• KSII Transactions on Internet and Information Systems (TIIS)
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• 제2권6호
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• pp.280-298
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• 2008

For efficient content-based image retrieval, diverse visual features such as color, texture, and shape have been widely used. In the case of leaf images, further improvement can be achieved based on the following observations. Most plants have unique shape of leaves that consist of one or more blades. Hence, blade-based matching can be more efficient than whole shape-based matching since the number and shape of blades are very effective to filtering out dissimilar leaves. Guaranteeing rotational invariance is critical for matching accuracy. In this paper, we propose a new shape representation, indexing and matching scheme for leaf image retrieval. For leaf shape representation, we generated a distance curve that is a sequence of distances between the leaf’s center and all the contour points. For matching, we developed a blade-based matching algorithm called rotation invariant - partial dynamic time warping (RI-PDTW). To speed up the matching, we suggest two additional techniques: i) priority queue-based pruning of unnecessary blade sequences for rotational invariance, and ii) lower bound-based pruning of unnecessary partial dynamic time warping (PDTW) calculations. We implemented a prototype system on the GEMINI framework [1][2]. Using experimental results, we showed that our scheme achieves excellent performance compared to competitive schemes.

• Journal of Radiation Protection and Research
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• 제46권3호
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• pp.112-119
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• 2021

Background: This work aims to develop a new imaging system based on a pulse shape discrimination-capable Cs₂LiYCl₆:Ce (CLYC) scintillation detector combined with the rotational modulation collimator (RMC) technique for dual-particle imaging. Materials and Methods: In this study, a CLYC-based RMC system was designed based on Monte Carlo simulations, and a prototype was fabricated. Therein, a rotation control system was developed to rotate the RMC unit precisely, and a graphical user interface-based software was also developed to operate the data acquisition with RMC rotation. The RMC system was developed to allow combining various types of collimator masks and detectors interchangeably, making the imaging system more versatile for various applications and conditions. Results and Discussion: Operational performance of the fabricated system was studied by checking the accuracy and precision of the collimator rotation and obtaining modulation patterns from a gamma-ray source repeatedly. Conclusion: The prototype RMC system showed reliability in its mechanical properties and reproducibility in the acquisition of modulation patterns, and it will be further investigated for its dual-particle imaging capability with various complex radioactive source conditions.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.728-735
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• 2022

Roofers get exposed to increased risk of knee musculoskeletal disorders (MSDs) at different phases of a sloped shingle installation task. As different phases are associated with different risk levels, this study explored the application of machine learning for automated classification of seven phases in a shingle installation task using knee kinematics and roof slope information. An optical motion capture system was used to collect knee kinematics data from nine subjects who mimicked shingle installation on a slope-adjustable wooden platform. Four features were used in building a phase classification model. They were three knee joint rotation angles (i.e., flexion, abduction-adduction, and internal-external rotation) of the subjects, and the roof slope at which they operated. Three ensemble machine learning algorithms (i.e., random forests, decision trees, and k-nearest neighbors) were used for training and prediction. The simulations indicate that the k-nearest neighbor classifier provided the best performance, with an overall accuracy of 92.62%, demonstrating the considerable potential of machine learning methods in detecting shingle installation phases from workers knee joint rotation and roof slope information. This knowledge, with further investigation, may facilitate knee MSD risk identification among roofers and intervention development.

• 한국측량학회지
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• 제32권6호
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• pp.625-635
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• 2014

Multiple strips are required for large area mapping using ALS (Airborne Laser Scanner) system. LiDAR (Light Detection And Ranging) data collected from the ALS system has discrepancies between strips due to systematic errors of on-board laser scanner and GPS/INS, inaccurate processing of the system calibration as well as boresight misalignments. Such discrepancies deteriorate the overall geometric quality of the end products such as DEM (Digital Elevation Model), building models, and digital maps. Therefore, strip adjustment for minimizing discrepancies between overlapping strips is one of the most essential tasks to create seamless point cloud data. This study implemented area-based matching (ABM) to determine conjugate features for computing 3D transformation parameters. ABM is a well-known method and easily implemented for this purpose. It is obvious that the exact same LiDAR points do not exist in the overlapping strips. Therefore, the term "conjugate point" means that the location of occurring maximum similarity within the overlapping strips. Coordinates of the conjugate locations were determined with sub-pixel accuracy. The major drawbacks of the ABM are sensitive to scale change and rotation. However, there is almost no scale change and the rotation angles are quite small between adjacent strips to apply AMB. Experimental results from this study using both simulated and real datasets demonstrate validity of the proposed scheme.

• 한국정밀공학회지
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• 제28권3호
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• pp.265-274
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• 2011

This paper presents current state of the prediction simulator of structural characteristics of machinery equipment accuracy. Developed accuracy prediction simulator proceeds and estimates the structural analysis between the designer and simulator through the internet for convenience of designer. 3D CAD model which is input to the accuracy prediction simulator would simplified by the process of removing the small hole, fillet and chamfer. And the structural surface joints would be presented as the spring elements and damping elements for the structural analysis. The structural analysis of machinery equipment joints, containing rotary motion unit, linear motion unit, mounting device and bolted joint, are presented using Finite Element Method and their experiment. Finally, a general method is presented to tune the static stiffness at a rotation joint considering the whole machinery equipment system by interactive use of Finite Element Method and static load experiment.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1995년도 봄 학술발표회 논문집
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• pp.17-27
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• 1995

For the post-buckling and elasto-plastic analysis of shell structures, the total Lagrangian formulation is presented based upon the degenerated shell element. Geometrically correct formulation is developed by updating the direction of normal vectors in the iteration process and evaluating the total Green-Lagrange stain corresponding U total displacements. In the calculation of the stiffness matrix, the element formulation takes into account the effect of finite rotation increments by retaining second order rotation terms in the incremental displacement field. The selective or reduced integration scheme using the heterosis element is applied in order to overcome both shear locking phenomena and the zero energy mode. The load/displacement incremental scheme is adopted for geometric non-linear F .E. analysis. Based on such methodology, the computer program is developed and numerical examples to demonstrate the accuracy and the effectiveness of the proposed shell element are presented and compared with references's results.

• Journal of Information Processing Systems
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• 제11권2호
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• pp.165-172
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• 2015

The inactive student rate is becoming a major problem in most open universities worldwide. In Indonesia, roughly 36% of students were found to be inactive, in 2005. Data mining had been successfully employed to solve problems in many domains, such as for educational purposes. We are proposing a method for preventing inactive students by mining knowledge from student record systems with several state of the art ensemble methods, such as Bagging, AdaBoost, Random Subspace, Random Forest, and Rotation Forest. The most influential attributes, as well as demographic attributes (marital status and employment), were successfully obtained which were affecting student of being inactive. The complexity and accuracy of classification techniques were also compared and the experimental results show that Rotation Forest, with decision tree as the base-classifier, denotes the best performance compared to other classifiers.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 춘계학술대회 논문집
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• pp.1944-1947
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• 2005

In this paper, the control of a prosthetic arm using the flex sensor signal is described. The flex sensors are attached to the biceps and triceps brchii muscle. The signals are passed a differential amplifier and noise filter. And then the signals are converted to digital data by PCI 6036E ADC. From the data, position and velocity of arm joint are obtained. Also motion of the forearm - flexion and extension, the pronation and supination are abstracted from the data by proposed algorithm. A two D.O.F arm with RC servo-motor is designed for experiment. The arm length is 200 mm, weight is 4.5 N. The rotation angle of elbow joint is $120^{\circ}$. Also the rotation angle of the wrist is $180^{\circ}$. Through the experiment, we verified the possibility of the prosthetic arm control using the flex sensor signal. We will try to improve the control accuracy of the prosthetic arm continuously.

• Journal of Astronomy and Space Sciences
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• 제16권2호
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• pp.159-166
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• 1999

As the spatial resolution of remote sensing satellites becomes higher, very accurate determination of the position of a LEO (Low Earth Orbit) satellite is demanding more than ever. Non-symmetric Earth gravity is the major perturbation force to LEO satellites. Since the orbit propagation is performed in the celestial frame while Earth gravity is defined in the terrestrial frame, it is required to convert the coordinates of the satellite from one to the other accurately. Unless the coordinate conversion between the two frames is performed accurately the orbit propagation calculates incorrect Earth gravitational force at a specific time instant, and hence, causes errors in orbit prediction. The coordinate conversion between the two frames involves precession, nutation, Earth rotation and polar motion. Among these factors, unpredictability and uncertainty of Earth rotation, called UTI-UTC, is the largest error source. In this paper, the effect of UTI-UTC on the accuracy of the LEO propagation is introduced, tested and analzed. Considering the maximum unpredictability of UTI-UTC, 0.9 seconds, the meaningful order of non-spherical Earth harmonic functions is derived.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1995년도 춘계공동학술대회논문집; 전남대학교; 28-29 Apr. 1995
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• pp.587-599
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• 1995

This paper proposes a method for pattern recognition using spectral analysis and a hybrid genetic-neural-fuzzy networks. The feature vectors using spectral analysis on contour sequences of 2-D images are extracted, and the vectors are not effected by translation, rotation and scale variance. A combined model using the advantages of conventional method is proposed, those are supervised learning BP, global searching genetic algorithm, and unsupervised learning fuzzy c-method. The proposed method is applied to 10 aircraft recognition to confirm the performance of the method. The experimental results show that the proposed method is better accuracy than conventional method using BP or fuzzy c-method, and learning speed is enhanced.