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Development of a computer vision system to detect inactivity in group-housed pigs

International Journal of Agricultural and Biological Engineering 2020年第1期13卷 42-46页

作者： christopher chijioke ojukwu Yaoze Feng Guifeng Jia Haitao Zhao Hequn Tan College of Engineering Huazhong Agricultural UniversityWuhan 430070China Key Laboratory of Agricultural Equipment in Mid-lower Yangtze River Ministry of Agriculture and Rural AffairsWuhan 430070China

Excessive inactivity in farm animals can be an early indication of *** way for detecting excessive inactivity in pigs relies on manual inspection which can be laborious and especially *** paper proposed a computer vision system that could detect inactivity of individual pigs housed in group pens which is potential in alarming the farmer of the animals *** system recorded sequential depth images for the animals in a pen and implemented a proposed image processing and logic analysis scheme named as‘DepInact’to keep track of the inactive time of group-housed individual pigs over *** verify the robustness and accuracy of the developed system,a total of 656 pairs of corresponding depth data and color images,consecutively taken 4 s apart from each other,were *** verification process involved manually identifying all pigs using the color images *** results of identification of all pigs that were inactive for more than the preset period of time by DepInact were compared to those by manual inspection through the color images *** accuracy of 85.7%was achieved using the verification data,thus demonstrating that the developed system is a viable alternative to manual detection of inactivity of group-housed ***,more research is still needed to improve the accuracy of the developed system.

关键词： Matlab computer vision sows machine vision depth image pigs inactivity

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Emerging trends in expansive soil stabilisation: A review

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Journal of Rock Mechanics and Geotechnical Engineering 2019年第2期11卷 423-440页

作者： chijioke christopher Ikeagwuani Donald Chimobi Nwonu Civil Engineering Department University of Nigeria

Expansive soils are problematic due to the performances of their clay mineral constituent, which makes them exhibit the shrink-swell characteristics. The shrink-swell behaviours make expansive soils inappropriate for direct engineering application in their natural form. In an attempt to make them more feasible for construction purposes, numerous materials and techniques have been used to stabilise the soil. In this study, the additives and techniques applied for stabilising expansive soils will be focused on,with respect to their efficiency in improving the engineering properties of the soils. Then we discussed the microstructural interaction, chemical process, economic implication, nanotechnology application, as well as waste reuse and sustainability. Some issues regarding the effective application of the emerging trends in expansive soil stabilisation were presented with three categories, namely geoenvironmental,standardisation and optimisation issues. Techniques like predictive modelling and exploring methods such as reliability-based design optimisation, response surface methodology, dimensional analysis, and artificial intelligence technology were also proposed in order to ensure that expansive soil stabilisation is efficient.

关键词： Expansive soil Engineering properties Soil stabilisation Geoenvironmental issues Standardisation Optimisation

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利用深度图像分析检测不活动性和估计猪的实际体重

利用深度图像分析检测不活动性和估计猪的实际体重

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作者： ojukwu christopher chijioke 华中农业大学

学位级别：硕士

深度图像分析在农业中具有很大的潜力,在动物行为检测和体重估计中具有重要应用价值。检测猪不活动行为及其体重的传统方法依赖于费时费力的人工检查。本论文提出了使用深度图像检测围栏中群养母猪的不活动行为的相关方法,并建立了个体... 详细信息

深度图像分析在农业中具有很大的潜力,在动物行为检测和体重估计中具有重要应用价值。检测猪不活动行为及其体重的传统方法依赖于费时费力的人工检查。本论文提出了使用深度图像检测围栏中群养母猪的不活动行为的相关方法,并建立了个体仔猪体重的检测模型。研究通过搭建的图像采集系统自动连续记录动物的深度图像,通过提出的DepInact图像处理和逻辑分析方法跟踪处于非活动状态的群养猪个体,并对处于这一状态超过一定时间阈值的猪只(目标猪只)进行识别。为了验证所开发系统的稳健性和准确性,获得了 656对间隔4秒拍摄的相应的深度数据和彩色图像,其中深度数据用来自动检测目标猪只,而彩色图像用来人工确定真实的非活动目标猪只。通过比较DepInact识别结果与人工真实标记结果,得到利用DepInact进行非活动目标猪只检测的准确率为85.7%,从而证明所开发的系统可以用于非活动目标猪只的自动识别。特别的,该系统对猪舍光线条件改变不敏感,具有较好的环境适应性。本研究的第二部分讨论了基于深度图像的仔猪体重检测方法。研究提取单个仔猪特征(如背部区域,高度和高度总和)并利用这些特征建立了支持向量机(SVM)模型来估计仔猪重量。研究比较了单一特征输入和多特征输入的结果,最优模型为使用三个输入特征时建立的SVM模型,校正集相关系数和均方根误差分别为0.82和0.09 kg,预测集相关系数和均方根误差为0.95和0.08 kg。然而,但仍需开展更多深入的研究来提高系统识别和预测的准确性。

关键词：母猪深度图像 matlab 不活动机器视觉小猪体重预测

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Towards an Antimicrobial Stewardship Program in a Young Tertiary Hospital in Southern Nigeria: A Point Prevalence Survey of Antimicrobial Usage

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Open Journal of Medical Microbiology 2023年第4期13卷 292-302页

作者： Ibinabo Laura Oboro Mienye Bob-Manuel Datonye christopher Briggs Afam Chibuike Okafor Simeon chijioke Amadi Stella Ogbonnie Enyinnaya Stephenson Danagogo Lawson Oyinlola Omoniyi Oduyebo Department of Medical Microbiology and Parasitology Rivers State University Teaching Hospital Port Harcourt Nigeria Department of Paediatrics Rivers State University Teaching Hospital Port Harcourt Nigeria Department of Obstetrics and Gynaecology Rivers State University Teaching Hospital Port Harcourt Nigeria Department of Medical Microbiology and Parasitology Lagos University Teaching Hospital Lagos Nigeria

Background: Antimicrobial resistance (AMR) is one of the top 10 global public health threats facing humanity and this burden is borne largely by low and middle-income countries. As part of efforts to combat AMR, the World Health Organization has identified Antimicrobial Stewardship as one of the strategic objectives of its global action plan on antimicrobial resistance. This survey aimed to observe antimicrobial prescribing and usage patterns in the Rivers State University Teaching Hospital with the purpose of identifying gaps to inform the specific antimicrobial stewardship interventions necessary to address our specific needs. Methodology: A point prevalence survey was conducted using the protocol and web-based automated data management system designed by the Global Point Prevalence Survey of Antimicrobial Consumption and Resistance, University of Antwerp, Belgium, in November 2021. Results: A total of 69 adult medical and surgical patients were surveyed;27 males and 18 females. Antimicrobial prevalence was 65.2%. Third generation cephalosporins (24.4%;33.3%), fluoroquinolones (17.8%;22.2%) and imidazole derivatives (20%;36.1%) were most prescribed on the medical and surgical wards. Antimicrobial guidelines were completely unavailable, most antimicrobials (93.8%) were prescribed empirically and 64.4% of these remained empirical after 72 hours of commencement. Conclusion: Antimicrobial stewardship interventions are necessary to minimize sub-optimal antimicrobial prescribing practices in our facility. Most critical are education on appropriate use of antimicrobials, support for development of antimicrobial guidelines, diagnostic stewardship, and the drive for improved use of the laboratory to guide antimicrobial prescriptions. The antimicrobial stewardship committee and team must drive this, having the requisite support from the management and prescribers, with the primary outcomes being reduced antimicrobial prevalence and improved antimicrobial prescription patter

关键词： Antimicrobial Stewardship Antimicrobial Resistance Point Prevalence Survey Rivers State University Teaching Hospital

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