A Cost-Efficient NVM-Based Journaling Scheme for File Systems

The paper considers the modern university as an economic growth driver within the University 3.0 concept (education, research, and commercialization of knowledge). It demonstrates how the University 3.0 is becoming the basis for global competitiveness of national economies and international alliances, and how its business ecosystem generates new fast-growing industries, advanced technology markets and cost-efficient administrative territories.

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Unravelling a microbial synergy to boost caproate production via carboxylates chain elongation with ethanol

HKIE Transactions ◽

10.33430/v26n2thie-2018-0041 ◽

2019 ◽

Vol 26 (2) ◽

pp. 63-71

Author(s):

Ling Leng ◽

Ying Wang ◽

Peixian Yang ◽

Takashi Narihiro ◽

Masaru Konishi Nobu ◽

...

Keyword(s):

Fatty Acids ◽

Volatile Fatty Acids ◽

Microbial Consortia ◽

Chain Elongation ◽

Desulfovibrio Vulgaris ◽

Rrna Gene ◽

Selective Enrichment ◽

Microbial Network ◽

Cost Efficient ◽

Rrna Gene Sequencing

Chain elongation of volatile fatty acids for medium chain fatty acids production (e.g. caproate) is an attractive approach to treat wastewater anaerobically and recover resource simultaneously. Undefined microbial consortia can be tailored to achieve chain elongation process with selective enrichment from anaerobic digestion sludge, which has advantages over pure culture approach for cost-efficient application. Whilst the metabolic pathway of the dominant caproate producer, Clostridium kluyveri, has been annotated, the role of other coexisting abundant microbiomes remained unclear. To this end, an ethanol-acetate fermentation inoculated with fresh digestion sludge at optimal conditions was conducted. Also, physiological study, thermodynamics and 16 S rRNA gene sequencing to elucidate the biological process by linking the system performance and dominant microbiomes were integrated. Results revealed a possible synergistic network in which C. kluyveri and three co-dominant species, Desulfovibrio vulgaris, Fusobacterium varium and Acetoanaerobium sticklandii coexisted. D. vulgaris and A. sticklandii (F. varium) were likely to boost the carboxylates chain elongation by stimulating ethanol oxidation and butyrate production through a syntrophic partnership with hydrogen (H2) serving as an electron messenger. This study unveils a synergistic microbial network to boost caproate production in mixed culture carboxylates chain elongation.

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Out-of-autoclave Process and Automation: A Successful Path to Highly Integrated and Cost Efficient Composite Wing Moveables

10.33599/nasampe/s.19.1409 ◽

2019 ◽

Author(s):

Thibault de Lumley ◽

François Mathieu ◽

Didier Cornet ◽

Dimitri Gueuning ◽

Nicolas Van Hille

Keyword(s):

Autoclave Process ◽

Cost Efficient ◽

Out Of Autoclave ◽

Composite Wing

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Resource and cost efficient selective collection

Pollack Periodica ◽

10.1556/pollack.9.2014.s.5 ◽

2014 ◽

Vol 9 (Supplement 1) ◽

pp. 43-54 ◽

Cited By ~ 4

Author(s):

Csaba Leitol

Keyword(s):

Cost Efficient ◽

Selective Collection

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Cost-Efficient Design

10.1007/978-3-540-34648-7 ◽

2007 ◽

Cited By ~ 3

Keyword(s):

Efficient Design ◽

Cost Efficient

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An Adaptive Binarization Method for Cost-efficient Document Image System in Wavelet Domain

Journal of Imaging Science and Technology ◽

10.2352/j.imagingsci.technol.2020.64.3.030401 ◽

2020 ◽

Vol 64 (3) ◽

pp. 30401-1-30401-14 ◽

Cited By ~ 1

Author(s):

Chih-Hsien Hsia ◽

Ting-Yu Lin ◽

Jen-Shiun Chiang

Keyword(s):

Wavelet Transform ◽

Discrete Wavelet Transform ◽

Document Image ◽

Background Information ◽

Raspberry Pi ◽

Discrete Wavelet ◽

Image System ◽

Low Frequencies ◽

Cost Efficient ◽

Binarization Method

Abstract In recent years, the preservation of handwritten historical documents and scripts archived by digitized images has been gradually emphasized. However, the selection of different thicknesses of the paper for printing or writing is likely to make the content of the back page seep into the front page. In order to solve this, a cost-efficient document image system is proposed. In this system, the authors use Adaptive Directional Lifting-Based Discrete Wavelet Transform to transform image data from spatial domain to frequency domain and perform on high and low frequencies, respectively. For low frequencies, the authors use local threshold to remove most background information. For high frequencies, they use modified Least Mean Square training algorithm to produce a unique weighted mask and perform convolution on original frequency, respectively. Afterward, Inverse Adaptive Directional Lifting-Based Discrete Wavelet Transform is performed to reconstruct the four subband images to a resulting image with original size. Finally, a global binarization method, Otsu’s method, is applied to transform a gray scale image to a binary image as the output result. The results show that the difference in operation time of this work between a personal computer (PC) and Raspberry Pi is little. Therefore, the proposed cost-efficient document image system which performed on Raspberry Pi embedded platform has the same performance and obtains the same results as those performed on a PC.

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