Abstract: Technologies for detecting minority events are disclosed. By performing a guided hierarchical classification algorithm with a decision tree structure and grouping the minority class(es) in with some of the majority classes, large majority classes may be separated from a minority class without requiring good detection of the minority events by themselves. The decision tree structure may be used only for the purpose of identifying if the data sample in question is a member of a minority class. If it is determined that it is not, a primary classification algorithm may be used. With this approach, the guided hierarchical classification algorithm need not perform as well as the primary classification algorithm for the majority events, but may provide improved detection for minority events.

Abstract: Embodiments herein relate to gas identification with a gas identification apparatus having a plurality of metal oxide semiconductor (MOS) sensors. In various embodiments, a gas identification apparatus may include a set of heterogeneous MOS sensors to provide different response patterns for the presence of different gases and an identification engine coupled with the sensors, and having a plurality of regression models and one or more artificial neural networks, to analyze a response pattern to identify presence of a gas, based at least in part on a plurality of property measurements of the MOS sensors when exhibiting the response pattern, and using one or more of the plurality of regression models and the one or more artificial neural networks. Other embodiments may be described and/or claimed.

Abstract: Embodiments herein relate to gas identification with a gas identification apparatus having a plurality of metal oxide semiconductor (MOS) sensors. In various embodiments, a gas identification apparatus may include a set of heterogeneous MOS sensors to provide different response patterns for the presence of different gases and an identification engine coupled with the sensors, and having a plurality of regression models and one or more artificial neural networks, to analyze a response pattern to identify presence of a gas, based at least in part on a plurality of property measurements of the MOS sensors when exhibiting the response pattern, and using one or more of the plurality of regression models and the one or more artificial neural networks. Other embodiments may be described and/or claimed.

Abstract: Technologies for detecting minority events are disclosed. By performing a guided hierarchical classification algorithm with a decision tree structure and grouping the minority class(es) in with some of the majority classes, large majority classes may be separated from a minority class without requiring good detection of the minority events by themselves. The decision tree structure may be used only for the purpose of identifying if the data sample in question is a member of a minority class. If it is determined that it is not, a primary classification algorithm may be used. With this approach, the guided hierarchical classification algorithm need not perform as well as the primary classification algorithm for the majority events, but may provide improved detection for minority events.

Abstract: In one embodiment, a receiver includes: a data path having a first slicer to receive and sample an incoming analog signal and to determine a bit level for the incoming analog signal, the first slicer to provide a bit decision to a consuming logic; an analysis path having a second slicer to receive and sample the incoming analog signal and to determine a second bit level for the incoming analog signal; and a controller coupled to receive an output of the first slicer and an output of the second slicer to determine a bit error rate for the data path based on the first and second slicer outputs. Other embodiments are described and claimed.