267 research outputs found
Effect of Human Resource Practices on Employee Performance at Yangon Aerodrome Company Limited (Arkar Minn, 2025)
No full textThis study aims to examine the effect of human resource practices on employee
job satisfaction, to analyze the mediating effect of employee engagement on the
relationship between job satisfaction and organizational commitment, and to analyze the
effect of organizational commitment on employee performance at Yangon Aerodrome
Company Limited (YACL). This study utilizes both primary and secondary data. The
sample size of this study is 292 out of 1,070 employees, determined using Yamane’s
formula. Primary data are collected through a structured questionnaire with a five-point
Likert scale. A simple random sampling method is applied to collect data from employees
across various departments and job positions at YACL in 2025. Descriptive statistics and
regression analysis are used to analyze the data. The findings reveal that HR practices,
specifically employee compensation and training and development have a positive
significant effect on job satisfaction. The finding shows that there is a mediating effect of
employee engagement on the relationship between job satisfaction and organizational
commitment. It also finds that organizational commitment has a positive significant effect
on employee performance. This study highlights the importance of strategic HR practices
in shaping employee outcomes at YACL should prioritize effective training programs,
fair compensation systems, and initiatives to enhance employee engagement to build a
motivated, committed, and high-performing workforce
Coffee Leaf Rust Disease Detection and Implementation of an Edge Device for Pruning Infected Leaves via Deep Learning Algorithms
No full textGlobal warming and extreme climate conditions caused by unsuitable temperature and humidity lead to coffee leaf rust (Hemileia vastatrix) diseases in coffee plantations. Coffee leaf rust is a severe problem that reduces productivity. Currently, pesticide spraying is considered the most effective solution for mitigating coffee leaf rust. However, the application of pesticide spray is still not efficient for most farmers worldwide. In these cases, pruning the most infected leaves with leaf rust at coffee plantations is important to help pesticide spraying to be more efficient by creating a more targeted, accessible treatment. Therefore, detecting coffee leaf rust is important to support the decision on pruning infected leaves. The dataset was acquired from a coffee farm in Majalengka Regency, Indonesia. Only images with clearly visible spots of coffee leaf rust were selected. Data collection was performed via two devices, a digital mirrorless camera and a phone camera, to diversify the dataset and test it with different datasets. The dataset, comprising a total of 2024 images, was divided into three sets with a ratio of 70% for training (1417 images), 20% for validation (405 images), and 10% for testing (202 images). Images with leaves infected by coffee leaf rust were labeled via LabelImg® with the label “CLR”. All labeled images were used to train the YOLOv5 and YOLOv8 algorithms through the convolutional neural network (CNN). The trained model was tested with a test dataset, a digital mirrorless camera image dataset (100 images), a phone camera dataset (100 images), and real-time detection with a coffee leaf rust image dataset. After the model was trained, coffee leaf rust was detected in each frame. The mean average precision (mAP) and recall for the trained YOLOv5 model were 69% and 63.4%, respectively. For YOLOv8, the mAP and recall were approximately 70.2% and 65.9%, respectively. To evaluate the performance of the two trained models in detecting coffee leaf rust on trees, 202 original images were used for testing with the best-trained weight from each model. Compared to YOLOv5, YOLOv8 demonstrated superior accuracy in detecting coffee leaf rust. With a mAP of 73.2%, YOLOv8 outperformed YOLOv5, which achieved a mAP of 70.5%. An edge device was utilized to deploy real-time detection of CLR with the best-trained model. The detection was successfully executed with high confidence in detecting CLR. The system was further integrated into pruning solutions for Arabica coffee farms. A pruning device was designed using Autodesk Fusion 360® and fabricated for testing on a coffee plantation in Indonesia
Harriet Beecher Stowe author and advocate
No full textA biography of the American author who, in writing Uncle Tom's cabin, revealed the cruelties of slavery and further split an already divided country
Witnessing and Testifying: Black Women, Religion, and Civil Rights
No full textAuthor: Ross, Rosetta E. Title: Witnessing and testifying. Publisher: Minneapolis, Minn: Fortress, 2003
Early Christian Worship
No full textAuthor: Bradshaw, Paul F. Title: Early Christian worship. Publisher: Collegeville, Minn: Liturgical Pr, 2001
The Colonized Apostle: Paul Through Postcolonial Eyes
No full textTitle: The colonized Apostle: Paul through postcolonial eyes Author: Christopher D Stanley Publisher: Minneapolis, Minn.: Fortress Press, 2011. ISBN: 978080066458
Disrupting Homelessness: Alternative Christian Approaches
No full textTitle: Disrupting homelessness: alternative Christian approaches Author: Laura A Stivers Publisher: Minneapolis, Minn.: Fortress Press, 2011. ISBN: 978080069797
The Political Aims of Jesus
No full textTitle: The political aims of Jesus Author: Douglas E Oakman Publisher: Minneapolis, Minn.: Fortress Press, 2012. ISBN: 978080063847
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