Knowledge Augmented Machine Learning with Applications in Autonomous Driving: A Survey

The existence of representative datasets is a prerequisite of many successful artificial intelligence and machine learning models. However, the subsequent application of these models often involves scenarios that are inadequately represented in the data used for training. The reasons for this are manifold and range from time and cost constraints to ethical considerations. As a consequence, the reliable use of these models, especially in safety-critical applications, is a huge challenge. Leveraging additional, already existing sources of knowledge is key to overcome the limitations of purely data-driven approaches, and eventually to increase the generalization capability of these models. Furthermore, predictions that conform with knowledge are crucial for making trustworthy and safe decisions even in underrepresented scenarios. This work provides an overview of existing techniques and methods in the literature that combine data-based models with existing knowledge. The identified approaches are structured according to the categories integration, extraction and conformity. Special attention is given to applications in the field of autonomous driving

Prevalence and risk factors for RBC alloantibodies in blood donors in the Recipient Epidemiology and Donor Evaluation Study‐III (REDS‐III)

Little information exists on red blood cell (RBC) alloimmunization in healthy US blood donors, despite the potential significance for donors themselves, blood recipients, and the blood center. Donor/donation data were sourced from the Recipient Epidemiology and Donor Evaluation Study-III, which contains information from four US blood centers during 2012 through 2016. Multivariable logistic regression was used to assess prevalence of positive antibody screen by donor demographics, blood type, parity, and transfusion history. More than 2 million units were collected from 632,378 donors, with 0.51% of donations antibody screen positive and 0.77% of donors having at least one positive antibody screen. The most common antibody specificities were D (26.4%), E (23.8%), and K (21.6%). Regression analysis indicated that increasing age, female sex, D-negative status, and history of transfusion and pregnancy were positively associated with a positive antibody screen. Prior transfusion history was most strongly associated with a positive antibody screen, with donors reporting a prior transfusion having a higher adjusted odds ratio (3.9) of having a positive antibody screen compared to donors reporting prior pregnancy (adjusted odds ratio, 2.0). Though transfusion was a more potent immune stimulus for RBC alloantibody formation than pregnancy, the sheer number of previously pregnant donors contributed to pregnancy being a risk factor for the majority of clinically significant RBC alloantibodies detected in females. These findings on prevalence of and risk factors for RBC antibodies may have implications for future medical care of donors and for operations at blood centers

The effect of previous pregnancy and transfusion on HLA alloimmunization in blood donors: implications for a transfusion-related acute lung injury risk reduction strategy.

BackgroundAntibodies to human leukocyte antigens (HLA) in donated blood have been implicated as a cause of transfusion-related acute lung injury (TRALI). A potential measure to reduce the risk of TRALI includes screening plateletpheresis donors for HLA antibodies. The prevalence of HLA antibodies and their relationship to previous transfusion or pregnancy in blood donors was determined.Study design and methodsA total of 8171 volunteer blood donors were prospectively recruited by six US blood centers from December 2006 to May 2007. Donors provided a detailed history of pregnancy and transfusion and a sample for HLA Class I and II antibody testing by multiantigen bead flow analysis.ResultsA total of 8171 donors were enrolled; 7920 (96.9%) had valid HLA antibody test results and 7841 (99%) of those had complete pregnancy and transfusion information. The prevalence of any HLA antibody was similar in nontransfused (n = 1138) and transfused (n = 895) men, 1.0% versus 1.7% (p = 0.16). HLA antibodies were detected in 17.3% of all female donors (n = 5834) and in 24.4% of those with a history of previous pregnancy (n = 3992). The prevalence of HLA antibodies increased in women with greater numbers of pregnancy: 1.7% (zero), 11.2% (one), 22.5% (two), 27.5% (three), and 32.2% (four or more pregnancies; p < 0.0001).ConclusionHLA Class I and Class II antibodies are detectable at low prevalence in male donors regardless of transfusion and in female donors without known immunizing events. The prevalence of HLA antibodies increases significantly with more pregnancies. These data will allow blood centers to estimate the impact of HLA antibody testing as a potential TRALI risk reduction measure

The effect of previous pregnancy and transfusion on HLA alloimmunization in blood donors: implications for a transfusion-related acute lung injury risk reduction strategy.

BackgroundAntibodies to human leukocyte antigens (HLA) in donated blood have been implicated as a cause of transfusion-related acute lung injury (TRALI). A potential measure to reduce the risk of TRALI includes screening plateletpheresis donors for HLA antibodies. The prevalence of HLA antibodies and their relationship to previous transfusion or pregnancy in blood donors was determined.Study design and methodsA total of 8171 volunteer blood donors were prospectively recruited by six US blood centers from December 2006 to May 2007. Donors provided a detailed history of pregnancy and transfusion and a sample for HLA Class I and II antibody testing by multiantigen bead flow analysis.ResultsA total of 8171 donors were enrolled; 7920 (96.9%) had valid HLA antibody test results and 7841 (99%) of those had complete pregnancy and transfusion information. The prevalence of any HLA antibody was similar in nontransfused (n = 1138) and transfused (n = 895) men, 1.0% versus 1.7% (p = 0.16). HLA antibodies were detected in 17.3% of all female donors (n = 5834) and in 24.4% of those with a history of previous pregnancy (n = 3992). The prevalence of HLA antibodies increased in women with greater numbers of pregnancy: 1.7% (zero), 11.2% (one), 22.5% (two), 27.5% (three), and 32.2% (four or more pregnancies; p < 0.0001).ConclusionHLA Class I and Class II antibodies are detectable at low prevalence in male donors regardless of transfusion and in female donors without known immunizing events. The prevalence of HLA antibodies increases significantly with more pregnancies. These data will allow blood centers to estimate the impact of HLA antibody testing as a potential TRALI risk reduction measure

Knowledge Augmented Machine Learning with Applications in Autonomous Driving: A Survey

The existence of representative datasets is a prerequisite of many successful artificial intelligence and machine learning models. However, the subsequent application of these models often involves scenarios that are inadequately represented in the data used for training. The reasons for this are manifold and range from time and cost constraints to ethical considerations. As a consequence, the reliable use of these models, especially in safety-critical applications, is a huge challenge. Leveraging additional, already existing sources of knowledge is key to overcome the limitations of purely data-driven approaches, and eventually to increase the generalization capability of these models. Furthermore, predictions that conform with knowledge are crucial for making trustworthy and safe decisions even in underrepresented scenarios. This work provides an overview of existing techniques and methods in the literature that combine data-based models with existing knowledge. The identified approaches are structured according to the categories integration, extraction and conformity. Special attention is given to applications in the field of autonomous driving.Comment: 93 page

A cultural theory analysis of e-government: Insights from a local government council in Malaysia

In this paper, we use the ways of life proposed by cultural theory—hierarchism, fatalism, individualism, and egalitarianism—to explain the social relations and dynamics over time, which affected the ability to implement and manage a major ICT-enabled government change initiative (e-services). This is illustrated using an in-depth case study of one local government council in Malaysia. Our analysis found culture to be evident across multiple levels, including organizational (local council), subgroup (project team, operators, user group) and individual (IT consultants) in the context of the e-services project. More specifically, various characteristics of the ways of life were salient in the e-services project, particularly during the early years—mostly, hierarchism and fatalism at the organizational and subgroup levels, and individualism at the individual level. Furthermore, the study found changes, for instance, the emergence of egalitarianism at the subgroup level over time. The paper acknowledges that in order for researchers to understand how culture influences e-government, the focus of attention needs to shift from solely concentrating on the organizational level to also understanding the dynamic and fragmented nature of culture at the group and individual levels