Dynamic Web-Page Generation in Resource-Constrained Environments The Kertasarie Server Pages

2008 ◽  
Author(s):  
Christian Hochberger ◽  
Christian Meusel
2021 ◽  
Vol 27 (1) ◽  
Author(s):  
J. M. Lazarus ◽  
M. Ncube

Abstract Background Technology currently used for surgical endoscopy was developed and is manufactured in high-income economies. The cost of this equipment makes technology transfer to resource constrained environments difficult. We aimed to design an affordable wireless endoscope to aid visualisation during rigid endoscopy and minimally invasive surgery (MIS). The initial prototype aimed to replicate a 4-mm lens used in rigid cystoscopy. Methods Focus was placed on using open-source resources to develop the wireless endoscope to significantly lower the cost and make the device accessible for resource-constrained settings. An off the shelf miniature single-board computer module was used because of its low cost (US$10) and its ability to handle high-definition (720p) video. Open-source Linux software made monitor mode (“hotspot”) wireless video transmission possible. A 1280 × 720 pixel high-definition tube camera was used to generate the video signal. Video is transmitted to a standard laptop computer for display. Bench testing included latency of wireless digital video transmission. Comparison to industry standard wired cameras was made including weight and cost. The battery life was also assessed. Results In comparison with industry standard cystoscope lens, wired camera, video processing unit and light source, the prototype costs substantially less. (US$ 230 vs 28 000). The prototype is light weight (184 g), has no cables tethering and has acceptable battery life (of over 2 h, using a 1200 mAh battery). The camera transmits video wirelessly in near real time with only imperceptible latency of < 200 ms. Image quality is high definition at 30 frames per second. Colour rendering is good, and white balancing is possible. Limitations include the lack of a zoom. Conclusion The novel wireless endoscope camera described here offers equivalent high-definition video at a markedly reduced cost to contemporary industry wired units and could contribute to making minimally invasive surgery possible in resource-constrained environments.


2018 ◽  
Vol 4 (3) ◽  
pp. 137-155 ◽  
Author(s):  
Sajid Nazir ◽  
Hassan Hamdoun ◽  
Fabio Verdicchio ◽  
Gorry Fairhurst

2012 ◽  
Vol 241-244 ◽  
pp. 2779-2782
Author(s):  
Heng Yao Tang ◽  
Xiao Yan Zhan

On the problems existing in the realization of current accessibility website, we design a web designing architecture, using the web log mining technique to extract user interests and access priority sequence and adopting the dynamic web page information to fill the web page commonly used structure, realize the intelligent , personalized accessibility.


Author(s):  
Yang Carl Lu ◽  
Holly Krambeck ◽  
Liang Tang

Deployment of an adaptive area traffic control system is expensive; physical sensors require installation, calibration, and regular maintenance. Because of the high level of technical and financial resources required, area traffic control systems found in developing countries often are minimally functioning. In Cebu City, Philippines, for example, the Sydney Coordinated Adaptive Traffic System was installed before 2000, and fewer than 35% of detectors were still functioning as of January 2015. To address this challenge, a study was designed to determine whether taxi company GPS data are sufficient to evaluate and improve traffic signal timing plans in resource-constrained environments. If this work is successful, the number of physical sensors required to support those systems may be reduced and thereby substantially lower the costs of installation and maintenance. Taxi GPS data provided by a regional taxi-hailing app were used to design and implement methodologies for evaluating the performance of traffic signal timing plans and for deriving updated fixed-dynamic plans, which are fixed plans (with periods based on observable congestion patterns rather than only time of day) iterated regularly until optimization is reached. To date, three rounds of iterations have been conducted to ensure the stability of the proposed signal timings. Results of exploratory analysis indicate that the algorithm is capable of generating reasonable green time splits, but cycle length adjustment must be considered in the future.


2002 ◽  
Vol 13 (04) ◽  
pp. 521-530 ◽  
Author(s):  
WEN GAO ◽  
SHI WANG ◽  
BIN LIU

This paper presents a new real-time, dynamic web page recommendation system based on web-log mining. The visit sequences of previous visitors are used to train a classifier for web page recommendation. The recommendation engine identifies a current active user, and submits its visit sequence as an input to the classifier. The output of the recommendation engine is a set of recommended web pages, whose links are attached to bottom of the requested page. Our experiments show that the proposed approach is effective: the predictive accuracy is quite high (over 90%), and the time for the recommendation is quite small.


2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Cheng-Jian Lin ◽  
Chun-Hui Lin ◽  
Shyh-Hau Wang

Deep learning has accomplished huge success in computer vision applications such as self-driving vehicles, facial recognition, and controlling robots. A growing need for deploying systems on resource-limited or resource-constrained environments such as smart cameras, autonomous vehicles, robots, smartphones, and smart wearable devices drives one of the current mainstream developments of convolutional neural networks: reducing model complexity but maintaining fine accuracy. In this study, the proposed efficient light convolutional neural network (ELNet) comprises three convolutional modules which perform ELNet using fewer computations, which is able to be implemented in resource-constrained hardware equipment. The classification task using CIFAR-10 and CIFAR-100 datasets was used to verify the model performance. According to the experimental results, ELNet reached 92.3% and 69%, respectively, in CIFAR-10 and CIFAR-100 datasets; moreover, ELNet effectively lowered the computational complexity and parameters required in comparison with other CNN architectures.


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