Source: http://www.google.com/patents/US6888951?dq=7,181,690
Timestamp: 2015-07-07 13:20:32
Document Index: 64235123

Matched Legal Cases: ['application No. 60', 'art 172', 'art 172', 'art 240', 'art 122', 'art 172', 'art 172', 'art 172', 'art 171', 'art 172', 'art 171', 'art 172', 'art 171', 'art 172', 'art 129', 'art 121', 'art 110', 'art 120', 'art 120', 'art 123', 'art 123', 'art 122', 'art 123', 'art 123', 'art 125', 'art 124', 'art 125', 'art 126', 'arts 124', 'art 126', 'art 125', 'art 126', 'art 127', 'arts 124', 'art 127', 'art 126', 'art 127', 'arts 126', 'arts 128', 'arts 124', 'arts 128', 'art 127', 'art 128', 'art 127', 'art 128', 'art 128', 'art 129']

Patent US6888951 - Methods and apparatus for analyzing operational and analyte data acquired ... - Google PatentsSearch Images Maps Play YouTube News Gmail Drive More »Sign inAdvanced Patent SearchPatentsMethods and apparatus for analyzing nonoperational data acquired from optical discs, and in particular, trackable optical discs having concurrently readable nonoperational structures are provided. Analysis can involve identifying patterns in the data that reproducibly distinguish underlying structures,...http://www.google.com/patents/US6888951?utm_source=gb-gplus-sharePatent US6888951 - Methods and apparatus for analyzing operational and analyte data acquired from optical discAdvanced Patent SearchPublication numberUS6888951 B1Publication typeGrantApplication numberUS 09/378,878Publication dateMay 3, 2005Filing dateAug 23, 1999Priority dateAug 23, 1999Fee statusPaidAlso published asUS7664289, US20050053260Publication number09378878, 378878, US 6888951 B1, US 6888951B1, US-B1-6888951, US6888951 B1, US6888951B1InventorsMark O. Worthington, Gregory R. BasileOriginal AssigneeNagaoka & Co., Ltd., Burstein Technologies, Inc.Export CitationBiBTeX, EndNote, RefManPatent Citations (63), Non-Patent Citations (18), Classifications (13), Legal Events (11) External Links: USPTO, USPTO Assignment, EspacenetMethods and apparatus for analyzing operational and analyte data acquired from optical disc
US 6888951 B1Abstract
Methods and apparatus for analyzing nonoperational data acquired from optical discs, and in particular, trackable optical discs having concurrently readable nonoperational structures are provided. Analysis can involve identifying patterns in the data that reproducibly distinguish underlying structures, or identifying patterns in the data that report physical properties of the nonoperational structures. When an optical disc has a plurality of physically nonidentical concurrently readable nonoperational structures, analysis can involve identifying patterns in the data that distinguish among the physically nonidentical nonoperational structures. Also, relative physical locations of nonoperational structures on the disc can be calculated. A system for remotely analyzing data in order to expedite complex data analysis and reporting the results thereof is also provided.
The present invention relates to methods and apparatus for analyzing nonoperational data acquired by reading optical discs, and in particular, by reading trackable optical discs having concurrently readable nonoperational structures. More particularly, the methods and apparatus described herein may be used to identify, discriminate, and classify patterns in the data that report one or more physical properties of nonoperational structures disposed upon or within an optical disc. The invention also relates to methods and apparatus for interpreting clusters of such patterns and methods of mapping them according to positional information present within the digital data.
In the two decades since the development of audio compact discs, the progression of standards for physically mastering data on optical discs has been matched by a corresponding evolution in the logical approaches to encoding the data. Thus, the progression from single data layer discs with pits mastered along a continuous spiral to multiple data layer discs with zoned wobbled grooves has been matched by a corresponding evolution from the eight-to-fourteen modulation of CIRC-encoded digitized audio data to the sophisticated data encoding strategies established for DVD video and DVD-RAM.
The present invention solves these and other problems in the art by providing methods and apparatus for analyzing data acquired by reading an optical disc having at least one readable nonoperational structure, the methods and apparatus including the step of identifying patterns in the data that report a physical property of the nonoperational structure. The present invention particularly provides methods and apparatus for analyzing data acquired by reading a trackable optical disc having at least one concurrently readable nonoperational structure.
In order that the invention herein described may be fully understood, the following detailed description is set forth. In the description, the following terms are employed.
As used herein, the term “radial” denotes, in the plane of one or more of a disc's data-encoding surfaces, the direction forward or backward along a tracking spiral. A disc surface, according to this invention, can be an internal or external surface.
As used herein, the term “tangential” denotes, in the plane of one or more of a disc's data-encoding surfaces, the direction inward or outward along a line drawn from the disc's physical center to its outer circumference.
As used herein, the phrase “radial plane” refers to the plane in which a disc's tracking (e.g., spiral tracking) features are disposed, and is the plane of one or more of the disc's data-encoding surfaces.
As used herein, the term “nonoperational structure” or investigational features means any structure on or within an optical disc that is capable of producing a signal when the disc is read by an optical disc reader, the signal of which, however, is not required (although possibly useful) for drive operation during reading. Nonoperational structures and investigational features include, for example, analyte-specific signal elements, as described immediately below.
As used herein, the term “analyte-specific signal element” refers to any nonoperational structure that may be used to signal the presence of a specific analyte in a sample applied to an optical disc. The term thus includes, inter alia, such signal elements as are exemplified herein—including beads—as well as those that are described in copending and commonly owned U.S. patent application Ser. Nos. 08/888,935 filed Jul. 7, 1997, 09/120,049 filed Jul. 21, 1998, 09/183,842 filed Oct. 30, 1998, and 09/311,329 filed May 14, 1999, the disclosures of which are incorporated herein by reference in their entireties. The term includes both those structures that are alone detectable by an optical disc reader and those that require additional components to be rendered detectable.
As used herein, the term “turn” denotes a 360� arc of a spiral track of an optical disc.
Although the outer diameter of the spheres used in the examples of this invention is typically on the order of microns (i.e., μm), it will be appreciated that a wide range of sizes can be detected and characterized according to this invention. Thus, a nonoperational structure can be almost any structure of sufficient size to be detectable—with commercially-available optical disc readers, presently about � the incident laser wavelength—yet not so large as to interrupt tracking, focus, speed control, or synchronization. The protean nature of such structures—the extraordinary range in permissible size, reflectivity, absorbence, and shape—creates an enormous diversity in resulting signal patterns.
In order to selectively acquire data from any portion of an optical disc (e.g., the portion with nonoperational structures disposed thereon), physical synchronization markers can be used, as described more fully in Worthington et al. U.S. patent application No. 60/150,288 filed Aug. 23, 1999, entitled “Methods and Apparatus for Optical Disc Data Acquisition Using Physical Synchronization Markers” which is hereby incorporated by reference in its entirety.
First, a lead was attached to tap the nonequalized HF output of the drive. The analogue HF signal was buffered with a unity gain amplifier and input to an ULTRAD-1280 dual 40 MHZ 12 bit A/D PCI data acquisition board (Ultraview Corporation, Orinda, Calif.) installed, with its own bundled software, in a second Pentium� processor-based personal computer (the “data” computer). In Example 3, described briefly above and in detail below, the HF signal was fed in real time to a digital oscilloscope to generate the tracings shown in FIGS. 13-18. The ULTRAD data acquisition board permits the analogue signal to be sampled, digitized, and written as a bit stream to a binary file on the computer's hard disk, thereafter to be interpreted by software.
If it is determined in step 32 that the data item is operational, it may be determined in step 33 whether the operational data item is the last data item in the record (e.g., an end of data marker). If the number of data items contained in the data record is known, one way that this determination can be made is by counting the data items retrieved in step 31 and comparing the count with the known number. Another way to make this determination is by decoding one or more identifying bits (i.e., a logical synchronization marker) that may be contained within or adjacent to the data item. Yet another way to make this determination is by use of a physical synchronization marker (i.e., an “end of data” marker), as described more fully in U.S. Provisional Application Ser. No. 60/150,288 which is hereby incorporated by reference herein. If the data item is determined to be the last item in the record, control of the process can be returned to a higher level via step 36. Although FIG. 3 shows step 33 after step 32, it will be appreciated that the determination made in step 33 can be made at any time during process 30, including before step 32.
As discussed above, the data items processed according to process 40 correspond to time- or position-varying data points that represent a varying amount of returned optical energy. As shown in trace chart 172 of FIG. 20, five sets of position-dependent track data are selected and plotted between radial track positions −850 μm and −820 μm. The amplitude in the middle three data sets varies substantially at radial positions between about −835 μm and −825 μm. As described above, certain amplitude variations are believed to be due to the presence of nonoperational structures (e.g., analyte-specific signal elements) on the surface of or contained within the optical disc (e.g., an external or internal surface). The process shown in FIG. 4, then, characterizes these amplitude variations by measuring their width measured above or below a given amplitude threshold. As used herein, the term “width” refers to the time period, or equivalently the radial distance along a track, that the amplitude remains above (or below, depending on the sign of the signal) the amplitude threshold. After the width of a data feature is measured, the width can be used to determine the type of underlying structure (e.g., whether the structure is an analyte-specific signal element or a dust particle), such as by comparing the width to one or more previously identified width values. Such values can be stored in a computer database for automated comparison.
For example, as shown in trace chart 172 shown in FIG. 20, position-dependent signal 174 includes substantially flat portions 175 and 176 and may include one or bumps and/or dips 177. Although dependent upon the nature of the original data acquisition and storage, a dip typically indicates a decrease in the amount of returned light. To detect such a dip, amplitude threshold 178 preferably has a sign that is the same as the dip and a magnitude that is less than or equal to the dip amplitude (as measured from the flat background portion of the signal). A signal refers to any electrical analog signal generated by a photodetector, or the like, in response to receiving light, and includes, for example, signals derived from a high frequency (“HF”) signal, a tracking error signal, a focus error signal, and any combination thereof.
FIG. 6 is a flow chart of steps for carrying out an illustrative embodiment of process 50 according to this invention. Although any number of result objects can be created and displayed according to this invention, three composite result objects, which were created according to this invention, are described in detail below. The three result objects include a map chart, which can be displayed in step 61, a jitter chart, which can be displayed in step 62, and a histogram chart, which can be displayed in step 63. As explained more fully below, FIG. 8, for example, shows user selectable buttons 101, 102, and 103, which are labeled “Map/Trace,” “Histogram,” and “Jitter,” respectively, for displaying respective charts in steps 61-63. Each of these result objects were designed to capture different aspects of data retrieved in step 13 of FIG. 1. It will be appreciated that other result objects can be designed to capture other aspects of the data, including, for example image chart 240, as shown in FIG. 35.
A “map” chart is a result object that can be used for graphically displaying operational and nonoperational features as a function of position. In one embodiment, the features are superimposed on a schematic of an optical disc. Examples of operational data features that have been used according to this invention include track markers and data collection start and stop markers. Examples of nonoperational data features include data features that corresponds to nonoperational structures, such as beads. It has been found that a map chart displayed in accordance with this invention is useful for finding spatially-dependent correlations between mapped features on nearby (e.g., adjacent) tracks and for finding other qualitative relationships between such data features.
For example, a map chart (and/or a “trace” chart, which is discussed more fully below) can be helpful in determining whether multiple amplitude variations on two or more adjacent tracks correspond to a single, underlying structure. This could occur, for example, when a single nonoperational structure, such as an analyte-specific signal element (e.g., a bead), is sufficiently large to produce amplitude variations (i.e., a cluster of amplitude variations) on two or more tracks. A “cluster profile” characterizes the spatial arrangement, magnitude, and/or shape of such amplitude variations. It has been discovered that different types of signal elements can produce different cluster profiles. Therefore, according to this invention, data that includes a cluster of amplitude variations can be compared, using any conventional comparison technique, with one or more known cluster profiles in order to identify the type of underlying structure. As mentioned above, map and/or trace charts can be used to visually identify clusters. FIG. 11 b, for example, is a zoomed-in map chart 122 a that shows seven clusters 198, each of which includes three or four distinct features (e.g., features 199 a, 199 b, and 199 c).
As described briefly above with respect to distinguishing complex data features, an automated process can be used to identify unknown clusters appearing in the data. One example of such an automated process includes detecting and/or identifying a first data feature (e.g., according to process 40) using a first set of criteria (e.g., amplitude and width criteria), and then detecting and/or identifying a second “local” feature using a second set of criteria. If a known cluster profile includes three or more features, the automated process for identifying such a cluster can include additional detection steps. Once again, these data features correspond to physical structures and that the term local could be either refer to the real physical position of the underlying structure of the mapped physical representation of the data feature.
It will be appreciated that a cluster of data features could appear in the data when two or more discontinuous data features (e.g., patterns) correspond to different structures (e.g., different physical portions of a single bead, multiple coupled beads, etc.) positioned about 360� apart (e.g., on adjacent turns) of a spiral track. It will be further appreciated that any useful selection rules could be used to identify such clusters and that the “local” definitions described above are merely demonstrative. It will be further appreciated that two or more of these selection rules could be used in combination, as necessary.
A “histogram” chart is an example of a result object that can be used for graphically displaying (i.e., in a histogram) information regarding nonoperational structures. In particular, it has been found that a histogram chart displayed in accordance with this invention (such as the one shown in FIG. 12) can be useful for determining appropriate amplitude thresholds, such as for use in process 40 of FIG. 4.
A “jitter” chart is another example of a result object that can be created and output according to this invention. A jitter chart may be used for graphically displaying (e.g., in a histogram) jitter. Jitter normally refers to any rapid variation in the amplitude, frequency, or other characteristic of a signal, including, for example, variation in the width of data features. Process 40 of FIG. 4 shows one way to detect data features and to determine widths for a given data set.
Located at the top of trace region 180 is “Track Frst/Nbr,” which identifies first trace track 182 and trace number 183. As shown in FIG. 20, track 182 is the first trace displayed in trace chart 172. Trace number 183 is the number of tracks displayed in trace chart 172. Together, first track 182 and trace number 183 define the range of traces (i.e., tracks) included in trace chart 172. This range may be useful because it can include substantially fewer tracks than are shown in map chart 171. By choosing an appropriate range, a user can display a convenient subset of tracks for detailed analysis of raw or processed data. In one embodiment, the tracks included in the trace chart can be highlighted, or otherwise identified, in the map chart.
“Multi-Trace Offset (in Volts)” identifies offset 184 and is located in trace region 180. Offset 184 contains a value in volts that determines the vertical distance between successive traces of trace chart 172. Without an offset, all of the traces would be superimposed on top of one another. “Merge Panes” identifies merge button 185. When selected, merge button 185 eliminates space 175 between map chart 171 and trace chart 172, causing the two charts to merge (not shown). This allows more resolution and space for displaying map and trace charts by eliminating “dead” space between the two charts. “Print with Map” identifies print button 186. When button 186 is selected, trace chart will automatically print when a map chart prints. “Select to Zoom” identifies zoom button 187. When selected, a user is provided with an opportunity to select with a pointing device (e.g., a mouse) a region (i.e., subset) of map chart for display in a trace chart without specifying the first trace track and number of traces. “Hide” and “Show” identifies Hide and Show Trace buttons 188 and 189. When a map chart is being displayed in accordance with this invention, “Show” button 188 provides a user with an ability to simultaneously display a trace chart. Alternatively, “Hide” button 189 provides a user with an ability to not display a trace chart. In FIG. 20, for example, map chart 171 is displayed simultaneously with trace chart 172. In FIG. 19, map chart 129 is displayed without a trace chart. Although a trace chart can be linked to a map chart in one illustrative embodiment of this invention, it will be appreciated that the trace chart and the map chart need not be linked and could be displayed separately.
Rather than display data, a map chart replaces raw or processed data (e.g., that correspond to particular nonoperational structures) with mapping markers. A mapping marker is used to identify any discernible feature in the data, including, for example, a single data item, a group of data items, or a cluster of features. Mapping markers of any type can be used according to this invention, including the solid squares shown in FIG. 11. Preferably, the type of markers displayed is user-selectable. Some of the different types of markers that may be selected and displayed on a map chart include, but are not limited to, solid and open squares (e.g., “▪” and “□”) solid and open diamonds (e.g., “♦” and “⋄”), solid and open circles (e.g., e.g., “●” and “◯”), up and down carets (e.g., “^” and “”), etc. Furthermore, markers of different types, sizes, and colors can be displayed simultaneously on a single map chart to identify and differentiate between different types of data features. “Mapping Markers” identifies marker type 192 in visual panel 190. In FIGS. 10, 11, 14-20, “Solid Square1” is the selected type of mapping marker, and is used for display in their respective map charts.
Features can be grouped into viewable classes for inclusion in result objects and output, such as in map charts. An example of a viewable class is the set of features that meets specific selection rules (e.g., width criteria). Map charts can then display the selected viewable class by replacing the data corresponding to selected features with viewable elements. Any type of viewable element can be displayed in map charts in accordance with this invention, including, for example, circles, lines, spheres, ellipses, etc. Preferably, the type of viewable classes displayed is user-selectable. Some of the different types of viewable classes that may be selected (e.g., as shown in FIGS. 10, 11, 14-20) and displayed in a map chart include, but are not limited to, “MapBounds,” “MapCircle,” “MapTrack,” “MapTracedTrack,” “MapPoint,” “MapSphereEllipse,” “MapSphereCircle,” “MapsphereLine,” “MapObectLine,” “TraceLine,” “TraceThreshold,” etc. Each viewable class can be defined differently and, when used to create a map chart, can provide a user a unique different way to view the data. As shown in the FIGS., the ability to select a particular viewable class can be provided on visual panel 190 as viewable class 193 and is identified by “Viewable Classes.” “Color” button 194, when selected, provides the user to select one or more colors.
As shown in FIG. 14 b, printing options are provided to a user in step 74 with “Print” and “Print SetUp” buttons, possibly on printer panel 200 when printing tab 201 is selected. Alternatively, printing options can be provided to a user on a drop down menu.
After any of steps 72, 73, and 74, a map chart may be displayed in step 76, with or without a trace chart in step 77, in accordance with the particular display options selected (e.g., whether “Hide” button 188 or “Show” button 189 is engaged). After selected result objects are displayed in steps 76 and 77, a user can repeat the process by immediately returning to the beginning of process 70 or by printing the map and/or trace chart(s) in step 79 a directly. In step 79, a user may select to exit process 70.
Alternatively, a user may be provided an opportunity to create a submap file in step 75, such as by modifying a current map chart and then saving the modified object. This opportunity could be made available to a user when the user selects “file” and then “Save” (see below). In one embodiment, the user is provided with an ability to specify a submap filename and header information, and to process map data and trace information.
Region 110 of screen 100 includes a number of Windows™-based options, including “File,” “View,” “SubMap,” and “Help.” When selected, these options provide a user with a drop-down menu that includes additional details or options.
When “File” is selected, a drop-down menu may be provided to a user. Such a drop-down menu can contain various file-related options, including “Open,” “Save,” “Print,” and “Print Setup.” An “Open” option can be one way to initiate data retrieval according to step 13 of FIG. 1. “Save” and “Print” options can be used to initiate data analysis and output in steps 14 and 16 of FIG. 1. A standard option that may be further included in such a drop down menu, even though unrelated to file activities, is the self-explanatory “Exit” button.
When “View” is selected, a drop-down menu can be provided to a user. Such a drop-down menu can contain various result object viewing options, including “Map,” “Trace,” “Histogram,” “Jitter,” and “Debug Information.” When “Map,” “Trace,” “Histogram,” or “Jitter” is selected, the respective chart(s) may be displayed in charting region 120. As explained above, another way to display these charts is through user selectable buttons 101, 102, and 103. “When “Debug” is selected, a debug information panel, such as panel 170 of FIG. 9, may be provided. Some of the information that can be included in panel 170 is current track being processed and number of data points processed (i.e., “Trk Curr/NbrPts”) 171 a and 171 b, number of features detected and number of these features that meet the width criteria, i.e., identified as spheres (“Nbr Pts/Sphs”) 172 a and 172 b, total number of data points read from the file (“Total Pts Read”) 173, current position of the data file in bytes (“File Position”) 174, starting and ending points plotted in the chart (“Points Plotted”) 175 a and 175 b, number of skipped points passed and failed (“Points Skipped”) 176 a and 176 b, high and low numbers of points per track (“Points Per Trk”) 177 a and 177 b, total number of data points tested during processing (“Total Pts Tested”) 178, and difference between the number of detected features and number of those features determined to correspond to spheres (“Difference”) 179.
When “Submap” is selected, a drop-down menu may also be provided to a user that contain one or more options relating to a subset of the map chart, including “Save” and “Restore.” The “Save” option can be one way to initiate data storage according to steps 75 and 78 of FIG. 7. The “Restore” option can be used to retrieve previously stored data or result objects, such as according to step 13 of FIG. 1.
In FIG. 8, no data are displayed in map chart 121. In this embodiment, and as explained in more detail above, a map chart can be used to map result objects (e.g., that may include operational and/or nonoperational data) onto optical representation 130. For this purpose, the concentric circles superimposed on chart 110 depict various physical and/or logical boundaries of disc 130. For example, innermost circle 132 may depict the outermost circumference of the mounting ring of disc 130, with circle 135 depicting the outer diameter of optical disc 130. Circle 133 may depict the stacking ring or, alternatively, may depict the innermost edge of data storage region 131, commonly referred to as the “lead-in” boundary. Similarly, circle 134 will often depict the outermost edge of data storage region 131 and is, in such cases, sometimes referred to as the “lead-out” boundary. The x and y axes of chart 120 are measured in distance (i.e., μm) from the center of optical disc 120.
“Trk Start/Stop” identifies start and stop data track fields 141 and 142 used in a decoding process according to this invention. Together, fields 141 and 142 define a range of tracks. As shown in FIG. 8, the default values of these track fields are 800 and 830. After data 160 is loaded, a map chart can be displayed, as shown in FIG. 10. The start and stop tracks used in FIG. 10 are 1 and 2,000. It will be appreciated that although a user may choose to zoom in on data 160 of map chart 120 with zoom window 152, as shown in FIG. 11 (where only a subset of tracks is displayed), the start and stop tracks specified in fields 141 and 142, respectively, remain unchanged. Alternatively, the start and stop tracks displayed in fields 141 and 142 could reflect the dimensions of the zoom window.
“TH Raw/Volts” identifies amplitude threshold fields 143 and 144. Field 143 contains a digital representation of the amplitude threshold between 1 and 4096. It will be appreciated that the maximum value depends on the level of quantization performed by the analog-to-digital converter used to convert the time-varying signal. The value in field 144 is an equivalent voltage corresponding to the value in field 143. As explained above, other threshold criteria could be used, including the sign and/or slope of the time-varying signal.
“Sph Min/Max” identifies minimum and maximum acceptable widths 145 and 146. As already described with respect to step 47 of FIG. 4, a width can be calculated for a feature (such as a bump or a dip) in a time-varying signal. The width corresponds to the size (in units of time or distance) of the underlying structure and scales with the number of data items (e.g., points) that meet the amplitude threshold criteria. If the measured width falls within the range defined by fields 145 and 146 (e.g., see step 50 of FIG. 4), a result object corresponding to the feature can be stored for output. Together, the minimum and maximum acceptable widths defines a range (i.e., a window) of acceptable widths.
Three user-selectable buttons are provided in panel 140. “Start” button 147 and “Stop” button 148 starts and stops data analysis (e.g., processing according to process 40 of FIG. 4). “Clip” button 149 provides a user with another opportunity to save a modified map chart (e.g., creating a Submap according to steps 75 and 78). Once again, the user can be provided with an ability to specify a Submap filename and/or header information, and to further process map data and/or trace information.
Near the bottom of panel 140 are a few display-related information boxes. “Trk Upd/Curr” identifies both the number 149 a of tracks to be processed between display updates and the number 149 b of the current track being processed. “Nbr Pts/Sphs” identifies the number 149 c of data points processed and the number 149 d of data features that meet the width criteria—namely, the number of features that fall within the range defined by minimum and maximum acceptable widths 145 and 146.
Control panel 150 includes three options that are used exclusively for controlling zoom. First, “Zoom Off” identifies Zoom Off button 156. When selected, button 156 prevents a pointing device from controlling the zoom control. Second, “Zoom In” identifies Zoom In button 157. When selected, button 157 allows a pointing device to be used for selecting a window (i.e., box) in a currently displayed result object (e.g., a map chart). After being selected, the current result object (e.g., map chart) is redisplayed with the portion defined by the box enlarged. Third, “In/Out” identifies In/Out button 158. The purpose of In/Out button 158 is essentially the same as Zoom In, except for one difference. If a zoom box (e.g., box 152) is drawn from lower right hand corner 152 a to upper left hand corner 152 b, the zoom power will be adjusted in proportion to the area of the box compared to the area of the current chart.
Control panel 150 also includes one option that is used exclusively for controlling the pan direction. “Pan” identifies pan button 159, which, when selected, allows a map chart to be panned by a user.
Finally, control panel 150 includes two options that can affect both the zoom and pan settings. First, “Reset” identifies reset button 159 a, which, when selected, resets a map chart to a default display size and position. Second, “Recall” identifies recall representation 159 b, which identifies which of the previously used zoom (and/or pan) displays is currently being viewed.
FIG. 13 shows an illustrative embodiment of a graphical user interface with jitter (e.g., width) histogram chart 123 constructed according to this invention. Although jitter chart 123 is a histogram, the term “jitter” is used to distinguish it from amplitude histogram chart 122 b. Jitter chart 123 shows the number of data points in various segments of a width band. Thus, the x-axis has units of distance (e.g., μm) or time and represents the width of a data feature detected during a decoding process (e.g., process 40 of FIG. 4). The y-axis represents the number of features that fall within a particular width segment. As shown in FIG. 13, chart 123 includes a plurality of distinct peaks, including peaks at about 1.8, 3.8, and 4.4 μm.
FIG. 15 shows an illustrative embodiment of a graphical user interface, including map chart 125, that has been constructed according to this invention. Like map chart 124, map chart 125 only shows the tracks located in the region between about 24,575 and 24,620 μm of the y-axis and between about −842 and −894 μm of the x-axis. Only solid square mapping markers are shown in FIG. 15. There can be no visible viewable objects shown because viewable classes “visible” button 195 is not selected. The mapping markers shown in FIG. 15 correspond to all of the data features found within the zoomed region, regardless of their widths.
FIG. 16 shows an illustrative embodiment of a graphical user interface, including map chart 126, that has been constructed according to this invention. Like map charts 124 and 125, map chart 126 only shows the tracks located in the region between about 24,575 and 24,620 μm of the y-axis and between about −842 and −894 μm of the x-axis. Unlike map chart 125, which includes solid square mapping markers, map chart 126 includes no mapping markers. Rather, map 126 includes one viewable class—spheres. The spheres were created using minimum and maximum acceptable widths of 2.7 μm and 4.1 μm, respectively.
It will be appreciated that a map chart created according to this invention can include any number of viewable classes with different width criteria for detecting different size or type signal elements. For example, FIG. 17 shows an illustrative embodiment of a graphical user interface, including map chart 127, that has been constructed according to this invention. Like map charts 124-126, map chart 127 only shows the tracks located in the region between about 24,575 and 24,620 μm of the y-axis and between about −842 and −894 μm of the x-axis. Unlike map chart 126, which includes a viewable class of spheres, map chart 127 includes a different viewable class—ellipses. The spheres and ellipses included in map charts 126 and 127 were created with different processes using different width criteria. In particular, the spheres were created using minimum and maximum acceptable widths of 2.7 and 4.1 μm, respectively, and the ellipses were created for any features that met the threshold criteria (i.e., crossed the threshold). The width of each ellipse represents the length of time the data met the criteria (see FIG. 4).
FIGS. 18 and 19 show illustrative embodiments of a graphical user interface, including map charts 128 and 129, respectively, that have been constructed according to this invention. Like map charts 124-127, map charts 128 and 129 only show tracks located in the region located between about 24,575 and 24,620 μm along the y-axis and between about −842 and −894 μm along the x-axis. Like map chart 127, map chart 128 only shows features that have widths that fall between the minimum and maximum acceptable widths of 2.7 and 4.1 μm, respectively. The only difference between map chart 127 and map chart 128 is that map chart 128 uses one viewable class of horizontal lines—not two viewable classes of spheres and ellipses. Furthermore, map chart 129 only shows features that have widths that fall outside the range defined by the minimum and maximum acceptable widths of 2.7 and 4.1 μm, respectively. The same features were also shown in FIG. 124, but in combination with features (i.e., two viewable classes of spheres and ellipses) that fall inside the same range. The physical widths used by this process were calculated by dividing by 10 the values used in minimum and maximum acceptable widths 145 and 146.
Positional Mapping of Stochastically Disposed Beads on the Surface of an Optical Disc
A single data layer inverted wobble groove optical disc was manufactured essentially as described in co-pending and commonly owned U.S. patent application Ser. No. 09/311,329 filed May 14, 1999, incorporated herein by reference in its entirety. The disc was cleaned with oxygen plasma at 75 Watts for 1 minute. A 1.5 μL aliquot of streptavidin-coated magnetic Dynabeads� (2.8 μm diameter, Dynal, suspended in water at approximately 1,000 beads/μL) was spotted onto the disc's cleaned gold surface approximately 25 mm from the physical center of the disc (i.e., from the center of the mounting ring).
Discrimination and Classification of Nonoperational Feature Structures Using Data Feature Patterns
A single data layer inverted wobble groove optical disc was manufactured essentially as described in co-pending and commonly owned U.S. patent application Ser. No. 09/311,329 filed May 14, 1999, incorporated herein by reference in its entirety.
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