Patent Description:
In some situations, understanding or analyzing an entity that is made up of multiple items may require understanding or analyzing a relative relationship between the items with respect to some category of interest. For example, understanding how the different regions of the human body are seen from the perspective of the brain may require understanding how richly innervated the different regions are by the brain.

The term "homunculus" is generally used to mean any representation of a small or miniature human being. For example, the homunculus may take the form of a three-dimensional physical model, a two-dimensional image, a three-dimensional computer-aided design model, or some other type of representation. A cortical homunculus is a modified version of a typical homunculus. With a cortical homunculus, the sizes of the different anatomical regions of the human body are in proportion to the amount of brain tissue associated with the anatomical regions in the sensorimotor cortex. This type of visual representation of the human body provides an understanding of how the various anatomical regions are weighted in terms of their relative significance in the human brain.

In some situations, it may be desirable to apply this concept of providing a visual representation of the relative relationship of the different anatomical regions of the human body with respect to the amount of sensorimotor cortical tissue designated for the different anatomical regions to other disciplines. Therefore, it would be desirable to have a method and apparatus that take into account the natural sensory processing and understanding capabilities of humans, as well as other possible aspects, and apply these capabilities to other disciplines.

<CIT> states in its abstract: a method and apparatus for representing sensory effects, and a computer readable recording medium storing user sensory preference metadata. A method for providing user preference information includes: receiving preference information for predetermined sensory effects from a user; and generating user sensory preference metadata including the received preference information, wherein the user sensory preference metadata includes personal preference information that describes the preference information.

<CIT>states in its abstract: importance guided image transformation. A subject image is accessed, an importance is assigned to respective features of the subject image and a scaling scheme is determined for the subject image based on the importance assigned to the respective features of the subject image. A transformed image is generated based on the determined scaling scheme and the transformed image is provided to an image presentation system for display.

<CIT>) states in its abstract: a method for displaying a marker in a map service is provided. In the method, a plurality of markers each representing information are displayed differentially in a propagation range set according to the importance of a user in the map service. When the plurality of markers are displayed overlapped, a marker representing information of highest importance is displayed uppermost.

<CIT> states, according to its abstract, a method is provided whereby combinations of ecologically valid images and sounds are used for visualization of large amounts of information. Icons and sounds are selected and combined to accentuate natural recognition of pattern information and changes. A visual field of similar icons represents a corresponding field of data sets, where the appearance of each icon illustrates the respective values of the underlying data. Within each icon, elements change in shape, size, number, color, and motion to illustrate the respective changes of data within the corresponding data set. Stereophonic sound occurrence, spatial location, type, and volume signal the user about the general situation, as well as the type and importance of individual data changes, stimulating the user's attention during events of interest.

In one aspect, an apparatus comprises a transformer. The transformer receives an entity sensory representation that represents an entity. The entity sensory representation comprises a plurality of sensory representations that represent a plurality of items that are part of the entity. Each of the plurality of items is associated with a set of values for a set of measurable factors of interest. The set of measurable factors of interest comprises a level of importance of the plurality of items. The transformer calculates a set of scale factors for each of the plurality of sensory representations based on the set of values associated with the each of the plurality of items. The transformer modifies the plurality of sensory representations using the set of scale factors to form a plurality of modified sensory representations that establish a relative relationship between the plurality of items represented by the plurality of modified sensory representations with respect to the set of measurable factors of interest. The transformer acquires the set of values continuously over time from one or more sensor systems configured to monitor the set of measurable factors of interest. The transformer adjusts the set of scale factors to update the plurality of modified sensory representations in substantially real-time as the set of values changes. The entity sensory representation represents the entity using a sense of sound. The entity sensory representation comprises an audio recording and the plurality of sensory representations comprises a plurality of sections of the audio recording comprising verbal instructions for performing a manufacturing operation. Each section represents instructions for performing a different step of the manufacturing operation. The set of scale factors is used to modify a loudness of each of the plurality of sections according to the relative importance of the manufacturing operation of each of the plurality of sections.

In another aspect, a computer-implemented method for modifying an entity sensory representation that represents an entity is provided. The entity sensory representation that represents the entity is received. The entity sensory representation comprises a plurality of sensory representations that represent a plurality of items that are part of the entity. Each of the plurality of items is associated with a set of values for a set of measurable factors of interest. The set of measurable factors of interest comprises a level of importance of the plurality of items. A set of scale factors is calculated for each of the plurality of sensory representations based on the set of values associated with the each of the plurality of items. The plurality of sensory representations is modified using the set of scale factors to form a plurality of modified sensory representations that establish a relative relationship between the plurality of items represented by the plurality of modified sensory representations with respect to the set of measurable factors of interest. The transformer acquires the set of values continuously over time from one or more sensor systems configured to monitor the set of measurable factors of interest. The transformer adjusts the set of scale factors to update the plurality of modified sensory representations in substantially real-time as the set of values changes. The entity sensory representation represents the entity using a sense of sound. The entity sensory representation comprises an audio recording and the plurality of sensory representations comprises a plurality of sections of the audio recording comprising verbal instructions for performing a manufacturing operation. Each section represents instructions for performing a different step of the manufacturing operation. The set of scale factors is used to modify a loudness of each of the plurality of sections according to the relative importance of the manufacturing operation of each of the plurality of sections.

In an illustrative example useful for understanding but not pertaining to the invention as claimed, a computer-implemented method for automating the transformation of an entity image into a transformed entity image is provided. The entity image representing an entity is received. The entity image comprises a plurality of image portions that represent a plurality of items that are part of the entity. A set of values for a set of measurable factors of interest is identified for each of the plurality of items. A set of scale factors is calculated for the each of the plurality of image portions based on the set of values associated with the each of the plurality of items. The plurality of image portions is modified using the set of scale factors identified for the each of the plurality of image portions to form a plurality of modified image portions. A position of the plurality of modified image portions is adjusted relative to each other with respect to a total display area to form the transformed entity image. The transformed entity image visually establishes a relative relationship between the plurality of items represented by the plurality of modified image portions with respect to the set of measurable factors of interest.

The illustrative embodiments recognize and take into account different considerations. For example, the illustrative embodiments recognize and take into account that it may be desirable to apply the concept of visually representing the relative relationship between the different anatomical regions of the human body with respect to their relative significance in the brain to other disciplines. In particular, the general concept of creating a visual representation that provides the relative significance between a plurality of items with respect to some factor of interest may be applied to the aerospace industry, corporate management, emergency alert systems, training programs, and any other number of disciplines or applications.

The illustrative embodiments also recognize and take into account that it may be desirable to transform a visual representation of an entity based on more than one factor of interest. Further, the illustrative embodiments recognize and take into account that it may be desirable to transform a sensory representation corresponding to some other sense other than the sense of sight. For example, transforming an audio recording such that the decibel levels of different sections of the audio recording are adjusted to reflect the relative importance between the different sections of the audio recordings may be desirable.

Additionally, the illustrative embodiments recognize and take into account that using a computer system to automate the process by which a sensory representation is transformed may reduce the time, expense, and labor associated with the transformation. For example, it may be desirable to automate the transformation process such that a same visual representation may be transformed multiple times to form multiple transformed visual representations corresponding to different factors of interest. Automating this type of process may significantly reduce the time, expense, and labor needed to create these transformed visual representations as compared to hand-drawing each of the transformed visual representations or manually calculating the needed modifications for each transformation of the visual representation.

Thus, the illustrative embodiments provide a method and apparatus for modifying an entity sensory representation that represents an entity using at least one of the five human senses. In particular, the entity sensory representation may be comprised of a plurality of sensory representations that represent a plurality of items that make up the entity. The entity sensory representation may be modified to create a transformed sensory representation that establishes a relative relationship between the plurality of items represented by the entity sensory representation with respect to a set of measurable factors of interest.

For example, the transformed entity sensory representation may establish the relative significance of the plurality of items in a manner that can be easily understood. When the transformed entity sensory representation is a transformed entity image, the transformed entity image may provide, at a glance, the relative significance of the plurality of items in a manner that can be easily recognized. In some cases, the transformed entity image may be referred to as providing a "snapshot understanding" of the relative significance of the plurality of items. When the transformed entity sensory representation is some other form of sensory output, the human may receive the sensory output as a simple perceptual input that provides a quick, and in some cases, near-instantaneous understanding of the relative significance of the plurality of items.

Referring now to the figures and, in particular, with reference to <FIG>, an illustration of a transformer is depicted in the form of a block diagram in accordance with an illustrative embodiment. In this illustrative example, transformer <NUM> may be implemented using software, hardware, firmware, or a combination thereof.

When software is used, the operations performed by transformer <NUM> may be implemented using, for example, without limitation, program code configured to run on a processor unit. When firmware is used, the operations performed by transformer <NUM> may be implemented using, for example, without limitation, program code and data and stored in persistent memory to run on a processor unit.

When hardware is employed, the hardware may include one or more circuits that operate to perform the operations performed by transformer <NUM>. Depending on the implementation, the hardware may take the form of a circuit system, an integrated circuit, an application specific integrated circuit (ASIC), a programmable logic device, or some other suitable type of hardware device configured to perform any number of operations.

A programmable logic device may be configured to perform certain operations. The device may be permanently configured to perform these operations or may be reconfigurable. A programmable logic device may take the form of, for example, without limitation, a programmable logic array, a programmable array logic, a field programmable logic array, a field programmable gate array, or some other type of programmable hardware device.

In some illustrative examples, the operations and processes performed by transformer <NUM> may be performed using organic components integrated with inorganic components. In some cases, the operations and processes may be performed by entirely organic components, excluding a human being. As one illustrative example, circuits in organic semiconductors may be used to perform these operations and processes.

As depicted in <FIG>, transformer <NUM> may be implemented using computer system <NUM> in one illustrative example. Computer system <NUM> may include one or more computers that are in communication with each other.

Transformer <NUM> may transform entity sensory representation <NUM> into transformed entity sensory representation <NUM>. As used herein, a "sensory representation" is a representation that can be understood by a person using at least one of the five human senses. These five senses include the sense of sight <NUM>, the sense of sound <NUM>, the sense of smell <NUM>, the sense of touch <NUM>, and the sense of taste <NUM>.

A sensory representation corresponding to the sense of sight <NUM> may be referred to as a visual representation. A visual representation may take the form of, for example, without limitation, an image, a three-dimensional physical model, alphanumeric text, an icon, or other type of visual representation.

A sensory representation corresponding to the sense of sound <NUM> may be referred to as an audible representation. An audible representation may take the form of, for example, without limitation, an audio recording, a sound, music, or some other type of audible representation.

Further, a sensory representation corresponding to the sense of smell <NUM> may be referred to as an olfactory representation. A sensory representation corresponding to the sense of touch <NUM> may be referred to as a tactile representation. The tactile representation may take the form of, for example, without limitation, a texture, a temperature, or some other type of representation that may be perceived through touch. A sensory representation corresponding to the sense of taste <NUM> may be referred to as a gustatory representation.

Entity sensory representation <NUM> represents entity <NUM>. As used herein, entity sensory representation may "represent" entity <NUM> by symbolizing, presenting a meaning for, presenting an understanding of, standing in for, being an equivalent of, serving as an example of, or providing some other type of indication of entity <NUM>.

Entity <NUM> is the whole formed by plurality of items <NUM>. Entity <NUM> may take a number of different forms. For example, entity <NUM> may take the form of a body, a group, a collection, or some other type of "whole" that is comprised of plurality of items <NUM>. As used herein, an "item" may take the form of a part, a portion of an object or structure, a person, a group of people, a time interval, an alert, a security level, a building, a floor of a building, a section of a shop floor area, a title, an employee number, a social security number, a phone number, an aircraft component, an electronic component, a hardware component, a software component, or some other type of item.

As depicted, entity sensory representation <NUM> comprises plurality of sensory representations <NUM> that represent plurality of items <NUM>. In these illustrative examples, plurality of sensory representations <NUM> may be individual sensory representations that are collectively referred to as entity sensory representation <NUM>. In other illustrative examples, plurality of sensory representations <NUM> may be portions of a single entity sensory representation <NUM>. Examples of different types of entities and entity sensory representations corresponding to these entities are described in <FIG> below.

Set of measurable factors of interest <NUM> may be used to evaluate or analyze plurality of items <NUM>. As used herein, a "set of" items may include one or more items. For example, set of measurable factors of interest <NUM> may include one or more measurable factors of interest.

Measurable factor of interest <NUM> is an example of one of set of measurable factors of interest <NUM>. Measurable factor of interest <NUM> may be an attribute, parameter, characteristic, or other type of factor that can be measured quantitatively, qualitatively, or both. For example, measurable factor of interest <NUM> may be, but is not limited to, a level of importance, a salary amount, a level of activity, energy usage, surface area, intensity, amplitude, phase, price, a physical dimension such as width, length, or height, or some other type of factor that can be measured as having a value with some range of values.

Item <NUM> may be an example of one of plurality of items <NUM>. With respect to measurable factor of interest <NUM>, item <NUM> may have value <NUM>. Value <NUM> may be a nominal value, a numeric value, a range of values, a level, a category, a color, a physical quantity, a measure of amount, or some other type of qualitative or quantitative measurement. In other illustrative examples, value <NUM> may be an audible tone, an audible frequency, an odor, an odor intensity, a texture, a roughness of texture, a taste, or a quality of taste such as saltiness or sweetness.

For example, measurable factor of interest <NUM> may be length and item <NUM> may be a structure having a value for the length of about <NUM> inches. In another example, measurable factor of interest <NUM> may be a salary amount and item <NUM> may be an employee having a value for the salary amount of about $<NUM>,<NUM>. In yet another example, measurable factor of interest <NUM> may be energy usage and item <NUM> may be an aircraft engine having a value for energy usage equal to one of a very low level, a low level, a normal level, a high level, or a very high level.

Each of plurality of items <NUM> may be associated with a set of values, similar to value <NUM> described above, for set of measurable factors of interest <NUM>. For example, item <NUM> may be associated with set of values <NUM> for set of measurable factors of interest <NUM>. In these illustrative examples, transformer <NUM> may receive input that includes set of values <NUM> for set of measurable factors of interest <NUM> for each of plurality of items <NUM>. In other illustrative examples, transformer <NUM> may be configured to identify set of values <NUM> for set of measurable factors of interest <NUM> for each of plurality of items <NUM> based on input data received by transformer <NUM>.

Transformer <NUM> is configured to modify plurality of sensory representations <NUM> in a manner that establishes a relative relationship between plurality of items <NUM> represented by plurality of sensory representations <NUM> with respect to set of measurable factors of interest <NUM>. In particular, transformer <NUM> may calculate a set of scale factors for each of plurality of sensory representations <NUM> based on the set of values associated with each of plurality of items <NUM>. The set of scale factors may be used to adjust a set of parameters for each of plurality of sensory representations <NUM> to form plurality of modified sensory representations <NUM>. Plurality of modified sensory representations <NUM> together form transformed entity sensory representation <NUM>.

In this manner, entity sensory representation <NUM> may be homuncularly transformed using the different sets of scale factors for each of plurality of sensory representations <NUM> to form transformed entity sensory representation <NUM>. In other words, entity sensory representation <NUM> may be transformed in a manner similar to the manner in which a cortical homunculus is formed. Transformed entity sensory representation <NUM> may be referred to as a homuncularized entity sensory representation.

For example, sensory representation <NUM> may be one of plurality of sensory representations <NUM> and may represent item <NUM>. Sensory representation <NUM> may be associated with set of parameters <NUM>. A parameter in set of parameters <NUM> may take a number of different forms. For example, the parameter may be a width, a height, a center point, a center point distance, a transparency value, a contrast value, a decibel level, a speed, a pitch, a bandwidth, a start time, an end time, a total time, a texture, a thickness, a spiciness level, a sweetness level, or some other type of parameter.

Each of set of parameters <NUM> may be scalable. In particular, each of set of parameters <NUM> may be scalable using a linear scale factor, a nonlinear scale factor, or both. The nonlinear scale factor may be, for example, without limitation, an exponential factor, a logarithmic scale factor, or some other type of nonlinear scale factor. In this manner, set of parameters <NUM> may be referred to as a set of scalable parameters.

Transformer <NUM> calculates set of scale factors <NUM> for sensory representation <NUM> based on set of values <NUM> for set of measurable factors of interest <NUM> for item <NUM> represented by sensory representation <NUM>. Transformer <NUM> uses set of scale factors <NUM> to adjust set of parameters <NUM> for sensory representation <NUM> to form modified sensory representation <NUM>. Depending on set of scale factors <NUM>, modified sensory representation <NUM> may be the same or different from sensory representation <NUM>.

In one illustrative example, set of scale factors <NUM> may have a one-to-one correspondence with set of parameters <NUM>. For example, transformer <NUM> may linearly scale each parameter in set of parameters <NUM> by a corresponding scale factor in set of scale factors <NUM>. In other illustrative examples, set of scale factors <NUM> may include a single scale factor that is used to linearly scale each of set of parameters <NUM>.

Transformer <NUM> adjusts set of parameters <NUM> using set of scale factors <NUM> to form scaled set of parameters <NUM>. Transformer <NUM> may then use scaled set of parameters <NUM> to create modified sensory representation <NUM>.

In one illustrative example, entity sensory representation <NUM> may take the form of entity image <NUM>. Entity image <NUM> may take the form of, for example, without limitation, an aircraft image, a spacecraft image, a watercraft image, an engine system image, or an image of some other type of entity. In some illustrative examples, entity image <NUM> may be a combined image formed by multiple images or a single image divisible into image portions. Entity image <NUM> may represent entity <NUM>.

When entity sensory representation <NUM> takes the form of entity image <NUM>, plurality of sensory representations <NUM> may take the form of plurality of image portions <NUM>. Each of plurality of image portions <NUM> may take the form of a portion of entity image <NUM> or an individual image used to form entity image <NUM>. Further, each of plurality of image portions <NUM> may represent a corresponding item in plurality of items <NUM>.

Set of parameters <NUM> for each image portion in plurality of image portions <NUM> may take the form of, for example, a set of dimensions for each image portion. For example, the set of dimensions for an image portion may include a width and a height for the image portion.

Transformer <NUM> calculates a set of scale factors for each image portion in plurality of image portions <NUM> based on the set of values for set of measurable factors of interest <NUM> associated with the corresponding item in plurality of items <NUM> represented by each image portion. Transformer <NUM> then uses these sets of scale factors to adjust the set of parameters for each of plurality of image portions <NUM> to form scaled sets of parameters. These scaled sets of parameters may then be used to create plurality of modified image portions <NUM>, which may be an example of plurality of modified sensory representations <NUM>.

Plurality of modified image portions <NUM> may form transformed entity image <NUM>. Transformed entity image <NUM> with plurality of modified image portions <NUM> may visually establish the relative relationship between plurality of items <NUM> represented by plurality of modified image portions <NUM> with respect to set of measurable factors of interest <NUM>. Transformed entity image <NUM> with plurality of modified image portions <NUM> may provide a "snapshot understanding," or an understanding at a glance, of the relative relationship between plurality of items <NUM> with respect to set of measurable factors of interest <NUM>.

In these illustrative examples, transformer <NUM> may send transformed entity sensory representation <NUM> to output device <NUM>. Output device <NUM> may output transformed entity sensory representation <NUM> in a manner that can be understood using at least one of the five human senses.

For example, when transformed entity sensory representation <NUM> is a transformed visual representation, output device <NUM> may take the form of display device <NUM>. Display device <NUM> may visually present a display of the transformed visual representation. In particular, when transformed entity sensory representation <NUM> takes the form of transformed entity image <NUM>, display device <NUM> may be used to visually present a display of transformed entity image <NUM>. Display device <NUM> may take the form of a monitor, a screen, a liquid crystal display device, a plasma display device, a touch screen device, a projection system, or some other type of display device.

Thus, transformer <NUM> allows entity sensory representation <NUM> of entity <NUM> to be transformed in a manner that reflects a relative measure of set of measurable factors of interest <NUM> for plurality of items <NUM> that make up entity <NUM>. This type of transformed entity sensory representation <NUM> may provide a user with a way to quickly and easily understand the relative relationship between plurality of items <NUM> with respect to set of measurable factors of interest <NUM> without needing to rely on the sets of values identified for plurality of items <NUM>.

This type of understanding may be preferable for a user that does not have the training to understand or process the sets of values for the plurality of items. For example, a user may need to understand a relative significance of each of plurality of items <NUM> with respect to some measurable factor of interest for performing a type of operation. However, the user may not have the training, knowledge, or skill to understand, interpret, or process the data to identify the value for the measurable factor of interest for each of plurality of items <NUM>. Transformed entity sensory representation <NUM> may provide the user with the relative significance of each of plurality of items <NUM> without the user needing to understand, interpret, or process the data.

Further, implementing this type of evaluation or analysis within a computer system, such as computer system <NUM>, allows the process to be automated. For example, a new transformed entity sensory representation may be quickly and easily created by transformer <NUM> when transformer <NUM> receives new input that includes a new set of values for set of measurable factors of interest <NUM> for at least one of plurality of items <NUM>.

Further, transformer <NUM> may be capable of quickly and easily creating a new transformed entity sensory representation for different sets of measurable factors of interest. In this manner, entity sensory representation <NUM> may be transformed from a baseline for entity sensory representation in any number of ways and any number of times. This baseline may be the initial or original values for the set of parameters for each of plurality of sensory representations that make up entity sensory representation <NUM>.

Depending on the implementation, the sets of values for set of measurable factors of interest <NUM> for plurality of items <NUM> may be static or dynamic. When the sets of values are dynamic, transformer <NUM> may, in some cases, be configured to update the sets of scale factors calculated for plurality of sensory representations <NUM> in correspondence with changes to the sets of values. Further, transformer <NUM> may update transformed entity sensory representation <NUM> in correspondence with the updates to the sets of scale factors. In this manner, the changing relative relationship between plurality of items <NUM> may be reflected in substantially real-time or near real-time.

As one illustrative example, transformer <NUM> acquires the sets of values for plurality of items <NUM> in sensor data generated by one or more sensor systems configured to monitor set of measurable factors of interest <NUM> for plurality of items <NUM>. The sets of values may be dynamic in that the sensor data is received continuously over time. Transformer <NUM> adjusts the sets of scale factors for plurality of sensory representations <NUM> to update plurality of modified sensory representations <NUM> as the sets of values change. Computer system <NUM> allows these adjustments and updates to be performed in substantially real-time.

With reference now to <FIG>, an illustration of a set of entities and a set of entity sensory representations is depicted in the form of a block diagram in accordance with an illustrative embodiment. Set of entities <NUM> and set of entity sensory representations <NUM> are depicted.

Set of entities <NUM> includes aircraft <NUM>, corporate management team <NUM>, manufacturing instructions <NUM>, and alert system <NUM>. Each of aircraft <NUM>, corporate management team <NUM>, manufacturing instructions <NUM>, and alert system <NUM> is an example of one implementation for entity <NUM> in <FIG>.

Aircraft <NUM> is comprised of plurality of aircraft sections <NUM>. Corporate management team <NUM> is comprised of plurality of employees <NUM>. Manufacturing instructions <NUM> is comprised of plurality of steps <NUM>. Alert system <NUM> is comprised of plurality of alerts <NUM>. Each of plurality of aircraft sections <NUM>, plurality of employees <NUM>, plurality of steps <NUM>, and plurality of alerts <NUM> is an example of one implementation for plurality of items <NUM> in <FIG>.

As depicted, set of entity sensory representations <NUM> includes aircraft image <NUM>, picture cloud <NUM>, audio recording <NUM>, and audio recording group <NUM>. Each of aircraft image <NUM>, picture cloud <NUM>, audio recording <NUM>, and audio recording group <NUM> may be an example of one implementation for entity sensory representation <NUM> in <FIG>. Aircraft image <NUM>, picture cloud <NUM>, audio recording <NUM>, and audio recording group <NUM> are sensory representations of aircraft <NUM>, corporate management team <NUM>, manufacturing instructions <NUM>, and alert system <NUM>, respectively.

In this illustrative example, aircraft image <NUM> may be comprised of plurality of image portions <NUM>. Picture cloud <NUM> may be comprised of plurality of employee pictures <NUM>. Further, audio recording <NUM> may be comprised of plurality of audio sections <NUM>. Audio recording group <NUM> may be comprised of plurality of audio recordings <NUM>.

Each of plurality of image portions <NUM>, plurality of employee pictures <NUM>, plurality of audio sections <NUM>, and plurality of audio recordings <NUM> may be an example of one implementation for plurality of sensory representations <NUM> in <FIG>. Further, plurality of image portions <NUM>, plurality of employee pictures <NUM>, plurality of audio sections <NUM>, and plurality of audio recordings <NUM> represent plurality of aircraft sections <NUM>, plurality of employees <NUM>, plurality of steps <NUM>, and plurality of alerts <NUM>, respectively.

In this illustrative example, the set of parameters that are scalable for each of plurality of image portions <NUM> may be set of dimensions <NUM>. In one illustrative example, set of dimensions <NUM> includes a width and a height of an image portion. The set of parameters that are scalable for each of plurality of employee pictures <NUM> may be set of dimensions <NUM>.

As depicted, each of plurality of audio sections <NUM> may have a single scalable parameter, which is decibel level <NUM>. Similarly, each of plurality of audio recordings <NUM> may have a single scalable parameter, which is decibel level <NUM>.

Although only sensory representations corresponding to the sense of sight and sound are depicted in set of entity sensory representations <NUM>, set of entity sensory representations <NUM> may include other types of sensory representations in other illustrative examples. For example, other entity sensory representations may be tactile, olfactory, or gustatory. In yet other illustrative examples, an entity sensory representation may correspond to more than one human sense.

The illustrations of transformer <NUM> in <FIG> and set of entities <NUM> and set of entity sensory representations <NUM> in <FIG> are not meant to imply physical or architectural limitations to the manner in which an illustrative embodiment may be implemented. Other components in addition to or in place of the ones illustrated may be used. Some components may be optional. Also, the blocks are presented to illustrate some functional components. One or more of these blocks may be combined, divided, or combined and divided into different blocks when implemented in an illustrative embodiment.

In some cases, transformer <NUM> may normalize the set of parameters for each of plurality of sensory representations <NUM> prior to adjusting these parameters. For example, set of parameters <NUM> may be normalized to form normalized set of parameters <NUM>. Normalized set of parameters <NUM> may then be adjusted using set of scale factors <NUM> to form scaled set of parameters <NUM>.

In other illustrative examples, set of entities <NUM> may include other types of entities. For example, set of entities <NUM> may include a spacecraft, a building, a corporate infrastructure, a financial portfolio, a safety manual, or some other type of entity.

With reference now to <FIG>, an illustration of a display of an aircraft image that visually represents an aircraft is depicted in accordance with an illustrative embodiment. In this illustrative example, display <NUM> of aircraft image <NUM> may be visually presented by a display device such as, for example, without limitation, display device <NUM> in <FIG>. In particular, aircraft image <NUM> is an example of one implementation for transformed entity image <NUM>.

Aircraft image <NUM> in display <NUM> is a visual representation of an aircraft. The aircraft is an example of an entity, such as entity <NUM> in <FIG>.

As depicted, aircraft image <NUM> may be comprised of plurality of image portions <NUM>. Plurality of image portions <NUM> includes fuselage portion <NUM>, cockpit portion <NUM>, tail portion <NUM>, rudder portion <NUM>, right wing portion <NUM>, left wing portion <NUM>, right aileron portion <NUM>, left aileron portion <NUM>, right engine portion <NUM>, and left engine portion <NUM>. Plurality of image portions <NUM> represents the different aircraft sections or aircraft regions of an aircraft that are of interest.

In this illustrative example, a total display area for display <NUM> may be defined by identifying top boundary <NUM>, left boundary <NUM>, bottom boundary <NUM>, and right boundary <NUM> of display <NUM>. Identifying the boundaries of display <NUM> allows the coordinates for the four corners formed by these boundaries to be identified. In particular, the x,y-coordinates for each corner may be identified. In particular, the coordinates for first corner <NUM>, second corner <NUM>, third corner <NUM>, and fourth corner <NUM> may be identified. With these corner coordinates, the x,y-coordinates for center point <NUM> may also be identified. Center point <NUM> is the x,y center of display <NUM>.

In some illustrative examples, the total display area for display <NUM> may also be three-dimensional and may have three-dimensional boundaries. In this manner, center point <NUM> may comprise three-dimensional coordinates, such as x,y,z-coordinates. In other illustrative examples, when other senses are being used, the total output area for the output device may be n-dimensional and have n-dimensional boundaries. Consequently, a center point of this total output area may comprise n-dimensional coordinates.

All of this information may be used to define a plurality of display areas within display <NUM> corresponding to plurality of image portions <NUM> of aircraft image <NUM>. These display areas are outlined in <FIG> below.

With reference now to <FIG>, an illustration of display areas for the image portions of aircraft image <NUM> from <FIG> is depicted in accordance with an illustrative embodiment. In this illustrative example, plurality of display areas <NUM> has been defined within display <NUM>.

As depicted, plurality of display areas <NUM> includes fuselage display area <NUM>, cockpit display area <NUM>, tail display area <NUM>, rudder display area <NUM>, right wing display area <NUM>, left wing display area <NUM>, right aileron display area <NUM>, left aileron display area <NUM>, right engine display area <NUM>, and left engine display area <NUM>. Fuselage display area <NUM>, cockpit display area <NUM>, tail display area <NUM>, rudder display area <NUM>, right wing display area <NUM>, left wing display area <NUM>, right aileron display area <NUM>, left aileron display area <NUM>, right engine display area <NUM>, and left engine display area <NUM> contain fuselage portion <NUM>, cockpit portion <NUM>, tail portion <NUM>, rudder portion <NUM>, right wing portion <NUM>, left wing portion <NUM>, right aileron portion <NUM>, left aileron portion <NUM>, right engine portion <NUM>, and left engine portion <NUM>, respectively.

In one illustrative example, coordinates may be identified for each of the display areas identified. For example, without limitation, a leftmost x-coordinate, a rightmost x-coordinate, a topmost y-coordinate, and a bottommost y-coordinate may be identified for each of the display areas. These coordinates may be used to establish a width and a height for each of the display areas.

A reference center point for each of the display areas may then be identified using the coordinates, the width and height, or both. For example, cockpit center point <NUM> may be identified for cockpit display area <NUM>. Thereafter, a distance from the reference center point identified for each of the display areas to center point <NUM> is identified.

With reference now to <FIG>, an illustration of a table indicating the energy usage of the different aircraft sections of an aircraft is depicted in accordance with an illustrative embodiment. Table <NUM> has column <NUM>, column <NUM>, and column <NUM>.

Column <NUM> identifies the different aircraft sections of the aircraft represented by aircraft image <NUM> in <FIG>. Column <NUM> identifies the energy usage for each of the aircraft sections. In this illustrative example, energy usage is an example of a measurable factor of interest, such as measurable factor of interest <NUM> in <FIG>. Column <NUM> identifies the scale factor that may be calculated for the image portions corresponding to the aircraft sections identified in column <NUM>.

Row <NUM> indicates that the fuselage of the aircraft has an energy usage with a value of low. Row <NUM> further indicates that the corresponding scale factor to be used for fuselage portion <NUM> of aircraft image <NUM> in <FIG> is <NUM>.

Row <NUM> indicates that the cockpit of the aircraft has an energy usage with a value of high. Row <NUM> further indicates that the corresponding scale factor to be used for cockpit portion <NUM> of aircraft image <NUM> in <FIG> is <NUM>.

Row <NUM> indicates that the right engine of the aircraft has an energy usage with a value of very high. Row <NUM> further indicates that the corresponding scale factor to be used for right engine portion <NUM> of aircraft image <NUM> in <FIG> is <NUM>.

The scale factors identified in column <NUM> may be used to modify the corresponding image portions of aircraft image <NUM> in <FIG>. In particular, these scale factors may be used to resize the display areas of display <NUM> corresponding to these image portions to resize the image portions.

With reference now to <FIG>, an illustration of a display of a transformed aircraft image is depicted in accordance with an illustrative embodiment. In this illustrative example, aircraft image <NUM> in <FIG> has been transformed into transformed aircraft image <NUM> within display <NUM>. In particular, scale factors identified in column <NUM> of table <NUM> in <FIG> have been used to modify the image portions of aircraft image <NUM> in <FIG> to form transformed aircraft image <NUM>.

Transformed aircraft image <NUM> includes plurality of modified image portions <NUM> that have been modified based on the scale factors identified in column <NUM> in table <NUM> in <FIG>. In particular, each of plurality of image portions <NUM> from <FIG> has been increased in size by the corresponding scale factor in <FIG>.

In this illustrative example, the width and height of each of plurality of display areas <NUM> in <FIG> may be linearly scaled by the corresponding scale factor to form the corresponding modified image portion. Further, in this illustrative example, each modified image portion may be centered within display <NUM> at the previously calculated reference center point for the corresponding original display area. The type of transformed entity image that results may be referred to as an overlapping transformed entity image.

In other illustrative examples, the new modified image portion may be centered about a new center point within display <NUM>. For example, the distance from the previously calculated reference center point for the original display area to display center point <NUM> may be scaled by the corresponding scale factor. The new modified image portion may be centered at a new center point having the scaled distance away from center point <NUM>. The type of transformed entity image that results by performing this process for each of the modified image portions may be referred to as an exploded, transformed entity image.

In some cases, this type of process may result in transformed aircraft image <NUM> requiring a larger display area. Consequently, transformed aircraft image <NUM> may then be adjusted in the entirety such that transformed aircraft image <NUM> may be displayed within the original total display area of display <NUM>. In particular, transformed aircraft image <NUM> may be scaled to fit within the original total display area of display <NUM>.

Plurality of modified image portions <NUM> include modified fuselage portion <NUM>, modified cockpit portion <NUM>, modified tail portion <NUM>, modified rudder portion <NUM>, modified right wing portion <NUM>, modified left wing portion <NUM>, modified right aileron portion <NUM>, modified left aileron portion <NUM>, modified right engine portion <NUM>, and modified left engine portion <NUM>. As depicted, modified cockpit portion <NUM> is larger than cockpit portion <NUM> in <FIG>. Further, modified right engine portion <NUM> and modified left engine portion <NUM> are larger than right engine portion <NUM> and left engine portion <NUM>, respectively, in <FIG>.

Modified cockpit portion <NUM>, modified right engine portion <NUM>, and modified left engine portion <NUM> are larger, proportionally, than the other modified portions of transformed aircraft image <NUM>. The proportionally increased size of modified cockpit portion <NUM>, modified right engine portion <NUM>, and modified left engine portion <NUM> provides an understanding, at a glance, that the cockpit, right engine, and left engine, respectively, have increased energy usage as compared to the other aircraft sections of the aircraft. In this manner, the relative significance of the aircraft sections represented by plurality of modified image portions <NUM> with respect to energy usage may be quickly and easily understood using transformed aircraft image <NUM>.

With reference now to <FIG>, an illustration of display of a picture cloud representing a social networking group is depicted in accordance with an illustrative embodiment. In this illustrative example, picture cloud <NUM> is an example of one implementation for entity sensory representation <NUM> in <FIG>. In particular, picture cloud <NUM> may be an example of one implementation for entity image <NUM> in <FIG>.

Picture cloud <NUM> visually represents a social networking group. This social networking group may be a singular group in which the members of the social networking group are grouped based on one or more factors. As one illustrative example, the social networking group may be comprised of members that have signed up on a dating website, a group of buyers, a group of sellers, or some other type of group. As depicted, picture cloud <NUM> includes plurality of member pictures <NUM>, which may be an example of one implementation for plurality of image portions <NUM> in <FIG>. Plurality of member pictures <NUM> includes member pictures <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, and <NUM>.

Plurality of member pictures <NUM> represents the plurality of members in the social networking group. The measurable factor of interest for each of the plurality of members may be a level of social networking activity for each member. The value for this level of social networking activity may be the number of posts created by each member.

In this illustrative example, each of plurality of member pictures <NUM> may be considered at "baseline. " In particular, each of plurality of member pictures <NUM> has a same width <NUM> and height <NUM>.

With reference now to <FIG>, an illustration of a table indicating the social networking activity of members in a social networking group is depicted in accordance with an illustrative embodiment. In this illustrative example, table <NUM> has column <NUM>, column <NUM>, and column <NUM>.

Column <NUM> identifies the different members of the social network group represented by plurality of member pictures <NUM> in <FIG>. Column <NUM> identifies the social networking activity of each of the members based on the number of posts created by each member. Column <NUM> identifies the scale factor calculated for each of plurality of member pictures <NUM> based on the values for social networking activity of the members represented by plurality of member pictures <NUM> identified in column <NUM>.

With reference now to <FIG>, an illustration of a display of a transformed picture cloud is depicted in accordance with an illustrative embodiment. In this illustrative example, picture cloud <NUM> from <FIG> has been transformed using the scale factors identified in column <NUM> in <FIG> to form transformed picture cloud <NUM>. Transformed picture cloud <NUM> may be an example of one implementation for transformed entity image <NUM> in <FIG>.

Transformed picture cloud <NUM> includes plurality of modified member pictures <NUM>. In this illustrative example, each of plurality of member pictures <NUM> from <FIG> has been resized using the corresponding scale factor identified in column <NUM> to form plurality of modified member pictures <NUM>. Plurality of modified member pictures <NUM> includes modified member pictures <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, and <NUM>, which are the modified versions of member pictures <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, and <NUM>, respectively, in <FIG>.

In some cases, the relative position of each of plurality of modified member pictures <NUM> within transformed picture cloud <NUM> may be determined based on scale factors used to perform the transformation. For example, plurality of modified member pictures <NUM> may be arranged from largest scale factor to smallest scale factor in a left to right direction, in a clockwise manner, or in some other manner.

With reference now to <FIG>, an illustration of an audio recording group representing an alert system is depicted in accordance with an illustrative embodiment. In this illustrative example, audio recording group <NUM> is an example of one implementation for entity sensory representation <NUM> in <FIG>. Audio recording group <NUM> may represent an alert system.

As depicted, audio recording group <NUM> includes plurality of audio recordings <NUM> that represent a plurality of alerts that form the alert system. Plurality of audio recordings <NUM> may be an example of one implementation for plurality of sensory representations <NUM> in <FIG>.

Each of the plurality of alerts may be an alert that indicates a threat to a particular room in a building as identified by a security system. The measurable factor of interest for these alerts may be the threat level. The value for the threat level may be selected from one of very minor, minor, moderate, serious, and very serious.

Plurality of audio recordings <NUM> includes audio recordings <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, and <NUM>. In this illustrative example, each of plurality of audio recordings <NUM> is at a baseline at which each audio recording is configured to play with a same loudness or decibel level. This baseline may be set to, for example, a moderate threat level.

With reference now to <FIG>, an illustration of a table indicating the threat level for alerts in an alert system is depicted in accordance with an illustrative embodiment. In this illustrative example, table <NUM> includes column <NUM>, column <NUM>, and column <NUM>.

Column <NUM> identifies the different alerts represented by plurality of audio recordings <NUM> in <FIG>. Column <NUM> identifies a current threat level for each of these alerts. Column <NUM> identifies the scale factor calculated for use in modifying each of plurality of audio recordings <NUM> in <FIG> based on the threat level of the corresponding alert.

With reference now to <FIG>, an illustration of a transformed audio recording group is depicted in accordance with an illustrative embodiment. In this illustrative example, audio recording group <NUM> from <FIG> has been transformed into transformed audio recording group <NUM>. Transformed audio recording group <NUM> is another example of one implementation for transformed entity sensory representation <NUM> in <FIG>.

Transformed audio recording group <NUM> includes plurality of modified audio recordings <NUM>, which may be another example of one implementation for plurality of modified sensory representations <NUM> in <FIG>. Each of plurality of audio recordings <NUM> in <FIG> has been modified using the corresponding scale factor identified in <FIG> to form plurality of modified audio recordings <NUM>.

As depicted, plurality of modified audio recordings <NUM> includes modified audio recordings <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, and <NUM>. Modified audio recordings <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, and <NUM> may be the modified versions of audio recordings <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, and <NUM>, respectively.

Plurality of modified audio recordings <NUM> may be played in succession, one after the other. A user, listening to plurality of modified audio recordings <NUM>, may be able to quickly and easily understand the relative significance with respect to the threat level of each of the alerts represented by plurality of modified audio recordings <NUM>. For example, alerts corresponding to higher threat levels may be played at higher volumes as compared to alerts corresponding to lower threat levels. With this type of understanding, a user may, for example, be able to quickly and easily determine which of the alerts, and thereby rooms in the building, may need to be addressed first.

In another illustrative example, a particular modified audio recording in plurality of modified audio recordings <NUM> may be played throughout an entire building or other area when the corresponding alert is appropriate. The volume at which the modified audio recording is played may provide an understanding of the threat level associated with that alert.

With reference now to <FIG>, an illustration of an audio recording representing manufacturing instructions is depicted in accordance with an illustrative embodiment. In this illustrative example, audio recording <NUM> may be an example of one implementation for entity sensory representation <NUM> in <FIG>.

Audio recording <NUM> represents manufacturing instructions. In particular, audio recording <NUM> is a recording of a human operator providing verbal instructions for performing a manufacturing operation.

As depicted, audio recording <NUM> includes plurality of sections <NUM>. Plurality of sections <NUM> may be an example of one implementation for plurality of sensory representations <NUM> in <FIG>. Each of plurality of sections <NUM> represents the instructions for performing a different step of the manufacturing operation.

In this illustrative example, plurality of sections <NUM> includes sections <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, and <NUM>. Each of plurality of sections <NUM> is at baseline in this example. In particular, each of plurality of sections <NUM> is configured to play at a same loudness or similar decibel level.

With reference now to <FIG>, an illustration of a table indicating the importance of the different steps for performing a manufacturing operation is depicted in accordance with an illustrative embodiment. In this illustrative example, table <NUM> includes column <NUM>, column <NUM>, and column <NUM>.

Column <NUM> identifies the different steps for which instructions are provided by audio recording <NUM> in <FIG>. Column <NUM> identifies the importance assigned to the different steps. Column <NUM> identifies the scale factors calculated for plurality of sections <NUM> representing the instructions for the different steps. These scale factors are used to modify a loudness of each of plurality of sections <NUM>.

With reference now to <FIG>, an illustration of a transformed audio recording is depicted in accordance with an illustrative embodiment. In this illustrative example, audio recording <NUM> from <FIG> has been transformed into transformed audio recording <NUM>. Transformed audio recording <NUM> is yet another example of one implementation for transformed entity sensory representation <NUM> in <FIG>.

Transformed audio recording <NUM> includes plurality of modified sections <NUM>. Plurality of modified sections <NUM> includes modified sections <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, and <NUM>. The loudness of each of plurality of sections <NUM> has been adjusted based on the corresponding scale factor identified in <FIG> for the corresponding step represented by each section to form plurality of modified sections <NUM>.

When transformed audio recording <NUM> is played to a user, the user may be able to quickly and easily understand which portions of the audio instructions to which the user should pay close attention. Plurality of modified sections <NUM> provides the user with a sensory understanding of the relative importance of the plurality of steps represented by plurality of modified sections <NUM>.

The illustrations in <FIG> are not meant to imply physical, architectural, or logical limitations to the manner in which an illustrative embodiment may be implemented. Other elements in addition to or in place of the ones illustrated may be used. Some elements may be optional. For example, other graphical features may be added to display <NUM> in <FIG> to indicate the relative energy usage of the different aircraft sections in addition to the resizing of the image portions.

With reference now to <FIG>, an illustration of a process for modifying an entity sensory representation that represents an entity is depicted in the form of a flowchart in accordance with an illustrative embodiment. The process illustrated in <FIG> may be implemented using transformer <NUM> in <FIG> to transform an entity sensory representation, such as entity sensory representation <NUM> in <FIG>.

The process may begin by receiving an entity sensory representation that represents an entity (operation <NUM>). In operation <NUM>, the entity sensory representation comprises a plurality of sensory representations that represent a plurality of items that are part of the entity. Each of the plurality of items may be associated with a set of values for a set of measurable factors of interest.

Next, a set of scale factors is calculated for each of the plurality of sensory representations based on the set of values associated with each of the plurality of items (operation <NUM>). The plurality of sensory representations may then be modified using the set of scale factors calculated for each of the plurality of sensory representations to form a plurality of modified sensory representations that establish a relative relationship between the plurality of items represented by the plurality of modified sensory representations with respect to the set of measurable factors of interest (operation <NUM>), with the process terminating thereafter.

With reference now to <FIG>, an illustration of a process for creating an entity sensory representation is depicted in the form of a flowchart in accordance with an illustrative embodiment. The process illustrated in <FIG> may be implemented to form an entity sensory representation, such as entity sensory representation <NUM> in <FIG>.

The process begins by identifying an entity comprising a plurality of items (operation <NUM>). In one illustrative example, the entity may be identified in operation <NUM> by a computer system, such as computer system <NUM> in <FIG>, receiving input comprising one or more n-dimensional arrays of items. In operation <NUM>, the one or more n-dimensional arrays of items may be stored in the computer system using one or more data structures.

Next, a sensory representation is obtained for each of the plurality of items (operation <NUM>). In operation <NUM>, the sensory representations may be obtained by receiving the sensory representations as input at the computer system, retrieving the sensory representations from a database or cloud storage, creating new sensory representations, or in some other manner.

As one illustrative example, the sensory representations obtained in operation <NUM> may take the form of images. The images may be received as input from an imaging system; retrieved from a database, server system, or cloud storage; created based on predetermined criteria or specifications; created by a user using a graphics program; or obtained in some other manner.

Thereafter, a set of parameters is quantified for each of the sensory representations (operation <NUM>). In operation <NUM>, a value for each of the set of parameters may be acquired, measured, or quantified in some other manner for each of the plurality of sensory representations. When the sensory representations are images, the set of parameters may include a width and height in pixels.

Next, the quantified set of parameters may be normalized to form a normalized set of parameters for each of the sensory representations (operation <NUM>). The sensory representations are then modified using the normalized set of parameters to form a plurality of sensory representations that together form an entity sensory representation (operation <NUM>), with the process terminating thereafter.

In operation <NUM>, each of the plurality of sensory representations may be set to a same baseline. When the plurality of sensory representations take the form of images, the width and height of the images may be normalized in operation <NUM> such that each of the images may be modified in operation <NUM> to have a baseline width and a baseline height in pixels.

With reference now to <FIG>, an illustration of a process for calculating a set of scale factors for each of a plurality of sensory representations that form an entity sensory representation is depicted in the form of a flowchart in accordance with an illustrative embodiment. The process illustrated in <FIG> may be implemented to identify a set of scale factors for, for example, each of plurality of sensory representations <NUM> in <FIG>.

The process begins by identifying a factor of interest for a plurality of items that form an entity (operation <NUM>). In other illustrative examples, more than one factor of interest may be identified in operation <NUM>.

The factor of interest identified in operation <NUM> may be measurable. Further, the factor of interest may be static or dynamic. When the factor of interest is static, a value measured for the factor of interest may not change over time. When the factor of interest is dynamic, a value measured for the factor of interest may change over time. Depending on the implementation, the factor of interest may be multi-dimensional. For example, the factor of interest may be a position that comprises three coordinates.

Next, a value for the factor of interest may be identified for each of the plurality of items (operation <NUM>). In operation <NUM>, the value may be quantified by at least one of performing a measurement, interpreting sensor data, converting subjective information into a value, or performing some other type of quantification.

As used herein, the phrase "at least one of," when used with a list of items, means different combinations of one or more of the listed items may be used and only one of each item in the list may be needed. In other words, "at least one of" means any combination of items and number of items may be used from the list but not all of the items in the list are required. The item may be a particular object, thing, or a category.

For example, "at least one of item A, item B, or item C" or "at least one of item A, item B, and item C" may include, without limitation, item A, item A and item B, or item B. Of course, any combinations of these items may be present. In other examples, "at least one of" may be, for example, without limitation, two of item A; one of item B; and ten of item C; four of item B and seven of item C; or other suitable combinations.

Thereafter, an initial scale factor may be calculated for each of the plurality of items (operation <NUM>). In one illustrative example, the initial scale factor for a particular item may be calculated by dividing the value identified for the factor of interest for the particular item in operation <NUM> by a sum of all of the values identified for the plurality of items. Of course, the initial scale factor may be computed in some other manner in other illustrative examples. In some cases, the scale factor may be referred to as a computed relative significance.

Next, a final scale factor may be calculated for each of the plurality of sensory representations corresponding to the plurality of items using a nonlinear factor (operation <NUM>), with the process terminating thereafter. In one illustrative example, the nonlinear factor may be a logarithmic factor. Operation <NUM> may be performed by multiplying the initial scale factor identified for a particular item by the logarithmic factor and setting the product of this multiplication as the final scale factor for the corresponding sensory representation.

With reference now to <FIG>, an illustration of a process for creating a transformed entity sensory representation is depicted in the form of a flowchart in accordance with an illustrative embodiment. The process illustrated in <FIG> may be implemented to transform the entity sensory representation formed by the process described in <FIG> using the scale factors identified for the plurality of sensory representations in the entity sensory representation as described in <FIG>.

The process may begin by scaling the normalized set of parameters for each of the plurality of sensory representations to form a scaled set of parameters for each of the plurality of sensory representations (operation <NUM>). A plurality of modified sensory representations may be created using the scaled set of parameters formed for each of the plurality of sensory representations (operation <NUM>).

Then, a transformed entity sensory representation may be created using the plurality of modified sensory representations (operation <NUM>). Operation <NUM> may be performed in any number of ways. For example, the plurality of modified sensory representations may be combined, overlapped, sequenced, positioned relative to each other, or manipulated in any number of ways to form transformed entity sensory representation.

The transformed entity sensory representation may then be output to establish, using at least one human sense, a relative relationship between the plurality of items represented by the plurality of modified sensory representations with respect to the factor of interest (operation <NUM>), with the process terminating thereafter. In other illustrative examples, the factor of interest may be a set of measurable factors of interest.

With reference now to <FIG> and <FIG>, an illustration of a process for creating a transformed entity image is depicted in the form of a flowchart in accordance with an illustrative embodiment. The process illustrated in <FIG> and <FIG> may be implemented to create, for example, without limitation, transformed entity image <NUM> in <FIG>.

The process may begin by identifying a plurality of image portions of an entity image (operation <NUM>). Next, boundaries of a total display area for displaying the entity image are identified (operation <NUM>).

Coordinates for the boundaries of the total display area are then identified (operation <NUM>). Depending on the shape of the total display area, these coordinates may be for the corners of the total display area, starting end points and ending end points for the boundaries of the total display area, or for other types of points along the boundaries of the total display area. Then, a center point of the total display area is identified (operation <NUM>).

Thereafter, a plurality of display areas for the plurality of image portions is identified in the total display area (operation <NUM>). A set of size parameters are quantified for each of the plurality of display areas (operation <NUM>). In operation <NUM>, the set of size parameters for each of the plurality of display areas may include, for example, a width in pixels and a height in pixels for each display area.

Next, a reference center point may be identified for each of the plurality of display areas (operation <NUM>). A distance from each reference center point identified to the center point of the total display area is computed (operation <NUM>). In operation <NUM>, this distance may be calculated using Cartesian point-coordinates such as x,y-coordinates, or x,y,z-coordinates. In other examples, the distance may be calculated using distance-angle vectors in two dimensions, three dimensions, n-dimensions, or some combination thereof using some other type of distance measurement technique.

Each of the set of size parameters for each of the plurality of display areas is multiplied by a scale factor computed for the image portion corresponding to each display area to form a plurality of modified display areas and thereby, a plurality of modified image portions (operation <NUM>). In some cases, the resizing may be a one-to-one resizing. For example, resizing a display area by a scale factor of <NUM> may not change a size of the display area. Thus, the size of the corresponding image portion may not be changed.

A determination is then made as to whether an overlapping transformed entity image or an exploded transformed entity image is to be created (operation <NUM>). If an overlapping transformed entity image is to be created, the process then creates the overlapping transformed entity image by centering each of the plurality of modified display areas, and thereby the plurality of modified image portions, at the reference center points originally calculated for the plurality of display areas (operation <NUM>), with the process terminating thereafter.

In operation <NUM>, one or more of the plurality of modified image portions may overlap over other modified image portions. In some illustrative examples, the modified display areas, and thereby the modified image portions, may be added to the total display area starting from the modified image portion associated with the smallest scale factor and ending with the modified image portion associated with the largest scale factor. In this manner, a modified image portion representing an item with greater relative significance may overlap another modified image portion representing an item with lesser relative significance.

With reference again to operation <NUM>, if the exploded transformed entity image is to be created, the process computes a new reference center point for each of the plurality of modified display areas by multiplying the distance from the center point of the total display area to the reference center point for each modified display area by the corresponding scale factor (operation <NUM>). Next, each of the plurality of modified display areas, and thereby the plurality of modified image portions, may be centered at the corresponding new reference center point to create the exploded transformed entity image (operation <NUM>).

Thereafter, the new total display area for the exploded transformed entity image may be adjusted to have a same size as the original total display area (operation <NUM>), with the process terminating thereafter. In some illustrative examples, operation <NUM> or operation <NUM> may include adding lines to reconnect the plurality of modified image portions.

In some cases, a continuous relationship may be present between the sensory representations that make up an entity sensory representation. As one illustrative example, a continuous relationship may be present between the plurality of image portions identified in operation <NUM> when the entity image is an aircraft and the plurality of image portions are parts of the aircraft. As another example, a continuous relationship may be present between segments of speech in an audio recording. When this type of continuous relationship is present in an entity image, it may be desirable to preserve this continuity between the plurality of modified portions that form an exploded transformed entity image.

For example, one or more techniques or algorithms may be used to create intermediary sensory representation content to preserve continuity between the plurality of modified image portions in the exploded transformed entity image formed in operation <NUM> after the plurality of modified image portions have been centered at the corresponding new reference center points in operation <NUM>. The one or more techniques or algorithms used may include, for example, without limitation, an interpolation technique, a smoothing algorithm, a filling algorithm, an extrapolation technique, a linear extrapolation technique, a drawing technique, some other type of algorithm or technique, or some combination thereof.

In some illustrative examples, an operation similar to operation <NUM> may be performed after operation <NUM>. In other words, in some cases, the new total display area for the overlapping transformed entity image may be adjusted to have a same size as the original total display area. In other illustrative examples, operation <NUM> may be performed to adjust the new total display area to some other size.

With reference now to <FIG>, an illustration of a process for creating a transformed entity sensory representation is depicted in accordance with an illustrative embodiment. The process illustrated in <FIG> may be used to create, for example, without limitation, transformed entity sensory representation <NUM> in <FIG>.

The process may begin by identifying a plurality of sensory representations that make up an entity sensory representation (operation <NUM>). Next, boundaries of a total output range for outputting the entity sensory representation are identified (operation <NUM>). Coordinates of the boundaries of the total output range are then identified (operation <NUM>). Then, a center point of the total output range is identified (operation <NUM>).

With respect to operations <NUM>, <NUM>, and <NUM>, the total output range may take different forms, depending on the type of entity sensory representation being processed. When the entity sensory representation takes the form of audio, the boundaries of the total output range may correspond to one or more dimensions such as, for example, without limitation, time, frequency, sound pressure, and intensity.

As one illustrative example, the boundaries of the total output range for an audio recording, such as audio recording <NUM> in <FIG>, may take the form of parameters such as time and sound pressure. The coordinates for these boundaries may include, for example, a start time, and end time, and a maximum sound pressure level and minimum sound pressure level for the boundary corresponding to sound pressure. A center point for the total output range may be comprised of the middle time between the start and end times and the mid-point between the maximum and minimum sound pressure levels.

In another illustrative example, the boundaries for the audio recordings may take the form of parameters, such as frequency and one of volume, intensity, or sound pressure. When the boundaries are frequency and volume, the coordinates for these boundaries may include, for example, a lowest frequency and highest frequency and a maximum volume level and minimum volume level. The center point for the total output range may then be comprised of the mid-frequency point and the middle volume level. The mid-frequency point may be computed using linear or logarithmic measurements of the frequencies.

Thereafter, a plurality of outputs for the plurality of sensory representations is identified within the total output range (operation <NUM>). When the entity sensory representation is an audio recording and the plurality of sensory representations are sections of the audio recording, the plurality of outputs may be the corresponding sections of the total output range.

A set of parameters are quantified for each of the plurality of outputs (operation <NUM>). In operation <NUM>, the set of parameters for each of the plurality of outputs may include, for example, a frequency range, a volume range, a time interval, an intensity range, or some other type of parameter.

Next, a reference center point may be identified for each of the plurality of outputs (operation <NUM>). A distance from each reference center point identified to the center point of the total output range is computed (operation <NUM>). As one illustrative example, this distance may be a temporal distance in the case of audio.

Each of the set of parameters for each of the plurality of outputs is multiplied by a scale factor computed for the sensory representation corresponding to each output to form a plurality of modified outputs and thereby, a plurality of modified sensory representations (operation <NUM>). In operation <NUM>, when the sensory representation is audio, each output may be scaled in frequency, volume, time, intensity, sound pressure, or some other parameter.

A new reference center point may be computed for each of the plurality of modified outputs by multiplying the distance from the center point of the total output range to the reference center point for each modified output by the corresponding scale factor (operation <NUM>). Next, the plurality of modified outputs, and thereby the plurality of sensory representations, may be reconfigured using the corresponding new reference center points identified to create the transformed entity sensory representation (operation <NUM>), with the process terminating thereafter.

The flowcharts and block diagrams in the different depicted embodiments illustrate the architecture, functionality, and operation of some possible implementations of apparatuses and methods in an illustrative embodiment. In this regard, each block in the flowcharts or block diagrams may represent a module, a segment, a function, a portion of an operation or step, some combination thereof.

In some alternative implementations of an illustrative embodiment, the function or functions noted in the blocks may occur out of the order noted in the figures. For example, in some cases, two blocks shown in succession may be executed substantially concurrently, or the blocks may sometimes be performed in the reverse order, depending upon the functionality involved. Also, other blocks may be added in addition to the illustrated blocks in a flowchart or block diagram.

In some illustrative examples, operation <NUM> in <FIG> may be an optional step. In this manner, the normalized set of parameters formed in operation <NUM> may be referred to as an optionally normalized set of parameters. In one illustrative example, the process described in <FIG> above may be made to terminate after operation <NUM> such that the sensory representations with the quantified sets of parameters are used to form the entity sensory representation. In other illustrative examples, operation <NUM> in <FIG> may be an optional step. When operation <NUM> is not performed, the initial scale factor computed in operation <NUM> for each of plurality of items may be used as the final scale factor for each corresponding sensory representation.

Turning now to <FIG>, an illustration of a data processing system is depicted in the form of a block diagram in accordance with an illustrative embodiment. Data processing system <NUM> may be used to implement computer system <NUM> in <FIG>. As depicted, data processing system <NUM> includes communications framework <NUM>, which provides communications between processor unit <NUM>, storage devices <NUM>, communications unit <NUM>, input/output unit <NUM>, and display <NUM>. In some cases, communications framework <NUM> may be implemented as a bus system.

Processor unit <NUM> is configured to execute instructions for software to perform a number of operations. Processor unit <NUM> may comprise at least one of a number of processors, a multi-processor core, or some other type of processor, depending on the implementation. In some cases, processor unit <NUM> may take the form of a hardware unit, such as a circuit system, an application specific integrated circuit (ASIC), a programmable logic device, or some other suitable type of hardware unit.

Instructions for the operating system, applications and programs run by processor unit <NUM> may be located in storage devices <NUM>. Storage devices <NUM> may be in communication with processor unit <NUM> through communications framework <NUM>. As used herein, a storage device, also referred to as a computer readable storage device, is any piece of hardware capable of storing information on a temporary basis, a permanent basis, or both. This information may include, but is not limited to, data, program code, other information, or some combination thereof.

Memory <NUM> and persistent storage <NUM> are examples of storage devices <NUM>. Memory <NUM> may take the form of, for example, a random access memory or some type of volatile or nonvolatile storage device. Persistent storage <NUM> may comprise any number of components or devices. For example, persistent storage <NUM> may comprise a hard drive, a flash memory, a rewritable optical disk, a rewritable magnetic tape, or some combination of the above. The media used by persistent storage <NUM> may or may not be removable.

Communications unit <NUM> allows data processing system <NUM> to communicate with other data processing systems, devices, or both. Communications unit <NUM> may provide communications using physical communications links, wireless communications links, or both.

Input/output unit <NUM> allows input to be received from and output to be sent to other devices connected to data processing system <NUM>. For example, input/output unit <NUM> may allow user input to be received through a keyboard, a mouse, some other type of input device, or a combination thereof. As another example, input/output unit <NUM> may allow output to be sent to a printer connected to data processing system <NUM>.

Display <NUM> is configured to display information to a user. Display <NUM> may comprise, for example, without limitation, a monitor, a touch screen, a laser display, a holographic display, a virtual display device, some other type of display device, or a combination thereof. Display <NUM> may be an example of one manner in which display device <NUM> in <FIG> may be implemented.

In this illustrative example, the processes of the different illustrative embodiments may be performed by processor unit <NUM> using computer-implemented instructions. These instructions may be referred to as program code, computer usable program code, or computer readable program code and may be read and executed by one or more processors in processor unit <NUM>.

In these examples, program code <NUM> is located in a functional form on computer readable media <NUM>, which is selectively removable, and may be loaded onto or transferred to data processing system <NUM> for execution by processor unit <NUM>. Program code <NUM> and computer readable media <NUM> together form computer program product <NUM>. In this illustrative example, computer readable media <NUM> may be computer readable storage media <NUM> or computer readable signal media <NUM>.

Computer readable storage media <NUM> is a physical or tangible storage device used to store program code <NUM> rather than a medium that propagates or transmits program code <NUM>. Computer readable storage media <NUM> may be, for example, without limitation, an optical or magnetic disk or a persistent storage device that is connected to data processing system <NUM>.

Alternatively, program code <NUM> may be transferred to data processing system <NUM> using computer readable signal media <NUM>. Computer readable signal media <NUM> may be, for example, a propagated data signal containing program code <NUM>. This data signal may be an electromagnetic signal, an optical signal, or some other type of signal that can be transmitted over physical communications links, wireless communications links, or both.

The illustration of data processing system <NUM> in <FIG> is not meant to provide architectural limitations to the manner in which the illustrative embodiments may be implemented. The different illustrative embodiments may be implemented in a data processing system that includes components in addition to or in place of those illustrated for data processing system <NUM>. Further, components shown in <FIG> may be varied from the illustrative examples shown.

With this type of data processing system <NUM>, a computer-implemented method, useful for understanding but not pertaining to the invention as claimed, for automating a transformation of an entity image into a transformed entity image, is enabled that includes the following steps of:.

Thus, the illustrative embodiments provide a method and apparatus for using a sensory representation to provide an understanding of the relative significance of items in an entity with respect to one or more measurable factors of interest. In particular, transformed entity sensory representation <NUM> described in <FIG> may allow a user to more quickly and easily understand the relative significance of items, the relative importance of items, or some other relative measure of items without needing to interpret, understand, or process the underlying data.

The description of the different illustrative embodiments has been presented for purposes of illustration and description, and is not intended to be exhaustive or limited to the embodiments in the form disclosed. Many modifications and variations within the scope of the invention as claimed.

Claim 1:
An apparatus comprising:
a transformer (<NUM>) that receives an entity sensory representation (<NUM>) that represents an entity (<NUM>);
wherein the entity sensory representation (<NUM>) comprises a plurality of sensory representations (<NUM>) that represent a plurality of items (<NUM>) that are part of the entity (<NUM>) in which each of the plurality of items (<NUM>) is associated with a set of values (<NUM>) for a set of measurable factors of interest (<NUM>), wherein the set of measurable factors of interest (<NUM>) comprises a level of importance of the plurality of items (<NUM>);
wherein the transformer (<NUM>) calculates a set of scale factors (<NUM>) for each of the plurality of sensory representations (<NUM>) based on the set of values (<NUM>) associated with the each of the plurality of items (<NUM>);
wherein the transformer (<NUM>) modifies the plurality of sensory representations (<NUM>) using the set of scale factors (<NUM>) to form a plurality of modified sensory representations (<NUM>) that establish a relative relationship between the plurality of items (<NUM>) represented by the plurality of modified sensory representations (<NUM>) with respect to the set of measurable factors of interest (<NUM>);
wherein the transformer (<NUM>) acquires the set of values (<NUM>) continuously over time from one or more sensor systems configured to monitor the set of measurable factors of interest (<NUM>);
wherein the transformer (<NUM>) adjusts the set of scale factors (<NUM>) to update the plurality of modified sensory representations (<NUM>) in substantially real-time as the set of values (<NUM>) changes;
wherein the entity sensory representation (<NUM>) represents the entity (<NUM>) using at least a sense of sound (<NUM>) ;
wherein the entity sensory representation (<NUM>) comprises an audio recording (<NUM>, <NUM>) and the plurality of sensory representations (<NUM>) comprises a plurality of sections (<NUM>, <NUM>) of the audio recording (<NUM>, <NUM>) comprising verbal instructions for performing a manufacturing operation, wherein each section represents instructions for performing a different step of the manufacturing operation; and
wherein the set of scale factors (<NUM>) is used to modify a loudness of each of the plurality of sections (<NUM>, <NUM>) according to the relative importance of the manufacturing operation of each of the plurality of sections (<NUM>, <NUM>).