• Journal of Korean Society of Transportation
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• v.27 no.1
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• pp.129-141
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• 2009

Intermodal freight transportation is defined as the movement of freight from origins to destinations by two or more transportation modes. When implemented in hub networks, it could enhance the efficiency of the networks because consolidated flows are transported by more suitable modes and technologies. In spite of this advantage, the intermodal hub network design problem has received limited attention in the literature partly because of the complex nature of the problem. This paper aims to develop an optimization model for designing intermodal hub networks with sin91e allocation strategy. The model takes into account various cost components of intermodal hub networks including transportation, stationary inventory, and service delay costs. Moreover, using transport frequency variables, it is capable of endogenously determining the transportation economies of scale achieved by consolidation of flows. As such, the model is able to realistically represent the characteristics of intermodal hub networks in practice. Since the model Is a complicated nonlinear integer programming problem, we perform model simplification based on the analytical study of the model, which could facilitate the development of solution algorithms in the future. We expect that this study contributes to the design of intermodal hub networks as well as to the assessment of existing logistics systems.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.46-51
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• 2014

The most important process of engineering system optimal design is to identify the relationship between the design variables and system response. In case of the system optimization, Response Surface Method (RSM) is widely used. The optimization process of RSM generates the design space using the typical alternative candidates and finds the optimal design point in the generated design space. By changing the optimal point depending on the configuration of the design space, it is important to generate the design space. Therefor in this study, the design space is generated by using the relationship between design variables and system response based on Neuro-Response Surface Method (NRSM). And I try to construct the framework for optimal shape design based on NRSM that the optimum shape can be predicted using the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) within the generated design space. In order to verify the usefulness of the constructed framework, we applied the nonlinear mathematical function problem. In this study, we can solve the constraints of time in the optimization process for the engineering problem and effective to determine the optimal design was possible. by using the generated framework for optimal shape design based on NRSM. In the future research, we try to apply the optimization problem for Naval Architectural & Ocean Engineering based on the results of this study.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.40-45
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• 2014

This paper suggests the optimal generation dispatch algorithm for ensuring voltage stability margin considering high wind energy injection. Generally, with wind generation being installed into the power system, we would have to consider several factors such as the voltage stability margin because wind turbine generators are mostly induction machines. If the proportion of wind generation increases in the power system increases this would affect the overall stability of the system including the voltage stability. This paper considers a specific system that is composed of two areas: area 1 and area 2. It is assumed that generation cost in area 1 is relatively higher than that in area 2. From an economic point of view generation in area 1 should be decreased, however, in the stability point of view the generation in area 2 should be decreased. Since the power system is a nonlinear system, it is very difficult to find the optimal solution and the genetic algorithm is adopted to solve the objective function that is composed of a cost function and a function concerned with voltage stability constraints. For the simulations, the New England system was selected. The algorithm is implemented and Python 2.5.

• Journal of the Society of Naval Architects of Korea
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• v.55 no.5
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• pp.401-414
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• 2018

Planing hull type ships are often equipped with interceptor or trim tab to improve the excessive trim angle which leads to poor resistance and sea keeping performances. The purpose of this study is to design a controller to control the attitude of the ship by controllable stern interceptor and validate the effectiveness of the attitude control by the towing tank test. Embedded controller, servo motor and controllable stern interceptor system were equipped with planing hull type model ship. Prior to designing the control algorithm, a model test was performed to identify the system dynamic model of the planing hull type ship including the stern interceptor. The matrix components of model were optimized by Genetic Algorithm. Using the identified model, PID controller which is a classical controller and sliding mode controller which is a nonlinear robust controller were designed. Gain tuning of the controllers and running simulation was conducted before the towing tank test. Inserting the designed control algorithm into the embedded controller of the model ship, the effectiveness of the active control of the stern interceptor was validated by towing tank test. In still water test with small disturbance, the sliding mode controller showed better performance of canceling the disturbance and the steady-state control performance than the PID controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.9-14
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• 2004

Rational sense is affected by emotion. If we add the factor of estimated emotion by environment information into robots, we may get more intelligent and human-friendly robots. However, various sensory information and pattern classification are prescribed for robots to learn emotion so that the networks are suitable for the necessity of robots. Neural network has superior ability to extract character of system but neural network has defect of temporal cross talk and local minimum convergence. To solve the defects, many kinds of modular neural networks have been proposed because they divide a complex problem into simple several subproblems. The modular neural network, introduced by Jacobs and Jordan, shows an excellent ability of recomposition and recombination of complex work. On the other hand, the recurrent network acquires state representations and representations of state make the recurrent neural network suitable for diverse applications such as nonlinear prediction and modeling. In this paper, we applied recurrent network for the expert network in the modular neural network structure to learn data pattern based on emotional assessment. To show the performance of the proposed network, simulation of learning the environment and behavior pattern is proceeded with the real time implementation. The given problem is very complex and has too many cases to learn. The result will show the performance and good ability of the proposed network and will be compared with the result of other method, general modular neural network.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.2
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• pp.215-221
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• 2006

This paper is concerned with the control of multiple nonlinearities included in a humanoid robot system. A humanoid robot has some problems such as the structural instability, which leads to consider the control of multiple nonlinearities caused by driver parts as well as gear reducer. Saturation and backlash are typical examples of nonlinearities in the system. The conventional algorithms of backlash control were fuzzy algorithm, disturbance observer and neural network, etc. However, it is not easy to control the system by employing only single algorithm since the system usually includes multiple nonlinearities. In this paper, a switching Pill is considered for a control of saturation and a dual feedback algorithm is proposed for a backlash control. To implement the above algorithms, the system identification is firstly performed for the minimization of the difference between the results of simulation and experiment, and then the switching Pill gains are determined using genetic algorithm with some heuristic approach. The performance of the switching Pill controller for saturation and the dual feedback for backlash control is investigated through the simulation. Finally, it is shown that the implemented control system has good results and can be applied to the real humanoid robot system ISHURO.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.11A
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• pp.1827-1840
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• 2001

In digital data transmission/storage systems, the compensation for channel distortion is conducted normally using a training sequence that is known a priori to both the sender and receiver. The use of the training sequences results in inefficient utilization of channel bandwidth. Sometimes, it is also impossible to send training sequences such as in the burst-mode communication. As such, a great deal of attention has been given to the approach requiring no training sequences, which has been called the blind equalization technique. On the other hand, to utilize the limited bandwidth effectively, the concept of partial response (PR) signaling has widely been adopted in both the high-speed transmission and high-density recording/playback systems such as digital microwave, digital subscriber loops, hard disk drives, digital VCRs and digital versatile recordable disks and so on. This paper is concerned with blind adaptive equalization of partial response channels whose transfer function zeros are located on the unit circle, thereby causing some problems in performance. Specifically we study how the problems of blind channel equalization associated with the PR channels can be improved. In doing so, we first discuss the existing methods and then propose new structures for blind PR channel equalization. Our structures have been extensively tested by computer simulation and found out to be encouraging in performance. The results seem very promising as well in terms of the implementation complexity compared to the previous approach reported in literature.

• Restorative Dentistry and Endodontics
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• v.33 no.4
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• pp.323-331
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• 2008

Flexibility and fracture properties determine the performance of NiTi rotary instruments. The purpose of this study was to evaluate how geometrical differences between three NiTi instruments affect the deformation and stress distributions under bending and torsional conditions using finite element analysis. Three NiTi files (ProFile .06 / #30, F3 of ProTaper and ProTaper Universal) were scanned using a Micro-CT. The obtained structural geometries were meshed with linear, eight-noded hexahedral elements. The mechanical behavior (deformation and von Mises equivalent stress) of the three endodontic instruments were analyzed under four bending and rotational conditions using ABAQUS finite element analysis software. The nonlinear mechanical behavior of the NiTi was taken into account. The U-shaped cross sectional geometry of ProFile showed the highest flexibility of the three file models. The ProTaper, which has a convex triangular cross-section, was the most stiff file model. For the same deflection, the ProTaper required more force to reach the same deflection as the other models, and needed more torque than other models for the same amount of rotation. The highest von Mises stress value was found at the groove area in the cross-section of the ProTaper Universal. Under torsion, all files showed highest stresses at their groove area. The ProFile showed highest von Mises stress value under the same torsional moment while the ProTaper Universal showed the highest value under same rotational angle.

• Earthquakes and Structures
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• v.12 no.4
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• pp.397-407
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• 2017

To estimate the structural seismic demand, some methods are based on an equivalent linear system such as the Capacity Spectrum Method, the N2 method and the Equivalent Linearization method. Another category, widely investigated, is based on displacement correction such as the Displacement Coefficient Method and the Coefficient Method. Its basic concept consists in converting the elastic linear displacement of an equivalent Single Degree of Freedom system (SDOF) into a corresponding inelastic displacement. It relies on adequate modifying or reduction coefficient such as the inelastic deformation ratio which is usually developed for systems with known ductility factors ($C_{\mu}$) and ($C_R$) for known yield-strength reduction factor. The present paper proposes a rational approach which estimates this inelastic deformation ratio for SDOF bilinear systems by rigorous nonlinear analysis. It proposes a new inelastic deformation ratio which unifies and combines both $C_{\mu}$ and $C_R$ effects. It is defined by the ratio between the inelastic and elastic maximum lateral displacement demands. Three options are investigated in order to express the inelastic response spectra in terms of: ductility demand, yield strength reduction factor, and inelastic deformation ratio which depends on the period, the post-to-preyield stiffness ratio, the yield strength and the peak ground acceleration. This new inelastic deformation ratio ($C_{\eta}$) is describes the response spectra and is related to the capacity curve (pushover curve): normalized yield strength coefficient (${\eta}$), post-to-preyield stiffness ratio (${\alpha}$), natural period (T), peak ductility factor (${\mu}$), and the yield strength reduction factor ($R_y$). For illustrative purposes, instantaneous ductility demand and yield strength reduction factor for a SDOF system subject to various recorded motions (El-Centro 1940 (N/S), Boumerdes: Algeria 2003). The method accuracy is investigated and compared to classical formulations, for various hysteretic models and values of the normalized yield strength coefficient (${\eta}$), post-to-preyield stiffness ratio (${\alpha}$), and natural period (T). Though the ductility demand and yield strength reduction factor differ greatly for some given T and ${\eta}$ ranges, they remain take close when ${\eta}>1$, whereas they are equal to 1 for periods $T{\geq}1s$.

• Journal of Appropriate Technology
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• v.6 no.2
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• pp.136-145
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• 2020

Agriculture is the backbone of the economy of most developing countries. In these countries, agriculture or farming is mostly done manually with little integration of machinery, intelligent systems and data monitoring. Irrigation is an essential process that directly influences crop production. The fluctuating amount of rainfall per year has led to the adoption of irrigation systems in most farms. The absence of smart sensors, monitoring methods and control, has led to low harvests and draining water sources. In this research paper, we introduce a 433 MHz Radio Frequency and 2G based Smart Irrigation Meter System and a water prepayment system for rural areas of Tanzania with no reliable internet coverage. Specifically, Ngurudoto area in Arusha region where it will be used as a case study for data collection. The proposed system is hybrid, comprising of both weather data (evapotranspiration) and soil moisture data. The architecture of the system has on-site weather measurement controllers, soil moisture sensors buried on the ground, water flow sensors, a solenoid valve, and a prepayment system. To achieve high precision in linear and nonlinear regression and to improve classification and prediction, this work cascades a Dynamic Regression Algorithm and Naïve Bayes algorithm.