• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.1-10
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• 2021

The interest in underwater acoustic sensor networks (UWASNs), along with the rapid development of underwater industries, has increased. To operate UWASNs efficiently, it is important to adopt well-designed medium access control (MAC) protocols that prevent collisions and allow the sharing of resources between nodes efficiently. On the other hand, underwater channels suffer from a narrow bandwidth, long propagation delay, and low data rate, so existing terrestrial node pairing schemes for non orthogonal multiple access (NOMA) cannot be applied directly to underwater environments. Therefore, a multi-dimensional node pairing scheme is proposed to consider the unique underwater channel in UWASNs. Conventional NOMA schemes have considered the channel quality only in node pairing. Unlike previous schemes, the proposed scheme considers the channel gain and many other features, such as node fairness, traffic load, and the age of data packets to find the best node-pair. In addition, the sender employs a list of candidates for node-pairs rather than path loss to reduce the computational complexity. The simulation results showed that the proposed scheme outperforms the conventional scheme by considering the fairness factor with 23.8% increases in throughput, 28% decreases in latency, and 5.7% improvements in fairness at best.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.12
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• pp.291-306
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• 2020

Nowadays, Data-Network-AI (DNA)-based intelligent services and applications have become a reality to provide a new dimension of services that improve the quality of life and productivity of businesses. Artificial intelligence (AI) can enhance the value of IoT data (data collected by IoT devices). The internet of things (IoT) promotes the learning and intelligence capability of AI. To extract insights from massive volume IoT data in real-time using deep learning, processing capability needs to happen in the IoT end devices where data is generated. However, deep learning requires a significant number of computational resources that may not be available at the IoT end devices. Such problems have been addressed by transporting bulks of data from the IoT end devices to the cloud datacenters for processing. But transferring IoT big data to the cloud incurs prohibitively high transmission delay and privacy issues which are a major concern. Edge computing, where distributed computing nodes are placed close to the IoT end devices, is a viable solution to meet the high computation and low-latency requirements and to preserve the privacy of users. This paper provides a comprehensive review of the current state of leveraging deep learning within edge computing to unleash the potential of IoT big data generated from IoT end devices. We believe that the revision will have a contribution to the development of DNA-based intelligent services and applications. It describes the different distributed training and inference architectures of deep learning models across multiple nodes of the edge computing platform. It also provides the different privacy-preserving approaches of deep learning on the edge computing environment and the various application domains where deep learning on the network edge can be useful. Finally, it discusses open issues and challenges leveraging deep learning within edge computing.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.3
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• pp.72-83
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• 2017

GPUs can provide high throughput with latency hiding by executing many warps in parallel. MSHR(Miss Status Holding Registers) for L1 data cache tracks cache miss requests until required data is serviced from lower level memory. In recent GPUs, excessive requests for cache resources cause underutilization problem of GPU resources due to cache resource reservation fails. In this paper, we propose a new warp scheduling technique to reduce stall cycles under MSHR resource shortage. Cache miss rates for each warp is predicted based on the observation that each warp shows similar cache miss rates for long period. The warps showing low miss rates or computation-intensive warps are given high priority to be issued when MSHR is full status. Our proposal improves GPU performance by utilizing cache resource more efficiently based on cache miss rate prediction and monitoring the MSHR entries. According to our experimental results, reservation fail cycles can be reduced by 25.7% and IPC is increased by 6.2% with the proposed scheduling technique compared to loose round robin scheduler.

• Sleep Medicine and Psychophysiology
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• v.10 no.1
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• pp.32-38
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• 2003

Objectives: The purpose of this study is to investigate the effects of stress and personality on sleep patterns, and further, to identify potential correlations between stress and personality characteristics. Methods: A total of 174 healthy college students were subjects for this study. Participants filled out the Daily Stress Inventory before sleep and the Modified Pittsburgh Sleep Quality Index after sleep on three consecutive days. They also filled out the 16 Personality Factor Questionnaire (16-PF), BDI (Beck Depression Inventory) and STAI (State-Trait Anxiety Inventory). Results: Minor stresses highly correlated with subjective sleep quality and symptoms of non-restorative sleep. However, total sleep time, sleep latency, awakening frequency, and frequency of dreams were not explained by stress scores. The O (guilty feeling), C (low ego strength) and Q4 (high anxiety) factors of the 16-PF also highly correlated with symptoms of non-restorative sleep and significantly affected sleep patterns. BDI and STAI scores also correlated with the above personality factors and minor stresses. Conclusion: This study showed that minor stresses impaired the restorative effects of sleep. Personality characteristics such as low ego strength, high levels of anxiety, and feelings of guilt were vulnerable to minor stresses. Minor stress, various personality characteristics, different coping patterns, and emotional response are highly correlated with each other and affect sleep patterns.

• Sleep Medicine and Psychophysiology
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• v.7 no.2
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• pp.96-101
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• 2000

Objectives: Through comparing sleep variables and autonomic activities among three shifts in shift workers, the authors intended to clarify which shift is most tolerable and to identify the characteristics of their psychological and physical problems. This study is also expected to help shift workers to adapt themselves to their work more effectively. Methods: Fifty one shift workers took part in this study. They were working in a rapidly rotating system in which they worked for 3 days in one shift with one day off between each shift. Based on a sleep diary, sleep latency (SL), sleep period time (SPT), and number of wake after sleep onset (NWASO) were estimated and compared among the three shifts. In assessing sleepiness, Epworth sleepiness scale (ESS) and visual analogue scale (VAS) were used. To evaluate mood states among the three shifts, profile of mood states (POMS) was administered. Heart rate variability (HRV), and the level of adrenaline and noradrenaline were measured to assess autonomic activities. HRV included low frequency power (LF), high frequency power (HF), and LF/HF. Results: SPT was significantly lengthened during the evening shift and SL was shortened during the night shift. The workers showed a drop in alertness at wake-up during morning shift and a drop in alertness at work during night shift. During night shift the subjects complained of physical fatigue and cognitive decline. Comparison of HRV showed that parasympathetic activity was most prominent during the evening shift. Secretion of adrenaline and noradrenaline decreased during the evening shift, though statistically not significant. Conclusion: We found that the evening shift was most tolerable among the three shifts. It is recommended that morning light exposure be done during the morning shift and nocturnal light exposure during the night shift.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.12
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• pp.108-116
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• 2009

In this paper, we propose a Ethernet based audio distribution system with a new L1/L2 hybrid switching scheme, and evaluate its performance. The proposed scheme not only offers guaranteed low latency and jitter characteristics that are essentially required for the distribution of high-quality uncompressed audio traffic, and but also provide an efficient transmission of data traffic on the Ethernet environment. The audio distribution system with a proposed scheme consists of a master node and a number of relay nodes, and all nodes are mutually connected as a daisy-chain topology through up and downlinks. The master node generates an audio frame for each cycle of 125us, and the audio frame has 24 time slotted audio channels for carrying stereo 24 channels of 16-bit PCM sampled audio. On receiving the audio frame from its upstream node via the downlink, each intermediate node inserts its audio traffic to the reserved time slot for itself, then relays again to next node through its physical layer(L1) transmission - repeating. After reaching the end node, the audio frame is loopbacked through the uplink. On repeating through the uplink, each node makes a copy of audio slot that node has to receive, then play the audio. When the audio transmission is completed, each node works as a normal L2 switch, thus data frames are switched during the remaining period. For supporting this L1/L2 hybrid switching capability, we insert a glue logic for parsing and multiplexing audio and data frames at MII(Media Independent Interlace) between the physical and data link layers. The proposed scheme can provide a good delay performance and transmission efficiency than legacy Ethernet based audio distribution systems. For verifying the feasibility of the proposed L1/L2 hybrid switching scheme, we use OMNeT++ as a simulation tool with various parameters. From the simulation results, one can find that the proposed scheme can provides outstanding characteristics in terms of both jitter characteristic for audio traffic and transmission efficiency of data traffics.

• The Korean Journal of Pharmacology
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• v.16 no.1 s.26
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• pp.25-34
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• 1980

The in vitro guinea pig ureter responded to 5 sec trains of electrical stimuli with two contractions; the first an 'on response' (ON) occurred with $0.1{\sim}0.3$ sec after the onset o the stimulus train, the second an 'off response'(OFF) occurred $0.2{\sim}1.0$ sec after the termination of the stimulus train. Relaxation occurred between the two responses during a time when the stimulus was still being delivered. Longer duration and/or higher frequencies of stimuli within the train were required to elicit the OFF than the ON. Decreasing temperature from $37^{\circ}$ to $22^{\circ}$ decreased ON amplitude and increased OFF amplitude. $Ca^{++}$-free solution, 2 mM EDTA, 1 mM $Mn^{++}$ or $1{\mu}M$ verapamil rapidly abolished ON. OFF persisted when ON had disappeared by repeated stimulation at 0.12 train per sec. Conversely, caffeine, $50{\mu}M$ and theophylline, $10{\mu}M$ abolished OFF with only slight reduction of ON, and sodium nitroprusside decreased preferentially ON amplitude rather than OFF. Relaxation between ON and OFF was incomplete in low $Na^+$ solution. ON and OFF were not affected by the neural blockers tetrodotoxin, atropine or phentolamine, also pyrilamine and methysergide, and relaxation between ON and OFF was $Na^+$ dependent. Furthermore, ON depends on free $Ca^{++}$ and OFF is more dependent on bound or stored $Ca^{++}$.