scholarly journals Evaluation of Beef Cattle Temperament Attributes Using Infrared Thermography Technology

2019 ◽  
Vol 3 (2) ◽  
Author(s):  
W. P. Ogdahl ◽  
J. Young ◽  
J. Frandrup ◽  
L. L. Hulsman Hanna ◽  
X. Sun
Keyword(s):  
Standard Deviation ◽  
Beef Cattle ◽  
Infrared Thermography ◽  
Thermal Imaging ◽  
Qualitative Behavior ◽  
Regression Analyses ◽  
Imaging Data ◽  
Total N ◽  
Thermal Images ◽  
Temperament Traits

ObjectivesThe objective of this study was to evaluate beef cattle temperament scores using infrared thermography technology.Materials and MethodsAngus and Angus × Hereford calves (total n = 650) were brought through a handling chute system over two weaning sessions (October 2016 and 2017). Beef cattle temperament was subjectively quantified by (1) temperament score (TS), the disposition of the animal observed by an individual evaluator on a scale of 1 (calm) to 5 (excitable); (2) docility score (DS), the level of observed calmness of the animal displayed (1 = calm to 6 = excitable); and (3) qualitative behavior assessment (QBA), scored on twelve different attributes, (i.e., active, relaxed, etc.). There were two traits measured on a four-platform standing scale: (1) the standard deviation of total weight over time (SSD); and (2) the SSD’s coefficient of variation (CVSSD). Thermal images of the animal’s head were acquired by industrial fixed focus infrared camera (TiS40, Fluke Corporation, Everett, WA). The maximum, minimum, average, and standard deviation of temperature of the eye region were extracted from the thermal images. Stepwise and linear regression analyses to estimate subjective temperament traits from thermal imaging data and scale data were conducted using the reg procedure in SAS (v. 9.4, SAS Institute, Inc., Cary, NC). Correlations were estimated using the corr procedure in SAS.ResultsThe results showed low correlations between thermal imaging and subjective temperament traits. The correlations that were significant were around an absolute value of 0.1. However, all four thermal imaging traits were significantly correlated when the animal exhibited distress observed by QBA. When fitting only thermal imaging data into the regression analyses, R2 values were all under 0.03. When including SSD and CVSSD, there were a few traits with an R2 > 0.1 and none having an R2 > 0.15. The QBA traits that had an R2 between 0.1 and 0.15 were active, fearful, calm, apathetic, happy, and distressed for both linear and stepwise regressions.ConclusionAdditional validation research on this thermal imaging technology needs to be conducted with temperamental cattle as this current data was collected using observed calmer cattle, to give a more realistic application to beef cattle production. Overall this result shows potential to achieve beef cattle temperament evaluation with thermal imaging.Figure 1.

scholarly journals Infrared Thermal Imaging for Evaluation of Clubfoot After the Ponseti Casting Method—An Exploratory Study

2021 ◽  
Vol 9 ◽  
Author(s):  
Balasankar Ganesan ◽  
Joanne Yip ◽  
Ameersing Luximon ◽  
Paul J. Gibbons ◽  
Alison Chivers ◽  
...  
Keyword(s):  
Skin Temperature ◽  
Infrared Thermography ◽  
Thermal Imaging ◽  
Lateral Side ◽  
Thermal Images ◽  
Temperature Changes ◽  
Surgical Methods ◽  
Before And After ◽  
Significant Temperature ◽  
Casting Pressure

Background: Conservative treatment, Ponseti method, has been considered as a standard method to correct the clubfoot deformity among Orthopedic society. Although the result of conservative methods have been reported with higher success rates than surgical methods, many more problems have been reported due to improper casting, casting pressure or bracing discomfort. Nowadays, infrared thermography (IRT) is widely used as a diagnostic tool to assess musculoskeletal disorders or injuries by detecting temperature abnormalities. Similarly, the foot skin temperature evaluation can be added along with the current subjective evaluation to predict if there is any casting pressure, excessive manipulation, or overcorrections of the foot, and other bracing pressure-related complications.Purpose: The main purpose of this study was to explore the foot skin temperature changes before and after using of manipulation and weekly castings.Methods: This is an explorative study design. Infrared Thermography (IRT), E33 FLIR thermal imaging camera model, was used to collect the thermal images of the clubfoot before and after casting intervention. A total of 120 thermal images (Medial region of the foot–24, Lateral side of the foot–24, Dorsal side of the foot−24, Plantar side of the foot−24, and Heel area of the foot–24) were collected from the selected regions of the clubfoot.Results: The results of univariate statistical analysis showed that significant temperature changes in some regions of the foot after casting, especially, at the 2nd (M = 32.05°C, SD = 0.77, p = 0.05), 3rd (M = 31.61, SD = 1.11; 95% CI: 31.27–31.96; p = 0.00), and 6th week of evaluation on the lateral side of the foot (M = 31.15°C, SD = 1.59; 95% CI: 30.75–31.54, p = 0.000). There was no significant temperature changes throughout the weekly casting in the medial side of the foot. In the heel side of the foot, significant temperature changes were noticed after the third and fourth weeks of casting.Conclusion: This study found that a decreased foot skin temperature on the dorsal and lateral side of the foot at the 6th week of thermography evaluation. The finding of this study suggest that the infrared thermography (IRT) might be useful as an adjunct assessment tool to evaluate the thermophysiological changes, which can be used to predict the complications caused by improper casting, over manipulative or stretching and casting-pressure related complications.

scholarly journals Comparison of Infrared Thermal Imaging with Two Canine Pain Assessment Tools in Dogs Undergoing Treatment for Chronic Back Pain

2021 ◽  
Author(s):  
Emily Freeman ◽  
Jennifer F. Johnson ◽  
John C. Godbold, Jr ◽  
Ronald J. Riegel
Keyword(s):  
Back Pain ◽  
Thermal Imaging ◽  
Chronic Back Pain ◽  
Intervertebral Disk ◽  
Assessment Tools ◽  
Response To Treatment ◽  
Imaging Data ◽  
Thermal Images ◽  
Additional Tool ◽  
Monitoring Therapy

Historically, the evaluation and assessment of the clinical response to treatment for canine back pain is subjective and relies on owner and clinician assessment of pain. This study evaluated the use of sequential infrared thermal images as a measure of the response of canine patients with back pain to a prescribed series of photobiomodulation therapy (PBMT) treatments. Qualifying participants had histories of pain and dysfunction associated with spinal osteoarthritis or intervertebral disk disease, or of non-specific uni- or bilateral back pain along the paravertebral epaxial muscles. Each patient was initially thermally imaged prior to PBMT treatment and then received multiple PBMT treatments delivered to the appropriate spinal area on days 1, 2, 3, and 4. Participants were reimaged on day 7. Thermal images provided an objective measure of superficial temperature changes over the area of PBMT treatment of each patient after the PBMT regimen. The temperature correlated with statistically significant changes in Colorado State University Canine Chronic Pain Scale scoring (CPS) and owner assessment using the Canine Brief Pain Inventory (CBPI), which includes a Pain Severity Score (PSS) and Pain Interference Score (PIS). The correlation of objective thermal imaging data with more subjective outcome measures suggests thermal imaging may be a valuable additional tool in monitoring therapy outcome.

scholarly journals APPRAISAL OF MOISTURE PROBLEM OF INHERITANCE BUILDING ENVELOPE ASSEMBLIES VIA VISIBLE AND INFRARED THERMOGRAPHY METHODS

2015 ◽  
Vol 75 (5) ◽  
Author(s):  
Ting Siew Jing ◽  
Md Azree Othuman Mydin ◽  
Nangkula Utaberta
Keyword(s):  
Infrared Thermography ◽  
Thermal Imaging ◽  
Building Envelope ◽  
Temporary Reduction ◽  
Infrared Thermal Imaging ◽  
Thermal Images ◽  
Heritage Building ◽  
Moisture Performance ◽  
Infrared Thermal Images ◽  
Wall Assembly

In order to gauge the moisture performance of walls and roofs there is a need to investigate the paths of moisture penetrating into the wall assembly, how long and where the moisture stays, and whether it causes temporary reduction of performance or permanent damage. The non-contact safe nature and usefulness in temperature measurement of infrared thermography have made it a popular instrument for building diagnostics. Hence, this paper depicts a documentation process which makes use of both visible and infrared thermal images to identify moisture anomalies in heritage building envelope assemblies. In sequence to achieve the purpose, visible and infrared thermal images are recorded for comparison and further analysis. It can be concluded that infrared thermal imaging camera is useful for identification of moisture problems in building façade, whereas combination of both visible and infrared thermal imaging methods produces a more advanced, accurate and effective approach for building diagnostics.

scholarly journals Local Entropy and Standard Deviation for Facial Expressions Recognition in Thermal Imaging

2018 ◽  
Vol 7 (4) ◽  
pp. 580-586
Author(s):  
Yomna M. Elbarawy ◽  
Rania S. El-Sayed ◽  
Neveen I. Ghali
Keyword(s):  
Standard Deviation ◽  
Facial Expressions ◽  
Thermal Imaging ◽  
Water Status ◽  
Emotional Reactions ◽  
Spatial And Temporal Variation ◽  
Support Vector ◽  
Local Entropy ◽  
K Nearest Neighbor ◽  
Thermal Images

Emotional reactions are the best way to express human attitude and thermal imaging mainly used to utilize detection of temperature variations as in detecting spatial and temporal variation in the water status of grapevine. By merging the two facts this paper presents the Discrete Cosine Transform (DCT) with Local Entropy (LE) and Local Standard Deviation (LSD) features as an efficient filters for investigating human emotional state in thermal images. Two well known classifiers, K-Nearest Neighbor (KNN) and Support Vector Machine (SVM) were combined with the earlier features and applied over a database with variant illumination, as well as occlusion by glasses and poses to generate a recognition model of facial expressions in thermal images. KNN based on DCT and LE gives the best accuracy compared with other classifier and features results.

Evaluation of Package Defects by Thermal Imaging Techniques

2002 ◽  
Author(s):  
Yongmei Liu ◽  
Rajen Dias
Keyword(s):  
Infrared Thermography ◽  
Thermal Imaging ◽  
High Speed ◽  
Imaging Techniques ◽  
Thermal Response ◽  
Analysis Tool ◽  
Nondestructive Analysis ◽  
Ir Camera ◽  
External Heating

Abstract Study presented here has shown that Infrared thermography has the potential to be a nondestructive analysis tool for evaluating package sublayer defects. Thermal imaging is achieved by applying pulsed external heating to the package surface and monitoring the surface thermal response as a function of time with a high-speed IR camera. Since the thermal response of the surface is affected by the defects such as voids and delamination below the package surface, the technique can be used to assist package defects detection and analysis.

Innovative yield mapping system using hyperspectral and thermal imaging for precision tree crop management

2014 ◽  
Author(s):  
W.S. Lee ◽  
Victor Alchanatis ◽  
Asher Levi
Keyword(s):  
Image Registration ◽  
Navigation System ◽  
Thermal Imaging ◽  
Imaging System ◽  
Citrus Fruit ◽  
Mobile Platform ◽  
Yield Estimation ◽  
Yield Mapping ◽  
Thermal Images ◽  
Mapping System

Original objectives and revisions – The original overall objective was to develop, test and validate a prototype yield mapping system for unit area to increase yield and profit for tree crops. Specific objectives were: (1) to develop a yield mapping system for a static situation, using hyperspectral and thermal imaging independently, (2) to integrate hyperspectral and thermal imaging for improved yield estimation by combining thermal images with hyperspectral images to improve fruit detection, and (3) to expand the system to a mobile platform for a stop-measure- and-go situation. There were no major revisions in the overall objective, however, several revisions were made on the specific objectives. The revised specific objectives were: (1) to develop a yield mapping system for a static situation, using color and thermal imaging independently, (2) to integrate color and thermal imaging for improved yield estimation by combining thermal images with color images to improve fruit detection, and (3) to expand the system to an autonomous mobile platform for a continuous-measure situation. Background, major conclusions, solutions and achievements -- Yield mapping is considered as an initial step for applying precision agriculture technologies. Although many yield mapping systems have been developed for agronomic crops, it remains a difficult task for mapping yield of tree crops. In this project, an autonomous immature fruit yield mapping system was developed. The system could detect and count the number of fruit at early growth stages of citrus fruit so that farmers could apply site-specific management based on the maps. There were two sub-systems, a navigation system and an imaging system. Robot Operating System (ROS) was the backbone for developing the navigation system using an unmanned ground vehicle (UGV). An inertial measurement unit (IMU), wheel encoders and a GPS were integrated using an extended Kalman filter to provide reliable and accurate localization information. A LiDAR was added to support simultaneous localization and mapping (SLAM) algorithms. The color camera on a Microsoft Kinect was used to detect citrus trees and a new machine vision algorithm was developed to enable autonomous navigations in the citrus grove. A multimodal imaging system, which consisted of two color cameras and a thermal camera, was carried by the vehicle for video acquisitions. A novel image registration method was developed for combining color and thermal images and matching fruit in both images which achieved pixel-level accuracy. A new Color- Thermal Combined Probability (CTCP) algorithm was created to effectively fuse information from the color and thermal images to classify potential image regions into fruit and non-fruit classes. Algorithms were also developed to integrate image registration, information fusion and fruit classification and detection into a single step for real-time processing. The imaging system achieved a precision rate of 95.5% and a recall rate of 90.4% on immature green citrus fruit detection which was a great improvement compared to previous studies. Implications – The development of the immature green fruit yield mapping system will help farmers make early decisions for planning operations and marketing so high yield and profit can be achieved. 

scholarly journals Is Thermal Imaging a Useful Predictor of the Healing Status of Diabetes-Related Foot Ulcers? A Pilot Study

2018 ◽  
Vol 13 (3) ◽  
pp. 561-567
Author(s):  
Behzad Aliahmad ◽  
Aye Nyein Tint ◽  
Sridhar Poosapadi Arjunan ◽  
Priya Rani ◽  
Dinesh Kant Kumar ◽  
...  
Keyword(s):  
Temperature Distribution ◽  
Pilot Study ◽  
Thermal Imaging ◽  
Color Image ◽  
Foot Ulcer ◽  
Clinic Visit ◽  
Color Images ◽  
Thermal Images ◽  
Reduction In Area

Introduction: In clinical practice, both area and temperature of the ulcer have been shown to be effective in tracking the healing status of diabetes-related foot ulcer (DRFU). However, traditionally, the area of the DRFU is measured regardless of the temperature distribution. The current prospective, observational study used thermal imaging, as a more accurate tool, to measure both the area and the temperature of DRFU. We aimed to predict healing of DRFU using thermal imaging within the first 4 weeks of ulceration. Method: A pilot study was conducted where thermal and color images of 26 neuropathic DRFUs (11 healing vs 15 nonhealing) from individuals with type 1 or 2 diabetes were taken at the initial clinic visit (baseline), at week 2, and at week 4. The thermal images were segmented into isothermal patches to identify the wound boundary and area corresponding to temperature distribution. Five parameters were obtained: temperature of the wound bed, area of the isothermal patch of the wound bed, area of isothermal patch of periwound, number of isolated isothermal patches of the wound region, and physical wound bed area from color image. The ulcers were also measured by experienced podiatrists over 4 consecutive weeks and used as the healing reference. Results: For healing cases, the ratio of the area of the wound bed to its baseline measured using thermal images was found to be significantly lower at 2 weeks compared to nonhealing cases and this corresponded with a 50% reduction in area of DRFU at 4 weeks (group rank-based nonparametric analysis of variance P = .036). In comparison, neither the planimetric area measured using color images nor the temperature of the wound bed was associated with the healing. Conclusion: This study of 26 patients demonstrates that change in the isothermal area of DRFU can predict the healing status at week 4. Thermal imaging of DRFUs has the advantage of incorporating both area and temperature allowing for early prediction of the healing of these ulcers. Further studies with greater sample sizes are required to test the significance of these results.

scholarly journals Classification of the coefficient of variation to variables in beef cattle experiments

2017 ◽  
Vol 47 (11) ◽  
Author(s):  
Marcos André Braz Vaz ◽  
Paulo Santana Pacheco ◽  
Enio Júnior Seidel ◽  
Angela Pellegrin Ansuj
Keyword(s):  
Standard Deviation ◽  
Beef Cattle ◽  
Coefficient Of Variation ◽  
Theses And Dissertations

ABSTRACT: This research was conducted to propose a classification of the coefficient of variation (CV%) in many categories of variables of production and carcass of beef cattle experiments. The data was collected from theses and dissertations. We used the methods of classification considering mean and standard deviation, and considering median and pseudo-sigma. The two methods showed similar results so both can be used to classify CV%. We propose only three categories to rank CV%: low, medium and high.

scholarly journals Do aggression and impulsivity dominate dark triad across genders?

2020 ◽  
Author(s):  
Anupriya Singh ◽  
Aisha Naeem ◽  
Komal Chandiramani
Keyword(s):  
Gender Differences ◽  
Standard Deviation ◽  
Pearson Correlation ◽  
Correlation Method ◽  
Dark Triad ◽  
T Test ◽  
Descriptive Statistics ◽  
Regression Analyses ◽  
Future Directions ◽  
Significant Relationships

The study investigated gender differences in Overall Dark Triad (Machiavellianism, Narcissism, and Psychopathy), Aggression, Impulsivity, and impact of Dark triad on Aggression and Impulsivity. Data was collected from 214 young adults. Analyses was done using descriptive statistics (mean and standard deviation). T-test was employed to analyze gender differences. Pearson Correlation Method and Multiple regression were used to assess the relation and prediction amongst the variables, respectively. T-test suggested significant gender differences in Machiavellianism, Psychopathy, and Overall Dark Triad, with females scoring high than males. No gender difference was observed in Aggression and Impulsivity. Correlation and regression analyses revealed several significant relationships between the above constructs. The research was concluded by briefly foregrounding some of the study’s implications and future directions.

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