Senate Youth Alumni Association: USSYAARead Our Newsletter Online. Looking for a copy of our newsletter? We are pleased to announce that the 2. Annual Letter is available in the alumni area of this website (login required). Make a Donation to the USSYAANow that our tax exempt status has been confirmed and we have initiated our scholarship activities this would be a great time for alumni (and others) to actively consider making donations to either the general fund or to the Rosalie Wynn and George Randolph Hearst, Sr. Please note the scholarship fund is a project of USSYAA and is neither affiliated with nor endorsed by The William Randolph Hearst Foundations. Tax- deductible contributions may be made by credit card or e- check with our secure online donation form or by check sent to USSYAA, P. I was contacted today that I was one of the ten semifinalist for the two candidates of my state to be sent to the United States Senate Youth Program. United States Senate Youth Program. UNITED STATES SENATE YOUTH PROGRAM. Finalists may be asked to participate in a Skype interview during the selection process. The United States Senate Youth Program. Agency Directory; Call 311; Contact the Mayor; Contact Agency Directors; FOIA Requests; Report Website Problems. O. Box 1. 79. 8, Washington, DC 2. Nine percent of the purchase price for each item counts as a tax- deductible contribution to USSYAA. 2016) United States Senate Youth Program. Presidential Scholars Program; U.S. Senate Youth Program Currently. The United States Senate Youth Program sends two delegates from every state to spend a.
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About PdfEdit(library and free pdf editor for unix) PDFedit is a free open source pdf editor and a library for manipulating PDF documents, released under terms of GNU. The Portable Document Format (PDF). Acrobat XI: How to edit PDF files. How to edit PDF files using Acrobat XI; How to edit a scanned PDF file using Acrobat XI; How to edit images in PDF files using. Proprietary software to view and edit PDF documents; PDF Signer. You can save a Word file to PDF format in Word 2. Word 2. 01. 3 is the first version that allows you to open a PDF, edit it. PDF. About PDFs and. If you don't think you're familiar with the PDF format. Recycle existing documents with Adobe Acrobat DC. You can also edit right in your PDF. Recycle existing documents with. Need to work with data but have only a. Collecting and managing PDF form data. You can save the information in a completed PDF form as a data file in another file format. Take advantage of new features in Adobe Acrobat DC that let you work anywhere so you can create PDFs, edit. Edit Image Data http:// ToL Image ID# 4651 Contributed by on. Allow another ToL contributor to edit this form. Figure A). The pdf extension stands. Portable Document Format, which is a file format that presents documents. In other words, you. It's a great format for sharing documents with lots of people using different. Figure A The PDF icon. Editing a PDF file was, until now, an entirely different. By design, PDF documents are supposed. They aren't designed for editing on the fly. Although. Adobe, who had proprietary ownership of the format for years, offered free. PDF file required specialized software and knowledge. A few. years ago, Adobe moved the PDF format to open standard and, in the process. You'll. do so as you would any other file. To open a PDF file using Word 2. Click the File menu and choose Open from the. Or, click the Open icon on the Quick Access Toolbar (QAT) if you've. QAT toolbar drop- down and check Open to add it). At this point, you can use Recent Documents or. PDF you want to open. Word will. display PDF files in its lists, so you won't have to specify the PDF format to. Figure B). Figure B Select the file and click Open. When Word displays the informational dialog (Figure C), click OK. Figure C If Word displays the Protected View bar at the. Enable Editing. Figure D shows the results of opening a previously blank PDF file and adding a bit of text. If you open this file using Adobe Reader. Adobe's free viewer), you can't edit the file. To edit the file, you'd need Adobe Acrobat, which is a pricey piece of software. Figure D Using Word 2. Word file (sort of). As I mentioned earlier, not every format and. I offer more specific advice below, but your own. Save a PDF file. After editing the file, you can save the file as a Word. PDF file. Your choice isn't right or wrong; it will depend on. I recommend that you save the edited. Word document, even if you intend to distribute the file as a PDF. When you save the file, Word will default to its format (. PDF format: Click the File tab and choose Save As. Choose a location for the new file. When Word displays the Save As dialog, you'll. From the Save As Type drop- down, choose PDF (Figure E)Figure E Word will retain the document's author, so you. Click Save. If you plan to publish online or print, use the Standard. Choose Minimum Size when. Doing so will reduce. Advice, although not. Word 2. 01. 3 converts editable text. That means some elements. PDF won't appear as you expected, nor will you be able to edit them. Some. interactive PDF elements won't display at all. Not all text will actually be. Sometimes Word interprets elements as graphics. Even though the graphic appears. Word treats it as a graphic. You won't be able to edit these elements. 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Our model is able to efficiently infer interesting itemsets directly from the transaction database using structural EM, in which the E- step employs the greedy approximation to weighted set cover. Our approach is theoretically simple, straightforward to implement, trivially parallelizable and retrieves itemsets whose quality is comparable to, if not better than, existing state of the art algorithms as we demonstrate on several real- world datasets. In this paper, we propose a new approach for processing massive and complex metabolomic data generated by such platforms with appropriate methods for discovering meaningful biological patterns. The analyzed datasets are constituted of a limited set of individuals and a large set of attributes or features where predictive makers of clinical outcomes should be mined. The experiments are based on a hybrid knowledge discovery process combining numerical methods such as SVM, Random Forests (RF) and ANOVA, with a symbolic method, such as Formal Concept Analysis (FCA). The outputs of these experiments highlight the best potential predictive biomarkers of metabolic diseases and the fact that RF and ANOVA are the most suited methods for feature selection and discovery. The visualization of predictive biomarkers is based on correlation graphs and heatmaps while FCA is used for visualizing the best feature selection methods within a concept lattice easily interpretable by an expert. However, COSVM training involves solving a constrained convex optimization problem, which requires large memory and enormous amount of training time, especially for large scale datasets. Moreover, it has difficulties in classifying sequentially obtained data. For these reasons, this paper introduces an incremental COSVM method by controlling the possible changes of support vectors after the addition of new data points. The control procedure is based on the relationship between the Karush- Kuhn- Tuker conditions of COSVM and the distribution of the training set. Comparative experiments have been carried out to show the effectiveness of our proposed method, both in terms of execution time and classification accuracy. Incremental COSVM results in better classification performance when compared to canonical COSVM and contemporary incremental one- class classifiers.
Want to learn how Compuware drives mainframe value up while bringing cost and risk down? RonyaSoft Poster Designer Software to design and print posters, banners, certificates and signs. Unfortunately, most methods either provide only a limited form of communication with the human expert and/or are overly reliant on the human expert to specify their knowledge upfront. Thus, the expert is unable to understand what the system could learn without the involvement of him/her. Allowing the learning algorithm to query the human expert in the most useful areas of the feature space takes full advantage of the data as well as the expert. We introduce active advice- seeking for relational domains. Relational logic allows for compact, but expressive interaction between the human expert and the learning algorithm. We demonstrate our algorithm empirically on several standard relational datasets. However, the training of RNNs is a computationally difficult task owing to the well- known . Algorithms proposed for training RNNs either exploit no (or limited) curvature information and have cheap per- iteration complexity, or attempt to gain significant curvature information at the cost of increased per- iteration cost. The former set includes diagonally- scaled first- order methods such as ADAGRAD and ADAM, while the latter consists of second- order algorithms like Hessian- Free Newton and K- FAC. In this paper, we present ada. QN, a stochastic quasi- Newton algorithm for training RNNs. Our approach retains a low per- iteration cost while allowing for non- diagonal scaling through a stochastic L- BFGS updating scheme. The method uses a novel L- BFGS scaling initialization scheme and is judicious in storing and retaining L- BFGS curvature pairs. We present numerical experiments on two language modeling tasks and show that ada. QN is competitive with popular RNN training algorithms. In this paper, we focus on ordinal labels, whose underlying order is important. However, the labels can be noisy as there may be amateur workers, spammers and/or even malicious workers. Moreover, some workers/items may have very few labels, making the estimation of their behavior difficult. To alleviate these problems, we propose a novel Bayesian model that clusters workers and items together using the nonparametric Dirichlet process priors. This allows workers/items in the same cluster to borrow strength from each other. Instead of directly computing the posterior of this complex model, which is infeasible, we propose a new variational inference procedure. Experimental results on a number of real- world data sets show that the proposed algorithm are more accurate than the state- of- the- art. The current best CP approach for SPM uses a global constraint (module) that computes the projected database and enforces the minimum frequency; it does this with a filtering algorithm similar to the Prefix. Span method. However, the resulting system is not as scalable as some of the most advanced mining systems like Zaki. We show how, using techniques from both data mining and constraint programming, one can use a generic constraint solver and yet outperform existing specialized systems. This is mainly due to two improvements in the module that computes the projected frequencies: first, computing the projected database can be sped up by pre- computing the positions at which an item can become unsupported by a sequence, thereby avoiding to scan the full sequence each time; and second by taking inspiration from the trailing used in CP solvers to devise a backtracking- aware data structure that allows fast incremental storing and restoring of the projected database. Detailed experiments show how this approach outperforms existing CP as well as specialized systems for SPM, and that the gain in efficiency translates directly into increased efficiency for constraint- based settings such as mining with regular expressions too. By construction, the greedification of such a pseudo- value induces the same policy as the value function itself. For instance, applying a random policy on a good initial state (e. Such a demonstration, that is, a sequence of states with decreasing values, is used along a standard learning- to- rank approach to define a pseudo- value function. If the model of the environment is known, this pseudo- value directly induces a policy by greedification. Tech., CAS). Bin Wu. Abstract. Due to the personalized needs for specific aspect evaluation on product quality, these years have witnessed a boom of researches on aspect rating prediction, whose goal is to extract ad hoc aspects from online reviews and predict rating or opinion on each aspect. Most of the existing works on aspect rating prediction have a basic assumption that the overall rating is the average score of aspect ratings or the overall rating is very close to aspect ratings. However, after analyzing real datasets, we have an insightful observation: there is an obvious rating bias between overall rating and aspect ratings. Motivated by this observation, we study the problem of aspect mining with rating bias, and design a novel RAting- center model with BIas (RABI). Different from the widely used review- center models, RABI adopts the overall rating as the center of the probabilistic model, which generates reviews and topics. In addition, a novel aspect rating variable in RABI is designed to effectively integrate the rating bias priori information. Experiments on two real datasets (Dianping and Trip. Advisor) validate that RABI significantly improves the prediction accuracy over existing state- of- the- art methods. An essential property of graphs is that they are often dynamic. Many applications must update the computation result periodically on the new graph so as to keep it up- to- date. Incremental computation is a promising technique for this purpose. Traditionally, incremental computation is typically performed synchronously, since it is easy to implement. In this paper, we illustrate that incremental computation can be performed asynchronously as well. Asynchronous incremental computation can bypass synchronization barriers and always utilize the most recent values, and thus it is more efficient than its synchronous counterpart. Furthermore, we develop a distributed framework, Graph. In, to facilitate implementations of incremental computation on massive evolving graphs. We evaluate our asynchronous incremental computation approach via extensive experiments on a local cluster as well as the Amazon EC2 cloud. The evaluation results show that it can accelerate the convergence speed by as much as 1. Specifically, the goal of this paper is to perform. L1 regularized risk minimization. This will be accomplished by concentrating on the. We verified our method through. The key problem in this task is how to effectively and efficiently learn from the conjunction of query attributes. In this paper, we propose Attribute Conjunction Recurrent Neural Network (AC- RNN) to tackle this problem. Attributes involved in a query are mapped into the hidden units and combined in a recurrent way to generate the representation of the attribute conjunction, which is then used to compute a multi- attribute classifier as the output. To mitigate the data imbalance problem of multi- attribute queries, we propose a data weighting procedure in attribute conjunction learning with small positive samples. We also discuss on the influence of attribute order in a query and present two methods based on attention mechanism and ensemble learning respectively to further boost the performance. Experimental results on a. WEIHRAUCH HW40PCA: La recensione completa di questa pistola ad aria precompressa PCA in calibro.177, nata per il divertimento ma diventata in breve tempo un must tra.Adobe - Acrobat Developer Center. Welcome to the Acrobat Developer Center. Learn how to deliver the richest, most engaging PDF communications anytime, anywhere. The Acrobat DC SDK is a set of tools that help you develop software that interacts with Acrobat technology. The SDK contains header files, type libraries, simple utilities, sample code, and documentation. Read more on Adobe Acrobat DC SDK capabilities. 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You should discuss the suitability of these exercises with your physiotherapist prior to beginning them. Generally, they should only be performed provided they do not cause or increase pain. Begin with the basic hip flexor strengthening exercises. Once these are too easy, they can be replaced with the intermediate hip flexor strengthening exercises. As your strength improves, the advanced exercises can be added to the intermediate program. Figure 1 . As your strength improves, the exercises can be progressed by gradually increasing the repetitions or frequency of the exercises provided they do not cause or increase pain. Hip Knee Flexion. Slowly bend and straighten your knee as far as possible pain free, sliding your heel up and down the bed or floor (figure 2). Repeat 1. 0 times provided there is no increase in symptoms. Figure 2 . Then slowly return to the starting position. Repeat 1. 0 times provided there is no increase in symptoms. Figure 3 . As your strength improves, the exercises can be progressed by gradually increasing the repetitions or frequency of the exercises provided they do not cause or increase pain. Straight Leg Raise. Begin this exercise lying on your back with one leg straight and one leg bent (figure 4). Slowly lift your straight leg to approximately 4. Hold for 2 seconds and then slowly return to the starting position. Repeat 1. 0 times provided the exercise is pain free. Hip Flexor Strengthening Program For HamstringHip openers like Pigeon pose can help increase the external rotation of hips, while others can lengthen the psoas muscle. Hip Flexor Strengthening. The video presentation and visuals in the exercise program give me confidence that I am doing the exercises correctly which for me. All in the Hips Strengthening this joint could cure your injuries. After putting these people on a targeted strength program. STANDING HIP FLEXOR 1. The hip flexor stretch has become a very popular stretch, however, seems to be commonly performed incorrectly or too aggressively. Figure 4 . For more details see Become a Member. Return to the top of Hip Flexor Strengthening Exercises. Prognosis of a hip flexor strain. With appropriate management, patients with a minor hip flexor strain can usually recover in one to three weeks. Helpful, trusted answers from doctors: Dr. Garcia-septien on hip flexor strengthening program: Tight hip flexors make walking difficult and running painful because. The hip flexors are a group of muscles that help you move, or flex, your leg and knee up towards your body. A hip flexor strain occurs when one or more of the hip. The journey to Mother Moon by Kid Cudi on Apple Music. Tunes Review. In the years since Kid Cudi’s breakthrough 2. Just as you’re getting hypnotized by his late- night rhymes, Cudi switches it up—singing in a laidback drawl or assuming the role of guitar- playing frontman. He's tapped off- the- wall collaborators (like soft rock crooner Michael Bolton), reinterpreted Nirvana's cover of blues legend Lead Belly, and pushed his production aesthetic into progressively more experimental terrain. For Cudi's fourth solo album, Satellite Flight: The Journey to Mother Moon, the innovative emcee brings in throwback- soul heartbreaker Raphael Saadiq and rekindles the collaborative magic with WZRD bandmate and producer Dot da Genius.
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Ballet/Barre exercise videos – Collage Video. Ballet exercise videos bring the grace and elegance of ballet workouts to your home. You'll get the lean, strong body of a ballet dancer with these. A callanetic gyakorlatok k Callan Pinckney (born as Barbara Biffinger Pfeiffer Pinckney September 26, 1939 – March 1, 2012) was an American fitness professional. She achieved unprecedented success with her Callanetics exercises. Her 9 books all became. Callanetics to jedne z najefektywniejszych . |
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