• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.1
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• pp.26-32
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• 2005

Rotor position information is essential in the operation of the switched reluctance motor(SRM) drive for generation the phase current switching signals. When an incremental encoder is used as a rotor position sensor, the initial rotor position can not be detected. Some sensorless rotor position estimation methods also have the same problem. In these systems, to initially align the rotor, the forced alignment method has a delay and reverse rotation before the motor can start. Therefore it can not be acceptable for unidirectional drive systems. So the forced alignment method is not desirable in all drive systems and the research on the SRM drives should be directed to a system without rotor alignment. In this paper, a new detection method of initial rotor position using the rate of change of current is suggested. Firstly, di/dt versus θ/sub R/ reference table, which is the relation between the rate of change of current and rotor position, is generated and then the squared Euclidean distance method is used to estimate the rotor position based on the table. The simulated and experimental results are presented demonstrating the feasibility and accuracy of this method.

• Journal of The Korean Association For Science Education
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• v.33 no.3
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• pp.679-693
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• 2013

The purpose of this study is to develop an inventory to classify task commitment types of science learning and to classify highschool students' task commitment types. Firstly, inventory questions were designed following the literature analysis on the task commitment components which involve self confidence, high goal setting, and focused attention. Prototype inventory underwent the content validity test, pilot test, and reliability test. Through these steps, final inventory was input to 462 high school students and underwent the factor analysis and cluster analysis. Factor analysis confirmed three components of task commitment as the three factors of inventory questions. In order to find how many clusters exist, factors of developed inventory became new variables. Each factor's factor mean was calculated and served as the new variable of the cluster analysis. Cluster analysis extracted five clusters as task commitment types. The 5 clusters were suggested by the agglomarative schedule and dendrogram gained from a hierarchical cluster analysis with the setting of the Ward algorithm and Squared Euclidean distance. Based on the factor mean score, traits of each cluster could be drawn out. Inventory developed by this study is expected to be used to identify student commitment types and assess the effectiveness of task commitment enhancement programs.

• Proceedings of the KIPE Conference
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• 2003.07b
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• pp.681-685
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• 2003

In this paper, an sensing method of initial rotor position in Switched Reluctance Motor(SRM) at standstill is proposed. In case search coils are used as a position sensor, A search coil used in a method of detecting positions of TSRM has many advantages, which is highly efficient in low cost and maintenance free, and characterized by its function and role as a position sensor. However, the initial rotor position detection is very difficult because the search coil's EMF is not exist at a standstill. In this paper, a new sensing method of initial rotor position using squared Euclidean distance at a standstill too is suggested. The simulation and experiment for the proposed method are achieved. The validity of the proposed method is verified by experimental results.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.2
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• pp.37-44
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• 2002

In this paper, the Viterbi decoder containing new branch metrics of the squared Euclidean distance with multiple order phase differences is introduced in order to improve the bit error rate (BER) in the differential detection of the trellis-coded MDPSK-DFDM. The proposed Viterbi decoder is conceptually same as the sliding multiple phase differential detection method that uses the branch metric with multiple phase differences. Also, we describe the Viterbi algorithm in order to use this branch metrics. Our study shows that such a Viterbi decoder improves BER peformance without sacrificing bandwidth and power efficiency. Also, the proposed algorithm can be used in the single carrier modulation.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.31A no.6
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• pp.1-8
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• 1994

In this paper, in order to apply the idea MDPSK to TCM, we use signal set expansion and set partition by phase differences. Through this we propose the trellis-coded MDPSK. And the Viterbi decoder containing branch metrics of the squared Euclidean distance of the Lth order phase difference as well as the first order phase difference is introduced in order to improve the bit error rate(BER) in the differential detection of the trellis-coded MDPSK. The proposed Viterbi decoder is conceptually same to the sliding multiple symbol dection method which uses the branch metric with the first and Lth order phase differences. We investigate the performance of the uncoded DQPSK and the trallis-coded D8PSK in additive white Gaussian noise (AWGN) through the Monte Carlo simulation under the two cases of using and not using the Lth order phase difference metric. The study shows that trellis-coded 8DPSK is an attractive scheme for power and bandlimited systems while also improving the BER performance when the Viterbi decoder is employed to the Lth order phase order difference metric. This performance improvement has been obtained without sacrificing the bandwidth or the power efficiency.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.4
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• pp.405-414
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• 2016

IC-implementations provide high performance for solving the high computational cost of pattern matching but have relative low flexibility for satisfying different applications. In this paper, we report an associative memory architecture for k nearest neighbor (KNN) search, which is one of the most basic algorithms in pattern matching. The designed architecture features reconfigurable vector-component parallelism enabled by programmable switching circuits between vector components, and a dedicated majority vote circuit. In addition, the main time-consuming part of KNN is solved by a clock mapping concept based weighted frequency dividers that drastically reduce the in principle exponential increase of the worst-case search-clock number with the bit width of vector components to only a linear increase. A test chip in 180 nm CMOS technology, which has 32 rows, 8 parallel 8-bit vector-components in each row, consumes altogether in peak 61.4 mW and only 11.9 mW for nearest squared Euclidean distance search (at 45.58 MHz and 1.8 V).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.568-573
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• 2002

In this paper, the Viterbi decoder containing new branch metrics of the squared Euclidean distance with multiple order phase differences is introduced in order to improve the bit error rate (BER) in the differential detection of the trellis-coded MDPSK-OFDM. The proposed Viterbi decoder is conceptually same as the Continuous multiple phase differential detection method that uses the branch metric with multiple phase differences. Also, we describe the Viterbi algorithm in order to use this branch metrics. Our study shows that such a Viterbi decoder improves BER performance without sacrificing bandwidth and power efficiency Also. the proposed algorithm ran be used in the single carrier modulation.

• Journal of Power Electronics
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• v.5 no.3
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• pp.173-179
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• 2005

In this paper, a very low cost and robust sensing method for the rotor position of a TSRM(Toroidal Switched Reluctance Motors) is described. Position information of the rotor is essential for SRM drives. The rotor position sensor such as an opto-interrupter or high performance encoder is generally used for the estimation of rotor position. However, these discrete position sensors not only add complexity and cost to the system but also tend to reduce the reliability of the drive system. In order to solve these problems, in the proposed method, rotor position detection is achieved using voltage waveforms induced by the time varying flux linkage in the search coils, and then the appropriate phases are excited to drive the SRM. But the search coil's EMF is generated only when the motor rotates. Therefore the rotor position sensing method using squared Euclidean distance at a standstill is also examined. The simulation and experimental results are presented to verify the performance of the proposed method in this paper.

• Journal of Ocean Engineering and Technology
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• v.37 no.4
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• pp.145-157
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• 2023

Due to a recent increase in maritime activities in South Korea, the frequency of maritime distress is escalating and poses a significant threat to lives and property. The aim of this study was to validate a drift trajectory prediction technique to help mitigate the damages caused by maritime distress incidents. In this study, OpenDrift was verified using satellite drifter data from the Korea Hydrographic and Oceanographic Agency. OpenDrift is a Monte-Carlo-based Lagrangian trajectory modeling framework that allows for considering leeway, an important factor in predicting the movement of floating marine objects. The simulation results showed no significant differences in the performance of drift trajectory prediction when considering leeway using four evaluation methods (normalized cumulative Lagrangian separation, root mean squared error, mean absolute error, and Euclidean distance). However, leeway improved the performance in an analysis of location prediction conformance for maritime search and rescue operations. Therefore, the findings of this study suggest that it is important to consider leeway in drift trajectory prediction for effective maritime search and rescue operations. The results could help with future research on drift trajectory prediction of various floating objects, including marine debris, satellite drifters, and sea ice.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.670-684
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• 2024

3D Cross-Modal Retrieval (3DCMR) is a task that retrieves 3D objects regardless of modalities, such as images, meshes, and point clouds. One of the most prominent methods used for 3DCMR is the Cross-Modal Center Loss Function (CLF) which applies the conventional center loss strategy for 3D cross-modal search and retrieval. Since CLF is based on center loss, the center features in CLF are also susceptible to subtle changes in hyperparameters and external inferences. For instance, performance degradation is observed when the batch size is too small. Furthermore, the Mean Squared Error (MSE) used in CLF is unable to adapt to changes in batch size and is vulnerable to data variations that occur during actual inference due to the use of simple Euclidean distance between multi-modal features. To address the problems that arise from small batch training, we propose a Noisy Center Loss (NCL) method to estimate the optimal center features. In addition, we apply the simple Siamese representation learning method (SimSiam) during optimal center feature estimation to compare projected features, making the proposed method robust to changes in batch size and variations in data. As a result, the proposed approach demonstrates improved performance in ModelNet40 dataset compared to the conventional methods.