• Title/Summary/Keyword: Temporal Scale

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Indoor RSSI Characterization using Statistical in Wireless Sensor Network (무선 센서네트워크에서의 통계적 방법에 의한 실내 RSSI 측정)

  • Pu, Chuan-Chin;Chung, Wan-Young
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.11
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    • pp.2172-2178
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    • 2007
  • In indoor environment, the combination of the two variations, large scale(path loss) and small scale(fading), leads to non-linear variation of RSSI(received signal strength indicator) values as distance varied. This has been one of the difficulties for indoor location estimation. This paper presents new findings on indoor RSSI characterization for more accurate model building. Experiments have been done statistically to find overall trend of RSSI values at different places and times within the same room. From experiments, it has been shown that the variation of RSSI values can be determined by both spatial and temporal factors. These two factors are directly indicated by the two main parameters of path loss model. The results show that all sensor nodes which are located at different places share the same characterization value for the temporal parameter whereas different values for the spatial parameters. The temporal parameter also has a large scale variation effect that is slowly time varying due to environmental changes. Using this relationship, the characterization for location estimation can be more efficient and accurate.

Effectiveness of Temporal Augmentation Using a Calvarial Onlay Graft during Pterional Craniotomy

  • Kim, Yoon Soo;Yi, Hyung Suk;Kim, Han Kyu;Han, Yea Sik
    • Archives of Plastic Surgery
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    • v.43 no.2
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    • pp.204-209
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    • 2016
  • Temporal hollowing occurs to varying degrees after pterional craniotomy. The most common cause of temporal hollowing is a bony defect of the pterional and temporal regions due to the resection of the sphenoid ridge and temporal squama for adequate exposure without overhang. The augmentation of such bony defects is important in preventing craniofacial deformities and postoperative hollowness. Temporal cranioplasty has been performed using a range of materials, such as acrylics, porous polyethylene, bone cement, titanium, muscle flaps, and prosthetic dermis. These methods are limited by the risk of damage to adjacent tissue and infection, a prolonged preparation phase, the possibility of reabsorption, and cost inefficiency. We have developed a method of temporal augmentation using a calvarial onlay graft as a single-stage neurosurgical reconstructive operation in patients requiring craniotomy. In this report, we describe the surgical details and review our institutional outcomes. The patients were divided into pterional craniotomy and onlay graft groups. Clinical temporal hollowing was assessed using a visual analog scale (VAS). Temporal soft tissue thickness was measured on preoperative and postoperative computed tomography (CT) studies. Both the VAS and CT-based assessments were compared between the groups. Our review indicated that the use of an onlay graft was associated with a lower VAS score and left-right discrepancy in the temporal contour than were observed in patients undergoing pterional craniotomy without an onlay graft.

Efficient Model Checking of Asynchronous Systems Exploiting Temporal Order-Based Reduction Method

  • Yamada, Chikatoshi;Nagata, Yasunori;Nakao, Zensho
    • Proceedings of the IEEK Conference
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    • 2002.07c
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    • pp.1964-1967
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    • 2002
  • Recently design verification have been played an important role in the design of large scale and complex systems. In this article, we especially focus on model checking methods. Behaviors of modeled systems are generally specified by temporal formulas of computation tree logic. However. Users must know well temporal specification because the specification might be complex. We proposed method that temporal formulas are gained inductively and amounts of memory and time are reduced. Finally, we will show verification results using our proposed method.

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Processing of dynamic wind pressure loads for temporal simulations

  • Hemon, Pascal
    • Wind and Structures
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    • v.21 no.4
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    • pp.425-442
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    • 2015
  • This paper discusses the processing of the wind loads measured in wind tunnel tests by means of multi-channel pressure scanners, in order to compute the response of 3D structures to atmospheric turbulence in the time domain. Data compression and the resulting computational savings are still a challenge in industrial contexts due to the multiple trial configurations during the construction stages. The advantage and robustness of the bi-orthogonal decomposition (BOD) is demonstrated through an example, a sail glass of the Fondation Louis Vuitton, independently from any tentative physical interpretation of the spatio-temporal decomposition terms. We show however that the energy criterion for the BOD has to be more rigorous than commonly admitted. We find a level of 99.95 % to be necessary in order to recover the extreme values of the loads. Moreover, frequency limitations of wind tunnel experiments are sometimes encountered in passing from the scaled model to the full scale structure. These can be alleviated using a spectral extension of the temporal function terms of the BOD.

Forecasting COVID-19 confirmed cases in South Korea using Spatio-Temporal Graph Neural Networks

  • Ngoc, Kien Mai;Lee, Minho
    • International Journal of Contents
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    • v.17 no.3
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    • pp.1-14
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    • 2021
  • Since the outbreak of the coronavirus disease 2019 (COVID-19) pandemic, a lot of efforts have been made in the field of data science to help combat against this disease. Among them, forecasting the number of cases of infection is a crucial problem to predict the development of the pandemic. Many deep learning-based models can be applied to solve this type of time series problem. In this research, we would like to take a step forward to incorporate spatial data (geography) with time series data to forecast the cases of region-level infection simultaneously. Specifically, we model a single spatio-temporal graph, in which nodes represent the geographic regions, spatial edges represent the distance between each pair of regions, and temporal edges indicate the node features through time. We evaluate this approach in COVID-19 in a Korean dataset, and we show a decrease of approximately 10% in both RMSE and MAE, and a significant boost to the training speed compared to the baseline models. Moreover, the training efficiency allows this approach to be extended for a large-scale spatio-temporal dataset.

An Analysis of Ecosystem Service's trade-off through Systems Thinking (시스템 사고를 통한 생태계서비스의 trade-off 관계 고찰)

  • Ham, Eun Kyung;Kim, Min;Chon, Jinhyung
    • Korean System Dynamics Review
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    • v.16 no.2
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    • pp.75-100
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    • 2015
  • The purpose of this study is to analyze causation of Ecosystem service's trade-off(ES trade-off) and to establish baseline data for wise spatial planning and management. In order to understand why and how ES trade-off occurs, systems thinking and causal loops were employed. The causal loop of ecosystem service creation cycle includes profits quantification process, decision making process, spatial planning and management process, and ecosystem services creation process. The profits quantification process has a limitation that all ecosystem service categories were not included in profits quantification, because quantification method for cultural services is insufficient. These problems led to unequal discussion opportunity in decision making process. ES trade-off occurs through transition of ecosystem function in spatial scale and temporal scale. In spatial scale, land-use variation and resource-use variation contribute to change an ecosystem function for different ES category by spatial planning and management. In temporal scale, a change of an ecosystem function for different ES category is influenced by ecological succession, seasonal change and land cover variation, which are parameter from environmental features. This study presented that spatial planning and management should ecosystem service assessment in order to enhance balanced ecosystem services.

Surf points based Moving Target Detection and Long-term Tracking in Aerial Videos

  • Zhu, Juan-juan;Sun, Wei;Guo, Bao-long;Li, Cheng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.11
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    • pp.5624-5638
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    • 2016
  • A novel method based on Surf points is proposed to detect and lock-track single ground target in aerial videos. Videos captured by moving cameras contain complex motions, which bring difficulty in moving object detection. Our approach contains three parts: moving target template detection, search area estimation and target tracking. Global motion estimation and compensation are first made by grids-sampling Surf points selecting and matching. And then, the single ground target is detected by joint spatial-temporal information processing. The temporal process is made by calculating difference between compensated reference and current image and the spatial process is implementing morphological operations and adaptive binarization. The second part improves KALMAN filter with surf points scale information to predict target position and search area adaptively. Lastly, the local Surf points of target template are matched in this search region to realize target tracking. The long-term tracking is updated following target scaling, occlusion and large deformation. Experimental results show that the algorithm can correctly detect small moving target in dynamic scenes with complex motions. It is robust to vehicle dithering and target scale changing, rotation, especially partial occlusion or temporal complete occlusion. Comparing with traditional algorithms, our method enables real time operation, processing $520{\times}390$ frames at around 15fps.

Investigating the underlying structure of particulate matter concentrations: a functional exploratory data analysis study using California monitoring data

  • Montoya, Eduardo L.
    • Communications for Statistical Applications and Methods
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    • v.25 no.6
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    • pp.619-631
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    • 2018
  • Functional data analysis continues to attract interest because advances in technology across many fields have increasingly permitted measurements to be made from continuous processes on a discretized scale. Particulate matter is among the most harmful air pollutants affecting public health and the environment, and levels of PM10 (particles less than 10 micrometers in diameter) for regions of California remain among the highest in the United States. The relatively high frequency of particulate matter sampling enables us to regard the data as functional data. In this work, we investigate the dominant modes of variation of PM10 using functional data analysis methodologies. Our analysis provides insight into the underlying data structure of PM10, and it captures the size and temporal variation of this underlying data structure. In addition, our study shows that certain aspects of size and temporal variation of the underlying PM10 structure are associated with changes in large-scale climate indices that quantify variations of sea surface temperature and atmospheric circulation patterns.

Formation CubeSat Constellation, SNIPE mission

  • Lee, Jaejin
    • The Bulletin of The Korean Astronomical Society
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    • v.46 no.1
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    • pp.58.4-59
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    • 2021
  • This presentation introduces Korea's SNIPE (Small scale magNespheric and Ionospheric Plasma Experiment) mission, formation flying CubeSat constellation. Observing particles and waves on a single satellite suffers from inherent space-time ambiguity. To observe spatial and temporal variations of the micro-scale plasma structures on the topside ionosphere, four 6U CubeSats (~ 10 kg) will be launched into a polar orbit of the altitude of ~500 km in 2021. The distances of each satellite will be controlled from 10 km to more than 100 km by formation flying algorithm. The SNIPE mission is equipped with identical scientific instruments, solid-state telescope, magnetometer, and Langmuir probe. All the payloads have a high temporal resolution (sampling rates of about 10 Hz). Iridium modules provide an opportunity to upload changes in operational modes when geomagnetic storms occur. SNIPE's observations of the dimensions, occurrence rates, amplitudes, and spatiotemporal evolution of polar cap patches, field-aligned currents (FAC), radiation belt microbursts, and equatorial and mid-latitude plasma blobs and bubbles will determine their significance to the solar wind-magnetosphere-ionosphere interaction and quantify their impact on space weather.

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