• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.10a
• /
• pp.492-494
• /
• 2021

The decision tree technique is used as a classification technique in machine learning. However, the decision tree has a problem of consuming a lot of speed or resources due to the problem of overfitting. To solve this problem, there are bagging and boosting techniques. Bagging creates multiple samplings and models them using them, and boosting models the sampled data and adjusts weights to reduce overfitting. In addition, recently, techniques Xgboost have been introduced to improve performance. Therefore, in this paper, we collect wifi signal data for indoor positioning, apply it to the existing method and Xgboost, and perform performance evaluation through it.

• Journal of Information Processing Systems
• /
• v.20 no.4
• /
• pp.514-523
• /
• 2024

In the Internet of Medical Things, due to the sensitivity of medical information, data typically need to be retained locally. The training model of heart disease data can predict patients' physical health status effectively, thereby providing reliable disease information. It is crucial to make full use of multiple data sources in the Internet of Medical Things applications to improve model accuracy. As network communication speeds and computational capabilities continue to evolve, parties are storing data locally, and using privacy protection technology to exchange data in the communication process to construct models is receiving increasing attention. This shift toward secure and efficient data collaboration is expected to revolutionize computer modeling in the healthcare field by ensuring accuracy and privacy in the analysis of critical medical information. In this paper, we train and test a multiparty decision tree model for the Internet of Medical Things on a heart disease dataset to address the challenges associated with developing a practical and usable model while ensuring the protection of heart disease data. Experimental results demonstrate that the accuracy of our privacy protection method is as high as 93.24%, representing a difference of only 0.3% compared with a conventional plaintext algorithm.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.39 no.1
• /
• pp.42-48
• /
• 2002

In this paper, a decision method using multiple threshold values for PN code acquisition in Direct Sequence Code Division Multiple Access (DS-CDMA) systems is described. We apply this technique to the conventional double dwell serial search algorithm and analyze it in terms of mean code acquisition time. For the analysis, we present mathematical model of proposed algorithm and also perform the simulation under IMT-2000 channel models. Numerical results show that our proposed scheme outperforms the conventional one by 0.2 - 0.5 sec with respect to the mean code acquisition time because multiple threshold values mitigate the possible decline in search performance caused by the use of a single threshold.

• Journal of Auto-vehicle Safety Association
• /
• v.14 no.2
• /
• pp.26-38
• /
• 2022

This paper proposes multiple RLS and actuator performance index-based adaptive actuator fault-tolerant control and detection algorithms for longitudinal autonomous driving. The proposed algorithm computes the desired acceleration using feedback law for longitudinal autonomous driving. When actuator fault or performance degradation exists, it is designed that the desired acceleration is adjusted with the calculated feedback gains based on multiple RLS and gradient descent method for fault-tolerant control. In order to define the performance index, the error between the desired and actual accelerations is used. The window-based weighted error standard deviation is computed with the design parameters. Fault level decision algorithm that can represent three fault levels such as normal, warning, emergency levels is proposed in this study. Performance evaluation under various driving scenarios with actuator fault was conducted based on co-simulation of Matlab/Simulink and commercial software (CarMaker).

• Journal of KIISE:Software and Applications
• /
• v.28 no.9
• /
• pp.681-687
• /
• 2001

In order to raise a class discrimination power by combining multiple classifiers under the Bayesian decision theory, the upper bound of a Bayes error rate bounded by the conditional entropy of a class variable and decision variables obtained from training data samples should be minimized. Wang and Wong proposed a tree dependence first-order approximation scheme of a high order probability distribution composed of the class and multiple feature pattern variables for minimizing the upper bound of the Bayes error rate. This paper presents an extended high order product approximation scheme dealing with higher order dependency more than the first-order tree dependence, based on the minimization of the upper bound of the Bayes error rate. Multiple recognizers for unconstrained handwritten numerals from CENPARMI were combined by the proposed approximation scheme using the Bayesian formalism, and the high recognition rates were obtained by them.

• Journal of KIISE:Software and Applications
• /
• v.26 no.12
• /
• pp.1468-1481
• /
• 1999

didates.본 논문은 절차 중심 소프트웨어를 객체 지향 소프트웨어로 재/역공학하기 위한 다단계 절차중 첫 절차인 객체 추출 절차에 대하여 기술한다. 사용한 객체 추출 방법은 전처리, 기본 분할 및 결합, 정제 결합, 결정 및 통합의 다섯 단계로 이루어진다 : 1) 전처리 과정에서는 객체 추출을 위한 FTV(Function, Type, Variable) 그래프를 생성/분할 및 클러스터링하고, 2) 기본 분할 및 결합 단계에서는 다중 객체 추출을 위한 그래프를 생성하고 생성된 그래프의 정적 객체를 추출하며, 3) 정제 결합 단계에서는 동적 객체를 추출하며, 4) 결정 단계에서는 영역 모델링과 다중 객체 후보군과의 유사도를 측정하여 영역 전문가가 하나의 최적합 후보를 선택할 수 있는 측정 결과를 제시하며, 5) 통합 단계에서는 전처리 과정에서 분리된 그래프가 여러 개 존재할 경우 각각의 처리된 그래프를 통합한다. 본 논문에서는 클러스터링 순서가 고정된 결정론적 방법을 사용하였으며, 가능한 경우의 수에 따른 다중 객체 후보, 객관적이고 의미가 있는 객체 추출 방법으로의 정제와 결정, 영역 모델링을 통한 의미적 관점에 기초한 방법 등을 사용한다. 이러한 방법을 사용함으로써 전문가는 객체 추출 단계에서 좀더 다양하고 객관적인 선택을 할 수 있다.Abstract This paper presents an object extraction process, which is the first phase of a methodology to transform procedural software to object-oriented software. The process consists of five steps: the preliminary, basic clustering & inclusion, refinement, decision and integration. In the preliminary step, FTV(Function, Type, Variable) graph for object extraction is created, divided and clustered. In the clustering & inclusion step, multiple graphs for static object candidate groups are generated. In the refinement step, each graph is refined to determine dynamic object candidate groups. In the decision step, the best candidate group is determined based on the highest similarity to class group modeled from domain engineering. In the final step, the best group is integrated with the domain model. The paper presents a new clustering method based on static clustering steps, possible object candidate grouping cases based on abstraction concept, a new refinement algorithm, a similarity algorithm for multiple n object and m classes, etc. This process provides reengineering experts an comprehensive and integrated environment to select the best or optimal object candidates.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.23 no.9A
• /
• pp.2131-2140
• /
• 1998

Signal-to-interference ratio (SIR)-based dynamic code allocation method to be rioritized for handoff call is proposed and evaluated in a direct sequence-code division multiple access (DS-CDMA) cellular systm. Proposed method allocates a code to a mobile terminal according to the restidual capacity computed by SIR in the base station. We consider the voice activity detection to increase the system capacity. We evaluate the performance of proposed method with computer simulation. And the handoff decision function that controls handoff of mobile terminal is interodcued. The proposed method provide much improvement in the forced termination probability and handoff call fail probability.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.64 no.5
• /
• pp.661-666
• /
• 2015

This paper proposes a method for solving running cost problem by minimizing switching reactive power compensation devices. An objective function was modeled by calculating the weighting value of cost, and a solution was derived using ILP. This paper suggests optimal coordinative control method between FACTS, Shunt Reactors, Capacitors and OLTC. Therefore, it is valuable for decision maker in determining order and capacity of devices which gaining a voltage stabilization. As a result, the objectives of voltage stabilization and cost minimization were achieved simultaneously. This realizes the economic efficiency of the system. We start by showing how to solve systems of linear equations using the language of pivots and tableaus. The effectiveness of this technique is demonstrated in modified PSS/E MIGUM 45 bus system. The simulation results show the effectiveness of this algorithm by comparing the outcome withseveral established methods.

• Industrial Engineering and Management Systems
• /
• v.11 no.4
• /
• pp.397-405
• /
• 2012

This research proposes a framework of buffer management for multi-project systems in the critical chain project management (CCPM) method, expressed in the form of max-plus linear (MPL) representation. Since time buffers are inserted in the projects for absorbing uncertainties in task durations and protecting the completion times, the proposed method provides a procedure for frequently surveying the rates of consumed buffers and the rate of elapsed times. Their relation expresses the performance of the projects which is plotted on a chart through the completed processes. The chart presents the current performance of the projects and their interaction, which alerts managers to make necessary decisions at the right time for managing each project and the entire multi-project system. The proposed framework can analyze the complex system readily, and it enables managers to make an effective decision on scheduling. The effectiveness of the framework is demonstrated through a numerical example.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.46 no.4
• /
• pp.199-208
• /
• 2023

Taguchi method is one of the most popular approaches for design optimization such that performance characteristics become robust to uncontrollable noise variables. However, most previous Taguchi method applications have addressed a single-characteristic problem. Problems with multiple characteristics are more common in practice. The multi-criteria decision making(MCDM) problem is to select the optimal one among multiple alternatives by integrating a number of criteria that may conflict with each other. Representative MCDM methods include TOPSIS(Technique for Order of Preference by Similarity to Ideal Solution), GRA(Grey Relational Analysis), PCA(Principal Component Analysis), fuzzy logic system, and so on. Therefore, numerous approaches have been conducted to deal with the multi-characteristic design problem by combining original Taguchi method and MCDM methods. In the MCDM problem, multiple criteria generally have different measurement units, which means that there may be a large difference in the physical value of the criteria and ultimately makes it difficult to integrate the measurements for the criteria. Therefore, the normalization technique is usually utilized to convert different units of criteria into one identical unit. There are four normalization techniques commonly used in MCDM problems, including vector normalization, linear scale transformation(max-min, max, or sum). However, the normalization techniques have several shortcomings and do not adequately incorporate the practical matters. For example, if certain alternative has maximum value of data for certain criterion, this alternative is considered as the solution in original process. However, if the maximum value of data does not satisfy the required degree of fulfillment of designer or customer, the alternative may not be considered as the solution. To solve this problem, this paper employs the desirability function that has been proposed in our previous research. The desirability function uses upper limit and lower limit in normalization process. The threshold points for establishing upper or lower limits let us know what degree of fulfillment of designer or customer is. This paper proposes a new design optimization technique for multi-characteristic design problem by integrating the Taguchi method and our desirability functions. Finally, the proposed technique is able to obtain the optimal solution that is robust to multi-characteristic performances.