• International journal of advanced smart convergence
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• 제1권2호
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• pp.30-33
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• 2012

This paper propose a new design of fuzzy neural networks based on hard partition to generate the rules of the networks. For this we use hard c-means (HCM) clustering algorithm. The premise part of the rules of the proposed networks is realized with the aid of the hard partition of input space generated by HCM clustering algorithm. The consequence part of the rule is represented by polynomial functions. And the coefficients of the polynomial functions are learned by BP algorithm. The number of the hard partition of input space equals the number of clusters and the individual partitioned spaces indicate the rules of the networks. Due to these characteristics, we may alleviate the problem of the curse of dimensionality. The proposed networks are evaluated with the use of numerical experimentation.

• International journal of advanced smart convergence
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• 제1권1호
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• pp.52-56
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• 2012

As inexhaustible clean energy, solar energy will be the most ideal green energy in the 21st century. The effective method to convert solar energy into electrical energy is by solar photovoltaic power generation technologies. LED Emitting Diode is a kind of component which can transform electricity into visible light. As the smart current control system for photovoltaic street lights, the proposed system has improved the battery charging and discharging mechanism to extend the lifespan and effectively controls the LED discharge current according to battery charge state and lighting.

• International journal of advanced smart convergence
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• 제2권1호
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• pp.27-29
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• 2013

This paper discusses comparative analysis of the effects of surge protection devices (SPD) upon the power line communication channels. The quality of the data transmission channel is measured based on the data rate for the various channel parameters which include channel length and application method of the lightning protection device. The performance measurements are also carried out for various lengths of the communication channel. Experiment results show that specific combination of SPDs applied in the network causes severe degradation of the channel quality which is associated with the combination of grade levels and channel lengths.

• International journal of advanced smart convergence
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• 제2권1호
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• pp.12-17
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• 2013

This paper introduces the fuzzy scatter partition-based fuzzy inference system to construct the model for nonlinear process to analyze nonlinear characteristics. The fuzzy rules of fuzzy inference systems are generated by partitioning the input space in the scatter form using Fuzzy C-Means (FCM) clustering algorithm. The premise parameters of the rules are determined by membership matrix by means of FCM clustering algorithm. The consequence part of the rules is represented in the form of polynomial functions and the parameters of the consequence part are estimated by least square errors. The proposed model is evaluated with the performance using the data widely used in nonlinear process. Finally, this paper shows that the proposed model has the good result for high-dimension nonlinear process.

• International journal of advanced smart convergence
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• 제8권2호
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• pp.199-203
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• 2019

In this paper, we propose the efficient impulsive noise mitigation scheme for power line communication (PLC) systems in smart grid applications. The proposed scheme estimates the channel impulsive noise information of receiver by applying machine learning. Then, the estimated impulsive noise is updated in data base. In the modulator, the impulsive noise which reduces the PLC performance is effectively mitigated through proposed technique. As an impulsive noise model, Middleton Class A interference model was employed. The performance is evaluated in terms of bit error rate (BER). From the simulation results, it is confirmed that the proposed scheme has better BER performance compared to the conventional model. As a result, the proposed noise mitigation improves the signal quality of PLC systems by effectively removing the channel noise. The results of the paper can be applied to PLC systems for smart grid.

• International journal of advanced smart convergence
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• 제8권2호
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• pp.218-226
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• 2019

The use of Information and Communication Technologies (ICT) is the key to operate a change from the traditional manual reading of water meters and sensors to an automated system where high frequency data is remotely collected and analyzed in real time, one of the main components of a Smart Water Grid. The recent boom of ICT offers a wide range of both wired and wireless technologies to achieve this objective. We review and present in this article the most widely recognized technologies and protocols along with their respective advantages, drawbacks and applicability range which can be Home Area Network (HAN), Building Area Network (BAN) or Local/Neighborhood Area Network (LAN/NAN). We also present our findings and we give recommendations on the application of ICT in Smart Water Grids and future work needed.

• International journal of advanced smart convergence
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• 제10권3호
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• pp.89-96
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• 2021

In various areas of the 4th industry, a big issue is software quality enhancement for stability and reliability of the smart software systems. After revising software promotion law at 2020, we must clearly define requirements and separate design parts and implementation parts of an all public software development contracts. In this study, we need to validate whether the final implementation of software is followed by the original design or not. To do this, we consider the design restoration through software visualization based on reverse engineering. Therefore we propose an UML design extraction and visualization method based on reverse engineering. Based on this, we may validate whether it is implemented according to the original design, and how much visualizes and includes the code the internal complexity for improvement of software quality.

• International journal of advanced smart convergence
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• 제10권3호
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• pp.207-213
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• 2021

Informatization and digital transformation across industries are big trends in the world. However, although a few food groups are investing in informatization on a pilot basis, informatization is still delayed in related industries, such as distribution, logistics, etc. Therefore, consumers often are not able to have easy access to detailed information about products. In this paper, to improve these problems, we propose a fresh food logistics solution that adopts Proof of Nonce (PoN) consensus algorithm with Internet of Thing (IoT) technology. The recently developed PoN algorithm dramatically reduces a time for generating a block and is suitable for a platform that collects and services real-time information. We expect to improve their trust in the platform by preventing forgery/falsification of information recorded in real time through this paper.

• International journal of advanced smart convergence
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• 제10권1호
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• pp.56-61
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• 2021

Neighbor path selection is to pre-select alternate routes in case geographically correlated failures occur simultaneously on the communication network. Conventional heuristic-based algorithms no longer improve solutions because they cannot sufficiently utilize historical failure information. We present a novel solution model for neighbor path selection by using machine learning technique. Our proposed machine learning neighbor path selection (ML-NPS) model is composed of five modules- random graph generation, data set creation, machine learning modeling, neighbor path prediction, and path information acquisition. It is implemented by Python with Keras on Tensorflow and executed on the tiny computer, Raspberry PI 4B. Performance evaluations via numerical simulation show that the neighbor path communication success probability of our model is better than that of the conventional heuristic by 26% on the average.

• International journal of advanced smart convergence
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• 제12권3호
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• pp.13-18
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• 2023

This paper aims to investigate data features for neighbor path selection (NPS) in computer network with regional failures. It is necessary to find an available alternate communication path in advance when regional failures due to earthquakes or forest fires occur simultaneously. We describe previous general heuristics and simulation heuristic to solve the NPS problem in the regional fault network. The data features of general heuristics using proximity and sharing factor and the data features of simulation heuristic using machine learning are explained through examples. Simulation heuristic may be better than general heuristics in terms of communication success. However, additional data features are necessary in order to apply the simulation heuristic to the real environment. We propose novel data features for NPS in computer network with regional failures and Keras modeling for computing the communication success probability of candidate neighbor path.