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

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.10
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• pp.511-520
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• 2007

Decay usage scheduling algorithm gives preference to processes that have consumed little CPU in the recent past. It has been widely-used in time-sharing systems such as UNIX, where CPU-intensive processes and interactive processes are mixed. However, there has been no sound understanding about the mixed effects of decay usage parameters on the service performance. This paper empirically analyzes their effects in terms of the resulting service bandwidth and delay Based on such empirical analysis, we derive the clear meaning of each parameter. Such analysis and understanding provides a basis of controlling decay usage parameters for desirable service provision as required by applications.

• JSTS:Journal of Semiconductor Technology and Science
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• v.7 no.2
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• pp.76-81
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• 2007

Threshold voltage ($V_{th}$) modeling of doublegate (DG) MOSFETs was performed, for the first time, by considering barrier lowering in the short channel devices. As the gate length of DG MOSFETs scales down, the overlapped charge-sharing length ($x_h$) in the channel which is related to the barrier lowering becomes very important. A fitting parameter ${\delta}_w$ was introduced semi-empirically with the fin body width and body doping concentration for higher accuracy. The $V_{th}$ model predicted well the $V_{th}$ behavior with fin body thickness, body doping concentration, and gate length. Our compact model makes an accurate $V_{th}$ prediction of DG devices with the gate length up to 20-nm.

• The Transactions of the Korean Institute of Power Electronics
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• v.7 no.5
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• pp.499-508
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• 2002

In this paper, a novel wireless parallel operation algorithm of N+l redundant UPS system with no control interconnections for load-sharing is presented. The proposed control system eliminates the sensing noise and interconnections interference of conventional parallel operation system. To reduce a reactive power deviation in wireless control method, this technique automatically compensates for inverter parameter variation and line impedance imbalances with wireless auto-tuning method. In addition, to increase reliability on transient characteristics of parallel operation, a virtual injected impedance is adopted to eliminate a circulation current among inverter modules. Simulation results are provided in this paper to prove the proposed novel wireless algorithm.

• The Journal of the Acoustical Society of Korea
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• v.21 no.7
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• pp.641-647
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• 2002

In this paper, we propose the reduction method of the number of parameters in the segmental-feature HMM using trend quantization method. The proposed method shares the trend information of the polynomial trajectories by quantization. The trajectory is obtained by the sequence of feature vectors of speech signals and can be divided by trend and location information. The trend indicates the variation of consequent frame features, while the location points to the positional difference of the trajectories. Since the trend occupies the large portion of SFHMM, if the trend is shared, the number of parameters maybe decreases. To exploit the proposed system the experiments are performed on TIMIT corpus. The experimental results show that the performance of the proposed system is roughly similar to that of previous system. Therefore, the proposed system can be considered one of parameter reduction method.

• ETRI Journal
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• v.33 no.4
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• pp.621-628
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• 2011

The redactable signature scheme was introduced by Johnson and others in 2002 as a mechanism to support disclosing verifiable subdocuments of a signed document. In their paper, a redactable signature based on RSA was presented. In 2009, Nojima and others presented a redactable signature scheme based on RSA. Both schemes are very efficient in terms of storage. However, the schemes need mechanisms to share random prime numbers, which causes huge time consuming computation. Moreover, the public key in the scheme of Johnson and others is designed to be used only once. In this paper, we improve the computational efficiency of these schemes by eliminating the use of a random prime sharing mechanism while sustaining the storage efficiency of them. The size of our signature scheme is the same as that of the standard RSA signature scheme plus the size of the security parameter. In our scheme, the public key can be used multiple times, and more efficient key management than the scheme of Johnson and others is possible. We also prove that the security of our scheme is reduced to the security of the full domain RSA signature scheme.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.46
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• pp.33-49
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• 1998

In order to improve the performance of relational databases, one has to reduce the number of disk accesses necessary to transfer data from disk to main memory. The paper proposes to reduce the number of disk I/O accesses by vertically partitioning relation into fragments and allowing attribute replication to fragments if necessary. When zero-one integer programming model is solved by the branch-and-bound method, it requires much computing time to solve a large sized problem. Therefore, heuristic solutions using genetic algorithm(GA) are presented. GA in this paper adapts a few ideas which are different from traditional genetic algorithms, for examples, a rank-based sharing fitness function, elitism and so on. In order to improve performance of GA, a set of optimal parameter levels is determined by the experiment and makes use of it. As relations are vertically partitioned allowing attribute replications and saved in disk, an attribute replicating vertical partition method by GA can attain less access cost than non-attribute-replication one and require less computing time than the branch-and-bound method in large-sized problems. Also, it can acquire a good solution similar to the optimum solution in small-sized problem.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.5
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• pp.879-884
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• 2012

In this paper, we analyze the sharing parameters in order to co-use of different communication systems in adjacent channels. We analyze the performance result according to various density of interfering transmitter and transmitter output in hetero systems. In order to get the relationship with between density of interfering transmitter and transmitter output, we consider the case that WiBro is an interfering transmitter an WLAN is a victim receiver. When the interferer density is 50/$km^2$ and the center frequency of WLAN and WiBro are 185 and 201MHz respectively, required guard band is 4MHz. Analyzed coexistence results may be widely applied into the technique developed to get the coexisting condition for wireless devices using many communication protocols in same frequency.

• Journal of Information Processing Systems
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• v.17 no.2
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• pp.369-384
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• 2021

In a personalized product recommendation system, when the amount of log data is large or sparse, the accuracy of model recommendation will be greatly affected. To solve this problem, a personalized product recommendation method using deep factorization machine (DeepFM) to analyze user behavior is proposed. Firstly, the K-means clustering algorithm is used to cluster the original log data from the perspective of similarity to reduce the data dimension. Then, through the DeepFM parameter sharing strategy, the relationship between low- and high-order feature combinations is learned from log data, and the click rate prediction model is constructed. Finally, based on the predicted click-through rate, products are recommended to users in sequence and fed back. The area under the curve (AUC) and Logloss of the proposed method are 0.8834 and 0.0253, respectively, on the Criteo dataset, and 0.7836 and 0.0348 on the KDD2012 Cup dataset, respectively. Compared with other newer recommendation methods, the proposed method can achieve better recommendation effect.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.1-7
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• 2022

This paper aims to compare the mean object size of M/G/1/PS model with that of M/BP/1 model used in the web service. The mean object size is one of important measure to control and manage web service economically. M/G/1/PS model utilizes the processor sharing in which CPU rotates in round-robin order giving time quantum to multiple tasks. M/BP/1 model uses the Bounded Pareto distribution to describe the web service according to file size. We may infer that the mean waiting latencies of M/G/1/PS and M/BP/1 model are equal to the mean waiting latency of the deterministic model using the round robin scheduling with the time quantum. Based on the inference, we can find the mean object size of M/G/1/PS model and M/BP/1 model, respectively. Numerical experiments show that when the system load is smaller than the medium, the mean object sizes of the M/G/1/PS model and the M/BP/1 model become the same. In particular, when the shaping parameter is 1.5 and the lower and upper bound of the file size is small in the M/BP/1 model, the mean object sizes of M/G/1/PS model and M/BP/1 model are the same. These results confirm that it is beneficial to use a small file size in a web service.