The Future of the European Environment for Telecommunications

Pieter S. Weltevreden 정보통신정책연구원 1990 세미나및공청회 Vol.1990 No.

Redefining Effusive-Constrictive Pericarditis with Echocardiography

Pieter van der Bijl,Philip Herbst,Anton F. Doubell 한국심초음파학회 2016 Journal of Cardiovascular Imaging (J Cardiovasc Im Vol.24 No.4

Background: Effusive-constrictive pericarditis (ECP) is traditionally diagnosed by using the expensive and invasive techniqueof direct pressure measurements in the pericardial space and the right atrium. The aim of this study was to assess the diagnosticrole of echocardiography in tuberculous ECP. Methods: Intrapericardial and right atrial pressures were measured pre- and post-pericardiocentesis, and right ventricular andleft ventricular pressures were measured post-pericardiocentesis in patients with tuberculous pericardial effusions. Echocardiographywas performed post-pericardiocentesis. Traditional, pressure-based diagnostic criteria were compared with post-pericardiocentesissystolic discordance and echocardiographic evidence of constriction. Results: Thirty-two patients with tuberculous pericardial disease were included. Sixteen had ventricular discordance (invasivelymeasured), 16 had ECP as measured by intrapericardial and right atrial invasive pressure measurements and 17 had ECP determinedechocardiographically. The sensitivity and specificity of pressure-guided measurements (compared with discordance) forthe diagnosis of ECP were both 56%. The positive and negative predictive values were both 56%. The sensitivity of echocardiography(compared with discordance) for the diagnosis of ECP was 81% and the specificity 75%, while the positive and the negativepredictive values were 76% and 80%, respectively. Conclusion: Echocardiography shows a better diagnostic performance than invasive, pressure-based measurements for the diagnosisof ECP when both these techniques are compared with the gold standard of invasively measured systolic discordance.

How to tackle congestion in acute heart failure

( Pieter Martens ),( Wilfried Mullens ) 대한내과학회 2018 The Korean Journal of Internal Medicine Vol.33 No.3

Acute heart failure is a common complication of chronic heart failure and is associated with a high risk for subsequent mortality and morbidity. In 90% of case acute heart failure is the resultant of congestion, a manifestation of fluid build-up due to increased filling pressures. As residual congestion at discharge following an acute heart failure episodes is one of the strongest predictors of poor outcome, the goal of therapy should be to resolve congestion completely. Important to comprehend is that increased cardiovascular filling pressures are not solely the resultant of intravascular volume excess but can also be induced by a decreased venous capacitance. This review article focusses on the pathophysiology, diagnoses, and treatment of congestion in acute heart failure. A clear distinction is made between states of volume overload (intravascular volume excess) or volume redistribution (decreased venous capacitance) contributing to congestion in acute heart failure.

2D LIDAR 스캐너와 파티클 필터 레이저빔 모델 기반의 과수 로봇의 주간 내 자율주행

Pieter M. Blok,서현권(Hyun Kwon Suh),Koen van Boheemen,김학진(Hak-Jin Kim),김국환(Gook-Hwan Kim) 제어로봇시스템학회 2018 제어·로봇·시스템학회 논문지 Vol.24 No.8

In mountainous orchards, agricultural tasks, such as crop protection and harvesting, are characterized as being labor intensive and dangerous. An autonomous orchard robot that can execute these unattended seems a promising alternative to increase task operability. An essential function in the development of an autonomous orchard robot is navigation, which is usually based on tree-row detection from LIDAR scan data by using navigational algorithms. This research applies a probabilistic particle filter (PF) algorithm with a novel laser-beam model for the autonomous in-row navigation of an orchard robot. The navigational accuracy of the algorithm is assessed in a Dutch apple orchard over a distance of 500 m, with the robot driving at two velocities: 0.25 m/s and 0.50 m/s. At both speeds, almost 50% of the observed lateral deviations were lower than 0.05 m from the optimal navigation line. With the use of the PF algorithm, the robot navigated itself between six patterns of tree rows with artificially removed trees. Some lateral deviations exceeded 0.10 m when three adjacent trees were missing in both tree rows. Based on these results, a PF with a laser beam model is an accurate and robust algorithm for the autonomous in-row navigation in semi-structured outdoor environments, such as orchards.

Cross-Layer Reduction of Wireless Network Card Idle Time to Optimize Energy Consumption of Pull Thin Client Protocols

Pieter Simoens,Farhan Azmat Ali,Bert Vankeirsbilck,Lien Deboosere,Filip De Turck,Bart Dhoedt,Piet Demeester,Rodolfo Torrea-Duran,Liesbet Van der Perre,Antoine Dejonghe 한국통신학회 2012 Journal of communications and networks Vol.14 No.1

Thin client computing trades local processing for network bandwidth consumption by offloading application logic to remote servers. User input and display updates are exchanged between client and server through a thin client protocol. On wireless devices, the thin client protocol traffic can lead to a significantly higher power consumption of the radio interface. In this article, a cross-layer framework is presented that transitions the wireless network interface card (WNIC) to the energy-conserving sleep mode when no traffic from the server is expected. The approach is validated for different wireless channel conditions, such as path loss and available bandwidth, as well as for different network roundtrip time values. Using this cross-layer algorithm for sample scenario with a remote text editor, and through experiments based on actual user traces, a reduction of the WNIC energy consumption of up to 36.82% is obtained, without degrading the application’s reactivity.

Parallel Deblocking Filtering in MPEG-4 AVC/H.264 on Massively Parallel Architectures

Pieters, Bart,Hollemeersch, Charles-Frederik J,De Cock, Jan,Lambert, Peter,De Neve, Wesley,Van de Walle, Rik IEEE 2011 IEEE transactions on circuits and systems for vide Vol.21 No.1

<P>The deblocking filter in the MPEG-4 AVC/H.264 standard is computationally complex because of its high content adaptivity, resulting in a significant number of data dependencies. These data dependencies interfere with parallel filtering of multiple macroblocks (MBs) on massively parallel architectures. In this letter, we introduce a novel MB partitioning scheme for concurrent deblocking in the MPEG-4 AVC/H.264 standard, based on our idea of deblocking filter independency, a corrected version of the limited error propagation effect proposed in the letter. Our proposed scheme enables concurrent MB deblocking of luma samples with limited synchronization effort, independently of slice configuration, and is compliant with the MPEG-4 H.264/AVC standard. We implemented the method on the massively parallel architecture of the graphics processing unit (GPU). Experimental results show that our GPU implementation achieves faster-than real-time deblocking at 1309 frames per second for 1080p video pictures. Both software-based deblocking filters and state-of-the-art GPU-enabled algorithms are outperformed in terms of speed by factors up to 10.2 and 19.5, respectively, for 1080p video pictures.</P>

Mineral Nutrient Uptake, Distribution and Requirement of Higher Density Nectarine Trees (cv. Donnarine) under a Pulsing Drip System

Pieter J.C. Stassen,Graeme T. Krige 한국원예학회 2006 한국원예학회 기타간행물 Vol.- No.-

Apple Rootstock Research Progress in South Africa

Pieter J. C. Stassen,Carlo Costa 한국원예학회 2006 한국원예학회 기타간행물 Vol.- No.-

이차원 레이저 센서와 파티클 필터가 장착된 과원 로봇의 자율 항법 정확도 평가

( Pieter M. Blok ),( Koen Van Boheemen ),김국환 ( Gookhwan Kim ),이대현 ( Daehyun Lee ),홍영기 ( Youngki Hong ) 한국농업기계학회 2017 한국농업기계학회 학술발표논문집 Vol.22 No.2

과원에서 과실을 재배 할 때 직면하게 되는 어려움 중 하나는 효율적인 잡초 방제, 즉 제초 작업이다. 제초 작업은 종종 트랙터와 잔디 깎기 기계로 수행되는데 이 작업의 노동 집약적 특성으로 인해 그 빈도를 최소로 할 필요가 있다. 자율 주행이 가능한 로봇 플랫폼의 개발은 대규모 노동 투입 없이 정기적으로 과수원에서 잡초를 제거 할 수 있게 해준다. 과원 로봇의 설계에 있어 중요한 것은 장착되는 센서들을 활용하여 탐색 및 주행에 연관된 최적의 알고리즘 조합을 개발하여 수동 조종하는 현재의 제초 방법과 유사하거나 더 높은 항법 정확도를 제공해야 한다. 본 연구의 목적은 과원 로봇의 자율 항법을 위한 센서 및 알고리즘 조합의 최적화 및 정확성을 평가하여 신뢰성을 보고자 하였다. 자율 항법 알고리즘의 검증을 위한 테스트를 위한 로봇 플랫폼은 Clearpath Robotics사의 Husky A200로봇을 사용하였다. 이 로봇에는 장애물 및 과수열을 검출하기 위한 이차원 레이저 거리 센서(laser range finder, LRF), 로봇의 자세측정 및 데이터 보정을 위한 3축 관성측정장치(inertial measurement unit, IMU), 로봇의 주행 거리 및 속도를 추정하기 위한 바퀴 주행 측정기(odometry) 및 로봇의 자율 항법 알고리즘에 대한 정확도 검증을 위하여 고정도의 실시간 위성 항법 시스템(RTK-GNSS)가 장착되었다. 과수열 및 장애물 탐색 알고리즘은 파티클 필터(particle filter)를 기반으로 알고리즘을 구축하였다. 알고리즘 평가를 위한 실험은 네덜란드에 있는 사과 과원에서 수행하였다. 로봇에 적용한 파티클 필터 기반의 알고리즘 검증을 위하여 RTK-GNSS를 사용하여 정확한 로봇의 현재 위치를 파악하여 양 쪽에 심겨진 과수열을 따라 로봇이 얼마나 잘 추종하고 있는지를 기준 경로에 대한 편차 및 각도 편차를 계산하는 방식으로 수행하였다. 기준 경로와 비교하여 파티클 필터가 장착된 로봇은 속도가 0.25 m/s일 때, 평균 편차는 0.07 m, 평균 각도 편차는 2.57°였고, 0.5 m/s의 속도일 때는 0.08 m, 1.73°였다. 이차원 레이저 센서와 파티클 필터를 사용한 항법 알고리즘은 수동 조종하는 로봇의 대안으로 과원에서 과수열을 따라 자율 주행하는 것이 적합함을 입증하였다. 선회 구간 검출 및 장애물 회피는 이 연구에서 고려되지 않았으며 추후 개발되어 로봇에 탑재할 예정이다.

Automatic Sugar Beet Phenotyping in Open Field by a Computer Vision System

( Pieter M. Blok ),( Jochen Hemming ),( Youngki Hong ),( Jaesu Lee ),( Daehyun Lee ),( Gookhwan Kim ) 한국농업기계학회 2016 한국농업기계학회 학술발표논문집 Vol.21 No.2

Crop growth is an important quality assessment in plant breeding, especially in open field crops which grow in fluctuating and unfavorable outdoor conditions. To evaluate the growth potential of different plant varieties, researchers conduct leaf area measurements of emerged plants to evaluate its growth potential. This is a time consuming and labor intensive activity and therefore often only conducted on random spots on the field. An automatic computer vision system was built to automate and to speed up this plant phenotyping process. The system consist of three color cameras mounted on an implement facing straight downwards, lamps for illumination, an encoder wheel and a computer system. Natural light was blocked by a surrounding cover to limit the effect of variable outdoor light conditions on the image quality. The computer vision software makes use of an excessive green algorithm (2G - R - B) to segment the plant material from the soil. As the crop plants are sown by a precision sowing device in a regular pattern a method based on the fast-fourier transform (FFT) is used to distinguish crop plants from weed plants. A rectangular based clustering algorithm, based on 8-pixel nearest-neighbor connectivity, is used to cluster separated plant-parts together as one individual plant object used to measure the leaf area. The system was validated in an open-field sugar beet crop at the growing stage off our leaves. Fifty-five sugar beet plants were manually measured by experienced plant scouts(“ground truth”). The same plants were measured with the computer vision system. An ANOVA F-test(P<0.05) was used to discriminate the two measurement methods. The F-probability was 0.055 an djust above the significance level. So the H0 hypothesis that there is not a difference between human measurement and machine vision measurement was no trejected. Possible causes of difference was the inability of the system to detect and measure plants damaged by animals and very small plants which were occluded by clods or bigger plants. Nevertheless,with improvements on the vision software and camera/lamp configuration, the system is profitable for a fast and accurate leaf area measurement and corresponding plant phenotyping.