Sirindhorn International Institute of Technology

About: Sirindhorn International Institute of Technology is a based out in . It is known for research contribution in the topics: Supply chain & Combustion. The organization has 1048 authors who have published 1678 publications receiving 30067 citations.

Implementing e-tendering to improve the efficiency of public construction contract in Saudi Arabia

Abstract: The demand from the construction industry for paperless business processes has increased the use of e-tendering systems around the world. E-tendering systems are quite complex since they involve many stages to meet the need of construction sectors. This paper developed an e-tendering model the public construction contract in Saudi Arabia to improve its efficiency with addresses the dilemma of traditional tendering. Moreover, to assist the development of the proposed e-tendering model, literature review, ten interviews, a focus group, and 52 questionnaire participants are conducted. Therefore, the model allows a contractor to be involved during the design stage and involved officially during the design process. This feature seeks to minimise the pre-construction time, reduce the bidder's risks and maximise the quality and transparency of e-tendering. As a result, this paper identified the stage of tender document handling to the bidders is the most affected stage toward more efficient of e-tendering process.

Bioelectricity Generation in Plant Microbial Fuel Cell Using Forage Grass under Variations of Circadian Rhythm, Ambient Temperature, and Soil Water Contents

Abstract: Plant microbial fuel cell (PMFC) is an intriguing and sustainable technology which can spontaneously generate electricity from biodegradable materials excreted through plant roots in rhizosphere by electroactive microbes. In this study, experiments were conducted to determine the effects of soil water contents, temperature fluctuations, and circadian rhythm on current and power densities of PMFCs using Purple guinea grass. Three PMFC systems were investigated including dry-soil, wet-soil, and waterlog PMFC under greenhouse temperature of 27 – 47°C. Plants cultivation in waterlog were found to deliver a better performance as compared to the others with power density of 10.13 mW/m2of anode area. Wet soil and arid soil provided power densities of 6.7 and 2.3 mW/ m2, respectively. Soil water contents and temperature were found to have a substantial role in controlling the system performance. In account for temperature variations during the period of study, average power densities of 4.4, 5.9, and 6.0 mW/m2were obtained at a high temperature range between 41 °C to 47 °C for dry-, wet- and waterlog-soil, respectively. Within the intermediate temperature range of 34 °C to 41 °C, the obtained power densities were 1.0, 1.7, and 1.9 mW/m2while 0.3, 0.4, and 0.6 mW/m2were attained for a low temperature range of 27 °C – 34 °C for dry-, wet- and waterlog soil, respectively. The lower performance during low temperature were attributed to the electroactive bacteria activities in anode and the carbohydrate metabolism of plants. The power and current outputs during photo-period were much higher than at night. These outcomes authenticated that PMFCs are significantly affected by soil water contents, ambient temperatures, and photosynthesis.

Camera operation estimation from video shot using 2D motion vector histogram

Abstract: This paper presents a novel technique for classifying several camera operations in videos. First of all, we obtain a series of 2D motion vector (MV) fields by applying an existing MV estimation method. Then, a 2D MV histogram is generated in polar coordinates. The histogram shows that how many MVs in each frame share the similar magnitude and orientation. These two MV features are utilized simultaneously to classify the camera operations by representing on the 2D histogram. The proposed method can detect not only single camera operations but also a combination of two camera operations. The 2D histogram can describe the speed of the camera operations. Moreover, the 2D MV field itself can separate zoom-in and zoom-out camera operations that may produce exactly the same pattern in the 2D MV histogram. Especially, separating zoom-in and zoom-out camera operations because these two operations produce a similar 2D histogram. The proposed method can achieve a processing time of 5-10 millisecond per frame for a low-resolution video, while it takes 40-80 millisecond for a high-resolution video.