• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.3B
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• pp.181-188
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• 2012

In this paper, the time slot assignment algorithm, which is based on various transmission interval in TDMA DAMA communication system, has been proposed. The performance of the proposed algorithm and the random assignment algorithm is compared through computer simulations. The simulation results show that the new algorithm can enhance the efficiency of time slot usage much more than the random assignment algorithm. Especially, the lower the congestion of the network is, the higher the efficiency of time slot usage for short transmission interval is.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.832-844
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• 2020

The degree of dispersion of a random variable can be described by the variance, which reflects the distance of the random variable from its mean. However, the time complexity of the traditional variance calculation algorithm is O(n), which results from full calculation of all samples. When the number of samples increases or on the occasion of high speed signal processing, algorithms with O(n) time complexity will cost huge amount of time and that may results in performance degradation of the whole system. A novel multi-step recursive algorithm for variance calculation of the time-varying data series with O(1) time complexity (constant time) is proposed in this paper. Numerical simulation and experiments of the algorithm is presented and the results demonstrate that the proposed multi-step recursive algorithm can effectively decrease computing time and hence significantly improve the variance calculation efficiency for time-varying data, which demonstrates the potential value for time-consumption data analysis or high speed signal processing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4567-4583
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• 2021

This study proposes an analytical approximation algorithm based on extreme value theory (EVT) for the inverse of the power of the incomplete Gamma function. First, the Gumbel function is used to approximate the power of the incomplete Gamma function, and the corresponding inverse problem is transformed into the inversion of an exponential function. Then, using the tail equivalence theorem, the normalized coefficient of the general Weibull distribution function is employed to replace the normalized coefficient of the random variable following a Gamma distribution, and the approximate closed form solution is obtained. The effects of equation parameters on the algorithm performance are evaluated through simulation analysis under various conditions, and the performance of this algorithm is compared to those of the Newton iterative algorithm and other existing approximate analytical algorithms. The proposed algorithm exhibits good approximation performance under appropriate parameter settings. Finally, the performance of this method is evaluated by calculating the thresholds of space-time block coding and space-frequency block coding pattern recognition in multiple-input and multiple-output orthogonal frequency division multiplexing. The analytical approximation method can be applied to other related situations involving the maximum statistics of independent and identically distributed random variables following Gamma distributions.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.190-198
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• 2023

To enhance customer satisfaction for higher profits, an e-commerce sector can establish a continuous relationship and acquire new customers. Utilize machine-learning models to analyse their customer's behavioural evidence to produce their competitive advantage to the e-commerce platform by helping to improve overall satisfaction. These models will forecast customers who will churn and churn causes. Forecasts are used to build unique business strategies and services offers. This work is intended to develop a machine-learning model that can accurately forecast retainable customers of the entire e-commerce customer data. Developing predictive models classifying different imbalanced data effectively is a major challenge in collected data and machine learning algorithms. Build a machine learning model for solving class imbalance and forecast customers. The satisfaction accuracy is used for this research as evaluation metrics. This paper aims to enable to evaluate the use of different machine learning models utilized to forecast satisfaction. For this research paper are selected three analytical methods come from various classifications of learning. Classifier Selection, the efficiency of various classifiers like Random Forest, Logistic Regression, SVM, and Gradient Boosting Algorithm. Models have been used for a dataset of 8000 records of e-commerce websites and apps. Results indicate the best accuracy in determining satisfaction class with both gradient-boosting algorithm classifications. The results showed maximum accuracy compared to other algorithms, including Gradient Boosting Algorithm, Support Vector Machine Algorithm, Random Forest Algorithm, and logistic regression Algorithm. The best model developed for this paper to forecast satisfaction customers and accuracy achieve 88 %.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.5
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• pp.370-376
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• 2020

In this study, we consider a group-based random access method for group connection and delivery by grouping devices when H2H devices and large-scale M2M devices coexist in a cell in NB-IoT environment. H2H devices perform individual random access, but M2M devices are grouped according to a NPRACH transmission period, and a leader of each group performs random access. The preamble is allocated using the variable preamble allocation algorithm of the Disjoint Allocation(DA) method. The proposed preamble allocation algorithm is an algorithm that preferentially allocates preambles that maximizes throughput of H2H to H2H devices and allocates the rest to M2M devices. The access distribution of H2H and M2M devices was set as Poisson distribution and Beta distribution, respectively, and throughput, collision probability and resource utilization were analyzed. As the random access transmission slot is repeated, the proposed preamble allocation algorithm decreases the collision probability from 0.93 to 0.83 and 0.79 when the number M2M device groups are 150. In addition, it was found that the amount of increase decreased to 33.7[%], 44.9[%], and 48.6[%] of resource used.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.65 no.4
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• pp.292-297
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• 2016

The first-order plus dead time(FOPDT) and second-order plus dead time(SOPDT), which describes a linear monotonic process quite well in most chemical and industrial processes and is often sufficient for PID and IMC controller tuning. This paper presents an application of heuristic harmony search(HS) optimization algorithm to the identification of linear continuous time-delay systems from step response. This recently developed HS algorithm is conceptualized using the musical process of searching for a perfect state of harmony. It uses a stochastic random search instead of a gradient search so that derivative information is unnecessary. The effectiveness of the proposed identification method has been demonstrated through a number of simulation examples.

• Geomechanics and Engineering
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• v.15 no.4
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• pp.937-945
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• 2018

A probabilistic study of a reinforced earth wall in a frictional soil using the surface response methodology (RSM) is presented. A deterministic model based on numerical simulations is used (Abdelouhab et al. 2011, 2012b) and the serviceability limit state (SLS) is considered in the analysis. The model computes the maximum horizontal displacement of the wall. The response surface methodology is utilized for the assessment of the Hasofer-Lind reliability index and is optimized by the use of a genetic algorithm. The soil friction angle and the unit weight are considered as random variables while studying the SLS. The assumption of non-normal distribution for the random variables has an important effect on the reliability index for the practical range of values of the wall horizontal displacement.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.9
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• pp.2086-2097
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• 2012

A terminal-based dynamic clustering algorithm is proposed in a multi-cell scenario, where the user could select the cooperative BSs from the predetermined static base stations (BSs) set based on dynamic channel condition. First, the user transmission rate is derived based on linear precoding and per-cell feedback scheme. Then, the dynamic clustering algorithm can be implemented based on two criteria: (a) the transmission rate should meet the user requirement for quality of service (QoS); (b) the rate increment exceeds the predetermined constant threshold. By adopting random vector quantization (RVQ), the optimized number of cooperative BSs and the corresponding channel conditions are presented respectively. Numerical results are given and show that the performance of the proposed method can improve the system resources utilization effectively.

• Journal of Electrical Engineering and information Science
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• v.2 no.5
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• pp.33-39
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• 1997

In this paper we proposed a new traffic load shedding scheme which maximizes the throughput of traffic control by decreasing the load of the hot-spot cell using minimum load cell selection (MLCS) algorithm and deployed control flow of calls to define characteristic for hadoff region. we compared the performance of the random shedding approach with that of the proposed algorithm. The results of simulation show that MLCS algorithm minimizes the cal blocking rate under a high-density traffic compared to the random shedding scheme.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1453-1459
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• 2016

Recently, vector map has developed, used in many domains, and in most cases vector map data contains confidential information which must be kept away from unauthorized users. Moreover, the manufacturing process of a vector map is complex and the maintenance of a digital map requires substantial monetary and human resources. This paper presents the selective encryption scheme based on polyline simplification methods for GIS vector map data protection to store, transmit or distribute to authorized users. Main advantages of our algorithm are random vertices and transformation processes but it still meets requirements of security by random processes, and this algorithm can be implement to many types of vector map formats.