Process of steel truss incremental launching. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

CGAN and AutoML stacking device. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

Comprehensive prediction process of shape errors. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

Shape error manual calculation process. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

U-wave estimates versus R-matrix noise variance. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

Sliding window process. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

Assembly error angle of a single spline. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

Original record form of error matrix. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

Form for machine recognition. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

RMSE versus architectural parameters. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

Kalman process. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

Attention mechanism. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

Shape error measurement results statistics. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

Individual data. by JoEllen M. Sefton (16880253)

“…Total kcals did not differ between conditions (with/without exoskeleton; t = 0.98; p = 0.357). Kcals/min were significantly lower (1.06 kcals/min) with the exoskeleton (t = 3.94; p = 0.004). …”

Descriptive statistics. by JoEllen M. Sefton (16880253)

“…Total kcals did not differ between conditions (with/without exoskeleton; t = 0.98; p = 0.357). Kcals/min were significantly lower (1.06 kcals/min) with the exoskeleton (t = 3.94; p = 0.004). …”

Time matched metabolic cost. by JoEllen M. Sefton (16880253)

“…Total kcals did not differ between conditions (with/without exoskeleton; t = 0.98; p = 0.357). Kcals/min were significantly lower (1.06 kcals/min) with the exoskeleton (t = 3.94; p = 0.004). …”

Research design. by JoEllen M. Sefton (16880253)

“…Total kcals did not differ between conditions (with/without exoskeleton; t = 0.98; p = 0.357). Kcals/min were significantly lower (1.06 kcals/min) with the exoskeleton (t = 3.94; p = 0.004). …”

Time matched physiological strain. by JoEllen M. Sefton (16880253)

“…Total kcals did not differ between conditions (with/without exoskeleton; t = 0.98; p = 0.357). Kcals/min were significantly lower (1.06 kcals/min) with the exoskeleton (t = 3.94; p = 0.004). …”

Physiological strain. by JoEllen M. Sefton (16880253)

“…Total kcals did not differ between conditions (with/without exoskeleton; t = 0.98; p = 0.357). Kcals/min were significantly lower (1.06 kcals/min) with the exoskeleton (t = 3.94; p = 0.004). …”

Diagram of exercise intervention progression. by JoEllen M. Sefton (16880253)

“…Total kcals did not differ between conditions (with/without exoskeleton; t = 0.98; p = 0.357). Kcals/min were significantly lower (1.06 kcals/min) with the exoskeleton (t = 3.94; p = 0.004). …”