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This will look up your Zwift ID, and get your maximum FTP (95% of 20min) from the past 30 days, or your last ten rides if you haven't raced recently.
As you’re expected to be on ZwiftPower, your Zwift ID can be found on your profile page, and clicking on the Settings tab.


Fill out the form for each principle following the instructions outlined here:
a. Calculate transparency scores between 1 and 10 based on these metrics:
-
Completeness: Does the project describe its complete approach to the relevant topic? Are all facts on the table or are some important pieces of information missing?
-
Clarity: Are the disclosures easy to understand? Consumer tokens can be complex, so it is important to consider how easy it is to comprehend the information being disseminated.
-
Consistency: Does the project describe its approach consistently, or are there conflicting pieces of information that could lead to confusion about the project’s approach?
Judged on these factors, the following scores and symbols are assigned within the scorecard to indicate the quality of relevant statements for each topic.
| score |
assessment |
| - |
Not applicable. Not applicable at the time of assessment. |
| 1-2 |
Red flag. Disclosures are non-existent or contain directly conflicting information. |
| 3-4 |
Poor. Disclosures fail to reveal any useful information. |
| 5-6 |
Present but lacking. Disclosures are only partially complete or lacking in clarity or completeness. |
| 7-8 |
Good. Disclosures meet standards, but have room for improvement. |
| 9-10 |
Very good. Disclosures are complete, clear, easy to understand and consistent. |
b. For each disclosure, indicate under the “Status” column whether the disclosure has been provided (✓) or whether it is missing, incomplete or unclear (X). Include the source of each disclosure in the “Source” column.
c. We suggest that reviewers describe the disclosures and analyze the adherence to the Framework. A few guiding questions have been provided for each Principle to help you carry out this exercise.


I really like Garments grid system, the left side bar will disappear when you reduce the browser size. I am not really understanding how it works, I wish I can figure it out next week and use this function on my blog.
As I understand it, if you think about building a house, first you need the brick or wood to build the foundation of the house. HTML would be the tool that to build the structure of housing. CSS would be the decorator to make the house looks beautiful and nicer. DOM is your future renovation manual; it tells you how each component work in the house and what you do if you want to make a change of the house.
Boxifying design is a concept to help you understand the structure of the webpage. Every element you see in a webpage; it is in a box.
The box model is the concept of the design and layout of webpage. Every HTML element is wrapped in a box. It consists of: margins, borders, padding, and content.c


|
momentumopt
|
Classes | |
| class | Clock |
| Helper class to measure time required to run an optimization procedure. More... | |
| class | ContactPlanFromFile |
| This class implements the ContactPlanInterface by reading a sequence of contacts from a configuration file. More... | |
| class | ContactPlanInterface |
| This class implements a simple interface to store a sequence of contacts, including its activation and de-activation time, position and orientation of the contact, and a variable (set to 1) indicating if the forces at this contact are subject to friction cone constraints or (set to 2) if not, such as in the case of hands grasping bars. More... | |
| class | ContactSequence |
| This class is a container for a sequence of contact states, for all end-effectors. More... | |
| class | ContactState |
| This class is a container for all variables required to define a contact state: position and orientation of the contact, time of activation and de-activation of the contact, and a ContactType variable indicating whether, forces are subject to a friction cone (ContactType::FlatContact) or not (ContactType::FullContact) such as in the case of a hand grasping a bar. More... | |
| class | DynamicsFeedback |
| Class that implements the dynamic description of momentum dynamics as an optimal control problem, to be used by an LQR algorithm to derive a feedback sequence. More... | |
| class | DynamicsFeedbackWrapper |
| class | DynamicsOptimizer |
| class | DynamicsSequence |
| This class is a container for a sequence of dynamic states, for all time steps in the optimization. More... | |
| struct | DynamicsState |
| This class is a container for all variables required to define a dynamic state: center of mass position, linear and angular momenta and its rates; forces, torques and center of pressure of the end- effectors; positions, orientations, activations and contact types of each end-effector. More... | |
| struct | FrictionCone |
| Helper class to define a linear approximation of a friction cone. More... | |
| class | Interpolator |
| class | KinematicsInterface |
| class | KinematicsOptimizer |
| class | KinematicsSequence |
| This class is a container for a sequence of kinematic states. More... | |
| class | KinematicsState |
| This class is a container for all variables required to define a kinematics state: joint posture, joint velocities and accelerations, endeffector poses and momentum. More... | |
| class | PlannerSetting |
| struct | Problem |
| Helper structure used to define common functionality and naming conventions. More... | |
| class | PyKinematicsInterface |
| class | RobotAcceleration |
| class | RobotPosture |
| class | RobotVelocity |
| class | TerrainDescription |
| This class is a container for a terrain description in terms of terrain surfaces. More... | |
| class | TerrainRegion |
| This class is a container for all variables required to define a terrain region. More... | |
| class | TrajectoryGenerator |
| class | ViapointSequence |
| This class is a container for a sequence of viapoint states for all end-effectors. More... | |
| class | ViapointState |
| This class defines a viapoint state including position and orientation. More... | |
Typedefs | |
| typedef Eigen::Matrix< double, 4, 4 > | Matrix4 |
| typedef Eigen::Transform< double, 3, Eigen::Affine > | Transform |
Enumerations | |
| enum | ContactType { FreeContact = 0, FlatContact = 1, FullContact = 2 } |
| Definition of contact type: FlatContact: forces subject to friction cone constrains of flat surface FullContact: forces free in any direction (e.g. More... | |
| enum | PlannerIntParam { PlannerIntParam_NumDofs, PlannerIntParam_NumTimesteps, PlannerIntParam_NumViapoints, PlannerIntParam_NumJointViapoints, PlannerIntParam_NumActiveDofs, PlannerIntParam_MaxNumTimeIterations, PlannerIntParam_NumExtendedActiveDofs, PlannerIntParam_NumActiveEndeffectors, PlannerIntParam_MaxKinTrajectoryIterations, PlannerIntParam_MaxKinConvergenceIterations, PlannerIntParam_NumSubsamples, PlannerIntParam_KinDynIterations } |
| enum | PlannerBoolParam { PlannerBoolParam_IsTimeHorizonFixed, PlannerBoolParam_IsFrictionConeLinear, PlannerBoolParam_DisplayMotion, PlannerBoolParam_LoadKinematics, PlannerBoolParam_StoreData, PlannerBoolParam_UseDefaultSolverSetting } |
| enum | PlannerDoubleParam { PlannerDoubleParam_Gravity, PlannerDoubleParam_TimeStep, PlannerDoubleParam_RobotMass, PlannerDoubleParam_RobotWeight, PlannerDoubleParam_TimeHorizon, PlannerDoubleParam_MinRelHeight, PlannerDoubleParam_MassTimesGravity, PlannerDoubleParam_FrictionCoefficient, PlannerDoubleParam_MaxTimeResidualTolerance, PlannerDoubleParam_MinTimeResidualImprovement, PlannerDoubleParam_WeightArmTorque, PlannerDoubleParam_WeightLegTorque, PlannerDoubleParam_WeightTimePenalty, PlannerDoubleParam_WeightTimeRegularization, PlannerDoubleParam_FloorHeight, PlannerDoubleParam_KinSlacksPenalty, PlannerDoubleParam_KinIntegrationStep, PlannerDoubleParam_LambdaRegularization, PlannerDoubleParam_KinConvergenceTolerance, PlannerDoubleParam_SwingTrajViaZ, PlannerDoubleParam_WeightLinMomentumTracking, PlannerDoubleParam_WeightAngMomentumTracking, PlannerDoubleParam_WeightEndEffContact, PlannerDoubleParam_WeightEndEffTracking, PlannerDoubleParam_PGainEndEffTracking, PlannerDoubleParam_PGainComTracking, PlannerDoubleParam_WeightJointReg, PlannerDoubleParam_PGainOrientationTracking } |
| enum | PlannerStringParam { PlannerStringParam_ConfigFile, PlannerStringParam_SaveDynamicsFile, PlannerStringParam_SaveKinematicsFile, PlannerStringParam_DefaultSolverSettingFile } |
| enum | PlannerIntVectorParam { PlannerIntVectorParam_ActiveDofs, PlannerIntVectorParam_ExtendedActiveDofs } |
| enum | PlannerVectorParam { PlannerVectorParam_TimeRange, PlannerVectorParam_TorqueRange, PlannerVectorParam_ExternalForce, PlannerVectorParam_GravityVector, PlannerVectorParam_CenterOfMassMotion, PlannerVectorParam_MaxEndeffectorLengths, PlannerVectorParam_WeightArmForce, PlannerVectorParam_WeightLegForce, PlannerVectorParam_WeightArmForceRate, PlannerVectorParam_WeightLegForceRate, PlannerVectorParam_WeightCenterOfMass, PlannerVectorParam_WeightLinearMomentum, PlannerVectorParam_WeightAngularMomentum, PlannerVectorParam_WeightLinearMomentumRate, PlannerVectorParam_WeightAngularMomentumRate, PlannerVectorParam_WeightFinalLinearMomentum, PlannerVectorParam_WeightCenterOfMassViapoint, PlannerVectorParam_WeightFinalAngularMomentum, PlannerVectorParam_WeightDynamicTrackingCenterOfMass, PlannerVectorParam_WeightDynamicTrackingLinearMomentum, PlannerVectorParam_WeightDynamicTrackingAngularMomentum, PlannerVectorParam_MinJointAngles, PlannerVectorParam_MaxJointAngles, PlannerVectorParam_KinematicDefaultJointPositions, PlannerVectorParam_WeightJointVelocity, PlannerVectorParam_WeightJointAcceleration, PlannerVectorParam_WeightKinematicTrackingCenterOfMass, PlannerVectorParam_WeightKinematicDefaultJointPositions, PlannerVectorParam_WeightKinematicTrackingLinearMomentum, PlannerVectorParam_WeightKinematicTrackingAngularMomentum, PlannerVectorParam_WeightKinematicTrackingBaseOrientation, PlannerVectorParam_WeightKinematicTrackingLinearMomentumRate, PlannerVectorParam_WeightKinematicTrackingAngularMomentumRate, PlannerVectorParam_WeightKinematicTrackingEndeffectorPosition, PlannerVectorParam_WeightKinematicTrackingNonActiveEndeffectorPosition } |
| enum | PlannerArrayParam { PlannerArrayParam_EndeffectorOffset, PlannerArrayParam_CenterOfPressureRange } |
| enum | PlannerCVectorParam { PlannerCVectorParam_Viapoints, PlannerCVectorParam_JointViapoints } |
| enum | Heuristic { TrustRegion, SoftConstraint, TimeOptimization } |
| enum | InterpolationMethod { PiecewiseLinear, PiecewiseConstant } |
Functions | |
| ContactType | idToContactType (int cnt_type_id) |
| Eigen::Vector3d | orientationError (const Eigen::Quaternion< double > &desired_orientation, const Eigen::Quaternion< double > ¤t_orientation) |
| computes the error between two quaternions by rotating the desired orientation back by the current orientation, and taking the logarithm of the result. | |
| Eigen::Vector3d | requiredAngularVelocity (const Eigen::Quaternion< double > &desired_orientation, const Eigen::Quaternion< double > ¤t_orientation, const double &time_step, bool in_body_coordinates=false) |
| computation of the required angular velocity to move from a current orientation to a desired orientation in a given time interval. More... | |
| Eigen::Quaternion< double > | integrateAngularVelocity (const Eigen::Quaternion< double > ¤t_orientation, const Eigen::Vector3d &angular_velocity, const double &time_step, bool in_body_coordinates=false) |
| integration of a quaternion given an angular velocity given either in body or world coordinates and a time interval for integration | |
| Eigen::Matrix3d | skewMatrix (const Eigen::Vector3d &vec) |
| Eigen::Vector3d | logarithmicMap (const Eigen::Quaternion< double > &quaternion) |
| Eigen::Quaternion< double > | exponentialMap (const Eigen::Vector3d &rotation_vector) |
| Eigen::Matrix4d | toQuaternionMatrix (const Eigen::Quaternion< double > &quaternion, bool is_conjugate) |
| Eigen::Matrix< double, 4, 3 > | jacobianQuaternionWrtRotationVector (const Eigen::Vector3d &rotation_vector) |
| Eigen::Matrix3d | jacobianAngularVelocityWrtRotationVector (const Eigen::Vector3d &rotation_vector) |
| Eigen::Vector3d | toAngularVelocity (const Eigen::Vector3d &rotation_vector, const Eigen::Vector3d &rotation_vector_rates, bool in_body_coordinates) |
| Eigen::Vector3d | fromAngularVelocity (const Eigen::Vector3d &rotation_vector, const Eigen::Vector3d &angular_velocity, bool in_body_coordinates) |
Use ipython run display.py -i <path_to_datafile>
Computes gains using lqr in the end_effector space for solo (assumes legs are weightless) and performs a backward pass to compute gains using a trajectory
Computes gains using lqr in the end_effector space for solo (assumes legs are weightless) and performs a backward pass to compute gains using a trajectory
Computes gains using lqr in the end_effector space for solo (assumes legs are weightless) and performs a backward pass to compute gains using a trajectory
|
strong |
Definition of contact type: FlatContact: forces subject to friction cone constrains of flat surface FullContact: forces free in any direction (e.g.
hand grasp)
Available array variables used by the planner
Available boolean variables used by the planner
Available c-vector variables used by the planner
Available double variables used by the planner
Available integer variables used by the planner
Available vector variables used by the planner
Available string variables used by the planner
Available vector variables used by the planner
| Eigen::Vector3d momentumopt::requiredAngularVelocity | ( | const Eigen::Quaternion< double > & | desired_orientation, |
| const Eigen::Quaternion< double > & | current_orientation, | ||
| const double & | time_step, | ||
| bool | in_body_coordinates = false |
||
| ) |
computation of the required angular velocity to move from a current orientation to a desired orientation in a given time interval.
Angular velocity can be returned in body or world coordinates.


--- layout: post title: 757rb Memcached Talk disqus_id: /2009/07/18/757rb-memcached-talk/ categories: - heuristics - ruby-rails ---
Earlier this week I gave a talk at our local ruby users group, 757.rb, about Memcached. Here recently I started picking it up again so that I could keep track of large sets of PK/FK changes during a big database move. In doing so, I decided to dig deep into it's internals and get a better grasp of how I would use it when I decided to do some serious fragment caching again.
The biggest thing I took away from the talk was -- First, that you can use an array of strings/objects for the key passed to various caching methods. If the object responds to #cache_key, the return of that method would be used. The default implementation of ActiveRecord's #cache_key method is to use the updated_at column for a unique timestamp. It is even smart enough to know weather the object is new or not. Thanks to Brennan Dunn for pointing that out! The second and most important thing was an article by Nahum Wild that talked about item level caching. This seemed like a strange place to start as typically I would start with a page or big sections of fragments. But as the demo app shows, this is an incredibly good place to start. Especially if you have heavy hitting pages of paginated views that talk to deep nested associations.


§385-13 Administration; other sections applicable. For the purposes of this chapter, sections 383-91, 383-92, 383-95, 383-96, and 383-98 to 383-103 shall apply, mutatis mutandis, to the administration of this chapter. [L 1961, c 157, pt of §1; Supp, §93B-14; HRS §385-13]


nips nips2007 nips2007-141 nips2007-141-reference knowledge-graph by maker-knowledge-mining
Source: pdf
Author: David Sontag, Tommi S. Jaakkola
Abstract: We give a new class of outer bounds on the marginal polytope, and propose a cutting-plane algorithm for efﬁciently optimizing over these constraints. When combined with a concave upper bound on the entropy, this gives a new variational inference algorithm for probabilistic inference in discrete Markov Random Fields (MRFs). Valid constraints on the marginal polytope are derived through a series of projections onto the cut polytope. As a result, we obtain tighter upper bounds on the log-partition function. We also show empirically that the approximations of the marginals are signiﬁcantly more accurate when using the tighter outer bounds. Finally, we demonstrate the advantage of the new constraints for ﬁnding the MAP assignment in protein structure prediction. 1
[1] E. Althaus, O. Kohlbacher, H.-P. Lenhof, and P. M¨ ller. A combinatorial approach to protein docking u with ﬂexible side-chains. In RECOMB ’00, pages 15–24, 2000.
[2] F. Barahona. On cuts and matchings in planar graphs. Mathematical Programming, 60:53–68, 1993.
[3] F. Barahona, M. Gr¨ tschel, M. Junger, and G. Reinelt. An application of combinatorial optimization to o statistical physics and circuit layout design. Operations Research, 36(3):493–513, 1988.
[4] F. Barahona and A. R. Mahjoub. On the cut polytope. Mathematical Programming, 36:157–173, 1986.
[5] T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein. Introduction to Algorithms. MIT Press, 2nd edition, 2001.
[6] M. M. Deza and M. Laurent. Geometry of Cuts and Metrics, volume 15 of Algorithms and Combinatorics. Springer, 1997.
[7] C. L. Kingsford, B. Chazelle, and M. Singh. Solving and analyzing side-chain positioning problems using linear and integer programming. Bioinformatics, 21(7):1028–1039, 2005.
[8] A. Koster, S. van Hoesel, and A. Kolen. The partial constraint satisfaction problem: Facets and lifting theorems. Operations Research Letters, 23:89–97, 1998.
[9] M. Wainwright, T. Jaakkola, and A. Willsky. MAP estimation via agreement on trees: message-passing and linear programming. IEEE Transactions on Information Theory, 51(11):3697–3717, November 2005.
[10] M. Wainwright, T. Jaakkola, and A. Willsky. A new class of upper bounds on the log partition function. IEEE Transactions on Information Theory, 51:2313–2335, July 2005.
[11] M. Wainwright and M. I. Jordan. Graphical models, exponential families and variational inference. Technical Report 649, UC Berkeley, Dept. of Statistics, 2003.
[12] M. Wainwright and M. I. Jordan. Log-determinant relaxation for approximate inference in discrete Markov random ﬁelds. IEEE Transactions on Signal Processing, 54(6):2099–2109, June 2006.
[13] D. B. West. Introduction to Graph Theory. Prentice Hall, 2001.
[14] C. Yanover, T. Meltzer, and Y. Weiss. Linear programming relaxations and belief propagation – an empirical study. JMLR Special Issue on Machine Learning and Large Scale Optimization, 7:1887–1907, September 2006.
[15] J. Yedidia, W. Freeman, and Y. Weiss. Bethe free energy, Kikuchi approximations, and belief propagation algorithms. Technical Report 16, Mitsubishi Electric Research Lab, 2001. 8


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BetterMe supports Google Calendar integration
To integrate you own google calendar follow the steps below...
First Make Your Calendar Public
1. In the Google Calendar interface, locate the "Calendars" area on the left.
2. Hover over the calendar you need and click the downward arrow.
3. A menu will appear. Click "Share this Calendar".
4. Check "Make this calendar public".
5. Make sure "Share only my free/busy information" is unchecked.
6. Click "Save".
 In the Google Calendar interface, locate the "Calendars" area on the left.
2. Hover over the calendar you need and click the downward arrow.
3. A menu will appear. Click "Calendar settings".
4. In the "Calendar Address" section of the screen, you will see your Calendar ID.
5. Update you BetterMe profile page with your Calendar Id


Welcome
Step 1: Select your Enex files
Step 2: Configuration
Step 3: Set up your Template
Step 4: Pick your output location
Step 5: Convert
Tested with Electron v6.0.0
(Currently running Electron v)


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Order in our specially-crafted wines from XDODE's Stellenbosch wine farm. Our Merlot is world-renowned and especially loved by the Asian markets.
The food here is so good I don't even cook anymore. I literally order everyday!
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Breakfast Burrito
This is a great recipe for mornings. When you make them, make a big batch because you can freeze them and then pop them in the microwave for 45 seconds to a minute before going to school or work.
This is a great recipe for mornings. When you make them, make a big batch because you can freeze them and then pop them in the microwave for 45 seconds to a minute before going to school or work.