scholarly journals Automated Wormscan

F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 192 ◽  
Author(s):  
Timothy Puckering ◽  
Jake Thompson ◽  
Sushruth Sathyamurthy ◽  
Sinduja Sukumar ◽  
Tirosh Shapira ◽  
...  
Keyword(s):  
Large Scale ◽  
Moving Objects ◽  
Low Cost ◽  
Automated System ◽  
Software Training ◽  
Robust Identification ◽  
Labour Costs ◽  
Difference Images ◽  
Rapid Data Acquisition

There has been a recent surge of interest in computer-aided rapid data acquisition to increase the potential throughput and reduce the labour costs of large scale Caenorhabditis elegans studies. We present Automated WormScan, a low-cost, high-throughput automated system using commercial photo scanners, which is extremely easy to implement and use, capable of scoring tens of thousands of organisms per hour with minimal operator input, and is scalable. The method does not rely on software training for image recognition, but uses the generation of difference images from sequential scans to identify moving objects. This approach results in robust identification of worms with little computational demand. We demonstrate the utility of the system by conducting toxicity, growth and fecundity assays, which demonstrate the consistency of our automated system, the quality of the data relative to manual scoring methods and congruity with previously published results.

scholarly journals Automated Wormscan

F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 192 ◽  
Author(s):  
Timothy Puckering ◽  
Jake Thompson ◽  
Sushruth Sathyamurthy ◽  
Sinduja Sukumar ◽  
Tirosh Shapira ◽  
...  
Keyword(s):  
Large Scale ◽  
Moving Objects ◽  
Low Cost ◽  
Automated System ◽  
Software Training ◽  
Robust Identification ◽  
Labour Costs ◽  
Difference Images ◽  
Rapid Data Acquisition

There has been a recent surge of interest in computer-aided rapid data acquisition to increase the potential throughput and reduce the labour costs of large scale Caenorhabditis elegans studies. We present Automated WormScan, a low-cost, high-throughput automated system using commercial photo scanners, which is extremely easy to implement and use, capable of scoring tens of thousands of organisms per hour with minimal operator input, and is scalable. The method does not rely on software training for image recognition, but uses the generation of difference images from sequential scans to identify moving objects. This approach results in robust identification of worms with little computational demand. We demonstrate the utility of the system by conducting toxicity, growth and fecundity assays, which demonstrate the consistency of our automated system, the quality of the data relative to manual scoring methods and congruity with previously published results.

scholarly journals Automated Wormscan

F1000Research ◽  
2019 ◽  
Vol 6 ◽  
pp. 192 ◽  
Author(s):  
Timothy Puckering ◽  
Jake Thompson ◽  
Sushruth Sathyamurthy ◽  
Sinduja Sukumar ◽  
Tirosh Shapira ◽  
...  
Keyword(s):  
Large Scale ◽  
Moving Objects ◽  
Low Cost ◽  
Automated System ◽  
Software Training ◽  
Robust Identification ◽  
Labour Costs ◽  
Difference Images ◽  
Rapid Data Acquisition

There has been a recent surge of interest in computer-aided rapid data acquisition to increase the potential throughput and reduce the labour costs of large scale Caenorhabditis elegans studies. We present Automated WormScan, a low-cost, high-throughput automated system using commercial photo scanners, which is extremely easy to implement and use, capable of scoring tens of thousands of organisms per hour with minimal operator input, and is scalable. The method does not rely on software training for image recognition, but uses the generation of difference images from sequential scans to identify moving objects. This approach results in robust identification of worms with little computational demand. We demonstrate the utility of the system by conducting toxicity, growth and fecundity assays, which demonstrate the consistency of our automated system, the quality of the data relative to manual scoring methods and congruity with previously published results.

Data Science and Knowledge Analytic Contexts on IoE Data for E-BI Application Case

2019 ◽  
pp. 100-126
Author(s):  
Nilamadhab Mishra
Keyword(s):  
Large Scale ◽  
Data Science ◽  
Low Cost ◽  
Edge Computing ◽  
The Other ◽  
High Quality ◽  
Main Research ◽  
Cognitive Values ◽  
Research Challenge

The progressive data science and knowledge analytic tasks are gaining popularity across various intellectual applications. The main research challenge is to obtain insight from large-scale IoE data that can be used to produce cognitive actuations for the applications. The time to insight is very slow, quality of insight is poor, and cost of insight is high; on the other hand, the intellectual applications require low cost, high quality, and real-time frameworks and algorithms to massively transform their data into cognitive values. In this chapter, the author would like to discuss the overall data science and knowledge analytic contexts on IoE data that are generated from smart edge computing devices. In an IoE-driven e-BI application, the e-consumers are using the smart edge computing devices from which a huge volume of IoE data are generated, and this creates research challenges to traditional data science and knowledge analytic mechanisms. The consumer-end IoE data are considered the potential sources to massively turn into the e-business goldmines.

Development of an Automatic Plant Monitoring System

2015 ◽  
Vol 1115 ◽  
pp. 458-461
Author(s):  
Moinul Bhuiyan ◽  
Tengku Muhammad Afif bin Tengku Azmi
Keyword(s):  
Monitoring System ◽  
Mobile Communication ◽  
Large Scale ◽  
Low Cost ◽  
Human Interaction ◽  
Automated System ◽  
Test Plant ◽  
Global System ◽  
Suitable Amount ◽  
Plant Monitoring

Automated system operates with less human interaction which reduces job overheads. This paper represents an automated plant monitoring system which could be applicable for practical plantation field in Malaysia to boost up the agricultural productions. The monitoring system, which is presented in this paper, uses three sensors to measure humidity, temperature, and moisture of the surroundings of the test plant and provides the most suitable amount of water to plant depending on the coefficient generated from the sensors’ data. Arduino Global System for Mobile Communication (GSM) Shield is also integrated with the system to monitor the process using mobile phone. Considering the reduction of environmental pollution, solar power system is used to power-up the designed monitoring system. Low cost and good results of practical experimentations present that the system is viable to implement in large scale plant monitoring and irrigation.

scholarly journals Assessing the impact of different grouping methods: time to rethink and regroup?

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Sean Randall ◽  
Anna Ferrante ◽  
Adrian Brown ◽  
James Boyd ◽  
James Semmens
Keyword(s):  
Record Linkage ◽  
Large Scale ◽  
Low Cost ◽  
Administrative Records ◽  
Grouping Strategy ◽  
Grouping Strategies ◽  
Linkage Quality ◽  
One To One ◽  
The Impact

ABSTRACT ObjectivesThe grouping of record-pairs to determine which administrative records belong to the same individual is an important process in record linkage. A variety of grouping methods are used but the relative benefits of each are unknown. We evaluate a number of grouping methods against the traditional merge based clustering approach using large scale administrative data. ApproachThe research aimed to both describe current grouping techniques used for record linkage, and to evaluate the most appropriate grouping method for specific circumstances. A range of grouping strategies were applied to three datasets with known truth sets. Conditions were simulated to appropriately investigate one-to-one, many-to-one and ongoing linkage scenarios. ResultsResults suggest alternate grouping methods will yield large benefits in linkage quality, especially when the quality of the underlying repository is high. Stepwise grouping methods were clearly superior for one-to-one linkage. There appeared little difference in linkage quality between many-to-one grouping approaches. The most appropriate techniques for ongoing linkage depended on the quality of the population spine and the underlying dataset. ConclusionsThese results demonstrate the large effect that the choice of grouping strategy can have on overall linkage quality. Ongoing linkages to high quality population spines provide large improvements in linkage quality compared to merge based linkages. Procuring or developing such a population spine will provide high linkage quality at far lower cost than current methods for improving linkage quality. By improving linkage quality at low cost, this resource can be further utilised by health researchers.

scholarly journals Cumulus: a cloud-based data analysis framework for large-scale single-cell and single-nucleus RNA-seq

2019 ◽  
Author(s):  
Bo Li ◽  
Joshua Gould ◽  
Yiming Yang ◽  
Siranush Sarkizova ◽  
Marcin Tabaka ◽  
...  
Keyword(s):  
Single Cell ◽  
Large Scale ◽  
Bone Marrow Cells ◽  
Low Cost ◽  
Data Generation ◽  
Rna Seq ◽  
User Friendliness ◽  
Health And Disease ◽  
Single Nucleus

AbstractMassively parallel single-cell and single-nucleus RNA-seq (sc/snRNA-seq) have opened the way to systematic tissue atlases in health and disease, but as the scale of data generation is growing, so does the need for computational pipelines for scaled analysis. Here, we developed Cumulus, a cloud-based framework for analyzing large scale sc/snRNA-seq datasets. Cumulus combines the power of cloud computing with improvements in algorithm implementations to achieve high scalability, low cost, user-friendliness, and integrated support for a comprehensive set of features. We benchmark Cumulus on the Human Cell Atlas Census of Immune Cells dataset of bone marrow cells and show that it substantially improves efficiency over conventional frameworks, while maintaining or improving the quality of results, enabling large-scale studies.

scholarly journals An Automation System for Controlling Streetlights and Monitoring Objects Using Arduino

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3178 ◽  
Author(s):  
Zain Mumtaz ◽  
Saleem Ullah ◽  
Zeeshan Ilyas ◽  
Naila Aslam ◽  
Shahid Iqbal ◽  
...  
Keyword(s):  
Large Scale ◽  
Low Cost ◽  
Automated System ◽  
Automation System ◽  
Infrared Sensors ◽  
Night Time ◽  
Require Time ◽  
The Road ◽  
Automation Systems ◽  
Objects Detection

We present an Arduino-based automation system to control the streetlights based on solar rays and object’s detection. We aim to design various systems to achieve the desired operations, which no longer require time-consuming manual switching of the streetlights. The proposed work is accomplished by using an Arduino microcontroller, a light dependent resistor (LDR) and infrared-sensors while, two main contributions are presented in this work. Firstly, we show that the streetlights can be controlled based on the night and object’s detection. In which the streetlights automatically turn to DIM state at night-time and turn to HIGH state on object’s detection, while during day-time the streetlights will remain OFF. Secondly, the proposed automated system is further extended to skip the DIM condition at night time, and streetlights turn ON based on the objects’ detection only. In addition, an automatic door system is introduced to improve the safety measurements, and most importantly, a counter is set that will count the number of objects passed through the road. The proposed systems are designed at lab-scale prototype to experimentally validate the efficiency, reliability, and low-cost of the systems. We remark that the proposed systems can be easily tested and implemented under real conditions at large-scale in the near future, that will be useful in the future applications for automation systems and smart homes.

scholarly journals An IoT-Based Services Infrastructure for Utility-Scale Distributed Solar Farms

Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 440
Author(s):  
Salsabeel Shapsough ◽  
Imran Zualkernan
Keyword(s):  
Large Scale ◽  
Smart Cities ◽  
Low Cost ◽  
Data Transport ◽  
Resource Monitoring ◽  
Efficient Resource ◽  
Networking Technologies ◽  
Edge Based ◽  
Utility Scale

Internet of Things (IoT) provides large-scale solutions for efficient resource monitoring and management. As such, the technology has been heavily integrated into domains such as manufacturing, healthcare, agriculture, and utilities, which led to the emergence of sustainable smart cities. The success of smart cities depends on the availability of data, as well as the quality of the data management infrastructure. IoT introduced numerous new software, hardware, and networking technologies designed for efficient and low-cost data transport, storage, and processing. However, proper selection and integration of the correct technologies is crucial to ensuring a positive return on investment for such systems. This paper presents a novel end-to-end infrastructure for solar energy analysis and prediction via edge-based analytics.

scholarly journals Biosorption of Water Pollutants by Fungal Pellets

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 1155 ◽  
Author(s):  
Adriana Legorreta-Castañeda ◽  
Carlos Lucho-Constantino ◽  
Rosa Beltrán-Hernández ◽  
Claudia Coronel-Olivares ◽  
Gabriela Vázquez-Rodríguez
Keyword(s):  
Large Scale ◽  
High Efficiency ◽  
Low Cost ◽  
Fungal Cell ◽  
Water Pollutants ◽  
Operational Conditions ◽  
Fungal Pellets ◽  
Water And Wastewater ◽  
Real Wastewater

Fungal biosorption is an environmental biotechnology based on the ability of the fungal cell wall to concentrate harmful water pollutants. Among its advantages are its simplicity, high efficiency, flexibility of operation, and low cost. The biosorptive performance of fungal pellets is getting growing attention since they offer process advantages over the culture of disperse mycelia, such as an enhanced biomass separation, and a high resilience in severe environmental conditions. In this review, biosorption capacity of fungal pellets towards heavy metals, dyes, phenolic compounds, humic substances, pesticides, and pharmaceuticals was reviewed. Available data about the adsorption capacity of pellets, their removal efficiency, and the operational conditions used were collected and synthesized. The studies relying on biodegradation were discarded to present only the possibilities of fungal pellets for removing these concern pollutants through biosorption. It was found that the biosorption of complex mixtures of pollutants on fungal pellets is scarcely studied, as well as the interfering effect of anions commonly found in water and wastewater. Furthermore, there is a lack of research with real wastewater and at pilot and large scale. These topics need to be further explored to take full advantage of fungal pellets on improving the quality of aquatic systems.

Effect of Computerized Auditory Training on Speech Perception of Adults With Hearing Impairment

2013 ◽  
Vol 20 (3) ◽  
pp. 91-106 ◽  
Author(s):  
Rachel Pizarek ◽  
Valeriy Shafiro ◽  
Patricia McCarthy
Keyword(s):  
Hearing Loss ◽  
Speech Perception ◽  
Literature Review ◽  
Low Cost ◽  
Experimental Designs ◽  
Auditory Training ◽  
Hearing Impairments ◽  
Communicative Disorders ◽  
And Training

Computerized auditory training (CAT) is a convenient, low-cost approach to improving communication of individuals with hearing loss or other communicative disorders. A number of CAT programs are being marketed to patients and audiologists. The present literature review is an examination of evidence for the effectiveness of CAT in improving speech perception in adults with hearing impairments. Six current CAT programs, used in 9 published studies, were reviewed. In all 9 studies, some benefit of CAT for speech perception was demonstrated. Although these results are encouraging, the overall quality of available evidence remains low, and many programs currently on the market have not yet been evaluated. Thus, caution is needed when selecting CAT programs for specific patients. It is hoped that future researchers will (a) examine a greater number of CAT programs using more rigorous experimental designs, (b) determine which program features and training regimens are most effective, and (c) indicate which patients may benefit from CAT the most.

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