• Journal of Internet Computing and Services
• /
• v.17 no.5
• /
• pp.51-58
• /
• 2016

The unprecedented power of cloud computing (CC) that enables free sharing of confidential data records for further analysis and mining has prompted various security threats. Thus, supreme cyberspace security and mitigation against adversaries attack during data mining became inevitable. So, privacy preserving data mining is emerged as a precise and efficient solution, where various algorithms are developed to anonymize the data to be mined. Despite the wide use of generalized K-anonymizing approach its protection and truthfulness potency remains limited to tiny output space with unacceptable utility loss. By combining L-diversity and (${\alpha}$,k)-anonymity, we proposed a hybrid K-anonymity data relocation algorithm to surmount such limitation. The data relocation being a tradeoff between trustfulness and utility acted as a control input parameter. The performance of each K-anonymity's iteration is measured for data relocation. Data rows are changed into small groups of indistinguishable tuples to create anonymizations of finer granularity with assured privacy standard. Experimental results demonstrated considerable utility enhancement for relatively small number of group relocations.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.8
• /
• pp.3516-3541
• /
• 2018

Task scheduling is one of the most challenging aspects of cloud computing nowadays, and it plays an important role in improving overall performance in, and services from, the cloud, such as response time, cost, makespan, and throughput. A recent cloud task-scheduling algorithm based on the symbiotic organisms search (SOS) algorithm not only has fewer specific parameters, but also incurs time complexity. SOS is a newly developed metaheuristic optimization technique for solving numerical optimization problems. In this paper, the basic SOS algorithm is reduced, and chaotic local search (CLS) is integrated into the reduced SOS to improve the convergence rate. Simulated annealing (SA) is also added to help the SOS algorithm avoid being trapped in a local minimum. The performance of the proposed SA-CLS-SOS algorithm is evaluated by extensive simulation using the Matlab framework, and is compared with SOS, SA-SOS, and CLS-SOS algorithms. Simulation results show that the improved hybrid SOS performs better than SOS, SA-SOS, and CLS-SOS in terms of convergence speed and makespan.

• Restorative Dentistry and Endodontics
• /
• v.47 no.1
• /
• pp.5.1-5.11
• /
• 2022

Objectives: This study aimed to assess the clinical longevity of a bulk-fill resin composite in Class II restorations for 3-year. Materials and Methods: Patient record files acquired from the 40 patients who were treated due to needed 2 similar sizes Class II composite restorations were used for this retrospective study. In the experimental cavity, the flowable resin composite SDR was inserted in the dentinal part as a 4 mm intermediate layer. A 2 mm coverage layer with a nano-hybrid resin composite (CeramX) was placed on SDR. The control restoration was performed by an incremental technique of 2 mm using the nano-hybrid resin composite. The restorations were blindly assessed by 2 calibrated examiners using modified United States Public Health Service criteria at baseline and 1, 2, and 3 years. The data were analyzed using non-parametric tests (p = 0.05). Results: Eighty Class II restorations were evaluated. After 3-years, 4 restorations (5%) failed, 1 SDR + CeramX, and 3 CeramX restorations. The annual failure rate (AFR) of the restorations was 1.7%. The SDR + CeramX group revealed an AFR of 0.8%, and the CeramX group an AFR of 2.5% (p > 0.05). Regarding anatomical form and marginal adaptation, significant alterations were observed in the CeramX group after 3-years (p < 0.05). The changes in the color match were observed in each group over time (p < 0.05). Conclusions: The use of SDR demonstrated good clinical durability in deep Class II resin composite restorations.

• Proceedings of the KIEE Conference
• /
• 2005.04a
• /
• pp.152-154
• /
• 2005

This paper is proposed a fuzzy control and neural network based on the vector controlled induction motor drive system. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability Also, this paper is proposed estimation and control of speed of Induction motor using fuzzy and neural network. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. This paper is proposed the experimental results to verify the effectiveness of the new method.

• Journal of the Korean earth science society
• /
• v.38 no.7
• /
• pp.496-510
• /
• 2017

This study presents a new nationwide quantitative precipitation estimation (QPE) based on the hybrid surface rainfall (HSR) technique using the weather radar network of Korea Meteorological Administration (KMA). This new nationwide HSR is characterized by the synthesis of reflectivity at the hybrid surface that is not affected by ground clutter, beam blockage, non-meteorological echoes, and bright band. The nationwide HSR is classified into static (STATIC) and dynamic HSR (DYNAMIC) mosaic depending on employing a quality control process, which is based on the fuzzy logic approach for single-polarization radar and the spatial texture technique for dual-polarization radar. The STATIC and DYNAMIC were evaluated by comparing with official and operational radar rainfall mosaic (MOSAIC) of KMA for 10 rainfall events from May to October 2014. The correlation coefficients within the block region of STATIC, DYNAMIC and MOSAIC are 0.52, 0.78, and 0.69, respectively, and their mean relative errors are 34.08, 30.08, and 40.71%.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.25 no.3B
• /
• pp.472-486
• /
• 2000

This paper analysis the performance of joint receiving structure consisting of the decorrelating multiuser detection and beamfromenr-RAKE receive for DS-CDMA communication systems. In asynchronous transmission as the number of simultaneous users increase. the capacity of CDMA system becomes severly reduced due to the nonideal orthogonality between user-assigned PN sequences and improper power control. Accordingly, the CDMA receiving system becomes vulnerable to the multiple access interferences and the near-far problem under multipath fading channel environment. To withstand these undesired performance degradations, this paper proposes the new type of multiuser detection which has a form of the hybrid structure of concatenating beamformer-RAKE receiver and decorrelating multiuser detection. the beam former-RAKE receiver performs temporal and spatial diversity combining with alleviating fading effect and suppressing undesired interferences, and the multiuser detection plays a role of making the receiver robust to the near-far problem. Regarding the individual merit on the usage of either multiuser detection or beamformer-RAKE receiver, the hybrid one is expected to produce the enhanced performance in multipath fading CDMA channel. However major drawback of using decorrelating multiuser detection for practical deployment is arised from its computational complexity , which is exponentially increased as more number of users and transmitted symbols involve. To diminish the computational complexity, this paper exploits an efficient block Toeplitz inversion technique using matrix Levinson polynomial will be introduced. And this paper provided the mathematical analysis to show the efficiency of the proposed joint structure under the multipath propagation environment. And results of a series of exhaustive computer simulations are presented in order to demonstrate the overall performance of the proposed hybrid structure in multipath fading CDMA channel.

• Journal of the Korean Society of School Health
• /
• v.36 no.3
• /
• pp.113-125
• /
• 2023

Purpose: The purpose of this study is to develop a model for predicting mental health risk among adolescents based on health behavior information by employing a hybrid machine learning method. Methods: The study analyzed data of 51,850 domestic middle and high school students from 2022 Youth Health Behavior Survey conducted by the Korea Disease Control and Prevention Agency. Firstly, mental health risk levels (stress perception, suicidal thoughts, suicide attempts, suicide plans, experiences of sadness and despair, loneliness, and generalized anxiety disorder) were classified using the k-mean unsupervised learning technique. Secondly, demographic factors (family economic status, gender, age), academic performance, physical health (body mass index, moderate-intensity exercise, subjective health perception, oral health perception), daily life habits (sleep time, wake-up time, smartphone use time, difficulty recovering from fatigue), eating habits (consumption of high-caffeine drinks, sweet drinks, late-night snacks), violence victimization, and deviance (drinking, smoking experience) data were input to develop a random forest model predicting mental health risk, using logistic and XGBoosting. The model and its prediction performance were compared. Results: First, the subjects were classified into two mental health groups using k-mean unsupervised learning, with the high mental health risk group constituting 26.45% of the total sample (13,712 adolescents). This mental health risk group included most of the adolescents who had made suicide plans (95.1%) or attempted suicide (96.7%). Second, the predictive performance of the random forest model for classifying mental health risk groups significantly outperformed that of the reference model (AUC=.94). Predictors of high importance were 'difficulty recovering from daytime fatigue' and 'subjective health perception'. Conclusion: Based on an understanding of adolescent health behavior information, it is possible to predict the mental health risk levels of adolescents and make interventions in advance.

• Earthquakes and Structures
• /
• v.4 no.1
• /
• pp.63-84
• /
• 2013

A semi-active mass damping (SMD) system with magnetorheological (MR) dampers focusing on low- and mid-rise buildings is proposed in this paper. The main purpose of this study is to integrate the reliable characteristics of the traditional tuned mass damper (TMD) and the superior performance of the active mass damper (AMD) to the new system. In addition, the commonly seen solution of deploying dense seismic dampers throughout the structure nowadays to protect the main structure is also expected to switch to the developed SMD system on the roof with a similar reduction performance. In order to demonstrate this concept, a full-size three-story steel building representing a typical mid-rise building was used as the benchmark structure to verify its performance in real life. A numerical model with the interpolation technique integrated was first established to accurately predict the behavior of the MR dampers. The success of the method was proven through a performance test of the designated MR damper used in this research. With the support of the MR damper model, a specific control algorithm using a continuous-optimal control concept was then developed to protect the main structure while the response of the semi-active mass damper is discarded. The theoretical analysis and the experimental verification from a shaking table test both demonstrated the superior mitigation ability of the method. The proposed SMD system has been demonstrated to be readily implemented in practice.

• Proceedings of the Korean Vacuum Society Conference
• /
• 2013.02a
• /
• pp.627-627
• /
• 2013

Recently, most studies concerning inorganic CdSe/ZnS quantum dot (QD)-polymer hybrid LEDs have been concentrated on the structure with multiple layers [1,2]. The QD LEDs used almost CdSe materials for color reproduction such as blue, green and red from the light source until current. However, since Cd is one of six substances banned by the Restriction on Hazardous Substances (RoHS) directive and classified into a hazardous substance for utilization and commercialization as well as for use in life, it was reported that the use of CdSe is not suitable to fabricate a photoelectronic device. In this work, we demonstrate a novel, simple and facile technique for the synthesis of ZnO-graphene quasi-core.shell quantum dots utilizing graphene nanodot in order to overcome Cd material including RoHS materials. Also, We investigate the optical and structural properties of the quantum dots using a number of techniques. In result, At the applied bias 10 V, the device produced bluish-white color of the maximum brightness 1118 cd/$m^2$ with CIE coordinates (0.31, 0.26) at the bias 10 V.

• Proceedings of the KIEE Conference
• /
• 2005.10c
• /
• pp.195-197
• /
• 2005

This paper is proposed adaptive fuzzy neural network(AFNN) and artificial neural network(ANN) based on the vector controlled induction motor drive system. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed control and estimation of speed of induction motor using fuzzy and neural network. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed. so that the actual state variable will coincide with the desired one. This paper is proposed the experimental results to verify the effectiveness of the new method.