• Structural Engineering and Mechanics
• /
• v.58 no.6
• /
• pp.1127-1143
• /
• 2016

The pounding phenomenon in adjacent structures happens in severing earthquakes that can cause great damages. Connecting neighboring structures with active and semi-active control devices is an effective method to avoid mutual colliding between neighboring buildings. One of the most important issues in control systems is applying online control force. There will be a time delay if the prose of producing control force does not perform on time. This paper proposed a time-delay compensation method in coupled structures control, with semi-active Magnetorheological (MR) damper. This method based on Newmark's integration is adopted to mitigate the time-delay effect. In this study, Lyapunov's direct approach is employed to compute demanded voltage for MR dampers. Using Lyapunov's direct algorithm guarantees the system stability to design a controller based on feedback. Because of the strong nonlinearity of MR dampers, the equation of motion of coupled structures becomes an involved equation, and it is impossible to solve it with the common time step methods. In present paper modified Newmark-Beta integration based on the instantaneous optimal control algorithm, used to solve the involved equation. In this method, the response of a coupled system estimated base on optimal control force. Two MDOF structures with different degrees of freedom are finally considered as a numeric example. The numerical results show, the Newmark compensation is an efficient method to decrease the negative effect of time delay in coupled systems; furthermore, instantaneous optimal control algorithm can estimate the response of structures suitable.

• Journal of Biosystems Engineering
• /
• v.39 no.3
• /
• pp.174-183
• /
• 2014

Purpose: A robust, efficient auto-grading computer vision system for meat carcasses is in high demand by researchers all over the world. In this paper, we discuss our study, in which we developed a system to speed up line processing and provide reliable results for pork grading, comparing the results of our algorithms with visual human subjectivity measurements. Methods: We differentiated fat and lean using an entropic correlation algorithm. We also developed a self-designed robust segmentation algorithm that successfully segmented several porkcut samples; this algorithm can help to eliminate the current issues associated with autothresholding. Results: In this study, we carefully considered the key step of autoextracting lean tissue. We introduced a self-proposed scheme and implemented it in over 200 pork-cut samples. The accuracy and computation time were acceptable, showing excellent potential for use in online commercial systems. Conclusions: This paper summarizes the main results reported in recent application studies, which include modifying and smoothing the lean area of pork-cut sections of commercial fresh pork by human experts for an auto-grading process. The developed algorithms were implemented in a prototype mobile processing unit, which can be implemented at the pork processing site.

• Tribology and Lubricants
• /
• v.11 no.5
• /
• pp.99-107
• /
• 1995

This paper reported research results to develop an algorithm of on-lin evaluation of surface profiles and roughness generated by turning. The developed module consisted of computer simulation of surface profiles using mechanism of cutting mark formation and cutting vibrations, and online measurement of cutting vibrations. The relative cutting vibrations between tool and worpkiece were measured through an inductance pickup at the rate of one sample per rotation of the workpiece. The sampling process was monitored using an encoder to avoid conceling out the phase lag between waves. The digital cutting signals from the Analog-to-Digital converter were transferred to the simulation module of surface profile where the surface profiles were generated. The developed algorithm or surface generation in a hard turning was analyzed through computer simulations to consider the stochastic and dynamic nature of cutting process. Cutting tests were performed using AISI 304 Stainless Steel and carbide inserts in practical range of cutting conditions. Experimental results showed good correlation between the surface profiles and roughness obtained using the developed algorithm and the surface texture measured using a surface profilemeter. The research provided the feasibility to monitor surface characteristics during tribelogical tests considering wear effect on surface texture in machining.

• KIISE Transactions on Computing Practices
• /
• v.21 no.1
• /
• pp.40-45
• /
• 2015

Online social networks(OSN) are very popular nowadays. As OSNs grows, the commercial markets are expanding their social commerce by applying Influence Maximization. However, in reality, there exist more than two players(e.g., commercial companies or service providers) in this same market sector. To address the Influence Maximization problem between adversaries, we first introduced Influence Maximization against the social adversaries' problem. Then, we proposed an algorithm that could efficiently solve the problem efficiently by utilizing social network properties such as Betweenness Centrality, Clustering Coefficient, Local Bridge and Ties and Triadic Closure. Moreover, our algorithm performed orders of magnitudes better than the existing Greedy hill climbing algorithm.

• The KIPS Transactions:PartC
• /
• v.11C no.5
• /
• pp.569-576
• /
• 2004

Conventional researches of standard tool validating public key cryptographic algorithm have been studied for the internet environment, not for the mobile internet. It is important to develop the validation tool for establishment of interoperability and convenience of users in mobile internet. Therefore, this paper presents the validation tool of Elliptic Curie Cryptography algorithm that can test if following X9.62 technology standard specification. The validation tool can be applied all information securities using ECDSA, ECKCDSA, ECDH, etc. Moreover, we can en-hace the precision of validation through several experiments and perform the validation tool in the online environment.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.8
• /
• pp.4093-4107
• /
• 2019

Proof of Work (PoW) based blockchains have limitations in throughput, time consumption, and energy efficiency. In these systems, a miner will consume significant time and resources to obtain a reward for contributing to the blockchain. To overcome these limitations, recent research on blockchains are focused on accelerating the speed, scalability, and enhancing the security level. By enhancing specific procedures of blockchain system, the level of data integrity supported by the blockchain can become more robust, and efficient. In this paper, a new blockchain consensus model based on the Bryllite Consensus Protocol (BCP) is proposed to support a hyper-connected massively multiplayer online game (MMOG) ecosystem. The BCP scheme enables users to participate directly in new consensus processes through a Proof of Participation (PoP) algorithm. In this model, the consensus algorithm has a simpler form while maintaining high security level. In addition, because the BCP scheme gives users an equal chance to make a contribution to the blockchain, rewards are distributed in an equal fashion, which motivates user participation. The analysis of the proposed scheme is applied to the Bryllite consortium blockchain system (homed in Hong Kong), which is a new blockchain network developed for international game industries, gamers, and game events.

• Journal of Korea Multimedia Society
• /
• v.24 no.2
• /
• pp.285-294
• /
• 2021

This study developed a responsive healthcare system that users can easily use in real life to prevent turtle neck syndrome by posture correction. We propose a system that naturally induces direct posture improvement by adjusting the height with a responsive cradle through a turtle neck discrimination algorithm detecting the turtle neck posture in real time using a webcam. The turtle neck algorithm was developed based on machine learning, using the points that the distance relationship between the jaw line and the shoulder varies depending on the posture. For the younger age group, which is particularly problematic due to the increase in the use of IT devices, image data in different situations according to the height and posture of the cradle was collected and learned as a support vector machine classifier. In addition, a height-adjustable cradle that can support a laptop has been created and expanded into a responsive cradle that can be controlled with software by interlocking with the Arduino. Therefore, this service enables posture correction of many modern people suffering from turtle neck syndrome and will become an essential platform in the increasing online environment in the non-contact era.

• Journal of Creative Information Culture
• /
• v.4 no.3
• /
• pp.221-230
• /
• 2018

Collaborative filtering technique is a major method of recommender systems and has been successfully implemented and serviced in real commercial online systems. However, this technique has several inherent drawbacks, such as data sparsity, cold-start, and scalability problem. Clustering-based collaborative filtering has been studied in order to handle scalability problem. This study suggests a collaborative filtering system which utilizes genetic algorithms to improve shortcomings of K-means algorithm, one of the widely used clustering techniques. Moreover, different from the previous studies that have targeted for optimized clustering results, the proposed method targets the optimization of performance of the collaborative filtering system using the clustering results, which practically can enhance the system performance.

• Journal of Biosystems Engineering
• /
• v.39 no.2
• /
• pp.142-149
• /
• 2014

Purpose: A multispectral algorithm for detection and differentiation of defective (defects on apple skin) and normal Red Delicious apples was developed from analysis of a series of hyperspectral line-scan images. Methods: A fast line-scan hyperspectral imaging system mounted on a conventional apple sorting machine was used to capture hyperspectral images of apples moving approximately 4 apples per second on a conveyor belt. The detection algorithm included an apple segmentation method and a threshold function, and was developed using three wavebands at 676 nm, 714 nm and 779 nm. The algorithm was executed on line-by-line image analysis, simulating online real-time line-scan imaging inspection during fruit processing. Results: The rapid multispectral algorithm detected over 95% of defective apples and 91% of normal apples investigated. Conclusions: The multispectral defect detection algorithm can potentially be used in commercial apple processing lines.

• Journal of the Korean Data and Information Science Society
• /
• v.24 no.5
• /
• pp.989-998
• /
• 2013

We cannot analyze big data, which attracts recent attentions in industry and academy, by batch processing algorithms developed in data mining because big data, by definition, cannot be uploaded and processed in the memory of a single system. So an imminent issue is to develop various leaning algorithms so that they can be applied to big data. In this paper, we review various algorithms for support vector machines in the literature. Particularly, we introduce online type and parallel processing algorithms that are expected to be useful in big data classifications and compare the strengths, the weaknesses and the performances of those algorithms through simulations for linear classification.