• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.7B
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• pp.686-693
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• 2009

In this paper, we propose an efficient tag sleep method utilizing empty time slots for improving the tag collection performance in active RFID systems. In the proposed tag sleep method, the reader detects the occurrence of empty time slots by carrier sensing and utilizes the wasted empty time slots to transmit sleep commands to the collected tags throughout the framed slotted aloha-based tag collection process, resulting in reducing the time required for tag collection. Via the simulation experiments, we evaluated the performance of the tag collection applied with the proposed tag sleep method, compared with that of the basic tag collection. The simulation results showed that the tag collection applied with the proposed tag sleep method could reduce the average tag collection time by 12.28%, 12.30%, and 13.31 %, for the framed slotted aloha with the fixed 128 time slots and 256 time slots, and the dynamic framed slotted aloha anticollision protocols, respectively.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07a
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• pp.415-417
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• 2005

Core operations (e.9. TDMA scheduler, synchronized sleep period, data aggregation) of many proposed protocols for different layer of sensor network necessitate clock synchronization. Our Paper mingles the scheme of dynamic clustering and diffusion based asynchronous averaging algorithm for clock synchronization in sensor network. Our proposed algorithm takes the advantage of dynamic clustering and then applies asynchronous averaging algorithm for synchronization to reduce number of rounds and operations required for converging time which in turn save energy significantly than energy required in diffusion based asynchronous averaging algorithm.

• Sleep Medicine and Psychophysiology
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• v.19 no.1
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• pp.11-17
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• 2012

Objective: Among various methods developed to quantitatively explore electroencephalograms (EEG), we focused on a wavelet method that was known to yield robust results under nonstationary conditions. The aim of this study was thus to introduce the wavelet method and demonstrate its potential use in clinical sleep studies. Method: This study involved artificial EEG specifically designed to validate the wavelet method. The method was performed to obtain time-dependent spectral power and phase angles of the signal. Synchrony of multichannel EEG was analyzed by an order parameter of the instantaneous phase. The standard methods, such as Fourier transformation and coherence, were also performed and compared with the wavelet method. The method was further validated with clinical EEG and ERP samples available as pilot studies at academic sleep centers. Result: The time-frequency plot and phase synchrony level obtained by the wavelet method clearly showed dynamic changes in the EEG waveforms artificially fabricated. When applied to clinical samples, the method successfully detected changes in spectral power across the sleep onset period and identified differences between the target and background ERP. Conclusion: Our results suggest that the wavelet method could be an alternative and/or complementary tool to the conventional Fourier method in quantifying and identifying EEG and ERP biomarkers robustly, especially when the signals were nonstationary in a short time scale (1-100 seconds).

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.6
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• pp.126-134
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• 2015

A sleep disorder is being recognized as one of the major health issues related to high levels of stress. At the same time, interests about quality of sleep are rapidly increasing. However, diagnosing sleep disorder is not a simple task because patients should undergo polysomnography test, which requires a long time and high cost. To solve this problem, an accelerometer embedded wrist-worn device is being considered as a simple and low cost solution. However, conventional methods determine a state of user to "sleep" or "wake" according to whether values of individual section's accelerometer data exceed a certain threshold or not. As a result, a high miss-classification rate is observed due to user's intermittent movements while sleeping and tiny movements while awake. In this paper, we propose a novel method that resolves the above problems by employing a dynamic classifier which evaluates a similarity between the neighboring data scores obtained from SVM classifier. A performance of the proposed method is evaluated using 50 data sets and its superiority is verified by achieving 88.9% accuracy, 88.9% sensitivity, and 88.5% specificity.

• Journal of Information Processing Systems
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• v.9 no.1
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• pp.41-52
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• 2013

One of the obstacles preventing the Zigbee protocol from being widely used is the excessive power consumption of Zigbee devices in low bandwidth and low power requirement applications. This paper proposes a protocol that resolves the power efficiency problem. The proposed protocol reduces the power consumption of Zigbee devices in beacon-enabled networks without increasing the time taken by Zigbee peripherals to communicate with their coordinator. The proposed protocol utilizes a beacon control mechanism called a "sleep pattern," which is updated based on the previous event statistics. It determines exactly when Zigbee peripherals wake up or sleep. A simulation of the proposed protocol using realistic parameters and an experiment using commercial products yielded similar results, demonstrating that the protocol may be a solution to reduce the power consumption of Zigbee devices.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.9
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• pp.971-976
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• 2014

In this paper, we proposed a low power algorithm using state transition ready method. The proposed algorithm defined a sleep state, a idle state and a run state for the task. A state transition occurring at the time due to the delay time created in order to reduce the power consumption state in the middle of each inserted into the ready state. The ready state considering a power consumption and a delay time in state transition. A scheduling step of performing the steps in excess of the increasing problems have the delay time is long. The power consumption increased for the operation step increase. A state transition from a sleep state with the longest delay time in operating state occurs when the state is switched by the time delay caused by the increase in operating time reduces the overall power consumption reduced. Experiments [6] were compared with the results of the power consumption. The experimental results [6] is reduced power consumption than the efficiency of the algorithm has been demonstrated.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.5
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• pp.107-116
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• 2011

In this paper, a traffic adaptive sleep based medium access control (TAS-MAC) protocol for wireless sensor networks (WSNs) is proposed. The protocol aims for WSNs which consist of clustered sensor nodes and is based on TDMA-like schema. It is a typical schedule based mechanism which is adopted in previous protocols such as LEACH and Bit-Map Assisted MAC. The proposed MAC, however, considers unexpected long silent period in which sensor nodes have no data input and events do not happen in monitoring environment. With the simple traffic measurement, the TAS-MAC eliminates scheduling phases consuming energy in previous centralized approaches. A frame structure of the protocol includes three periods, investigation (I), transmission (T), and sleep-period (S). Through the I-period, TAS-MAC aggregates current traffic information from each end node and dynamically decide the length of sleep period to avoid energy waste in long silent period. In spite of the energy efficiency of this approach, the delay of data might increase. Thus, we propose an advanced version of TAS-MAC as well, each node in cluster sends one or more data packets to cluster head during the T-period of a frame. Through simulation, the performance in terms of energy consumption and transmission delay is evaluated. By comparing to BMA-MAC, the results indicate the proposed protocol is more energy efficient with tolerable expense in latency, especially in variable traffic situation.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
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• 2005.11a
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• pp.121-124
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• 2005

The High Rate Wireless Personal Area Networks (WPAN) is mainly targeted to consumer electronics and portable communication devices which need high rates and QoS. To achieve these goals, the WPAN provides data rates up to 1Gbps and adopts a Time Division Multiple Access (TDMA) MAC protocol. Since IEEE 802.15.3 MAC is based on TDMA scheme, it has good performance in dealing with real traffics. But it does not give better results for dynamic traffic. For dynamic traffic, IEEE 802.15.3 MAC needs a kind of request and response policy that brings about the degradation of performance in order to adapt to network changes. To overcome this problem and enhance the data throughput, this paper proposes a superframe structure which uses the Enhanced Contention Access Period (ECAP) to transmit data during sleep-CTA in PM mode.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.312-334
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• 2023

In large-scale computing, cloud computing plays an important role by sharing globally-distributed resources. The evolution of cloud has taken place in the development of data centers and numerous servers across the globe. But the cloud information centers incur huge operational costs, consume high electricity and emit tons of dioxides. It is possible for the cloud suppliers to leverage their resources and decrease the consumption of energy through various methods such as dynamic consolidation of Virtual Machines (VMs), by keeping idle nodes in sleep mode and mistreatment of live migration. But the performance may get affected in case of harsh consolidation of VMs. So, it is a desired trait to have associate degree energy-performance exchange without compromising the quality of service while at the same time reducing the power consumption. This research article details a number of novel algorithms that dynamically consolidate the VMs in cloud information centers. The primary objective of the study is to leverage the computing resources to its best and reduce the energy consumption way behind the Service Level Agreement (SLA)drawbacks relevant to CPU load, RAM capacity and information measure. The proposed VM consolidation Algorithm (PVMCA) is contained of four algorithms: over loaded host detection algorithm, VM selection algorithm, VM placement algorithm, and under loading host detection algorithm. PVMCA is dynamic because it uses dynamic thresholds instead of static thresholds values, which makes it suggestion for real, unpredictable workloads common in cloud data centers. Also, the Algorithms are adaptive because it inevitably adjusts its behavior based on the studies of historical data of host resource utilization for any application with diverse workload patterns. Finally, the proposed algorithm is online because the algorithms are achieved run time and make an action in response to each request. The proposed algorithms' efficiency was validated through different simulations of extensive nature. The output analysis depicts the projected algorithms scaled back the energy consumption up to some considerable level besides ensuring proper SLA. On the basis of the project algorithms, the energy consumption got reduced by 22% while there was an improvement observed in SLA up to 80% compared to other benchmark algorithms.

• Journal of the Ergonomics Society of Korea
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• v.16 no.2
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• pp.15-27
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• 1997

Brain potential is described using the mesocolumnar activity defined by averaged firings of excitatory and inhibitory neuron of neocortex. Lagrangian is constructed based on SMNI(Statistical Mechanics of Neocortical Interaction) and then Euler Lagrange equation is obtained. Excitatory neuron firing is assumed to be amplitude- modulated dominantly by the sum of two modes of frequency .omega. and 2 .omega. . Time series of this neuron firing is calculated numerically by Euler Lagrangian equation. I .omega. L related to low frequency distribution of power spectrum, I .omega. H hight frequency, and Sd(standard deviation) were introduced for the effective extraction of the dynamic property in the simulated brain potential. The relative behavior of I .omega. L, I .omega. H, and Sd was found by parameters .epsilon. and .gamma. related to nonlinearity and harmonics respectively. Experimental I .omega L, I .omega. H, and Sd were obtained from EEG of human in rest state and of canine in deep sleep state and were compared with theoretical ones.