Abstract: A method includes: accessing an attack record defining actions representing a previous known attack on a second computer network; initializing an attack graph; for each action, defining a set of behaviors—analogous to the action and executable by an asset on a target network to emulate an effect of the action on the second computer network—and storing the set of behaviors in a node in the attack graph; connecting nodes in the attack graph according to an order of actions in the known attack; scheduling the asset to selectively execute analogous behaviors stored in the set of nodes in the attack graph; accessing alerts generated by a set of security tools deployed on the target network; and characterizing vulnerability of the target network based on alerts, in the set of alerts, indicating detection and prevention of behaviors executed by the asset according to the attack graph.

Abstract: Diffing subject and comparison traces. A first call tree representing function calls made by a first executable entity is created based on subject trace, and a second call tree representing function calls made by a second executable entity is created based on a comparison trace. A differencing tree is created from the call trees, with differencing tree nodes indicate a differencing status between the first and second call trees. A differencing cost is assigned to each differencing tree node, based at least on the nodes' differencing status. A differencing tree node is identified based on following nodes that most contribute to differences between the first and second call trees, and it is used to provide an indicia of a difference between the first and second function calls.

Abstract: The technology disclosed herein enables a processor to receive program code comprising a plurality of program code instructions generated by a compiler in view of source code, identify, among the program code instructions, one or more optimizable instructions, wherein at least one of the optimizable instructions is associated with an execution characteristic, and the execution characteristic is associated with an optimization decision, identify a profiling instruction location associated with the at least one of the optimizable instructions, and add a profiling instruction to the program code at the profiling instruction location. The at least one profiling instruction comprises a profiling identifier, and causes the processing device to: generate a profiling information item in view of the execution characteristic of the optimizable instructions, and store the profiling information item in a persistent memory region at a memory location corresponding to the profiling identifier.

Abstract: Disclosed herein are system, method, and computer program product embodiments for replaying a large concurrency workload. The embodiments disclosed herein may be used to test the workload capacity of a database. An embodiment operates by executing a first database transaction statement to a database. The execution status of the first database transaction statement is checked and the number of work threads connecting to the database is adjusted. In an embodiment, the number of work threads used may be less than the number of sessions simulated.

Abstract: A computer program product embodied on a non-transitory computer usable medium includes a sequence of instructions causing at least one processor to execute a method of identification of useful untested states of an electronic design. A computer receives a representation of said electronic design comprised at least in part of at least one analog portion, at least one specification of said electronic design, at least one manufacturing process variation of said at least one analog portion of said electronic design and at least one functional variation of said at least one analog portion of said electronic design. At least one set of valid states delimited by one of said at least one specification, said at least one manufacturing process variation and said at least one functional variation is then generated.

Abstract: Described herein are systems, apparatus, methods and computer program products configured for componentized dashboards for data visualization. In certain embodiments, a component may be configured to be integrated within a dashboard. The component may receive data from one or more user database and provide one or more representations of the data. The component may be integrated within the dashboard as a separate component. That is, the component may provide the plurality of representations independent of the dashboard. The component may be maintained independent of the dashboard and, thus, may be updated independent of the dashboard.

Abstract: A system for generating algorithmic models comprising a function module to generate a desirability function, an automated machine learning module, and a UI module. The desirability function defines a single desirability value based on an algorithmic model accuracy criteria, criteria for algorithmic model quality, criteria for model fidelity, and criteria for the benefits and cost of model deployment. Specific hard and soft constraints regarding these and other user-defined criteria can also be specified by the user. The automated machine learning module generates an algorithmic model by training the algorithmic model against a model data set, identifying the model with the greatest desirability with respect to all criteria as combined via the desirability function. The UI module generates a user interface to display the overall desirability as well as all model criteria configured by the user. The displayed criteria and desirability are selectable and definable.

Abstract: An approach for updating one or more serverless runtime configurations based on predicting usage patterns of a serverless computing cluster is disclosed. The approach includes collecting one or more attributes associated with an application on a serverless computing cluster and a user of the application and analyzing the one or more collected attributes. Furthermore, the approach includes predicting one or more usage patterns based the analyzing and updating one or more serverless runtime configurations based on the one or more usage patterns.

Abstract: A method is disclosed for determining a conformation of a molecule on at least one degree of freedom to optimize according to at least one molecular objective function, the method comprising generating using at least one corresponding degree of freedom to optimize a connected rigid bodies representation for the molecule by identifying a plurality of groups of atoms, generating a data structure representative of the connected rigid bodies representation generating at least one neighborhood for each generated neighborhood of the at least one generated neighborhoods, generating a corresponding binary optimization problem using the data structure, providing the generated corresponding binary optimization problem to a high-performance binary optimizer, obtaining a solution from the high-performance binary optimizer; and providing at least one corresponding solution.

Abstract: Capturing dependencies between variables using a variable agnostic object is disclosed. A system is configured to obtain an indication of a first dependency of a first variable to a second variable via a programming interface and depict the first dependency, the first variable, and the second variable in a first instance of a variable agnostic object in a source code. The system is also configured to obtain an indication of a second dependency of a third variable to a fourth variable via the programming interface and depict the second dependency, the third variable, and the fourth variable in a second instance of the variable agnostic object in the source code. The system is also configured to compile the source code to generate a computer-executable program capturing the first dependency and the second dependency based on the first instance and the second instance of the variable agnostic object.

Abstract: Embodiments of the invention are directed to techniques that include predicting, by a computer system, a number of predicted opportunities and signatures of the predicted opportunities expected in a time window. Based on the signatures of the predicted opportunities, the computer system generates a listing of entities ranked according to signatures of the predicted opportunities. The computer system selects the entities to be assigned to the predicted opportunities based, at least in part, on computing capacity related to sales while accounting for any current opportunities having been assigned to the entities.

Abstract: Computer-implemented machines, systems and methods for providing insights about a machine learning model, the machine learning model trained, during a training phase, to learn patterns to correctly classify input data associated with risk analysis. Analyzing one or more features of the machine learning model, the one or more features being defined based on one or more constraints associated with one or more values and relationships and whether said one or more values and relationships satisfy at least one of the one or more constraints. Displaying one or more visual indicators based on an analysis of the one or more features and training data used to train the machine learning model, the one or more visual indicators providing a summary of the machine learning model's performance or efficacy.

Abstract: A distributed security system can include instances of a compute engine that can execute either locally in security agents on client devices or as cloud instances in a security network. Event data can be processed by elements of the distributed security system according to centrally-defined ontological definitions and/or configurations. Bounding managers of local security agents can control how much event data is sent to the security network. A storage engine in the security network can store event data received from client devices, can route event data to other elements of the security network, including cloud instances of the compute engine. An experimentation engine of the security network can also at least temporarily adjust other elements of the distributed security system during experiments or tests.

Abstract: Diffing subject and comparison traces. A first call tree representing function calls made by a first executable entity is created based on subject trace, and a second call tree representing function calls made by a second executable entity is created based on a comparison trace. A differencing tree is created from the call trees, with differencing tree nodes indicate a differencing status between the first and second call trees. A differencing cost is assigned to each differencing tree node, based at least on the nodes' differencing status. A differencing tree node is identified based on following nodes that most contribute to differences between the first and second call trees, and it is used to provide an indicia of a difference between the first and second function calls.

Abstract: Embodiments described herein provide a round-trip engineering system. During operation, the system can maintain an intermediate system representation (ISR) for a set of artifacts of a piece of software. The set of artifacts can include a piece of code and a development model. The ISR can remain persistent upon synchronization of the set of artifacts. The system can incorporate, in a respective component of the ISR, a reference to a code block in the piece of code and a corresponding element in the development model. If the system determines a first update in a first segment of a first artifact of the set of artifacts, the system can identify a second segment in a second artifact from the set of artifacts based on a corresponding component in the ISR. The system can then propagate a second update to the second segment to reflect the first update in the first segment.

Abstract: According to the invention, simulation code and production code are generated as source code from a model. The model comprises one or more blocks which specify a desired behavior of a program, in particular a control program. At least one of the blocks is marked with a simulation code attribute. Simulation code is generated for those blocks that include a simulation code attribute. Production code is generated for all other blocks. The generated source code includes both simulation code and production code. The simulation code portions are contained in the source code in a separable manner from the production code portions.

Abstract: Method and system for validating a control program for an automation system, wherein the control program is created in a first controller programming language and is arranged and setup to control an apparatus or device of the automation system when executed by an automation controller of the automation system, where the system includes a controller environment for executing the control program, an equipment simulation environment for executing a simulation program for simulating behavior of the apparatus or device or parts thereof, whereas the equipment simulation environment is communicatively coupled to the controller environment to enable and/or perform a simulation of the automation system, and whereas the simulation program is created in the first controller programming language or a second controller programming language.

Abstract: Techniques for implementing a virtual assistant using directed acyclic graphs (DAGs) are described. When a trigger event occurs (e.g., the receipt of a natural language input, the receipt of sensor data, the detection of a performed gesture, etc.), an endpoint of processing of the trigger event is determined. A DAG is then generated that represents processing of the trigger event. Generate of the DAG starts by building a portion of the DAG for the endpoint processing component, and working backward based on data dependencies. Within the DAG, one or more components that output data, but do not receive data output by another component, may be determined. Thereafter, processing of the trigger event may be commences by initiating processing of the determined one or more components.

Abstract: Examples relate to load testing. The examples disclosed herein enable obtaining lines of code that are recorded as an application is executed in a client computing device, the lines of code being recorded in chronological order of the execution; determining whether a dependency on at least one variable exists in individual lines of the lines of code; in response to determining that the dependency exists, storing the dependency in a data storage; identifying, from the lines of code, a line of code including a network call statement that calls a called variable; and eliminating a first subset of the lines of code based on the called variable and dependencies stored in the data storage, wherein a second subset of the lines of code that remain after the elimination comprises user-entered parameter data.

Abstract: Systems and methods for namespace masking in an integration flow. In order to mitigate issues arising due to application updates impacting integration flows, during the metadata generation phase, all the elements which are available for operation selection can be cloned and replaced with a new namespace. The original elements are deleted from the metadata. The systems and methods can maintain the original namespace and the element name at a predefined place in the metadata (e.g., as an attribute of the cloned Element). The cloned element in addition to all the original fields of the element, can have one additional field which will store the value of the original namespace.

Abstract: Techniques for time-series analysis for forecasting computational workloads are disclosed. A resource management system monitors a computing system and obtains metrics data from the computing system. The metrics data is stored as a set of historical data points of a data set. A first portion of the set of historical data points comprise an outlier that does not correspond to a seasonality pattern associated with a second portion of the set of historical data points. The resource management system tests a first time-series model that incorporates a first exogenous variable corresponding to a first exogeneous factor to determine that the first time-series model fits both the first portion of the set of historical data points and the second portion of the set of historical data points within an error threshold. Then, the resource management system selects the first time-series model to predict future data points of the data set.

Abstract: A light detection and ranging system includes synchronously scanning transmit and receive mirrors that scan a pulsed fanned laser beam in two dimensions. Imaging optics image a receive aperture onto an arrayed receiver that includes a plurality of light sensitive devices. A phase offset may be injected into a scanning trajectory to mitigate effects of interfering light sources.

Abstract: Data channel parameter optimization with intelligent selection of initial data channel conditions and optimization algorithm hyperparameters for use of a black box optimizer to optimize one or more data channel parameters. It is currently identified that the initial data channel condition affects the ability of a black box optimizer to optimize data channel parameters. In turn, by use of an intelligent agent (e.g., employing artificial intelligence or machine learning) to iteratively select optimized initial data channel conditions, the optimization of the data channel may be improved. Moreover, the sensitivity of the data channel parameters may be determined, which allows for identification of a subset of data channel parameters that are varied in an optimization approach. This may result in improved performance of the optimization without sacrificing optimized performance of the data channel.

Abstract: Process evolution for robotic process automation (RPA) and RPA workflow micro-optimization are disclosed. Initially, an RPA implementation may be scientifically planned, potentially using artificial intelligence (AI). Embedded analytics may be used to measure, report, and align RPA operations with strategic business outcomes. RPA may then be implemented by deploying AI skills (e.g., in the form of machine learning (ML) models) through an AI fabric that seamlessly applies, scales, manages AI for RPA workflows of robots. This cycle of planning, measuring, and reporting may be repeated, potentially guided by more and more AI, to iteratively improve the effectiveness of RPA for a business. RPA implementations may also be identified and implemented based on their estimated return on investment (ROI).

Abstract: Techniques for heterogeneous compute instance auto-scaling with reinforcement learning (RL) are described. A user specifies a reward function that generates rewards for use with an application simulation for determining what different instance types should be added to or removed from the application as part of training a RL model. The RL model can be automatically deployed and used to monitor an application to automatically scale the application fleet using heterogenous compute instances.

Abstract: An example system comprises: a master bus electrically coupled to a master multiplexer controlled by a test mode signal selecting between a master physical interface (PHY) and a slave bus of a plurality of slave buses, wherein each slave bus is electrically coupled to a respective slave multiplexer selecting between a respective slave PHY and the master bus; a plurality of electrical circuits, wherein each electrical circuit of the plurality of electrical circuits is electrically coupled to one of: the master bus or a slave bus of the plurality of slave buses; and a memory test interface electrically coupled to the master bus.

Abstract: Dynamically normalizing intervals in a table including receiving, from a client computing system, a request to normalize intervals for a data set on a cloud-based data warehouse, wherein the request comprises a reference to the data set and a data range; generating, on the cloud-based data warehouse, an interval table using the data range; joining, into a joined table on the cloud-based data warehouse, the interval table and the data set; receiving the joined table from the cloud-based data warehouse; and presenting, via a graphical user interface on the client computing system, the joined table as a worksheet.

Abstract: Computer-implemented machines, systems and methods for managing missing values in a dataset for a machine learning model. The method may comprise importing a dataset with missing values; computing data statistics and identifying the missing values; verifying the missing values; updating the missing values; imputing missing values; encoding reasons for why values are missing; combining imputed missing values and the encoded reasons; and recommending models and hyperparameters to handle special or missing values.

Abstract: Introduced here are health management platforms able to monitor changes in the health state of a subject based on the context of digital activities performed by, or involving, the subject. Initially, a health management platform can identify a physiological response by examining physiological data associated with a subject. Then, the health management platform can identify a stimulus presented by an electronic device that provoked the physiological response by examining contextual data associated with the subject. The contextual data may be in the form of a screenshot of a computer program in use by the subject during the physiological response. In some embodiments, the health management platform prompts the subject to specify whether the physiological response is a positive physiological response that resulted in an upward shift in health or a negative physiological response that resulted in a downward shift in health.

Abstract: One variation of a method for emulating a known attack on a computer network includes: generating a set of data packets by recombining packet fragments within a packet capture file representing packet fragments transmitted between machines during a prior malicious attack on a second network; defining transmission triggers for transmission of the set of data packets between pairs of agents connected to a target network based on timestamps of packet fragments in the packet capture file; initiating transmission of the set of data packets between the pairs agents according to the set of transmission triggers to simulate the malicious attack on the target network; and, in response to absence of a security event related to the simulation in a log of a security technology deployed on the target network, generating a prompt to reconfigure the security technology to respond to the malicious attack.

Abstract: The present disclosure relates to a method for use with an electronic design. Embodiments may include receiving one or more user defined processor configurations at a processor generator. Embodiments may also include generating a customized testbench based upon, at least in part, the user defined processor configurations and generating an RTL model while the customized testbench is generating.

Abstract: A method, system and computer program product for forecasting a storage requirement of a database management system (DBMS). The storage-related operations (e.g., create, delete, update) of the applications connected to the DBMS are monitored. The impact on the storage usage of the DBMS based on these storage-related operations performed by the applications is monitored. Furthermore, the applications are categorized into groups of applications based on the monitored storage-related operations. A mathematical model is then built to forecast the storage requirement of the DBMS based on the monitored impact on the storage usage of the DBMS by the monitored storage-related operations of the applications and the categorization of the applications. The storage requirement of the DBMS is then forecasted based on the built mathematical model. In this manner, the storage requirements of the DBMS may be accurately predicted to ensure that there is available storage thereby preventing performance degradation.

Abstract: A learning automaton can be trained to merge data from input data streams, optionally with different data rates, into a single output data stream. The learning automaton can learn over time from the input data streams. The input data streams can be low-pass filtered to suppress data having frequencies greater than a time-varying cutoff frequency. Initially, the cutoff frequency can be relatively low, so that the effective data rates of the input data streams are all equal. This can ensure that initially, high data-rate data does not overwhelm low data-rate data. As the learning automaton learns, an entropy of the learning automaton changes more slowly, and the cutoff frequency is increased over time. When the entropy of the learning automaton has stabilized, the training is completed, and the cutoff frequency can be large enough to pass all the input data streams, unfiltered, to the learning automaton.

Abstract: The present teaching relates to generating an updated model related to advertisement selection. In one example, a request is obtained for updating a model to be utilized for selecting an advertisement. A plurality of copies of the model is generated. The model is pre-selected based on a performance metric related to advertisement selection. Based on each of the plurality of copies, a candidate model is created by modifying one or more parameters of the copy of the model to create a plurality of candidate models. One of the plurality of candidate models is selected based on the performance metric. The steps of generating, creating, and selecting are repeated until a predetermined condition is met. The model is updated with the latest selected candidate model when the predetermined condition is met.

Abstract: A displaying method of a robot simulator for intuitively recognizing the working direction of a tool is provided. A displaying method on a robot simulator includes displaying a real image of a robot to mount a tool at an end effector of a robot arm, displaying a tool coordinate system indicating an operating direction of the tool at the end effector of the robot arm which is displayed in the displaying of the real image of the robot, displaying a virtual reality (VR) image having a three-dimension image at the end effector of the robot arm which is displayed in the displaying of the real image of the robot.

Abstract: The following description is directed to a logic repository service supporting adaptable host logic. In one example, a method of a logic repository service can include receiving a first request to generate configuration data for configurable hardware using a specification for application logic. The method can include selecting a particular host logic shell from a group of host logic shells. The particular host logic shell can be used to encapsulate the application logic when the configurable hardware is configured. Configuration data for the configurable hardware can be generated. The configuration data can include data for implementing the application logic and at least a portion of the particular host logic shell. The method can include receiving a second request to download the configuration data to a host server computer comprising the configurable hardware. The configuration data can be transmitted to the host server computer in response to the second request.

Abstract: Network management techniques are described. A controller device of this disclosure manages a device group of a network. The controller device includes processing circuitry in communication with the memory, the processing circuitry being configured to receive, using a programmable diagnosis service executed by the processing circuitry, a programming input, to form, using the programmable diagnosis service, based on the programming input, a resource definition graph that models interdependencies between a plurality of resources supported by the device group, to detect, using the programmable diagnosis service, an event affecting a first resource of the plurality of resources, and to identify, using the programmable diagnosis service, based on the interdependencies modeled in the resource definition graph formed based on the programming input, a root cause event that caused the event affecting the first resource, the root cause event occurring at a second resource of the plurality of resources.

Abstract: A processing method, rendering method and device for static components in a game scene are provided. The rendering method includes: a parent model corresponding to a plurality of static components is loaded, the parent model comprising at least two sub-models corresponding to at least two sub-components, and information of each of the at least two sub-models is recorded in a model file of the parent model; a scene global identifier of the at least one sub-model marked as hidden in the parent model is determined, wherein the scene global identifier includes identification information of each of the at least two sub-models in the game scene; and at least one sub-model not marked as hidden of the parent model is rendered in a preset manner.

Abstract: A scaling manager manages deques that track groups of preinitialized instances used to scale respective groups of active compute instances. Various techniques for deque management include a technique where a total instance quantity is preconfigured for the total number of instances assigned to both the group and the deque of preinitialized instances. As the size of the group grows for scale-ups, the size of the deque may go down. For example, the deque is not replenished when the group scales, but does expand when the group scales down. The total instance quantity may be bounded, in some examples, and an additional “buffer amount” of preinitialized instances may be implemented to provide a safety margin for burst scaling, which can be further enhanced by transferring instances between data structures of different groups of instances in some cases.

Abstract: A system includes a compute circuit that preemptively performs a computation on a data word before receiving an indication of data errors from an error checking and correction (ECC) circuit. The ECC circuit reads the data word from a memory array and performs error detection and error correction on the data word. The compute circuit reads the data word and performs the computation on the data word to generate an output value, without waiting for the ECC circuit to check and correct the data word. In response to error detection in the data word by the ECC circuit, the compute circuit delays outputting the output value until correction of the output value in accordance with the error detection by the ECC circuit.

Abstract: A system and method for flexible read-access of a set of procedures during runtime of a regulated system, the system comprising a set of procedures each defining a respective set of systematic data and an executable operation, a specialized data store configured to receive at least a subset of procedures, at least one memory including at least one set of data relating to the set of procedures, a receiving component communicatively coupled to the regulated system, and a flexible reader authorized for read-access to the specialized data store and the at least one memory.

Abstract: A method of motor control device emulation includes receiving, via a network-enabled motor control device, a communication request corresponding to an emulated motor control device. The method further includes modifying the communication request to match an expected communication request. Additionally, the method includes providing a modified communication request to an associated hardware module within the network-enabled motor control device. Further, the expected communication request is based on the network-enabled motor control device.

Abstract: A switchgear or controlgear with unmanned operation and maintenance includes: an equipment safety system that includes a steering and control system for calculating a action radius of a robot system. An acting area in an internal space of the switchgear or controlgear is divided into virtual zones. Each action in each virtual zone is precalculated predictively as a micro simulation in which actual sensor data are considered before an intended action is triggered.

Abstract: A method for performing access management of a memory device with aid of a Universal Asynchronous Receiver-Transmitter (UART) connection and associated apparatus are provided. The method may include: utilizing a UART of a memory controller within the memory device to receive a set of intermediate commands corresponding to a set of operating commands through the UART connection between the memory device and a host device, wherein before sending the set of intermediate commands to the controller through the UART connection, the host device converts the set of operating commands into the set of intermediate commands; converting the set of intermediate commands into the set of operating commands according to a command mapping table; and accessing a non-volatile (NV) memory within the memory device with the set of operating commands for the host device, and sending a response to the host device through the UART connection.

Abstract: A design inspector tool generates secure source code related to stencils and design elements of an architecture diagram. The design inspector tool may retrieve source code from a source code repository that includes source code that is relevant to the stencils and design elements implemented by the design inspector tool. When or after a user modifies the source code, the design inspector tool feeds contextual information associated with the stencils and the design elements into a trained machine learning logic. The trained machine learning logic processes the contextual information to retrieve contextually relevant auto complete secure code suggestions from the source code repository. The contextually relevant auto complete source code suggestions may be presented to the user as an option for replacing or augmenting the modified source code.

Abstract: An asset management method for a substation in accordance with the present invention generates a unique reliability model for each element of the substation by comparing reliability of a reference reliability model for each substation type with a health index of the each element thereof generated based on state data and real-time monitoring data of the each element of the substation and compensating the reference reliability model for the each element of the substation; assessing system reliability index and economic feasibility for each maintenance scenario based on a reference system reliability model for each candidate element subject to maintenance among the elements of the substation; selecting a maintenance scenario as a result of the health index and the unique reliability model for the each element of the substation, the system reliability index, and the economic feasibility and updating the unique reliability model for the each element of the substation by executing maintenance.

Abstract: A solution is proposed for resource management of a software application including a plurality of software components interacting with each other. A corresponding method includes monitoring present conditions of the software components and estimating a future consumption of one or more computing resources by each software component from the present conditions of the software components; an allocation of the computing resources to the software components is then controlled accordingly. A computer program and a computer program product for performing the method are also proposed. Moreover, a system for implementing the method is proposed.

Abstract: A system and a computer-implemented method for analyzing workflow of test automation associated with a robotic process automation (RPA) application are disclosed herein. The computer-implemented method includes receiving the workflow of the test automation associated with the RPA application and analyzing, via an Artificial Intelligence (AI) model associated with a workflow analyzer module, the workflow of the test automation based on a set of pre-defined test automation rules. The computer-implemented method further includes determining one or more metrics associated with the analyzed workflow of the test automation and generating, via the AI model, corrective activity data based on the determined one or more metrics.

Abstract: Embodiments relate to configuring artificial-intelligence (AI) decision nodes throughout a communication decision tree. The decision nodes can support successive iteration of AI models to dynamically define iteration data that corresponds to a trajectory through the tree.

Abstract: A computing device is provided, including a processor. The processor may generate a three-dimensional device model at least by receiving one or more three-dimensional substrate elements and one or more two-dimensional lithography elements. Generating the three-dimensional device model may further include generating a conformal coating on the one or more three-dimensional substrate elements over a plurality of conformal coating iterations that have respective iteration layer thicknesses. Each conformal coating iteration may include, for each two-dimensional lithography element, generating an iteration layer overlaid on the one or more three-dimensional substrate elements and having an iteration layer shape of at least a portion of that two-dimensional lithography element. Each conformal coating iteration may further include adding the iteration layer to the conformal coating.