• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.5
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• pp.182-189
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• 2002

This paper presents a framework of hybrid dynamic control systems for the motion control of wheeled mobile robot systems with nonholonomic constraints. The hybrid control system has the 3-layered hierarchical structure: digital automata for the higher process, mobile robot system for the lower process, and the interface as the interaction process between the continuous dynamics and the discrete dynamics. In the hybrid control architecture of mobile robot, the continuous dynamics of mobile robots are modeled by the switched systems. The abstract model and digital automata for the motion control are developed. In high level, the discrete states are defined by using the sensor-based search windows and the reference motions of a mobile robot in low level are specified in the abstracted motions. The mobile robots can perform both the motion planning and autonomous maneuvering with obstacle avoidance in indoor navigation problem. Simulation and experimental results show that hybrid system approach is an effective method for the autonomous maneuvering in indoor environments

• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.101-106
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• 2023

Chronic illnesses are among the most common serious problems affecting human health. Early diagnosis of chronic diseases can assist to avoid or mitigate their consequences, potentially decreasing mortality rates. Using machine learning algorithms to identify risk factors is an exciting strategy. The issue with existing feature selection approaches is that each method provides a distinct set of properties that affect model correctness, and present methods cannot perform well on huge multidimensional datasets. We would like to introduce a novel model that contains a feature selection approach that selects optimal characteristics from big multidimensional data sets to provide reliable predictions of chronic illnesses without sacrificing data uniqueness.[1] To ensure the success of our proposed model, we employed balanced classes by employing hybrid balanced class sampling methods on the original dataset, as well as methods for data pre-processing and data transformation, to provide credible data for the training model. We ran and assessed our model on datasets with binary and multivalued classifications. We have used multiple datasets (Parkinson, arrythmia, breast cancer, kidney, diabetes). Suitable features are selected by using the Hybrid feature model consists of Lassocv, decision tree, random forest, gradient boosting,Adaboost, stochastic gradient descent and done voting of attributes which are common output from these methods.Accuracy of original dataset before applying framework is recorded and evaluated against reduced data set of attributes accuracy. The results are shown separately to provide comparisons. Based on the result analysis, we can conclude that our proposed model produced the highest accuracy on multi valued class datasets than on binary class attributes.[1]

• Journal of the Korea Society of Computer and Information
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• v.18 no.4
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• pp.141-152
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• 2013

The current web implementation largely falls into process-oriented and object-oriented methods. Both ways implement the programs to be used for simple design of external outfit and auxiliary function of hybrid webs and it might lead to cost problems arising from waste of time and man-power to develop with it. Therefore, managed structural system programming which can be applied under .NET framework is suggested in a bid to solve these problems. The structural system design method under .NET environment by applying CS concept prefers to adopting the optimized design configuration suited to proper interfaces of UI configuration, which offers the environment to maintain the inheritance relationship by taking form of the balanced class allotment by domain, and continue to keep the connectivity between UX and UI which leads to application of interface of UX objects as form of objects through connection with objects in class design process. This development method enables programs to be implemented focused on representation methods of UI and UX, and helps relieve much of the burden on development costs.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.131-137
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• 2014

The advent of various smart devices like smart phones and tablets has triggered the changes in information systems of medical centers. Especially, diversifying devices of clients and the need for N-Screen services increase necessities for sharing effectively information in medical centers. However, developing and managing clients for each OS like iOS and Android cost high and make it hard to provide seamless service through multi devices. Also, in the aspect of security it is necessary to share information between clients and health information systems. In this paper, we develop a smart health information client based real-time health information sharing framework. The developed client is based on hybrid app, that enables to share information in real time between N devices through health information sharing framework and to adopted to developments of various clients.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.3
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• pp.403-416
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• 2024

Malware is being commercialized and sold on the black market, primarily driven by financial incentives. With the increasing demand driven by these sales, the scope of attacks via malware has expanded. In response, there has been a surge in research efforts leveraging artificial intelligence for detection and classification. However, adversaries are integrating various anti-analysis techniques into their malware to thwart analytical efforts. In this study, we introduce the "Malware Analysis with Dynamic Extraction (MADE)" framework, a hybrid binary analysis tool devised to procure datasets from advanced malware incorporating Anti-Analysis techniques. The MADE framework has the proficiency to autonomously execute dynamic analysis on binaries, encompassing those laden with Anti-VM and Anti-Debugging defenses. Experimental results substantiate that the MADE framework can effectively circumvent over 90% of diverse malware implementations using Anti-Analysis techniques and can adeptly extract relevant datasets.

• Journal of the Earthquake Engineering Society of Korea
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• v.22 no.4
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• pp.253-259
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• 2018

Structure behaviors resulting from an earthquake are experimentally simulated mainly through a shaking table test. As for large-scale structures, however, size effects over a miniature may make it difficult to assess actual behaviors properly. To address this problem, research on the hybrid simulation is being conducted actively. This method is to implement numerical analysis on framework members that affect the general behavior of the structure dominantly through an actual scale experiment and on the rest parts by applying the substructuring technique. However, existing studies on hybrid simulation focus mainly on Slow experimental methods, which are disadvantageous in that it is unable to assess behaviors close to the actual level if material properties change depending on the speed or the influence of inertial force is significant. The present study aims to establish a Real-time hybrid simulation system capable of excitation based on the actual time history and to verify its performance and applicability. The hybrid simulation system built up in this study utilizes the ATS Compensator system, CR integrator, etc. in order to make the target displacement the same with the measured displacement on the basis of MATLAB/Simulink. The target structure was a 2-span bridge and an RC pier to support it was produced as an experimental model in order for the shaking table test and Slow and Real-time hybrid simulations. Behaviors that result from the earthquake of El Centro were examined, and the results were analyzed comparatively. In comparison with the results of the shaking table test, the Real-time hybrid simulation produced more similar maximum displacement and vibration behaviors than the Slow hybrid simulation. Hence, it is thought that the Real-time hybrid simulation proposed in this study can be utilized usefully in seismic capacity assessment of structural systems such as RC pier that are highly non-linear and time-dependent.

• Structural Engineering and Mechanics
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• v.34 no.4
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• pp.525-539
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• 2010

Polymer matrix composites are widely used in many engineering applications as they can be customized to meet a desired performance while not only maintaining low cost but also reducing weight. Polymers can experience viscoelastic-viscoplastic response when subjected to external loadings. Various reinforcements and fillers are added to polymers which bring out more complexity in analyzing the timedependent response. This study formulates an integrated micromechanical model and finite element (FE) analysis for predicting effective viscoelastic-viscoplastic response of polymer based hybrid composites. The studied hybrid system consists of unidirectional short-fiber reinforcements and a matrix system which is composed of solid spherical particle fillers dispersed in a homogeneous polymer constituent. The goal is to predict effective performance of hybrid systems having different compositions and properties of the fiber, particle, and matrix constituents. A combined Schapery's viscoelastic integral model and Valanis's endochronic viscoplastic model is used for the polymer constituent. The particle and fiber constituents are assumed linear elastic. A previously developed micromechanical model of particle reinforced composite is first used to obtain effective mechanical properties of the matrix systems. The effective properties of the matrix are then integrated to a unit-cell model of short-fiber reinforced composites, which is generated using the FE. The effective properties of the matrix are implemented using a user material subroutine in the FE framework. Limited experimental data and analytical solutions available in the literatures are used for comparisons.

• Current Optics and Photonics
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• v.1 no.4
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• pp.325-335
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• 2017

Hybrid radio frequency/free space optical (RF/FSO) wireless mesh networks have attracted increasing attention for they can overcome the limitations of RF and FSO communications and significantly increase the throughput of wireless mesh networks (WMNs). In this article, a resource assignment optimization scheme is proposed for hybrid RF/FSO wireless mesh networks. The optimization framework is proposed for the objective of maximizing throughput of overall hybrid networks through joint transmission slot assignment, FSO links allocation and power control with the consideration of the fading nature of RF and FSO links. The scheme is formulated as an instance of mixed integer linear program (MILP) and the optimal solutions are provided using CPLEX and Gurobi optimizers. How to choose the appropriate optimizer is discussed by comparing their performance. Numerous simulations are done to demonstrate that the performance of our optimization scheme is much better than the current case of having the same topology.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.11-25
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• 2024

The proliferation of IoT devices has presented an unprecedented challenge in managing device identities securely and efficiently. In this paper, we introduce an innovative Hybrid Blockchain-Based Approach for IoT Identity Management that prioritizes both security and efficiency. Our hybrid solution, strategically combines the advantages of direct and indirect connections, yielding exceptional performance. This approach delivers reduced latency, optimized network utilization, and energy efficiency by leveraging local cluster interactions for routine tasks while resorting to indirect blockchain connections for critical processes. This paper presents a comprehensive solution to the complex challenges associated with IoT identity management. Our Hybrid Blockchain-Based Approach sets a new benchmark for secure and efficient identity management within IoT ecosystems, arising from the synergy between direct and indirect connections. This serves as a foundational framework for future endeavors, including optimization strategies, scalability enhancements, and the integration of advanced encryption methodologies. In conclusion, this paper underscores the importance of tailored strategies in shaping the future of IoT identity management through innovative blockchain integration.

• Advances in aircraft and spacecraft science
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• v.7 no.5
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• pp.387-404
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• 2020

The numerical simulation of shock waves in supersonic flows is challenging because of several instabilities which can affect the solution. Among them, the carbuncle phenomenon can introduce nonphysical perturbations in captured shock waves. In the present work, a hybrid numerical flux is proposed for the evaluation of the convective fluxes that avoids carbuncle and keeps high-accuracy on shocks and boundary layers. In particular, the proposed flux is a combination between an upwind approximate Riemann problem solver and the Local Lax-Friedrichs scheme. A simple strategy to mix the two fluxes is proposed and tested in the framework of a discontinuous Galerkin discretisation. The approach is investigated on the subsonic flow in a channel, on the supersonic flow around a cylinder, on the supersonic flow on a flat plate and on the flow in a overexpanded rocket nozzle.