• Journal of Construction Engineering and Project Management
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• v.9 no.2
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• pp.1-24
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• 2019

Poor project performance has been noted as the bane in the construction industry globally. This paper sought to investigate, by way of literature, the performance patterns of construction projects in Kenya since independence (1963-2018). This was informed by reports of undesirable project performance in the industry. This descriptive study used available studies previously done in this subject area. In sum, literature is replete with evidence on a myriad of challenges facing the execution of projects. The study established that generally, the project performance is poor and has assumed a chronic trajectory spanning over five decades. On average, the findings reveal that 35-60% of projects initiated in Kenya face cost overruns while time overrun is most severe with 35-73% projects overrunning their schedule. In addition, the findings problematize the issue of plurality of performance measurement regimes in the construction industry. Here, it was observed that no singular construct exists to objectively measure the various facets that constitute the 'health' of a project. This paper has contributed to the body of knowledge by examining the performance patterns in Kenya for over fifty years while at the same time identifying the bottlenecks inherent in projects execution. Importantly, the conceptual performance efficiency framework derived in the current study presents a paradigm shift in the monitoring and evaluation of projects. To this end, an in-depth analysis is recommended on the interaction of efficiency enablers in the buildup of performance efficiency index (PEI). Similarly, a further inquiry is recommended on the integration and impact of the proposed framework in the management of projects.

• Journal of Biomedical Engineering Research
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• v.25 no.6
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• pp.565-573
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• 2004

In this paper, we proposed a heart activity control model for simulation of the aortic sinus baroreceptor, which was the most representative baroreceptor sensing the variance of pressure in the cardiovascular system. And then, the heart activity control model composed electric circuit model of the cardiovascular system with baroreflex control and time delay sub-model to observe the effect of time delay in heart period and stroke volume under the regulation of baroreflex in the aortic sinus. The mechanism of time delay in the heart activity baroreflex control model is as follows. A control function is conduct sensing pressure information in the aortic sinus baroreceptor to transmit the efferent nerve through central nervous system. As simulation results of the proposed model, we observed three patterns of the cardiovascular system variability by the time delay. First of all, if the time delay over 2.5 second, aortic pressure and stroke volume and heart rate was observed non-periodically and irregularly. However, if the time delay from 0.1 second to 0.25 second, the regular oscillation was observed. And then, if time delay under 0.1 second, then heart rate and aortic pressure-heart rate trajectory were maintained in stable state.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.251-264
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• 2008

One of the crucial elements to fully facilitate the various benefits of intelligent transportation systems (ITS) is to obtain more reliable traffic monitoring in real time. To date, point and section-based traffic measurements have been available through existing surveillance technologies, such as loops and automatic vehicle identification (AVI) systems. However, seamless and more reliable traffic data are required for more effective traffic information provision and operations. Technology advancements including vehicle tracking and wireless communication enable the acceleration of the availability of individual vehicle travel information. This study presents a UBIquitous PRObe vehicle Surveillance System (UBIPROSS) using vehicle-to-vehicle (V2V) wireless communications. Seamless vehicle travel information, including origin-destination information, speed, travel times, and other data, can be obtained by the proposed UBIPROSS. A set of parameters associated with functional requirements of the UBIPROSS, which include the market penetration rate (MPR) of equipped vehicles, V2V communication range, and travel time update interval, are investigated by a Monte Carlo simulation- (MCS) based evaluation framework. In addition, this paper describes prototypical implementation. Field test results and identified technical issues are also discussed. It is expected that the proposed system would be an invaluable precursor to develop a next-generation traffic surveillance system.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1015-1023
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• 2022

The Entry-Descent-Landing process of a lander involves many environmental and technical challenges. To solve these problems, recently, terrestrial relative navigation (TRN) technology has been essential for landers. TRN is a technology for estimating the position and attitude of a lander by comparing Inertial Measurement Unit (IMU) data and image data collected from a descending lander with pre-built reference data. In this paper, we present a method for generating descent dataset and extracting landmarks, which are key elements for developing TRN technologies to be used on Mars. The proposed method generates IMU data of a descending lander using a simulated Mars landing trajectory and generates descent images from high-resolution ortho-map and digital elevation map through a ray tracing technique. Landmark extraction is performed by an area-based extraction method due to the low-textured surfaces on Mars. In addition, search area reduction is carried out to improve matching accuracy and speed. The performance evaluation result for the descent dataset generation method showed that the proposed method can generate images that satisfy the imaging geometry. The performance evaluation result for the landmark extraction method showed that the proposed method ensures several meters of positioning accuracy while ensuring processing speed as fast as the feature-based methods.