Prior User Research Articles

Prior Use as Trade Secret Versus Obtaining a Patent

Trade secrets and patents have a thin line of difference, indeed, and it is particularly for the integrity of trade secrets that prior user rights are very important. It is not possible and practicable to obtain patents on all patentable albeit marginal inventions and it would be much too costly. Being 'first,' however, does not automatically entitle an inventor to a patent. In certain instances a subsequent independent inventor may receive a patent. In other instances, the first inventor may receive the patent after a subsequent independent inventor has already commercially used, or taken substantial steps to commercially use, the invention before the filing date of the first inventor/patentee. It is in these situations that the concept of prior user rights is relevant. These rights would provide a limited defense for any party who independently develops or uses the subsequently patented invention, in good faith, before the patentee's filing date, who continues such development or use after the patent issues, and who is sued by the patentee for infringement. In this situation, the party (the prior user) could claim a prior user right and legally continue to exploit the invention in a manner that normally would constitute infringement. This article addresses the rationales for the adoption of prior user rights in the United States' first-to-invent patent system with a comparative study in the Indian legal scenario.

Context-Aware Expert Finding in Tag Based Knowledge Sharing Communities

With the rapid development of online Knowledge Sharing Communities (KSCs), the problem of finding experts becomes increasingly important for knowledge propagation and putting crowd wisdom to work. A recent development trend of KSCs is to allow users to add text tags for annotating their posts, which are more accurate than traditional category information. However, how to leverage these user-generated tags for finding experts is still underdeveloped. To this end, this paper develops a novel approach for finding experts in tag based KSCs by leveraging tag context and the semantic relationship between tags. Specifically, the extracted prior knowledge and user profiles are first used for enriching the query tags to infer tag context, which represents the user’s latent information needs. Specifically, two different approaches for addressing the problem of tag sparseness in authority ranking are proposed. The first is a memory-based collaborative filtering approach, which leverages non-negative matrix factorization (NMF) to find similar users for alleviating tag sparseness. The second approach is based on Latent Dirichlet Allocation (LDA) topic model, which can further capture the latent semantic relationship between tags. A large-scale real-world data set is collected from a tag based Chinese commercial Q&A web site. Experimental results show that the proposed method outperforms several baseline methods with a significant margin.

Three‐dimensional gravity modelling and focusing inversion using rectangular meshes

ABSTRACTRectangular grid cells are commonly used for the geophysical modeling of gravity anomalies, owing to their flexibility in constructing complex models. The straightforward handling of cubic cells in gravity inversion algorithms allows for a flexible imposition of model regularization constraints, which are generally essential in the inversion of static potential field data. The first part of this paper provides a review of commonly used expressions for calculating the gravity of a right polygonal prism, both for gravity and gradiometry, where the formulas of Plouff and Forsberg are adapted. The formulas can be cast into general forms practical for implementation. In the second part, a weighting scheme for resolution enhancement at depth is presented. Modelling the earth using highly digitized meshes, depth weighting schemes are typically applied to the model objective functional, subject to minimizing the data misfit. The scheme proposed here involves a non‐linear conjugate gradient inversion scheme with a weighting function applied to the non‐linear conjugate gradient scheme's gradient vector of the objective functional. The low depth resolution due to the quick decay of the gravity kernel functions is counteracted by suppressing the search directions in the parameter space that would lead to near‐surface concentrations of gravity anomalies. Further, a density parameter transformation function enabling the imposition of lower and upper bounding constraints is employed. Using synthetic data from models of varying complexity and a field data set, it is demonstrated that, given an adequate depth weighting function, the gravity inversion in the transform space can recover geologically meaningful models requiring a minimum of prior information and user interaction.

An Analysis of Google Logs Retention Policies

To preserve search log data utility, Google groups search queries in log bundles by deleting the last octet of logged IP address. Because these bundles still contain identifying information, part of these search logs can be de-anonymized [Jones et al., 2008]. Without an external audit of these search logs, it is currently impossible to evaluate their robustness against de-anonymizing attacks. In this paper, we leverage log retention policy ambiguities to show that quasi-identifiers could be stored in sanitized search query logs and could help to de-anonymize user searches. This paper refers to Google Search and Google Suggest log retention policies and shows that even with the highest degree of anonymization that Google offers, one could separate user queries with a high granularity. Because Google Suggest is queried every time a user types a character in the Google Chrome navigation box, the privacy of Chrome users could be compromised with respect to their browsing histories. Such ambiguities within log retention policies are critical and should be addressed, as anonymized logs could be shared with third parties without prior user consent.

Patenting in the shadow of independent discoveries by rivals

This paper studies the decision of whether to apply for a patent in a dynamic model in which firms innovate stochastically and independently. In the model, a firm can choose between patenting and maintaining secrecy to protect a successful innovation. I consider a legal environment characterized by imperfect patent protection and no prior user rights. Thus, patenting grants probabilistic protection, and secrecy is effectively maintained until rivals innovate. I show that (1) firms that innovate early are more inclined to choose secrecy, whereas firms that innovate late have a stronger tendency to patent; (2) the incentives to patent increase with the innovation arrival rate; and (3) an increase in the number of firms may cause patenting to occur earlier or later, depending on the strength of patent protection. The socially optimal level of patent protection, which balances the trade-off between the provision of patenting incentives and the avoidance of deadweight loss caused by a monopoly, is lower with a higher innovation arrival rate or a larger number of firms.

APIMED MEDICAL HONEY LTD v BRIGHTWAKE LTD

H1 Patent—Infringement—Counterclaim for revocation—Validity—Novelty—Inventive step—Common general knowledge—Unconventional knowledge—Claim construction—‘Gelling agent’—Whether used as scientific term of art—Prior user—Prior art—Mindset of skilled addressee

Nonpatentability of Business Methods: Legal and Economic Analysis

In this brief filed in Bilski vs. Kappos, pending before the U.S. Supreme Court, we argue that the useful Arts limitation of the the Intellectual Property Clause of the U.S.Constitution restricts the scope of Congress's patent power to technological advances. Beyond this constitutional limitation, Congress has not extended patent protection to business methods. The subject matter provision of the 1952 Patent Act merely codified existing subject matter categories and limitations, including the exclusion of business methods. The First Inventor Defense Act of 1999 did not alter this limitation on patentable subject matter. It did not amend the subject matter provision. It merely created a prior user defense. To read § 273 to override more than two centuries of jurisprudence as well as § 101 without an express statement to that effect would be unwarranted and unwise.We also address warnings that upholding the business method exclusion would hamper innovation. Economic research indicates that restoring the business method exclusion could well promote progress, innovation, and competition. Although we doubt that these considerations bear significantly if at all on the interpretive questions before the Court, they should certainly not be weighed on the side of extending patent protection to business methods.The courts and the Patent Office successfully navigated the line between technological and non-technological fields for over two centuries. Patent systems throughout the world continue to do so. Reestablishing technological advance as the touchstone for patent protection in the United States will help to restore confidence in, the efficacy of, and the logic of this vital institution.

The Authority of States to Use Names in International Law and the Macedonian Affair: Unilateral Entitlements, Historic Title, and Trademark Analogies

AbstractThe international legal entitlement by which a state constitutionally designates its name, or a province therein, involves a unilateral act. Where, however, another state wishes to choose the same appellation, as is the case with the former Yugoslav Republic of Macedonia (FYROM), the matter can only be resolved by reference to the first user and the maxim prior in tempore potior in jure. The first user must provide evidence of continuous use and of protest in those cases where the same appellation was appropriated by a third state. Under such circumstances the entitlement becomes exclusive, rather than concurrent, because the prior user may be said to possess a sound historic title, such that has been recognized by international judicial bodies to determine acquisition of territory, effective administration, historic bays, and so on. The exclusivity of the entitlement is further reinforced by analogy with general principles derived from the law of trademarks. At a practical level, the application of the international law of geographical indications clearly demonstrates that the designation ‘Macedonia’ cannot be used for a significant number of products originating in FYROM, since the Greek province of Macedonia has for a long time branded and registered such products. This will create insurmountable problems for producers in FYROM when they try to brand their goods under the country's constitutional name. A change of name, particularly through the compromisory use of a compound, would alleviate legal, political, and financial concerns.

Simulated evaluation of faceted browsing based on feature selection

In this paper we explore the limitations of facet based browsing which uses sub-needs of an information need for querying and organising the search process in video retrieval. The underlying assumption of this approach is that the search effectiveness will be enhanced if such an approach is employed for interactive video retrieval using textual and visual features. We explore the performance bounds of a faceted system by carrying out a simulated user evaluation on TRECVid data sets, and also on the logs of a prior user experiment with the system. We first present a methodology to reduce the dimensionality of features by selecting the most important ones. Then, we discuss the simulated evaluation strategies employed in our evaluation and the effect on the use of both textual and visual features. Facets created by users are simulated by clustering video shots using textual and visual features. The experimental results of our study demonstrate that the faceted browser can potentially improve the search effectiveness.

Integrating Household-Level Mode Choice and Modal Expenditure Decisions in a Developing Country

This paper investigates two mode-related dimensions at the household level, namely, mode choice and modal use intensity (as reflected by modal expenditures). These dimensions are analyzed jointly in the context of Chennai city in India, by using a large disaggregate database consisting of more than 2,000 households. Specifically, the objectives of this study are to analyze mode choice decisions at the household level, to integrate mode choice and mode usage using a suitable model, and to analyze the effect of contextual factors relevant to developing countries on the mode choice propensity and mode use intensity. At the household level, the mode choice problem is a multiple discrete choice problem (multiple alternatives may be selected) in contrast to the singly discrete nature of the individual mode choice problem. Therefore, a multiple discrete–continuous extreme value model is formulated to integrate choice and usage, based on a coherent utility maximization framework. To the authors’ knowledge, this study is the first to model mode choice as a multiple discrete choice problem. The results reveal that several unique and context-specific features in developing countries affect household-level mode choice significantly. Further, the mode use intensity of alternative modes is influenced by prior mode choice decisions, inertia, and user's perception of safety and congestion. The results have important planning and policy implications for transit improvement and congestion mitigation strategies.

Computer aided analysis and design of power transformers

In this paper, an integrated, three-dimensional, finite element package for the analysis and design of power transformers is developed, requiring no prior user experience in numerical methods and magnetic field simulation. The package consists of an automated pre-processor, magnetostatic solver and post-processor. High accuracy, low computational cost, minimization of user interaction and functional interface are the main advantages of the software, rendering it a powerful computational tool for characteristics prediction of single and dual voltage transformers, suitable for an automated design environment. For the development of the package, a particular scalar potential formulation was adopted. This method, in conjunction with the detailed representation of the real transformer geometry enables the achievement of high accuracy with the use of meshes of low density. The computational efficiency is also enhanced by the use of Morse technique for the storage of finite element matrices and Preconditioned Conjugate Gradient method for the solution of the finite element equations. The software has been incorporated in the design process of a transformer manufacturing industry for the evaluation of the leakage field and short-circuit impedance. The comparison of its results with measured values indicates the improvement of accuracy in comparison to the existing methodology, resulting in reduction of the design margin. Moreover, its employment has contributed to the decrease of the transformer industrial cycle and production cost.

Support vector machines regression for retrieval of leaf area index from multiangle imaging spectroradiometer

The retrieval of biophysical variables using canopy reflectance models is hindered by the fact that the inverse problem is ill posed. This is due to the measurement, model errors and the inadequacy between the model and reality, which produces similar reflectances for the different combination of the input parameters into the radiative transfer model. This leads to unstable and often inaccurate inversion results. The ill-posed nature of the inverse problem requires some regularization. Regularization means that one tries to consider only those solutions that are in the proximity of the true value. In order to regularize the model inversion, we propose kernel-based regularization by support vector machines regression (SVR) method. The formulation of the SVR contains meta-parameters C (regularization) and ε-insensitive loss. The SVR generalization performance (estimation accuracy) depends on these two parameters and the kernel parameters. Often the meta-parameters are selected using prior knowledge and/or user expertise. In this paper we adopt methods for the estimation of the meta-parameters from the input data itself instead of relying on any prior information. This paper is focused on the retrieval of leaf area index (LAI) from multiangle imaging spectroradiometer (MISR) data. The proposed methodology was implemented by inverting a 1D canopy reflectance model (PROSAIL) using SVR over MISR data. The results were validated against the LAI retrievals at the Alpilles EOS validation core site. An RMSE of 0.64 was obtained using both near-infrared (NIR) in conjunction with the red band and an RMSE of 0.50 using only the NIR band.

A Robust Approach for Structure from Planar Motion by Stereo Image Sequences

This paper proposes a robust method for recovery of motion and structure from two image sequences taken by stereo cameras undergoing a planar motion. The feature correspondences between images are extracted and refined automatically by the relation of the stereo cameras and the property of the motion. To improve the robustness, an auto-scale random sample consensus (RANSAC) algorithm is adopted in the motion and structure estimation. Unlike other work recovering epipolar geometry, here we use a random sampling algorithm to recover the 2D motion and to exclude the outliers which lie both on and out of the epipolar lines. Further more, the idea of RANSAC is used in structure estimation to exclude the outliers from the image sequence. The contribution of this work is the development of an approach to make structure and motion estimation more robust and efficient so as to be applicable to real applications. With the adoption of the auto-scale technique, the algorithm completely automates the estimation process without any prior information or user’s specification of parameters like thresholds. Indoor and outdoor experiments have been done to verify the performance of the algorithm. The results demonstrated that the proposed algorithm is robust and efficient for applications in planar motions.

Fighting the 1000 snakes [commercial-off-the-shelf in military environment

This paper describes the many significant advantages of using commercial-off-the-shelf (COTS) equipment in the military environment. Aside from reducing the design and development costs by capitalizing on the investment in technology made by the commercial industry, using COTS allows simpler and faster upgrading to insert additional operating capability, rapid procurement from the world market, and provides the potential to reduce support costs and the opportunity for common support across a range of capabilities. Moreover, training requirements can often be reduced thanks to prior user familiarity with many COTS products. However, there are a number of critical factors that must be taken into account in selecting the appropriate COTS products. In particular, environmental idiosyncrasies must be accounted for to ensure that the COTS design is fully compliant and suitable for military use, and will deliver the design capability when subjected to the operational military environment.

Patent System Reform: Economic Analysis and Critique

Considerable recent research suggests that the U.S. patent system is out of balance: the PTO's typically brief review process is allowing too many patents to be issued that would likely be found invalid with more thorough review. When patents are issued for inventions that are not truly novel, or are obvious, consumers are harmed, competition is restricted, and innovation is hindered-all contrary to the underlying purposes of the patent system. Critics of the current system claim that patents are indeed having significant, adverse effects on consumers, competition, and innovation. The Federal Trade Commission and the National Academies of Science recently issued extensive reports suggesting that major reforms to the U.S. patent system are needed to reduce these adverse effects. This Article reviews some of the evidence on the prevalence of such questionable patents, diagnoses their commercial impact, and then critiques a number of the FTC and NAS patent reform proposals. A strong economic case can be made for proposals to strengthen the PTO to improve the speed and accuracy of the patent examination process; to publish all patent applications after eighteen months; to establish a new administrative procedure to allow post-grant review of patents; to strengthen prior user rights; and to restrict the ability of patent owners to seek treble damages for willful infringement.

Translating user control availability into perception: the moderating role of prior experience

On a basic level, perception of user control over media content should be partially a function of control option availability. At the same time, prior user experience with control options should interact with control availability to produce joint effects on control perception. To assess these ideas, we present experimental data from 101 University students in the United States. Participants engaged a documentary in one of three ways: by simply watching the documentary, by watching the documentary with the option of using typical VCR-type controls (such as fast-forward or reverse), or by watching and having available both VCR-type controls and scene sequencing control. Data support our hypotheses. While there was a generally positive relationship between exposure to user control options and user control perception across all participants, those participants with relatively less prior experience with Internet-based applications demonstrated a somewhat different relationship between control availability and control perception.

FIT-recommend ing TV programs to family members

The proliferation of cable and satellite TV channels exposes the viewer to a huge variety of contents requiring the investment of substantial efforts in search of interesting programs. Recommendation systems may alleviate the problem by proposing the preferred programs according to prior user choices. However, in most homes, watching TV is a “family” event requiring the recommendation system to represent the individual preferences of the family members, identifying them for recommending the preferred programs of all the current viewers. This work deals with the representation and adaptation of family member preferences. We introduce FIT, a Family Interactive TV system that aims to filter TV programs according to the different viewer's preferences. We assume that the choice of a viewer may change in the presence of other family members. For creating initial family members preferences’ profiles, FIT uses a predefined stereotype user representation along with the user preferred watching times. Implicit relevance feedback is assessed by monitoring the actual viewers watching choices. FIT checks its prediction, updating the member/s preferences and their correlated vector accordingly. In case of error detection, FIT will verify the mistake with the user. We evaluated FIT predictions by comparing it with two other algorithms (one that request user identification, and another that chooses randomly the program genre). Simulation results indicate that FITs performance resembles the system that asks for user identification (without requiring that), and considerably outperforms the random system.

Cima: An interactive concept learning system for end-user applications

Personalizable software agents will learn new tasks from their users. In many cases the most appropriate way for users to teach is to demonstrate examples. Learning complex concepts from examples alone is hard, but agents can exploit other forms of instruction that users might give, ranging from yes/no responses to ambiguous, incomplete hints. Agents can also exploit background knowledge customized for applications such as drawing, word processing, and form filling. The Cima system learns generalized rules for classifying, generating, and modifying data, given examples, hints, and background knowledge. It copes with the ambiguity of user instructions by combining evidence from these sources. A dynamic bias manager generates candidate features (attribute values, functions, or relations) from which the learning algorithm selects relevant ones and forms appropriate rules. When tested on dialogs observed in a prior user study on a simulated interface agent, the system achieved 95% of the learning efficiency observed in that study.

Quantification of intensity variations in functional MR images using rotated principal components

In functional MRI (fMRI), the changes in cerebral haemodynamics related to stimulated neural brain activity are measured using standard clinical MR equipment. Small intensity variations in fMRI data have to be detected and distinguished from non-neural effects by careful image analysis. Based on multivariate statistics we describe an algorithm involving oblique rotation of the most significant principal components for an estimation of the temporal and spatial distribution of the stimulated neural activity over the whole image matrix. This algorithm takes advantage of strong local signal variations. A mathematical phantom was designed to generate simulated data for the evaluation of the method. In simulation experiments, the potential of the method to quantify small intensity changes, especially when processing data sets containing multiple sources of signal variations, was demonstrated. In vivo fMRI data collected in both visual and motor stimulation experiments were analysed, showing a proper location of the activated cortical regions within well known neural centres and an accurate extraction of the activation time profile. The suggested method yields accurate absolute quantification of in vivo brain activity without the need of extensive prior knowledge and user interaction.

User Participation, Management Support and System Types

This paper explores user participation in the systems development process and examines this variable in relation to the type of system under development. Prior user participation research has not shown conclusive support for its impact on system success. Ives and Olson 1984 have suggested that much of the prior research on user involvement/participation has not been strongly grounded in theory. Using Simon's 1965 model of decision-making together with Zmud's 1983 typology of systems, it is hypothesized that user participation's impact on perceived usefulness should be greater for the more unstructured non-programmed decision-based systems than for transaction processing systems. This paper thus tests for moderating influences by system type. This study provides evidence that system type or problem type is an important moderating variable between user participation and perceived usefulness.