• Title/Summary/Keyword: P2P networks

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Data Mining and FNN-Driven Knowledge Acquisition and Inference Mechanism for Developing A Self-Evolving Expert Systems

  • Kim, Jin-Sung
    • Proceedings of the KAIS Fall Conference
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    • 2003.11a
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    • pp.99-104
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    • 2003
  • In this research, we proposed the mechanism to develop self evolving expert systems (SEES) based on data mining (DM), fuzzy neural networks (FNN), and relational database (RDB)-driven forward/backward inference engine. Most former researchers tried to develop a text-oriented knowledge base (KB) and inference engine (IE). However, thy have some limitations such as 1) automatic rule extraction, 2) manipulation of ambiguousness in knowledge, 3) expandability of knowledge base, and 4) speed of inference. To overcome these limitations, many of researchers had tried to develop an automatic knowledge extraction and refining mechanisms. As a result, the adaptability of the expert systems was improved. Nonetheless, they didn't suggest a hybrid and generalized solution to develop self-evolving expert systems. To this purpose, in this study, we propose an automatic knowledge acquisition and composite inference mechanism based on DM, FNN, and RDB-driven inference. Our proposed mechanism has five advantages empirically. First, it could extract and reduce the specific domain knowledge from incomplete database by using data mining algorithm. Second, our proposed mechanism could manipulate the ambiguousness in knowledge by using fuzzy membership functions. Third, it could construct the relational knowledge base and expand the knowledge base unlimitedly with RDBMS (relational database management systems). Fourth, our proposed hybrid data mining mechanism can reflect both association rule-based logical inference and complicate fuzzy logic. Fifth, RDB-driven forward and backward inference is faster than the traditional text-oriented inference.

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Zearalenone exposure affects the Wnt/β-catenin signaling pathway and related genes of porcine endometrial epithelial cells in vitro

  • Song, Tingting;Yang, Weiren;Huang, Libo;Yang, Zaibin;Jiang, Shuzhen
    • Animal Bioscience
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    • v.34 no.6
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    • pp.993-1005
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    • 2021
  • Objective: Zearalenone (ZEA) has estrogen-like effects. Our previous study has shown that ZEA (0.5 to 1.5 mg/kg) could induce abnormal uterine proliferation through transforming growth factor signaling pathway. To further study the other regulatory networks of uterine hypertrophy caused by ZEA, the potential mechanism of ZEA on porcine endometrial epithelial cells (PECs) was explored by the Illumina Hiseq 2000 sequencing system. Methods: The PECs were treated with ZEA at 0 (ZEA0), 5 (ZEA5), 20 (ZEA20), and 80 (ZEA80) µmol/L for 24 h. The collected cells were subjected to cell cycle, RNA-seq, real-time quantitative polymerase chain reaction, immunofluorescence, and western blot analysis. Results: The proportion of cells in the S and G2 phases decreased (p<0.05), but the proportion of cells in the G1 phase increased (p<0.05) in the ZEA80 treatment. Data analysis revealed that the expression of Wnt pathway-related genes, estrogen-related genes, and mitogen-activated protein kinase pathway-related genes increased (p<0.05), but the expression of genetic stability genes decreased (p<0.05) with increasing ZEA concentrations. The relative mRNA and protein expression of WNT1, β-catenin, glycogen synthase kinase 3β (GSK-3β) were increased (p<0.05) with ZEA increasing, while the relative mRNA and protein expression of cyclin D1 (CCND1) was decreased (p<0.05). Moreover, our immunofluorescence results indicate that β-catenin accumulated around the nucleus from the cell membrane and cytoplasm with increasing ZEA concentrations. Conclusion: In summary, ZEA can activate the Wnt/β-catenin signaling pathway by up-regulating WNT1 and β-catenin expression, to promote the proliferation and development of PECs. At the same time, the up-regulation of GSK-3β and down-regulation of CCND1, as well as the mRNA expression of other pathway related genes indicated that other potential effects of ZEA on the uterine development need further study.

Design of Particle Swarm Optimization-based Polynomial Neural Networks (입자 군집 최적화 알고리즘 기반 다항식 신경회로망의 설계)

  • Park, Ho-Sung;Kim, Ki-Sang;Oh, Sung-Kwun
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.60 no.2
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    • pp.398-406
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    • 2011
  • In this paper, we introduce a new architecture of PSO-based Polynomial Neural Networks (PNN) and discuss its comprehensive design methodology. The conventional PNN is based on a extended Group Method of Data Handling (GMDH) method, and utilized the polynomial order (viz. linear, quadratic, and modified quadratic) as well as the number of node inputs fixed (selected in advance by designer) at Polynomial Neurons located in each layer through a growth process of the network. Moreover it does not guarantee that the conventional PNN generated through learning results in the optimal network architecture. The PSO-based PNN results in a structurally optimized structure and comes with a higher level of flexibility that the one encountered in the conventional PNN. The PSO-based design procedure being applied at each layer of PNN leads to the selection of preferred PNs with specific local characteristics (such as the number of input variables, input variables, and the order of the polynomial) available within the PNN. In the sequel, two general optimization mechanisms of the PSO-based PNN are explored: the structural optimization is realized via PSO whereas in case of the parametric optimization we proceed with a standard least square method-based learning. To evaluate the performance of the PSO-based PNN, the model is experimented with using Gas furnace process data, and pH neutralization process data. For the characteristic analysis of the given entire data with non-linearity and the construction of efficient model, the given entire system data is partitioned into two type such as Division I(Training dataset and Testing dataset) and Division II(Training dataset, Validation dataset, and Testing dataset). A comparative analysis shows that the proposed PSO-based PNN is model with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

The Effect of Mutual Trust on Relational Performance in Supplier-Buyer Relationships for Business Services Transactions (재상업복무교역중적매매관계중상호신임대관계적효적영향(在商业服务交易中的买卖关系中相互信任对关系绩效的影响))

  • Noh, Jeon-Pyo
    • Journal of Global Scholars of Marketing Science
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    • v.19 no.4
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    • pp.32-43
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    • 2009
  • Trust has been studied extensively in psychology, economics, and sociology, and its importance has been emphasized not only in marketing, but also in business disciplines in general. Unlike past relationships between suppliers and buyers, which take considerable advantage of private networks and may involve unethical business practices, partnerships between suppliers and buyers are at the core of success for industrial marketing amid intense global competition in the 21st century. A high level of mutual cooperation occurs through an exchange relationship based on trust, which brings long-term benefits, competitive enhancements, and transaction cost reductions, among other benefits, for both buyers and suppliers. In spite of the important role of trust, existing studies in buy-supply situations overlook the role of trust and do not systematically analyze the effect of trust on relational performance. Consequently, an in-depth study that determines the relation of trust to the relational performance between buyers and suppliers of business services is absolutely needed. Business services in this study, which include those supporting the manufacturing industry, are drawing attention as the economic growth engine for the next generation. The Korean government has selected business services as a strategic area for the development of manufacturing sectors. Since the demands for opening business services markets are becoming fiercer, the competitiveness of the business service industry must be promoted now more than ever. The purpose of this study is to investigate the effect of the mutual trust between buyers and suppliers on relational performance. Specifically, this study proposed a theoretical model of trust-relational performance in the transactions of business services and empirically tested the hypotheses delineated from the framework. The study suggests strategic implications based on research findings. Empirical data were collected via multiple methods, including via telephone, mail, and in-person interviews. Sample companies were knowledge-based companies supplying and purchasing business services in Korea. The present study collected data on a dyadic basis. Each pair of sample companies includes a buying company and its corresponding supplying company. Mutual trust was traced for each pair of companies. This study proposes a model of trust-relational performance of buying-supplying for business services. The model consists of trust and its antecedents and consequences. The trust of buyers is classified into trust toward the supplying company and trust toward salespersons. Viewing trust both at the individual level and the organizational level is based on the research of Doney and Cannon (1997). Normally, buyers are the subject of trust, but this study supposes that suppliers are the subjects. Hence, it uniquely focused on the bilateral perspective of perceived risk. In other words, suppliers, like buyers, are the subject of trust since transactions are normally bilateral. From this point of view, suppliers' trust in buyers is as important as buyers' trust in suppliers. The suppliers' trust is influenced by the extent to which it trusts the buying companies and the buyers. This classification of trust using an individual level and an organization level is based on the suggestion of Doney and Cannon (1997). Trust affects the process of supplier selection, which works in a bilateral manner. Suppliers are actively involved in the supplier selection process, working very closely with buyers. In addition, the process is affected by the extent to which each party trusts its partners. The selection process consists of certain steps: recognition, information search, supplier selection, and performance evaluation. As a result of the process, both buyers and suppliers evaluate the performance and take corrective actions on the basis of such outcomes as tangible, intangible, and/or side effects. The measurement of trust used for the present study was developed on the basis of the studies of Mayer, Davis and Schoorman (1995) and Mayer and Davis (1999). Based on their recommendations, the three dimensions of trust used for the study include ability, benevolence, and integrity. The original questions were adjusted to the context of the transactions of business services. For example, a question such as "He/she has professional capabilities" has been changed to "The salesperson showed professional capabilities while we talked about our products." The measurement used for this study differs from those used in previous studies (Rotter 1967; Sullivan and Peterson 1982; Dwyer and Oh 1987). The measurements of the antecedents and consequences of trust used for this study were developed on the basis of Doney and Cannon (1997). The original questions were adjusted to the context of transactions in business services. In particular, questions were developed for both buyers and suppliers to address the following factors: reputation (integrity, customer care, good-will), market standing (company size, market share, positioning in the industry), willingness to customize (product, process, delivery), information sharing (proprietary information, private information), willingness to maintain relationships, perceived professionalism, authority empowerment, buyer-seller similarity, and contact frequency. As a consequential variable of trust, relational performance was measured. Relational performance is classified into tangible effects, intangible effects, and side effects. Tangible effects include financial performance; intangible effects include improvements in relations, network developing, and internal employee satisfaction; side effects include those not included either in the tangible or intangible effects. Three hundred fifty pairs of companies were contacted, and one hundred five pairs of companies responded. After deleting five company pairs because of incomplete responses, one hundred five pairs of companies were used for data analysis. The response ratio of the companies used for data analysis is 30% (105/350), which is above the average response ratio in industrial marketing research. As for the characteristics of the respondent companies, the majority of the companies operate service businesses for both buyers (85.4%) and suppliers (81.8%). The majority of buyers (76%) deal with consumer goods, while the majority of suppliers (70%) deal with industrial goods. This may imply that buyers process the incoming material, parts, and components to produce the finished consumer goods. As indicated by their report of the length of acquaintance with their partners, suppliers appear to have longer business relationships than do buyers. Hypothesis 1 tested the effects of buyer-supplier characteristics on trust. The salesperson's professionalism (t=2.070, p<0.05) and authority empowerment (t=2.328, p<0.05) positively affected buyers' trust toward suppliers. On the other hand, authority empowerment (t=2.192, p<0.05) positively affected supplier trust toward buyers. For both buyers and suppliers, the degree of authority empowerment plays a crucial role in the maintenance of their trust in each other. Hypothesis 2 tested the effects of buyerseller relational characteristics on trust. Buyers tend to trust suppliers, as suppliers make every effort to contact buyers (t=2.212, p<0.05). This tendency has also been shown to be much stronger for suppliers (t=2.591, p<0.01). On the other hand suppliers trust buyers because suppliers perceive buyers as being similar to themselves (t=2.702, p<0.01). This finding confirmed the results of Crosby, Evans, and Cowles (1990), which reported that suppliers and buyers build relationships through regular meetings, either for business or personal matters. Hypothesis 3 tested the effects of trust on perceived risk. It has been found that for both suppliers and buyers the lower is the trust, the higher is the perceived risk (t=-6.621, p<0.01 for buyers; t=-2.437, p<0.05). Interestingly, this tendency has been shown to be much stronger for buyers than for suppliers. One possible explanation for this higher level of perceived risk is that buyers normally perceive higher risks than do suppliers in transactions involving business services. For this reason, it is necessary for suppliers to implement risk reduction strategies for buyers. Hypothesis 4 tested the effects of trust on information searching. It has been found that for both suppliers and buyers, contrary to expectation, trust depends on their partner's reputation (t=2.929, p<0.01 for buyers; t=2.711, p<0.05 for suppliers). This finding shows that suppliers with good reputations tend to be trusted. Prior experience did not show any significant relationship with trust for either buyers or suppliers. Hypothesis 5 tested the effects of trust on supplier/buyer selection. Unlike buyers, suppliers tend to trust buyers when they think that previous transactions with buyers were important (t=2.913 p<0.01). However, this study did not show any significant relationship between source loyalty and the trust of buyers in suppliers. Hypothesis 6 tested the effects of trust on relational performances. For buyers and suppliers, financial performance reportedly improved when they trusted their partners (t=2.301, p<0.05 for buyers; t=3.692, p<0.01 for suppliers). It is interesting that this tendency was much stronger for suppliers than it was for buyers. Similarly, competitiveness was reported to improve when buyers and suppliers trusted their partners (t=3.563, p<0.01 for buyers; t=3.042, p<0.01 for suppliers). For suppliers, efficiency and productivity were reportedly improved when they trusted buyers (t=2.673, p<0.01). Other performance indices showed insignificant relationships with trust. The findings of this study have some strategic implications. First and most importantly, trust-based transactions are beneficial for both suppliers and buyers. As verified in the study, financial performance can be improved through efforts to build and maintain mutual trust. Similarly, competitiveness can be increased through the same kinds of effort. Second, trust-based transactions can facilitate the reduction of perceived risks inherent in the purchasing situation. This finding has implications for both suppliers and buyers. It is generally believed that buyers perceive higher risks in a highly involved purchasing situation. To reduce risks, previous studies have recommended that suppliers devise risk-reducing tactics. Moving beyond these recommendations, the present study uniquely focused on the bilateral perspective of perceived risk. In other words, suppliers are also susceptible to perceived risks, especially when they supply services that require very technical and sophisticated manipulations and maintenance. Consequently, buyers and suppliers must solve problems together in close collaboration. Hence, mutual trust plays a crucial role in the problem-solving process. Third, as found in this study, the more authority a salesperson has, the more he or she can be trusted. This finding is very important with regard to tactics. Building trust is a long-term assignment; however, when mutual trust has not been developed, suppliers can overcome the problems they encounter by empowering a salesperson with the authority to make certain decisions. This finding applies to suppliers as well.

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Synthesis of Vegetable Oil-Based Poly(β-amino ester) (식물성 오일 기반 Poly(β-amino ester) 합성)

  • Jang, Na-Ri;Kim, Beom Soo
    • Korean Chemical Engineering Research
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    • v.50 no.6
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    • pp.1064-1067
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    • 2012
  • Recently, there is a growing interest in vegetable oils, cheap and abundant renewable natural resources. Vegetable oils can be used as raw materials for ecofriendly biodegradable polymer materials. In this study, poly(${\beta}$-amino esters) were synthesized by polymerization reaction of acrylated epoxidized soybean oil (AESO) and 2-aminoethanol. Various polymer films were prepared by changing the molar ratio of AESO to 2-aminoethanol. The formation of C-N bonds in poly(${\beta}$-amino ester) was confirmed using FT-IR. Gel contents higher than 98% confirmed the synthesis of crosslinked polymer networks. Tensile strengths and elongation at breaks of polymer films ranged from 0.3 to 1.3 MPa and 32 to 55%, respectively. Polymer films degraded 2 to 7% of the initial weight in 35 days in phosphate buffer solution (pH 7.2) containing lipase enzyme.

Studies on S-band Broadband Amplifier using compensated matching network (정합회로 보상 방법을 이용한 S-밴드용 광대역 증폭기 연구)

  • Kim, Jin-Sung;An, Dan;Rhee, Jin-Koo
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.40 no.6
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    • pp.247-252
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    • 2003
  • In this paper, we have designed and fabricated a broadband 2-stage MMIC amplifier. Broadband characteristics could be obtained by compensated matching networks in a 2-stage amplifier design. This method is compensating low gains at lower frequencies in the 1st-stage with higher gains at lower frequencies in the 2nd- stage and then finally flat gains are obtained in the wide frequency ranges. Also, we have obtained not only broadband characteristics but also high gain using compensation matching network. The fabricated amplifier is measured by attaching on the test PCB(Printed Circuits Board). The measurement results are bandwidth of 1.1~2.8 GHz, S$_{21}$ gain of 11.1$\pm$0.3 ㏈ and P1㏈ of 12.6 ㏈m at 2.4 GHz.

Prediction Acidity Constant of Various Benzoic Acids and Phenols in Water Using Linear and Nonlinear QSPR Models

  • Habibi Yangjeh, Aziz;Danandeh Jenagharad, Mohammad;Nooshyar, Mahdi
    • Bulletin of the Korean Chemical Society
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    • v.26 no.12
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    • pp.2007-2016
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    • 2005
  • An artificial neural network (ANN) is successfully presented for prediction acidity constant (pKa) of various benzoic acids and phenols with diverse chemical structures using a nonlinear quantitative structure-property relationship. A three-layered feed forward ANN with back-propagation of error was generated using six molecular descriptors appearing in the multi-parameter linear regression (MLR) model. The polarizability term $(\pi_1)$, most positive charge of acidic hydrogen atom $(q^+)$, molecular weight (MW), most negative charge of the acidic oxygen atom $(q^-)$, the hydrogen-bond accepting ability $(\epsilon_B)$ and partial charge weighted topological electronic (PCWTE) descriptors are inputs and its output is pKa. It was found that properly selected and trained neural network with 205 compounds could fairly represent dependence of the acidity constant on molecular descriptors. For evaluation of the predictive power of the generated ANN, an optimized network was applied for prediction pKa values of 37 compounds in the prediction set, which were not used in the optimization procedure. Squared correlation coefficient $(R^2)$ and root mean square error (RMSE) of 0.9147 and 0.9388 for prediction set by the MLR model should be compared with the values of 0.9939 and 0.2575 by the ANN model. These improvements are due to the fact that acidity constant of benzoic acids and phenols in water shows nonlinear correlations with the molecular descriptors.

Simple Forecasting of Surface Ozone through a Statistical Approach

  • Ma, Chang-Jin;Kang, Gong-Unn
    • Journal of Environmental Health Sciences
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    • v.44 no.6
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    • pp.539-547
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    • 2018
  • Objectives: Ozone ($O_3$) advisories are issued by provincial/prefectural and city governments in Korea and Japan when oxidant concentrations exceed the criteria of the related country. Advisories issued only after exposure to high $O_3$ concentrations cannot be considered ideal measures. Forecasts of $O_3$ would be more beneficial to citizens' health and daily life than real-time advisories. The present study was undertaken to present a simplified forecasting model that can predict surface $O_3$ concentrations for the afternoon of the day of the forecast. Methods: For the construction of a simple and practical model, a multivariate regression model was applied. The monitored data on gases and climate variables from Japan's air quality networks that were recorded over nearly one year starting from April 2016 were applied as the subject for our model. Results: A well-known inverse correlation between $NO_2$ and $O_3$ was confirmed by the monitored data for Iksan, Korea and Fukuoka, Japan. Typical time fluctuations for $O_3$ and $NO_x$ were also found. Our model suggests that insolation is the most influential factor in determining the concentration of $O_3$. $CH_4$ also plays a major role in our model. It was possible to visually check for the fit of a theoretical distribution to the observed data by examining the probability-probability (P-P) scatter plot. The goodness of fit of the model in this study was also successfully validated through a comparison (r=0.8, p<0.05) of the measured and predicted $O_3$ concentrations. Conclusions: The advantage of our model is that it is capable of immediate forecasting of surface $O_3$ for the afternoon of the day from the routinely measured values of the precursor and meteorological parameters. Although a comparison to other approaches for $O_3$ forecasting was not carried out, the model suggested in this study would be very helpful for the citizens of Korea and Japan, especially during the $O_3$ season from May to June.

A Study on Video Quality Estimation on IPTV under Lab Network Environment (실험망 환경에서의 IPTV 비디오 성능측정에 관한 연구)

  • Cho, Tae-Kyung
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.61 no.2
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    • pp.103-109
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    • 2012
  • This paper analyzed major factors affecting video quality in IPTV (Internet Protocol TV) services in multicasting under our lab network environment similar to practical IPTV service networks. We measured video qualities for the broadcasting traffics in IPTV multicasting with or without applying QoS (Quality of Service) technique. The measurements allowed us to extract thresholds of network measurement factors affecting the quality for the service. It will be a good choice that the factors can be a reference to ensure stable video quality for practical IPTV services in multicasting.

The MPPT of Photovoltaic Solar System by Controlled Boost Converter with Neural Network

  • Cha, In-Su;Lim, Jung-Yeol;Yu, Gwon-Jong
    • Journal of IKEEE
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    • v.2 no.2 s.3
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    • pp.255-262
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    • 1998
  • The neural network can roughly be classified as the specialized control, indirect control and general schemes. Neural network is adopted for MPPT of solar array. And back propagation algorithm also is used to train neural network controller. We investigate the possibilities of $P_{max}$ control using the neural networks, and then we also examine about operating the solar cell at an optimal voltage comprise of temperature compensated voltage with boost converter. Proposed boost converter of MPPT system is studied by simulation and is implemented by using a microprocessor(80c196kc) which controls duty ratio of the boost converter.

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