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Journal articles on the topic 'Sleep mode'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Jayakumar, Hrishikesh, Arnab Raha, and Vijay Raghunathan. "Sleep-Mode Voltage Scaling." ACM Transactions on Embedded Computing Systems 16, no. 1 (2016): 1–25. http://dx.doi.org/10.1145/2950054.

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Igrec, Dalibor, Jože Hebar, and Amor Chowdhury. "ENERGY MANAGEMENT IN MICROPROCESSOR-DRIVEN CIRCUIT DESIGN USING SLEEP MODES." Journal of Energy Technology 17, no. 3 (2025): 11–25. https://doi.org/10.18690/jet.17.3.11-25.2024.

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The article explores the important significance of sleep mode in the design of microprocessorcentric electronic devices, emphasising energy efficiency, device longevity and environmental sustainability. Sleep mode enables devices to enter low-power states during periods of inactivity, conserving energy and extending battery life. Various levels of sleep modes are examined, ranging from light to deep sleep, each with unique power savings and system responsiveness advantages.1 The article also presents a case study involving an electronic circuit controlling sensors, actuators, LTE, WiFi and a g

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Indraganti, Madhavi, Farsana Kutty, Reem Ali, Lulwa Al Noaimi, Saaeda Al-Bader, and Maryam Adel Al Mulla. "OCCUPANT PERCEPTION OF THERMAL COMFORT IN SLEEP ENVIRONMENTS IN QATAR." Journal of Engineering Research [TJER] 18, no. 2 (2022): 137–45. http://dx.doi.org/10.53540/tjer.vol18iss2pp137-145.

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A thermal comfort field survey in sleep environments in winter and spring seasons in Qatar collected 833 sets of objective and subjective thermal and sleep quality responses before going to bed and after getting up. The subjects felt cooler sensations most of the time, preferred warmer sensations and the sleep environments are considered comfortable overall. Griffiths comfort temperature (Tc) was 24.3 ˚C and 20.2 ˚C in FR and AC modes respectively. Subjects used air-conditioner (AC)s adaptively in heating mode in winter. In 82.7% cases in air-conditioned (AC) mode, the comfort temperature was

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Xiao, Zhu, Shuangchun Li, Xiaochun Chen, Dong Wang, and Wenjie Chen. "A Load-Balancing Energy Consumption Minimization Scheme in 5G Heterogeneous Small Cell Wireless Networks Under Coverage Probability Analysis." International Journal of Pattern Recognition and Artificial Intelligence 31, no. 07 (2017): 1759013. http://dx.doi.org/10.1142/s0218001417590133.

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Heterogeneous small cell networks (HSCN), as a promising paradigm to increase end-user data rates and improve the overall capacity, is expected to be a key cellular architecture in 5G wireless networks. However, energy consumed in HSCN is considerable due to the massive use of small cells. In this paper, we investigate the energy consumption issue which stems from the enormous number of running small cell base stations (SBSs) deploying in the HSCN. We first propose power consumption models so as to characterize the active state and the idle state of SBSs, respectively. Then two sleep modes for

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Veerappan Kousik, Nalliyanna Goundar, Yuvaraj Natarajan, Kallam Suresh, Rizwan Patan, and Amir H. Gandomi. "Improving Power and Resource Management in Heterogeneous Downlink OFDMA Networks." Information 11, no. 4 (2020): 203. http://dx.doi.org/10.3390/info11040203.

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In the past decade, low power consumption schemes have undergone degraded communication performance, where they fail to maintain the trade-off between the resource and power consumption. In this paper, management of resource and power consumption on small cell orthogonal frequency-division multiple access (OFDMA) networks is enacted using the sleep mode selection method. The sleep mode selection method uses both power and resource management, where the former is responsible for a heterogeneous network, and the latter is managed using a deactivation algorithm. Further, to improve the communicat

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Indraganti, Madhavi. "Investigation of thermal comfort in bedrooms in Qatar." E3S Web of Conferences 396 (2023): 01070. http://dx.doi.org/10.1051/e3sconf/202339601070.

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Good quality sleep is essential for overall health and productivity of human beings. In a field survey in bedrooms in Qatar, 833 sets of occupant responses on thermal comfort and sleep quality before going to bed and after getting up were made together with the corresponding environmental measurements and occupant’s clothing and bedding information. Subject’s thermal sensation was on the cooler side with a preference for warmer environments mostly. People generally felt comfortable, with Griffiths comfort temperature (Tc) being 24.3 °C. and 20.2 °C in free-running (FR) and air-conditioned (AC)

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Vacca, Irene. "Vibrio enters 'sleep mode' to survive." Nature Reviews Microbiology 15, no. 9 (2017): 515. http://dx.doi.org/10.1038/nrmicro.2017.102.

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8

Farrahi, Amir H., Gustavo E. Téllez, and Majid Sarrafzadeh. "Exploiting Sleep Mode for Memory Partitioning and Other Applications." VLSI Design 7, no. 3 (1998): 271–87. http://dx.doi.org/10.1155/1998/50491.

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Sleep mode operation and exploiting it to minimize the average power consumption are of great importance in modern VLSI circuits. In general, sleep mode refers to the mode in which part(s) of the system are idle. In this paper, we study the problem of partitioning a circuit according to the activity patterns of its elements such that circuit elements with similar activity patterns are packed into the same partition. Then a partition can be placed in sleep mode during the time intervals all elements contained in that partition are idle. We formulate the partitioning problem to exploit sleep mod

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Kim, Taehwa, Seungjin Lee, Hyungwoo Choi, Hong-Shik Park, and Junkyun Choi. "An Energy-Efficient Multi-Level Sleep Strategy for Periodic Uplink Transmission in Industrial Private 5G Networks." Sensors 23, no. 22 (2023): 9070. http://dx.doi.org/10.3390/s23229070.

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This paper proposes an energy-efficient multi-level sleep mode control for periodic transmission (MSC-PUT) in private fifth-generation (5G) networks. In general, private 5G networks meet IIoT requirements but face rising energy consumption due to dense base station (BS) deployment, particularly impacting operating expenses (OPEX). An approach of BS sleep mode has been studied to reduce energy consumption, but there has been insufficient consideration for the periodic uplink transmission of industrial Internet of Things (IIoT) devices. Additionally, 5G New Reno’s synchronization signal interval

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Zheng, Xiangwei, Xiaochun Yin, Xuexiao Shao, Yalin Li, and Xiaomei Yu. "Collaborative Sleep Electroencephalogram Data Analysis Based on Improved Empirical Mode Decomposition and Clustering Algorithm." Complexity 2020 (June 13, 2020): 1–14. http://dx.doi.org/10.1155/2020/1496973.

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Sleep-related diseases seriously affect the life quality of patients. Sleep stage classification (or sleep staging), which studies the human sleep process and classifies the sleep stages, is an important reference to the diagnosis and study of sleep disorders. Many scholars have conducted a series of sleep staging studies, but the correlation between different sleep stages and the accuracy of classification still needs to be improved. Therefore, this paper proposes an automatic sleep stage classification based on EEG. By constructing an improved empirical mode decomposition and K-means experim

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Negelspach, David, Anna Alkozei, Alisa Huskey, and William Killgore. "0008 Wake Onset Variability Effect on Functional Connectivity in the Default Mode Network." SLEEP 47, Supplement_1 (2024): A4. http://dx.doi.org/10.1093/sleep/zsae067.0008.

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Abstract Introduction Decoupling patterns of sleep and wake from underlying circadian oscillations is associated with poor sleep health. While this has been studied with respect to shift work, it is unclear if minor variations in normative sleep/wake patterns affect the restoration of cognitive function during sleep intervals while controlling for total sleep time. It is commonplace to adhere to a fixed sleep/wake schedule, however, this practice does not account for day-to-day variations in physiological need for sleep. We examined the relationship between sleep-interval variability and fMRI

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Paul, Ayan, Khin Wee Lai, Juliana Usman, et al. "Investigating the Effects of Ogawa Master Drive AI Automated Massage on Blood Circulation and Sleep Quality." Journal of Medical Imaging and Health Informatics 11, no. 5 (2021): 1357–63. http://dx.doi.org/10.1166/jmihi.2021.3810.

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Sleep and stress-related disorders are increasingly becoming more prevalent among adult population. Massage therapy (MT) may assist in improving the peripheral circulation through mechanical manipulation of soft tissues and passively act upon reducing stress stimuli as well as induce relaxation and sleep. For the purpose of evaluating the efficacy of massage chair therapy (MCT), this study is divided into two parts. First, 15 participants (mean age = (21.00 ±2.00) years; body mass index (BMI) = (19.22 ±2.23)) were enrolled in a randomized controlled, cross-over, and single-blinded trial on pre

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Rajagopal, Anita, and Cynthia Bodkin. "1095 Treatment with Trilogy AVAPS AE Mode in Pompe Disease with Chronic Respiratory Failure Unresponsive to AVAPS ST Mode." Sleep 41, suppl_1 (2018): A407. http://dx.doi.org/10.1093/sleep/zsy063.1094.

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Elleithy, Abdelrahman, Gonhsin Liu, and Ali Elrashidi. "A New Model of the Lifetime of Wireless Sensor Networks in Pure Water Communications." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 3, no. 1 (2012): 24–33. http://dx.doi.org/10.24297/ijct.v3i1a.2723.

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Abstractâ€”In this paper we present an a new model for thelifetime of wireless sensor networks used for underwatercommunications in pure water. The new model for powercommunications takes into consideration parameters such aspower consumption for the active mode, power consumption forthe sleep mode, power consumption for the transient mode,transmission period, transient mode duration, sleep modeduration, and active mode duration. The power communicationsmodel is incorporated in the life time model of wireless sensornetworks. The life time model takes into consideration severalparameters such a

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15

Ashraf, Imran, Federico Boccardi, and Lester Ho. "SLEEP mode techniques for small cell deployments." IEEE Communications Magazine 49, no. 8 (2011): 72–79. http://dx.doi.org/10.1109/mcom.2011.5978418.

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16

Wang, R., H. Haas, J. S. Thompson, and P. M. Grant. "Sleep mode design for green base stations." IET Communications 5, no. 18 (2011): 2606–16. http://dx.doi.org/10.1049/iet-com.2011.0104.

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Mizutani, Noboru, Katsuhisa Waseda, Kenji Asai, and Isao Katou. "Effect of pacing mode on sleep disturbance." Journal of Artificial Organs 6, no. 2 (2003): 106–11. http://dx.doi.org/10.1007/s10047-003-0212-1.

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18

Gujar, Ninad, Seung-Schik Yoo, Peter Hu, and Matthew P. Walker. "The Unrested Resting Brain: Sleep Deprivation Alters Activity within the Default-mode Network." Journal of Cognitive Neuroscience 22, no. 8 (2010): 1637–48. http://dx.doi.org/10.1162/jocn.2009.21331.

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The sleep-deprived brain has principally been characterized by examining dysfunction during cognitive task performance. However, far less attention has been afforded the possibility that sleep deprivation may be as, if not more, accurately characterized on the basis of abnormal resting-state brain activity. Here we report that one night of sleep deprivation significantly disrupts the canonical signature of task-related deactivation, resulting in a double dissociation within anterior as well as posterior midline regions of the default network. Indeed, deactivation within these regions alone dis

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Huang, Muzhi, Yangpan Ou, Huabing Li, et al. "Association between abnormal default mode network homogeneity and sleep disturbances in major depressive disorder." General Psychiatry 37, no. 2 (2024): e101371. http://dx.doi.org/10.1136/gpsych-2023-101371.

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BackgroundSleep disturbance is a common comorbidity of major depressive disorder (MDD). However, network homogeneity (NH) changes of the default mode network (DMN) in MDD with sleep disturbances are unclear.AimsThe purpose of this study was to probe the abnormal NH in the DMN in MDD with sleep disturbances and to reveal the differences between MDD with or without sleep disturbances.MethodsTwenty-four patients with MDD and sleep disturbances (Pa_s), 33 patients with MDD without sleep disturbances (Pa_ns) and 32 healthy controls (HCs) were recruited in this study. Resting-state functional imagin

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Hakim, Galang Persada Nurani, Muhammad Hafizd Ibnu Hajar, Ahmad Firdausi, and Eko Ramadhan. "Benchmarking In Microcontroller Development Board Power Consumption For Low Power Iot Wsn Application." Jurnal Teknologi Elektro 13, no. 1 (2022): 25. http://dx.doi.org/10.22441/jte.2022.v13i1.005.

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One of the advantages of Wireless Sensor Network would be its ability to reduce cost of communication system using node to node communication. However Wireless Sensor Network also had a disadvantage which is has limited energy which is include this as low power application. This small energy capacity has limit WSN node capability to operate for a long time. In this paper, we compare power consumption for 3 popular microcontroller development platforms that use for fast development and prototyping Wireless Sensor Network node. The power consumption was including active mode (using most energy)

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Xue, Jian Bin, Song Bai Li, Ting Zhang, and Wen Hua Wang. "Type II Sleep Mode Operation for IEEE 802.16e Based WiMAX." Applied Mechanics and Materials 128-129 (October 2011): 343–49. http://dx.doi.org/10.4028/www.scientific.net/amm.128-129.343.

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To overcome the flaw of energy efficiency drop in broad band wireless communication with the short time sleep, the energy-saving mechanism of the sleep mode operation was researched in IEEE 802.16e. In this paper we propose a dynamic algorithm to tune the ratio of the sleep windows and receive windows according to the traffic load. Then, a Markov chain model was set up to analyze the energy efficiency and mean access delay. NS2 simulation results show that the proposed algorithm can achieve marked gain in energy efficiency compared to the traditional energy saving mechanism.

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22

Fawzi, Sura, and Norashidah Md Din. "A Mininet emulation study for SDN fat tree data center sleep mode routing algorithms." Edelweiss Applied Science and Technology 8, no. 6 (2024): 8956–67. https://doi.org/10.55214/25768484.v8i6.3921.

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Big-data networks are raising energy use and associated ecological effects and have become a significant cause for concern in the last decade. With the expected significant increase in the traffic demand in data centres escalates the need to be energy efficient. In this scenario, the implementation of sleep mode in software defined network (SDN) data centres could provide an energy aware solution. Energy consumed of the network can be reduced by putting underutilized network devices or components to sleep. Employing sleep mode aligns with sustainability goals and can reduce the environmental i

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23

Werth, Esther, Peter Achermann, and Alexander A. Borbély. "II. Muscle atonia in non-REM sleep." American Journal of Physiology-Regulatory, Integrative and Comparative Physiology 283, no. 2 (2002): R527—R532. http://dx.doi.org/10.1152/ajpregu.00466.2001.

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One of the hallmarks of rapid eye movement (REM) sleep is muscle atonia. Here we report extended epochs of muscle atonia in non-REM sleep (MAN). Their extent and time course was studied in a protocol that included a baseline night, a daytime sleep episode with or without selective REM sleep deprivation, and a recovery night. The distribution of the latency to the first occurrence of MAN was bimodal with a first mode shortly after sleep onset and a second mode 40 min later. Within a non-REM sleep episode, MAN showed a U-shaped distribution with the highest values before and after REM sleep. Whe

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Bang, Hakjeon, Jongdeog Kim, Sang-Soo Lee, and Chang-Soo Park. "Determination of Sleep Period for Cyclic Sleep Mode in XG-PON Power Management." IEEE Communications Letters 16, no. 1 (2012): 98–100. http://dx.doi.org/10.1109/lcomm.2011.111011.111322.

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Rho, Y., and S. Vijayan. "0124 A Prefrontal-Amygdala Network Model of the Cellular and Circuit-Level Mechanisms of Emotional Memory Consolidation During the Awake State and REM Sleep." Sleep 43, Supplement_1 (2020): A49. http://dx.doi.org/10.1093/sleep/zsaa056.122.

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Abstract Introduction Rapid eye movement (REM) sleep has been implicated in the consolidation of emotional memories. Our recent work found a candidate system for REM-related memory consolidation. We showed that during REM sleep, the frontal cortices are dominated by theta (4–8 Hz) oscillations and bursts of beta (15–35 Hz) activity. Studies suggest that rhythmic interactions between the frontal cortices and limbic structures, in particular the amygdala, play a critical role in the consolidation of emotional memories. However, the mechanisms responsible for memory consolidation during these rhy

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Parajuli, Madan, Amy W. Amara, and Mohamed Shaban. "Deep-learning detection of mild cognitive impairment from sleep electroencephalography for patients with Parkinson’s disease." PLOS ONE 18, no. 8 (2023): e0286506. http://dx.doi.org/10.1371/journal.pone.0286506.

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Parkinson’s disease which is the second most prevalent neurodegenerative disorder in the United States is a serious and complex disease that may progress to mild cognitive impairment and dementia. The early detection of the mild cognitive impairment and the identification of its biomarkers is crucial to support neurologists in monitoring the progression of the disease and allow an early initiation of effective therapeutic treatments that will improve the quality of life for the patients. In this paper, we propose the first deep-learning based approaches to detect mild cognitive impairment in t

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Shen, Xue Li, and Ying Le Fan. "Sleep Stage Classification Based on EEG Signals by Using Improved Hilbert-Huang Transform." Applied Mechanics and Materials 138-139 (November 2011): 1096–101. http://dx.doi.org/10.4028/www.scientific.net/amm.138-139.1096.

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Research on automatic sleep staging based on EEG signals has a significant meaning for objective evaluation of sleep quality. An improved Hilbert-Huang transform method was applied to time-frequency analysis of non-stable EEG signals for the sleep staging in this paper. In order to settle the frequency overlapping problem of intrinsic mode function obtained from traditional HHT, wavelet package transform was introduced to bandwidth refinement of EEG before the empirical mode decomposition was conducted. This method improved the time-frequency resolution effectively. Then the intrinsic mode fun

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Sun-Jong Kwon, Yun Won Chung, and Dan Keun Sung. "Queueing model of sleep-mode operation in cellular digital packet data." IEEE Transactions on Vehicular Technology 52, no. 4 (2003): 1158–62. http://dx.doi.org/10.1109/tvt.2003.814218.

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Zhou, Wenzhe, and Zilu Liu. "Design and Optimization of Hotel Management Information System Based on Artificial Intelligence." Scientific Programming 2022 (June 14, 2022): 1–9. http://dx.doi.org/10.1155/2022/2445343.

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With the improvement of people’s living standards, the traditional hotel management model has been unable to meet the needs of customers. The traditional hotel management model also has the defects of low efficiency. The hotel management model is also gradually developing towards the direction of intelligence. The combination of artificial intelligence technology and hotel management can not only improve the operation efficiency of the hotel but also solve the operation cost of the hotel. For customers, artificial intelligence technology can bring smarter and more comfortable accommodation con

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Jia, Zonghang, Zhonghui Li, and Yujie Li. "Causal relationship between sleep characteristics and thyroid function: A bidirectional Mendelian randomization study." Medicine 103, no. 46 (2024): e40516. http://dx.doi.org/10.1097/md.0000000000040516.

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Background: Previous researches have revealed some links between thyroid function and sleep characteristics, however it remains unclear which one causes the other. The purpose of this study was to investigate the potential causal relationship between hyperthyroidism, hypothyroidism, and sleep characteristics. Methods: We utilized aggregated data from published genome-wide association studies (GWAS) to select genetic instruments for sleep variables. The 5 sleep-related traits (chronotype, short sleep duration, long sleep duration, daytime sleepiness, and insomnia) were associated with distinct

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Zhang, Lincong, Lei Guo, Yejun Liu, Kefeng Wei, and Weigang Hou. "A Multicast-Traffic-Oriented Energy-Saving Algorithm with a Hybrid Sleep Mode for EPONs." Journal of Electrical and Computer Engineering 2016 (2016): 1–10. http://dx.doi.org/10.1155/2016/6785752.

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High energy consumption in Ethernet Passive Optical Networks (EPONs) has caused intense research on energy-saving methods in recent years. The most common method for EPON energy saving is to cause optical network units (ONUs) to sleep which are idle or low loaded. With the popularity of multimedia applications, the ONUs carry not only unicast traffic but also more and more multicast traffic. However, existing studies mainly focus on ONUs that support only unicast traffic. The many differences between multicast traffic and unicast traffic make it necessary to design novel energy-saving methods.

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RAMCHARAN, EION J., JAMES W. GNADT, and S. MURRAY SHERMAN. "Burst and tonic firing in thalamic cells of unanesthetized, behaving monkeys." Visual Neuroscience 17, no. 1 (2000): 55–62. http://dx.doi.org/10.1017/s0952523800171056.

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Thalamic relay cells fire in two distinct modes, burst or tonic, and the operative mode is dictated by the inactivation state of low-threshold, voltage-gated, transient (or T-type) Ca2+ channels. Tonic firing is seen when the T channels are inactivated via membrane depolarization, and burst firing is seen when the T channels are activated from a hyperpolarized state. These response modes have very different effects on the relay of information to the cortex. It had been thought that only tonic firing is seen in the awake, alert animal, but recent evidence from several species suggests that burs

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Li, Tiefeng, Caiwen Ma, and WenHua Li. "The System Power Control Unit Based on the On-Chip Wireless Communication System." Scientific World Journal 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/939254.

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Currently, the on-chip wireless communication system (OWCS) includes 2nd-generation (2G), 3rd-generation (3G), and long-term evolution (LTE) communication subsystems. To improve the power consumption of OWCS, a typical architecture design of system power control unit (SPCU) is given in this paper, which can not only make a 2G, a 3G, and an LTE subsystems enter sleep mode, but it can also wake them up from sleep mode via the interrupt. During the sleep mode period, either the real-time sleep timer or the global system for mobile (GSM) communication sleep timer can be used individually to arouse

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Olcese, Umberto, Steve K. Esser, and Giulio Tononi. "Sleep and Synaptic Renormalization: A Computational Study." Journal of Neurophysiology 104, no. 6 (2010): 3476–93. http://dx.doi.org/10.1152/jn.00593.2010.

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Recent evidence indicates that net synaptic strength in cortical and other networks increases during wakefulness and returns to a baseline level during sleep. These homeostatic changes in synaptic strength are accompanied by corresponding changes in sleep slow wave activity (SWA) and in neuronal firing rates and synchrony. Other evidence indicates that sleep is associated with an initial reactivation of learned firing patterns that decreases over time. Finally, sleep can enhance performance of learned tasks, aid memory consolidation, and desaturate the ability to learn. Using a large-scale mod

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QU, Hong-wei. "Improved sleep mode mechanism based on IEEE 802.16e." Journal of Computer Applications 28, no. 8 (2008): 1959–64. http://dx.doi.org/10.3724/sp.j.1087.2008.01959.

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Kamitsos, Ioannis, Paschalis Tsiaflakis, Ken J. Kerpez, Sangtae Ha, and Mung Chiang. "Stable Sleep Mode Optimization for Energy Efficient DSL." IEEE Transactions on Communications 63, no. 12 (2015): 5116–27. http://dx.doi.org/10.1109/tcomm.2015.2481885.

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Yuan, Zhaohui, Yuping Zhang, and Chun Jason Xue. "Sleep-aware mode assignment in wireless embedded systems." Journal of Parallel and Distributed Computing 71, no. 7 (2011): 1002–10. http://dx.doi.org/10.1016/j.jpdc.2010.11.006.

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Jurdak, Raja, Antonio G. Ruzzelli, and Gregory M. P. O'Hare. "Radio Sleep Mode Optimization in Wireless Sensor Networks." IEEE Transactions on Mobile Computing 9, no. 7 (2010): 955–68. http://dx.doi.org/10.1109/tmc.2010.35.

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Tashjian, Sarah M., Diane Goldenberg, Martin M. Monti, and Adriana Galván. "Sleep quality and adolescent default mode network connectivity." Social Cognitive and Affective Neuroscience 13, no. 3 (2018): 290–99. http://dx.doi.org/10.1093/scan/nsy009.

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40

Bhaskaran, Arun M. "Adaptive Sleep Mode Mechanism for 3G WiMax Networks." IOSR Journal of Electronics and Communication Engineering 8, no. 6 (2013): 56–61. http://dx.doi.org/10.9790/2834-0865661.

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41

Vu, T. H., V. C. Luc, N. T. Quan, T. Thanh, N. H. Thanh, and P. N. Nam. "Sleep Mode and Wakeup Method for OpenFlow Switches." Journal of Low Power Electronics 10, no. 3 (2014): 347–53. http://dx.doi.org/10.1166/jolpe.2014.1328.

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42

Caughey, Aaron B. "Poor sleep in pregnancy and mode of delivery." American Journal of Obstetrics and Gynecology 193, no. 3 (2005): 1286. http://dx.doi.org/10.1016/j.ajog.2005.02.122.

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43

Chiaraviglio, Luca, Delia Ciullo, Marco Mellia, and Michela Meo. "Modeling sleep mode gains in energy-aware networks." Computer Networks 57, no. 15 (2013): 3051–66. http://dx.doi.org/10.1016/j.comnet.2013.07.011.

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Olson, Magdalena, Megan Petrov, Li Liu, and Corrie Whisner. "Infant Night Sleep Trajectories Differ by Feeding Mode." Current Developments in Nutrition 9 (May 2025): 106857. https://doi.org/10.1016/j.cdnut.2025.106857.

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Raymann, Roy, Nyayabrata Nayak, Nathaniel Watson, Luke Gahan, and Elie Gottlieb. "0351 Towards Interpreting Consumer Sleep Data: Distributions of Sleep Scores." Sleep 45, Supplement_1 (2022): A158. http://dx.doi.org/10.1093/sleep/zsac079.348.

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Abstract Introduction With the rise of sleep measurement technology becoming widely available to the public, it has become apparent that traditional sleep metrics might not be best suited for a lay audience. Most consumer industry has started including a metric that would capture sleep quality, although the exact calculations of these scores remain proprietary. These novel outcome metrics require a set of reference values in order to become interpretable. Here, we provide reference values for the parameters SleepScore, BodyScore and MindScore as included in the SleepScore Labs non-contact radi

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Jin, Shun Fu, Rong Yu Fan, and Li Chen. "Performance Analysis of a Simple Power Saving Scheme for Energy Efficient Ethernet." Applied Mechanics and Materials 151 (January 2012): 583–86. http://dx.doi.org/10.4028/www.scientific.net/amm.151.583.

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In order to improve the energy efficiency and build a green Ethernet, we propose a simple power saving (SPS) scheme with a burst transmission for Energy Efficient Ethernet. In SPS scheme, let the link transfer to the sleep mode as soon as no packets are ready for transmission, whereas let the link return to the awake mode when a fixed number of packets arrive during the sleep mode. We build a vacation queueing model with N strategy to describe the working principle of SPS scheme. By using the method of embedded Markov chain, the formulas of performance measures are given. Finally, numerical re

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Hill, Sean, and Giulio Tononi. "Modeling Sleep and Wakefulness in the Thalamocortical System." Journal of Neurophysiology 93, no. 3 (2005): 1671–98. http://dx.doi.org/10.1152/jn.00915.2004.

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When the brain goes from wakefulness to sleep, cortical neurons begin to undergo slow oscillations in their membrane potential that are synchronized by thalamocortical circuits and reflected in EEG slow waves. To provide a self-consistent account of the transition from wakefulness to sleep and of the generation of sleep slow waves, we have constructed a large-scale computer model that encompasses portions of two visual areas and associated thalamic and reticular thalamic nuclei. Thousands of model neurons, incorporating several intrinsic currents, are interconnected with millions of thalamocor

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Killgore, William, Samantha Jankowski, Kymberly Henderson-Arredondo, et al. "0332 Improving Sleep with Continuous Theta Burst Transcranial Magnetic Stimulation (TMS) of the Default Mode Network." SLEEP 46, Supplement_1 (2023): A147—A148. http://dx.doi.org/10.1093/sleep/zsad077.0332.

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Abstract Introduction Chronic insomnia is a disorder associated with increased cognitive arousal. Insomnia is also associated with activation/connectivity within the default mode network (DMN) of the brain, consistent with the hyperarousal theory. We hypothesized that suppression of the DMN with a type of repetitive transcranial magnetic stimulation (rTMS) known as continuous theta burst stimulation (cTBS) would lead to improved overnight sleep. Methods Twenty participants (12 female; age=26.9, SD=6.6 years) meeting criteria for insomnia/sleep disorder completed a counterbalanced sham-controll

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Zeng, Xiaobo, Min Zhu, Lu Wang, and Xiaohan Sun. "Optimization of sleep period in watchful sleep mode for power-efficient passive optical networks." Photonic Network Communications 35, no. 3 (2017): 300–308. http://dx.doi.org/10.1007/s11107-017-0747-3.

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Sree, R. Krithiga. "A Single-Lead Electrocardiogram-Derivative Empirical Mode Decomposition-Based Deep Learning Model for Sleep Apnea Identification." International Journal for Research in Applied Science and Engineering Technology 12, no. 7 (2024): 1116–26. http://dx.doi.org/10.22214/ijraset.2024.63676.

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Abstract: While polysomnography (PSG) is the gold standard for detecting sleep apnea (SA), the insertion of several disruptive devices may impair the quality of the patient's sleep, and its interpretation requires specialised training from a sleep scientist or technician. Heart rate variability (HRV) and electrocardiogram (ECG)-derived respiration (EDR) have been used in recent years to automatically detect SA and lessen the negative effects of PSG. Currently, the majority of suggested methods concentrate on feature engineering and machine learning (ML) techniques, which call for previous expe

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