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  • Small biz vpn solution

    - by Crash893
    I've been looking for a while but I'd like to to implement a vpn solution for anywhere from 1-5 employees at a time (possibly 10 in a year or so) I've looked at astaro gateway but im not sure if thats the right tool for the job. I know "best" is a subjective term so i would like to break it into to different suggestions 1) what is the cheapest solution given the criteria above 2) what solution will result in the least amount of headaches from the point of view of maintenance and learning curve.

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  • Create a linear trend line in Excel graphs with logarithmic scale

    - by Redsoft7
    I I have an Excel scatter chart with x and y values. I set the logarithmic scale in x-axis and y-axis. When I add a linear trend line to the graph, the line is not linear but appears like a curve. How can I make a linear trend line on a logarithmic-scaled chart? Sample data: x: 18449 22829 25395 36869 101419 125498 208144 2001508 14359478 17301785 y: 269,09 273,89 239,50 239,50 175,13 176,73 151,94 135,15 131,55 121,55

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  • Linux with winbind, disable local users while AD is available?

    - by Salkin
    Routers and switches with RADIUS authentication can be configured such that login is disabled for locally configured users as long as the RADIUS server is available. If the RADIUS server becomes unavailable, they fall back to allowing login as a locally configured user. Is it possible to achieve the same effect with Linux machines using winbind to authenticate Active Directory users? I have a feeling it could be done with the right PAM configuration, but I'm not very far along on the PAM learning curve...

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  • nginx support for .htaccess / rewrite rules? Differences from Apache?

    - by anonymous coward
    I've been working with Apache http servers for quite some time, and finally making the move to static-content servers alongside the others dynamic-content machines. I was wondering, does nginx support ".htaccess" files, and things like mod_rewrite? As I'm very used to the syntax, I was wondering what the (syntax) differences were, and what the learning curve is like moving from Apache configs to nginx.

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  • A Taxonomy of Numerical Methods v1

    - by JoshReuben
    Numerical Analysis – When, What, (but not how) Once you understand the Math & know C++, Numerical Methods are basically blocks of iterative & conditional math code. I found the real trick was seeing the forest for the trees – knowing which method to use for which situation. Its pretty easy to get lost in the details – so I’ve tried to organize these methods in a way that I can quickly look this up. I’ve included links to detailed explanations and to C++ code examples. I’ve tried to classify Numerical methods in the following broad categories: Solving Systems of Linear Equations Solving Non-Linear Equations Iteratively Interpolation Curve Fitting Optimization Numerical Differentiation & Integration Solving ODEs Boundary Problems Solving EigenValue problems Enjoy – I did ! Solving Systems of Linear Equations Overview Solve sets of algebraic equations with x unknowns The set is commonly in matrix form Gauss-Jordan Elimination http://en.wikipedia.org/wiki/Gauss%E2%80%93Jordan_elimination C++: http://www.codekeep.net/snippets/623f1923-e03c-4636-8c92-c9dc7aa0d3c0.aspx Produces solution of the equations & the coefficient matrix Efficient, stable 2 steps: · Forward Elimination – matrix decomposition: reduce set to triangular form (0s below the diagonal) or row echelon form. If degenerate, then there is no solution · Backward Elimination –write the original matrix as the product of ints inverse matrix & its reduced row-echelon matrix à reduce set to row canonical form & use back-substitution to find the solution to the set Elementary ops for matrix decomposition: · Row multiplication · Row switching · Add multiples of rows to other rows Use pivoting to ensure rows are ordered for achieving triangular form LU Decomposition http://en.wikipedia.org/wiki/LU_decomposition C++: http://ganeshtiwaridotcomdotnp.blogspot.co.il/2009/12/c-c-code-lu-decomposition-for-solving.html Represent the matrix as a product of lower & upper triangular matrices A modified version of GJ Elimination Advantage – can easily apply forward & backward elimination to solve triangular matrices Techniques: · Doolittle Method – sets the L matrix diagonal to unity · Crout Method - sets the U matrix diagonal to unity Note: both the L & U matrices share the same unity diagonal & can be stored compactly in the same matrix Gauss-Seidel Iteration http://en.wikipedia.org/wiki/Gauss%E2%80%93Seidel_method C++: http://www.nr.com/forum/showthread.php?t=722 Transform the linear set of equations into a single equation & then use numerical integration (as integration formulas have Sums, it is implemented iteratively). an optimization of Gauss-Jacobi: 1.5 times faster, requires 0.25 iterations to achieve the same tolerance Solving Non-Linear Equations Iteratively find roots of polynomials – there may be 0, 1 or n solutions for an n order polynomial use iterative techniques Iterative methods · used when there are no known analytical techniques · Requires set functions to be continuous & differentiable · Requires an initial seed value – choice is critical to convergence à conduct multiple runs with different starting points & then select best result · Systematic - iterate until diminishing returns, tolerance or max iteration conditions are met · bracketing techniques will always yield convergent solutions, non-bracketing methods may fail to converge Incremental method if a nonlinear function has opposite signs at 2 ends of a small interval x1 & x2, then there is likely to be a solution in their interval – solutions are detected by evaluating a function over interval steps, for a change in sign, adjusting the step size dynamically. Limitations – can miss closely spaced solutions in large intervals, cannot detect degenerate (coinciding) solutions, limited to functions that cross the x-axis, gives false positives for singularities Fixed point method http://en.wikipedia.org/wiki/Fixed-point_iteration C++: http://books.google.co.il/books?id=weYj75E_t6MC&pg=PA79&lpg=PA79&dq=fixed+point+method++c%2B%2B&source=bl&ots=LQ-5P_taoC&sig=lENUUIYBK53tZtTwNfHLy5PEWDk&hl=en&sa=X&ei=wezDUPW1J5DptQaMsIHQCw&redir_esc=y#v=onepage&q=fixed%20point%20method%20%20c%2B%2B&f=false Algebraically rearrange a solution to isolate a variable then apply incremental method Bisection method http://en.wikipedia.org/wiki/Bisection_method C++: http://numericalcomputing.wordpress.com/category/algorithms/ Bracketed - Select an initial interval, keep bisecting it ad midpoint into sub-intervals and then apply incremental method on smaller & smaller intervals – zoom in Adv: unaffected by function gradient à reliable Disadv: slow convergence False Position Method http://en.wikipedia.org/wiki/False_position_method C++: http://www.dreamincode.net/forums/topic/126100-bisection-and-false-position-methods/ Bracketed - Select an initial interval , & use the relative value of function at interval end points to select next sub-intervals (estimate how far between the end points the solution might be & subdivide based on this) Newton-Raphson method http://en.wikipedia.org/wiki/Newton's_method C++: http://www-users.cselabs.umn.edu/classes/Summer-2012/csci1113/index.php?page=./newt3 Also known as Newton's method Convenient, efficient Not bracketed – only a single initial guess is required to start iteration – requires an analytical expression for the first derivative of the function as input. Evaluates the function & its derivative at each step. Can be extended to the Newton MutiRoot method for solving multiple roots Can be easily applied to an of n-coupled set of non-linear equations – conduct a Taylor Series expansion of a function, dropping terms of order n, rewrite as a Jacobian matrix of PDs & convert to simultaneous linear equations !!! Secant Method http://en.wikipedia.org/wiki/Secant_method C++: http://forum.vcoderz.com/showthread.php?p=205230 Unlike N-R, can estimate first derivative from an initial interval (does not require root to be bracketed) instead of inputting it Since derivative is approximated, may converge slower. Is fast in practice as it does not have to evaluate the derivative at each step. Similar implementation to False Positive method Birge-Vieta Method http://mat.iitm.ac.in/home/sryedida/public_html/caimna/transcendental/polynomial%20methods/bv%20method.html C++: http://books.google.co.il/books?id=cL1boM2uyQwC&pg=SA3-PA51&lpg=SA3-PA51&dq=Birge-Vieta+Method+c%2B%2B&source=bl&ots=QZmnDTK3rC&sig=BPNcHHbpR_DKVoZXrLi4nVXD-gg&hl=en&sa=X&ei=R-_DUK2iNIjzsgbE5ID4Dg&redir_esc=y#v=onepage&q=Birge-Vieta%20Method%20c%2B%2B&f=false combines Horner's method of polynomial evaluation (transforming into lesser degree polynomials that are more computationally efficient to process) with Newton-Raphson to provide a computational speed-up Interpolation Overview Construct new data points for as close as possible fit within range of a discrete set of known points (that were obtained via sampling, experimentation) Use Taylor Series Expansion of a function f(x) around a specific value for x Linear Interpolation http://en.wikipedia.org/wiki/Linear_interpolation C++: http://www.hamaluik.com/?p=289 Straight line between 2 points à concatenate interpolants between each pair of data points Bilinear Interpolation http://en.wikipedia.org/wiki/Bilinear_interpolation C++: http://supercomputingblog.com/graphics/coding-bilinear-interpolation/2/ Extension of the linear function for interpolating functions of 2 variables – perform linear interpolation first in 1 direction, then in another. Used in image processing – e.g. texture mapping filter. Uses 4 vertices to interpolate a value within a unit cell. Lagrange Interpolation http://en.wikipedia.org/wiki/Lagrange_polynomial C++: http://www.codecogs.com/code/maths/approximation/interpolation/lagrange.php For polynomials Requires recomputation for all terms for each distinct x value – can only be applied for small number of nodes Numerically unstable Barycentric Interpolation http://epubs.siam.org/doi/pdf/10.1137/S0036144502417715 C++: http://www.gamedev.net/topic/621445-barycentric-coordinates-c-code-check/ Rearrange the terms in the equation of the Legrange interpolation by defining weight functions that are independent of the interpolated value of x Newton Divided Difference Interpolation http://en.wikipedia.org/wiki/Newton_polynomial C++: http://jee-appy.blogspot.co.il/2011/12/newton-divided-difference-interpolation.html Hermite Divided Differences: Interpolation polynomial approximation for a given set of data points in the NR form - divided differences are used to approximately calculate the various differences. For a given set of 3 data points , fit a quadratic interpolant through the data Bracketed functions allow Newton divided differences to be calculated recursively Difference table Cubic Spline Interpolation http://en.wikipedia.org/wiki/Spline_interpolation C++: https://www.marcusbannerman.co.uk/index.php/home/latestarticles/42-articles/96-cubic-spline-class.html Spline is a piecewise polynomial Provides smoothness – for interpolations with significantly varying data Use weighted coefficients to bend the function to be smooth & its 1st & 2nd derivatives are continuous through the edge points in the interval Curve Fitting A generalization of interpolating whereby given data points may contain noise à the curve does not necessarily pass through all the points Least Squares Fit http://en.wikipedia.org/wiki/Least_squares C++: http://www.ccas.ru/mmes/educat/lab04k/02/least-squares.c Residual – difference between observed value & expected value Model function is often chosen as a linear combination of the specified functions Determines: A) The model instance in which the sum of squared residuals has the least value B) param values for which model best fits data Straight Line Fit Linear correlation between independent variable and dependent variable Linear Regression http://en.wikipedia.org/wiki/Linear_regression C++: http://www.oocities.org/david_swaim/cpp/linregc.htm Special case of statistically exact extrapolation Leverage least squares Given a basis function, the sum of the residuals is determined and the corresponding gradient equation is expressed as a set of normal linear equations in matrix form that can be solved (e.g. using LU Decomposition) Can be weighted - Drop the assumption that all errors have the same significance –-> confidence of accuracy is different for each data point. Fit the function closer to points with higher weights Polynomial Fit - use a polynomial basis function Moving Average http://en.wikipedia.org/wiki/Moving_average C++: http://www.codeproject.com/Articles/17860/A-Simple-Moving-Average-Algorithm Used for smoothing (cancel fluctuations to highlight longer-term trends & cycles), time series data analysis, signal processing filters Replace each data point with average of neighbors. Can be simple (SMA), weighted (WMA), exponential (EMA). Lags behind latest data points – extra weight can be given to more recent data points. Weights can decrease arithmetically or exponentially according to distance from point. Parameters: smoothing factor, period, weight basis Optimization Overview Given function with multiple variables, find Min (or max by minimizing –f(x)) Iterative approach Efficient, but not necessarily reliable Conditions: noisy data, constraints, non-linear models Detection via sign of first derivative - Derivative of saddle points will be 0 Local minima Bisection method Similar method for finding a root for a non-linear equation Start with an interval that contains a minimum Golden Search method http://en.wikipedia.org/wiki/Golden_section_search C++: http://www.codecogs.com/code/maths/optimization/golden.php Bisect intervals according to golden ratio 0.618.. Achieves reduction by evaluating a single function instead of 2 Newton-Raphson Method Brent method http://en.wikipedia.org/wiki/Brent's_method C++: http://people.sc.fsu.edu/~jburkardt/cpp_src/brent/brent.cpp Based on quadratic or parabolic interpolation – if the function is smooth & parabolic near to the minimum, then a parabola fitted through any 3 points should approximate the minima – fails when the 3 points are collinear , in which case the denominator is 0 Simplex Method http://en.wikipedia.org/wiki/Simplex_algorithm C++: http://www.codeguru.com/cpp/article.php/c17505/Simplex-Optimization-Algorithm-and-Implemetation-in-C-Programming.htm Find the global minima of any multi-variable function Direct search – no derivatives required At each step it maintains a non-degenerative simplex – a convex hull of n+1 vertices. Obtains the minimum for a function with n variables by evaluating the function at n-1 points, iteratively replacing the point of worst result with the point of best result, shrinking the multidimensional simplex around the best point. Point replacement involves expanding & contracting the simplex near the worst value point to determine a better replacement point Oscillation can be avoided by choosing the 2nd worst result Restart if it gets stuck Parameters: contraction & expansion factors Simulated Annealing http://en.wikipedia.org/wiki/Simulated_annealing C++: http://code.google.com/p/cppsimulatedannealing/ Analogy to heating & cooling metal to strengthen its structure Stochastic method – apply random permutation search for global minima - Avoid entrapment in local minima via hill climbing Heating schedule - Annealing schedule params: temperature, iterations at each temp, temperature delta Cooling schedule – can be linear, step-wise or exponential Differential Evolution http://en.wikipedia.org/wiki/Differential_evolution C++: http://www.amichel.com/de/doc/html/ More advanced stochastic methods analogous to biological processes: Genetic algorithms, evolution strategies Parallel direct search method against multiple discrete or continuous variables Initial population of variable vectors chosen randomly – if weighted difference vector of 2 vectors yields a lower objective function value then it replaces the comparison vector Many params: #parents, #variables, step size, crossover constant etc Convergence is slow – many more function evaluations than simulated annealing Numerical Differentiation Overview 2 approaches to finite difference methods: · A) approximate function via polynomial interpolation then differentiate · B) Taylor series approximation – additionally provides error estimate Finite Difference methods http://en.wikipedia.org/wiki/Finite_difference_method C++: http://www.wpi.edu/Pubs/ETD/Available/etd-051807-164436/unrestricted/EAMPADU.pdf Find differences between high order derivative values - Approximate differential equations by finite differences at evenly spaced data points Based on forward & backward Taylor series expansion of f(x) about x plus or minus multiples of delta h. Forward / backward difference - the sums of the series contains even derivatives and the difference of the series contains odd derivatives – coupled equations that can be solved. Provide an approximation of the derivative within a O(h^2) accuracy There is also central difference & extended central difference which has a O(h^4) accuracy Richardson Extrapolation http://en.wikipedia.org/wiki/Richardson_extrapolation C++: http://mathscoding.blogspot.co.il/2012/02/introduction-richardson-extrapolation.html A sequence acceleration method applied to finite differences Fast convergence, high accuracy O(h^4) Derivatives via Interpolation Cannot apply Finite Difference method to discrete data points at uneven intervals – so need to approximate the derivative of f(x) using the derivative of the interpolant via 3 point Lagrange Interpolation Note: the higher the order of the derivative, the lower the approximation precision Numerical Integration Estimate finite & infinite integrals of functions More accurate procedure than numerical differentiation Use when it is not possible to obtain an integral of a function analytically or when the function is not given, only the data points are Newton Cotes Methods http://en.wikipedia.org/wiki/Newton%E2%80%93Cotes_formulas C++: http://www.siafoo.net/snippet/324 For equally spaced data points Computationally easy – based on local interpolation of n rectangular strip areas that is piecewise fitted to a polynomial to get the sum total area Evaluate the integrand at n+1 evenly spaced points – approximate definite integral by Sum Weights are derived from Lagrange Basis polynomials Leverage Trapezoidal Rule for default 2nd formulas, Simpson 1/3 Rule for substituting 3 point formulas, Simpson 3/8 Rule for 4 point formulas. For 4 point formulas use Bodes Rule. Higher orders obtain more accurate results Trapezoidal Rule uses simple area, Simpsons Rule replaces the integrand f(x) with a quadratic polynomial p(x) that uses the same values as f(x) for its end points, but adds a midpoint Romberg Integration http://en.wikipedia.org/wiki/Romberg's_method C++: http://code.google.com/p/romberg-integration/downloads/detail?name=romberg.cpp&can=2&q= Combines trapezoidal rule with Richardson Extrapolation Evaluates the integrand at equally spaced points The integrand must have continuous derivatives Each R(n,m) extrapolation uses a higher order integrand polynomial replacement rule (zeroth starts with trapezoidal) à a lower triangular matrix set of equation coefficients where the bottom right term has the most accurate approximation. The process continues until the difference between 2 successive diagonal terms becomes sufficiently small. Gaussian Quadrature http://en.wikipedia.org/wiki/Gaussian_quadrature C++: http://www.alglib.net/integration/gaussianquadratures.php Data points are chosen to yield best possible accuracy – requires fewer evaluations Ability to handle singularities, functions that are difficult to evaluate The integrand can include a weighting function determined by a set of orthogonal polynomials. Points & weights are selected so that the integrand yields the exact integral if f(x) is a polynomial of degree <= 2n+1 Techniques (basically different weighting functions): · Gauss-Legendre Integration w(x)=1 · Gauss-Laguerre Integration w(x)=e^-x · Gauss-Hermite Integration w(x)=e^-x^2 · Gauss-Chebyshev Integration w(x)= 1 / Sqrt(1-x^2) Solving ODEs Use when high order differential equations cannot be solved analytically Evaluated under boundary conditions RK for systems – a high order differential equation can always be transformed into a coupled first order system of equations Euler method http://en.wikipedia.org/wiki/Euler_method C++: http://rosettacode.org/wiki/Euler_method First order Runge–Kutta method. Simple recursive method – given an initial value, calculate derivative deltas. Unstable & not very accurate (O(h) error) – not used in practice A first-order method - the local error (truncation error per step) is proportional to the square of the step size, and the global error (error at a given time) is proportional to the step size In evolving solution between data points xn & xn+1, only evaluates derivatives at beginning of interval xn à asymmetric at boundaries Higher order Runge Kutta http://en.wikipedia.org/wiki/Runge%E2%80%93Kutta_methods C++: http://www.dreamincode.net/code/snippet1441.htm 2nd & 4th order RK - Introduces parameterized midpoints for more symmetric solutions à accuracy at higher computational cost Adaptive RK – RK-Fehlberg – estimate the truncation at each integration step & automatically adjust the step size to keep error within prescribed limits. At each step 2 approximations are compared – if in disagreement to a specific accuracy, the step size is reduced Boundary Value Problems Where solution of differential equations are located at 2 different values of the independent variable x à more difficult, because cannot just start at point of initial value – there may not be enough starting conditions available at the end points to produce a unique solution An n-order equation will require n boundary conditions – need to determine the missing n-1 conditions which cause the given conditions at the other boundary to be satisfied Shooting Method http://en.wikipedia.org/wiki/Shooting_method C++: http://ganeshtiwaridotcomdotnp.blogspot.co.il/2009/12/c-c-code-shooting-method-for-solving.html Iteratively guess the missing values for one end & integrate, then inspect the discrepancy with the boundary values of the other end to adjust the estimate Given the starting boundary values u1 & u2 which contain the root u, solve u given the false position method (solving the differential equation as an initial value problem via 4th order RK), then use u to solve the differential equations. Finite Difference Method For linear & non-linear systems Higher order derivatives require more computational steps – some combinations for boundary conditions may not work though Improve the accuracy by increasing the number of mesh points Solving EigenValue Problems An eigenvalue can substitute a matrix when doing matrix multiplication à convert matrix multiplication into a polynomial EigenValue For a given set of equations in matrix form, determine what are the solution eigenvalue & eigenvectors Similar Matrices - have same eigenvalues. Use orthogonal similarity transforms to reduce a matrix to diagonal form from which eigenvalue(s) & eigenvectors can be computed iteratively Jacobi method http://en.wikipedia.org/wiki/Jacobi_method C++: http://people.sc.fsu.edu/~jburkardt/classes/acs2_2008/openmp/jacobi/jacobi.html Robust but Computationally intense – use for small matrices < 10x10 Power Iteration http://en.wikipedia.org/wiki/Power_iteration For any given real symmetric matrix, generate the largest single eigenvalue & its eigenvectors Simplest method – does not compute matrix decomposition à suitable for large, sparse matrices Inverse Iteration Variation of power iteration method – generates the smallest eigenvalue from the inverse matrix Rayleigh Method http://en.wikipedia.org/wiki/Rayleigh's_method_of_dimensional_analysis Variation of power iteration method Rayleigh Quotient Method Variation of inverse iteration method Matrix Tri-diagonalization Method Use householder algorithm to reduce an NxN symmetric matrix to a tridiagonal real symmetric matrix vua N-2 orthogonal transforms     Whats Next Outside of Numerical Methods there are lots of different types of algorithms that I’ve learned over the decades: Data Mining – (I covered this briefly in a previous post: http://geekswithblogs.net/JoshReuben/archive/2007/12/31/ssas-dm-algorithms.aspx ) Search & Sort Routing Problem Solving Logical Theorem Proving Planning Probabilistic Reasoning Machine Learning Solvers (eg MIP) Bioinformatics (Sequence Alignment, Protein Folding) Quant Finance (I read Wilmott’s books – interesting) Sooner or later, I’ll cover the above topics as well.

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  • "Build your own website" - Developing a CMS with Vague Requirements on a Tight Deadline

    - by walnutmon
    I'm a Java developer in charge of making a product which allows clients to "build their own site". I've spent a lot of time looking into Liferay, as I don't have any experience in building CMSs, and want to either use it, or get ideas of how to build a decent system. The time line is short, requirements are vague, yada yada Is Liferay a good technology to work with when showing the client (who may be very low on computer expertise) a user interface to build a site? The thing is, I want the power and flexibility to avoid the learning curve in building a CMS like product, but I don't want to waste time learning a new technology only to find its over-kill, or can't do the simple - but uncommon and unimplemented - things that we are asked to add as features Ideally I'd like to provide multiple web interfaces to the core API to build the sites - one that is very powerful, and another that is watered down and easy to use.

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  • Objective-c Cocos2d moving a sprite

    - by marcg11
    I hope someone knows how to do the following with cocos2d: I want a sprite to move but not in a single line by using [cocosGuy runAction: [CCMoveTo actionWithDuration:1 position:location]]; What I want is the sprite to do some kind of movements that I preestablish. For example in some point i want the sprirte to move for instance up and then down but in a curve. Do I have to do this with flash like this documents says? http://www.cocos2d-iphone.org/wiki/doku.php/prog_guide:animation Does animation in this page means moving sprites or what? thanks

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  • Experience formula with javascript

    - by StealingMana
    I'm having trouble working out a formula using this experience curve to get the total exp after each level. I bet its easy and im just over thinking it. maxlvl = 10; increment = 28; baseexp = 100; function calc(){ for (i = 0;i<(maxlvl*increment);i+=increment){ expperlvl = baseexp + i; document.writeln(expperlvl); } } I figured it out. maxlvl=6; base=200; increment=56; function total(){ totalxp= (base*(maxlvl-1))+(increment*(maxlvl-2)*(maxlvl-1)/2); document.write(totalxp); }

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  • Bring Office 2003 Menus Back to 2010 with UBitMenu

    - by Matthew Guay
    Are you having trouble getting used to the Ribbon interface in Office 2010?  Here’s how you can roll back the clock a bit and bring back the familiar menus and toolbars from 2003. The Office 2007 Ribbon was both praised and criticized.  While many users felt they were more productive with the new interface, others felt frustrated searching for commands they had memorized in older versions of Office.  Now, with Office 2010, the ribbon interface has been brought to every app in the Office suite, and is integrated into many newer programs from Microsoft. If you’re moving from Office 2003, using UBitMenu allows you to add the old familiar menus back along with the new Ribbon interface for an easier learning curve. Also, with the customizability of Office 2010, we can strip away the extra Ribbon tabs to make it more like 2003. Get the 2003 Menus and Toolbars Back in Office 2010 Download UBitMenu (link below), and install as normal.  Make sure all of your Office programs are closed during the installation.  This handy utility is very small, and installed amazingly quick. Open Word, Excel, or PowerPoint and there’s now a new Menu tab beside Home in the Ribbon.  Now you can access all of your favorite old Office commands in the familiar menus, and access many of the newer Office features such as SmartArt.   Here’s a close-up of the toolbar.  Notice that the layout is very similar to that of Word 2003. You can access all of the new Transitions in PowerPoint 2010 from the menu bar.   The menu in Excel even included support for the new PivotTable and PivotCharts Wizard. One problem we noticed was that the toolbars were condensed to a drop-down menu if the Office window was less than 870px wide.  This may be a frustration to users with low-resolution displays, and you might want to use the Office Apps maximized. Get Rid of the Ribbon Now that you’ve got the old menus back, you can get rid of the extra ribbon tabs if you’d like.  Office 2010 lets you customize your ribbon and remove tabs, so let’s get rid of all the other tabs except for our new Menu tab.  In our example we’re using Word, but you can do it in Excel or PowerPoint the same way. Click the File tab and select Options. Alternately, in the Menu tab, select Tools and then Word Options. Select Customize Ribbon on the left sidebar, then uncheck the boxes beside all the ribbon tabs you want to hide on the right.  Click Ok when you’re finished. While you’re at it, you can change the default color scheme as well. Note: The color change will automatically change the color scheme in all of the Office apps, so you’ll only need to do that once. Now the ribbon only has 2 tabs…the File tab for the new Backstage View, and the UBitMenu tab we just installed.  It almost has the appearance Word 2003, but with the new features of Word 2010!  You’ll need to repeat these steps in Excel and PowerPoint if you want to customize their ribbon the same.   Conclusion If you’ve been having a hard time getting used to Office 2010, UBitMenu is a great way to get familiar with the new interface, or simply stay productive with your old tricks.  We do wish it supported the other Office applications like OneNote and Outlook. That doesn’t make it a deal breaker though, it can make the learning curve easier in Word, PowerPoint, and Excel. UBitMenu is free for personal use, and available at a very reasonable price for businesses. If you’re using Office 2007 and not a fan of the Ribbon, UBitMenu works for it as well. Download UBitMenu Similar Articles Productive Geek Tips How To Bring Back the Old Menus in Office 2007Upgrade Office 2003 to 2010 on XP or Run them Side by SideHow to Find Office 2003 Commands in Office 2010Make Word 2007 Always Save in Word 2003 FormatMake Excel 2007 Always Save in Excel 2003 Format TouchFreeze Alternative in AutoHotkey The Icy Undertow Desktop Windows Home Server – Backup to LAN The Clear & Clean Desktop Use This Bookmarklet to Easily Get Albums Use AutoHotkey to Assign a Hotkey to a Specific Window Latest Software Reviews Tinyhacker Random Tips HippoRemote Pro 2.2 Xobni Plus for Outlook All My Movies 5.9 CloudBerry Online Backup 1.5 for Windows Home Server Speed Up Windows With ReadyBoost Awesome World Cup Soccer Calendar Nice Websites To Watch TV Shows Online 24 Million Sites Windows Media Player Glass Icons (icons we like) How to Forecast Weather, without Gadgets

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  • Google Analytics API - Super simple?

    - by Jens Törnell
    Google Analytics API - Too complicated? I've read about Google Analytics API but heard of others that it is a bit complicated to make it work. I use PHP. Copy / paste example My question is if there is a copy / paste example anywhere on the web for getting a stats curve of the latest month, or just the numbers for that period? Important I need to use the new Google Analytics API version for 2012. The other one is going to die soon.

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  • Were you a good programmer when you first left university?

    - by dustyprogrammer
    I recently graduated, from university. I have since then joined a development team where I am by far the least experienced developer, with maybe with a couple work terms under my belt, meanwhile the rest of the team is rocking 5-10 years experience. I am/was a very good student and a pretty good programmer when it came to bottled assignments and tests. I have worked on some projects with success. But now I working with a much bigger code-base, and the learning curve is much higher... I was wondering how many other developers started out their careers in teams and left like they sucked. When does this change? How can I speed up the process? My seniors are helping me but I want to be great and show my value now. I don't to start a flame war, this is just a question I have been having and I was hoping to get some advice from other experienced developers, as well as other beginners like me.

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  • Does software testing methodology rely on flawed data?

    - by Konrad Rudolph
    It’s a well-known fact in software engineering that the cost of fixing a bug increases exponentially the later in development that bug is discovered. This is supported by data published in Code Complete and adapted in numerous other publications. However, it turns out that this data never existed. The data cited by Code Complete apparently does not show such a cost / development time correlation, and similar published tables only showed the correlation in some special cases and a flat curve in others (i.e. no increase in cost). Is there any independent data to corroborate or refute this? And if true (i.e. if there simply is no data to support this exponentially higher cost for late discovered bugs), how does this impact software development methodology?

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  • How to customize the gnome classic panel

    - by Luis Alvarado
    First the picture: As you can see in the image, the color used for the icons and words Applications and Places (In spanish in this case) they have a different background dark gray color than the rest of the panel. Also the icons look rather bigger in that panel. Now my questions are: Can the background colors be customized so they look the same all the way in the panel. Can the icons be somehow minimized a little so they do not look strange (bigger actually) How to edit the way to add icons to the panel. I have to actually have to press the ALT key then right click on it to add something. That extra key is not friendly at all. In this particular case am trying to help an older man start in Ubuntu. Unity is too much for him but Gnome is friendlier for him (Learning curve is not the best for older people.. specially 68+ year old people).

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  • Thoughts of Cloud Development/Google App Engine

    - by jiewmeng
    I use mainly PHP for web development, but recently, I started thinking about using Google App Engine. It doesn't use PHP which I am already familiar with, so there will be a steeper learning curve. Probably using Python/Django. But I think it maybe worthwhile. Some advantages I see: Focus on App/Development. No need to setup/maintain server ... no more server configs Scales automatically Pay for what you use. Free for low usage Reliable, it's Google after all Some concerns though: Does database with no joins pose a problem for those who used App Engine before? Do I have to upload to Google just to test? Will it be slow compared to testing locally? What are your thoughts and opinions? Why would you use or not use App Engine?

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  • How to find the number of packages needing update from the command line?

    - by KayEss
    I'm working on some system admin automation using fabric and I'd like to be able to monitor the number of packages that need upgrading on a given machine. This is the same information that I can see when I first log in to a machine, i.e. this part: 35 packages can be updated. 22 updates are security updates. Is there a command that I can run (preferably without sudo) that gives just that information? I'd also like to know whether or not apg/dpkg thinks that the machine needs a reboot after packages are installed/upgraded. bybobu shows this at the bottom of the screen. That way I can decide whether or not to reboot machines after I update packages a bit more intelligently. I've looked at the apt-python bindings, but they seem to have a high learning curve and they also appear to be changed around a lot -- I'd like something that will work at least as far back as lucid without needing to do different things on different Ubuntu versions.

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  • Most popular Open-Source License on github?

    - by John R
    This is a two part question: 1) What is the most popular Open-Source License used by developers on github? 2) Assuming people follow the rules - will this license (the most popular on github) assure that my name is always associated with the project - regardless of how it forks or is picked up elsewhere. The reason I ask is I have not yet used github nor released an open source project. My main incentive for releasing a particular project is to develop a name for myself and improve my resume. I have a lot of reading to do, but I suspect that knowing the most popular licensing schemes will reduce my reading and my learning curve.

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  • Corona SDK (Lua) vs Native Obj-C for iPhone only word puzzle type game [closed]

    - by dodgy_coder
    I am trying to decide on whether to use the Corona SDK & Lua versus native Objective-C to develop an iOS app. This will be the first game on any smartphone I have developed and so its not that ambitious - a single player word puzzle type game - something sort of like scrabble. The advantages of Corona I can see are: Lua is probably easier to learn than Obj-C (shorter learning curve) meaning a possibly quicker development time Possibility to port to Android once its finished Advantages of native Obj-C are: Access to all and latest features of iOS More / faster available libraries Has anyone made this decision before? Are there any major advantages or disadvantages I've missed or got wrong here? Thanks.

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  • jMonkey Quest Database

    - by theJollySin
    I am building a game in jMonkey (Java) and I have so far only used default quest text. But now I need to start populating a lot of quests with text. My design requires A LOT of quests texts. What is the best way to build a database of quest texts in jMonkey? I don't have a lot of real experience with databases. Is there a database that integrates well with jMonkey? Here are the ideal properties I want in my database, in order of priority: Reasonably light learning curve Easy portability (in Java) to Windows, Linux, and Mac OSX Good interface with Java Good interface with jMonkey The ability to add properties to the quests: ID, level, gender, quest chain ID, etc. Or am I wrong in thinking I need to use some giant monster like SQL? I haven't been able to find much information on this, so are people using some non-database methods for storing things like quest text in jMonkey?

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  • Server Side Developer Prerequisites

    - by Jking
    I am new to server side development and am currently learning node.js. What sort of networking information should I be familiar with to allow for a smooth learning curve with server side development. Could anyone provide resources pertaining to the information required to get into server programming? To give you a better idea of my standpoint: I do not know how a server interacts with a database [Q: How does a NoSQL database, or database in general, communicate with a server?] I am unsure of how a web stack works [Q: I have heard of LAMP but do not know how Apache, MySQL, and PHP interact. Hopefully this applies to other stacks as well. How do the components of a stack work together? Also, is a MEAN stack an alternative, or is it completely irrelevant to this] I have trivial knowledge of internet protocol [however extremely inefficient][Q: What resources are beneficial when learning about networking, and how much/what knowledge should I acquire to program on the server side] I am unsure of what I am unsure of concerning networking information necessary to start development Information on how the client-server model works would be greatly appreciated

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  • How to change speed without changing path travelled?

    - by Ben Williams
    I have a ball which is being thrown from one side of a 2D space to the other. The formula I am using for calculating the ball's position at any one point in time is: x = x0 + vx0*t y = y0 + vy0*t - 0.5*g*t*t where g is gravity, t is time, x0 is the initial x position, vx0 is the initial x velocity. What I would like to do is change the speed of this ball, without changing how far it travels. Let's say the ball starts in the lower left corner, moves upwards and rightwards in an arc, and finishes in the lower right corner, and this takes 5s. What I would like to be able to do is change this so it takes 10s or 20s, but the ball still follows the same curve and finishes in the same position. How can I achieve this? All I can think of is manipulating t but I don't think that's a good idea. I'm sure it's something simple, but my maths is pretty shaky.

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  • Why has there been no serious research in statistical programming languages for 25 years?

    - by Robert
    The two main statistical languages today are S (in the form of R) and SAS, which today pretty much have the form they had 25 years ago. Whatever usability problems or worker productivity problems they had then, they still have today. I'm a data language designer, and I look at, largely, four aspects: Usability (learning curve & readability - here Python scores high) Productivity (how long it takes to finish your work) Flexibility (SAS and R don't have problems here, but a macro library will) Reliability (in the QA/reproducibility sense, usually a PL does better than a GUI here) By the way, I have a language that can produce complex statistical tables much faster than SAS (like 25 lines of code instead of several hundred lines of code). And I'm going to produce a language for data cleaning that will be great for usability (it'll be my third).

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  • EISK&ndash;Employee Info Starter Kit 5.0

    - by Tiago Salgado
    Employee Info Starter Kit is an open source project that is highly influenced by the concept ‘Pareto Principle’ or 80-20 rule, where it is targeted to enable a web developer to gain 80% productivity with 20% of effort with respect to learning curve and production. It is intended to address different types of real world challenges faced by web application developers when performing common CRUD operations. Using a single database table ‘Employee’, the current release illustrates how to utilize Microsoft ASP.NET 4.0 Web Form Data Controls, Entity Framework 4.0 and Visual Studio 2010 effectively in that context.   More information on codeplex project site.

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  • Breakout clone, how to handle/design for collision detection/physics between objects?

    - by Zolomon
    I'm working on a breakout clone, and I wish to create some realistic physics effects for collision - angles on the paddle should allow the ball to bounce, as well as doing curve balls etc. I could use per-pixel based collision detection, but then I thought it might be easier with line/circle intersection testing. So, then I naturally consider making a polygon class for the line-based objects and use the built-in circle class for the circular objects. That sounds like an OK approach, right? And then just check for collision using the specified algorithm based on the objects that might be within each other's range?

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  • The perfect crossfade

    - by epologee
    I find it hard to describe this problem in words, which is why I made a video (45 seconds) to illustrate it. Here's a preview of the questions, please have a look at it on Vimeo: http://vimeo.com/epologee/perfect-crossfade The issue of creating a flawless crossfade or dissolve of two images or shapes has been recurring to me in a number of fields over the last decade. First in video editing, then in Flash animation and now in iOS programming. When you start googling it, there are many workarounds to be found, but I really want to solve this without a hack this time. The summary: What is the name of the technique or curve to apply in crossfading two semi-transparent, same-colored bitmaps, if you want the resulting transparency to match the original of either one? Is there a (mathematical) function to calculate the neccessary partial transparency/alpha values during the fade? Are there programming languages that have these functions as a preset, similar to the ease in, ease out or ease in out functions found in ActionScript or Cocoa?

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