e number with the combination of measurement points. This means that the reduction of measurement variations from the microphone positions is needed for a better credibility of measurement results.

• The Journal of the Acoustical Society of Korea
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• v.25 no.5
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• pp.213-221
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• 2006

Phone segmentation of speech waveform is especially important for concatenative text to speech synthesis which uses segmented corpora for the construction of synthetic units. because the quality of synthesized speech depends critically on the accuracy of the segmentation. In the beginning. the phone segmentation was manually performed. but it brings the huge effort and the large time delay. HMM-based approaches adopted from automatic speech recognition are most widely used for automatic segmentation in speech synthesis, providing a consistent and accurate phone labeling scheme. Even the HMM-based approach has been successful, it may locate a phone boundary at a different position than expected. In this paper. we categorized adjacent phoneme pairs and analyzed the mismatches between hand-labeled transcriptions and HMM-based labels. Then we described the dominant error patterns that must be improved for the speech synthesis. For the experiment. hand labeled standard Korean speech DB from ETRI was used as a reference DB. Time difference larger than 20ms between hand-labeled phoneme boundary and auto-aligned boundary is treated as an automatic segmentation error. Our experimental results from female speaker revealed that plosive-vowel, affricate-vowel and vowel-liquid pairs showed high accuracies, 99%, 99.5% and 99% respectively. But stop-nasal, stop-liquid and nasal-liquid pairs showed very low accuracies, 45%, 50% and 55%. And these from male speaker revealed similar tendency.

• Journal of the Korea Society of Computer and Information
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• v.29 no.4
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• pp.115-123
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• 2024

In this paper, we propose a vibration notification system that combines navigation information and wearable bands to ensure safe driving for the transportation vulnerable. This system transmits navigation driving information to a linked application, converts it into a vibration signal, and provides notifications through a wearable band. Existing navigation systems focus on providing route guidance and location information, so the driver's concentration is dispersed, and safety and convenience are deteriorated, especially for those with mobility impairments, due to standard vision and delayed recognition of stimuli, resulting in an increasingly high traffic accident rate. To solve this problem, navigation driving information is converted into vibration signals through a linked application, and vibration notifications for events, left turns, right turns, and speeding are provided through a wearable band to ensure driver safety and convenience. In the future, we will use cameras and vehicle sensors to increase awareness of safety inside and outside the vehicle by adding a function that provides notifications with vibration and LED when the vehicle approaches or recognizes an object, and we will continue to conduct research to build a safer driving environment. plan.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.77-85
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• 2024

In this dissertation, a we designed and implemented a patrol robot that integrates a thermal imaging camera, speed dome camera, PTZ camera, radar, lidar sensor, and smartphone. This robot has the ability to monitor and respond efficiently even in complex environments, and is especially designed to demonstrate high performance even at night or in low visibility conditions. An orbital movement system was selected for the robot's mobility, and a smartphone-based control system was developed for real-time data processing and decision-making. The combination of various sensors allows the robot to comprehensively perceive the environment and quickly detect hazards. Thermal imaging cameras are used for night surveillance, speed domes and PTZ cameras are used for wide-area monitoring, and radar and LIDAR are used for obstacle detection and avoidance. The smartphone-based control system provides a user-friendly interface. The proposed robot system can be used in various fields such as security, surveillance, and disaster response. Future research should include improving the robot's autonomous patrol algorithm, developing a multi-robot collaboration system, and long-term testing in a real environment. This study is expected to contribute to the development of the field of intelligent surveillance robots.