• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2008.11a
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• pp.19-19
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• 2008

We investigated the programmable memory characteristics of nanoparticle-based memory devices based on the elementary metal nanoparticles (Co and Au) and their binary mixture synthesized by a micellar route to ordered arrays of metal nanoparticles as charge trapping layers. According to the metal nanoparticle species quite different programming/erasing efficiencies were observed, resulting in the tunable memory characteristics at the same programming/erasing bias conditions. This finding will be a good implication for further device scaling and novel device applications since most processes are based on the conventional semiconductor processes.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.11b
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• pp.46-51
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• 2001

For Fast Real-time Recognition of Nonlinear Error Data, a new Neural Network algorithm which recognized the map in real time is proposed. The proposed neural network technique is the real time computation method through the inter-node diffusion, In the network, a node corresponds to a state in the quantized input space. Each node is composed of a processing unit and fixed weights from its neighbor nodes as well as its input terminal. The most reliable algorithm derived for real time recognition of map, is a dynamic programming based algorithm based on sequence matching techniques that would process the data as it arrives and could therefore provide continuously updated neighbor information estimates. Through several simulation experiments, real time reconstruction of the nonlinear map information is processed,

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2005.11a
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• pp.80-81
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• 2005

Chalcogenide phase change memory has high performance to be next generation memory, because it is a nonvolatile memory processing high programming speed, low programming voltage, high sensing margin, low consumption and long cycle duration. We have developed a sample of PRAM with thermal protected layer. We have investigated the phase transition behaviors in function of process factor including thermal protect layer. As a result, we have observed that set voltage and duration of protect layer are more improved than no protect layer.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.20 no.2
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• pp.113-117
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• 2007

We have investigated the effects of doping concentration in polysilicon floating gate on the endurance characteristics of the EEPROM cell haying the structure of spacer select transistor. Several samples were prepared with different implantation conditions of phosphorus for the floating gate. Results show the dependence of doping concentration in polysilicon floating gate on performance of EEPROM cell from the floating gate engineering point of view. All of the samples were endured up to half million programming/erasing cycle. However, the best $program-{\Delta}V_{T}$ characteristic was obtained in the cell doped at the dose of $1{\times}10^{15}/cm^{2}$.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.22 no.1
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• pp.7-11
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• 2009

In this study, p-channel silicon-oxide-nitride-oxide-silicon(SONOS) transistors are fabricated and characterized as an unit cell for NAND flash memory. The SONOS transistors are fabricated by $0.13{\mu}m$ low power standard logic process technology. The thicknesses of gate insulators are 2.0 nm for the tunnel oxide, 1.4 nm for the nitride layer, and 4.9 nm for the blocking oxide. The fabricated SONOS transistors show low programming voltage and fast erase speed. However, the retention and endurance of the devices show poor characteristics.

• Steel and Composite Structures
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• v.6 no.5
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• pp.435-457
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• 2006

The paper presents the cost optimization of composite floor trusses composed from a reinforced concrete slab of constant depth and steel trusses consisting of hot rolled channel sections. The optimization was performed by the nonlinear programming approach, NLP. Accordingly, a NLP optimization model for composite floor trusses was developed. An accurate objective function of the manufacturing material, power and labour costs was proposed to be defined for the optimization. Alongside the costs, the objective function also considers the fabrication times, and the electrical power and material consumption. Composite trusses were optimized according to Eurocode 4 for the conditions of both the ultimate and the serviceability limit states. A numerical example of the optimization of the composite truss system presented at the end of the paper demonstrates the applicability of the proposed approach.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.11a
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• pp.46-51
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• 2001

For Fast Real-time Recognition of Nonlinear Error Data, a new Neural Network algorithm which recognized the map in real time is proposed. The proposed neural network technique is the real time computation method through the inter-node diffusion. In the network, a node corresponds to a state in the quantized input space. Each node is composed of a processing unit and fixed weights from its neighbor nodes as well as its input terminal. The most reliable algorithm derived for real time recognition of map, is a dynamic programming based algorithm based on sequence matching techniques that would process the data as it arrives and could therefore provide continuously updated neighbor information estimates. Through several simulation experiments, real time reconstruction of the nonlinear map information is processed.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.05c
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• pp.194-199
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• 2003

Depth error correction effect for maladjusted stereo cameras with calibrated pixel distance parameter is presented. The proposed neural network technique is the real time computation method based theory of inter-node diffusion for searching the safety distances from the sudden appearance-objects during the work driving. The main steps of the distance computation using the theory of stereo vision like the eyes of man is following steps. One is the processing for finding the corresponding points of stereo images and the other is the interpolation processing of full image data from nonlinear image data of objects. All of them request much memory space and time. Therefore the most reliable neural-network algorithm is derived for real-time matching of objects, which is composed of a dynamic programming algorithm based on sequence matching techniques.

• Journal of The Korean Association of Information Education
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• v.17 no.4
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• pp.409-419
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• 2013

The aims of this paper were to review the usable possibility of the educational App Inventor Program in the field of programming education and to develop programming teaching materials that can overcome limitations of the established programming instruction. The study showed that the learners' motivations were strengthened through smart device programs. Containing the elements of STEAM, the teaching materials were developed for the logical and systematic learning that deals with elementary students' real-life situations, and that helps children follow the procedures of software development. By introducing the Waterfall Model to the process of programming, students are able to follow the software developers' thinking process. In addition, beyond the simplistic programming language and simply acquiring related knowledge, the App Inventor programming was designed to enhance students' higher-order thinking skills such as creativity, problem solving ability, collaborative thinking, and so forth.

• Journal of Mechanical Science and Technology
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• v.17 no.10
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• pp.1496-1506
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• 2003

The SIMP (solid isotropic material with penalization) approach is perhaps the most popular density variable relaxation method in topology optimization. This method has been very successful in many applications, but the optimization solution convergence can be improved when new variables, not the direct density variables, are used as the design variables. In this work, we newly propose S-shape functions mapping the original density variables nonlinearly to new design variables. The main role of S-shape function is to push intermediate densities to either lower or upper bounds. In particular, this method works well with nonlinear mathematical programming methods. A method of feasible directions is chosen as a nonlinear mathematical programming method in order to show the effects of the S-shape scaling function on the solution convergence.