Design of a Remote Wireless Surveillance System Based on 3G

2012 ◽  
Vol 532-533 ◽  
pp. 606-609
Author(s):  
Bai Yan Hu ◽  
Zong Wu Ke ◽  
Lin Huang ◽  
Chong Wen Wang
Keyword(s):  
Data Transmission ◽  
Surveillance System ◽  
Large Scale ◽  
High Efficiency ◽  
High Quality ◽  
Image Capture ◽  
Front End ◽  
Large Scale Project

The remote wireless surveillance system based on 3G consist of the front-end image capture module, data transmission module, and the back-end monitoring part. The basis elements of the system and the principle is discussed .The system of software and the hardware is introduced. The system is high-compressed, of high quality ,easily wiring, and of high efficiency. The best use of the system is to surveillance the complicated enviroment of a large scale project.

scholarly journals An Automated Sample Preparation System for Large-Scale DNA Sequencing

1999 ◽  
Vol 9 (5) ◽  
pp. 457-462 ◽  
Author(s):  
Andre Marziali ◽  
Thomas D. Willis ◽  
Nancy A. Federspiel ◽  
Ronald W. Davis
Keyword(s):  
Sample Preparation ◽  
Dna Sequencing ◽  
High Throughput ◽  
Large Scale ◽  
Low Cost ◽  
High Quality ◽  
Dna Templates ◽  
Sequencing Technologies ◽  
Front End ◽  
Automated Sample Preparation

Recent advances in DNA sequencing technologies, both in the form of high lane-density gels and automated capillary systems, will lead to an increased requirement for sample preparation systems that operate at low cost and high throughput. As part of the development of a fully automated sequencing system, we have developed an automated subsystem capable of producing 10,000 sequence-ready ssDNA templates per day from libraries of M13 plaques at a cost of $0.29 per sample. This Front End has been in high throughput operation since June, 1997 and has produced > 400,000 high-quality DNA templates.

The Potential of Photoelectrochemical Carbon Sinks

2018 ◽  
Author(s):  
Matthias May ◽  
Kira Rehfeld
Keyword(s):  
Global Warming ◽  
High Temperature ◽  
Greenhouse Gas ◽  
Large Scale ◽  
High Efficiency ◽  
Carbon Sink ◽  
Solar Fuels ◽  
Negative Emissions ◽  
Viable Approach ◽  
Low Sensitivity

Greenhouse gas emissions must be cut to limit global warming to 1.5-2C above preindustrial levels. Yet the rate of decarbonisation is currently too low to achieve this. Policy-relevant scenarios therefore rely on the permanent removal of CO<sub>2</sub> from the atmosphere. However, none of the envisaged technologies has demonstrated scalability to the decarbonization targets for the year 2050. In this analysis, we show that artificial photosynthesis for CO<sub>2</sub> reduction may deliver an efficient large-scale carbon sink. This technology is mainly developed towards solar fuels and its potential for negative emissions has been largely overlooked. With high efficiency and low sensitivity to high temperature and illumination conditions, it could, if developed towards a mature technology, present a viable approach to fill the gap in the negative emissions budget.<br>

The Potential of Photoelectrochemical Carbon Sinks

2018 ◽  
Author(s):  
Matthias May ◽  
Kira Rehfeld
Keyword(s):  
Global Warming ◽  
High Temperature ◽  
Greenhouse Gas ◽  
Large Scale ◽  
High Efficiency ◽  
Carbon Sink ◽  
Solar Fuels ◽  
Negative Emissions ◽  
Viable Approach ◽  
Low Sensitivity

Greenhouse gas emissions must be cut to limit global warming to 1.5-2C above preindustrial levels. Yet the rate of decarbonisation is currently too low to achieve this. Policy-relevant scenarios therefore rely on the permanent removal of CO<sub>2</sub> from the atmosphere. However, none of the envisaged technologies has demonstrated scalability to the decarbonization targets for the year 2050. In this analysis, we show that artificial photosynthesis for CO<sub>2</sub> reduction may deliver an efficient large-scale carbon sink. This technology is mainly developed towards solar fuels and its potential for negative emissions has been largely overlooked. With high efficiency and low sensitivity to high temperature and illumination conditions, it could, if developed towards a mature technology, present a viable approach to fill the gap in the negative emissions budget.<br>

Peculiarities of the phytosanitary state of pome fruits in industrial horticulture

2020 ◽  
Vol 60 (1) ◽  
pp. 159-168
Author(s):  
V. V. Antonenko ◽  
A. V. Zubkov ◽  
S. N. Kruchina
Keyword(s):  
Mechanism Of Action ◽  
Large Scale ◽  
High Efficiency ◽  
Fruit Trees ◽  
Fruit Crops ◽  
Planting Material ◽  
Relative Safety ◽  
Pome Fruits ◽  
Weed Plants ◽  
Spread Of Infection

Data were obtained on the basis of the results of research carried out on the territory of the educational and experimental farm of the Timiryazev State Agrarian University, in Moscow during 2018-2019. As a result of the surveys, the most dangerous diseases and pests of pome crops on the territory of this farm were established. The most resistant apple and pear varieties to major diseases have been identified. Peculiarities of development of alternariosis on pear are described, the harmfulness of the disease on pear and apple seedlings is noted. A possible role in the transfer of alternariosis infection from garden-protective plantations and weed vegetation to fruit trees was noted. A possible role has been established in the transport of septoriosis, powdery dew infection from dicotyledonous weeds plants. The peculiarities of the spread of infection under the influence of wind direction are noted. The results and peculiarities of the application of various methods of scaring birds in the orchard are presented. As a result of route surveys the most harmful weed plants have been identified. The possibility of using herbicides of different mechanism of action in fruit gardens for weed control has been studied. High efficiency and relative safety of application of herbicides of contact action in nursery fields, operational orchards and for control of piglets on fruit trees are shown. Recommendations are given for the use of soil and systemic herbicides of soil in seedlings beds, the first and second fields of the nursery, as well as in the process of production of large-scale planting material and operational orchards of fruit crops. The safety of the herbicides in question is established when used in accordance with the recommended methods of use.

scholarly journals Functionalization of Congo red dye as a light harvester on solar cell

2020 ◽  
Vol 18 (1) ◽  
pp. 287-294
Author(s):  
Harsasi Setyawati ◽  
Handoko Darmokoesoemo ◽  
Irmina Kris Murwani ◽  
Ahmadi Jaya Permana ◽  
Faidur Rochman
Keyword(s):  
Solar Cell ◽  
Congo Red ◽  
Large Scale ◽  
High Efficiency ◽  
Solar Cell Device ◽  
Dye Sensitized ◽  
Congo Red Dye ◽  
Elemental Analyses ◽  
Red Dye ◽  
Solar Cell Technology

AbstractThe demands of ecofriendly technologies to produce a reliable supply of renewable energy on a large scale remains a challenge. A solar cell based on DSSC (Dye-Sensitized Solar Cell) technology is environmentally friendly and holds the promise of a high efficiency in converting sunlight into electricity. This manuscript describes the development of a light harvester system as a main part of a DSSC. Congo red dye has been functionalized with metals (Fe, Co, Ni), forming a series of complexes that serve as a novel light harvester on the solar cell. Metal-congo red complexes have been characterized by UV-VIS and FTIR spectroscopy, and elemental analyses. The performance of metal complexes in capturing photons from sunlight has been investigated in a solar cell device. The incorporation of metals to congo red successfully improved of the congo red efficiency as follows: Fe(II)-congo red, Co(II)-congo red and Ni(II)-congo red had efficiencies of 8.17%, 6.13% and 2.65%, respectively. This research also discusses the effect of metal ions on the ability of congo red to capture energy from sunlight.

scholarly journals Amalgamation of cloud-based colonoscopy videos with patient-level metadata to facilitate large-scale machine learning

2021 ◽  
Vol 09 (02) ◽  
pp. E233-E238
Author(s):  
Rajesh N. Keswani ◽  
Daniel Byrd ◽  
Florencia Garcia Vicente ◽  
J. Alex Heller ◽  
Matthew Klug ◽  
...  
Keyword(s):  
Machine Learning ◽  
Large Scale ◽  
Medical Center ◽  
Academic Medical Center ◽  
Procedure Time ◽  
Image Capture ◽  
Common Procedure ◽  
Patient Level Data ◽  
Patient Level ◽  
Level Data

Abstract Background and study aims Storage of full-length endoscopic procedures is becoming increasingly popular. To facilitate large-scale machine learning (ML) focused on clinical outcomes, these videos must be merged with the patient-level data in the electronic health record (EHR). Our aim was to present a method of accurately linking patient-level EHR data with cloud stored colonoscopy videos. Methods This study was conducted at a single academic medical center. Most procedure videos are automatically uploaded to the cloud server but are identified only by procedure time and procedure room. We developed and then tested an algorithm to match recorded videos with corresponding exams in the EHR based upon procedure time and room and subsequently extract frames of interest. Results Among 28,611 total colonoscopies performed over the study period, 21,170 colonoscopy videos in 20,420 unique patients (54.2 % male, median age 58) were matched to EHR data. Of 100 randomly sampled videos, appropriate matching was manually confirmed in all. In total, these videos represented 489,721 minutes of colonoscopy performed by 50 endoscopists (median 214 colonoscopies per endoscopist). The most common procedure indications were polyp screening (47.3 %), surveillance (28.9 %) and inflammatory bowel disease (9.4 %). From these videos, we extracted procedure highlights (identified by image capture; mean 8.5 per colonoscopy) and surrounding frames. Conclusions We report the successful merging of a large database of endoscopy videos stored with limited identifiers to rich patient-level data in a highly accurate manner. This technique facilitates the development of ML algorithms based upon relevant patient outcomes.

Tiered Sampling

2021 ◽  
Vol 15 (5) ◽  
pp. 1-52
Author(s):  
Lorenzo De Stefani ◽  
Erisa Terolli ◽  
Eli Upfal
Keyword(s):  
Large Scale ◽  
Analysis Of Algorithms ◽  
Base Layer ◽  
Single Edge ◽  
Real World Data ◽  
High Quality ◽  
Large Graphs ◽  
Massive Graphs ◽  
Variance Estimate ◽  
Low Probability

We introduce Tiered Sampling , a novel technique for estimating the count of sparse motifs in massive graphs whose edges are observed in a stream. Our technique requires only a single pass on the data and uses a memory of fixed size M , which can be magnitudes smaller than the number of edges. Our methods address the challenging task of counting sparse motifs—sub-graph patterns—that have a low probability of appearing in a sample of M edges in the graph, which is the maximum amount of data available to the algorithms in each step. To obtain an unbiased and low variance estimate of the count, we partition the available memory into tiers (layers) of reservoir samples. While the base layer is a standard reservoir sample of edges, other layers are reservoir samples of sub-structures of the desired motif. By storing more frequent sub-structures of the motif, we increase the probability of detecting an occurrence of the sparse motif we are counting, thus decreasing the variance and error of the estimate. While we focus on the designing and analysis of algorithms for counting 4-cliques, we present a method which allows generalizing Tiered Sampling to obtain high-quality estimates for the number of occurrence of any sub-graph of interest, while reducing the analysis effort due to specific properties of the pattern of interest. We present a complete analytical analysis and extensive experimental evaluation of our proposed method using both synthetic and real-world data. Our results demonstrate the advantage of our method in obtaining high-quality approximations for the number of 4 and 5-cliques for large graphs using a very limited amount of memory, significantly outperforming the single edge sample approach for counting sparse motifs in large scale graphs.

scholarly journals An Underwater Image Enhancement Algorithm Based on Generative Adversarial Network and Natural Image Quality Evaluation Index

2021 ◽  
Vol 9 (7) ◽  
pp. 691
Author(s):  
Kai Hu ◽  
Yanwen Zhang ◽  
Chenghang Weng ◽  
Pengsheng Wang ◽  
Zhiliang Deng ◽  
...  
Keyword(s):  
Image Quality ◽  
Image Enhancement ◽  
Quality Evaluation ◽  
High Efficiency ◽  
Natural Image ◽  
High Quality ◽  
Generative Adversarial Network ◽  
Image Quality Evaluation ◽  
Adversarial Network ◽  
Underwater Image

When underwater vehicles work, underwater images are often absorbed by light and scattered and diffused by floating objects, which leads to the degradation of underwater images. The generative adversarial network (GAN) is widely used in underwater image enhancement tasks because it can complete image-style conversions with high efficiency and high quality. Although the GAN converts low-quality underwater images into high-quality underwater images (truth images), the dataset of truth images also affects high-quality underwater images. However, an underwater truth image lacks underwater image enhancement, which leads to a poor effect of the generated image. Thus, this paper proposes to add the natural image quality evaluation (NIQE) index to the GAN to provide generated images with higher contrast and make them more in line with the perception of the human eye, and at the same time, grant generated images a better effect than the truth images set by the existing dataset. In this paper, several groups of experiments are compared, and through the subjective evaluation and objective evaluation indicators, it is verified that the enhanced image of this algorithm is better than the truth image set by the existing dataset.

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