Screenshot a the Hatching-Box server application (HB-server). by Julian Bigge (22331861)

Comparison with existing work. by Khondokar Oliullah (21553289)

“…In this paper, we incorporate a two-step authentication process, starting with anonymous authentication using a secret ID with Elliptic Curve Cryptography (ECC), followed by an intrusion detection algorithm for users flagged as suspicious activity. …”

Registration phase. by Khondokar Oliullah (21553289)

“…In this paper, we incorporate a two-step authentication process, starting with anonymous authentication using a secret ID with Elliptic Curve Cryptography (ECC), followed by an intrusion detection algorithm for users flagged as suspicious activity. …”

Performance comparison of different ML models. by Khondokar Oliullah (21553289)

“…In this paper, we incorporate a two-step authentication process, starting with anonymous authentication using a secret ID with Elliptic Curve Cryptography (ECC), followed by an intrusion detection algorithm for users flagged as suspicious activity. …”

Classification Report for the proposed model. by Khondokar Oliullah (21553289)

“…In this paper, we incorporate a two-step authentication process, starting with anonymous authentication using a secret ID with Elliptic Curve Cryptography (ECC), followed by an intrusion detection algorithm for users flagged as suspicious activity. …”

ROC curve of the proposed model. by Khondokar Oliullah (21553289)

“…In this paper, we incorporate a two-step authentication process, starting with anonymous authentication using a secret ID with Elliptic Curve Cryptography (ECC), followed by an intrusion detection algorithm for users flagged as suspicious activity. …”

Fog-IoT architecture. by Khondokar Oliullah (21553289)

“…In this paper, we incorporate a two-step authentication process, starting with anonymous authentication using a secret ID with Elliptic Curve Cryptography (ECC), followed by an intrusion detection algorithm for users flagged as suspicious activity. …”

Computational cost of the proposed approach. by Khondokar Oliullah (21553289)

“…In this paper, we incorporate a two-step authentication process, starting with anonymous authentication using a secret ID with Elliptic Curve Cryptography (ECC), followed by an intrusion detection algorithm for users flagged as suspicious activity. …”

Confusion Matrix of different ML models. by Khondokar Oliullah (21553289)

“…In this paper, we incorporate a two-step authentication process, starting with anonymous authentication using a secret ID with Elliptic Curve Cryptography (ECC), followed by an intrusion detection algorithm for users flagged as suspicious activity. …”

Performance metrics of applied ML models. by Khondokar Oliullah (21553289)

“…In this paper, we incorporate a two-step authentication process, starting with anonymous authentication using a secret ID with Elliptic Curve Cryptography (ECC), followed by an intrusion detection algorithm for users flagged as suspicious activity. …”

Archive containing manufacturing files. by Julian Bigge (22331861)

“…<div><p>In this paper we propose the Hatching-Box, a novel in situ imaging and analysis system to automatically monitor and quantify the developmental behavior of <i>Drosophila melanogaster</i> in standard rearing vials and during regular rearing routines, reducing the need for explicit experiments.This is achieved by combining custom tailored imaging hardware with dedicated detection and tracking algorithms, enabling the quantification of larvae, filled/empty pupae and flies over multiple days. …”

Landscape Change Monitoring System (LCMS) Puerto Rico USVI Annual QA Bits by U.S. Forest Service (17476914)

“…</p><p>Predictor layers for the LCMS model include outputs from the LandTrendr and CCDC change detection algorithms and terrain information. These components are all accessed and processed using Google Earth Engine (Gorelick et al., 2017). …”

Landscape Change Monitoring System (LCMS) Hawaii Annual Landcover by U.S. Forest Service (17476914)

“…</p><p>Predictor layers for the LCMS model include outputs from the LandTrendr and CCDC change detection algorithms and terrain information. These components are all accessed and processed using Google Earth Engine (Gorelick et al., 2017). …”

Landscape Change Monitoring System (LCMS) Alaska Most Recent Year of Gain (Image Service) by U.S. Forest Service (17476914)

“…</p><p>Predictor layers for the LCMS model include outputs from the LandTrendr and CCDC change detection algorithms and terrain information. These components are all accessed and processed using Google Earth Engine (Gorelick et al., 2017). …”

Landscape Change Monitoring System (LCMS) Hawaii Annual Landuse by U.S. Forest Service (17476914)

“…</p><p>Predictor layers for the LCMS model include outputs from the LandTrendr and CCDC change detection algorithms and terrain information. These components are all accessed and processed using Google Earth Engine (Gorelick et al., 2017). …”

Landscape Change Monitoring System (LCMS) Alaska Annual QA Bits by U.S. Forest Service (17476914)

“…</p><p>Predictor layers for the LCMS model include outputs from the LandTrendr and CCDC change detection algorithms and terrain information. These components are all accessed and processed using Google Earth Engine (Gorelick et al., 2017). …”

Landscape Change Monitoring System (LCMS) Hawaii Most Recent Year of Gain (Image Service) by U.S. Forest Service (17476914)

“…</p><p>Predictor layers for the LCMS model include outputs from the LandTrendr and CCDC change detection algorithms and terrain information. These components are all accessed and processed using Google Earth Engine (Gorelick et al., 2017). …”

Landscape Change Monitoring System (LCMS) Conterminous United States Year of Highest Probability of Gain (Image Service) by U.S. Forest Service (17476914)

“…</p><p>Predictor layers for the LCMS model include outputs from the LandTrendr and CCDC change detection algorithms and terrain information. These components are all accessed and processed using Google Earth Engine (Gorelick et al., 2017). …”

Landscape Change Monitoring System (LCMS) Puerto Rico USVI Annual Landcover by U.S. Forest Service (17476914)

“…</p><p>Predictor layers for the LCMS model include outputs from the LandTrendr and CCDC change detection algorithms and terrain information. These components are all accessed and processed using Google Earth Engine (Gorelick et al., 2017). …”

Landscape Change Monitoring System (LCMS) Hawaii Annual Change by U.S. Forest Service (17476914)

“…</p><p>Predictor layers for the LCMS model include outputs from the LandTrendr and CCDC change detection algorithms and terrain information. These components are all accessed and processed using Google Earth Engine (Gorelick et al., 2017). …”