• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.679-685
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• 2011

This paper presents an algorithm identifying devices that generate observed mixed signals that are collected at main power-supply line. The proposed algorithm, which is necessary for low cost electric power monitoring system at appliance-level, that is non-intrusive load monitoring system, divides incoming mixed signal into multiple time intervals, calculating difference-signals between consecutive time interval, and identifies which device is operating at the time interval by analysing the difference-signals. Since the features of one device can remain when the time interval is short enough and the features are independent and additive, well-known classification algorithms can be used to classify the difference-signals with features of N individual devices, otherwise $2^N$ features might be necessary. The proposed algorithm was verified using data mixed in a laboratory with individual devices's data collected from field. When maximum 4 devices operate or stop sequentially and when features satisfy the requirements of proposed algorithm, the proposed algorithm resulted nearly 100% success rate under the constrained test condition. In order to apply the proposed algorithm in real world, the number devices shall increase, the time interval shall be smaller and the pattern of mixture shall be more diverse. However we can expect, if features used follow guidelines of proposed algorithm, future system could have certain level of performance without the guideline.

• Journal of the Korean Wood Science and Technology
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• v.47 no.2
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• pp.229-238
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• 2019

Various wood defects occur during tree growing or wood processing. Thus, to use wood practically, it is necessary to objectively assess their quality based on the usage requirement by accurately classifying their defects. However, manual visual grading and species classification may result in differences due to subjective decisions; therefore, computer-vision-based image analysis is required for the objective evaluation of wood quality and the speeding up of wood production. In this study, the SIFT+k-NN and CNN models were used to implement a model that automatically classifies knots and analyze its accuracy. Toward this end, a total of 1,172 knot images in various shapes from five domestic conifers were used for learning and validation. For the SIFT+k-NN model, SIFT technology was used to extract properties from the knot images and k-NN was used for the classification, resulting in the classification with an accuracy of up to 60.53% when k-index was 17. The CNN model comprised 8 convolution layers and 3 hidden layers, and its maximum accuracy was 88.09% after 1205 epoch, which was higher than that of the SIFT+k-NN model. Moreover, if there is a large difference in the number of images by knot types, the SIFT+k-NN tended to show a learning biased toward the knot type with a higher number of images, whereas the CNN model did not show a drastic bias regardless of the difference in the number of images. Therefore, the CNN model showed better performance in knot classification. It is determined that the wood knot classification by the CNN model will show a sufficient accuracy in its practical applicability.

• Journal of Internet Computing and Services
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• v.19 no.6
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• pp.21-29
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• 2018

In the era of the 4-th industrial revolution, the concept of smart factory is emerging. There are efforts to predict the occurrences of facility errors which have negative effects on the utilization and productivity by using data analysis. Data composed of the situation of a facility error and the type of the error, called the facility error log, is required for the prediction. However, in many manufacturing companies, the types of facility error are not precisely defined and categorized. The worker who operates the facilities writes the type of facility error in the form with unstructured text based on his or her empirical judgement. That makes it impossible to analyze data. Therefore, this paper proposes a framework for constructing a phrase network to support the identification and classification of facility error types by using facility error logs written by operators. Specifically, phrase indicating the types are extracted from text data by using dictionary which classifies terms by their usage. Then, a phrase network is constructed by calculating the similarity between the extracted phrase. The performance of the proposed method was evaluated by using real-world facility error logs. It is expected that the proposed method will contribute to the accurate identification of error types and to the prediction of facility errors.

• Asia pacific journal of information systems
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• v.18 no.1
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• pp.145-162
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• 2008

One of the big concerns in e-society is privacy issue. In special, in developing robust ubiquitous smart space and corresponding services, user profile and preference are collected by the service providers. Privacy issue would be more critical in context-aware services simply because most of the context data themselves are private information: user's current location, current schedule, friends nearby and even her/his health data. To realize the potential of ubiquitous smart space, the systems embedded in the space should corporate personal privacy preferences. When the users invoke a set of services, they are asked to allow the service providers or smart space to make use of personal information which is related to privacy concerns. For this reason, the users unhappily provide the personal information or even deny to get served. On the other side, service provider needs personal information as rich as possible with minimal personal information to discern royal and trustworthy customers and those who are not. It would be desirable to enlarge the allowable personal information complying with the service provider's request, whereas minimizing service provider's requiring personal information which is not allowed to be submitted and user's submitting information which is of no value to the service provider. In special, if any personal information required by the service provider is not allowed, service will not be provided to the user. P3P (Platform for Privacy Preferences) has been regarded as one of the promising alternatives to preserve the personal information in the course of electronic transactions. However, P3P mainly focuses on preserving the buyers' personal information. From time to time, the service provider's business data should be protected from the unintended usage from the buyers. Moreover, even though the user's privacy preference could depend on the context happened to the user, legacy P3P does not handle the contextual change of privacy preferences. Hence, the purpose of this paper is to propose a mutual P3P-based negotiation mechanism. To do so, service provider's privacy concern is considered as well as the users'. User's privacy policy on the service provider's information also should be informed to the service providers before the service begins. Second, privacy policy is contextually designed according to the user's current context because the nomadic user's privacy concern structure may be altered contextually. Hence, the methodology includes mutual privacy policy and personalization. Overall framework of the mechanism and new code of ethics is described in section 2. Pervasive platform for mutual P3P considers user type and context field, which involves current activity, location, social context, objects nearby and physical environments. Our mutual P3P includes the privacy preference not only for the buyers but also the sellers, that is, service providers. Negotiation methodology for mutual P3P is proposed in section 3. Based on the fact that privacy concern occurs when there are needs for information access and at the same time those for information hiding. Our mechanism was implemented based on an actual shopping mall to increase the feasibility of the idea proposed in this paper. A shopping service is assumed as a context-aware service, and data groups for the service are enumerated. The privacy policy for each data group is represented as APPEL format. To examine the performance of the example service, in section 4, simulation approach is adopted in this paper. For the simulation, five data elements are considered: $\cdot$ UserID $\cdot$ User preference $\cdot$ Phone number $\cdot$ Home address $\cdot$ Product information $\cdot$ Service profile. For the negotiation, reputation is selected as a strategic value. Then the following cases are compared: $\cdot$ Legacy P3P is considered $\cdot$ Mutual P3P is considered without strategic value $\cdot$ Mutual P3P is considered with strategic value. The simulation results show that mutual P3P outperforms legacy P3P. Moreover, we could conclude that when mutual P3P is considered with strategic value, performance was better than that of mutual P3P is considered without strategic value in terms of service safety.

• Korean Journal of Agricultural Science
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• v.43 no.5
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• pp.734-741
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• 2016

Lily (Lilium davidii) is a high-yielding flowering plant. Besides roses and chrysanthemums, lily bulbs have long been used as food and in oriental medicine. However, the usage and value of cut lily bulbs has not been recognized. A bulb whose yield has been decreased is called a waste bulb, and a large amount of such bulbs is discarded every year. In this study, the functionality of waste bulbs from cut lilies was investigated to explore their potential use as a value-added product. We divided lily bulbs into two groups, one group with six varieties of new bulbs (Medusa, Siberia, Woori Tower, Yelloween, Le Reve, and Morning Star) used for cultivation and the other group with six varieties of waste bulbs (Medusa, Siberia, Woori Tower, Yelloween, Sorbonne, and Sheila). Physiological activities (${\alpha},{\alpha}$-diphenyl-${\beta}$-picrylhydrazyl: DPPH) and 3-ethlbenzthiazolne-6-sulfonic acid (ABTS) radical scavenging capability and tyrosinase inhibiting activity), the amount of total as well as eight individual phenolic compounds (chlorogenic acid, epicatechin, rutin hydrate, p-coumaric acid, kaempferol 3-O-${\beta}$-rutinoside, phloridzin dihydrate, myricetin, and quercetin), and total flavonoid content were measured in the bulbs by high performance liquid chromatography. We detected high amounts of total phenol and total flavonoid as well as high DPPH and ABTS radical scavenging ability. More tyrosinase inhibiting activity was detected in the new bulbs than in the waste bulbs. However, both the new and waste bulbs showed a higher inhibitory activity than the standard (100 ppm ascorbic acid). Although the content of phenolic compounds differed among varieties, under the conditions of the experiment, the most abundant phenolics were epicatechins, followed by chlorogenic acid, and rutins. Overall, the waste bulbs had a higher content of these compounds than the new bulbs. Based on these results, we concluded that bulbs from cut lilies could be used as functional foods in the future and farmers could expect economic gain from the hitherto neglected waste bulbs.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.12
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• pp.2539-2548
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• 2015

Overcoming inter-cell interference and spectrum scarcity are major issues in heterogeneous cellular networks. Static Frequency reuse schemes have been proposed as an effective way to manage the spectrum and reduce ICI(Inter cell Interference) in cellular networks. In a kind of static frequency reuse scheme, the allocations of transmission power and subcarriers in each cell are fixed prior to system deployment. This limits the potential performance of the static frequency reuse scheme. Also, most of dynamic frequency reuse schemes did not consider small cell and the network environment when the traffic load of each cell is heavy and non-uniform. In this paper, we propose an inter-cell resource allocation algorithm that dynamically optimizes subcarrier allocations for the multi-cell heterogeneous networks. The proposed dynamic frequency reuse scheme first finds the subcarrier usage in each cell-edge by using the exhaustive search and allocates subcarrier for all the cells except small cells. After that it allocates subcarrier for the small cell and then iteratively repeats the process. Proposed dynamic frequency reuse scheme performs better than previous frequency reuse schemes in terms of the throughput by improving the spectral efficiency due to it is able to adapt the network environment immediately when the traffic load of each cell is heavy and non-uniform.

• Korean Journal of Construction Engineering and Management
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• v.10 no.4
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• pp.26-37
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• 2009

Ministry of Land, Transportation and Marine Affairs(MLTM) has implemented Construction CALS project for improving productivity of construction industry and for making construction project management efficient by responding to informatization and knowledge base society in 21st century. CALS has beeb applied successfully to projects form MLTM, however, the outcomes of Construction CALS hasn't been recognized. In addition, there is no way to find how high the level of Construction CALS is when it is compared with other SOC informatization projects. This study found out the informatiziation level of Construction CALS by using the evaluation index proposed in the former study, and by comparing with other sectors. The evaluation on the level was implemented in the three parts such as informatization infrastructure(network, hardware, standardization, data, informatization, informatization security), informatization utilization(information usage, IT performance), and informatization support(informatization goal, organization of informatization, informatization investment, informatization education), and then, this evaluation was compared with "Assessment for level of industry information system", "Assessment for level of small and midium sized industry information system", and "IICI(Informatizaion Index for the Construction Industry)". With the result from the comparison, this study produced superior factors and inferior factors for each sector. These results are expected to be useful for prioritizing budget allocation by finding out the informatization level of Construction CALS.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.236-244
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• 2005

In this study, we introduce a new topology of Fuzzy Polynomial Neural Networks(FPNN) that is based on fuzzy relation and evolutionally optimized Multi-Layer Perceptron, discuss a comprehensive design methodology and carry out a series of numeric experiments. The construction of the evolutionally optimized FPNN(EFPNN) exploits fundamental technologies of Computational Intelligence. The architecture of the resulting EFPNN results from a synergistic usage of the genetic optimization-driven hybrid system generated by combining rule-based Fuzzy Neural Networks(FNN) with polynomial neural networks(PNN). FNN contributes to the formation of the premise part of the overall rule-based structure of the EFPNN. The consequence part of the EFPNN is designed using PNN. As the consequence part of the EFPNN, the development of the genetically optimized PNN(gPNN) dwells on two general optimization mechanism: the structural optimization is realized via GAs whereas in case of the parametric optimization we proceed with a standard least square method-based learning. To evaluate the performance of the EFPNN, the models are experimented with the use of several representative numerical examples. A comparative analysis shows that the proposed EFPNN are models with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• Spatial Information Research
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• v.20 no.1
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• pp.71-80
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• 2012

Carbon Point system is Climate Change Action Program by providing incentives in proportion to voluntary reduction of energy consumption such as electricity, gas and water for houses, commercial facilities. So far, existing researches have been limited to construction of GHG(Green House Gas) Inventory and have little attention to empirical impact analysis on carbon reduction policy regarding the residential section. Therefore, this paper is intended to provide convincing findings of impact analysis on carbon reduction, revolving around the carbon point system. For this, we firstly calculated the carbon emission by using electricity and gas usage data in household targeting to Seongbuk-Gu. Carrying out IPA and spatio-temporal analysis. Then, we are capable of visualizing spatial patterns from 2007 to 2009 as a macro analysis. Following that, we explored the effect on carbon point system through Ex ante-Ex post Analysis by paired t-test. To conclude, we can spatially identify the distribution with a significant difference between carbon emissions according to energy use as a micro analysis by Hot Spot to Analysis on point entities. It is to be hoped that this method will be utilized to establish various policies and to evaluate the effect of reduction of GHG.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.6C
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• pp.251-258
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• 2011

Steel pipe piles have been used as various deep foundation materials for a long time. Recent increase in steel material cost has made engineers reluctant in using it even with its good quality and ease of construction. Therefore when constructing with steel pipe pile, the decision to reuse the excessive pile length that is cut off from the designed pile head elevation after pile driving can be cost saving. This has caused many constructors to reuse the pile leftovers with new piles, but the absence of quantitative structural capacity behaviors of steel pipe pile after pile driving or appropriate countermeasures and standards in reusing steel pipe pile has resulted in wrong applications, pile structural integrity problems, inappropriate limitation of reusable pile length, etc. The structural performance analysis between a new pile and a pile that has undergone working state and ultimate state stress level during pile driving was performed in this research by means of comparing the results between the dynamic pile load test, tensile load test, charpy energy test and fatigue test for high strength steel of $440N/mm^2$ yield strength. Test results show that under working load conditions the yield strength variation is less than 2% and for ultimate load conditions the variation is less than 5% for maximum total blow count of 3000. The results have been statistically analyzed to check the sensitivity of each factors involved. From the test results, reusability of steel pipe pile lies not in the main pipe yield strength deviation but in the reduction of absorb energy, strength changes and quality control at the welded section, shape deformation and local buckling during pile driving.