• Composites Research
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• v.12 no.4
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• pp.42-54
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• 1999

FMLC(Fiber-Metal Laminate Composites) is a new structural material combining thin metal laminate with adhesive fiber prepreg, it nearly include all the advantage of metallic materials, for example: good plasticity, impact resistance, processibility, light weight and excellent fatigue properties. This research studied the optimum design of the FMLC subject to various loading conditions using genetic algorithm. The finite element method based on the shear deformation theory was used for the analysis of FMLC. Tasi-Hill failure criterion and Miser yield criterion were taken as fitness functions of the fiber prepreg and the metal laminate, respectively. The design variables were fiber orientation angles. In genetic algorithm, the tournament selection and the uniform crossover method were used. The elitist model was also used to be effective evolution strategy and the creeping random search method was adopted in order to approach a solution with high accuracy. Optimization results were given for various loading conditions and compared with CFRP(Carbon Fiber Reinforced Plastic). The results show that the FMLC is more excellent than the CFRP in point and uniform loading conditions and it is more stable to unexpected loading because the deviation of failure index is smaller than that of CFRP.

• International Journal of Industrial Entomology and Biomaterials
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• v.10 no.2
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• pp.147-151
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• 2005

Serious attempt for the improvement of quality parameters in silkworm hybrids came rather very late in India. Realising the need for productive breeds to the field and reorientation in breeding methodology, the silkworm breeders of CSRTI, Mysore were able to develop silkworm breeds with fine denier namely, JPN7, CSR48, B63 and B65 of specific industrial requirement through directional selection. As the success of silkworm breeds mainly depends on their combining ability, the developed breeds were subjected for hybrid evaluation. Out of 42 bivoltine hybrids studied, one hybrid, $CSR48{\times}CSR5$ was identified for its superiority over the existing bivoltine hybrids namely $CSR2{\times}CSR4,\;CSR2{\times}CSR5\;and\;CSR18{\times}CSR19$ for majority of qualitative traits. Post cocoon testing of large quantity of cocoons of $CSR48{\times}CSR5$ resulted in the production of high quality '3A'grade silk. It is for the first time in the Indian Sericulture industry that high quality silk with longer filament length of 1474 m, denier of 2.47, standard size deviation of 0.983 d, maximum size deviation of 1.322, neatness of 96 p, reelability of $85\%$, tenacity of 3.87 g/d, elongation of $22.32\%$ and cohesion of 110 strokes was produced. The superiority of fine denier silkworm breeds and their hybrids are discussed.

• Journal of Biomedical Engineering Research
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• v.29 no.2
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• pp.99-106
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• 2008

To improve $B_1$ homogeneity in high field MRI, the RF power is applied to the transmit array coil elements sequentially in the time-multiplexed way. Since only a single coil element is activated in a time-multiplexing slot, the global standing wave formation in the human body is greatly suppressed. The time-multiplexing slot width is on the order of micro seconds, hence, high-order-harmonic slices can be placed far from the transmit coil and simultaneous multiple slice selection can be avoided. The $B_1$ homogeneities of a birdcage coil and an eight-channel transmit array coil have been compared through finite difference time domain simulations. The simulation results indicate that the proposed technique can reduce the peak-to-peak $B_1$ inhomogeneity down to one fourth of the transmission with a birdcage coil on the central plane of the human head model at 3 T. The mimicking experiments at 3 T, eight separate experiments with a single coil element activated and image reconstruction by combining the eight images, also show promising results. It is expected that the proposed technique has some advantages over other $B_1$ improving methods in real practice since simple RF switching circuitries are only necessary and electromagnetic coupling between the coil elements is out of concern in its realization.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.1055-1060
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• 2009

In this paper, we design an e-Learning system for the Driver's License Teste studying through the Internet. The proposed system make users to be arrived at the goal for the license in a shorter time by offering learning contents and items according to the item-responses made by the users based on the Item Response Theory. Moreover we design the scheme to give the optimum items and the most necessary content to the user during the learning procedure in the form of concept-based objects. All the items in the problem bank DB maintain their difficulties, discriminations, and guessing parameters as is the case of 3-parameter logistic model. In addition user profile DB stores users' status informations, item responses, and ability parameters. Using these structures and combining agents, we can offer the optimum learning process or dynamic personalized studying structure to the user. We can construct interface agent and content selection and feedback agent with the DB's described above. User can study without any awareness of system operations or personal fitting scheme.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2018.10a
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• pp.116-116
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• 2018

Bioconversion, the enzymatic process by microorganism on organic precursor to desired products. The natural extract is converted into a form that can be easily absorbed into the skin, while scaling up of to higher quantity is possible. Selection of naturally processed raw material rather than chemically processed is preferred. Therefore, fermentation was carried out by mixing Rubus coreanus Miquel, soybean, Zanthoxylum schinifolium as bioconverting materials, the possibility of inflammation, whitening material were checked. In this study, useful microorganisms were isolated from various salted fish, and 16S rDNA sequence was analyzed to confirm their genetic characteristics. Combining the three natural materials using bioconversion technology to study their activity before and after fermentation. To evaluate the antioxidant activity and the active ingredient content the DPPH radical scavenging activity and the total polyphenol content were examined. Raw 264.7 cells were used to evaluate MTT assay, NO and $TNF-{\alpha}$ production inhibitory activity. Also, to evaluate the whitening activity, tyrosinase inhibitory activity and melanin formation inhibitory activity were measured using B16F10 cells. In total 34 strains were obtained from various salted fish. The effective strains useful for the bioconversion process, showed that DPPH radical scavenging ability and polyphenol content were increased in the two kinds of microbial treatment groups compared to the untreated group. 16S rDNA sequencing analysis of the strains showed excellent in Pediococcus pentosaceus B1 in comparison. An increase of up-to 156% in anti-oxidative activity and 141% in polyphenol content was observed after bioconversion. In addition, after mixed fermentation the toxidty of Raw 264.7 and B16F10 cells tended to decrease and a significant increase was observed in anti-inflammatory activity as well. Also, tyrosinase activity and melanin significantly. synthesis decreased significantly.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.7
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• pp.52-58
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• 2013

This paper proposes an adaptive algorithm based on a method of dynamic error signal generation suitable for signal state by examining the equalizer output signal in blind equalization. In the proposed method, it estimates the error signals using single modulus and multiple modulus each effective to the early stage of equalization or steady-state, and it generates a new error signal from the two error estimates. Two equalizer structures are implemented and their performances are compared: 1-equalizer structure that generates a new error signal by combining the two error estimates weightedly and updates the equalizer using this, and 2-equalizer structure that updates two equalizers respectively depending on the weights of the two error signals. In the proposed method, as the error signals were generated optimally before and after the initial convergence respectively, it was confirmed by computer simulations that the equalizer was updated effectively.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.6
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• pp.69-74
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• 2014

In this paper, an energy harvesting scheme is investigated in the multi-relay cooperation communication. Our proposal is to maximize the diversity gain and overcome the disadvantages of the limited power wireless devices. The best relay is selected based on the maximizing channel gains from source to relays so that the harvested energy at selected relay is best. If an internal power of the best relay is lower than a defined target power, the best relay will harvest the energy from the source, and the help of the source-destination link is changed to the second best relay. By this operation method, the diversity gain is maintained and the performance of the network is improved. Finally, performance of the proposed protocol is analyzed in terms of bit error rate, utilization efficiency, power collection efficiency.

• The KIPS Transactions:PartB
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• v.13B no.1 s.104
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• pp.71-76
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• 2006

To obtain a correctly translated sentence in a machine translation system, we must select target words that not only reflect an appropriate meaning in a source sentence but also make a fluent sentence in a target language. This paper points out that a source language word has various senses and each sense can be mapped into multiple target words, and proposes a new translation disambiguation method based on this 'word-to-sense and sense-to-word' relationship. In my method target words are chosen through disambiguation of a source word sense and selection of a target word. Most of translation disambiguation methods are based on a 'word-to-word' relationship that means they translate a source word directly into a target wort so they require complicate knowledge sources that directly link a source words to target words, which are hard to obtain like bilingual aligned corpora. By combining two sub-problems for each language, knowledge for translation disambiguation can be automatically extracted from knowledge sources for each language that are easy to obtain. In addition, disambiguation results satisfy both fidelity and intelligibility because selected target words have correct meaning and generate naturally composed target sentences.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.4 s.316
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• pp.44-50
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• 2007

In this paper, we proposed the algorithm for the extraction of the corresponding points from images. The proposed algorithm EMSAC is based on RANSAC and EM algorithms. In the RANSAC procedure, the N corresponding points are randomly selected from the observed total corresponding points to estimate the homography matrix, H. This procedure continues on its repetition until the optimum H are estimated within number of repetition maximum. Therefore, it takes much time and does not converge sometimes. To overcome the drawbacks, the EM algorithm was used for the selection of N corresponding points. The EM algorithm extracts the corresponding points with the highest probability density to estimate the optimum H. By the experiments, it is demonstrated that the proposed method has exact and fast performance on extraction of corresponding points by combining RANSAC with EM.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.1
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• pp.87-94
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• 2017

Reliability analysis(RA) and Reliability-based design optimization(RBDO) require statistical modeling of input random variables, which is parametrically or nonparametrically determined based on experimental data. For the parametric method, goodness-of-fit (GOF) test and model selection method are widely used, and a sequential statistical modeling method combining the merits of the two methods has been recently proposed. Kernel density estimation(KDE) is often used as a nonparametric method, and it well describes a distribution function when the number of data is small or a density function has multimodal distribution. Although accurate statistical models are needed to obtain accurate RA and RBDO results, accurate statistical modeling is difficult when the number of data is small. In this study, the accuracy of two statistical modeling methods, SSM and KDE, were compared according to the number of data. Through numerical examples, the RA results using the input models modeled by two methods were compared, and appropriate modeling method was proposed according to the number of data.