Abstract: A method and system for producing electronic label are disclosed. The electronic label includes a first substrate and a second substrate. Layout information associated with the electronic label is developed. The layout information is automatically processed to develop print commands, circuit layout information, and component placement information therefrom. Information is printed on the first substrate in accordance with the print information and a conductive trace is deposited on the second substrate in accordance with circuit layout information. Components are placed on the deposited conductive trace in accordance with the component placement information.

Abstract: Provided is a card with a built-in electronic component, which has a superior button click sensation. A card of the present invention into which is built-in a module substrate upon which an electronic component has been disposed is provided with: a front cover sheet stacked upon a side above the module substrate; an adhesion layer adhering between the module substrate and the front cover sheet; and a dome switch which is disposed upon the module substrate, and by way of the card upper surface being pressed, the switch's movable portion deforms to the module substrate side so that the electrical contact comes into tactile contact with the module substrate in order to operate the card; wherein the switch's movable portion is such that the upper surface does not adhere to the adhesion layer and the deformation to the module substrate side is unrestrained with respect to the adhesion layer.

Abstract: An RFID tag assembly and method of use with a RFID tag assembly the RFID tag assembly includes an RFID tag having a mounting substrate having a spacer with a first surface and an opposing second surface, the spacer having a predetermined thickness, a mounting carrier with a substantially planar body with a first portion having first and second ends with two sides defined therebetween and has two or more second portions extending from the body forming free ends each and having selectively attachable adhesive on a portion of the bottom surface being deformably attached to the first portion and with second surface attached to the top surface of the first portion with the first planar surface with the RFID tag position parallel and set apart above the top surface of the carrier at a distance equal to or greater than the predetermined thickness.

Abstract: A non-contact data receiving/transmitting body is provided which includes an IC chip, a first antenna to which the IC chip is connected, and a second antenna for use as a booster that resonates with the first antenna in a non-contact manner. The first antenna is a ring-shaped antenna having at least three straight portions. The second antenna has a central portion that is bent such that parts of the central portion extend respectively along the three straight portions of the first antenna and are at an angle equal to or greater than 90° to each other. The IC chip is provided on the three straight portions of the first antenna and is connected to the first antenna at the straight portions.

Abstract: A radio IC device includes an electromagnetic coupling module includes a radio IC chip arranged to process transmitted and received signals and a feed circuit board including an inductance element. The feed circuit board includes an external electrode electromagnetically coupled to the feed circuit, and the external electrode is electrically connected to a shielding case or a wiring cable. The shielding case or the wiring cable functions as a radiation plate. The radio IC chip is operated by a signal received by the shielding case or the wiring, and the answer signal from the radio IC chip is radiated from the shielding case or the wiring cable to the outside. A metal component functions as the radiation plate, and the metal component may be a ground electrode disposed on the printed wiring board.

Abstract: An apparatus comprising: one or more cells, each cell comprising: a proton conductor (25) configured to conduct proton charge carriers; an electron conductor region (26) configured to conduct electrons; a first electrode (27) associated with one of the proton conductor region (26) and the electron conductor region (26); and a second electrode (28) associated with the other of the proton conductor region (25) and the electron conduction region (26); an antenna (50), wherein at least a portion of the antenna (50) is configured to provide at least some of the first electrode(s) (27) of the one or more cells; and circuitry (80) configured to be powered via second electrode(s) (28) of the one or more cells in electrical parallel, wherein the circuitry (80) is configured to operably connect to the antenna (50).

Abstract: Embodiments of the present invention provide an artificial neural network system for feature pattern extraction and output labeling. The system comprises a first spiking neural network and a second spiking neural network. The first spiking neural network is configured to autonomously learn complex, temporally overlapping features arising in an input pattern stream. Competitive learning is implemented as spike timing dependent plasticity with lateral inhibition in the first spiking neural network. The second spiking neural network is connected with the first spiking neural network through dynamic synapses, and is trained to interpret and label the output data of the first spiking neural network. Additionally, the labeled output of the second spiking neural network is transmitted to a computing device, such as a central processing unit for post processing.

Abstract: A system and method are described for predicting road friction using data from a fleet of connected vehicles. Each fleet vehicle includes a communication arrangement for reporting, to a back end system, floating car data sets, including a position of the vehicle, time data and data regarding determined road friction influencing parameters and a determined road friction associated with that position. The data sets are collected and aggregated in a central database, over a predetermined time period. A neural network computer is trained and validated, using aggregated data sets, to create a model to predict future road friction for a specific road network position or segment associated with that specific position. Once trained and validated, the neural network computer, upon receiving the same type of new, up to date, input data, uses the model to predict future road friction for that specific position or segment of the road network.

Abstract: A programmable architecture specialized for convolutional neural networks (CNNs) processing such that different applications of CNNs may be supported by the presently disclosed method and apparatus by reprogramming the processing elements therein. The architecture may include an optimized architecture that provides a low-area or footprint and low-power solution desired for embedded applications while still providing the computational capabilities required for CNN applications that may computationally intensive, requiring a huge number of convolution operations per seconds to process inputs such as video streams in real time.

Abstract: A neural logic unit network acting as an agent to achieve machine or device consciousness and intent is disclosed. More specifically, an agent of consciousness and intent (The Agent) is disclosed consisting of neuronal logic units upon which are mapped and connected to the individual outputs of the host system's entire sensorium and which neuronal logic units are activated by the simultaneous presentation of the results of the host system's recognition, tracking, analyses and characterization computations similar to those performed by biological unconscious brains. The embodiment of the assembly of neural logic units is referred to as Hyper Aware Logic.

Abstract: Embodiments of the present invention provide an automated image tagging system that can predict a set of tags, along with relevance scores, that can be used for keyword-based image retrieval, image tag proposal, and image tag auto-completion based on user input. Initially, during training, a clustering technique is utilized to reduce cluster imbalance in the data that is input into a convolutional neural network (CNN) for training feature data. In embodiments, the clustering technique can also be utilized to compute data point similarity that can be utilized for tag propagation (to tag untagged images). During testing, a diversity based voting framework is utilized to overcome user tagging biases. In some embodiments, bigram re-weighting can down-weight a keyword that is likely to be part of a bigram based on a predicted tag set.

Abstract: Systems and methods for providing a predictive framework are provided. The predictive framework comprises plural neural layers of adaptable, executable neurons. Neurons accept one or more input signals and produce an output signal that may be used by an upper-level neural layer. Input signals are received by an encoding neural layer, where there is a 1:1 correspondence between an input signal and an encoding neuron. Input signals for a set of data are received at the encoding layer and processed successively by the plurality of neural layers. An objective function utilizes the output signals of the topmost neural layer to generate predictive results for the data set according to an objective. In one embodiment, the objective is to determine the likelihood of user interaction with regard to a specific item of content in a set of search results, or the likelihood of user interaction with regard to any item of content in a set of search results.

Abstract: Disclosed herein is a deep learning model that can be used for performing speech or image processing tasks. The model uses multi-task training, where the model is trained for at least two inter-related tasks. For face detection, the first task is face detection (i.e. face or non-face) and the second task is facial feature identification (i.e. mouth, eyes, nose). The multi-task model improves the accuracy of the task over single-task models.

Abstract: A method and apparatus for generating a training model based on feedback are provided. The method for generating a training model based an feedback, includes calculating an eigenvector of a sample among a plurality of samples; obtaining scores granted by a user for one or more of the plurality of samples in a round, obtaining scores granted by the user for a first number of samples; obtaining scores granted by the user for a second number of samples in response to detecting, based on the eigenvector, an inconsistency between the scores granted by the user for the first number of samples; and generating a training model based on the scores granted by the user for the first and second numbers of samples. A corresponding apparatus is also provided.

Abstract: An apparatus for generating the weight estimation model includes a training data collection unit that collects training data, the training data including skin spectrum information and weight information of a plurality of objects, and a model generation unit that generates the weight estimation model, used for a spectrum-based weight estimation, through machine learning based on the collected training data.

Abstract: Systems, apparatuses, and methods for the automated detection of incorrect data during a data entry process or detecting incorrect data that has been entered and stored previously. In one embodiment, the invention utilizes one or more of statistical analysis or a machine learning technique (either supervised or unsupervised) in order to identify potentially incorrect data.

Abstract: This invention relates to a system, method and computer program product for determining which anytime technique is the most efficient at solving an anytime problem using a first anytime technique and a second anytime technique to determine a first and a second plurality of solutions, respectively, wherein each of the first and the second the plurality of solutions includes a value and an associated computation time, respectively, and each of the first and the second plurality solutions including a minimized value and associated computation time, respectively. Determining a set of delta value ordinates and computation time ordinates. Determining a representative value ordinate and representative computation time ordinate. Determining an efficient anytime technique.

Abstract: A processing device executes a multi-threaded rule engine having multiple threads. A first thread is associated with user interactions. A second thread is associated with timing events. A third thread is associated with asynchronous execution of the rule engine. A rule engine core is accessible to the second and third threads. The processing device receives user input and generates a first command to perform a first action in view of the user input while executing the first thread. The processing device stores the first command in a queue where the first command is one of multiple commands stored in the queue. The processing device retrieves the multiple commands from the queue and processes the multiple commands using the rule engine core while executing the third thread. The rule engine core is inaccessible to the second thread while in use by the third thread.

Abstract: Mechanisms are provided for monitoring quality and correctness of content in communications handled by a vendor. The mechanisms sample a set of communications handled by the vendor to generate a sample set of communications and extract content from the sample set of communications. The mechanisms compare the extracted content with expected content of communications handled by the vendor and analyze the extracted content and the expected content to thereby identify differences between the extracted content and the expected content based on results of the analysis. In addition, the mechanisms determine a level of significance of the differences and generate a notification of whether or not to modify the communications, or an operation of the vendor, based on the determined level of significance of differences.

Abstract: Method for configuring an apparatus or method for prediction of a malfunction of a unit, includes providing components of the unit; providing single malfunctions for each component; providing probabilities for the single malfunctions of each component; providing a parameter of each component for each single malfunction of this component; dividing each parameter into discrete value states; providing values of the parameters; determining a transition matrix for each parameter on the basis of the measurements of this parameter, wherein the transition matrix includes for the plurality of discrete value states of each parameter the probabilities to switch from one of the discrete value states to another of the discrete value states within a certain time period; determining the probabilities of the discrete value states on the basis of the measurements of the parameters; and providing the conditional probabilities of the discrete value states given the corresponding single malfunction.

Abstract: Predicting a malfunction of a component of a unit includes providing a transition matrix of a parameter of the component, wherein the transition matrix includes for a number of discrete value states of the parameter probabilities to switch from one discrete value state to another within a certain time period; providing the conditional probability distribution for the malfunction given the discrete value states; providing a current discrete value state of the parameter; determining a conditional probability distribution of the discrete value states given the current discrete value state for a future point in time based on the current discrete value state and on the transition matrix by use of a Markov chain; and determining a probability for the malfunction for the future point in time based on the conditional probability distribution of the discrete value states for the future point in time and the conditional probability distribution for the malfunction.

Abstract: Techniques are disclosed herein for making predictions with respect to how content consumers will interact with a digital asset. For example, in the context of website visitors browsing digital assets provided via a website, web traffic data can be collected and modeled using a belief network. The belief network may represent a probability distribution for a set of variables that define the web traffic data. Examples of such variables include browser type, browsing session duration, geographic location, visitor demographic characteristics, and a browsing outcome. Certain of the embodiments disclosed herein can be used to extract knowledge from the belief network, thereby allowing statistical inferences to be drawn with respect to how certain classes of website visitors will interact with the website. The influence of one or more first variables (for example, geographic location) can be quantified with respect to one or more second variables (for example, the successful result indicator).

Abstract: An analytic rule generation application is integrated into an electronic customer technical support system to enable those using the customer technical support center systems to build custom analytic rules, on demand, for use in diagnosing and detecting issues at customer process plant sites, without having to submit a request to a developer and wait for one or more new rules to be provided in future releases of the customer technical support system. The analytic rule builder can be used by local offices and local technology groups if need be, or can be used by personnel at customer sites. The custom analytic rules created using the rule builder application can be shared among the engineers using the electronic customer technical support system to empower local engineers to immediately use newly created rules.

Abstract: According to one exemplary embodiment, a method for adjusting taste balance in culinary recipes is provided. The method may include receiving a template recipe, and a new recipe. The method may include determining a first taste profile corresponding with the template recipe. The method may include determining a second taste profile corresponding with the new recipe. The method may include identifying a taste to boost based on comparing the first taste profile to the second taste profile. The method may include determining a boosting ingredient from a substitution ingredients list. The method may include determining a boosting ingredient quantity based on the boosting ingredient and comparing the first taste profile to the second taste profile. The method may include determining a step alteration for the new recipe based on the boosting ingredient and the boosting ingredient quantity.

Abstract: A method is provided for scalable supervised high-order parametric embedding for big data visualization. The method is performed by a processor and includes receiving feature vectors and class labels. Each feature vector is representative of a respective one of a plurality of high-dimensional data points. The class labels denote classes for the high-dimensional data points. The method further includes multiplying each feature vector by one or more factorized high-order tensors to obtain respective product vectors. The method also includes performing a maximally collapsing metric learning on the product vectors using learned synthetic exemplars and learned high-order filters. The learned high-order filters represent high-order embedding parameters.

Abstract: A method and system for classifying input data arrived one by one in time, is provided including: a) respectively training a group of classifiers with a predetermined number with recent or previous input data whose real classes are obtained as learning samples, wherein a number of the recent input data are increased progressively in reverse chronological order; b) selecting the classifier having the highest accuracy on the recent input data from the group of classifiers based on recent classifying results of the group of classifiers; and c) classifying current input data using the selected classifier.

Abstract: A method of classifying machine alarms produced by a machine monitoring system may include: Collecting a plurality of machine alarms from the machine monitoring system, the machine alarms being indicative of out-of-range machine system parameters; collecting a plurality of alarm annotations associated with at least some of the machine alarms; grouping the plurality of machine alarms by criticality; determining a strength of alarm annotations; and developing an alarm classification policy for machine alarms based at least on the criticality of the alarms and the strength of the alarm annotations.

Abstract: The present disclosure provides a new scalable coordinate descent (SCD) algorithm and associated system for generalized linear models whose convergence behavior is always the same, regardless of how much SCD is scaled out and regardless of the computing environment. This makes SCD highly robust and enables it to scale to massive datasets on low-cost commodity servers. According to one aspect, by using a natural partitioning of parameters into blocks, updates can be performed in parallel a block at a time without compromising convergence. Experimental results on a real advertising dataset are used to demonstrate SCD's cost effectiveness and scalability.

Abstract: Methods and systems for developing a behavioral index model are described. According to various embodiments, the system accesses a set of behavioral data stored in association with a set of member profiles. The system generates a set of training data from the set of behavioral data and generates a set of feature vectors from the set of training data. The system generates a behavioral index model from the set of training data and the set of feature vectors. The system then generates a tuned behavioral index model from the behavioral index model by tuning a threshold of the behavioral index model using a precision recall curve.

Abstract: A computing device determines a kernel parameter value for a support vector data description for outlier identification. A first candidate optimal kernel parameter value is computed by computing a first optimal value of a first objective function that includes a kernel function for each of a plurality of kernel parameter values from a starting kernel parameter value to an ending kernel parameter value using an incremental kernel parameter value. The first objective function is defined for a SVDD model using observation vectors to define support vectors. A number of the observation vectors is a predefined sample size. The predefined sample size is incremented by adding a sample size increment. A next candidate optimal kernel parameter value is computed with an incremented number of vectors until a computed difference value is less than or equal to a predefined convergence value.

Abstract: A system and method for analyzing aircraft operation and maintenance history in light of maintenance reports, aircraft type system failure history, health management reports, and aircraft exterior structural conditions to produce a real time recommendation regarding aircraft maintenance and dispatch. A visual inspection report is generated by capturing a real time image of an exterior of the aircraft, inverting the real time image, superimposing the real time image on a previous image of the aircraft exterior, and detecting any variation on the combination of superimposed inverted image on the previous image of the aircraft exterior. Aircraft type historical systems failure reports are analyzed to identify any predictive latent system failure of the aircraft based on the aircraft type historical systems failure report and aircraft operation history and maintenance history.

Abstract: A key ingredient in the design and development of enterprise software systems is a precise description of the business endeavor. In practice the engineering designs for corporate systems are surprisingly poorly articulated due to the difficulty organisations face in clearly defining their business needs in a structured and unambiguous manner. One problem is that the notations used in business process specifications are technical in nature, notoriously complex and not particularly intelligible to business stakeholders. There is a constant disconnect between the fluid, evolving nature of business strategies and the brittle, rigid nature of process automation. This invention provides a method and corresponding system design for addressing these limitations by articulating a business endeavor in a comprehensive, structured conceptual model that is independent of underlying technology and responsive to the dynamics of business strategy.

Abstract: Among other things, information is obtained by computer about Internet-related assets of organizations. The information is used to identify relationships between the organizations with respect to the assets. The information about the identified relationships is made available for display or analysis or both.

Abstract: The present disclosure provides techniques for calculating an entity's cybersecurity risk based on identified relationships between the entity and one or more vendors. Customer/vendor relationships may impact the cybersecurity risk for each of the parties involved because a security compromise of a downstream or upstream provider can lead to a compromise of multiple other companies. For example, if organization A uses B (e.g., a cloud service provider) to store files, and B is compromised, this may lead to organization A being compromised (e.g., the files organization A stored using B may have been compromised by the breach of B's cybersecurity). Embodiments of the present disclosure further provide a technique for calculating a cybersecurity risk score for an organization based on identified customer/vendor relationships.

Abstract: Among other things, information is obtained by computer about Internet-related assets of organizations. The information is used to identify relationships between the organizations with respect to the assets. The information about the identified relationships is made available for display or analysis or both.

Abstract: Techniques are provided that produce a risk profile consisting of a risk score and trends of risk scores across devices and sensors in a machine-to-machine (M2M) or Internet of things (IOT) environment. For example, a device is assigned a risk score which is based on baseline factors such as expected network packets between two devices, normal network packets, access to critical devices, authorized access requests from one device to another device, normal communications to a device, and the critical ports of a device; access to and conflicts across physical, logical, and operational systems; historical and current usage of these systems, and anomalies from normal behavior patterns. Techniques encompass risk management by computing a risk score in a timely fashion in accordance with an architecture that enables achieving the required scaling necessitated by the huge number of devices in the machine-to-machine (M2M) or Internet of things (IOT) environment.

Abstract: A system and methods for generating an interaction-weighted visualization of an organization or group, with the relationships between members being based on or weighted by the amount, type, degree, or significance of interactions between them and the flow of communications between members, etc. In some embodiments, this may have the form of a tree structure with nodes representing employees being connected by branches. The size, color, or number of branches may indicate characteristics of the interactions between the connected nodes (e.g., the frequency, importance, or topic of the interactions, etc.). For some purposes this provides a more accurate and realistic view of how information and communications move within an organization. It may also be used to provide insight into the strength of certain relationships, the degree of involvement of certain people or groups in implementing policies or in making decisions, or the relative importance of certain communication channels.

Abstract: A more effective real time visual representation of the factors and parameters in a timeline that is involved in executing an overall process. Such a process may be a typically be a manufacturing process, but the process may be any in which materials and resources are used to produce an end product. In one embodiment, a computer-based system and computer-implemented method are directed to a generating a dynamic graphical representation or user interface that depicts a time-ordered sequence of sub-processes and parameters associated with those sub-processes.

Abstract: Embodiments of the invention operate to determine an optimal or more optimal way in which an order for multiple items or services is fulfilled by an organization. This is performed by considering the possible combinations or permutations of order elements, costs, warehouse locations and inventory levels, delivery channels, etc. in a specified manner or order of operations. The resulting fulfillment schedule may involve a reduction or minimization in the cost, delivery time, number of shipments, distance of pick-up from customer, or another characteristic of importance to either a vendor or to a customer.

Abstract: Systems and methods for enabling a user of a multi-tenant, cloud-based, business-data-processing platform to define one or more custom transactions. Custom transactions provide the power and flexibility for an enterprise resource planning (ERP) system to satisfy varying requirements of national/international markets that have and often require additional transaction types to cover aspects of business activity that have an ERP impact. The systems and methods directed to custom transactions provide a mechanism by which a multi-tenant, business-data-processing platform's core ERP functions and workflow can be extended in a seamless, scalable, sustainable manner to address vertical, international compliance, or customer-specific needs, while maintaining ERP integrity and a business document approach to transactions.

Abstract: An information processing apparatus determines human task counts each representing a number of human tasks in individual workflows. Each workflow defines a procedure of tasks to be performed on a device under management, where the tasks include human tasks to be performed by humans and automated tasks to be executed automatically with remote control via a network. The information processing apparatus then determines priorities of the workflows, based on the human task counts determined therefor, for prioritized use of a connection that is established to communicate with the device under management in order to perform automated tasks thereon.

Abstract: Certain example embodiments relate to techniques for improving business processes. A model object repository stores aspects, modeled as respective objects, of the business processes.

Abstract: A system and method for a process performed on a computer for constructing recommendation-based predictive models is disclosed. The system and methods access a collection of data records comprising a composite numerical representation of a primary performance indicator or PPI. The PPI comprises an ordinal data point having a calculated ordinal data level. A set of key drivers are determined having an influence on the PPI. Each of the key drivers comprises an ordinal data point having a calculated ordinal data level. An ordinal logistical regression is utilized to calculate the probability of increasing the PPI if each of the members of the set of key drivers are independently increased by a single ordinal data level. A recommended action from a user customizable candidate set of recommendations corresponding to the key driver having the highest probability of increasing the PPI is provided.

Abstract: An automated method and system for delivering items by connecting delivery persons with buyers and sellers. The delivery system substitutes human labor with software and automates the dispatching, including utilizing a driver polling system to assign deliveries to available drivers. The system may be applied to temporary or hourly shift workers across different industries to assign schedules and poll workers as to their availability.

Abstract: A system collects and manages sets of asset data that are indicative of operational performance of physical assets disposed at multiple physical locations in a plant. The system includes a database that associates each set of asset data to (1) a location at which the data was collected, (2) the asset for which the data was collected, and (3) the monitoring device that was used to collect the data. In this way, each location has its own history of all asset data ever collected on all assets disposed at that location, and its own history of all monitoring devices used to collect data at that location. Also, each asset has its own history of all asset data collected on that asset at all locations at which it was disposed and for all monitoring devices. This sort of asset data is referred to herein as multi-referenced data.

Abstract: The appearance of a properly-configured display that includes a plurality of discrete components is specified and then at least one image is formed that includes the appearance of the properly-configured display. The image (or images) and corresponding information regarding the discrete loose components is provided to a retail shopping facility and used in conjunction with a mobile camera-equipped device to visually overlay the image over a view of a display to thereby facilitate comparing the display with the appearance of a properly-configured display.

Abstract: A driver computer transmits notifications of arrival at destinations and possibly other notifications indicating departure or other actions. Based on these notifications the drop off delay required to make the delivery is estimated. The drop off delays for a destination are combined to arrive at a drop off estimate. The estimated arrival time at a destination in a route is then calculated as the estimated travel times to and between preceding destinations plus the drop off estimates for the preceding destinations. Drop off estimates may include a range of likely drop off times such that the estimated arrival time includes arrange of likely arrival times. The estimated arrival time is transmitted to recipients of the deliveries. The estimated arrival time may be updated based on actual delivery times and the updated arrival time transmitted to the recipients.

Abstract: A control circuit dynamically controls the routing of an autonomous package-delivery terrestrial vehicle configured to simultaneously carry a plurality of packages be variously delivered to a plurality of different address to accommodate a disrupted delivery of at least one of the plurality of packages. The disruption of a delivery can be detected, for example, as a function of a passage of time and/or a message from an intended recipient of at least one of the plurality of packages. Per these teachings, the control circuit can route the vehicle to a different one of the plurality of different addresses to effect delivery of a second one of the plurality of packages followed by routing the vehicle back to the first delivery address to complete the delivery that had been previously disrupted.

Abstract: An assigned endoscope information holding unit holds preferential endoscope information on an endoscope to be preferentially assigned to a doctor. An endoscope assignment unit determines an endoscope to be assigned to an endoscopic examination, based on the preferential endoscope information held in the assigned endoscope information holding unit and the information on a doctor of an endoscopic examination that the examination schedule management unit manages. A history recording unit records usage history information on an endoscope used in the performed endoscopic examination, and a display processing unit displays the usage history information on a plurality of endoscopes in a comparable format.

Abstract: An embodiment herein provides a blockchain configured crowdsourced initiatives exchange ecosystem that includes a plurality of computing terminals associated with respective plurality of innovators which serve as sources of initiatives identified as innovations and respective sub-innovations. The ecosystem includes a distributed trusted ledgers system, a computing device communicatively connected to the plurality of computing terminals and configured to access the plurality of computing terminals and monitor the innovations, and a processing circuit that includes an initiatives tracking device that tracks the innovations associated with the plurality of computing terminals. The processing circuit includes a central initiatives management device.