The invention is directed to characterizing a computerized system. Access key performance indicators (KPIs), for the computerized system. Each of the KPIs is a timeseries of KPI values and is categorized into one of n types. KPI values are channeled through n buffer channels. Each buffer channel buffers KPI values of one of n types. Finally, reconstructions errors are obtained by feeding initial KPI values to n respective input channels of a cognitive model, implemented as an autoencoder by a trained neural network including an encoder and a decoder. Encoder has temporal convolutional layer blocks connected by each input channel. Decoder has deconvolution layer blocks connected by encoder. Initial KPI values are independently processed in n input channels, then compressed by encoder, prior to being reconstructed by decoder. Reconstruction errors are obtained by comparing reconstructed KPI values with initial KPI values. Computerized system is characterized based on reconstruction errors obtained.

Systems and methods are provided for detecting and correcting address errors in a memory system. In the memory system, a memory device generates an error-detection code based on an address transmitted via an address bus and transmits the error-detection code to a memory controller. The memory controller transmits an error indication to the memory device in response to the error-detection code. The error indication causes the memory device to remove the received address and prevent a memory operation

Techniques are described for monitoring the health of services in a computing environment such as a data center. More particularly, the present disclosure describes techniques for monitoring the health and availability of capabilities in a computing environment such as a data center by enabling alarms to be associated with the capabilities. A capability refers to a set of resources in a data center. By providing the ability to associate an alarm with a capability, the health or availability of the associated capability can be monitored or ascertained by tracking the state of the alarm associated with the capability. For example, if the alarm associated with a particular capability is triggered, it may indicate that the particular capability and the one or more resources corresponding to the particular capability are not in a healthy state. Accordingly, by monitoring alarms associated with capabilities, the health of the associated capabilities can be ascertained.

Methods, systems, and devices for reporting control information errors are described. A state of a memory array may be monitored during operation. After detecting an error (e.g., in received control information), the memory device may enter a first state (e.g., a locked state) and may indicate to a host device that an error was detected, the state of the memory array before the error was detected, and/or at least a portion of a control signal carrying the received control information. The host device may diagnose a cause of the error based on receiving the indication of the error and/or the copy of the control signal. After identifying and/or resolving the cause of the error, the host device may transmit one or more commands (e.g., unlocking the memory device and returning the memory array to the original state) based on receiving the original state from the memory device.

A design support system includes memory, a receiving unit, and an associating unit. The memory stores information on design element classification that classifies a design element included in a product, and information on design requirement classification that classifies a design requirement required for the product. The receiving unit receives technical information regarding a design trouble. The associating unit refers to technical information regarding a design trouble, received by the receiving unit, and associates a classification item in the design requirement classification to which the design trouble belongs and a classification item in the design element classification to which a design element causing the design trouble belongs with each other, along with information on a phenomenon indicating a failure status of the design element included in the technical information.

Systems and methods are provided for detecting and correcting address errors in a memory system. In the memory system, a memory device generates an error-detection code based on an address transmitted via an address bus and transmits the error-detection code to a memory controller. The memory controller transmits an error indication to the memory device in response to the error-detection code. The error indication causes the memory device to remove the received address and prevent a memory operation

A method includes receiving a histogram output from a detector sensor, and calculating a median point of a pulse waveform within the histogram. The pulse waveform has an even probability distribution over at least one quantization step of the histogram around the median point. A corresponding apparatus can include a detector sensor and a co-processor coupled to the detector sensor.

Segments of a network having connectivity issues are detected in a network environment that may include one or more cloud computing platforms. A mutual information algorithm is used to determine relevance of network element factors, a subset of factors are selected based on relevance, and clustered according to values for the subset of factors, and quality of the clusters evaluated. Various thresholds for selecting the subset of factors may be used to determine which provides improved cluster quality. An approach for performing root cause analysis of events in a network environment selects bad events for logging alerts based on whether a factor is found to distinguish bad events according to a mutual information algorithm. Events for alerts maybe aggregated based on temporal proximity or similarity. Visualization may be performed using Sankey diagrams with each column representing a factor.

A method and system that efficiently selects sensors without requiring advanced expertise or extensive experience even in a case of new machines and unknown failures. An abnormality detection system includes a storage unit for storing a latent variable model and a joint probability model, an acquisition unit for acquiring sensor data that is output by a sensor, a measurement unit for measuring the probability of the sensor data acquired by the acquisition unit based on the latent variable model and the joint probability model stored by the storage unit, a determination unit for determining whether the sensor data is normal or abnormal based on the probability of the sensor data measured by the measurement unit, and a learning unit for learning the latent variable model and the joint probability model based on the sensor data output by the sensor.

Provided are a diagnostic model generating apparatus and a diagnostic model generating method therefor. The diagnostic model generating method may comprising: extracting at least one keyword from consultation data between a user and a consultant for resolving electronic device errors; on the basis of the at least one extracted keyword, determining a diagnostic sequence between the plurality of diagnostic commands for resolving errors and a plurality of diagnostic commands; and storing a diagnostic model comprising the plurality of determined diagnostic commands and determined diagnostic sequence.