Abstract: The generating of actionable recommendations for tuning model metrics of an Artificial Intelligence (AI) system includes partitioning a key performance indicator (KPI) range associated with a target system into a plurality of buckets. Log data including at least one KPI of the target system and one or more AI model metrics is partitioned and distributed across the plurality of buckets. For each bucket, an aggregate value of the one or more AI model metrics across the log data is computed and weighted according to the volume of log data in that bucket. A correlation factor between the aggregate value and a representative KPI value for each bucket is determined. A model tuning recommendation to increase ranking of the AI model metrics according to the determined correlation factor is provided to an output device and/or to the AI system for updating the one or more AI model.

Abstract: Methods, systems and computer program products for improving ground truth quality for modeling are provided. Aspects include receiving a plurality of data inputs, wherein each of the plurality of data inputs has an associated label. Aspects also include training a model based on the plurality of data inputs. Aspects also include generating a plurality of vector representations corresponding to the plurality of data inputs based on the model. Aspects also include clustering the plurality of vector representations into one or more clusters. Aspects also include identifying at least one anomalous data input based on the one or more clusters. The at least one anomalous data input can be a data input of the plurality of data inputs that is mislabeled, contributes to an ambiguous class structure or is an outlier. Aspects also include outputting a notification that provides an indication of the at least one anomalous data input.

Abstract: A technique for generating a performance prediction of a machine learning model with uncertainty intervals includes obtaining a first model configured to perform a task and a production dataset. At least one metric predicting a performance of the first model at performing the task on the production dataset is generated using a second model. The second model is a meta-model associated with the first model. At least one value predicting an uncertainty of the at least one metric predicting the performance of the first model at performing the task on the production dataset is generated using a third model. The third model is a meta-meta-model associated with the second model. An indication of the at least one metric and the at least one value is provided.

Abstract: Methods, systems and computer program products for improving ground truth quality for modeling are provided. Aspects include receiving a plurality of data inputs, wherein each of the plurality of data inputs has an associated label. Aspects also include training a model based on the plurality of data inputs. Aspects also include generating a plurality of vector representations corresponding to the plurality of data inputs based on the model. Aspects also include clustering the plurality of vector representations into one or more clusters. Aspects also include identifying at least one anomalous data input based on the one or more clusters. The at least one anomalous data input can be a data input of the plurality of data inputs that is mislabeled, contributes to an ambiguous class structure or is an outlier. Aspects also include outputting a notification that provides an indication of the at least one anomalous data input.

Abstract: The generating of actionable recommendations for tuning model metrics of an Artificial Intelligence (AI) system includes partitioning a key performance indicator (KPI) range associated with a target system into a plurality of buckets. Log data including at least one KPI of the target system and one or more AI model metrics is partitioned and distributed across the plurality of buckets. For each bucket, an aggregate value of the one or more AI model metrics across the log data is computed and weighted according to the volume of log data in that bucket. A correlation factor between the aggregate value and a representative KPI value for each bucket is determined. A model tuning recommendation to increase ranking of the AI model metrics according to the determined correlation factor is provided to an output device and/or to the AI system for updating the one or more AI model.

Abstract: A system for lubricating a pivot interface defined between adjacent components of a work vehicle may include a shaft and a shaft housing configured to receive an axial portion of the shaft such that the shaft housing is configured to rotate relative to the shaft. The system may also include an end cap installed relative to an end of the shaft housing and a sealing device configured to seal a radial gap defined between the shaft housing and the shaft at a seal location when a fluid pressure within the housing is below the seal's cracking pressure. Additionally, when the fluid pressure within the housing exceeds the cracking pressure, the sealing device may be configured to transition to an unsealed state to allow lubricant contained within the housing to flow axially between the sealing device and the shaft and be subsequently purged from the housing.

Abstract: A system for lubricating a pivot interface defined between adjacent components of a work vehicle may include a shaft and a shaft housing configured to receive an axial portion of the shaft such that the shaft housing is configured to rotate relative to the shaft. The system may also include an end cap installed relative to an end of the shaft housing and a sealing device configured to seal a radial gap defined between the shaft housing and the shaft at a seal location when a fluid pressure within the housing is below the seal's cracking pressure. Additionally, when the fluid pressure within the housing exceeds the cracking pressure, the sealing device may be configured to transition to an unsealed state to allow lubricant contained within the housing to flow axially between the sealing device and the shaft and be subsequently purged from the housing.

Abstract: A garbage collection system that needs to meet real-time requirements breaks large objects that need to be moved into a series of arraylets. The arraylets are sized such that the amount of time required to move the arraylets is bounded by a predetermined amount. The arrays are preferably uniformly represented in the header for each array with a series of arraylet pointers that indicate the location of the arraylets. Control-flow graph splitting is used to eliminate multiple tests and allow common sub-expression elimination. Strip-mining can also be used to improve the efficiency of the process.

Abstract: A method for evaluating software performance includes steps of: receiving a plurality of versions of code; selecting starting and stopping points for timing execution of the code versions; dispatching at least two of the plurality of code versions for execution; repeatedly executing the at least two code versions; recording execution times for the at least two code versions, according to the selected starting and stopping points; collecting the execution times; and processing the collected execution times. The method further includes steps of: performing a statistical analysis of the collected execution times for determining which code version is fastest; and invoking a confidence metric periodically to determine if a difference between means is statistically meaningful.

Abstract: Various non-limiting embodiments of the present invention relate to methods of processing titanium alloys wherein the alloys are subjected to deformation above the beta transus temperature (T?) of the alloys. For example, one non-limiting embodiment provides a method of processing an alpha+beta or a near-beta titanium alloy comprising deforming a body of the alloy at a first temperature (T1) that is above the T? of the alloy; recrystallizing at least a portion of the alloy by deforming and/or holding the body at a second temperature (T2) that is greater than T1; and deforming the body at a third temperature (T3), wherein T1?T3>T?; wherein essentially no deformation of the body occurs at a temperature below T? during the method of processing the titanium alloy.

Abstract: The invention comprises a point and cover assembly for a row crop header including a point; a cover coupled to the point with a hinge; a latch fixed to the cover, the latch having a first spring-loaded latch pin for pinning the cover to a first row unit, a second spring loaded latch pin for pinning the cover to a second row unit, and a member coupling the two latch pins together that is operable by one hand to release both latch pins; and a point support fixed to the cover, the point support comprising an elongate member fixed at its rear end to the cover and having an adjustable point rest at its front end for supporting the point at a plurality of different heights.

Abstract: A system, method, and computer readable medium, for automatically improving performance of, and optimizing, a program based on on-line profile data of the program and profile data (302) collected across multiple runs of the program and stored in a persistent off-line repository (114). The method includes executing a program in an execution environment. Profile data (302) is collected for the program across multiple runs thereof. The performance of the program is improved, such as by optimization of the program, based on on-line profile data of the executing program and the collected profile data in the persistent off-line repository.

Abstract: A formed article for making alloying additions to metal melts includes particles of at least one master alloy and a binder material binding the particles of the master alloy in the formed article. The binder material changes form and frees the master alloy particles when the formed article is heated to a predetermined temperature, preferably a temperature greater than 500° F. A method for making an alloy also is provided. The method includes preparing a melt comprising a predetermined quantity of a master alloy wherein the master alloy is added to the melt or the melt starting materials in the form of particles of the master alloy bound into at least one formed article by a binder material that decomposes at a predetermined temperature, preferably a temperature greater than 500° F., and releases the particles of master alloy.

Abstract: A garbage collection system that needs to meet real-time requirements breaks large objects that need to be moved into a series of arraylets. The arraylets are sized such that the amount of time required to move the arraylets is bounded by a predetermined amount. The arrays are preferably uniformly represented in the header for each array with a series of arralylet pointers that indicate the location of the arraylets. Control-flow graph splitting is used to eliminate multiple tests and allow common sub-expression elimination. Strip-mining can also be used to improve the efficiency of the process.