Abstract: Techniques are described for generating period profiles. According to an embodiment, a set of time series data is received, where the set of time series data includes data spanning a plurality of time windows having a seasonal period. Based at least in part on the set of time-series data, a first set of sub-periods of the seasonal period is associated with a particular class of seasonal pattern. A profile for a seasonal period that identifies which sub-periods of the seasonal period are associated with the particular class of seasonal pattern is generated and stored, in volatile or non-volatile storage. Based on the profile, a visualization is generated for at least one sub-period of the first set of sub-periods of the seasonal period that indicates that the at least one sub-period is part of the particular class of seasonal pattern.

Abstract: The present application relates to a steam iron (10) for ironing garments. The steam iron (10) comprises a steam generator (11), an ironing plate (13) and a thermal bridge arrangement (14). The steam generator (11) comprises a main body (11A) and a heating element (12) to heat the main body (11 A). The thermal bridge arrangement (14) extends between the main body (11A) and a thermal coupling area (15) of the ironing plate (13) to heat the ironing plate (13) by conduction of heat from the main body (11A). The thermal bridge arrangement (14) comprises a first portion (16) extending in a first direction (A) away from the thermal coupling area (15) and a second portion (17) extending in a second direction (B) towards the thermal coupling area (15). This invention allows promoting steam generation operating in a high temperature for a better steam capability, while keeping a lower temperature of the ironing plate which prevents damaging garments during ironing.

Abstract: Techniques are described for classifying seasonal patterns in a time series. In an embodiment, a set of time series data is decomposed to generate a noise signal and a dense signal, where the noise signal includes a plurality of sparse features from the set of time series data and the dense signal includes a plurality of dense features from the set of time series data. A set of one or more sparse features from the noise signal is selected for retention. After selecting the sparse features, a modified set of time series data is generated by combining the set of one or more sparse features with a set of one or more dense features from the plurality of dense features. At least one seasonal pattern is identified from the modified set of time series data. A summary for the seasonal pattern may then be generated and stored.

Abstract: Techniques are described for classifying seasonal patterns in a time series. In an embodiment, a set of time series data is decomposed to generate a noise signal and a dense signal, where the noise signal includes a plurality of sparse features from the set of time series data and the dense signal includes a plurality of dense features from the set of time series data. A set of one or more sparse features from the noise signal is selected for retention. After selecting the sparse features, a modified set of time series data is generated by combining the set of one or more sparse features with a set of one or more dense features from the plurality of dense features. At least one seasonal pattern is identified from the modified set of time series data. A summary for the seasonal pattern may then be generated and stored.

Abstract: Techniques are described for classifying seasonal patterns in a time series. In an embodiment, a set of time series data is decomposed to generate a noise signal and a dense signal. Based on the noise signal, a first classification is generated for a plurality of seasonal instances within the set of time series data, where each respective instance of the plurality of instances corresponds to a respective sub-period within the season and the first classification associates a first set of one or more instances from the plurality of instances with a particular class of seasonal pattern. Based on the dense signal, a second classification is generated that associates a second set of one or more instances with the particular class. Based on the first classification and the second classification, a third classification is generated, where the third classification associates a third set of one or more instances with the particular class.

Abstract: Techniques are described for generating period profiles. According to an embodiment, a set of time series data is received, where the set of time series data includes data spanning a plurality of time windows having a seasonal period. Based at least in part on the set of time-series data, a first set of sub-periods of the seasonal period is associated with a particular class of seasonal pattern. A profile for a seasonal period that identifies which sub-periods of the seasonal period are associated with the particular class of seasonal pattern is generated and stored, in volatile or non-volatile storage. Based on the profile, a visualization is generated for at least one sub-period of the first set of sub-periods of the seasonal period that indicates that the at least one sub-period is part of the particular class of seasonal pattern.

Abstract: Techniques are described for orchestrating execution of multi-step recipes. In an embodiment, a method comprises receiving a request to execute a recipe specification that defines a sequence of steps to execute for a particular recipe; responsive to receiving the request to execute the recipe specification, instantiating a set of one or more recipe-level processes; wherein each recipe-level process in the set of one or more recipe-level processes manages execution of a respective instance of the particular recipe; triggering, by each recipe-level process for the respective instance of the particular recipe managed by the recipe-level process, execution of the sequence of steps; wherein triggering execution of at least one step in the sequence of steps by a recipe-level process comprises instantiating, by the recipe-level process, a plurality of step-level processes to execute the step on a plurality of target resources in parallel.

Abstract: Techniques are provided for eager replication of uncommitted transactions. In embodiments, a replication client receives, in a data stream, change records corresponding to database changes applied to a source database in a transaction. The change records does not include a commit record that indicates that the transaction is committed on the source database. Before receiving the commit record, the replication client computes transaction dependency data based on the change records and detects, based on the transaction dependency data, that the transaction can be at least partially applied to a target database. Also before receiving the commit record, the replication client applies, to a target database and based on the detecting, at least some of the change records. Upon receiving the commit record of the transaction, the replication client completes applying the change records and commits the transaction on the target database.

Abstract: Techniques are described herein for providing highly available and scalable cloud services. In one or more embodiments, a network service receives from a first client of a plurality of clients, a request to lease a first slice of a plurality of slices of a workload. In response, the network services assigning, to the first client, a lease for the first slice, wherein the lease expires after a lease duration. The network service then receives, from a second client of the plurality of clients, a request to lease the first slice. Based on a state associated with the first client after the lease duration, the network service reassigns the lease for the first slice to the second client. The second client processes a subset of workflow executions associated with the first slice that have not previously been processed by the first client.

Abstract: Embodiments relate to dynamically defining and visually representing worker threads. More specifically, a set of parameters is defined for each of multiple worker threads, and a dot-matrix UI represents characteristics of individual parameter across worker threads to facilitate expedient configuration.

Abstract: Embodiments relate to dynamically defining and visually representing worker threads.

Abstract: A steam iron (10) comprises a steam generator (15) having a main body portion (15a) including an electrical heating element (16) to heat the steam generator (15), and an ironing plate (13) coupled to the steam generator (15) via a thermal coupling and configured to be passively heated by conduction of heat from the steam generator (15) via the thermal coupling. The thermal coupling between the steam generator (15) and the ironing plate (13) comprises an indirect thermal path formed by a flange (22) of the steam generator (15), the flange (22) being in contact with the ironing plate (13) and being spaced from the main body portion (15a) of the steam generator (15), the flange (22) also being configured to space the main body portion (15a) of the steam generator (15) from the ironing plate (13) to restrict the conduction of heat from the main body portion (15a) of the steam generator (15) to the ironing plate (13).

Abstract: The invention relates to a system (1) for a garment care device (20, 25) comprising a steam generator (7). The system (1) comprises a pressurization unit (2). The pressurization unit (2) comprises a chamber (3) for receiving water from a water supply system (5) and for delivering the received water towards the steam generator (7), and an actuator (8) cooperating with a retention member (9). The actuator (8) is adapted to displace and load the retention member (9) when water is received in the chamber (3). The retention member (9) is adapted to unload and apply a force to the actuator (8) after water has been received in the chamber (3) to pressurize water received in the chamber (3). The retention member (9) has a stiffness coefficient that varies as a function of displacement of the actuator (8). This invention allows that the flow of pressurized water from the chamber to the steam generator is more purposively controlled so that a given desired steam profile can be generated.

Abstract: Techniques are described for characterizing and summarizing seasonal patterns detected within a time series. According to an embodiment, a set of time series data is analyzed to identify a plurality of instances of a season, where each instance corresponds to a respective sub-period within the season. A first set of instances from the plurality of instances are associated with a particular class of seasonal pattern. After classifying the first set of instances, a second set of instances may remain unclassified or otherwise may not be associated with the particular class of seasonal pattern. Based on the first and second set of instances, a summary may be generated that identifies one or more stretches of time that are associated with the particular class of seasonal pattern. The one or more stretches of time may span at least one sub-period corresponding to at least one instance in the second set of instances.

Abstract: The invention relates to domestics appliance system which makes use of a push-fit fluid coupling (1) comprising a fluid feeding portion (2) and a fluid receiving portion (3) adapted to cooperate with each other to enable fluid to flow in a downstream direction (D1) from the fluid feeding portion (2) to the fluid receiving portion (3). The fluid receiving portion (3) comprises an actuator (65) comprising a fluid conduit (67) for fluid to flow from the fluid feeding portion (2) to the fluid receiving portion (3). The fluid feeding portion (2) comprises a housing (4) defining a fluid flow path (5) and comprising an opening (6) in which the actuator (65) is intended to be inserted, a chamber (37) arranged in the housing (4) in which fluid is intended to flow, a valve seat (8) and a valve member (7) engaging the valve seat (8) for closing the fluid flow path (5), a first piston (9) slidably received in the chamber (37) downstream of the valve member (7).

Abstract: Techniques are described for characterizing and summarizing seasonal patterns detected within a time series. A set of time series data is analyzed to identify a plurality of instances of a season, where each instance corresponds to a respective sub-period within the season. A first set of instances from the plurality of instances are associated with a particular class of seasonal pattern. After classifying the first set of instances, a second set of instances may remain unclassified or otherwise may not be associated with the particular class of seasonal pattern. Based on the first and second set of instances, a summary may be generated that identifies one or more stretches of time that are associated with the particular class of seasonal pattern. The one or more stretches of time may span at least one sub-period corresponding to at least one instance in the second set of instances.

Abstract: The invention relates to a garment steaming appliance comprising a sole plate assembly (1) comprising a steam channel (6) for receiving a flow of steam, an ironing plate (3) comprising an ironing surface (4) and an opposing upper surface, wherein the steam channel (6) extends along the upper surface of the ironing plate (3), and a vent (7) extending through said ironing plate (3) from said steam channel (6) to said ironing surface (4). The steam channel (6) is configured to divide the flow of steam into multiple flow paths that reconverge above said vent (7) from different directions to control the direction of the resultant flow of steam out of said vent (7) relative to said ironing surface (4).

Abstract: The invention relates to an ironing system (20) comprising a steam iron (200) and a base unit (250) adapted to cooperate with each other such that the steam iron (200) can take a first position (P1) in which the steam iron (200) is docked on the base unit (250), and a second position (P2) in which the steam iron (200) is undocked from the base unit (250). The steam iron (200) is cordlessly detached from the base unit (250) in the second position (P2). The steam iron (200) comprises a water reservoir (201) arranged to store water, and a soleplate (202) for generating steam from water in the water reservoir (201) when the steam iron (200) is in the second position (P2). The base unit (250) comprises a water delivery mechanism (251) for supplying water to the water reservoir (201) when the steam iron (200) is in the first position (PI), and a power supply unit (252) for supplying energy to the soleplate (202) when the steam iron (200) is in the first position (P1), for heating the soleplate (202).

Abstract: Techniques are described for characterizing and summarizing seasonal patterns detected within a time series. A set of time series data is analyzed to identify a plurality of instances of a season, where each instance corresponds to a respective sub-period within the season. A first set of instances from the plurality of instances are associated with a particular class of seasonal pattern. After classifying the first set of instances, a second set of instances may remain unclassified or otherwise may not be associated with the particular class of seasonal pattern. Based on the first and second set of instances, a summary may be generated that identifies one or more stretches of time that are associated with the particular class of seasonal pattern. The one or more stretches of time may span at least one sub-period corresponding to at least one instance in the second set of instances.

Abstract: Techniques are described for modeling variations in correlation to facilitate analytic operations. In one or more embodiments, at least one computing device receives first metric data that tracks a first metric for a first target resource and second metric data that tracks a second metric for a second target resource. In response to receiving the first metric data and the second metric data, the at least one computing device generates a time-series of correlation values that tracks correlation between the first metric and the second metric over time. Based at least in part on the time-series of correlation data, an expected correlation is determined and compared to an observed correlation. If the observed correlation falls outside of a threshold range or otherwise does not satisfy the expected correlation, then an alert and/or other output may be generated.