• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.4
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• pp.21-26
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• 1993

Network systems are of fundamental importance in programmable device in industrial automation, as they essential in order to active group management of integration and coordination. In this papers,MMS implemented on the basis ISO specification for industrial environment. In the MMS-MAP, MMS is situated in the application layer and on the datalink layer. This implemented software was operated with network interface unit which was designed in group objects and service primitives for group management network model system. This function of designed module showed possibility of operation through group state diagram transition in the Mini-MAP environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.1036-1057
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• 2013

Wireless body area network (WBAN) is a promising candidate for future health monitoring system. Nevertheless, the path to mature solutions is still facing a lot of challenges that need to be overcome. Energy efficient scheduling is one of these challenges given the scarcity of available energy of biosensors and the lack of portability. Therefore, researchers from academia, industry and health sectors are working together to realize practical solutions for these challenges. The main difficulty in WBAN is the uncertainty in the state of the monitored system. Intelligent learning approaches such as a Markov Decision Process (MDP) were proposed to tackle this issue. A Markov Decision Process (MDP) is a form of Markov Chain in which the transition matrix depends on the action taken by the decision maker (agent) at each time step. The agent receives a reward, which depends on the action and the state. The goal is to find a function, called a policy, which specifies which action to take in each state, so as to maximize some utility functions (e.g., the mean or expected discounted sum) of the sequence of rewards. A partially Observable Markov Decision Processes (POMDP) is a generalization of Markov decision processes that allows for the incomplete information regarding the state of the system. In this case, the state is not visible to the agent. This has many applications in operations research and artificial intelligence. Due to incomplete knowledge of the system, this uncertainty makes formulating and solving POMDP models mathematically complex and computationally expensive. Limited progress has been made in terms of applying POMPD to real applications. In this paper, we surveyed the existing methods and algorithms for solving POMDP in the general domain and in particular in Wireless body area network (WBAN). In addition, the papers discussed recent real implementation of POMDP on practical problems of WBAN. We believe that this work will provide valuable insights for the newcomers who would like to pursue related research in the domain of WBAN.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.2
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• pp.703-711
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• 2016

IDS (Intrusion Detection System) is used to detect network attacks through network data analysis. The system requires a high accuracy and detection rate, and low false alarm rate. In addition, the system uses a range of techniques, such as expert system, data mining, and state transition analysis to analyze the network data. The purpose of this study was to compare the performance of two data mining methods for detecting network attacks. They are Support Vector Machine (SVM) and a neural network called Forward Additive Neural Network (FANN). The well-known KDD Cup 99 training and test data set were used to compare the performance of the two algorithms. The accuracy, detection rate, and false alarm rate were calculated. The FANN showed a slightly higher false alarm rate than the SVM, but showed a much higher accuracy and detection rate than the SVM. Considering that treating a real attack as a normal message is much riskier than treating a normal message as an attack, it is concluded that the FANN is more effective in intrusion detection than the SVM.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.8B
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• pp.699-706
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• 2003

This paper is to verify that 2-state MMPP Model conform to ATM VBR traffic characteristics by measuring and analyzing real-time VBR traffic in KT's ATM network. As a result, we validated the fact that real-time VBR traffic of ATM network cannot be apply to MMPP model and must be represented by previously general On-Off Model with characteristics as follows: arrival rate of On state (λ$_1$) is deterministic, arrival rate of Off state (λ$_2$) is zero, and two transition rate (T$_1$,T$_2$) is only random variable. As research results are to handle real traffic, these results can be used to all ATM network traffic model with traffic management function such as KT's ATM network.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.308-313
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• 2005

For a real-time quadruped robot running control, there are many important objectives to consider. In this paper, the running control architecture based on global states, which describe the cyclic target motion, and central pattern is proposed. The main goal of the controller is how the robot can have robustness to an unpredictable environment with reducing calculation burden to generate control inputs. Additional goal is construction of a single framework controller to avoid discontinuities during transition between multi-framework controllers and of a training-free controller. The global state dependent neuron network induces adaptation ability to an environment and makes the training-free controller. The central pattern based approach makes the controller have a single framework, and calculation burden is resolved by extracting dynamic equations from the control loop. In our approach, the model of the quadruped robot is designed using anatomical information of a cat, and simulated in 3D dynamic environment. The simulation results show the proposed single framework controller is robustly performed in an unpredictable sloped terrain without training.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.4
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• pp.33-45
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• 2015

Currently, Internet is used an essential tool in the business area. Despite this importance, there is a risk of network attacks attempting collection of fraudulence, private information, and cyber terrorism. Firewalls and IDS(Intrusion Detection System) are tools against those attacks. IDS is used to determine whether a network data is a network attack. IDS analyzes the network data using various techniques including expert system, data mining, and state transition analysis. This paper tries to compare the performance of two data mining models in detecting network attacks. They are decision tree (C4.5), and neural network (FANN model). I trained and tested these models with data and measured the effectiveness in terms of detection accuracy, detection rate, and false alarm rate. This paper tries to find out which model is effective in intrusion detection. In the analysis, I used KDD Cup 99 data which is a benchmark data in intrusion detection research. I used an open source Weka software for C4.5 model, and C++ code available for FANN model.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.6
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• pp.838-844
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• 2012

This paper proposes the effective monitoring method for marine engine system, which is implemented based upon Controller Area Network (CAN). As the marine engine monitoring system requires various kind of information, a lot of sensor nodes are distributed to several places. The CAN supports huge numbers of message IDs for the sensor nodes and provides a stable communication channel in a wide area such as a 12,000 TEU container ship. Since the CAN is priority-based communication system, some of hard real-time messages like alarm messages which are time-critical to the operation of the vessel cannot be communicated within the dead-time. Therefore it is desirable to distinguish the bandwidth of the CAN for static state messages and transition-state messages not to be harmful to the engine operations. Using the features of message arbitration ability of the CAN, it is proposed in this paper that the bandwidth allocation is dynamically adjusted to cope with the increment of input signal to improve the performance of monitoring system. Effectiveness and validity of the proposed scheme have been demonstrated through real experiments.

• The Journal of Korea Robotics Society
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• v.3 no.3
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• pp.226-236
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• 2008

In this paper, control software architecture is designed to enable a heterogeneous multiple humanoid robot demonstration executing tasks cooperating with each other. In the heterogeneous humanoid robot team, one large humanoid robot and two small humanoid robots are included. For the efficient and reliable information sharing between many software components for humanoid control, sensing and planning, CORBA based software framework is applied. The humanoid tasks are given in terms of finite state diagram based human-robot interface, which is interpreted into the XML based languages defining the details of the humanoid mission. A state transition is triggered based on the event which is described in terms of conditions on the sensor measurements such as robot locations and the external vision system. In the demonstration of the heterogeneous humanoid team, the task of multiple humanoid cleaning the table is given to the humanoid robots and successfully executed based on the given state diagram.

• The KIPS Transactions:PartA
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• v.17A no.3
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• pp.127-136
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• 2010

A wireless sensor network(WSN) which roles as a mediator between living environment and computers in ubiquitous computing is very essential research area. Due to the constraint that sensor nodes should work in very resource-restricted circumstances, an operating system that can manage resources effectively is demanded. Also, a sensor network should be able to deal with many events quickly and simultaneously in order to respond to various physical changes in outer environment. The Sensor Network Operating System such as TinyOS, MANTIS and NanoQplus is much designed so that it can satisfy such requirement. But, for programmers who develop application program for sensor networks, they have lack of frameworks which the development is easily possible from restricted development environment. In this paper for this, we implemented a state machine framework apt for responsive systems in NanoQplus which is multi-thread-based sensor network operating system. In addition we propose an event broker module(EBM) for effective event dispatching, a message data structure for message sharing among state machines, and an execution module that handles messages and their queue and performs state transition of the machines. Furthermore, we could do the development more easily an application program with a state-based framework by developing CASE tools.

• ETRI Journal
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• v.18 no.3
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• pp.127-145
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• 1996

A new analytic framework based on a linear algebra approach is proposed for examining the performance of a direct sequence spread spectrum (DS/SS) slotted ALOHA wireless communication network systems with delay capture. The discrete-time Markov chain model has been introduced to account for the effect of randomized time of arrival (TOA) at the central receiver and determine the evolution of the finite population network performance in a single-hop environment. The proposed linear algebra approach applied to the given Markov problem requires only computing the eigenvector ${\prod}$ of the state transition matrix and then normalizing it to have the sum of its entries equal to 1. MATLAB computation results show that systems employing discrete TOA randomization and delay capture significantly improves throughput-delay performance and the employed analysis approach is quite easily and staightforwardly applicable to the current analysis problem.