Complying with the NIH Public Access Policy - Copyright Considerations and Options

On January 11, 2008, the National Institutes of Health ('NIH') adopted a revised Public Access Policy for peer-reviewed journal articles reporting research supported in whole or in part by NIH funds. Under the revised policy, the grantee shall ensure that a copy of the author's final manuscript, including any revisions made during the peer review process, be electronically submitted to the National Library of Medicine's PubMed Central ('PMC') archive and that the person submitting the manuscript will designate a time not later than 12 months after publication at which NIH may make the full text of the manuscript publicly accessible in PMC. NIH adopted this policy to implement a new statutory requirement under which: The Director of the National Institutes of Health shall require that all investigators funded by the NIH submit or have submitted for them to the National Library of Medicine's PubMed Central an electronic version of their final, peer-reviewed manuscripts upon acceptance for publication to be made publicly available no later than 12 months after the official date of publication: Provided, That the NIH shall implement the public access policy in a manner consistent with copyright law. This White Paper is written primarily for policymaking staff in universities and other institutional recipients of NIH support responsible for ensuring compliance with the Public Access Policy. The January 11, 2008, Public Access Policy imposes two new compliance mandates. First, the grantee must ensure proper manuscript submission. The version of the article to be submitted is the final version over which the author has control, which must include all revisions made after peer review. The statutory command directs that the manuscript be submitted to PMC 'upon acceptance for publication.' That is, the author's final manuscript should be submitted to PMC at the same time that it is sent to the publisher for final formatting and copy editing. Proper submission is a two-stage process. The electronic manuscript must first be submitted through a process that requires input of additional information concerning the article, the author(s), and the nature of NIH support for the research reported. NIH then formats the manuscript into a uniform, XML-based format used for PMC versions of articles. In the second stage of the submission process, NIH sends a notice to the Principal Investigator requesting that the PMC-formatted version be reviewed and approved. Only after such approval has grantee's manuscript submission obligation been satisfied. Second, the grantee also has a distinct obligation to grant NIH copyright permission to make the manuscript publicly accessible through PMC not later than 12 months after the date of publication. This obligation is connected to manuscript submission because the author, or the person submitting the manuscript on the author's behalf, must have the necessary rights under copyright at the time of submission to give NIH the copyright permission it requires. This White Paper explains and analyzes only the scope of the grantee's copyright-related obligations under the revised Public Access Policy and suggests six options for compliance with that aspect of the grantee's obligation. Time is of the essence for NIH grantees. As a practical matter, the grantee should have a compliance process in place no later than April 7, 2008. More specifically, the new Public Access Policy applies to any article accepted for publication on or after April 7, 2008 if the article arose under (1) an NIH Grant or Cooperative Agreement active in Fiscal Year 2008, (2) direct funding from an NIH Contract signed after April 7, 2008, (3) direct funding from the NIH Intramural Program, or (4) from an NIH employee. In addition, effective May 25, 2008, anyone submitting an application, proposal or progress report to the NIH must include the PMC reference number when citing articles arising from their NIH funded research. (This includes applications submitted to the NIH for the May 25, 2008 and subsequent due dates.) Conceptually, the compliance challenge that the Public Access Policy poses for grantees is easily described. The grantee must depend to some extent upon the author(s) to take the necessary actions to ensure that the grantee is in compliance with the Public Access Policy because the electronic manuscripts and the copyrights in those manuscripts are initially under the control of the author(s). As a result, any compliance option will require an explicit understanding between the author(s) and the grantee about how the manuscript and the copyright in the manuscript are managed. It is useful to conceptually keep separate the grantee's manuscript submission obligation from its copyright permission obligation because the compliance personnel concerned with manuscript management may differ from those responsible for overseeing the author's copyright management. With respect to copyright management, the grantee has the following six options: (1) rely on authors to manage copyright but also to request or to require that these authors take responsibility for amending publication agreements that call for transfer of too many rights to enable the author to grant NIH permission to make the manuscript publicly accessible ('the Public Access License'); (2) take a more active role in assisting authors in negotiating the scope of any copyright transfer to a publisher by (a) providing advice to authors concerning their negotiations or (b) by acting as the author's agent in such negotiations; (3) enter into a side agreement with NIH-funded authors that grants a non-exclusive copyright license to the grantee sufficient to grant NIH the Public Access License; (4) enter into a side agreement with NIH-funded authors that grants a non-exclusive copyright license to the grantee sufficient to grant NIH the Public Access License and also grants a license to the grantee to make certain uses of the article, including posting a copy in the grantee's publicly accessible digital archive or repository and authorizing the article to be used in connection with teaching by university faculty; (5) negotiate a more systematic and comprehensive agreement with the biomedical publishers to ensure either that the publisher has a binding obligation to submit the manuscript and to grant NIH permission to make the manuscript publicly accessible or that the author retains sufficient rights to do so; or (6) instruct NIH-funded authors to submit manuscripts only to journals with binding deposit agreements with NIH or to journals whose copyright agreements permit authors to retain sufficient rights to authorize NIH to make manuscripts publicly accessible.

TCP Optimization through FEC, ARQ and Transmission Power Tradeoffs

TCP performance degrades when end-to-end connections extend over wireless connections-links which are characterized by high bit error rate and intermittent connectivity. Such link characteristics can significantly degrade TCP performance as the TCP sender assumes wireless losses to be congestion losses resulting in unnecessary congestion control actions. Link errors can be reduced by increasing transmission power, code redundancy (FEC) or number of retransmissions (ARQ). But increasing power costs resources, increasing code redundancy reduces available channel bandwidth and increasing persistency increases end-to-end delay. The paper proposes a TCP optimization through proper tuning of power management, FEC and ARQ in wireless environments (WLAN and WWAN). In particular, we conduct analytical and numerical analysis taking into "wireless-aware" TCP) performance under different settings. Our results show that increasing power, redundancy and/or retransmission levels always improves TCP performance by reducing link-layer losses. However, such improvements are often associated with cost and arbitrary improvement cannot be realized without paying a lot in return. It is therefore important to consider some kind of net utility function that should be optimized, thus maximizing throughput at the least possible cost.

3D Trajectory Recovery for Tracking Multiple Objects and Trajectory Guided Recognition of Actions

A mechanism is proposed that integrates low-level (image processing), mid-level (recursive 3D trajectory estimation), and high-level (action recognition) processes. It is assumed that the system observes multiple moving objects via a single, uncalibrated video camera. A novel extended Kalman filter formulation is used in estimating the relative 3D motion trajectories up to a scale factor. The recursive estimation process provides a prediction and error measure that is exploited in higher-level stages of action recognition. Conversely, higher-level mechanisms provide feedback that allows the system to reliably segment and maintain the tracking of moving objects before, during, and after occlusion. The 3D trajectory, occlusion, and segmentation information are utilized in extracting stabilized views of the moving object. Trajectory-guided recognition (TGR) is proposed as a new and efficient method for adaptive classification of action. The TGR approach is demonstrated using "motion history images" that are then recognized via a mixture of Gaussian classifier. The system was tested in recognizing various dynamic human outdoor activities; e.g., running, walking, roller blading, and cycling. Experiments with synthetic data sets are used to evaluate stability of the trajectory estimator with respect to noise.

Trajectory Guided Tracking and Recognition of Actions

A combined 2D, 3D approach is presented that allows for robust tracking of moving people and recognition of actions. It is assumed that the system observes multiple moving objects via a single, uncalibrated video camera. Low-level features are often insufficient for detection, segmentation, and tracking of non-rigid moving objects. Therefore, an improved mechanism is proposed that integrates low-level (image processing), mid-level (recursive 3D trajectory estimation), and high-level (action recognition) processes. A novel extended Kalman filter formulation is used in estimating the relative 3D motion trajectories up to a scale factor. The recursive estimation process provides a prediction and error measure that is exploited in higher-level stages of action recognition. Conversely, higher-level mechanisms provide feedback that allows the system to reliably segment and maintain the tracking of moving objects before, during, and after occlusion. The 3D trajectory, occlusion, and segmentation information are utilized in extracting stabilized views of the moving object that are then used as input to action recognition modules. Trajectory-guided recognition (TGR) is proposed as a new and efficient method for adaptive classification of action. The TGR approach is demonstrated using "motion history images" that are then recognized via a mixture-of-Gaussians classifier. The system was tested in recognizing various dynamic human outdoor activities: running, walking, roller blading, and cycling. Experiments with real and synthetic data sets are used to evaluate stability of the trajectory estimator with respect to noise.