Impact of endophytic fungi on hemp leaf pigments, under non-stress, salinity and drought stress conditions. حسب Shasha Hu (5880887)

Impact of endophytic fungi on weight of hemp leaf, stem and root, under non-stress, salinity and drought stress conditions. حسب Shasha Hu (5880887)

Impact of endophytic fungi on soil humidity, under non-stress, salinity and drought stress conditions. حسب Shasha Hu (5880887)

Impact of endophytic fungi on the concentration of protoporphyrin (PPIX) and magnesium protoporphyrin (MGPP) in hemp leaves under non-stress, salinity and drought stress conditions... حسب Shasha Hu (5880887)

Impact of endophytic fungi on the expression patterns <i>CsNAC3</i> in hemp under non-stress, salinity and drought stress conditions. حسب Shasha Hu (5880887)

Implementation framework. حسب Amos Asiedu (4996946)

"…HMIS data showed statistically significant improvement in data completeness (from 62 to 87% (p < 0.001)) and decreased error rate (from 37 to 18% (p < 0.001)) after completion of the coaching visit series. …"

DHIMS2 data quality over time. حسب Amos Asiedu (4996946)

"…HMIS data showed statistically significant improvement in data completeness (from 62 to 87% (p < 0.001)) and decreased error rate (from 37 to 18% (p < 0.001)) after completion of the coaching visit series. …"

Availability of modern family planning methods in 2014 and 2017. حسب Rajon Banik (12066099)

الموضوعات:

Facilities offering modern family planning services by division in 2014 (A) and 2017 (B). حسب Rajon Banik (12066099)

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Facilities offering modern family planning services by survey years and facility types, 2014 and 2017. حسب Rajon Banik (12066099)

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Factors associated with facility readiness for providing modern family planning services in 2014 and 2017. حسب Rajon Banik (12066099)

الموضوعات:

Modern family planning service readiness score by division in 2014 (A) and 2017 (B). حسب Rajon Banik (12066099)

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Flowchart of the sample selection procedure from BHFS 2014 and 2017. حسب Rajon Banik (12066099)

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Mean readiness score of modern family planning service by facility type in 2014 and 2017. حسب Rajon Banik (12066099)

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Overall and domain-specific mean readiness score by survey years, 2014 and 2017. حسب Rajon Banik (12066099)

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Percentage distribution (weighted) of surveyed facilities in 2014 and 2017. حسب Rajon Banik (12066099)

الموضوعات:

Datasets used in the study. حسب Rajon Banik (12066099)

الموضوعات:

Comparison experiment of accuracy improvement. حسب Zhongjian Xie (4633099)

"…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …"

Comparison experiment of accuracy improvement. حسب Zhongjian Xie (4633099)

"…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …"

Improved model distillation structure. حسب Zhongjian Xie (4633099)

"…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …"