• Korean Journal of Applied Biomechanics
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• v.26 no.2
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• pp.175-181
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• 2016

Objective: The aim of this study was to investigate age-related changes of multi-finger synergy during a constant force production task with and without an additional mechanical constraint. Method: Fourteen elderly subjects (age: $78.50{\pm}4.63yrs$, height: $157.29{\pm}8.97cm$, weight: $65.13{\pm}6.93kg$) and 14 young subjects (age: $21.13{\pm}1.35yrs$, height: $171.57{\pm}8.43cm$, weight: $70.29{\pm}16.77kg$) participated in this study. The subjects were asked to place their index and middle fingers on two force transducers fixed on a small non-moving teeterboard and produce 10 N by pressing the sensors while watching force feedback on a computer screen under the no additional constraint condition (NAC). The subjects also performed the same task with an additional mechanical constraint (AC) where the subjects were asked to balance a teeterboard that could be rotated by finger forces. An uncontrolled manifold approach was used to calculate within-trial and between-trial multi-finger synergy indices, variance in uncontrolled subspace ($V_{UCM}$), and variance in subspace orthogonal to UCM subspace ($V_{ORT}$). Two-way repeated measured ANOVA was performed with the within-factor of task condition (with and without an additional constraint) and the between factor of groups (elderly and young). Results: The elderly group showed significantly increased within-trial $V_{ORT}$ in AC compared with NAC (p < .05) while the young group showed no significant difference between AC and NAC. There was no significant group difference for within-trial $V_{UCM}$. Between-trial $V_{ORT}$ remained unchanged between groups and conditions. However, between-trial $V_{UCM}$ for the elderly group significantly decreased in AC as compared to NAC, along with no significant difference for the young group. For multi-finger synergy, there was no significant group difference of within-trial synergy. However, between-trial synergy for the elderly group significantly decreased in AC as compared to NAC (p < .05). Conclusion: Our results indicate that aging decreased consistency (i.e., ability to perform the task on a moment-to-moment basis) with an additional mechanical constraint. In addition, aging was associated with decreased multi-finger synergy on a trial-to-trial basis.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.4
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• pp.396-400
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• 2009

The demand of JIB crane to handle a container or a bulk in a vessel is increasingly because of the growth of the scale of trade through the sea. This deck crane such as JIB crane is required the weight reduction design because it is installed in the deck of a vessel due to the environment regulation. In this study first we carry out the structural analysis of JIB with respect to the luffing angle of it to calculate the maximum equivalent stress of JIB, and next the optimum design for the weight reduction design of JIB. The thickness in a cross section of JIB is adopted as the design variable, the weight of JIB as the objective function, and the von mises stress as the constraint condition for the optimum design of JIB using the ANSYS 10.0.

• The Journal of the Acoustical Society of Korea
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• v.36 no.3
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• pp.151-157
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• 2017

A general linearly constrained adaptive array is proposed to improve the nulling performance. The nulling performance is examined in the array weight vector space. It is shown that the constraint plane is shifted to the origin perpendicularly by the gain factor such that the increase of the gain factor results in the decrease of the distance from the constraint plane to the origin. Thus the variation of the gain factor has an effect on the extent of orthogonality between the weight vector and the steering vectors for the interferences such that the nulling performance of the general linearly constrained adaptive array is improved by the gain factor. It is observed that the proposed adaptive array with an optimum value of the gain factor yields a better nulling performance in coherent signal environment and a similar nulling performance in noncoherent signal environment compared to the conventional linearly constrained adaptive array.

• Journal of Advanced Navigation Technology
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• v.22 no.2
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• pp.111-122
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• 2018

At present, the ground transportation system is saturated in many countries including Korea. To overcome this problem, many researches of developing a roadable personal air vehicle (PAV) are being carried out to alleviate traffic congestion and to accomplish door-to-door mobility through three-dimensional traffic system. In this study, the thrust-to-weight ratio, the wing loading, and the power-to-weight ratio that are major design parameters for the sizing of roadable PAVs were calculated under the constraints of ground roll, climb rate, maximum cruise speed, service ceiling, stall speed. Also, in the sizing process, the study was conducted to determine the design point using the graphs of thrust-to-weight ratio, wing loading, power-to-weight ratio, and brake horse power for the mission profiles considering domestic environments and the FAR PART 23 which is the GA class aircraft certification standard.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.492-497
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• 2000

This paper focuses on the weight minimization of radial gate, as an extention of the previous work. Radial gates are commonly used to regulate the flow-rate of general purpose dams, due to its simplicity in manufacture and control. The present study identifies the optimum position of support point for 2 and 3 arm type radial gate, which guarantees the minimum weight satisfying strength constraint condition. These optimum designs are then compared with previously constructed radial gates. The results indicate that the weights of the optimized radial gates reduce by about 20%, compared to those of the conventionally designed radial gates.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.3
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• pp.17-23
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• 2008

In this research article, scheduling a casting sequence in a job-shop type foundry involving a variety of casts made of an identical alloy but with different shapes and II weights, has been investigated. The objective is to produce the assigned mixed orders satisfying due dates and obtaining the highest ingot efficiency simultaneously. Implementing simple integer programming instead of complicated genetic algorithms accompanying rigorous calculations proves that it can provide a feasible solution with a high accuracy for a complex, multi-variable and multi-constraint optimization problem. Enhancing the ingot efficiency under the constraint of discrete ingot sizes is accomplished by using a simple and intelligible algorithm in a standard integer programming. Employing this simple methodology, a job-shop type foundry is able to maximize the furnace utilization and minimize ingot waste.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1990.10a
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• pp.95-100
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• 1990

An optimization method has been developed to find the minimum weight design of steel building structures which consist of the commercially available discrete sections. In this study, an emphasis was particularly placed on the practical applicability of optimization algorithm in engineering practice. The structure Is optimized through element optimization under the element level constraints first and then, if there is any violation of structural level constraints, it is adequately compensated by the constraint error correction vector obtained through the sensitivity analysis. A scaling procedure is introduced for the problems of large violated displacement constraint. The oscillation control in the objective function is also discussed. By dividing the available H-sections into two groups based on their section characteristics, much improved relationships between section variables were obtained and used efficiently in searching the optimum section in the section table.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.6
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• pp.71-78
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• 1997

In this paper, a new neural network training algorithm will be devised for function approximator with good generalization characteristics and tested with the time series prediction problem using santaFe competition data sets. To enhance the generalization ability a constraint term of hidden neuraon activations is added to the conventional output error, which gives the curvature smoothing characteristics to multi-layer neural networks. A hybrid learning algorithm of the error-back propagation and Hebbian learning algorithm with weight decay constraint will be naturally developed by the steepest decent algorithm minimizing the proposed cost function without much increase of computational requriements.

• Bulletin of the Korean Chemical Society
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• v.34 no.1
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• pp.197-200
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• 2013

The bound state wave functions for all the known exactly solvable potentials can be expressed in terms of orthogonal polynomials because the polynomials always satisfy the boundary conditions with a proper weight function. The orthogonality of polynomials is of great importance because the orthogonality characterizes the wave functions and consequently the quantum system. Though the orthogonality of orthogonal polynomials has been known for hundred years, the known orthogonality is found to be inadequate for polynomials appearing in some exactly solvable potentials, for example, Ginocchio potential. For those potentials a more general orthogonality is defined and algebraically derived. It is found that the general orthogonality is valid with a certain constraint and the constraint is very useful in understanding the system.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.441-452
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• 2021

Federated learning provides an efficient integrated model for distributed data, allowing the local training of different data. Meanwhile, the goal of multi-task learning is to simultaneously establish models for multiple related tasks, and to obtain the underlying main structure. However, traditional federated multi-task learning models not only have strict requirements for the data distribution, but also demand large amounts of calculation and have slow convergence, which hindered their promotion in many fields. In our work, we apply the rank constraint on weight vectors of the multi-task learning model to adaptively adjust the task's similarity learning, according to the distribution of federal node data. The proposed model has a general framework for solving optimal solutions, which can be used to deal with various data types. Experiments show that our model has achieved the best results in different dataset. Notably, our model can still obtain stable results in datasets with large distribution differences. In addition, compared with traditional federated multi-task learning models, our algorithm is able to converge on a local optimal solution within limited training iterations.