• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.9A
• /
• pp.719-726
• /
• 2009

CR systems performs spectrum sensing operation to detect the appearance of primary users. However, since it is not feasible to do spectrum sensing and data transmission simultaneously, they typically operate alternatively in a time domain. There have been an effort(8) to investigate the optimal spectrum sensing duration for maximum throughput for the scheme with cooperative spectrum sensing. This is based on an assumption that the communication channels between each secondary user and the fusion center are ideal and does not consider the effects of transmission error. Motivated by this, we here model the channels as binary symmetric channels and examined its effect on the maximum throughput and the associated optimal sensing duration. Analysis shows that the performance degradation due to the transmission error is smaller for the case of using the AND fusion rule than for the OR fusion rule.

• Journal of Korean Neurosurgical Society
• /
• v.64 no.6
• /
• pp.901-912
• /
• 2021

Objective : In the cervical spine, many surgical procedures have been developed to achieve optimal results for various disorders, including degenerative diseases, traumatic injury, and tumor. In this study, we report our experience and follow-up results with a new surgical technique for cervical spine entitled posterior floating laminotomy (PFL) in comparison with conventional laminectomy and fusion (LF). Methods : Data for 85 patients who underwent conventional LF (n=66) or PFL (n=19) for cervical spine disorders between 2012 and 2019 were analyzed. Radiological parameters, including cervical lordosis (CL), T1 slope (T1S), segmental lordosis (SL), and C2-7 sagittal vertical axis (SVA), were measured with lateral spine X-rays. Functional outcomes, comprising the modified Japanese Orthopaedic Association (mJOA), neck disability index (NDI), and visual analog scale (VAS) scores, were also measured. For the patients who underwent PFL, postoperative magnetic resonance image (MRI) was performed in a month after the surgery, and the degree of decompression was evaluated at the T2-weighted axial image, and postoperative computed tomography (CT) was conducted immediately and 1 year after the operation to evaluate the gutter fusion. Results : There was no difference in CL, T1S, SL, and C2-7 SVA between the groups but there was a difference in the preoperative and postoperative SL angles. The mean difference in the preoperative SL angle compared with that at the last follow-up was -0.3° after conventional LF and 4.7° after PFL (p=0.04), respectively. mJOA, NDI, and VAS scores showed significant improvements (p<0.05) during follow-up in both groups. In the PFL group, postoperative MRI showed sufficient decompression and postoperative CT revealed gutter fusion at 1 year after the operation. Conclusion : PFL is a safe surgical method which can preserve postoperative CL and achieve good clinical outcomes.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.37 no.2
• /
• pp.16-28
• /
• 2000

In this paper, we propose a navigation algorithm for a mobile robot, which is intelligently searching the goal location in unknown dynamic environments using an ultrasonic sensor. Instead of using "sensor fusion"method which generates the trajectory of a robot based upon the environment model and sensory data, "command fusion"method is used to govern the robot motions. The major factors for robot navigation are represented as a cost function. Using the data of the robot states and the environment, the weight value of each factor is determined for an optimal trajectory in dynamic environments. For the evaluation of the proposed algorithm, we peformed simulations in PC as well as real experiments with ZIRO. The results show that the proposed algorithm is apt to identify obstacles in unknown environments to guide the robot to the goal location safely.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.22 no.5
• /
• pp.126-135
• /
• 2014

This paper describes the development and verification of control algorithms for V2X and environmental sensor integrated intersection support and safety systems. The objective of the research is to develop core technologies for effective fusion of V2X and environmental sensors and to develop new safety function for intersection safety. One of core technologies is to achieve the improvement of GPS accuracy, and the other is to develop the algorithm of a vehicle identification which matches all data from V2X, vehicle sensors and environmental sensors to specific vehicles. A intersection optimal pass (IOP) algorithm is designed based on these core technologies. IOP recommends appropriate speed to pass the intersection in the consideration of traffic light signal and preceeding vehicle existence. Another function is developed to prevent a collision avoidance when car crash caused by traffic violation of surrounding vehicles is expected. Finally all functions are implemented and tested in three test vehicles. It is shown that IOP can support convenient and comfortable driving with recommending optimal pass speed and collision avoidance algorithm can effectively prevent collision caused by traffic sign violation of surrounding vehicles.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.36S no.9
• /
• pp.49-57
• /
• 1999

The fusion of fuzzy set theory and neural networks technologies have concentrated on applying neural networks to obtain the optimal rule bases of fuzzy logic system. Unfortunately, this is very hard to achieve due to limited learning capabilities of neural networks. To overcome this difficulty, we propose a new approach in which rough set theory and neuro-fuzzy fusion are combined to obtain the optimal rule base from input/output data. Compared with conventional FNN, the proposed algorithm is considerably more realistic because it reduces overlapped data when construction a rule base. This results are applied to the construction of inference rules for controlling the temperature at specified points in a refrigerator.

• Nuclear Engineering and Technology
• /
• v.48 no.3
• /
• pp.795-798
• /
• 2016

Transmission X-ray tubes based on carbon nanotube have attracted significant attention recently. In most of these tubes, tungsten is used as the target material. In this article, the well-known simulator Geant4 was used to obtain some of the tungsten target parameters. The optimal thickness for maximum production of usable X-rays when the target is exposed to electron beams of different energies was obtained. The linear variation of optimal thickness of the target for different electron energies was also obtained. The data obtained in this study can be used to design X-ray tubes. A beryllium window was considered for the X-ray tube. The X-ray energy spectra at the moment of production and after passing through the target and window for different electron energies in the 30-110 keV range were also obtained. The results obtained show that with a specific thickness, the target material itself can act as filter, which enables generation of X-rays with a limited energy.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.44-46
• /
• 2003

In 1996, Thailand's participation in the Pacific Rim as a part of NASA's Mission to Planet Earth (MTPE) Program, was titled 'AIRSAR Thailand Project'. In this project the Department of Land Development utilized Topographic SAR (TOPSAR) which had multi-frequencies: C band, L band, and P band with multi-polarization: HH, VV, and HV as well as C band VV DEM. Satellite data such as LANDSAT TM was also utilized for optimal use. Results of AIRSAR image processing including data fusion among difference wavelength bands and polarization revealed the quality of AIRSAR that best suit for detection of agricultural land uses. The HH-L band AIRSAR was proven to be useful to distinguish among crop types when combined with appropriate data. The HH, VV, and HV-P band enhanced surface characteristics of swamp forest and wetland. In addition, TOPSAR has its great advantage for identification of salt farms and shrimp ponds.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.15 no.3
• /
• pp.593-602
• /
• 2020

Recently, as research on smart farms has been actively conducted, systems for efficiently cultivating crops have been introduced and various energy systems using renewable energy such as solar, geothermal and wind power generation have been proposed to save the energy. In this paper, we propose a new and renewable energy convergence system for crops that provides energy independence and improved crop cultivation environment. First, we present LPWA-based communication node and gateway for ICT-based data collection. Then we propose an integrated monitoring server that collects energy data, crop growth data, and environmental data through a communication node and builds it as big data to perform optimal energy management that reflects the characteristics of the environment for cultivating crops. The proposed system is expected to contribute to the production of low-cost, high-quality crops through the fusion of renewable energy and smart farms.

• Journal of Broadcast Engineering
• /
• v.27 no.6
• /
• pp.885-896
• /
• 2022

Motor failure in manufacturing plays an important role in future A/S and reliability. Motor failure is detected by measuring sound, current, and vibration. For the data used in this paper, the sound of the car's side mirror motor gear box was used. Motor sound consists of three classes. Sound data is input to the network model through a conversion process through MelSpectrogram. In this paper, various methods were applied, such as data augmentation to improve the performance of classifying fault motors and various methods according to class imbalance were applied resampling, reweighting adjustment, change of loss function and representation learning and classification into two stages. In addition, the curriculum learning method and self-space learning method were compared through a total of five network models such as Bidirectional LSTM Attention, Convolutional Recurrent Neural Network, Multi-Head Attention, Bidirectional Temporal Convolution Network, and Convolution Neural Network, and the optimal configuration was found for motor sound classification.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.65 no.2
• /
• pp.130-135
• /
• 2016

Gait recognition has advantage of non-contact type recognition. But It has disadvantage of low recognition rate when the pedestrian silhouette is changed due to bag or coat. In this paper, we proposed new method using combination of gait energy image feature and thermal face image feature. First, we extracted a face image which has optimal focusing value using human body rate and Tenengrad algorithm. Second step, we extracted features from gait energy image and thermal face image using linear discriminant analysis. Third, calculate euclidean distance between train data and test data, and optimize weights using genetic algorithm. Finally, we compute classification using nearest neighbor classification algorithm. So the proposed method shows a better result than the conventional method.