PSX-A-1 Late-Breaking: A fully automated system for 3D image acquisition, classification and processing for real-time monitoring growth of finishing cattle in feedlots

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 364-364
Author(s):  
Joseane Padilha ◽  
Arthur Fernandes ◽  
Joao R Dorea ◽  
Tiago S Acedo ◽  
Guilherme J Rosa
Keyword(s):  
Body Weight ◽  
Real Time ◽  
Assessment Tool ◽  
Animal Movement ◽  
Automated System ◽  
Water Tank ◽  
Animal Body ◽  
Biological Features ◽  
Central Computer ◽  
Straight Position

Abstract Computer vision has been proposed as an alternative to monitor livestock growth, for example using 3D cameras to estimate body weight and condition. However, implementing this technology outdoors and with unrestrained animals poses a great challenge, because of harsh conditions for the equipment, as well as varying lighting and animal movement. Here we propose an automated system to acquire 3D images of individual animals, integrate the animal ID in the image file, and process images. This comprises a fundamental step for implementing a real-time assessment tool of growth of animals grouped in pens, to aid optimal feed management and marketing decision. The study comprised 50 beef cattle of Nellore breed during a finishing phase at DSM Innovation and Applied Center, in Brazil. Animals were tagged with RFID eartags, and 5 Intel RealSense D435 cameras were installed on the top of the water sources in each pen. For each animal approaching the water tank, an RFID antenna read the animal ID and triggered the camera to acquire a top-down view image. Images were then sent to a central computer using Wi-Fi, and later to the cloud. A decision tree algorithm was trained to sort images as usable or unusable, where the retained images had one single animal on the frame, with full body and relatively straight position. Selected frames were then processed using a threshold Otsu’s method to segment the animal body and obtain the necessary biological features, including body length, multiple width and height values, body area and volume. A total of 16,000+ images were collected, from which 3,100 were deemed usable. The algorithm successfully extracted the animal body from each image and obtained the biological features (cross-correlation values above 0.90). The proposed system was demonstrated to be extremely promising and the next stage of the study will be devoted to individual body weight prediction.

A real-time automated system for monitoring individual feed intake and body weight of group housed turkeys

2011 ◽  
Vol 75 (2) ◽  
pp. 313-320 ◽  
Author(s):  
Xuyong Tu ◽  
Shuxin Du ◽  
Lie Tang ◽  
Hongwei Xin ◽  
Ben Wood
Keyword(s):  
Body Weight ◽  
Real Time ◽  
Feed Intake ◽  
Automated System

Near-Perfect Automation: Investigating Performance, Trust, and Visual Attention Allocation

2021 ◽  
pp. 001872082110328
Author(s):  
Cyrus K. Foroughi ◽  
Shannon Devlin ◽  
Richard Pak ◽  
Noelle L. Brown ◽  
Ciara Sibley ◽  
...  
Keyword(s):  
Visual Attention ◽  
False Alarm ◽  
Real Time ◽  
Subjective Experience ◽  
Automated System ◽  
Automated Systems ◽  
High Stakes ◽  
Individual Level ◽  
Scan Pattern ◽  
Subjective Trust

Objective Assess performance, trust, and visual attention during the monitoring of a near-perfect automated system. Background Research rarely attempts to assess performance, trust, and visual attention in near-perfect automated systems even though they will be relied on in high-stakes environments. Methods Seventy-three participants completed a 40-min supervisory control task where they monitored three search feeds. All search feeds were 100% reliable with the exception of two automation failures: one miss and one false alarm. Eye-tracking and subjective trust data were collected. Results Thirty-four percent of participants correctly identified the automation miss, and 67% correctly identified the automation false alarm. Subjective trust increased when participants did not detect the automation failures and decreased when they did. Participants who detected the false alarm had a more complex scan pattern in the 2 min centered around the automation failure compared with those who did not. Additionally, those who detected the failures had longer dwell times in and transitioned to the center sensor feed significantly more often. Conclusion Not only does this work highlight the limitations of the human when monitoring near-perfect automated systems, it begins to quantify the subjective experience and attentional cost of the human. It further emphasizes the need to (1) reevaluate the role of the operator in future high-stakes environments and (2) understand the human on an individual level and actively design for the given individual when working with near-perfect automated systems. Application Multiple operator-level measures should be collected in real-time in order to monitor an operator’s state and leverage real-time, individualized assistance.

scholarly journals Body composition and net and dietary macrominerals requirements of Nellore steers under grazing

2009 ◽  
Vol 38 (6) ◽  
pp. 1081-1087 ◽  
Author(s):  
Vitor Visintin Silva de Almeida ◽  
Augusto César de Queiroz ◽  
Robério Rodrigues Silva ◽  
Fabiano Ferreira da Silva ◽  
Aline Cardoso Oliveira ◽  
...  
Keyword(s):  
Body Weight ◽  
Reference Group ◽  
Average Daily Gain ◽  
The Body ◽  
Regression Equations ◽  
Animal Body ◽  
Randomized Design ◽  
Dietary Requirements ◽  
Mineral Mixture ◽  
Daily Gain

This experiment was carried out with the objective of determining the macrominerals (Ca, P, Mg, K and Na) requirements of Nellore steers under grazing. Twenty four Nellore steers (371 ± 14 kg of BW and 26 mo old) were used. Four steers were slaughtered at the beginning of the experiment (reference group), serving as a reference in subsequent study. The remaining 20 animals were weighed and distributed into a completely randomized design with four supplementation levels offer: 0.0 (mineral mixture - control), 0.3, 0.6 and 0.9% of BW, with five replications. The supplements, based on ground corn, soybean meal and/or urea, were previously balanced to achieve an average daily gain of 350, 650 and 850g, respectively, for the different supplementation levels offer. The contents of macrominerals retained in the animal body were determined by regression equations of the macrominerals body content logarithm in function of the empty body weight logarithm (EBW). Net macrominerals requirements for a gain of 1kg of EBW were obtained using the equation Y'= b.10ª.Xb-1, with a and b, respectively, the intercept and the regression coefficient of the prediction equations of macrominerals in the animal body contents for each macromineral considered. The concentrations of all macrominerals, in the empty body weight and gain of the empty body weight, decreased with the increase in the body weight. Total calcium and phosphorus dietary requirements are higher than those recommended in the literature.

scholarly journals Models Predicting Hospital Admission of Adult Patients Utilizing Prehospital Data: Systematic Review Using PROBAST and CHARMS

10.2196/30022 ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. e30022
Author(s):  
Ann Corneille Monahan ◽  
Sue S Feldman
Keyword(s):  
Emergency Department ◽  
Hospital Admission ◽  
Real Time ◽  
Prediction Models ◽  
Assessment Tool ◽  
Predictive Performance ◽  
Patient Data ◽  
Adult Patients ◽  
Emergency Department Crowding ◽  
Exit Block

Background Emergency department boarding and hospital exit block are primary causes of emergency department crowding and have been conclusively associated with poor patient outcomes and major threats to patient safety. Boarding occurs when a patient is delayed or blocked from transitioning out of the emergency department because of dysfunctional transition or bed assignment processes. Predictive models for estimating the probability of an occurrence of this type could be useful in reducing or preventing emergency department boarding and hospital exit block, to reduce emergency department crowding. Objective The aim of this study was to identify and appraise the predictive performance, predictor utility, model application, and model utility of hospital admission prediction models that utilized prehospital, adult patient data and aimed to address emergency department crowding. Methods We searched multiple databases for studies, from inception to September 30, 2019, that evaluated models predicting adult patients’ imminent hospital admission, with prehospital patient data and regression analysis. We used PROBAST (Prediction Model Risk of Bias Assessment Tool) and CHARMS (Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modeling Studies) to critically assess studies. Results Potential biases were found in most studies, which suggested that each model’s predictive performance required further investigation. We found that select prehospital patient data contribute to the identification of patients requiring hospital admission. Biomarker predictors may add superior value and advantages to models. It is, however, important to note that no models had been integrated with an information system or workflow, operated independently as electronic devices, or operated in real time within the care environment. Several models could be used at the site-of-care in real time without digital devices, which would make them suitable for low-technology or no-electricity environments. Conclusions There is incredible potential for prehospital admission prediction models to improve patient care and hospital operations. Patient data can be utilized to act as predictors and as data-driven, actionable tools to identify patients likely to require imminent hospital admission and reduce patient boarding and crowding in emergency departments. Prediction models can be used to justify earlier patient admission and care, to lower morbidity and mortality, and models that utilize biomarker predictors offer additional advantages.

scholarly journals EFISIENSI PENGGUNAAN INPUT PAKAN DAN KEUNTUNGAN PADA USAHA TERNAK BABI DI KECAMATAN TARERAN KABUPATEN MINAHASA SELATAN

ZOOTEC ◽  
2014 ◽  
Vol 34 (1) ◽  
pp. 62 ◽  
Author(s):  
Rivo E Kojo ◽  
V V.J Panelewen ◽  
M A.V Manese ◽  
Nansi Santa
Keyword(s):  
Body Weight ◽  
Production Cost ◽  
Sampling Method ◽  
Secondary Data ◽  
Total Cost ◽  
Animal Body ◽  
Pig Farming ◽  
Pig Farm ◽  
Data Collections ◽  
Maximum Body

ABSTRACTFEED EFFICIENCY AND PROFITABILITY OF PIG FARM AT TARERAN DISTRICT OF SOUTH MINAHASA REGENCY. Tareran district is located in the South Minahasa regency consisted of 12 (twelve) villages and has the area of 7602.45 hectares or 76024.5 Km2. Generally, Tareran community work as farmers. The most pig populations at Tareran district were found at the three villages including villages of Lansot, Rumoong Atas, and Rumoong Atas Dua. The problems of this study are that; first, is the use of production cost in the pig business at the Tareran district efficient? Second, does the production cost provide benefits? Research objectives are to evaluate the type and total cost of production in the pig business at the Tareran district, to analyze the efficiency of input usedin pig farming, and to determine the optimum use of inputs in achieving the business benefits pigs. The research was conducted in the Tareran district of South Minahasa Regency involving the number of 30 breeders as respondents. Data collections were conducted in the period time of 2 months. The data in this study were obtained from two sources of primary and secondary data. Samples were taken using purposive sampling method. The use of this technique was always based on certain characteristics obtained through the population. The results of these studies showed the production cost of pig farm was Rp18.557.038 per period per year with a gain of about Rp 13.611.309 per period per year. Inefficient use of food inputs indicating to the farmers need to reduce feeding cost because it caused cost redundancy. It was known that animal body weight achieved was different for each type of pig. In addition, the use of ration inputs to achieve maximum body weight was also different for each animal.Keywords: Efficiency, Ration Input, Profit, Pig Farm, Tareran District.

scholarly journals TreeNet–The Biological Drought and Growth Indicator Network

2021 ◽  
Vol 4 ◽  
Author(s):  
Roman Zweifel ◽  
Sophia Etzold ◽  
David Basler ◽  
Reinhard Bischoff ◽  
Sabine Braun ◽  
...  
Keyword(s):  
Data Processing ◽  
Real Time ◽  
Environmental Conditions ◽  
Forest Growth ◽  
Water Dynamics ◽  
Automated System ◽  
Indicator Network ◽  
High Temporal Resolution ◽  
Stem Size ◽  
Wide Range

The TreeNet research and monitoring network has been continuously collecting data from point dendrometers and air and soil microclimate using an automated system since 2011. The goal of TreeNet is to generate high temporal resolution datasets of tree growth and tree water dynamics for research and to provide near real-time indicators of forest growth performance and drought stress to a wide audience. This paper explains the key working steps from the installation of sensors in the field to data acquisition, data transmission, data processing, and online visualization. Moreover, we discuss the underlying premises to convert dynamic stem size changes into relevant biological information. Every 10 min, the stem radii of about 420 trees from 13 species at 61 sites in Switzerland are measured electronically with micrometer precision, in parallel with the environmental conditions above and below ground. The data are automatically transmitted, processed and stored on a central server. Automated data processing (R-based functions) includes screening of outliers, interpolation of data gaps, and extraction of radial stem growth and water deficit for each tree. These long-term data are used for scientific investigations as well as to calculate and display daily indicators of growth trends and drought levels in Switzerland based on historical and current data. The current collection of over 100 million data points forms the basis for identifying dynamics of tree-, site- and species-specific processes along environmental gradients. TreeNet is one of the few forest networks capable of tracking the diurnal and seasonal cycles of tree physiology in near real-time, covering a wide range of temperate forest species and their respective environmental conditions.

scholarly journals Differences in Faculty and Standardized Patient Scores on Professionalism for Second-Year Podiatric Medical Students During a Standardized Simulated Patient Encounter

2018 ◽  
Vol 108 (2) ◽  
pp. 145-150
Author(s):  
James M. Mahoney ◽  
Vassilios Vardaxis ◽  
Noreen Anwar ◽  
Jacob Hagenbucher
Keyword(s):  
Medical Students ◽  
Faculty Member ◽  
Real Time ◽  
Assessment Tool ◽  
Simulated Patient ◽  
Standardized Patient ◽  
Patient Encounter ◽  
Second Year ◽  
The Difference ◽  
Share Information

Background: This study examined the differences between faculty and trained standardized patient (SP) evaluations on student professionalism during a second-year podiatric medicine standardized simulated patient encounter. Methods: Forty-nine second-year podiatric medicine students were evaluated for their professionalism behavior. Eleven SPs performed an assessment in real-time, and one faculty member performed a secondary assessment after observing a videotape of the encounter. Five domains were chosen for evaluation from a validated professionalism assessment tool. Results: Significant differences were identified in the professionalism domains of “build a relationship” (P = .008), “gather information” (P = .001), and share information (P = .002), where the faculty scored the students higher than the SP for 24.5%, 18.9%, and 26.5% of the cases, respectively. In addition, the faculty scores were higher than the SP scores in all of the “gather information” subdomains; however, the difference in scores was significant only in the “question appropriately” (P = .001) and “listen and clarify” (P = .003) subdomains. Conclusions: This study showed that professionalism scores for second-year podiatric medical students during a simulated patient encounter varied significantly between faculty and SPs. Further consideration needs to be given to determine the source of these differences.

Demystifying Essential Containers and Places for Aedes Mosquito Control in Thailand

2020 ◽  
Author(s):  
Naiyana Sahavechaphan ◽  
Asamaporn Chatrattikorn ◽  
Pongsakorn Sadakorn ◽  
Darin Areechokechai ◽  
Sopon Iamsirithaworn
Keyword(s):  
Real Time ◽  
Survey Data ◽  
Prevention And Control ◽  
Mosquito Control ◽  
Control Program ◽  
Water Tank ◽  
Effective Prevention ◽  
Larval Survey ◽  
Public Health Officials ◽  
And Control

Abstract Background: The strategy for prevention and control of Aedes-borne diseases relies on timely elimination of key breeding containers. There is thus a crucial need to identify key breeding containers to enhance vector control activities. The visual larval survey of wet containers has then been conducted as a routine mission of the Department of Disease Control (DDC). To facilitate this, DDC has deployed a mobile application, namely TanRabad SURVEY, since May 2016. As per an inspected place, TanRabad SURVEY supports the real-time collection of its larval survey data and processing of its larval indices and key breeding containers. Methods: Larval survey data from 2017 to 2019 were spatially and temporally collected by public health officials via TanRabad SURVEY. Several measurements were computed to identify the overall and regional key breeding containers and places; and the regional transmission potentiality of Aedes-borne diseases. The measurements for identifying essential containers were breeding potentiality, productivity, contribution and preference ratio. As for places, the larval productivity of places based on larval indices was employed. Such place productivity was also implemented for discovering the regional transmission potentiality of Aedes-borne diseases. Results: The overall essential breeding containers were water tank, unused containers, other used containers, old tyres, anti-ant bowls, drip tray of water dispensers, pet bowls and plant leaves. As for regional aspects, different regions had different essential breeding containers wherein their most common containers were unused containers, other used containers, old tyres and drip tray of water dispensers. All regions had similar experiences that villages and temples were the top two riskiest places, followed by schools, factories, hotels and hospitals. Additionally, all regions had high transmission potentiality of Aedes-borne disease as above 30 of all their places were moderate and high risk places. Conclusions: This study identified the overall and regional key breeding containers and places along with the regional transmission potentiality of Aedes-borne diseases. Beside this, the empirical evidence had shown that the breeding productivity of most containers and places in each type was gradually decreased from time to time. This was mainly because TanRabad SURVEY supported real-time risk communication to community participants and effective prevention and control program development.

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