4. Software Engineering: Code and Unit Test (25 pts.) You are the software systems Engineer for the US Transportation Security Administration (TSA) project "Acquisition of New Simultaneous Explosives and Narcotics Trace Detectors". After the evaluation of multiple systems and vendors during the RFP process, the ISOSCAN 500 DT manufactured by Point Security, Inc. was selected. The specifications require a factory acceptance test (FAT) to assess the performance of the system. The code and unit testing protocol require a sample of 10,000 simulations to test the classification model. The result are summarized in the for of a confusion matrix, where true positives (IP) are 2,387, the true negatives (TN) are 4.939, the false positives (FP) or type-1 error are 721, and the false negatives (FN) or type 2 error are 1.953. The performance and functional requirements, the specific metric, and the minimum acceptance criteria are listed. Estimate the actual metrics and based o your results determine whether you accept or reject the ISOSCAN 500 DT Explain the implications of the two types of errors and which one is the most critical DONU Reference https://pointsecurityinc.com/ionscan-500dt.html https://pintucurityin.com/med/www/PDF/IONSCAN2050 GOT pdf Contusion Matrix Predicted Specification Actual Positive Negative 2387 1953 721 4939 Positive Negative Actual Specifications and Functional Requirements Metrics Accuracy: Error Rate: Sensitivity: Precision False Positive Rate: Specificity: F1 Score: >70% 50% >75% 85% >50% 4. Software Engineering: Code and Unit Test (25 pts.) You are the software systems Engineer for the US Transportation Security Administration (TSA) project "Acquisition of New Simultaneous Explosives and Narcotics Trace Detectors". After the evaluation of multiple systems and vendors during the RFP process, the ISOSCAN 500 DT manufactured by Point Security, Inc. was selected. The specifications require a factory acceptance test (FAT) to assess the performance of the system. The code and unit testing protocol require a sample of 10,000 simulations to test the classification model. The result are summarized in the for of a confusion matrix, where true positives (IP) are 2,387, the true negatives (TN) are 4.939, the false positives (FP) or type-1 error are 721, and the false negatives (FN) or type 2 error are 1.953. The performance and functional requirements, the specific metric, and the minimum acceptance criteria are listed. Estimate the actual metrics and based o your results determine whether you accept or reject the ISOSCAN 500 DT Explain the implications of the two types of errors and which one is the most critical DONU Reference https://pointsecurityinc.com/ionscan-500dt.html https://pintucurityin.com/med/www/PDF/IONSCAN2050 GOT pdf Contusion Matrix Predicted Specification Actual Positive Negative 2387 1953 721 4939 Positive Negative Actual Specifications and Functional Requirements Metrics Accuracy: Error Rate: Sensitivity: Precision False Positive Rate: Specificity: F1 Score: >70% 50% >75% 85% >50%