Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The limitations, under their broadest reasonable interpretation, cover mental process using collected image data based on the visualization of collected image data to recognize the motion/movement of person by comparing/motion with reference based on observation, evaluating, judging and predicting (concept performed in a human mind, including as observation, evaluation, judgment, prediction, etc.). This judicial exception is not integrated into a practical application because the steps do not add meaningful limitations to be considered specifically applied to a particular technological problem to be solved. The claims 1-15 do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the steps of the claimed invention can be done mentally based on observation, evaluation, prediction, judgement based on visualizing the data and no additional features in the claims would preclude them from being performed as such except for the generic computer elements and generic display recited as high level of generality (i.e., processor and generic display)
According to the USPTO guidelines, a claim is directed to non-statutory subject matter if:
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), or
STEP 2: the claim recites a judicial exception, e.g. an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis:
STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
Using the two-step inquiry, it is clear that claims 1 and 19 are directed to an abstract idea as shown below:
Regarding independent claims 1 and 19.
STEP 1: Do the claims fall within one of the statutory categories?
YES.
Claims 1, 14 and 15 are directed to an image processing system, an image processing method and a non-transitory computer-readable medium storing a program which satisfy system, process and manufacture requirement.
STEP 2A (PRONG 1): Is the claim directed to a law of nature, a natural phenomenon or an abstract idea?
YES.
The claims are directed toward a mental process (i.e. abstract idea).
With regard to STEP 2A (PRONG 1), the guidelines provide three groupings of subject matter that are considered abstract ideas:
Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations;
Certain methods of organizing human activity – fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions); and
Mental processes – concepts that are practicably performed in the human mind (including an observation, evaluation, judgment, opinion).
Claims 1, 14 and 15 comprise a mental process that can be practicably performed in the human mind based on observation, evaluation, judgment, prediction, etc., based on the visualizing the image data and comparing/matching image data (except for generic optical sensor, generic computers or components and generic display) and, therefore, an abstract idea.
Regarding claim(s) 1, 14 and 15: (representative claim 1)
An image processing system comprising:
at least one memory storing instructions; and at least one processor executing the instructions to (generic computing hardware/software):
recognize a plurality of motion images indicating a motion of a person from image data related to a plurality of consecutive frames obtained by capturing the person who performs a series of motions (collecting a plurality of image data of a person which is insignificant extra solution activity and mental process of recognizing motion of a person by visualizing the plurality of collected image data and recognizing a plurality of motion of a person based on observation, evaluation, judgment and prediction);
determine whether or not each of the motion images and a predetermined reference motion are related to each other (mental process of determine whether or not each of the motion images and a predetermined reference motion are related to each other based on observation, evaluation, judgment and prediction by comparing/matching); and
assign a label to at least some of the consecutive frames in the motion image based on the determination (mental process of assigning labels/annotation/tags to plurality motion images based on observation, evaluation, judgment and prediction using pencil/paper).
The above limitations as drafted, is a simple process that, under their broadest reasonable interpretation, covers performance of the limitations in the mind based on observation, evaluation, judgment and prediction by comparing/matching motion images with reference using person/human intelligence . Furthermore limitations, “at least one memory storing instructions; and at least one processor executing the instructions to (generic computing hardware/software): recognize a plurality of motion images indicating a motion of a person from image data related to a plurality of consecutive frames obtained by capturing the person who performs a series of motions (collecting a plurality of image data of a person which is insignificant extra solution activity and mental process of recognizing motion of a person by visualizing the plurality of collected image data and recognizing a plurality of motion of a person based on observation, evaluation, judgment and prediction), determine whether or not each of the motion images and a predetermined reference motion are related to each other (mental process of determine whether or not each of the motion images and a predetermined reference motion are related to each other based on observation, evaluation, judgment and prediction by comparing/matching) and assign a label to at least some of the consecutive frames in the motion image based on the determination (mental process of assigning labels/annotation/tags to plurality motion images based on observation, evaluation, judgment and prediction using pencil/paper)” are insignificant.
The Examiner notes that under MPEP 2106.04(A) (2) (III), the courts consider a mental process (thinking, human intelligence) that can be performed in the mind/intelligence using a paper and pencil to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’" 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 ("‘[Mental processes and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 193, 197 (1978).
Other than generic and conventional computing hardware/instructions, generic imaging/optical sensing elements recited in the independent claims 1, 14 and 15, nothing in the independent claims 1, 14 and 15 elements preclude the processing from being performed as mental process, or merely based on the observations, evaluation, judgement, thought process based on comparing/matching plurality of motion images using person/human intelligence based on observation, evaluation, judgment and prediction i.e. mental process . The generic and conventional computing elements and imaging/optical sensing element recited in independent claims 1, 14 and 15 are a mere idea of a solution without details per MPEP 2106.05( f ) or the idea of a technological environment without detail per MPEP 2106.05 ( h ). The generic computing elements, generic imaging/optical elements and generic display are recited as just to automate the mental process (Step 2A, prong 1 Test Abstract idea = Yes).
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
The claims do not recite additional elements that integrate the judicial exception into a practical application.
With regard to STEP 2A (prong 2), whether the claim recites additional elements that integrate the judicial exception into a practical application, the guidelines provide the following exemplary considerations that are indicative that an additional element (or combination of elements) may have integrated the judicial exception into a practical application:
an additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to affect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
While the guidelines further state that the exemplary considerations are not an exhaustive list and that there may be other examples of integrating the exception into a practical application, the guidelines also list examples in which a judicial exception has not been integrated into a practical application:
an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea;
an additional element adds insignificant extra-solution activity to the judicial exception; and
an additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use.
Claim(s) 1, 14 and 15 do not recite any of the exemplary considerations that are indicative of an abstract idea having been integrated into a practical application.
Claim(s) 1, 14 and 15 recite(s) the further limitations of:
“at least one memory storing instructions; and at least one processor executing the instructions to (generic computing hardware/software):
recognize a plurality of motion images indicating a motion of a person from image data related to a plurality of consecutive frames obtained by capturing the person who performs a series of motions (collecting a plurality of image data of a person which is insignificant extra solution activity and mental process of recognizing motion of a person by visualizing the plurality of collected image data and recognizing a plurality of motion of a person based on observation, evaluation, judgment and prediction),
determine whether or not each of the motion images and a predetermined reference motion are related to each other (mental process of determine whether or not each of the motion images and a predetermined reference motion are related to each other based on observation, evaluation, judgment and prediction by comparing/matching) and
assign a label to at least some of the consecutive frames in the motion image based on the determination (mental process of assigning labels/annotation/tags to plurality motion images based on observation, evaluation, judgment and prediction using pencil/paper)”.
The above limitations are recited at a high level of generality (i.e. as a general action of mental process based on acquiring step) and amounts to mere post solution actions, which is a form of insignificant extra-solution activity without further detail. Furthermore, the claims are claimed generically and are operating in their ordinary capacity such that they do not use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
As stated above, other than generic and conventional computing hardware/instructions, generic imaging/optical sensing elements recited in the independent claims 1, 14 and 15, nothing in the independent claims 1, 14 and 15 elements preclude the processing from being performed as mental process, or merely based on the observations, evaluation, judgement, thought process based on comparing/matching plurality of motion images using person/human intelligence based on observation, evaluation, judgment and prediction i.e. mental process . The generic and conventional computing elements and imaging/optical sensing element recited in independent claims 1, 14 and 15 are a mere idea of a solution without details per MPEP 2106.05( f ) or the idea of a technological environment without detail per MPEP 2106.05 ( h ). The generic computing elements and generic imaging/optical elements are recited as just to automate the mental process (Step 2A, prong 2 Test Abstract idea = Yes).
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
NO.
The claims do not recite additional elements that amount to significantly more than the judicial exception.
With regard to STEP 2B, whether the claims recite additional elements that provide significantly more than the recited judicial exception, the guidelines specify that the pre-guideline procedure is still in effect. Specifically, that examiners should continue to consider whether an additional element or combination of elements:
adds a specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present; or
simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present.
As stated above, other than generic and conventional computing hardware/instructions, generic imaging/optical sensing elements recited in the independent claims 1, 14 and 15, nothing in the independent claims 1, 14 and 15 elements preclude the processing from being performed as mental process, or merely based on the observations, evaluation, judgement, thought process based on comparing/matching plurality of motion images using person/human intelligence based on observation, evaluation, judgment and prediction i.e. mental process . The generic and conventional computing elements and imaging/optical sensing element recited in independent claims 1, 14 and 15 are a mere idea of a solution without details per MPEP 2106.05( f ) or the idea of a technological environment without detail per MPEP 2106.05 ( h ). The generic computing elements and generic imaging/optical elements are recited as just to automate the mental process
Thus, since Claim(s) 1, 14 and 15 are: (a) directed toward an abstract idea, (b) do not recite additional elements that integrate the judicial exception into a practical application, and (c) do not recite additional elements that amount to significantly more than the judicial exception, it is clear that Claim(s) 1, 14 and 15 are not eligible subject matter under 35 U.S.C 101 (Step 2B, Test Abstract idea = Yes).
Regarding dependent claims 2-13, claims 2-13 further limit the abstract idea of performance of the limitations in the mind based on mental process of observations, judgement, evaluation, and thought process. Other than generic and conventional computing hardware/instructions, generic imaging/optical sensing elements recited in the independent claims 1, 14 and 15, nothing in the independent claims and dependent claims 2-13 elements preclude the processing from being performed as mental process, or merely based on the observations, evaluation, judgement, thought process based on comparing/matching plurality of motion images using person/human intelligence based on observation, evaluation, judgment and prediction i.e. mental process . The generic computing elements and generic imaging/optical elements are recited as just to automate the mental process recited in the independent claims 1, 14 and 15 and dependent claims 2-13 nothing in the independent/dependent claim (s) elements preclude the processing from being performed as mental process, or merely based on the observations, evaluation, judgement, thought process using based on the human intelligence and mental process. The generic and conventional computing elements, generic/conventional imaging/optical element recited in independent/dependent claims 2-13 is a mere idea of a solution without details per MPEP 2106.05( f ) or the idea of a technological environment without detail per MPEP 2106.05 ( h ). Furthermore the display control unit is insignificant post solution activity without any detail. There are no additional elements in the claims that would integrate the abstract idea into a practical application. The dependent claims 2-13 do not mention any improvement to a computer or to any other technology or technical field. The limitations of claims 2-13 fail to add inventive concept to otherwise mental process. Therefore the dependent claims 2-13b are no more than abstract idea without significantly more.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-15 are rejected under 35 U.S.C. 103 as being unpatentable over Kamel et al (Efficient Body Motion Quantification and Similarity Evaluation Using 3-D Joints Skeleton Coordinate, 2019 IEEE 2168-2216, IEEE TRANSACTION ON SYSTEM, MAN, CYBERNETICS: SYSTEMS, VOL. 51, NO. 5 MAY 2021, pages 2774-2788 USPTO-892) in view of CHIANG et al. (US 20210065022)
Regarding claims 1, 14 and 15 Kamel disclose image processing system/method/non-transitory computer-readable medium storing program (Kamel, Figs. 1-2, Abstract and page 2774, section I. INTRODUCTION ) comprising:
at least one memory storing instructions; and at least one processor executing the instructions to (Kamel, Figs. 1-2, Abstract and page 274, section I. INTRODUCTION, describe the system camera, deep learning model (CNN) Which obviously include memory storing instructions; and at least one processor executing the instructions and page 2777, section B. Motion Analysis):
recognize a plurality of motion images indicating a motion of a person from image data related to a plurality of consecutive frames obtained by capturing the person who performs a series of motions (Kamel Figs. 2-3, page 2777, section B Motion Analysis disclose “The development in motion capture systems opened the way to exploit the data for motion analysis and understanding human behavior. A variety of algorithms based on machine learning have been proposed to recognize the human actions from a 3-D skeleton model”, page 2777, Fig. 3 disclose consecutive frames Algorithm 2 );
determine whether or not each of the motion images and a predetermined reference motion are related to each other (Kamel, Fig. 2, page 2775 right column Kamel disclose Fig. 2. gives a general idea about our proposed method. The main contributions of this paper can be summarized as follows: 1) A motion quantification algorithm that estimates the movement of the body from only a raw 3-D joints coordinates without the need of prior knowledge about the body joints motion parameters that are usually offered by motion capture systems, which makes it appropriate to be used with any system that generates 3-D body joints, 2) A motion comparison algorithm evaluates the similarity between two motions based on the quantification of the joints movements. It assigns a percentage of similarity to each joint in each frame according to a calculated distance. The comparison algorithm can be applied to, e.g., applications that demand movement imitation. 3) The evaluation results comprehensively demonstrate the effectiveness of our motion quantification and Fig 2. pages 2779-2780 section C. Motion Comparison Kamel disclose a comparison algorithm between two skeletons motions to evaluate the performance of the quantification and provide an evaluation of motion similarity, which can be used for many human–computer interaction applications that demand imitating movements and automatic similarity evaluation. The comparison algorithm calculates the distance between two motions metrics, then evaluates their similarity depending on a given threshold for each metric. There are three levels for evaluation, joints comparison, frames comparison, then whole motion comparison. While the evaluation is based on a frame with frame comparison. This obviously corresponds to determine whether or not each of the motion images and a predetermined reference motion are related to each other ); and
assign a label to at least some of the consecutive frames in the motion image (Kamel in Fig. 1 show labelling different portion of joints and their motion).
Kamel has not explicitly disclose assign a label to at least some of the consecutive frames in the motion image based on the in the determination. However it would obvious to label the frames based on the result of comparison shown in Fig. 2 such as similarity percentage.
In the same field of endeavor CHIANG disclose determine whether or not each of the motion images and a predetermined reference motion are related to each other and assign a label to at least some of the consecutive frames in the motion image based on the determination (CHIANG disclose paragraph 0082 the motion data labeling system 100 of the present disclosure can be employed in a real-time tutorial, in order to provide an efficient way to manage the tutorial and better experience to the participants. For example, in a fitness class, each student and coach can wear the motion capture device 300 (or devices provide the same functions). These devices can be communicatively coupled to the motion data labeling system 100 via wireless connections (e.g., Bluetooth or the others). When the class takes place, the motion capture device 300 worn by the coach can keep collecting motion data from the coach and send the data to the motion data labeling system 100 so that the model of the motion trajectory passage MP can be trained. The motion capture device 300 worn by the student can keep collecting motion data from the student and send the data to the motion data labeling system 100. The motion data labeling system 100 can determine whether the motion of the student matches the motion trajectory passage MP (including the motion itself, the tempo, the time factors, or the others). The motion data labeling system 100 can further introduce a scoring method correspondingly. Furthermore, the coach can decide whether to give more intensive lessons based on the scores of the students, CHIANG paragraph 0083-0084 disclose It is noted that the processor 120 of the motion data labeling system 100 can execute the steps S3-S6, repeatedly, so as to filter some effective motion data from a big data of unlabeled motions based on specific standards e.g., matching the motion trajectory passage MP and the present invention provides a motion data labelling system, a motion data labelling method, and a non-transitory computer readable medium, which can build a standard motion trajectory passage, and determine whether the motion data matches the motion trajectory passage, and further label the motion data that passed the examination. Based on this mechanism, the system can automatically label the motion data that fits to the standard, which can improve the efficiency of data processing. All this obviously corresponds to determine whether or not each of the motion images and a predetermined reference motion are related to each other and assign a label to at least some of the consecutive frames in the motion image based on the determination as disclose by CHIANG).
Therefore it would be obvious before the filing data of the claimed invention to determine whether or not each of the motion images and a predetermined reference motion are related to each other and assign a label to at least some of the consecutive frames in the motion image based on the determination as shown by CHIANG and apply in the system of CHIANG because such a system/process provides automated system for student/participant performance in the fitness/sports classroom as stated by in paragraphs 000082-0084.
Regarding claim 2 Kamel disclose recognize the motion image from skeleton data regarding a structure of a body of a person extracted from the image data (Kamel Figs. 1-2 and section I, page 2775, right-column, last three paragraph page 2775 disclose the motion image from skeleton data regarding a structure of a body of a person extracted from the image data).
Regarding claim 3 Kamel disclose recognize the motion image from skeleton data including a movement of a finger of a person extracted from the image data (Kamel Figs 1-3 and Fig. 7, In the system of Kamel disclose recognize motion from skeleton and it would be obvious to includes hands and fingers to recognize the movement).
Regarding claim 4 Kamel disclose the skeleton data related to the motion is similar to the skeleton data as the reference motion based on a form of elements forming the skeleton data, the determination that the motion image is related to the reference motion (Kamel Figs 2-3 and page 2777 section B. Motion Quantification obviously skeleton data related to the motion is similar to the skeleton data as the reference motion based on a form of elements forming the skeleton data, the determination that the motion image is related to the reference motion i.e. coordinates).
Regarding claim 5 Kamel disclose recognize a body motion image from skeleton data regarding a structure of a body of a person extracted from the image data; and recognize an upper limb motion image from skeleton data of an upper limb including a movement of a finger of a person extracted from the image data, perform the determination on relevance of the reference motion corresponding to each of the body motion image and the upper limb motion image (Kamel Fig. 2-3 disclose movement of the upper limb and it would be obvious to include the finger motion in the system of Kamel such as shown in Fig. 7 the movement of finger).
Regarding claim 6 Kamel disclose whether or not one or both of the body motion image and the upper limb motion image are included in an analysis target according to a setting of a user, and perform the determination based on an image of a motion of the determined part (Kamel Figs 2-3 and 7 TABLE I, page 2783 show different/types sport motion and similarity score and Kamel in Fig. 2 and page 2777, section B. Motion Analysis disclose machine learning model in the system Kamel it would be obvious to whether or not one or both of the body motion image and the upper limb motion image are included in an analysis target according to a setting of a user, and perform the determination based on an image of a motion of the determined part ).
Regarding claim 7 CHIANG disclose recognize the motion image for each person when the image data includes a plurality of persons (CHIANG paragraph 0082-0084 disclose recognize the motion image for each person when the image data includes a plurality of person i.e. matching motion of participants with refence to recognize the motion).
Regarding claim 8 CHIANG disclose assigning means assigns the label indicating being related to the reference motion to the frame related to the motion image related to the predetermined reference motion (CHIANG paragraphs 0082-0084 disclose assigning means assigns the label indicating being related to the reference motion to the frame related to the motion image related to the predetermined reference motion).
Regarding claim 9 CHIANG disclose assign the label indicating being not related to the reference motion to the frame related to the motion image that is not related to any of the reference motions (CHIANG paragraphs 0082-0084, CHIANG comparing the motion of participants with reference/template MP and assign the label with matching score. In the system of CHIANG it would be obvious to label any participate motion image score [0] as not matching if the participant motion image is not matching).
Regarding claim 10 CHIANG disclose when the determination indicates that one of the motion images and a plurality of types of the reference motions are related to each other, assign a plurality of types of the labels to the corresponding frames in the image data (CHIANG paragraph 0082 it would be obvious assign the plurality of labels i.e. participant score, time factor, tempo and other as stated by CHIANG last six lines of paragraph 0082).
Regarding claim 11 CHIANG disclose assign the label in a user-editable manner (CHIANG paragraph 0082 disclose model for labelling system and the coach for fitness. In the system of CHIANG it would be obvious for coach to review motion score and labelling and be able to edit the labels based on coach assessment of matching and comparing) .
Regarding claim 12 CHIANG disclose stores a plurality of the predetermined reference motions in an updatable manner, determination is based on the updated reference motion (CHIANG paragraph 0082 disclose model for labelling system and matching/comparing motion of participant with MP i.e., template for labeling motions images and paragraph 0034-0035 CHIANG MP i.e. and various machine learning algorithms MP i.e. template. In the system of CHIANG it would be obvious to edit machine learning model and template (MP) for other fitness regimes for labelling and comparing/matching motion of participants disclosed in paragraph 0082).
Regarding claim 13 CHIANG disclose the reference motion for assigning the label to the motion image from motion data related to a plurality of the reference motions and perform determination base on the selected motion reference motion (CHIANG paragraph 0034-0035, paragraph 0082, CHIANG paragraph 0082 disclose model for labelling system and matching/comparing motion of participant with MP i.e., template for labeling motions images and paragraph 0034-0035 CHIANG MP i.e. and various machine learning algorithms MP i.e. template. In the system of CHIANG is obvious that the system includes reference motion for assigning the label to the motion image from motion data related to a plurality of the reference motions and perform determination base on the selected motion reference motion).
Communication Any inquiry concerning this communication or earlier communications from the examiner should be directed to ISHRAT I SHERALI whose telephone number is (571)272-7398. The examiner can normally be reached Monday-Friday 8:00AM -5:00 PM.
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ISHRAT I. SHERALI
Examiner
Art Unit 2667
/ISHRAT I SHERALI/Primary Examiner, Art Unit 2667
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