• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.1
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• pp.52-64
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• 1995

Robot manipulator is a highly nonlinear-time varying system. Therefore, a lot of control theory has been applied to the system. Robot manipulator has two types of control; one is path planning, another is path tracking. In this paper, we select the path tracking, and for this purpose, propose the intelligent control¬ler which is combined with fuzzy logic and neural network. The fuzzy logic provides an inference morphorlogy that enables approximate human reasoning to apply to knowledge-based systems, and also provides a mathematical strength to capture the uncertainties associated with human cognitive processes like thinking and reasoning. Based on this fuzzy logic, the fuzzy logic controller(FLC) provides a means of converhng a linguistic control strategy based on expert knowledge into automahc control strategy. But the construction of rule-base for a nonlinear hme-varying system such as robot, becomes much more com¬plicated because of model uncertainty and parameter variations. To cope with these problems, a auto-tuning method of the fuzzy rule-base is required. In this paper, the GA-based Fuzzy-Neural control system combining Fuzzy-Neural control theory with the genetic algorithm(GA), that is known to be very effective in the optimization problem, will be proposed. The effectiveness of the proposed control system will be demonstrated by computer simulations using a two degree of freedom robot manipulator.

• Korean Chemical Engineering Research
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• v.51 no.3
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• pp.388-393
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• 2013

The study was focused to evaluate the possibility for combination membrane of bacterial cellulose (BC) and graphene with high electrical properties. BC with natural polymer matrix was known to have strong physical strength. For the combination of graphene with BC, the surface of graphene was modified with oxygen plasma by changing strength and time of radio waves in room temperature. Water contact angle of modified graphene grew smaller from $130^{\circ}$ to $12^{\circ}$. XPS analysis showed that oxygen content after treatment increased from 2.99 to 10.98%. Damage degree of graphene was examined from $I_D/I_G$ ratio of Raman analysis. $I_D/I_G$ ratio of non-treated graphene (NTG) was 0.11, and 0.36 to 0.43 in plasma treated graphene (PTG), increasing structural defects of PTG. XRD analysis of PTG membrane with BC was $2{\theta}$ same to BC only, indicating chemically combined membrane. In FT-IR analysis, 1,000 to 1,300 $cm^{-1}$ (C=O) peak indicating oxygen radicals in PTG membrane had formed was larger than NTG membrane. The results suggest that BC as an alternation of plastic material for graphene combination has a possibility in some degree on the part like transparent conductive films.

• Information Systems Review
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• v.17 no.3
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• pp.95-111
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• 2015

The recommendation system automatically provides the predicted items which are expected to be purchased by analyzing the previous customer behaviors. This recommendation system has been applied to many e-commerce businesses, and it is generating positive effects on user convenience as well as the company's revenue. However, there are several limitations of the existing recommendation systems. They do not reflect specific criteria for evaluating products or the factors that affect customer buying decisions. Thus, our research proposes a collaborative recommendation model algorithm that utilizes each customer's online product reviews. This study deploys topic modeling method for customer opinion mining. Also, it adopts a kernel-based machine learning concept by selecting kernels explaining individual similarities in accordance with customers' purchase history and online reviews. Our study further applies a multiple kernel learning algorithm to integrate the kernelsinto a combined model for predicting the product ratings, and it verifies its validity with a data set (including purchased item, product rating, and online review) of BestBuy, an online consumer electronics store. This study theoretically implicates by suggesting a new method for the online recommendation system, i.e., a collaborative recommendation method using topic modeling and kernel-based learning.

• Journal of Convergence for Information Technology
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• v.9 no.4
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• pp.1-7
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• 2019

The medical environment, combined with IT technology, is changing the paradigm for medical services from treatment to prevention. In particular, as ICT convergence digital healthcare technology is applied to hospital medical systems, infrastructure technologies such as big data, Internet of Things, and artificial intelligence are being used in conjunction with the cloud. In particular, as medical services are used with IT devices, the quality of medical services is increasingly improving to make them easier for users to access. Medical institutions seeking to incorporate IoT services into cloud health care environment services are trying to reduce hospital operating costs and improve service quality, but have not yet been fully supported. In this paper, a patient information collection model from hospital IoT system, which has established a cloud environment, is proposed. The proposed model prevents third parties from illegally eavesdropping and interfering with patients' biometric information through IoT devices attached to the patient's body at hospitals in cloud environments that have established hospital IoT systems. The proposed model allows clinicians to analyze patients' disease information so that they can collect and treat diseases associated with their eating habits through IoT devices. The analyzed disease information minimizes hospital work to facilitate the handling of prescriptions and care according to the patient's degree of illness.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.2
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• pp.67-72
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• 2022

Recently, various intelligent application services using artificial intelligence are being actively developed. In particular, research on artificial intelligence-based real-time prediction services is being actively conducted in the manufacturing industry, and the demand for artificial intelligence services that can detect and predict fire and odors is very high. However, most of the existing detection and prediction systems do not predict the occurrence of fires and odors, but rather provide detection services after occurrence. This is because AI-based prediction service technology is not applied in existing systems. In addition, fire prediction, odor detection and odor level prediction services are services with ultra-low delay characteristics. Therefore, in order to provide ultra-low-latency prediction service, edge computing technology is combined with artificial intelligence models, so that faster inference results can be applied to the field faster than the cloud is being developed. Therefore, in this paper, we propose an LSTM algorithm-based learning model that can be used for fire prediction and odor detection/prediction, which are most required in the manufacturing industry. In addition, the proposed learning model is designed to be implemented in edge devices, and it is proposed to receive real-time sensor data from the IoT terminal and apply this data to the inference model to predict fire and odor conditions in real time. The proposed model evaluated the prediction accuracy of the learning model through three performance indicators, and the evaluation result showed an average performance of over 90%.

• Applied Chemistry for Engineering
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• v.20 no.3
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• pp.322-328
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• 2009

Emulsion polymerization of octamethylcyclotetrasiloxane (OMCTS) was conducted under ultrasonic irradiation. Two sources of ultrasound with different intensities and frequencies of 20 KHz and 40 KHz were used for horn and bath type reactor, respectively. A combined process of horn and bath was also investigated. The effectiveness of the reaction systems was investigated by measuring conversion as well as intrinsic viscosity of the products. The influence of reaction temperature and sonication time on the progress of sonochemical polymerization was examined. It was found that conversion of greater than 80% and high viscosity were achieved within a few minutes of sonication in a horn type reactor, however, conversion and viscosity showed maximum values depending upon the sonication time. In a bath type reactor where a relatively weak intensity was maintained, longer duration time of more than one hour of sonication was required to reach a high level of conversion and viscosity. Compared with the horn type system, the conversion and viscosity in the bath type reactor were increased along with the sonication time. When the polymerization was carried out in a combined system of horn and bath, the evolution of conversion and molecular weight was quite different from the other cases. For the given geometry of reaction system, acoustic analysis using a commercial software was carried out and the results were correlated with experimental observation.

• Journal of Digital Contents Society
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• v.14 no.4
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• pp.557-564
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• 2013

An important research challenge about the traditional Internet environment is to enable open networking architecture on which end users are able to innovate the Internet based on the technologies of network programmability, virtualization, and federation. The SDN (Software Defined Network) technology that includes OpenFlow protocol specifications, is suggested as a major driver for the open networking architecture, and is closely coupled with the classical Internet (non-SDN). Therefore, it is very important to keep the integrated SDN and non-SDN network infrastructure reliable from the view point of network operators and engineers. Under this background, this paper proposes an operations and management framework for the combined software defined network environment across not only a single-domain network, but also multi-domain networks. The suggested framework is designed to allow SDN controllers and DvNOC systems to interact with each other to achieve sustainable end-to-end user-oriented SDN and non-SDN integrated network environment. Plus, the proposed scheme is designed to apply enhanced functionalities on DvNOC to support four major network failure scenarios over the combined network infrastructure, mainly derived from SDN controllers, SDN devices, and the connected network paths.

• The korean journal of orthodontics
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• v.40 no.2
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• pp.87-94
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• 2010

Objective: Many studies have carried out research on comparisons between laser etching and conventional etching systems to investigate methods of reinforcing shear bond strength. The purposes of this study were to assess the efficiency of bonding with erbium, chromium doped: yttrium-scandium-gallium-garnet (Er,Cr:YSGG) laser etching combined with the conventional etching technique. Methods: Sixty-four sound premolars, extracted for orthodontic purposes, were randomly divided into 4 groups and treated in the following manner. First group, conventional etching of 37% phosphoric acid for 15 seconds (control); second group, 1.5 W laser etching for 10 seconds followed by conventional etching; third group, conventional etching followed by 1.5 W laser etching; fourth group, 1.5 W laser etching for 15 seconds only. We assessed the shear bond strength, the surface characteristics, and the adhesive remnant index scores between all groups. Results: Experimental groups showed higher shear bond strength than the control group. But no statistically significant differences were found between the second and third groups. Adhesive remnant scores were compared with the Kruskal-Wallis test, and no statistically significant differences were found between all groups. Conclusions: To obtain maximum shear bonding strength, a combined technique of Er,Cr:YSGG and 37% phosphoric acid is useful even though it may be inconvenient.

• Korean Journal of Poultry Science
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• v.36 no.3
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• pp.239-246
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• 2009

Animal welfare is of considerable importance to European consumers and citizens, this being most recently confirmed in EU barometer studies. Researchers and others have long proposed that animal-based measures (measures taken on animals, e.g. their health and behaviour) can provide a valid indicator of animal welfare; since welfare is a characteristic of the individual animal. Therefore, a welfare assessment can be essentially based on animal-based measures, but with use of resource measures to provide the capacity to assess 'risk factors'. The first goal of this project was to develop a welfare monitoring system that enables assessment of welfare status through standardised conversion of welfare measures into accessible and understandable information. The acquired information on one hand provides feedback to animal unit managers about the welfare status of their animals, and on the other, information on the welfare status of animal-related products for consumers and retailers. The second goal of Welfare $Quality^{(R)}$ was to improve animal welfare by minimising the occurrence of harmful behavioural and physiological states, improving human-animal relationships, and providing animals with safe and stimulating environments. The different measurable aspects of welfare to be covered are turned into welfare criteria. The criteria reflect what is meaningful to animals as understood by animal welfare science. Once all the measures have been performed on an animal unit, a bottom-up approach is followed to produce an overall assessment of animal welfare on that particular unit: first the data collected (i.e. values obtained for the different measures on the animal unit) are combined to calculate criterion-scores; then criterion-scores are combined to calculate principle-scores; and finally the animal unit is assigned to a welfare category according to the principle-scores it obtained.

• Asian-Australasian Journal of Animal Sciences
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• v.26 no.10
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• pp.1474-1483
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• 2013

The objective was to evaluate the use of prediction equations based on the chemical composition of feedstuffs to estimate the values of apparent metabolisable energy corrected for nitrogen balance (AMEn) of corn and soybean meal for broilers. For performance and carcass characteristics, 1,200 one-d-old birds (male and female) were allotted to a completely randomised factorial $2{\times}8$ (two genders and eight experimental diets) with three replicates of each sex with 25 birds. In the metabolism trial, 240 eight-d-old birds were distributed in the same design, but with a split plot in time (age of evaluation) with five, four and three birds per plot, respectively, in stages 8 to 21, 22 to 35, and 36 to 42 d of age. The treatments consisted of the use of six equations systems to predict the AMEn content of feedstuffs, tables of food composition and AMEn values obtained by in vivo assay, totalling eight treatments. Means were compared by Scott-Knott test at 5% probability and a confidence interval of 95% was used to check the fit of the energy values of the diets to the requirements of the birds. As a result of this study, the use of prediction equations resulted in better adjustment to the broiler requirements, resulting in better performance and carcass characteristics compared to the use of tables, however, the use of energy values of feedstuffs obtained by in vivo assay is still the most effective. The best equations were: AMEn = 4,021.8-227.55 Ash (for corn) combined with AMEn = -822.33+69.54 CP-45.26 ADF+90.81 EE (for soybean meal); AMEn = 36.21 CP+85.44 EE+37.26 NFE (nitrogen-free extract) (for corn) combined with AMEn = 37.5 CP+46.39 EE+14.9 NFE (for soybean); and AMEn = 4,164.187+51.006 EE-197.663 Ash-35.689 CF-20.593 NDF (for corn and soybean meal).