• Journal of Korea Society of Industrial Information Systems
• /
• v.16 no.2
• /
• pp.85-97
• /
• 2011

Wireless sensor networks have emerged as one of the key enabling technologies for ubiquitous computing since wireless intelligent sensor nodes connected by short range communication media serve as a smart intermediary between physical objects and people in ubiquitous computing environment. We recognize the wireless sensor network as a massively distributed and deeply embedded system. Such systems require concurrent and asynchronous event handling as a distributed system and resource-consciousness as an embedded system. Since the operating environment and architecture of wireless sensor networks, with the seemingly conflicting requirements, poses unique design challenges and constraints to developers, we propose a very new operating system for sensor nodes based on finite state machine. In this paper, we clarify the design goals reflected from the characteristics of sensor networks, and then present the heart of the design and implementation of a compact and efficient state-driven operating system, SenOS. We describe how SenOS can operate in an extremely resource constrained sensor node while providing the required reactivity and dynamic reconfigurability with low update cost. We also compare our experimental results after executing some benchmark programs on SenOS with those on TinyOS.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2015.10a
• /
• pp.107-110
• /
• 2015

In this paper, we propose a coalitonal game theoritic approach to the power control problem in resource-constrained wireless sensor networks, where the objective is to enhance power efficiency of individual sensors while providing the QoS requirements. We model this problem as two-sided one-to-one matching game and deploly deferred acceptance procedure that produces a single matching in the core. Furthermore, we show that, by applying the procedure repeatedly, a certain stable state is achieved where no sensor can anticipate improvements in their power efficiency as far as all of them are subject to their own QoS constraints. We evaluate our proposal by comparing them with cluster-based and the local optimal solution obtained by maximizing the total system energy efficiency, where the objective function is non-convex.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.5 no.3
• /
• pp.1-12
• /
• 1985

The linear tracking theory has a great merit that its solution can be analytically obtained under the quadratic performance measure. However, this theory has not been applied to reservoir system operation yet, because the tracking assumes no boundness of the control and state vectors. This paper presents deriving the optimal control law and solving the Riccati equations for the discrete time horizon, and its application to the real system. And the additional necessary conditions for the saturated vectors of the control and/or state are also derived using the concept of the Pontryagin's minimum principle. The logic and its algorithm in this work are not so positive to give a general solution. In fact, it is a matter of modeling in terms of relative magnitude of disturbance and time-step size. However its application to the real environment of the Han river, which comprises six major reservoirs in series/parallel, demonstrated satisfactory results over 36 monthly stages.

• Journal of Magnetics
• /
• v.18 no.2
• /
• pp.192-196
• /
• 2013

We have investigated the changes of electroencephalography (EEG) and electrocardiography (ECG) under pulsed magnetic field (PMF) and acupuncture stimulus on acupoint PC9. In order to compare quantitatively the effect of PMF and acupuncture stimulus, the difference of alpha activities are calculated from EEG spectra, and the spectrum curves of ECG were analyzed in the frequency domain of heart rate variability (HRV). The increase of alpha activities after both stimuli could be explained that the impulse of stimulus on PC9 might pass through sensory nerve following meridian and approach the cerebral cortex, causing the central nervous system (CNS) to be activated for pacifying emotion and calming the mind. The decrease in sympathovagal activity of HRV after both stimuli indicates that parasympathetic nerves were activated and the sympathetic nerves were in constrained condition. These findings suggest that PMF could be patient-friendly alternative non-invasive medical treatment for influencing human physiology, in comparison with acupuncture inserting the needle and inducing nervous and anxious state to subject.

• The Transactions of the Korean Institute of Electrical Engineers A
• /
• v.50 no.12
• /
• pp.584-590
• /
• 2001

This paper presents a windows program package for solving security constrained OPF in interconnected Power systems, which is based on the combined application of evolutionary programming(EP) and sequential quadratic programming(SQP). The objective functions are the minimization of generation fuel costs and system power losses. The control variables are the active power of the generating units, the voltage magnitude of the generator, transformer tap settings and SYC setting. The state variables are the bus voltage magnitude, the reactive power of the generating unit, line flows and the tie line flow In OPF considering security, the outages are selected by contingency ranking method. The resulting optimal operating point has to be feasible after outages such as any single line outage(respect of voltage magnitude, reactive power generation and power flow limits). The OPF package proposed is applied to IEEE 14 buses and 10 machines 39 buses model system.

• International conference on construction engineering and project management
• /
• 2009.05a
• /
• pp.242-249
• /
• 2009

High-rise construction sites, especially those situated in spatially constrained urban areas, have difficulties in timely delivery of materials. Modern techniques such as Just-in-time delivery, and use of information technology such as Project Management Information System (PMIS), are targeted to improve the efficiency of the logistics. Such IT-driven management techniques can be further benefited from state-of-the-art devices such as Radio Frequency Identification (RFID) tags and Ubiquitous Sensor Networks (USN), which has resulted in notable achievements in automated logistics management at the construction sites. Based on those achievements, this research develops USN hardware toolkits for construction lifts, which aims to be automated the vertical material delivery by sensing the material information and routing it automatically to the right place. The gathered information from the sensors can also be used for monitoring the overall status. The developed system will be tested in the actual high-rise construction sites to assess the system's feasibility. The proposed system is being implemented using Zigbee communication modules and RFID sensor networks which will communicate with the intelligent palette system (previously developed by the authors). To support the system, a lift-mountable intelligent toolkit is under development. Its feasibility test will be conducted by applying the implemented system to a test bed and then analyzing efficiency of the system and the toolkit. The collected test data will be provided as a basis of autonomous vertical transport equipment development. From this research, efficient management of the material lift is expected with increased accuracy, as well as better management of overall construction schedule benefited from the system. Further research will be expected to develop a smart construction lift, which will eliminate the need for human supervision, thus enabling a real 'autonomous' operation of the system.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.10
• /
• pp.4678-4702
• /
• 2018

Traffic Matrix estimation has always caught attention from researchers for better network management and future planning. With the advent of high traffic loads due to Cloud Computing platforms and Software Defined Networking based tunable routing and traffic management algorithms on the Internet, it is more necessary as ever to be able to predict current and future traffic volumes on the network. For large networks such origin-destination traffic prediction problem takes the form of a large under- constrained and under-determined system of equations with a dynamic measurement matrix. Previously, the researchers had relied on the assumption that the measurement (routing) matrix is stationary due to which the schemes are not suitable for modern software defined networks. In this work, we present our Compressed Sensing with Dynamic Model Estimation (CS-DME) architecture suitable for modern software defined networks. Our main contributions are: (1) we formulate an approach in which measurement matrix in the compressed sensing scheme can be accurately and dynamically estimated through a reformulation of the problem based on traffic demands. (2) We show that the problem formulation using a dynamic measurement matrix based on instantaneous traffic demands may be used instead of a stationary binary routing matrix which is more suitable to modern Software Defined Networks that are constantly evolving in terms of routing by inspection of its Eigen Spectrum using two real world datasets. (3) We also show that linking this compressed measurement matrix dynamically with the measured parameters can lead to acceptable estimation of Origin Destination (OD) Traffic flows with marginally poor results with other state-of-art schemes relying on fixed measurement matrices. (4) Furthermore, using this compressed reformulated problem, a new strategy for selection of vantage points for most efficient traffic matrix estimation is also presented through a secondary compression technique based on subset of link measurements. Experimental evaluation of proposed technique using real world datasets Abilene and GEANT shows that the technique is practical to be used in modern software defined networks. Further, the performance of the scheme is compared with recent state of the art techniques proposed in research literature.

• Journal of the Economic Geographical Society of Korea
• /
• v.21 no.2
• /
• pp.119-138
• /
• 2018

The Hmong people are one of the largest ethnic groups in Vietnam. They traditionally practice shifting cultivation for their daily subsistence. This group has a traditional governance system as well as strong clan and kinship relationships that occupy an important role in maintaining Hmong culture and livelihoods. The state's approval of the legitimate and statutory law for the Nature Reserve largely excluded local rights of access to and the use of natural resources. This study focusses on Hmong responses to the state interventions of the establishment of the Nature Reserve as well as forest land allocation. Based on Scott's contribution of Moral Economy (1976), the authors argue that local responses function as a 'risk-averter' against state intervention. Meanwhile, the intra and inter-ethnic relationships based on the 'subsistence ethic' help locals successfully mitigate state intervention. These findings help the state rethink their interventions, which have been constructed with very little respect for local differences or the desires of ethnic peoples. Furthermore, the main findings, which reveal that not only the intra-ethnic relationship but also the inter-ethnic relationship among ethnic minorities can play an important role in maintaining the Moral Economy, are expected to deepen the previous understanding on the Moral Economy, which has previously constrained its scope to the intra-ethnic relationship.

• Smart Structures and Systems
• /
• v.3 no.3
• /
• pp.245-261
• /
• 2007

Nonlinear time-domain system identification (SI) algorithm is proposed to assess damage in a shear building by synchronously estimating time-varying stiffness and damping parameters using measured acceleration data. Mass properties have been assumed as the a priori known information. Viscous damping was utilized for the current research. To chase possible nonlinear dynamic behavior under severe vibration, an incremental governing equation of vibrational motion has been utilized. Stiffness and damping parameters are estimated at each time step by minimizing the response error between measured and computed acceleration increments at the measured degrees-of-freedom. To solve a nonlinear constrained optimization problem for optimal structural parameters, sensitivities of acceleration increment were formulated with respect to stiffness and damping parameters, respectively. Incremental state vectors of vibrational motion were computed numerically by Newmark-${\beta}$ method. No model is pre-defined in the proposed algorithm for recovering the nonlinear response. A time-window scheme together with Monte Carlo iterations was utilized to estimate parameters with noise polluted sparse measured acceleration. A moving average scheme was applied to estimate the time-varying trend of structural parameters in all the examples. To examine the proposed SI algorithm, simulation studies were carried out intensively with sample shear buildings under earthquake excitations. In addition, the algorithm was applied to assess damage with laboratory test data obtained from free vibration on a three-story shear building model.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.63 no.1
• /
• pp.34-39
• /
• 2014

In cognitive radios, secondary users can use the spectrum exclusively allocated to a primary wireless system if the secondary users detect the spectrum in idle states. Because the secondary users can utilize the idle state of the spectrum, the utilization rate of the spectrum can be improved. The idle states can be detected by using secondary users' sensing schemes. However, the wireless channel environment where secondary users perform the spectrum sensing is not very friendly to secondary users because the signal-to-noise ratio of the received primary signal is very low. Hence, cooperative sensing scheme where more than one secondary user take part in the spectrum sensing is generally used in cognitive radios. In this paper, we investigate the cooperative sensing performance for machine-to-machine communication devices operated by batteries with limited energy. In general, the energy consumed for the spectrum sensing increases as the length of the sensing period and the number of cooperative sensing nodes. Accordingly, even though the total amount of the consumed energy is the same, an energy allocation methodology how to distribute the energy to the sensing period and sensing nodes can achieve the optimum sensing performance, which is numerically analyzed.