Also Try: Best Private Beaches in Dubai (Do NOT Miss Out!)
JBR Beach is easily one of the most popular beaches in Dubai for tourists & residents alike. It has all the amenities you could want and is next to one of Dubai’s best promenades: The Walk at JBR. This beach’s popularity can lead to crowds occasionally; this is particularly true when an event is being held. Also Try: Best Attractions in Jumeirah (STUNNING!)
Bathrooms & Showers: Available
Cost: Free
Location: Jumeirah Beach Residence, Dubai, United Arab Emirates
Dubaing Score: 5/5
If you enjoy photography, this beach is the perfect location to get jaw-dropping pictures of Dubai’s icon and this beach’s namesake: Burj al Arab. The beach includes most sports facilities, including a running track, and dining spots are within convenient reach. It’s also next to one of the Dubai’s most beautiful souks (Madinat Jumeirah). Also Try: Best Ways to get Sky Views of Dubai (You’ll LOVE it!)
Bathrooms & Showers: Available
Cost: Free
Location: Jumeirah, Dubai, United Arab Emirates
Dubaing Score: 5/5
Another wildly popular beach in Jumeirah that is close to Burj al Arab. The beach is somewhat small but it has all the beachness you could want: calm waters, sand, & sun. It offers great views of the city skyline & Burj al Arab. It’s also a short distance from the Palm Strip Mall. Also Try: Essential Things to See & Do in Dubai (Some are FREE!)
Bathrooms & Showers: Available
Cost: Free
Location: Jumeirah, Dubai, United Arab Emirates
Dubaing Score: 5/5
One of the largest beaches in Dubai, Mamzar Beach possibly has all the things you could want in a beach-side day. It’s adjacent to a massive park, it gives you access to barbeque pits, you can rent chalets & umbrellas, and life guards are on duty daily. It even has 2 large swimming pools nearby in case the open waters aren’t impressing you. Cafés and dining options are within easy reach. Also Try: Ranked Luxury Spas in Dubai (Surprisingly Cheap!)
Bathrooms & Showers: Available
Cost: AED 40 per car; AED 5 if entry by foot
Location: Mamzar, Dubai, United Arab Emirates
Dubaing Score: 4.5/5
Kite Beach retains a heavy popularity among residents and has only recently developed attraction from tourists. It’s also close to Burj al Arab but this beach lacks some amenities unlike other beaches on this list. It’s prime popularity is driven by its width allowing plenty of water sports to be done with ease—even when a crowd builds up. Be sure to get your own food and water here. Also Try: Ranking Best Water Sports in Dubai (BEST fun!)
Bathrooms & Showers: Available
Cost: Free
Location: Jumeirah, Dubai, United Arab Emirates
Dubaing Score: 4/5
This beach has been awarded the blue flag beach status and that has spurred its popularity. It blends sandy shores, grassy fields with palm trees (at a distance), and promenade-style dining options. It’s a full-day destination as you can enjoy the sand & water, sports in the grass, & some delicious food. Mondays here are termed “Ladies Day” and that limits entry to only women.
Bathrooms & Showers: Available
Cost: AED 5
Location: Jumeirah, Dubai, United Arab Emirates
Dubaing Score: 4/5
This beach is highly popular among bay spectators who enjoy having a seat in the car and just meditating off with blank stares into the beautiful sand, water, and bay. It has a massive expanse of sand and is rarely crowded; you’ll have a lot of beach space all to yourself. If you prefer staying away from crowds, this is a spot for you. Be sure to bring your own water & food. Also Try: 5 World-Famous Dubai Car Exhibits (New 2017)
Bathrooms & Showers: N/A
Cost: Free
Location: Jumeirah, Dubai, United Arab Emirates
Dubaing Score: 3.5/5
This is a massive stretch of sandy shoes beside a resorthave no worries, the resort does not charge you for using this beach. This beach offers no crowds, large expanse of sand, and clear waters. You can even camp here but that needs a permit from the Dubai Municipality; that can be a bit time consuming.
Bathrooms & Showers: N/A
Cost: Free
Location: Jebel Ali, Dubai, United Arab Emirates
Dubaing Score: 3.5/5
This beach derives its name from its close proximity to Dubai’s royal fortress. Black Palace Beach offers stunning views of the Palm Jumeirah and allows you to relax in calm waters in the presence of very few other visitors. Also Try: Best Palaces & Forts to Visit in Dubai (Almost GONE 2017)
Bathrooms & Showers: N/A
Cost: Free
Location: Jumeirah, Dubai, United Arab Emirates
Dubaing Score: 3.5/5
As the name hints, this is another beach away from the crowds. It’s located on the left side of Sheraton’s JBR resort. It’s the perfect place to take in the splendid views of the Jumeirah Lake Towers while enjoying the brilliance of the horizon meeting the water, as you lay in cozy, soft sand.
Bathrooms & Showers: N/A
Cost: Free
Location: Jumeirah, Dubai, United Arab Emirates
Dubaing Score: 3.5/5
If you are the owner or manager of a relevant business/institution and feel your business/institution has been overlooked, please contact us at Enquiry@Dubaing.ae


Teleports
Q: I've found a room action that tells me to "move anywhere in room XX"... but I've not discovered room XX yet! Is that right?
A: Yes! Some teleports in Stampadia may lead you to undiscovered rooms. To execute the action, find the destination room in the Rooms Table, draw it on the map, and place the Hero Token in any valid position you like in that room. Remember that you must read a room description when your Hero Token enters it only, so don't read the destination room description before using the teleport!
Q: I moved the Hero Token on a gray numbered square to teleport in another room. Should I move the token on a gray numbered square in the destination room?
A: No. Teleports usually have a room action that says "move anywhere in room XX". So you may place the Hero Token anywhere that's valid: on an empty cell and nothing happens or, if you feel brave, on a gray numbered cell and trigger some room condition. After reading some destination room conditions, you will soon discover that there may be two-way teleports in Stampadia. You can still decide to teleport your Hero on the way back, giving him that Portal feeling we all know. :)
Exploring
Q: I've no unexplored doors I can reach on my map but there are still rooms in the Rooms Table that I've not found. Why?
A: An old Stampadian proverb about completism says "Never trust the Rooms Table, the Equipment Scroll, and the Map!". On the adventure sheet there is a lot of fake stuff like enemies, doors, and rooms to avoid spoilers. So, If you never found a room it never existed. Or not?
Fighting
Q: How many HP does an enemy with no HP checkbox on its symbol have?
A: No HP.   You can watch a better explanation of the health system in the
basics video.
Q: Do I have to spend 1 gold when crossing a door in combat?
A: Yes, both when your hero or the enemies are moving. Keep an eye on the gold bar when trying to escape or get away for a ranged attack!
Q: How do I've to place my dice in combat on my turn?
A: First, look at the Hero Sheet section on the adventure sheet: your available actions are the two in the first column and the other pairs of actions that have a fully ticked group of XP checkboxes below. Then roll your 2 dice and discard all the rolled 1. If you don't have any dice left, you've to pass the turn to your enemies. If you have just one dice left, select any action you can perform. If both dice are available, pick the higher one and place it on any action you can perform. Then pick the lower one and place it on an available action on the right of the previous dice and on a different row: if you placed your dice on the upper row, you've to place your second dice on the second row and vice versa. Then apply the effect of the selected action in order from left to right as explained in the manual. Remember that you don't have to use all of your rolled dice, so you may decide to not play any dice and pass.
Adventure sheets
Q: Is it possible to access adventure sheets from previous days?
A: At the moment there is no official way to access older adventure sheets but the question is on the table from the very beginning of the project. This game wasn't thought of as a game the player rushes dungeon after dungeon, and I wanted to test the idea of players collecting and sharing adventure sheets (you can find parts of this concept in the Vs. Campaign explained in the manual). But the game has changed a lot since its launch so things may change in the future.
Q: But I want to collect all of the Chronicles of Stampadia adventure sheets!
A: Chronicles of Stampadia contents are selected and remixed daily, so any content you missed will probably return in the future. Feel free to scribble on the adventure sheet anything that comes to your mind while you play: your hero and enemies portraits, room details, tips on a specific room, routes, etc. Chronicles of Stampadia descriptions are often vague and features very simple gameplay.
More
Q: How you're monetizing this game?
A: Chronicles of Stampadia is one of my hobby projects and, as for the
others, I'm working on it in my spare time and it is released as opensource. I'm used to paying for hosting my stuff without getting anything back. So, yeah. I'm OK. If you find something I do that you may like it's more than enough for me.
Q: I have more questions!
A: Don't worry! There is a BGG page
here. There's also a Discord server
here - we talk about everything Stampadia there and you may ask questions about the rules in the #help-rules channel.


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CASPER A film review by Jeffrey Graebner Copyright 1995 Jeffrey Graebner
Universal/Amblin's new live-action version of CASPER is considerably more entertaining than it has any right to be. While the film suffers from a nearly incoherent story, it does contain some clever ideas, a lot of laughs, eye-popping visuals, and appealing performances by Christina Ricci and Bill Pullman.
From the beginning, a live-action film based on the "Casper the Friendly Ghost" cartoon series and comic books seems like a strange idea. While film adaptations of older TV series are popular right now, CASPER doesn't immediately generate the strong feelings of positive nostalgia that helped projects like THE FLINTSTONES or THE ADDAMS FAMILY. The project is further hampered by the fact that there just isn't all that much to the source material. It is an awfully thin basis for a full-length movie.
 I suspect that the visual-effects potential is a large part of what attracted Amblin to this project. Many members of the Industrial Light and Magic team that worked on JURASSIC PARK, including supervisors Dennis Muren and Michael Lantieri, also work on CASPER. The illusion created for the ghosts is so believable that it seems absolutely effortless. After the initial "wow" factor wore off, I found that I stopped even thinking about the fact that they *were* special effects. I was completely caught up by the illusion.
Some may object to the fact that the design of the ghosts is essentially the same as the cartoon series. At first the cartoon-like designs are a bit jarring in a live-action film, but I quickly grew used to it. In the long run, I think the familiarity of the design serves the film well. A large part of the success of the visuals comes from the fact that the ghosts seamlessly interact with the human characters and live-action props (using many of the techniques pioneered in WHO FRAMED ROGER RABBIT). This interaction helps the audience to easily lose the impression of watching cartoon characters.
While the film is fun to watch, the script turns out to be both a strength and a liability. Writers Sherri Stoner and Deanna Oliver are veterans of Amblin's "Tiny Toons Adventures" and "Animaniacs" TV series. That background does tend to be reflected in the film, which sometimes seems like a cartoon short stretched out to nearly two hours. The movie has some very clever sequences and some very funny dialog and slapstick. The plot doesn't really hold together, though. It seems like a strung-together collection of scenes rather than a coherent whole.
Like many of the recent TV series adaptations, CASPER is seriously overplotted. The main plot involves Ms. Carrigan (Cathy Moriarty), a rich woman who inherits the mansion haunted by Casper and his three obnoxious cousins. She believes that there is treasure hidden in the mansion, but the ghosts keep her from getting close enough to search. She eventually hires "ghost therapist" Dr. Harvey (Pullman) who moves into the mansion with his daughter Cat (Ricci). As Cat befriends Casper and Dr. Harvey tries to calm the obnoxious cousins, Carrigan and her associate Dibs (Eric Idle) try to find the treasure.
This plot is further complicated by several subplots. Some of them include Cat planning a school dance to be held at the mansion and Kat helping Casper to use a resurrection machine originally invented by his father to bring him back to life.  At times, Stoner and Oliver introduce plot elements that they eventually just abandon. The most blatant example is an unclear prank that a couple of Cat's classmates are trying to engineer. It was never clear exactly *what* they had intended.
Despite this overall incoherence, there are a lot of individual scenes that really *do* work. Many of the jokes do manage to find their mark and the writers wisely include a fair share of jokes aimed at the adults in the audience. They even manage a few clever and unpredictable twists that are quite welcome. The final fate of Moriarty's character is particularly unexpected.
The film does attempt to explore a few serious themes with some surprisingly effective results. There are several scenes where Kat tries to help Casper to remember what he was like when he was alive. These are quite well played and really do generate some dramatic interest. The film even manages a tasteful scene that explains how Casper died. There are also a few well- played scenes involving Dr. Harvey trying to get past the death of his wife. This eventually leads to an exceptionally satisfying conclusion late in the film.
There is one issue that the film conspicuously ignores. There are a number of references to the concept that ghosts are spirits that have been unable to "cross-over" due to unfinished business. This issue comes into play several times, but there are never any discussions of what unfinished business is keeping Casper around. Certainly, resolution of that would have hurt the chances for a sequel, but it should have at least been *discussed*.
In MERMAIDS and both of the ADDAMS FAMILY films, Christina Ricci managed to steal virtually every scene she was in. She gives another really strong performance here. She is an extremely likable performer and she is able to bring a lot even to this kind of cartoonish role. I'd love to see what she would do with a more complex role.
Bill Pullman has been a very solid character actor for many years and he is good here as well. He isn't given much to do, but he does a lot with what he is given. The combination of this film and WHILE YOU WERE SLEEPING might help to increase his marketability as an actor.
The rest of the performances are competent, but not particularly inspired. Moriarty is playing basically the same role she has played in numerous other films and is also allowed to go a little too far over the top here. Eric Idle isn't given a great deal to do, but he still manages to be pretty funny.
First time director Brad Silberling does a competent job and manages to generally keep the pace up. As might be expected here, the direction does seem to favor the visual effects over the acting (as particularly evidenced in the supporting roles). James Horner provides a decent (but not particularly original) musical score. The film does make the mistake of never playing a straightforward version of the old TV series' theme song (a version performed by Little Richard does play over the end credits).
By no means is CASPER a great film, but it is certainly a lot better than it might have been. The film doesn't make a heck of a lot of sense, but it a lot of fun and I left the theater with a big smile on my face.
-- Jeffrey P. Graebner Columbus, Ohio
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


Rule
The Rule class validates only one value once a rule is created it can be used multiple times
Static Method Summary
| Static Public Methods | ||
| public static |
Add custom rule to the Rule class |
Constructor Summary
| Public Constructor | ||
| public |
constructor(obj: String | Object, error: String) |
Method Summary
| Public Methods | ||
| public |
getError(path: *, value: *, key: *): [String] returns a list of errors if they are present |
|
| public |
|
|
| public |
Tests the validity of the constructor object thows an error if the object is invalid |
|
| public |
testEntryObjectOneType(type: *) Tests the validity of the constructor object thows an error if the object is invalid tests if all the keys are valid |
| Private Methods | ||
| private |
getRuleOperators(): [String] Returns a list of the operators when multiple types given its the case for example int|float |
|
| private |
getTypes(): [String] converts array from string if multiple types given in type its the case for exemple int|float |
|
| private |
testOneRule(val: *, obj: Object, type: String, path: String): boolean |
Static Public Methods
Public Constructors
Public Members
public error: * source
public errorCollector: * source
public rule: {"type": *} source
Public Methods
public getError(path: *, value: *, key: *): [String] source
returns a list of errors if they are present
Params:
| Name | Type | Attribute | Description |
| path | * | ||
| value | * | ||
| key | * |
Return:
| [String] |
public testEntryObject() source
Tests the validity of the constructor object thows an error if the object is invalid
public testEntryObjectOneType(type: *) source
Tests the validity of the constructor object thows an error if the object is invalid tests if all the keys are valid
Params:
| Name | Type | Attribute | Description |
| type | * |
Private Methods
private getRuleOperators(): [String] source
Returns a list of the operators when multiple types given its the case for example int|float
Return:
| [String] |
private getTypes(): [String] source
converts array from string if multiple types given in type its the case for exemple int|float
Return:
| [String] |


Bases: matplotlib.colors.LinearSegmentedColormap
LinearSegmentedColormap in which color varies smoothly.
This class is a simplification of LinearSegmentedColormap, which doesn’t support jumps in color intensities.
| Parameters : | name : str
segmented_data : dict
|
|---|
Bases: object
A class attribute that must be set before use.
| skimage.viewer.utils.figimage(image[, ...]) | Return figure and axes with figure tightly surrounding image. |
| skimage.viewer.utils.init_qtapp() | Initialize QAppliction. |
| skimage.viewer.utils.new_plot([parent, ...]) | Return new figure and axes. |
| skimage.viewer.utils.start_qtapp([app]) | Start Qt mainloop |
| skimage.viewer.utils.update_axes_image(...) | Update the image displayed by an image plot. |
Return figure and axes with figure tightly surrounding image.
Unlike pyplot.figimage, this actually plots onto an axes object, which fills the figure. Plotting the image onto an axes allows for subsequent overlays of axes artists.
| Parameters : | image : array
scale : float
dpi : int
|
|---|
Initialize QAppliction.
The QApplication needs to be initialized before creating any QWidgets
Return new figure and axes.
| Parameters : | parent : QtWidget
subplot_kw : dict
fig_kw : dict
|
|---|


Bloodstained Graphics And Performance Update For Switch Is Now Live
Addresses input lag, visual quality, crashes and load times
by Liam DoolanThe long-awaited graphics and performance update for Bloodstained: Ritual of the Night is now available on the Nintendo Switch. In version 1.03 there are four major areas of improvement: input lag, visual quality, crashes and load times.
According to 505, input lag has been "eliminated" throughout the game, controls are more responsive – with enemies easier to fight and environments now less of a hassle to navigate. This will be further optimised in update 1.04.
The visual quality now looks "more clear" and should also be more detailed. Below are some examples and above is a trailer.
The stability of the game has also been improved, and a number of "specific situations" have been addressed, which were causing crashes – most commonly when reading books from shelves.
 More improvements will be added in version 1.04.
What do you think of this latest update? Leave a comment below.
[via kickstarter.com]


|
iDreamSky Game Engine
v1.0.0
|
Animation blender. 更多...
#include <SkeletalAnimBlender.h>
公開方法(Public Methods) | |
| SkeletalAnimBlender () | |
| Constructor. | |
| virtual | ~SkeletalAnimBlender () |
| Destructor. | |
| void | initSkeleton (const SkeletalAnimBase *skelanim_) |
| This function initialized the blender with the information of the animation. 更多... | |
| virtual void | setTime (const float &time_) |
| This function initialized the blender with the information of the animation. 更多... | |
| virtual void | setSpeed (const float &speed) |
| This function set the animation play back speed. 更多... | |
| virtual void | setLoopBehavior (AnimBase::LoopBehavior lb_) |
| This function set the loop behaviour. 更多... | |
| bool | addAnimation (SkeletalAnimBase *skelanim_) |
| This function add animation as child of this blender. 更多... | |
| bool | removeAnimation (SkeletalAnimBase *skelanim_) |
| This function remove animation from the child animation list. 更多... | |
| bool | removeAllAnimation () |
| This function remove all animation from the child animation list. 更多... | |
| void | setBlendWeights (int animIdx_, int boneIdx_, const float &weight_, bool affectChild_=true) |
| This function set the weight of boneIdx_-th bone of animIdx_-th animation. 更多... | |
| void | setBlendWeights (int animIdx_, const Vector< int > &boneIndices_, const float &weight_, bool affectChild_=true) |
| This function set the weight of specifed bones of animIdx_-th animation. 更多... | |
| void | setBlendWeights (SkeletalAnimBase *skelanim_, const char *boneName_, const float &weight_, bool affectChild_=true) |
| This function set the weight of boneIdx_-th bone of animIdx_-th animation. 更多... | |
| void | setBlendWeights (SkeletalAnimBase *skelanim_, const Vector< const char * > &bonesName_, const float &weight_, bool affectChild_=true) |
| This function set the weight of specifed bones of animIdx_-th animation. 更多... | |
| void | setAllBlendWeights (int animIdx_, const float &weight_) |
| This function set the weight of all bones of animIdx_-th animation. 更多... | |
| void | setAllBlendWeights (SkeletalAnimBase *skelanim_, const float &weight_) |
| This function set the weight of specifed bones of animIdx_-th animation. 更多... | |
| virtual float | getTime () const |
| This function get the animation time. 更多... | |
| virtual float | getSpeed () const |
| This function get the animation play back speed. 更多... | |
| virtual AnimBase::LoopBehavior | getLoopBehavior () const |
| This function get the loop behaviour of animation. 更多... | |
| virtual float | getDuration () const |
| This function get the duration of the animation data. 更多... | |
| virtual int | getNumBones () const |
| This function get the Number of Bones in the animation data. 更多... | |
| virtual const char * | getBoneName (int boneIdx_) const |
| This function get the Name of Bone in the animation data. 更多... | |
| virtual int | getBoneIndex (const char *name_) const |
| This function try to find the position of Bone of animation data. 更多... | |
| virtual int | getBoneParentIndex (int boneIdx_) const |
| This function try to find the position of parent of Bone in of animation data. 更多... | |
| virtual void | getVector10 (int boneIdx_, Vector10 &v_) const |
| This function get the Vector10 (scale, rotation and translation) of the i-th bone. 更多... | |
| int | getNumAnimation () const |
| This function return the number of animation child in the blender. 更多... | |
| SkeletalAnimBase * | getAnimation (int animIdx_) const |
| This function return the i-th child animation in this blender. 更多... | |
| int | getAnimationIndex (SkeletalAnimBase *skelanim_) const |
| This function try to find the position of animation in this blender. 更多... | |
| void | getBlendWeight (int animIdx_, int boneIdx_, float &weight_) const |
| This function get the weight of boneIdx_-th bones of animIdx_-th animation. 更多... | |
| void | getBlendWeights (int animIdx_, const Vector< int > &boneIndices_, Vector< float > &weights_) const |
| This function get the weights of bones specified by boneIndices_ of animIdx_-th animation. 更多... | |
| void | getBonesChainIndices (int boneIdx_, Vector< int > &boneIndices_) const |
| This function collect the bone indices starting from boneidx_-th bones and all it descedents. 更多... | |
| virtual void | update () |
| This function is implemented thing need to do in each cycle of animation. 更多... | |
| virtual bool | isPlaying () const |
| This function get the playing status of the Animation. 更多... | |
| virtual void | play (AnimBase::LoopBehavior lb_=AnimBase::LOOP, const float &speed_=1, const float &starttime_=0) |
| This function start or resume the Animation. 更多... | |
| virtual void | stop () |
| This function stop the Animation. 更多... | |
| virtual void | pause () |
| This function pause the Animation. 更多... | |
| virtual void | rewind () |
| This function rewind the Animation (to its first frame), clears time. 更多... | |
| virtual bool | isPaused () const |
| This function get the pause status of the Animation. 更多... | |
| 公開方法(Public Methods) 繼承自 IDreamSky::SkeletalProceduralAnimation | |
| SkeletalProceduralAnimation () | |
| Constructor. | |
| virtual | ~SkeletalProceduralAnimation () |
| Destructor. | |
| 公開方法(Public Methods) 繼承自 IDreamSky::SkeletalAnimBase | |
| SkeletalAnimBase () | |
| Constructor. | |
| virtual | ~SkeletalAnimBase () |
| Destructor. | |
| virtual void | getLocalTransform (int boneIdx__, Matrix4 &mat_) const |
| This function get the local Transform of of the i-th bone. 更多... | |
| virtual void | getSystemTransform (int boneIdx__, Matrix4 &mat_) const |
| This function get the global Transform of of the i-th bone. 更多... | |
| 公開方法(Public Methods) 繼承自 IDreamSky::AnimBase | |
| AnimBase () | |
| Constructor. | |
| virtual | ~AnimBase () |
| Destructor. | |
| virtual void | setEventCallBack (Functor1< AnimBase * > *cb_) |
| This function set the animation call back. 更多... | |
| virtual Functor1< AnimBase * > * | getEventCallBack () |
| This function get the animation call back. 更多... | |
| void | invokeCallBack () |
| This function invoke the Animation CallBack. 更多... | |
額外的繼承成員 | |
| 公開型態 繼承自 IDreamSky::AnimBase | |
| enum | LoopBehavior { ONESHOT, CLAMP, LOOP, PINGPONG } |
| This Enum specified the way the animation is played. 更多... | |
| 保護屬性 繼承自 IDreamSky::AnimBase | |
| Functor1< AnimBase * > * | cb |
| This function retrieve the Animation that Triggered the callback. 更多... | |
Animation blender.
This is the class to handle the blend operation of character animation
| bool SkeletalAnimBlender::addAnimation | ( | SkeletalAnimBase * | skelanim_ | ) |
This function add animation as child of this blender.
After this function is called, the skelanim_ will become child of this blender and the blender will include skelanim_ into calculation. By default, this function will set the weight of bones to 1.
| skelanim_ | the animation to set |
| SkeletalAnimBase * SkeletalAnimBlender::getAnimation | ( | int | animIdx_ | ) | const |
This function return the i-th child animation in this blender.
| int SkeletalAnimBlender::getAnimationIndex | ( | SkeletalAnimBase * | skelanim_ | ) | const |
This function try to find the position of animation in this blender.
| skelanim_ | the pointer to SkeletalAnimBase to find |
| void SkeletalAnimBlender::getBlendWeight | ( | int | animIdx_, |
| int | boneIdx_, | ||
| float & | weight_ | ||
| ) | const |
This function get the weight of boneIdx_-th bones of animIdx_-th animation.
| animIdx_ | the index to child animation |
| boneIdx_ | the index to bone |
| weight_ | the variable to receive the returned weight |
| void SkeletalAnimBlender::getBlendWeights | ( | int | animIdx_, |
| const Vector< int > & | boneIndices_, | ||
| Vector< float > & | weights_ | ||
| ) | const |
This function get the weights of bones specified by boneIndices_ of animIdx_-th animation.
| animIdx_ | the index to child animation |
| boneIndices_ | the array of indices to bones chain |
| weight_ | the array to receive the returned weights |
|
virtual |
This function try to find the position of Bone of animation data.
| name_ | the name of Bone to find; |
|
virtual |
This function get the Name of Bone in the animation data.
| i | the idx to bone array; |
|
virtual |
This function try to find the position of parent of Bone in of animation data.
| i_ | the index of the bone; |
| void SkeletalAnimBlender::getBonesChainIndices | ( | int | boneIdx_, |
| Vector< int > & | boneIndices_ | ||
| ) | const |
This function collect the bone indices starting from boneidx_-th bones and all it descedents.
| boneIdx_ | the index to starting bone |
| boneIndices_ | the array of indices to bones chain |
|
virtual |
This function get the duration of the animation data.
The long duration amongst all child is returned
|
virtual |
This function get the loop behaviour of animation.
The loop behaviour of child 0 is returned
| int SkeletalAnimBlender::getNumAnimation | ( | ) | const |
This function return the number of animation child in the blender.
|
virtual |
This function get the Number of Bones in the animation data.
The number of bones returned by this function is equal to the animation set during initSkeleton.
|
virtual |
This function get the animation play back speed.
The speed of child 0 is returned
|
virtual |
This function get the animation time.
|
virtual |
| void SkeletalAnimBlender::initSkeleton | ( | const SkeletalAnimBase * | skelanim_ | ) |
This function initialized the blender with the information of the animation.
This function initialized the blender with the information of the animation Internally, it copy the all bones name, and bones parent. These data helps user to specify what part of the animation that he want to manipulated e.g. setting weight After this function is called, we can only add animation with the same skeletal structure of skelanim_
| skelanim_ | the animation that data is to copy from |
|
virtual |
This function get the pause status of the Animation.
|
virtual |
This function get the playing status of the Animation.
|
virtual |
This function pause the Animation.
This function will call all its childen's pause function.
|
virtual |
This function start or resume the Animation.
This function will call all its childen's start function.
| lb_ | the behaviour when animation is played to last frame |
| speed_ | the speed for the animation |
| starttime_ | from which the animation is played |
| bool SkeletalAnimBlender::removeAllAnimation | ( | ) |
This function remove all animation from the child animation list.
After this function is called, the skelanim_ will be removed from the child animation list. the influence of the skelanim_ will be removed afterward
| skelanim_ | the animation to set |
| bool SkeletalAnimBlender::removeAnimation | ( | SkeletalAnimBase * | skelanim_ | ) |
This function remove animation from the child animation list.
After this function is called, the skelanim_ will be removed from the child animation list. the influence of the skelanim_ will be removed afterward
| skelanim_ | the animation to set |
|
virtual |
This function rewind the Animation (to its first frame), clears time.
This function will call all its childen's rewind function.
| void SkeletalAnimBlender::setAllBlendWeights | ( | int | animIdx_, |
| const float & | weight_ | ||
| ) |
This function set the weight of all bones of animIdx_-th animation.
This function call void setBlendWeights(SkeletalAnimBase *skelanim_, const char *boneName_, const fix &weight_, bool affectChildBone_ = true); for each bonesName_[i], i = 0 to bonesName_.length()
| animIdx_ | the index to child animation |
| weight_ | the weight to set |
| void SkeletalAnimBlender::setAllBlendWeights | ( | SkeletalAnimBase * | skelanim_, |
| const float & | weight_ | ||
| ) |
This function set the weight of specifed bones of animIdx_-th animation.
This function call void setBlendWeights(SkeletalAnimBase *skelanim_, const char *boneName_, const fix &weight_, bool affectChildBone_ = true); for each bonesName_[i], i = 0 to bonesName_.length()
| animIdx_ | the index to child animation |
| weight_ | the weight to set |
| void SkeletalAnimBlender::setBlendWeights | ( | int | animIdx_, |
| int | boneIdx_, | ||
| const float & | weight_, | ||
| bool | affectChild_ = true |
||
| ) |
This function set the weight of boneIdx_-th bone of animIdx_-th animation.
This function will start at boneIdx_-th bone and set the weight if affectChildBone_ is set to true, all its descedent weight will also be set
| animIdx_ | the index to child animation |
| boneIdx_ | the index to bone to begin with |
| weight_ | the weight to set |
| affectChildBone_ | set to true if needed to recusively set child bone |
| void SkeletalAnimBlender::setBlendWeights | ( | int | animIdx_, |
| const Vector< int > & | boneIndices_, | ||
| const float & | weight_, | ||
| bool | affectChild_ = true |
||
| ) |
This function set the weight of specifed bones of animIdx_-th animation.
This function call void setBlendWeights(int animIdx_, int boneIdx_, const fix &weight_, bool affectChildBone_ = true); for each boneIndices_[i], i = 0 to boneIndices_.length()
| animIdx_ | the index to child animation |
| boneIndices_ | the array of indices to bone to begin with |
| weight_ | the weight to set |
| affectChildBone_ | set to true if needed to recusively set child bone |
| void SkeletalAnimBlender::setBlendWeights | ( | SkeletalAnimBase * | skelanim_, |
| const char * | boneName_, | ||
| const float & | weight_, | ||
| bool | affectChild_ = true |
||
| ) |
This function set the weight of boneIdx_-th bone of animIdx_-th animation.
This function will start at bone named as boneName_ and set the weight if affectChildBone_ is set to true, all its descedent weight will also be set
| animIdx_ | the index to child animation |
| boneName_ | the name of the bone to begin with |
| weight_ | the weight to set |
| affectChildBone_ | set to true if needed to recusively set child bone |
| void SkeletalAnimBlender::setBlendWeights | ( | SkeletalAnimBase * | skelanim_, |
| const Vector< const char * > & | bonesName_, | ||
| const float & | weight_, | ||
| bool | affectChild_ = true |
||
| ) |
This function set the weight of specifed bones of animIdx_-th animation.
This function call void setBlendWeights(SkeletalAnimBase *skelanim_, const char *boneName_, const fix &weight_, bool affectChildBone_ = true); for each bonesName_[i], i = 0 to bonesName_.length()
| animIdx_ | the index to child animation |
| bonesName_ | the array of bone to begin with |
| weight_ | the weight to set |
| affectChildBone_ | set to true if needed to recusively set child bone |
|
virtual |
This function set the loop behaviour.
After this function is called, all child animation's setLoopBehavior is called
| lb_ | the loop behaviour of the animation |
|
virtual |
This function set the animation play back speed.
After this function is called, all child animation's setSpeed is called
| speed | the speed of the animation, set to 1.0 for the same speed as exported data |
|
virtual |
This function initialized the blender with the information of the animation.
This function initialized the blender with the information of the animation Internally, it copy the all bones name, and bones parent. These data helps user to specify what part of the animation that he want to manipulated e.g. setting weight After this function is called, we can only add animation with the same skeletal structure of skelanim_
| skelanim_ | the animation that data is to copy from This function set the animation time |
After this function is called, all child animation's setTime function is called
| time | the time of the animation |
|
virtual |
This function stop the Animation.
This function will call all its childen's stop function.
|
virtual |
This function is implemented thing need to do in each cycle of animation.
this function will call all its childen's cycle function


Chicago-Based Data Enthusiast with 2+ years of Data Science and Machine Learning including 1 year of Healthcare Analytics experiences. With strong analytical and technical skills, able to solve problems with creative solutions and producing effective data-driven strategies. A quick learner who can absorb new ideas and can communicate clearly and effectively. Currently looking for full-time employment.
Our group sought to investigate grocery retailers through multiple data visualization techniques from data set called “The Complete Journey” released from the data science firm, dunnhumby. Doing so would help retailers have better understanding of buyer habits and product relationship to improve their marketing strategies. The data set we chose is consisted of 276,484 transactions, 2,500 households’ demographic details, and 92,353 items of products. We divided up into two big aspects of the investigation—marketing and product relationship aspects. I used R and Tableau to create these visualizations
This plot shows what age range spend the most when transactions occur. I present this chart as a bar graph including zero because it will not be exaggerated if I did not include zero. As we can see, the people whose age between 45-54 spend the most among others.
This plot helps us to clearly separate which campaign is the most successful (represented by area of squares) divided by age range (presented by different color). Campaign number 18 is the most successful in people with the age of 45-54, 25-34, 55-64 and 65+, and campaign number 13 for 35-44 and 19-24.
This plot reveals customers in which age range redeem the most coupons divided by campaign (Y-axis). The width of violin plot represents number of coupon redemption. We can obviously see Campaign number 18 is a big hit across all customers’ age range except 35-44 and 19-24 (can be clearly distinguished in graph 4). People with the age between 45-54 redeem most coupon across all customers, and 19-24 use least coupon.
This plot reveals the distribution of sale values summary by different age range. Having changed from normal scale to logarithmic scale for sale values summary helps the data exhibit itself better rather clumping on the X-axis. Overlaying box/whisker plots on violin plot also helps us to see which group of customers tend to spend the most. From the normal scale plot (left), the box/whiskers plots also help us detect the outliners that may affect analysis result.
This graph reveals the relationship between different products being randomly chosen linked together by lines. Line width show how much they are correlated to one another. The thicker line, the more highly correlated of products are. For example, from the thickness alone, we can see people who have baby are more likely to buy film/camera products, and beer rather than vitamins. The coffee and fitness & diet products are not correlated at all.
Having explored and analyzed the data through different visualization techniques, I found the different patterns in coupon redemption, how much different ages customers spend, the most successful campaign and product relationship. Those patterns potentially help retailers have better understanding their customers in order to make the decision for store improvement and gain more profit. Looking at the data alone does not help a non-technical person have an idea what is going on, yet after the proper visualization techniques been applied, the insights/patterns hidden in the data are revealed with easily understandable. The data visualization definitely facilitates the data analysis and decision-making processes.
Improving the classification algorithm performance can be done in many different ways, but the most popular approaches are to use bagging and boosting with different weak learners. In this project, we use the Lung nodules data set generated from 2D lung nodule images and extracted into content-based features. The data consists of 810 instances with 65 useful feature attributes with four likelihood of malignancy ratings given by four different radiologists. We also use three different data preprocessing approaches (binning, balancing and feature extraction (PCA)) and fit six different classifiers in each preprocessed data set. We then compare all classifiers in order to make assumption whether bagging or boosting is outperformed to one another.
Our data set consists of 5 malignancy ratings (1, 2, 3, 4 and 5) given by 4 different radiologists, we then decide to bin the classes by grouping them into 2 classes -class 1, 2, 3 and class 4 and 5 as inconclusive and likely suspicious of malignancy respectively. In order to do so, we have to average all ratings given by 4 different radiologists, and round it up to get the single rating values.
Having binned the class variables into two classes, we can obviously see the data become imbalanced with inconclusive and likely class, 682 and 128 respectively. Minorities would be ignored from the model prediction. We resolved this issue by applying SMOTE function in DMwR library on raw data. With this function, it is said by Torgo, L. (2010) to artificially generate new examples from the minority class using the nearest neighbors of these cases, and majority class examples are also under-sampled, leading to a more balanced dataset.
Principle Component Analysis (PCA) is the feature extraction technique that can reduce the dimension space of the data set. This data set has many attributes (more than 60 attributes). After applying PCA, the first feature we extract from the attribute space captures the most variability in the data.
Even though the scree plot suggests that the first four components to capture the most variance (66.89%) in the data, the variance still does not meet our expectation (at least 95%). In order to do so, we then decide to use 22 components to capture at least 95 percent of the variances in the data.
Once all our data preprocessed, we get three sets of data– unbalanced raw, balanced and feature extracted (PCA) data set. We then fit Boosted Tree, Stochastic Gradient Boosting (GBM), Boosted Logistic Regression, Random Forest (extension of bagging), Bagged CART(Bagged Tree) and Bagged LDA models on each data set.
In order to find the best model of each ensemble classifier, we use Grid Search function, which will try multiple combinations of parameters available in that ensemble classifier. We then choose the best model of each model based on the area under the ROC curve.
Furthermore, we decide to use 10-fold cross validation this data set is small. Another important reason that we use 10-fold cross validation because we would like to prevent the model overfitting to the training data.
This plot just shows an example of how the models performed with different parameters only on the balanced data set (the unbalanced data and the feature extraction(PCA) included in appendix). Grid Search has been performed to find the best parameters for each model. For Random Forest, number of randomly selected predictors(mtry) have been used to find the optimal model. The results revealed that when the number of mtry increases, the AUROC decrease. This might indicate that the RF model started getting overfitted.
For boosted Tree and GBM, tree depths and number of trees were parameters used to adjust the tree.After trying many combination, the result revealed that AUROC increases when the number of trees increases. More details about results are included in appendix.
Having fitted all models on each data set, we can see the the Random Forest has the best overall performance, even though the Boosted tree perform better in only imbalanced data. The second best model so far is Bagged Cart (Bagged Tree) model on both balanced and PCA data set, and Random Forest for the unbalanced data.
Across different preprocessing approaches, we can see the feature extraction (PCA) improve prediction performance on some models, and the rest are about the same as the result in balanced data. Therefore, it would better to use PCA approach to reduce over 60 features into 22 features to capture 95% of the variance in the data. The less features are in the models, the faster algorithm run. Since we use 10-folds cross validation with 10 iteration technique, it makes all of our ensemble models run really slow. We also see that the more complexity model is, the longer the algorithm run.
Based on this data set, we can conclude for these findings that Bagging is more outperformed than Boosting techniques on binary class variables, but Boosting might perform best on unbalanced data. Even though Kristína Machová found Boosting has higher performance in her work, it makes sense to us that we found Bagging has higher performance on this certain data because cross validation is used in experiment making our samples become small which fit very well in Bagging models. Within boosting technique, boosted tree perform the best across all different data. For the bagging, Random Forest perform the best among other bagging techniques (Bagged Tree and Bagged LDA).
For future work, we would use the multiple rating given by four different radiologists rather than binning them into binary class. The hybrid ensemble model could be fitted to multi-class label better than the single ensemble classifier. The elements of the hybrid ensemble model can be picked from this experiment, as well as we could combine both bagging and boosting altogether. Additionally, this data set is small. The model results would be better; we can collect more data for the minority class.
The purpose of this data analysis is to perform an exploratory analysis and develop time series model of Apple stock prices. We would like to provide the best model that can be used to precisely forecast the upcoming Apple stock price. As we have known, Apple is the number one company in the consumer electronics market. After 2001, the year that the company reinvented itself with the introduction of iPod, Apple stock has soared more than 100 percent to the most recent period. Today, AAPL’s price is around 102 per share.
However, the price fluctuation has occurred due to the market’s uncertainty and company’s movement. For example, Apple introduced the fourth version of its iPhone in 2010. After the press, Apple's stock fell about or 2 percent, to $250.94. On the same day, the Dow Jones industrial average and the Standard & Poor's 500 index both plunge to their lowest level of the year because of concerns about Europe's economic problems. In 2013, AAPL’s price changed dramatically in a short period of time. It fell sown about 26% and then gained more than 40%. It is also obvious that the variance of the AAPL’s price is not constant over time. To capture this sort of situation, we have decided to apply the time series model that has the effect of shock persistent to the return movement and the volatility affected by negative shocks.
We finally forecasted the AAPL’S price after March 8th, 2016 based on our suggested model. The forecast shows the higher prices and seems to have an upward trend following. We also did the model validation and compared our result with the actual AAPL’s price after March 8th, 2016. It turned out that our prediction is very close, indicating the appropriated model in the analysis. Therefore, we believe our suggested model is useful to analyze the future APPL’s price. However, analyst should carefully utilize not only with the model, but with the experience and the real-time market’s price.
The time plot of Apple daily stock prices in dollars, starting in January 2002 to March 2016, shows the growth began to slow soon after 2008. Although MacBook Air was first introduced in January 2008, a collapse had occurred until the growth recovered in the middle of 2009; when the new iPhone3GS was launched. The growth continued with the upward trend and reached to the peak in the second half of 2012. Following the peak, the stock prices changed dramatically since. The prices had decreased in 2013 and then rebounded to the upward trend in the same year. There was a huge spike in 2015, the highest in the history.
We applied log transformation to the dataset since there is evidence that our data with the time series is nonstationary, and it has a non-linear growing trend.
After applying log transformation, the histogram shows the symmetric of the distribution with the longer left tails (skewness = -0.179). Moreover, it shows that the distribution has large Kurtosis (Kurtosis = 5.129), demonstrating the fat tails, and mean zero. The Normal Probability plots show the skewness on both tails. Moreover, we test the hypothesis of normality for the distribution using the Jarque-Bera test at 5% level. Since P-value < 2.2e-16, we can reject null hypothesis and conclude that the data does not come from normal distribution at 5% significance level.
Time plots show returns varying around the zero line with an extremely large log return around 2002 (-0.15), 2008 (-0.20), and 2013 (-0.15) followed by a high volatility period. Conditional volatility is non-constant over time with periods of high volatility in in 2008-2010 during the European’s economic crisis, and when many technology stocks plunge on concerns about a slowdown in consumer spending. Negative shocks have an effect on the process volatility, where high volatility does not decrease quickly.
The ACF plots show that Apple stock log returns are not correlated – indicating a constant mean model for rt.  We can conclude that the log returns process has a strong non-linear dependence. We also know that time series shows an ARCH effect when squared or absolute values of time series are serially correlated. Moreover, the LB tests on squared returns and absolute returns confirm that both are auto correlated (p-values<0.05, we can reject H0 of no correlation).
Having done exploratory analysis, our apple stock log return does not show to be serial correlated and the normality in the data. The plots of log returns also show the non-constant volatility in data. It makes sense to apply GARCH model to capture conditional volatility.
We then start fitting three different types of model-GARCH, eGARCH and tGARCH with normally distribution error. BIC is also used to help us determine which model type turn out to be the best fit. Once model type is found, we then tune the model with different error distribution (Normal distribution, student distribution and Skewed- student distribution).
eGARCH model turns out to be the best type for this data. We therefore tweak parameter with two more different error distribution methods- student and skewed-student distribution. It totally makes sense that eGARCH and tGARCH fit better than GARCH on this data because eGARCH and tGARCH allow us to capture asymmetric between positive and negative effects on the asset, which GARCH does not.
Having fitted the eGARCH model with three different error distributions and obtained BIC, the model with student distribution turns out to be the best model for Apple stock return from 2002-2016. In order to accept the eGARCH with student error distribution, we have to check the adequacy of the model.
The best fitted model rt = 0.001320+ at, at=σtet, ln(σ2t) = -0.145191 + (-0.050335 et-1 + 0.0.981232(|et-1| - E(|et-1|)) + 0.142474 ln(σ2t-1) with t-distribution with 5 degrees of freedom. With significant P-value of alpha1, we can then conclude that there is the leverage effect significant at the 5% level. Since the alpha 1 is less than zero, the volatility is more likely to react to negative shocks. The large beta value indicates the effect of a shock is strong persistence.
If model is adequate, residuals should be white noise and squared residuals should be white noise (no ARCH effect).
P-values are larger than 0.05. Therefore, we cannot reject the hypothesis of independence for the residuals, and conclude that residual series behave as a white noise process. There is no evidence of autocorrelation in residuals.
Ljung-Box test for ARCH/GARCH effect computed on squared residuals. P-values are larger than 0.05. Therefore, we conclude that there is no evidence of serial correlation in squared residuals.
Shape parameter in Robust Standard Errors is significant (p-value = 0.0e+00), indicating that the t- distribution is a good choice. Also, from Adjusted Pearson Goodness-of-Fit Test, p-values are larger than 0.05. It means that t-distribution assumption cannot be rejected. This supports the choice of the t-distribution
Also, t-distribution probability plots for residuals show that t-distribution is appropriate. Some departure is seen above and under the left tail for extreme residuals.
Moreover, the series with 2 conditional SD superimposed plots show that our model seems to capture most of the extreme shock. However, it is not likely to capture some extreme shocks.
Having done 5-step forecast, the apple stock price is more likely to go up after March 7th, 2016 (our last date of the dataset). With 1000-out-of-sample rolling forecast, the yellow shade shows the area that our model can capture the actual movement represented by blue line. As shown the yellow shade, our model can capture most of the volatility of the Apple stock return.
Since all residuals of the eGARCH with t-distributed error have no sign of autocorrelation and serial correlation, we conclude eGARCH model with t-distributed error becomes our best adequately fitted model for the Apple stock price log return. It has the effect of shock persistent to the return movement and the volatility affected by negative shocks. Moreover, we can see that our model can still capture the asymmetric volatility behavior of Apple log return price from the 1000-out-of-sample one-step ahead rolling forecast in a previous section.
However, Apple stock fluctuations in stock prices are irrational sometimes. We have seen their prices go up and down more than a rollercoaster at times. Therefore, we should investigate the actual environment and circumstances. In a meantime, we thoroughly analyze and forecast of stock price by utilizing the suggested model.
With in the airline on-time data set, it has multiple zip files divided by years from 1988 to 2008. After all files unzipped, the data has different small CSV files that have to be merged together before moving forward. I got big CSV files with the size of 35 Gigabytes after unzipped. My next step is to implement Map functions in Python and apply/debug on the real data until they work properly before being used in Hadoop environment.
• Numbers of flight cancelations
• Numbers of operational flight through out the years
• Numbers of cancelations divided by months at O’Hare airport
• Numbers of flight delay departure at O’Hare airport by years
We can now create MapReduce funtions using Python.
At this point, I decided to debug the code by using the following command to see whether my Python codes are applicable before using them in Hadoop. I use this line of code below to debug the codes
The codes seem run pretty well, but there were some outputs did not return proper values. To narrow down this problem, I decided to check whether each line has the same numbers of columns. It turned out some years do not have the same columns. Thus, I checked the data year by year and picked some years before merging them together instead of using the whole period—1988 to 2008. In 2004, 2005 and 2006, the data have the same numbers/types of columns, I then merge these three years altogether with the size around 6.8GB (which is possibly big enough for Hadoop processing). The final data has 54 columns and 21,411,788 rows and it is ready to run on Hadoop clusters.
With this data set, Hive and Python MapReduce functions run about the same. The advantages of using Hive is handy and easier for people who have SQL background, as well as who are not hard coders. Hive will automatically transform your SQL-like entries to MapReduce functions. Unlike Hive, customized Python MapReduce functions require more coding skills, but it can be customized however we want. I also believe the customized codes can still be maximized the performance more if we know how to change the configurations and faster algorithms. All in all, I personally prefer using Hive as for a handy reason that I just fire SQL queries into system and wait the results.
I use Hive open server service, and link it to Tableau to reduce a bottle neck when create data visualizations. Having created connection between Hive and Tableau, let's test the performance. The data I used in this solution have different tables with 2,595,732 observations. I have joined all tables and created multiple plot through this solution. It was really faster than running on my local machine.


Terms set for using national product logo
In a bid to support and promote national products in local markets, the Ministry of Commerce and Industry has issued mandatory terms for the use of the national product logo on Qatari goods.
The mandatory terms compel all local manufacturers and producers to place the national product label on all agricultural products as well as all locally-manufactured and semi-manufactured goods that are sold in Qatar.
Through this new initiative, the Ministry aims to support and promote national products across local market and to enable investors to easily reach consumers as well as to provide traders and investors seeking to offer new products access to new markets.
The mandatory terms stipulate that all manufacturers and producers, as well as sales outlets who have obtained the necessary approvals and official licences, are allowed to use the logo. The logo can be used on all locally manufactured and semi-manufactured products.
The logo shall appear on the front cover of the product’s packaging or on any other place that is clearly visible to the consumer, taking into consideration not to place the label under the product.
According to the ministry, logo stickers can be placed on shipping and distribution vehicles and must be designed to be proportional to the vehicle’s size. The logo can be placed on advertising materials for marketing purposes.
It is prohibited to use the logo on products intended for export.
The slogan or phrase “Made in Qatar” may be used in such a case. Adherence to the design guidelines is required while changing the shape or content of the logo is prohibited, said the Ministry.
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Qatar Manpower Solutions Co receives ISO certificate for integrated management system
Qatar Manpower Solutions Co. (WISA) has announced that it has received an ISO certificate in Quality management systems ISO9001:2015, environmental management systems ISO14001:2015, and occupational health and safety ISO45001:2018 which represents the most important certificates in the field of quality management. This Achievement came after inspection done by the QACS International, one of the world’s respected
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Qatar Astronomical Center to hold training program
Qatar Astronomical Center will organise a training program on the “Development of Crescent Sighting Skills” at the centre’s headquarters next Wednesday.


The settings below will be used when creating new fleets.
Flagship is an application supporting Star Wars Armada play though fleet building, analytics, and campaign management. It was created and is maintained by Joshua Barron. You can file issues or contribute to the development of Flagship at GitHub.
This privacy notice discloses the privacy practices for Flagship. We only retain basic user information to provide persistence for created fleets and campaigns. We will never share your personal information with third parties except if required to do so by law. Your continued use of our website will be regarded as acceptance of our practices around privacy and personal information. If you have any questions about how we handle user data and personal information, feel free to contact us on GitHub.
Flagship's source code is licensed under the MIT License.
This software is not endorsed by Disney, Lucasfilm Ltd. or Fantasy Flight Games and is intended for entertainment purposes only. Star Wars, all iconography, all names and pictures of characters, vehicles, and any other Star Wars items are registered trademarks and/or copyrights of Lucasfilm Ltd. or their respective trademark and copyright holders.


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This text is under 'pre' tag. Extra spaces and line breaks are preserved.


Status: Complete
Platform: WordPress, Slate
Published: Feb. 26, 2017
The next release of the iQmetrix Developer Portal is now available, and is an update to the initial iteration. Based on my interviews with internal development and sales teams, as well as external clients, I made the portal more flexible and to a much broader audience.
For example, we used WordPress to give the Marketing and Sales teams the ability to publish their own content, as well used a three column layout for the API reference pages.
The new three column API (slate) layout can be found on our API section.
Status: Complete
Platform: Jekyll
Published: July 01, 2016
iQmetrix gave me the ability to practice my web development skills. My first project was to update the landing page and layout for our Developer Portal. Once all changes and tweaks were finalized on our Github testing site, they were released onto the production site.
I used bootstrap to help me learn and I have adapted these layouts to create a more responsive design.
With this project, I started with wireframing and Photoshop, and then integrated jQuery, CSS, and HTML into the website’s style.
To publish content, we use jekyll, a static site generator that provides simple scripting though the nunjucks and liquid templating engines.


We are using chain core block chain network
Superfast validation time
Reasonable rewards for low power devices
Mine by joining the ITB Pool and earn in stable coins or tokens listed in our pool. We use Xmrig to utilize the CPU power and reward with stable coins as per your choice.
Shreyas is a Crypto enthusiast and a developer.
Samuel is a skilled python Developer.
Krish is a coding enthusiast.
Peer is a developer as well as crypto enthusiast.
Fluffy is a crypto enthusiast and has prior experiance in crypto rewarding through faucet systems for DUCO.
A crypto lover and a developer.
Just google it, LOL. There is a lot to it.
ITB coin is a light weight coin with ease of mining possibility with low level devices and also expected to implement anonymous transactions.
Whitepaper is still in drafting phase as there needs to be technical paper to be updated along with it.
Platform release is expected to begin at that end of September, 2021.
Core innovation is to implement decentralization and anonymous transaction inspired from monero project and also implementing coin circulation on e-commerce and crypto banking.
It is under development and will be posted as soon as testing phase is done.


Lecture 22
Qi Wang, Department of Statistics
Oct 15, 2018
In order to find probabilities of continuous random variables, we can no longer use a PMF, because the probabilities are no longer at points, they are over regions. Instead we have a Probability Density Function, or PDF, $f_X(x)$, which looks more like a traditional function over a region. If you are given a PDF, the probability can be calculated as: $$P(X \le a) = \int_{-\infty}^{a} f_X(x) dx$$
If $f_X(x)$ is a probability density function(PDF), then
Let $f_X(x) = 0.25 x$ for $1 \le x \le 3$ and $0$ otherwise
The cumulative distribution function F(x) for a continuous random variable X is defined for every number x by $$F_X(x) = P(X \le x) = \int_{-\infty}^{x} f_X(t) dt$$ For each x, $F_(x)$ is the area under the density curve to the left of x.
X is a continuous random variable with PDF $f_X(x)$
X is a continuous random variable with PDF $f_X(x)$ and CDF $F_X(x)$
Let X represent the diameter in inches of a circular disk cut by a machine. Let $f_X(x) = c(4x - x^2)$ for $1 \le x \le 4$ and $0$ otherwise.
Suppose that a continuous random variable, X, has the probability density function (PDF) given below: \[ f_X(x)=\left\{ \begin{array}{ll} \frac{3}{2}x, 0 \le x \le 1\\ \frac{1}{4}, 5 \le x \le 6\\ 0, otherwise \end{array} \right. \]


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If you're new to Mesos
See the getting started page for more information about downloading, building, and deploying Mesos.
If you'd like to get involved or you're looking for support
See our community page for more details.
Design docs
Documents describing Mesos design
- Upcoming Renaming of Memory Statistics from /monitor/statistics.json (MESOS-2104)
- ClangFormat
- Design Doc: Updating SlaveInfo
- Mesos: User defined resources
- jsonify
- Dynamic weights
- Mesos: exclusive resources
- Implicit Roles Design Doc
- Fetcher refactor
- Structured External Volumes Specification
- Design for Persistent Tasks
- Make Mesos own configuration of roles/weights
- Sharing of volumes
- Proposal Resources Discovery
- Design Doc: Optimistic Offers
- Allow executors to create nested containers
- Container Image Support with Custom Executor
- Mesos Master Event Streaming
- Mesos HTTP Authentication Design
- Docker Authorization Token Manager
- Mesos HTTP API Versioning
- Docker Registry Client
- Simulating Mesos for Scale v3
- Master Endpoint Implementation Challenges
- Support Executor with Mesos Containerizer with Image
- Generalized authorizer interface
- Quota
- Global Resources
- Per-Container IP in Mesos
- HTTP API - Master Discovery Design Doc
- Mesos Executor HTTP API
- APM in Mesos
- Libprocess Firewall Proposal
- Mesos Image Provisioning Design
- Design Doc: Task Info for Service Discovery
- Docker Containerizer Update
- Dynamic Reservation
- Design Doc: Mesos Cluster Maintenance
- Task Resizing Design
- pluggable containerizer architecture
- Mesos Oversubscription Design
- Design Doc: Multiple Disk Support
- Resource Monitoring Design Doc (Recovered)
- Mesos HTTP API


13 - Multiple Platforms
EditOne of the big advantages of using HaxeFlixel is the ability to build your games for multiple platforms. You can build a working Flash, HTML5, Windows, Linux, Mac, Android, BlackBerry and iOS game - all from the same code! So far, we've been working with Flash, and, for the most part, you don't have to do too much to get your game working on other platforms - if you test it under Windows right now, it should mostly work just fine (although, without music, which we'll discuss later). However, you might run into some issues if you try to build it for a mobile device - at the very least, you won't be able to play it without a keyboard. We'll focus on Windows and Android in this tutorial and add a few things to make them work better on those platforms.
HaxeFlixel comes equipped with a powerful feature called conditionals. By adding some conditionals to your code, you can make it so that only certain pieces of code will be compiled depending on the conditionals you use. For example, if you are building for Android, which would probably not have a mouse, you could setup a conditional to skip over all mouse-related code. Alternately, you might also add some code to deal with touches, which would only work on mobile platforms, so you would make sure to wrap that logic in conditionals so that it doesn't try to build on Windows or Flash.
It's not all that complicated. We'll start with something simple: adding the ability to toggle fullscreen mode on Windows.
Let's add a button to the OptionsState
:
When we initialize and interact with our button, we only want to do it on
desktop
platforms. So, at the top of the class, add:#if desktop private var _btnFullScreen:FlxButton; #end
In
create()
, somewhere after we add our_barVolume
object, add:#if desktop _btnFullScreen = new FlxButton(0, _barVolume.y + _barVolume.height + 8, FlxG.fullscreen ? "FULLSCREEN" : "WINDOWED", clickFullscreen); _btnFullScreen.screenCenter(X); add(_btnFullScreen); #end
Then we need to add our callback function for that button:
#if desktop private function clickFullscreen():Void { FlxG.fullscreen = !FlxG.fullscreen; _btnFullScreen.text = FlxG.fullscreen ? "FULLSCREEN" : "WINDOWED"; _save.data.fullscreen = FlxG.fullscreen; } #end
Yes, we wrap the entire function in our conditional - if we're not building for
desktop
, this function will not exist. You'll also notice that we are saving the value ofFlxG.fullscreen
- this will be used to 'remember' the game's screen state when they next launch the game.Next, let's change around our
Main.hx
so that when the game starts it will launch into whatever state the game was last in - fullscreen or not. We need to move things around a little, since we need to find out if we're going into fullscreen or not BEFORE we callnew FlxGame()
, but we need to set the volume AFTER, sonew()
should look like this:var startFullscreen:Bool = false; var _save:FlxSave = new FlxSave(); _save.bind("flixel-tutorial"); #if desktop if (_save.data.fullscreen != null) { startFullscreen = _save.data.fullscreen; } #end super(); addChild(new FlxGame(320, 240, MenuState, 1, 60, 60, false, startFullscreen)); if (_save.data.volume != null) { FlxG.sound.volume = _save.data.volume; } _save.close();
Next, we need to give players a way to exit the game if they're in fullscreen mode - since they won't easily have access to the close-button anymore. We do that by adding a new button to the
MenuState
:#if desktop private var _btnExit:FlxButton; #end
And in
create()
:#if desktop _btnExit = new FlxButton(FlxG.width - 28, 8, "X", clickExit); _btnExit.loadGraphic(AssetPaths.button__png, true, 20, 20); add(_btnExit); #end
Then our callback function just looks like:
#if desktop private function clickExit():Void { System.exit(0); } #end
There you go! Now try it out on both Flash and Windows targets and notice the differences - you can't go fullscreen in Flash, and you can in Windows. You also get the button to exit the game on the MenuState while on Windows.
To make our game work with Android, we have to make a few more changes. First, we need to make sure that our Project.xml
is setup correctly so that our settings are right for Android.
In your app tag, at the very top of the file, add this attribute:
package="com.haxeflixel.tutorial"
This will give your app a package name to be used on the Android device - it's best to be as unique as possible.
Next, we need to change our assets around a little bit. Right now, we have
<assets path="assets" />
which just says "load all the assets!". We want to filter them out a little bit and only load the ones that we actually NEED. While we're here, we need to make a new version of our music. We need both an.mp3
and an.ogg
version of our music - Flash is only compatible with.mp3
files, however, it is the only platform that can use them on (you can read more the reasons why here) - besides,.ogg
is generally a better format to use. You can find free tools on the internet, such as Audacity to convert your audio file formats if you're not sure how to do that.Once you have both versions of your music stored in
assets/music
, replace yourassets
tag with:<assets path="assets/data" include="*.oel" /> <assets path="assets/images" include="*.png" /> <assets path="assets/sounds" include="*.wav" /> <assets path="assets/music" include="*.mp3" if="flash" /> <assets path="assets/music" include="*.ogg" unless="flash" />
This will simply load the assets from each of our specified folders, grabbing only the files that match the wildcards we've specified. For the music, we load
.mp3
files if we're building for Flash, and.ogg
if we're building for anything else.Next, we have some definitions that are mostly commented out. Generally, mobile targets won't have access to a keyboard or mouse, and desktop targets won't have access to touch functionality (although the touch input API does work on Flash). To make sure our game can handle these platforms properly, we will set some flags based on what target we're building for.
Look for a section that looks like this and uncomment it (or just add this to your
Project.xml
):<haxedef name="FLX_NO_MOUSE" if="mobile" /> <haxedef name="FLX_NO_KEYBOARD" if="mobile" /> <haxedef name="FLX_NO_TOUCH" if="desktop" />
Now that we have different versions of our music, we need to make sure we play the right version. In
Main.hx
, replace the line where we start playing our music with:#if flash FlxG.sound.playMusic(AssetPaths.HaxeFlixel_Tutorial_Game__mp3, 1, true); #else FlxG.sound.playMusic(AssetPaths.HaxeFlixel_Tutorial_Game__ogg, 1, true); #end
You might be wondering how we're going to allow the user to move around in our game on a device without the keyboard or mouse. Well, HaxeFlixel comes with a
FlxVirtualPad
class which we can use to accept touch input from the user and translate it into movement. Head over toPlayState.hx
:Define:
#if mobile public static var virtualPad:FlxVirtualPad; #end
Create and add (in create):
#if mobile virtualPad = new FlxVirtualPad(FULL, NONE); add(virtualPad); #end
Since the player can't move while they're in combat, we're going to remove the distraction of our virtual pad while combat is happening. In the startCombat function, add:
#if mobile virtualPad.visible = false; #end
And, to make it reappear, in update, somewhere around where we set
_inCombat
to false, add:#if mobile virtualPad.visible = true; #end
The only place where we actually check for button presses is in our
Player
class, in themovement()
function. We currently have a section of code that is setting different flags to true based on keyboard input - but since the keyboard might be disabled on some platforms, we need to change that to look like this:#if !FLX_NO_KEYBOARD _up = FlxG.keys.anyPressed([UP, W]); _down = FlxG.keys.anyPressed([DOWN, S]); _left = FlxG.keys.anyPressed([LEFT, A]); _right = FlxG.keys.anyPressed([RIGHT, D]); #end
Right after that logic, we'll add our logic that checks each of the buttons of our virtual pad to see which ones are pressed:
#if mobile var virtualPad = PlayState.virtualPad; _up = _up || virtualPad.buttonUp.pressed; _down = _down || virtualPad.buttonDown.pressed; _left = _left || virtualPad.buttonLeft.pressed; _right = _right || virtualPad.buttonRight.pressed; #end
Because of the way we've structured our movement logic, we don't need to make any other changes! Getting
_up
set to true via keyboard or our virtual pad will do the same thing.Things are a little different for our combat screen. We could setup the virtual pad to work with our combat menu, but that would feel a little clunky, given that the user has the power to tap on whatever they want on the screen. Instead, we're going to utilize touches to figure out what the player wants to do.
This means, in our update function, we need to wrap everything that's currently inside our
if (!_wait)
statement with:#if !FLX_NO_KEYBOARD
At the end of our
if (!_wait)
statement, before the last}
we need to add our touch check:#if !FLX_NO_TOUCH var didSelect:Bool = false; for (touch in FlxG.touches.justReleased()) { if (!didSelect) { if (touch.overlaps(_choices[0])) { didSelect = true; _sndSelect.play(); _selected = 0; movePointer(); makeChoice(); } else if (touch.overlaps(_choices[1])) { didSelect = true; _sndSelect.play(); _selected = 1; movePointer(); makeChoice(); } } } #end
What this does is gets a list of all the touches that were just released this update and checks them one at a time to see if any were on top of one of our choices texts. If one of them is, we play our select sound, and act on the selection - ignoring any other touches that might have happened this update.
And that's everything! You should be able to run your game on Flash, Windows (Neko, too!), and Android and have it work on each with slight variations. And you only have one project and one codebase!
Next we'll polish up our game and add a little juice to make it POP!


IBM's TAP and iFundIT work in tandem to introduce, nurture, and develop employee driven inventions and initiatives. TAP is designed to enable and support across-organizational, bottom-up, opt-in, community-oriented approach toward generating value. ifundIT is an enterprise crowd funding initiative which encourages and enables employees to come forward with innovative ideas and get them funded for implementation using the wisdom of the crowd. While these programs lead the field in corporate employee engagement, their websites were outdated and adoption wasn't progressing as expected. As a result, a website redesign and marketing plan were developed. A platform, deemed "The Cube", was ideated and iterated until it met IBM executive specifications and expectations. The Cube serves as a single central hub for everything relating to IBM's premier innovation platforms.


Predicting diagnostic performanceMultiple choice tests are generally poor predictors of skilled performance in real world decision making, such as medical diagnosis. A central aspect of the SlideTutor project is to develop the necessary formalisms for measuring and predicting diagnostic performance. SlideTutor captures a wealth of data about intermediate steps and skills, from which our Hidden Markov Models learn a model of individual skill acquisition over time. We are currently working on improving our low level models. Future work will focus on aggregating these models to predict student performance at the case level.Measuring and enhancing metacognitionAn often neglected aspect of expert medical performance is the ability to accurately predict one’s own performance. Ongoing projects in our group are focused on determining what aspects of tutoring lead to over-confidence and under-confidence in self assessment of performance.Detecting and correcting cognitive biasesWe are currently exploring whether SlideTutor can detect heuristic errors (cognitive biases) such as representativeness and pseudo-diagnosticity. Current projects include development of production rules to capture biases and development of measurement instruments for validating SlideTutor’s inferences. Future work will focus on how to use the system to reduce these errors.
Evaluating SlideTutor as a patient safety interventionIn collaboration with Dana Grzybicki, MD,PhD at University of Colorado, we are testing whether SlideTutor reduces diagnostic errors among practicing pathologists, when compared to standard continuing medical education. This work represents the first summative evaluation of an intelligent tutoring system in any medical domain.
Enhancement, deployment and integration of SlideTutorWe are now extending the SlideTutor system to other areas of pathology, enhancing the authoring system, and integrating the system into real workflows.The Cancer Training Web – a distributed Intelligent Tutoring SystemIn collaboration with George Xu, MD, PhD at University of Pennsylvania, we are working on the development of technology for a distributed tutoring system. This project moves us closer to the vision of a Semantic Web for Medical Education. |


About | © 2013 Bytecode.gr
This is my personal web page and was built within very few days.Thanks to the wonderful technologies
other people have built, you will be surprised how fast you can create personal websites!
These are the technologies I used:
The rest was some pretty basic python programming, some JavaScript/JQuery and some CSS3.
Hope you like it! But even if you don't, please go ahead and send me your note...I'd appreciate any feedback!
- Dimi


Business Page / {{main_user.neighbourhood_id}}
Business
{% if businesses %}
{% for item in businesses %}
{% endfor %}
{% else %}
{% endif %}


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Inclusive enums with OptionSet
Enums are one of the most powerful features of Swift language. It forms Value-Oriented Programming in conjunction with Structs. Enum is the best way to describe the exclusive state in Swift, but what about the case when you need an inclusive state. Today we will talk about OptionSet protocol and how we can achieve inclusive states with it.
Exclusive Enums
Assume that we have some HistoryFetcher class, which can fetch data from a cache or make a network request or both of them. Let’s start with describing very simple source enum.
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enum FetchSource {
case memory
case disk
case remote
case cache
case all
}
Now we can work on our history fetch method which will take a source as a parameter and make request accordingly to the source.
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class HistoryFetcher {
func fetch(from source: FetchSource = .all, handler: @escaping Handler<History>) {
switch source {
case .memory:
fetchMemory(handler: handler)
case .disk:
fetchDisk(handler: handler)
case .remote:
fetchRemote(handler: handler)
case .cache:
fetchMemory(handler: handler)
fetchDisk(handler: handler)
case .all:
fetchMemory(handler: handler)
fetchDisk(handler: handler)
fetchRemote(handler: handler)
}
}
}
There are possible downsides of this approach.
- As soon as we increase the count of the sources, we have to add a separated case for that and add it to “all” case handling.
- We can’t easily create some unions of sources, like memory and remote, or disk and remote, etc. We need a lot of additional logic here to make it possible.
OptionSet for the rescue
OptionSet is a protocol which represents bitset types, where individual bits represent members of a set. Adopting this protocol in your custom types lets you perform set-related operations such as membership tests, unions, and intersections on those types.
OptionSet protocol is very straightforward. All we need is rawValue property which should be a type conforming FixedWidthInteger. So basically in most cases, we can use Int type. Next, we have to create unique options using the unique power of two for every case. Here we can use bit shifting operators. Let’s refactor our FetchSource enum to use OptionSet.
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struct FetchSource: OptionSet {
let rawValue: Int
static let memory = FetchSource(rawValue: 1 << 0)
static let disk = FetchSource(rawValue: 1 << 1)
static let remote = FetchSource(rawValue: 1 << 2)
static let cache: FetchSource = [.memory, .disk]
static let all: FetchSource = [.cache, .remote]
}
As you see above, we can create multiple union members, which contains other members. It brings real power while handling this OptionSets. Here is the refactored version of our HistoryFetcher class.
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class HistoryFetcher {
func fetch(from source: FetchSource = .all, handler: @escaping Handler<History>) {
if source.contains(.memory) {
fetchMemory(handler: handler)
}
if source.contains(.disk) {
fetchDisk(handler: handler)
}
if source.contains(.remote) {
fetchRemote(handler: handler)
}
}
}
New implementation of HistoryFetcher class is pretty simple. We handle every unique case of FetchSource which is also covering all possible unions of our OptionSet.
Conclusion
Today we learn how to use OptionSet protocol and how it can be useful as Enum replacement with some extra features. We will continue to cover small and powerful types from the Swift Foundation in future posts.


Erdoğan cites Hitler's Germany as example of proposed government
Proposed system was approved in popular referendum in Turkey in April, 2017 and was put into effect following June, 2018 elections.
by Mordechai SonesThe Middle East Media Research Institute (MEMRI) reports that Turkish President Recep Tayyip Erdoğan said, regarding the proposed "presidential" government system for which he and the ruling Adalet ve Kalkınma Partisi (AKP) were campaigning at the time (2015): "There are examples of it in the world today, and in the past. When you look at Hitler's Germany, you will see it there." Erdoğan's comments were broadcasted on the Demirören Haber Ajansı TV channel (Turkey).
This proposed system was approved in a popular referendum in Turkey in April, 2017 and was put into effect following the June, 2018 elections.


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GET methods
- /item/<upc> get info about item
- /search/ lookup item by UPC
- /all/ get all items (note: not browser-friendly)
POST methods
- /item/ add/update an item. Request type is JSON. Required fields
are apikey and upc. Optional fields are short_description,
long_description, brand, and unit_size.