This Privacy Statement (“Statement”) describes the personal data that Nuance collects, how we use it, and when we share it, as we interact with you, deliver our products and services, and conduct our business operations.
This Statement applies to Nuance Communications, Inc., its affiliates and any wholly owned subsidiaries worldwide, referred to in this Statement as “Nuance.” When we refer to Nuance products, we mean all Nuance products and services.
For the purposes of applicable data privacy legislation, the Nuance affiliate or subsidiary responsible for the collection and use of your personal data is either the affiliate or subsidiary with which you contract or engage, or the affiliate or subsidiary located in the country in which you reside. You may contact us at<EMAIL_ADDRESS>if you wish to confirm the identity of the responsible Nuance affiliate.
Nuance collects personal data when we deliver our products, conduct marketing, and run our business operations. The personal data we collect varies based upon whether the data is collected (i) through our websites or applications, including www.nuance.com and shop.nuance.com and their local variations (“Sites”) or (ii) through our products and services, including but not limited to our software, support services, voice recognition technology, and medical information products (“Products”).
We may collect personal data directly in the following situations:
Through our Products, we may collect personal data directly in the following situations:
Nuance may collect personal data indirectly in certain situations, in particular:
Nuance and its partners use cookies and similar tracking tools to distinguish you from other users as described in our Cookie statement.
General Business Operations
We use contact information to market, sell, and service Nuance Products, subject to your consent where required by law. We allow recipients of marketing messages and collateral to opt out of receiving further communications from Nuance at any time without detriment.
We use your financial or payment information, and your contact details, to support, establish, and conduct customer relationships as necessary for the performance of our terms of service with you (including, for example, completing purchase transactions, fulfillment of an order, order confirmations, responding to requests for information about products and services, and the provision of purchased products and services). If you fail to provide the personal data we need, we may be unable to complete your transaction.
We use personal data from employment applications where necessary to support our legitimate interest in processing your application and to contact you if future opportunities arise.
We use personal data of individuals associated with proposed resellers and distributors to conduct reference and background checks ahead of entering into a contract and as necessary for compliance with legal obligations to which we are subject.
Data Processed Within Our Products
We use the personal data that is processed within our Products, such as voice data within voice recognition products, medical data within medical data products, personal data processed in communications products, and any personal data contained within product usage data we collect, to deliver our Products under applicable terms and for our legitimate interests in tuning, maintaining, enhancing, and developing Products. We never use this data, referred to as “Product Personal Data,” for marketing purposes and we never sell or transfer your data to third parties for the third party’s marketing purposes.
We use aggregated, non-identifying, electronic data collected from use of our Sites and Products to operate, analyze, improve, and develop our Sites and Products. This information is not used to inform decisions about specific individuals; rather, it is processed to understand how different categories of users interact with our Sites and Products so that we can consistently improve our Products.
We may share Product Personal Data in the following situations:
We may share personal data with our affiliates, subsidiaries, resellers, suppliers, sub-contractors, and distributors, and with vendors acting on our and their behalf, to service our customers and perform any contract we enter with you (including, for example, with resellers who support our management of potential clients and vendors who conduct transcription in connection with our products and services).
We may share aggregated, anonymous, or non-identifiable electronic data with our affiliates and with vendors acting on our behalf.
We may share personal data derived from Site usage (excluding Product Personal Data), with analytics and search engine providers that assist us in the improvement of our Sites, subject to the cookie section of this Privacy Statement. Our Sites may use Google Analytics. The way Google collects and processes data when delivering Google Analytics is described here: www.google.com/policies/privacy/partners/.
We may share personal data from employment applications with vendors acting on our behalf who help us in recruitment, background check and human resources matters.
If we share your personal data (including Product Personal Data) with affiliates or with vendors acting on our behalf, we do so under binding agreements that require the third party to use and protect the personal data in accordance with the principles described in this Privacy Statement. These third parties are authorized to use your personal data only as necessary to provide these services to us.
We may also share personal data to comply with law and legal process, to respond to governmental inquiries and lawful requests from by public authorities (including to meet national security or law enforcement requirements), and to protect life, property, or the security of Nuance or its customers. If Nuance enters any merger, acquisition, or asset sale of all or any part of its business, personal data held by Nuance may be transferred to a buyer or successor entity.
You can change your preferences to opt out of marketing communications at any time by contacting us at<EMAIL_ADDRESS>Alternatively, please follow the opt-out instructions in the relevant communication. If you opt out, we will retain your email address to confirm that we do not send you further communications.
If you have submitted an employment application to Nuance or if your personal data has been collected by Nuance to review a proposed reseller or distributor relationship, you may contact us at<EMAIL_ADDRESS>to request deletion of your data. We will respond to your request within a reasonable timeframe.
If you wish to access, correct, or request deletion your Product Personal Data, you may contact us at<EMAIL_ADDRESS>Nuance generally processes Product Personal Data on behalf of our healthcare, enterprise, and corporate customers. If you contact us, we may direct your inquiry to our customer on whose behalf the Product Personal Data is being processed. We will make reasonable efforts to delete your Product Personal Data upon your request within a reasonable timeframe. Nuance may refuse your request to access, request or delete Product Personal Data where entitled to do so under applicable law.
If you have submitted Product Personal Data to Nuance using your own user account which allows you to control your own data, you may delete the data you submitted by logging into your account and following the guidelines in the help system.
Nuance operates in over 35 countries. We may transfer personal data across international borders and may process personal data in jurisdictions other than the jurisdiction of original collection.
We may transfer personal data that we collect to other Nuance affiliates or other companies performing support functions on our behalf (each as described above) based in other countries including to the United States, India or the Philippines or other countries outside the European Economic Area or your country of residence and this personal data may be stored and/or processed in such countries.
Whether your personal data is processed within your country of residence or beyond, we will take steps to ensure that your data is subject to appropriate safeguards required of us under the Privacy Statement, applicable data protection laws, and appropriate legally recognized data transfer adequacy mechanisms. Personal data that is transferred outside your country of residence may be subject to lawful access by courts, law enforcement and other governmental authorities in accordance with the laws of the foreign jurisdiction.
Nuance participates in and has certified its compliance with the EU-U.S. Privacy Shield Framework and the Swiss-U.S. Privacy Shield Framework regarding the collection, use, and retention of personal data transferred from the European Union, the United Kingdom and Switzerland to the United States. We are committed to subjecting all personal data received from European Union (EU) member countries, the United Kingdom, and Switzerland, respectively, in reliance on each Privacy Shield Framework, to the Framework’s applicable Principles. To learn more about the Privacy Shield Frameworks, and to view our certification, visit the U.S. Department of Commerce’s Privacy Shield List.
Nuance is responsible for the processing of personal data it receives, under each Privacy Shield Framework, and subsequently transfers to a third party acting as an agent on its behalf. Nuance complies with the Privacy Shield Principles for all onward transfers of personal data from the EU, the United Kingdom, and Switzerland, including the onward transfer liability provisions.
With respect to personal data received or transferred pursuant to the Privacy Shield Framework, Nuance is subject to the regulatory enforcement powers of the U.S. Federal Trade Commission. In certain situations, we may be required to disclose personal data in response to lawful requests by public authorities, including to meet national security or law enforcement requirements.
If you have an unresolved privacy or data use concern that we have not addressed satisfactorily, please contact our U.S.-based third party dispute resolution provider (free of charge) at https://feedback-form.truste.com/watchdog/request.
Under certain conditions, more fully described on the Privacy Shield website, you may be entitled to invoke binding arbitration when other dispute resolution procedures have been exhausted.
We follow generally accepted standards to protect the personal data submitted to us, both during transmission and once it is received. Information you provide to us is stored on our secure servers. Any payment transactions will be encrypted using current PCI-DSS standards. If Nuance has issued you a password, you are responsible for keeping the password confidential. If you have any questions about the security of your personal data, you can contact us at<EMAIL_ADDRESS>We retain personal data to the extent necessary to provide Products to our customers, employees, and prospective employees. Generally, we retain personal data for as long as you remain an active customer or user of our Sites and Services and for 3 years afterwards, or otherwise as required for our business operations or by applicable laws. Longer retention may be necessary under contractual terms with the data controller for whom we provide services, for fraud prevention, to identify technical problems, or to resolve legal proceedings. Images added to PowerShare are automatically deleted after 45 days. Children's data may be deleted promptly after we have processed it for our customer.
We may retain non-personally identifiable aggregate information beyond this time for research purposes and to help us improve and further develop our Products. You cannot be identified from aggregate information retained or used for these purposes. Any record of a stated objection by you to receiving marketing communications will be retained by us so that we respect your wishes by not contacting you further.
If a Nuance customer puts Nuance voice recognition Product technology in a customer product, Nuance may receive speech data from product users to provide voice recognition to the user. This is a function of how Nuance’s voice technology works. This means that if the user is under the age of 13, Nuance may receive personal data from children under the age of 13. It is the responsibility of the Nuance customer to obtain any consents required under applicable law, including under the Children’s Online Privacy Protection Act and relevant data protection laws, for the collection of such personal data.
Except as described in the preceding paragraph, Nuance does not knowingly collect personal data from children under the age of 13. Nuance has adopted a policy that Nuance will not provide hosted services to primarily child-directed websites and online services. No child under 13 should submit personal data to Nuance. If you become aware that a child under the age of 13 has submitted personal data to Nuance, contact us at<EMAIL_ADDRESS>and we will promptly delete the data.
You may have the right under applicable laws in certain circumstances to:
Nuance never sells or transfers your data to third parties for the third party’s marketing purposes. You can object to receiving further marketing from Nuance at any time without detriment.
Nuance partners with a third party to display advertising on our website or to manage our advertising on other sites. Our third-party partner may use cookies and similar tracking tools in order to provide you advertising based upon your browsing activities and interests. If you wish to opt out of interest-based advertising click here [or if located in the European Union click here]. Please note you will continue to receive generic ads.
You can also exercise the rights listed above, or write to us with any complaints, at any time by contacting us, specifying the nature of your request, at:
<EMAIL_ADDRESS>or by mail (Worldwide) at:
Data Protection Officer
Nuance Communications, Inc.
1 Wayside Road
Burlington MA 01803
USA
Or by contacting our representative in the EU at:
Data Protection Officer
Nuance Communications Ireland, Ltd
20 Merrion Road
Ballsbridge, Dublin 4
IRELAND
If your request or concern is not satisfactorily resolved by us, you may approach your local data protection authority.
This Privacy Statement does not cover Nuance’s collection of personal data from employees and contingent workers, which is described in a separate HR Privacy Statement made available to Nuance personnel.
We may update this Privacy Statement from time to time by publishing an updated version on Nuance's Sites. Each updated version will include the date the statement was last updated. Please review the latest version of this Privacy Statement periodically to keep current with Nuance’s use of personal data. If we make material changes in the way Nuance uses or shares personal data, we will publish notice on our Sites and notify you by email to tell you of the proposed change. Any such material changes will only apply to personal data collected after the revised Privacy Statement takes effect.
Updated: March 6th, 2019.


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Variations on a theme
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Dynamic - ArrayList
Click to add more particles


Our clients are our greatest value. At the moment, our services have benefited from more than 310000 travelers and about 400 people trust us their daily travel. We are proud that our clients recommend us to their friends, relatives and acquaintances. We, in turn, are doing our utmost to make your rest positive and memorable, try to provide everything necessary to make you feel confident during the journey
Thanks to many years of experience, high professionalism of employees and mutual respect policy vis-à-vis clients and partners, the company has earned the trust and credibility among travel agencies, and private clients
Almost everyone calls Mount Everest "the highest mountain in the world," and climbers from everywhere travel to Everest hoping to earn the distinction of climbing the "World's Highest."
Mount Everest is called the world's highest mountain because it has the "highest elevation above sea level."We could also say that it has the "highest altitude." The peak of Mount Everest is 8,850 meters (29,035 feet) above sea level. No other mountain on Earth has a higher altitude. However, some mountains might be considered "taller" (with taller being "the total vertical distance between their base and their summit").
My partner and I just returned from our European vacation planned by Annie at The Travel Agency and we could not be happier! It was a 25 day trip through Italy, France, and Spain...
My family and I have been working with The Travel Agency in excess of 20 years in both business and personal travel. She has arranged trips that have allowed me to achieve my dreams of mountain climbing and summiting high mountain peaks in both the Antarctic and Ukraine
Thanks to you, we had a wonderful experience in Peru. The country was beautiful, the people gracious, a memory of a lifetime. Thanks to you and your connections, we have no regrets about our trip and look forward to working with you on our next adventure!
Greece
The cradle of ancient civilization, today's Greece is one of the most popular destinations among tourists..
Viet Nam
Viet Nam is notable for the beautiful nature, ancient temple complexes and hotels with good service and low prices...
Madagaskar
The Republic of Madagaskár is an island nation in the Indian Ocean, located on the island of Madagascar...
Seyshelles
The Republic of Seychelles is an island nation located in the Seychelles and Amirant...
Newsletter


nips nips2005 nips2005-176 nips2005-176-reference knowledge-graph by maker-knowledge-mining
Source: pdf
Author: Brian Taba, Kwabena Boahen
Abstract: We demonstrate the ﬁrst fully hardware implementation of retinotopic self-organization, from photon transduction to neural map formation. A silicon retina transduces patterned illumination into correlated spike trains that drive a population of silicon growth cones to automatically wire a topographic mapping by migrating toward sources of a diffusible guidance cue that is released by postsynaptic spikes. We varied the pattern of illumination to steer growth cones projected by different retinal ganglion cell types to self-organize segregated or coordinated retinotopic maps. 1
[1] T. Kohonen (1982), “Self-organized formation of topologically correct feature maps,” Biol. Cybernetics, vol. 43, no. 1, pp. 59-69.
[2] W.-C. Fang, B.J. Sheu, O.T.-C. Chen, and J. Choi (1992), “A VLSI neural processor for image data compression using self-organization networks,” IEEE Trans. Neural Networks, vol. 3, no. 3, pp. 506-518.
[3] S. Rovetta and R. Zunino (1999), “Efﬁcient training of neural gas vector quantizers with analog circuit implementation,” IEEE Trans. Circ. & Sys. II, vol. 46, no. 6, pp. 688-698.
[4] E.W. Dent and F.B. Gertler (2003), “Cytoskeletal dynamics and transport in growth cone mobility and axon guidance,” Neuron, vol. 40, pp. 209-227.
[5] B. Taba and K. Boahen (2003), “Topographic map formation by silicon growth cones,” in: Advances in Neural Information Processing Systems 15 (MIT Press, Cambridge, eds. S. Becker, S. Thrun, and K. Obermayer), pp. 1163-1170.
[6] S.Y.M. Lam, B.E. Shi, and K.A. Boahen (2005), “Self-organized cortical map formation by guiding connections,” Proc. 2005 IEEE Int. Symp. Circ. & Sys., in press.
[7] K.A. Zaghloul and K. Boahen (2004), “Optic nerve signals in a neuromorphic chip I: Outer and inner retina models,” IEEE Trans. Bio-Med. Eng., vol. 51, no. 4, pp. 657-666.
[8] K. Boahen (2000), “Point-to-point connectivity between neuromorphic chips using addressevents,” IEEE Trans. Circ. & Sys. II, vol. 47, pp. 416-434.
[9] K. Miller (1994), “A model for the development of simple cell receptive ﬁelds and the ordered arrangement of orientation columns through activity-dependent competition between on- and off-center inputs,” J. Neurosci., vol. 14, no. 1, pp. 409-441.
[10] D. Ringach (2004), “Haphazard wiring of simple receptive ﬁelds and orientation columns in visual cortex,” J. Neurophys., vol. 92, no. 1, pp. 468-476.
[11] T. Elliott and J. Kramer (2002), “Coupling an aVLSI neuromorphic vision chip to a neurotrophic model of synaptic plasticity: the development of topography,” Neural Comp., vol. 14, no. 10, pp. 2353-2370.


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:: com :: sun :: star :: script ::
|
| struct InvocationInfo |
|
- Description
- This struct is used to specify information about object members
(methods or properties) accessed via XInvocation, such as names,
types, or parameters.
|
| Elements' Summary |
| aName |
Name of the method or property.
|
| eMemberType |
Kind of the member (method or property).
|
| PropertyAttribute |
Only for property members:
This field may contain zero or more constants of the
::com::sun::star::beans::PropertyAttribute
constants group. It is not guaranteed that all necessary
constants are set to describe the property completely,
but a flag will only be set, if the corresponding charac-
teristic really exists. Example: If the READONLY flag
is set, the property is readonly. If it isn't set, the
property nevertheless can be readonly.
For methods this field is irrelevant and is set to 0.
|
| aType |
Type of the member, for methods the return type
|
| aParamTypes |
Types method parameters, for properties this sequence is empty
|
| aParamModes |
Mode of method parameters (IN, OUT, INOUT),
for properties this sequence is empty.
|
| Elements' Details |
aName
string aName;
- Description
- Name of the method or property.
|
|
eMemberType
MemberType eMemberType;
- Description
- Kind of the member (method or property).
|
|
PropertyAttribute
short PropertyAttribute;
- Description
- Only for property members:
This field may contain zero or more constants of the
::com::sun::star::beans::PropertyAttribute
constants group. It is not guaranteed that all necessary
constants are set to describe the property completely,
but a flag will only be set, if the corresponding charac-
teristic really exists. Example: If the READONLY flag
is set, the property is readonly. If it isn't set, the
property nevertheless can be readonly.
For methods this field is irrelevant and is set to 0.
|
|
aType
type aType;
- Description
- Type of the member, for methods the return type
|
|
aParamTypes
sequence< type > aParamTypes;
- Description
- Types method parameters, for properties this sequence is empty
|
|
aParamModes
sequence< ::com::sun::star::reflection::ParamMode > aParamModes;
- Description
- Mode of method parameters (IN, OUT, INOUT),
for properties this sequence is empty.
|
|
Top of Page
Copyright © 2013, The Apache Software Foundation, Licensed under the Apache License, Version 2.0. Apache, the Apache feather logo, Apache OpenOffice and OpenOffice.org are trademarks of The Apache Software Foundation. Other names may be trademarks of their respective owners.


Conducted research and data analysis to enhance phishing detection techniques.
Engineered a Deep Learning model using Tensorflow for identifying phishing websites through image scanning.
Built image indexing for a database of known websites utilizing Google ScaNN (Scalable Nearest Neighbors).
Achieved 88.67% prediction accuracy in current tests with a speed of 0.17s per test in the current model.
Also serving as a Teaching Assistant for the CS department, facilitating office hours and leading discussions and labs.
Amdocs
Sept 2021 - July 2022
Software Developer
Pune, India
Automated deployment and configuration management reducing deployment time by 70%.
Orchestrated Docker containers in Kubernetes for scalability, redundancy and disaster recovery.
Maintained Continuous Integration and Delivery pipelines using GitLab and Jenkins for faster release cycles.
Collaborated with cross-functional teams to troubleshoot and resolve production issues, reducing downtime by 40%.
Experienced with cloud platforms AWS, Azure and Google Cloud, including services such as EC2, S3, RDS, and VPC.
Implemented Git branching strategies and code review processes to ensure high code quality and team collaboration.
Deloitte
Jan 2020 - Sept 2021
DC Analyst
Mumbai, India
Collaborated with cross-functional client teams to build scalable data-driven solution for Oregon IE Healthcare System.
Designed and automated a testing framework that increased end-to-end testing efficiency by 150%.
Built and managed continuous integration and delivery pipelines with Jenkins and Git, resulting in automated and
streamlined application deployments in Azure Virtual Private Cloud.
Worked closely with different teams to optimize performance, troubleshoot issues, and implement new features.
Managed infrastructure costs, optimizing usage and implementing cost-saving, resulting in a 20% reduction in spend.
Utilized a regular tech stack including Azure, Docker, Jenkins, GitLab, IAM, Security Groups, Python, Bash.


Files CCore/inc/Cmp.h CCore/src/Cmp.cpp
Ordering is the one of the most important concept in the software world. CCore supports and utilizes the 3-way comparison. If you do compare two elements of the linear ordered set, then there are 3 possible outcomes: less, equal and greater. Pitiful (and shameful), but there is no a natural support for the 3-way comparison in the language. So the following helper entities are used for it.
enum CmpResult is used to represent an outcome of the 3-way comparison.
enum CmpResult { CmpLess = -1, CmpEqual = 0, CmpGreater = 1 }; inline CmpResult operator - (CmpResult cmp) { return CmpResult(-int(cmp)); } const char * GetTextDesc(CmpResult cmp);
The function LessCmp() can be used for the 3-way comparison of objects of types with defined operator <. It covers all basic integral types.
template <class T>
CmpResult LessCmp(const T &a,const T &b)
{
return (a<b)?CmpLess:( (b<a)?CmpGreater:CmpEqual );
}
To compare objects use the function Cmp(). If the destined type is a class type with the defined method objCmp(), then Cmp() calls this method, otherwise it calls LessCmp().
template <class T>
CmpResult Cmp(const T &a,const T &b);
Use the function AlphaCmp() to perform the alphabetical comparison:
struct S { A a; B b; C c; // cmp objects CmpResult objCmp(const S &obj) const { return AlphaCmp(a,obj.a,b,obj.b,c,obj.c); } };
The function AlphaCmp() expects any number of pairs of arguments:
CmpResult AlphaCmp(const T1 &a1,const T1 &b1,const T2 &a2,const T2 &b2,...,const Tn &an,const Tn &bn);
As usual, you may specialize the struct CmpAdapters to implement the 3-way comparison of a type:
namespace N { class C { .... }; } // namespace N namespace CCore { template<> struct CmpAdapters<false,N::C> { static CmpResult Cmp(const N::C &a,const N::C &b) { .... } }; } // namespace CCore
Use the function RangeCmp() or RangeLess() to perform the alphabetical comparison of two ranges of objects:
template <class T> CmpResult RangeCmp(const T *a,const T *b,ulen count); template <class T> CmpResult RangeCmp(PtrLen<T> a,PtrLen<T> b); template <class T> bool RangeLess(PtrLen<T> a,PtrLen<T> b);
There are also "by" variants of these functions. These variants use the given functor by to compare objects: to compare objects a and b they do compare by(a) and by(b).
template <class T,class Func> CmpResult RangeCmpBy(const T *a,const T *b,ulen count,Func by); template <class T,class Func> CmpResult RangeCmpBy(PtrLen<T> a,PtrLen<T> b,Func by); template <class T,class Func> bool RangeLessBy(PtrLen<T> a,PtrLen<T> b,Func by);
Use the functions StrCmp() or StrLess() to compare strings:
CmpResult StrCmp(StrLen a,StrLen b); bool StrLess(StrLen a,StrLen b);
There are two Property Type classes LessComparable and CmpComparable:
/* struct LessComparable<T> */ template <class T> struct LessComparable { friend bool operator > (const T &a,const T &b) { return b<a; } friend bool operator <= (const T &a,const T &b) { return !(b<a); } friend bool operator >= (const T &a,const T &b) { return !(a<b); } friend bool operator == (const T &a,const T &b) { return !( a<b || b<a ); } friend bool operator != (const T &a,const T &b) { return ( a<b || b<a ); } }; /* struct CmpComparable<T> */ template <class T> struct CmpComparable { friend bool operator < (const T &a,const T &b) { return a.objCmp(b)<0; } friend bool operator > (const T &a,const T &b) { return a.objCmp(b)>0; } friend bool operator <= (const T &a,const T &b) { return a.objCmp(b)<=0; } friend bool operator >= (const T &a,const T &b) { return a.objCmp(b)>=0; } friend bool operator == (const T &a,const T &b) { return a.objCmp(b)==0; } friend bool operator != (const T &a,const T &b) { return a.objCmp(b)!=0; } };
They can be used to simplify the implementation of the comparable classes:
class C : public CmpComparable<C> // provides all comparison operators for class C { public: // cmp objects CmpResult objCmp(const C &obj) const { .... } };
class C : public LessComparable<C> // provides all comparison operators for class C { public: bool operator < (const C &obj) const { .... } }; // Cmp() uses LessCmp() for this class
class C : public LessComparable<C> // provides all comparison operators for class C { public: bool operator < (const C &obj) const { .... } bool operator == (const C &obj) const { .... } // for efficiency bool operator != (const C &obj) const { .... } // for efficiency };
The answer is simple: it is more efficient and more usable in applications. 3-Way comparison has near the same cost for the simple types as 2-Way. In fact, the comparison command on the modern CPUs gives the complete answers how two integral values are ordered. So in practice only the absence of the language support for 3-Way or the lack of optimization capabilities of compilers makes 3-Way comparison of basic types is less efficient.
But once we compare combined types (usually using alphabetical ordering) we start winning:
bool Less(T1 a1,T1 b1,T2 a2,T2 b2) { if( a1<b1 ) { return true; } else { if( b1<a1 ) return false; // excessive double comparison of the same values return a2<b2; } } CmpResult Cmp(T1 a1,T1 b1,T2 a2,T2 b2) // more efficient, simple and clear code { if( CmpResult ret=Cmp(a1,b1) ) return ret; return Cmp(a2,b2); }
All usual comparison operations are simply derived from Cmp(). And, finally, many algorithms have advantage using 3-Way than 2-Way both in efficiency and simplicity.


Sysctl source validation
When a system distracts packets when the route for outbound traffic differs from the route of incoming traffic.
sysctl.conf
net.ipv4.conf.default.rp_filter = 0
net.ipv4.conf.<interface>.rp_filter = 0
net.ipv4.conf.all.rp_filter = 0
/proc
echo "0" > /proc/sys/net/ipv4/conf/default/rp_filter
echo "0" > /proc/sys/net/ipv4/conf/<interface>/rp_filter
echo "0" > /proc/sys/net/ipv4/conf/all/rp_filter
test config
hping <target> --spoof <spoofed_source> --udp -V -p <port> -d $(wc -m payload | awk '{print $1;}') -E payload


Whether a type is correctly assigned or not is a subjective judgment. The following are just some
general
criteria tips on how to evaluate the correctness of the predictions.
Note: mind that in several cases, more precise or abstract types do not exist.
If you are not sure
you can check the DBpedia
ontology hierarchy
Yes, totally
If you think the system nailed the prediction (e.g. predicting
Writer for a text describing Shakespeare)
Should be more precise
If you think there is a more concrete type for your description (e.g. the system predicted
Person but you expected something like
Soccer Player)
Should be more abstract
If you think there is a more generic type for your description (e.g. the system predicted
City
but you expected something like Place)
Somehow related
When you think the precition is neither more specific, nor more abstract, but still somehow
related to the type
you were expecting (e.g. the system predicted Valley,
but you were expecting Beach)
No, it is totally wrong
The system did a terrible job predicting, and the prediction is totally out of place (e.g. it
predicted
Musical Work and you expected an Spacecraft)


A scheduling and academic preparedness application developed for Android for college students. The app learns user preferences and behaviors and makes suggestions of study times that work best for the individual user.
In light of COVID-19, the topical choice for an embedded system is one that helps people stay safe and sanitized. The entire project was completed from the ground up; materials for the case of the device were 3D printed, a custom PCB was designed and ordered, and both hardware and software components were designed from scratch.
Because of it's nature, my work in Verilog has been very modular (pun definitely intended). The links below are two different projects I've worked on to further my skills in Verilog and RTL design. The first is a stack calculator that uses an FPGA as a source of input and output. The second is a matrix multiplier that works with a modified IEEE Floating point format.


| Maggie 's plan to have a baby on her own is derailed when she falls in love with John, a married man, destroying his volatile marriage to the brilliant and impossible Georgette. But one daughter and three years later, Maggie is out of love and in a quandary: what do you do when you suspect your man and his ex wife are actually perfect for each other? | |
| Genres: | Comedy, Drama, Romance |
| Director: | Rebecca Miller |
| Writer: | Rebecca Miller, Karen Rinaldi |
Cast: | Maggie - Greta Gerwig Blind Man - George Ashiotis Tony - Bill Hader Max - Monte Greene Guy - Travis Fimmel Beverly - Fredi Walker-Browne John - Ethan Hawke Felicia - Maya Rudolph Shakespearean Actor - Brendan Titley Shakespearean Actor's Lover - Stephen Lin Kliegler - Wallace Shawn Georgette - Julianne Moore Justine - Mina Sundwall Paul - Jackson Frazer Lily - Ida Rohatyn Al Benthwaithe - Alex Morf Debbie Wasserman - Angela Trento Komiko - Sue Jean Kim Québécois Cover Band - Kathleen Hanna Québécois Cover Band - Tommy Buck Restaurant Waiter - Leetopher Scott |


Ansible: My Playbook
Posted: | More posts about ansible WIP devops sysadmin
This is my first playbook that I manage to get it working. It's an achievement for me as it showed that I started to get the concept around ansible:-
- hosts: $hosts tasks: - name: Add main user user: name=kamal home=/home/kamal groups=sudo shell=/bin/bash - name: Set up authorized key for kamal authorized_key: user=kamal state=present key="{{ item }}" with_file: - /home/kamal/.ssh/id_rsa-do.pub - name: Upgrade apt packages apt: upgrade=yes update_cache=yes - name: Install common packages apt: pkg={{ item }} with_items: - build-essential - python-apt - telnet - vim - name: Set vim as default command: update-alternatives --set editor /usr/bin/vim.basic - name: Set up sudo action: template src=etc/sudoers.d/custom dest=/etc/sudoers.d/custom owner=root group=root mode=0440 - name: Set up ssh action: template src=etc/ssh/sshd_config dest=/etc/ssh/sshd_config owner=root group=root mode=0644 notify: - Restart sshd - name: Install nginx apt: name=nginx - name: Start nginx command: service nginx start #- include: playbooks/nginx.yml handlers: - name: Restart sshd action: service name=ssh state=reloaded
The next step is to make it more generic by parameterized certain such as username and file name:-
- hosts: $hosts gather_facts: no tasks: - name: Add main user user: name=$remote_username home=/home/{{ remote_username }} groups=sudo shell=/bin/bash - name: Set up authorized key for {{ remote_username }} authorized_key: user=$remote_username state=present key="{{ item }}" with_file: - '{{ ssh_public_key }}' - name: Upgrade apt packages apt: upgrade=yes update_cache=yes - name: Install common packages apt: pkg={{ item }} with_items: - build-essential - python-apt - telnet - vim - name: Set vim as default command: update-alternatives --set editor /usr/bin/vim.basic - name: Set up sudo action: template src=etc/sudoers.d/custom dest=/etc/sudoers.d/custom owner=root group=root mode=0440 - name: Set up ssh action: template src=etc/ssh/sshd_config dest=/etc/ssh/sshd_config owner=root group=root mode=0644 notify: - Restart sshd - name: Install nginx apt: name=nginx - name: Start nginx command: service nginx start handlers: - name: Restart sshd action: service name=ssh state=reloaded
Finally, I managed to modularized by splitting the tasks into separate files:-
- hosts: $hosts gather_facts: no tasks: - include: playbooks/base.yml - include: playbooks/admin_user.yml - include: playbooks/nginx.yml handlers: - include: playbooks/handlers.yml
With the included files look like:-
# base.yml - name: Upgrade apt packages apt: upgrade=yes update_cache=yes - name: Install common packages apt: pkg={{ item }} with_items: - build-essential - python-apt - telnet - vim - name: Set vim as default command: update-alternatives --set editor /usr/bin/vim.basic - name: Set up sudo action: template src=etc/sudoers.d/custom dest=/etc/sudoers.d/custom owner=root group=root mode=0440 - name: Set up ssh action: template src=etc/ssh/sshd_config dest=/etc/ssh/sshd_config owner=root group=root mode=0644 notify: - Restart sshd
# admin_user.yml - name: Add main user user: name=$remote_username home=/home/{{ remote_username }} groups=sudo shell=/bin/bash - name: Set up authorized key for {{ remote_username }} authorized_key: user=$remote_username state=present key="{{ item }}" with_file: - '{{ ssh_public_key }}'
# nginx.yml - name: Ensure nginx is installed apt: pkg=nginx-full state=present tags: nginx - name: Ensure nginx is started service: name=nginx state=started tags: nginx


Learn more about our first model
The purpose of preliminary fit 1 was to use basic feature engineering to make our initial predictions of test scores. We used a linear regression model with all variables in the data set (besides our outcome and ID variables). For this blog, we only sampled 10% (using sampl_frac()) of the data for computational efficiency.
full_train <- read.csv(here("data","train.csv")) %>%
select(-classification) %>%
sample_frac(.10)
One of the biggest hurdles for learning and using machine learning (ML) is getting the right balance of bias-variance. The purpose of ML is to be able to predict unseen scores or data, so we use available data to model the best prediction. The bias reflects how well the model fits the structure of our data; low bias is good, where high bias ignores important details of our data. Variance reflects variability of our model predictions for a specific data point; flexible models are more likely to have higher variance and are prone to overfitting to the training data and not generalize well to new data. Ideally, our model would have low bias and low variance, but for our first model we will run a linear model which typically has a high bias and low variance.
We used k-fold cross validation (CV) to split our training data into 10 distinct samples of data. Although k-fold may have more variability than other CV methods, it is the most widely used method. For each fold, 10% of the training data are sampled for assessment, and the remaining of the training data serve as our analysis set for that fold. Our performance measure (RMSE) will be the average RMSE across all 10 folds.
set.seed(200)
splt <- initial_split(data)
train <- training(splt)
cv <- vfold_cv(train)
Next we create a recipe (the regression equation that is usually defined inside of a lm call) that defined score as our dependent variable with all other variables predicting it.
We assigned all school and id vars to “id_vars”, this ignores them as predictors and does not apply any of the following steps to these variables. Next, we took care of missing data with step_unknown and step_novel and treated missing data with mean imputation. We also fixed the date format and removed predictors that had no variance, and dummy coded nominal variables.
As the “Inputs” displays, we have 6 ID variables, 1 outcome, and 40 predictors.
rec <- recipe(score ~ ., train) %>%
step_mutate(tst_dt = lubridate::mdy_hms(tst_dt)) %>%
update_role(contains("id"), ncessch, new_role = "id vars") %>%
step_medianimpute(all_numeric(), -all_outcomes(), -has_role("id vars")) %>%
step_unknown(all_nominal()) %>%
step_novel(all_nominal()) %>%
step_nzv(all_predictors(), freq_cut = 0, unique_cut = 0) %>%
step_dummy(all_nominal()) %>%
step_nzv(all_predictors())
rec
Data Recipe
Inputs:
role #variables
id vars 6
outcome 1
predictor 40
Operations:
Variable mutation for tst_dt
Median Imputation for all_numeric, -, all_outcomes(), ...
Unknown factor level assignment for all_nominal
Novel factor level assignment for all_nominal
Sparse, unbalanced variable filter on all_predictors
Dummy variables from all_nominal
Sparse, unbalanced variable filter on all_predictors
We specify that we want to a run a regression.
mod <- linear_reg() %>%
set_engine("lm") %>%
set_mode("regression")
cv <- vfold_cv(train)
m1 <- mod %>%
fit_resamples(preprocessor = rec,
resamples = cv,
control = control_resamples(verbose = TRUE))
m1
# 10-fold cross-validation
# A tibble: 10 x 4
splits id .metrics .notes
<list> <chr> <list> <list>
1 <split [12.8K/1.4K]> Fold01 <tibble [2 x 3]> <tibble [1 x 1]>
2 <split [12.8K/1.4K]> Fold02 <tibble [2 x 3]> <tibble [1 x 1]>
3 <split [12.8K/1.4K]> Fold03 <tibble [2 x 3]> <tibble [1 x 1]>
4 <split [12.8K/1.4K]> Fold04 <tibble [2 x 3]> <tibble [1 x 1]>
5 <split [12.8K/1.4K]> Fold05 <tibble [2 x 3]> <tibble [1 x 1]>
6 <split [12.8K/1.4K]> Fold06 <tibble [2 x 3]> <tibble [1 x 1]>
7 <split [12.8K/1.4K]> Fold07 <tibble [2 x 3]> <tibble [1 x 1]>
8 <split [12.8K/1.4K]> Fold08 <tibble [2 x 3]> <tibble [1 x 1]>
9 <split [12.8K/1.4K]> Fold09 <tibble [2 x 3]> <tibble [1 x 1]>
10 <split [12.8K/1.4K]> Fold10 <tibble [2 x 3]> <tibble [1 x 1]>
These results will differ a litte bit every time the model is rerun (because we only sampled 10% of the data). The RMSE for the full dataset was 87.8
m1 %>%
collect_metrics() %>%
filter(`.metric` == "rmse")
# A tibble: 1 x 5
.metric .estimator mean n std_err
<chr> <chr> <dbl> <int> <dbl>
1 rmse standard 87.9 10 0.381
In our next model we aimed to produce a more predictive model by using step_interact to model the interaction between longitude and latitude because we thought geographic location of schools would influence children’s test scores. We updated the recipe and used 10-fold CV again.
rec2 <- recipe(score ~ ., train) %>%
step_mutate(tst_dt = lubridate::mdy_hms(tst_dt)) %>%
update_role(contains("id"), ncessch, new_role = "id vars") %>%
step_medianimpute(all_numeric(), -all_outcomes(), -has_role("id vars")) %>%
step_unknown(all_nominal()) %>%
step_novel(all_nominal()) %>%
step_nzv(all_predictors(), freq_cut = 0, unique_cut = 0) %>%
step_dummy(all_nominal()) %>%
step_nzv(all_predictors()) %>%
step_interact(terms = ~ lat:lon)
rec2
Data Recipe
Inputs:
role #variables
id vars 6
outcome 1
predictor 40
Operations:
Variable mutation for tst_dt
Median Imputation for all_numeric, -, all_outcomes(), ...
Unknown factor level assignment for all_nominal
Novel factor level assignment for all_nominal
Sparse, unbalanced variable filter on all_predictors
Dummy variables from all_nominal
Sparse, unbalanced variable filter on all_predictors
Interactions with lat:lon
This model produced the same average rmse as in model 1, 87.8. We decided to keep this as our final model.
m2 %>%
collect_metrics() %>%
filter(`.metric` == "rmse")
# A tibble: 1 x 5
.metric .estimator mean n std_err
<chr> <chr> <dbl> <int> <dbl>
1 rmse standard 87.8 10 0.391
To better understand the predictive accuracy of our model, we can use a package called VIP to look at a plot of variable importance on score. We choose to examine variables we thought would be theoretically important for test scores, such as grade in school, ethnicity, whether children participated in a special education program or talented and gifted program, or qualified for a free or reduced lunch program (economic disadvantage). We also included the interaction between longitude and latitude since we thought it would improve our model.
plot1
As seen in the plot, latitude and longitude do not seem to be a variable with a lot of importance in our model, and instead grade in school and whether a child participated in a special education program or talented and gifted program seemed to be the most important variables of the ones examined. The salmon color bars represent negative values, while teal bars represent positive values.
We prepare for this process this by using prep() and bake(). Then we save the predicted score and subject ID to be able to upload out predictions to our class site on Kaggle. We recieved an rmse of 90.42 for predicting the final test dataset.
prepped_train <- rec2 %>%
prep() %>%
juice()
full_train_fit <- fit(mod, score ~ ., data = prepped_train)
final_test <- read.csv(here("data","test.csv"))
col_types = cols(.default = col_guess(), calc_admn_cd = col_character())
final_test <- left_join(final_test, frl, by = "ncessch")
prepped_test <- rec2 %>%
prep() %>%
bake(final_test)
preds_test <- prepped_test %>%
mutate(Predicted = predict(full_train_fit$fit, newdata = .)) %>%
mutate(Id = final_test$id) %>%
select(Id, Predicted)
write_csv(preds_test, "submission.csv")


Importing the library First of all, a modeling application having to deal with simplicial complexes must import the SimpleXn library, denoted smplxn in python. The name of the library was firstly used by our CAD Lab at University of Rome “La Sapienza” in years 1987/88 when we started working with dimension-independent simplicial complexes [PBCF93]. This one in turn imports some functions from the scipy package and the geometric library pyplasm [].


Genesis 50:23
And Joseph saw Ephraim's children of the third generation: the children also of Machir the son of Manasseh were brought up upon Joseph's knees.


Los Angeles, CA
I am a self-proclaimed techie/geek. I've been into web design and programming since the days of AOL and dial-up, but it was mostly a part-time hobby. Growing up on the net, I would find templates and tutorials and 'hack' them to look and work the way I wanted. Technology and the web has always been a passion of mine, but I am ready to make it a career.
Some of my other interests and hobbies include, information security, video & board games, comics, scifi & dark humor novels, coffee, ramen, and anything cyberpunk related.


CodePen by Cole Waldrip
© 2017 Nintendo. The Legend of Zelda, Wii U, and Nintendo Switch are trademarks of Nintendo.


Test Properties Dialog
The test properties dialog is displayed using either the View | Properties menu item on the main menu or the Properties item on the context menu. It shows information about the test and if it has been run about the results. The dialog contains a pin button in the upper right corner, which causes it to remain open as the user clicks on different tests.
Test Tab
This tab gives general information about the test itself.
Full Name
The fully qualified name of the test. In the image below, a tooltip is displaying the complete name, which did not fit in the label.
Test Count
The number of test cases contained directly or indirectly in this test.
Runnable?
Indicates whether the test can be run or not.
Reason
If the test is not Runnable, indicates the reason. This can be the reason given on an ignore attribute or an error such as trying to apply the Test attribute to a private method.
Result Tab
This tab is only visible if the user has run the selected test. It gives information about the success or failure of the test.
Success / Failure
Label indicating whether the test passed or failed.
Time
The elapsed time in seconds to run the test.
Message
If the test failed, the error message is shown here. In the image below, a tooltip is displaying the full text of the message.
Stack
If the test failed, the stack trace at the point of failure. In the image below, the stack display is truncated but could be displayed in a tooltip by the user hovering with the mouse.


randomTriangle()
[ "B", "C", "Both", "None" ]
randFromArray( ANSWERS )
ANSWER === "B" || ANSWER === "Both" ? shuffle( MAIN ) : randomTriangle( MAIN )
ANSWER === "C" || ANSWER === "Both" ? shuffle( MAIN ): randomTriangle( MAIN )
function(){
var tr = new Triangle( [ 3, -2 ], MAIN, 5, {} );
tr.labels = { "name" : "A", "angles" : clearArray( tr.niceAngles, [ 0, 2 ] ) };
tr.rotate( randRange( 0, 360 ) );
tr.boxOut( [ [ [ -4, 1.5 ], [ 10, 1.5 ] ] ], [ 0, -0.5 ] );
return tr;
}()
function(){
var trA = new Triangle( [ 2, -8 ], B, randRange( 400, 600 )/100, { } );
trA.labels = { "name" : "B", "angles" : clearArray( trA.niceAngles, [ 0, 1 ] ) };
trA.rotate( randRange( 0, 360 ) );
trA.color = "blue";
trA.boxOut( [ [ [ -1, -10 ], [ -1, 20 ] ] ], [ 0.5, 0 ] );
trA.boxOut( TR.sides, [ 0, -1 ] );
return trA;
}()
function(){
var trB = new Triangle( [ 7, -6 ], C, randRange( 400, 600 )/100, {} );
trB.labels = { "name" : "C", "angles" : clearArray( trB.niceAngles, [ 0, 2 ] ) };
trB.rotate( randRange( 0, 360 ) );
trB.color = "red";
trB.boxOut( [ [ [ 13, -10 ], [ 13, 20 ] ] ], [ -0.5, 0 ] );
trB.boxOut( TR.sides, [ 0, -1 ] );
trB.boxOut( TR_A.sides, [ 0, -1 ] );
return trB;
}()
Which triangles are similar to triangle A
?
init({
range: [ [-1, 13 ], [ -14, 2.5 ] ]
})
TR.draw();
TR.drawLabels();
style({
stroke: "blue",
});
TR_A.draw();
TR_A.drawLabels();
style({
stroke: "red",
});
TR_B.draw();
TR_B.drawLabels();
ANSWER
Two triangles are similar if their angles are congruent (equal).
We see that triangle A
has angles of MAIN[ 0 ]
and MAIN[ 2 ]
. The third angle is therefore 180 - MAIN[ 0 ] - MAIN[ 2 ] = MAIN[ 1 ]
TR.labels.angles = TR.niceAngles;
TR.drawLabels();
Triangle B
has angles of B[ 0 ]
and B[ 1 ]
. The third angle is 180 - B[ 0 ] - B[ 1 ] = B[ 2 ]
. Therefore triangle B
is not similar to triangle A
.
style({
stroke: "blue",
});
TR_A.labels.angles = TR_A.niceAngles;
TR_A.drawLabels();
Triangle C
has angles of C[ 0 ]
and C[ 2 ]
. The third angle is 180 - C[ 0 ] - B[ 2 ] = C[ 1 ]
. Therefore triangle C
is not similar to triangle A
.
style({
stroke: "red",
});
TR_B.labels.angles = TR_B.niceAngles;
TR_B.drawLabels();


Make a simple CORS request to a method that does not return CORS response headers
Make a simple CORS request to a method that returns CORS response headers
Make a simple CORS request to a method that uses the @CrossOrigin annotation
Make a not simple CORS request to a method that does not have an OPTIONS method defined
Make a not simple CORS request to a method that has an OPTIONS method defined


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Essential Statistics
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Projectiles with air resistance
Consider a spherical object, such as a baseball, moving through the air. The motion of an object though a fluid is one of the most complex problems in all of science, and it is still not completely understood to this day. One of the reasons this problem is so challenging is that, in general, there are many different forces acting on such objects, including:
- gravity
- drag
- lift
- thrust
- buoyancy
- bulk fluid motion, such as wind
- inertial forces, such as the centrifugal and Coriolis forces
In most introductory physics and dynamics courses, gravity is the only force that is accounted for (this is equivalent to assuming that the motion takes place in a vacuum). Here we will consider realistic and accurate models of air resistance that are used to model the motion of projectiles like baseballs.
Wrigley Field in Chicago, Illinois is the home of the Chicago Cubs baseball team. In baseball, an “out of the park” home run is scored when the ball is hit beyond the green outfield (past the yellow foul pole at the left of the above image). Image source: Flickr image by Mike Bash (CC BY NC ND 2.0) (full-sized image).
Drag forces and drag coefficients
The drag force is always directly opposed to the velocity of the object. In vector notation, \[ \vec{F}_{\rm D} = -F_{\rm D} \hat{v}, \] where $F_{\rm D}$ is the magnitude of the drag force, and $\hat{v}$ is the unit vector in the direction of the object's velocity.
Velocity angle from horizontal: $\theta = $ °
The free body diagram for a baseball subject to gravity and air resistance. Observe that the drag due to air resistance is always in the opposite direction to the velocity. Image credit: Microsoft clip art.
The magnitude of the drag force is characterized by the dimensionless drag coefficient $C_{\rm D}$, given by \[ C_{\rm D} = \frac{F_{\rm D}}{\frac{1}{2} \rho A v^2}, \] where $\rho$ is the density of the fluid (in this case, air), $A=(1/4)\pi D^{2}$ is the cross-sectional area of the object, and $v$ is the object's speed.
Drag coefficients as a function of Reynolds number
A dimensionless parameter that is very useful in fluid dynamics is the Reynolds number, which is defined as \[ {\rm Re} = \frac{\rho v L}{\mu}, \] where $L$ is a characteristic length for the flow (in this case, the diameter $D$ of the ball), and $\mu$ is the dynamic viscosity of the fluid. The Reynolds number gives a ratio between inertial forces and viscous forces in a fluid flow. For very small Reynolds numbers, the viscous forces are much stronger than the inertial forces (think of trying to stir a cup of honey). For very large Reynolds numbers, the viscous forces are negligible, and we refer to the flow as inviscid (think of stirring a cup of coffee).
An important result in fluid dynamics is that the drag coefficient is a function only of the Reynolds number of the fluid flow about the object. That is, \[ C_{\rm D} = C_{\rm D}({\rm Re}). \] This functional relationship has no closed form. However, the relationship has been established numerically based on experimental data. See Figure #aft-fd for a schematic diagram of the drag coefficient's dependence on the Reynolds number.
Quadratic drag model
Notice from Figure #aft-fd that there is a range of Reynolds numbers ($10^3 < {\rm Re} < 10^5$), characteristic of macroscopic projectiles, for which the drag coefficient is approximately constant at about 1/2 (see the part of the curve labeled “4” in Figure #aft-fd). That the drag coefficient is constant means that, within this region, the magnitude of the drag force is proportional to the square of the object’s speed. Substituting $C_{\rm D}=1/2$ into the definition of $C_{D}$ above, we obtain \[ F_{\rm D} = \frac{1}{4} \rho A v^2 = c v^2, \] where we have defined the quadratic drag parameter $c$ as \[ c = \frac{1}{4} \rho A = \frac{\pi}{16} \rho D^2, \] which is a constant for a given projectile. This is referred to as quadratic drag, because the drag force magnitude is proportional to the square of the speed. Using this result, we can write the drag force vector as \[ \vec{F}_{\rm D} = - c v^2 \hat{v}. \]
In the presence of gravity and quadratic drag alone, the net force on an object is given by \[ \sum \vec{F} = m \vec{g} - c v^2 \hat{v}, \] where $m$ is the mass of the object and $\vec{g}$ is the local acceleration due to gravity. Below is an interactive graphic showing the trajectory of an object with gravity and quadratic drag. You can change the various parameters to see their effects on the object’s motion.
| Initial speed: | $v_0 = $ m/s | |
| Initial angle: | $\theta_0 = $ ° | |
| Mass: | $m = $ g | |
| Diameter: | $D = $ cm |
Trajectories of a projectile in a vacuum (blue) and subject to quadratic drag from air resistance (red). The air density is $\rho = 1.225\rm\ kg/m^3$ (standard sea-level atmosphere) and the acceleration due to gravity is $g = 9.81\rm\ m/s^2$. A regulation baseball has a mass of about $m = 145\rm\ g$ and a diameter of about $D = 7.5\rm\ cm$.
There is no well-measured record for longest baseball home run. It is claimed that Mickey Mantle hit a ball 643 feet (196 m), although this apparently included rolling on the ground. Other power hits by Mantle are reliably measured to be over 500 feet (152 m).
Given that the record for fastest speed off-bat is around 120 mph (53.6 m/s), the simulation in Figure #aft-ft shows that it is unlikely that Mantle's long hits could have occurred without some additional assistance from wind, ball spin, or other effects.


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MicroBitLightSensor¶
Operation¶
Sensing Pins¶
If the current is inverted on an LED, it becomes sensitive to light. In particular it is sensitive to the same colour of light it emits.
You will find that the Light Sensor on the micro:bit is more reactive to red light than any other colour because that is the colour of light the display emits.
The display is architected with 3 rows, each with 9 columns. This is illustrated below:
On the micro:bit we have 6 analog pins, 3 are applicable to the display and reside on columns 1, 2 and 3.
This means that we have 9 pins in total that we can sense light on if we are fast enough to transition between emitting and sensing light.
The 9 sense pins are illustrated below:
_____________________________
| 1.1 | | 1.2 | | 1.3 |
|_____|_____|_____|_____|_____|
| | | | | |
|_____|_____|_____|_____|_____|
| 2.2 | | 2.3 | | 2.1 |
|_____|_____|_____|_____|_____|
| | | | | |
|_____|_____|_____|_____|_____|
| 3.3 | | 3.1 | | 3.2 |
|_____|_____|_____|_____|_____|
The ADC takes around 4ms to settle and give accurate values with minimal current. This places restrictions on our sensing window.
Interleaving¶
In the current implementation, the display and the Light sensor can operate in an
interleaving manner. This interleaving is enabled due to a special display mode on the display
which is automatically activated when readLightLevel
is called by the user.
This special mode (DISPLAY_MODE_BLACK_AND_WHITE_LIGHT_SENSE
), increases the rate of the systemTick
callback to 5ms, and the
display is thusly configured to drop the 4th frame for user processing,
which in this case, is entirely consumed by the light sensor. This reduces the display
refresh rate from 55Hz to around 50Hz.
To signify the window for user processing, the display will fire an event:
- ID:
MICROBIT_ID_DISPLAY
- Value:
MICROBIT_DISPLAY_EVT_LIGHT_SENSE
This will trigger an event handler in the MicroBitLightSensor
class.
Sensing Life Cycle¶
In the previous section we discussed how the display and the Light
Sensor interleave. This section will cover the actual operation of the sensor during
the MICROBIT_DISPLAY_EVT_LIGHT_SENSE
event.
Note
If you would like to manually trigger the Light Sensor, a few steps must be taken:
1) Disable the display so that the column pins are under the users' control.
2) Construct an instance of MicroBitLightSensor
3) Trigger the Light Sensor by firing a MicroBitEvent
with the ID MICROBIT_ID_DISPLAY
and the value MICROBIT_DISPLAY_EVT_LIGHT_SENSE
.
The Concept of Channels¶
As we previously discussed there are 9 pins we can sense light on. However, we face the problem of interference from the state of other Columns.
We found that the best combination was to treat each of the three analog enabled Columns as a channel. This leads our picture to look something more like this:
_____________________________
| 1 | | 2 | | 3 |
|_____|_____|_____|_____|_____|
| | | | | |
|_____|_____|_____|_____|_____|
| 2 | | 3 | | 1 |
|_____|_____|_____|_____|_____|
| | | | | |
|_____|_____|_____|_____|_____|
| 3 | | 1 | | 2 |
|_____|_____|_____|_____|_____|
This reduces the resolution of our light sensing capabilities as we can now no longer can use 9 pins to sense light, purely due to the unfortunate fact that we obtain interference from other pins that cannot be mitigated.
However, we do gain an accurate picture of the overall brightness detected by the display.
We expose a mean representation of the light level from the 3 channels on the display.
The Algorithm¶
Upon receiving an event:
- Set all rows to be a DigitalOut, with a value of 0.
- For the current channel:
- Set the current channel pin HI.
- Immediately transition the current channel to be an AnalogIn
- Attach an interrupt to occur 4ms into the future. (This allows our AnalogIn instance to settle correctly)
Upon interrupt:
- Obtain our analog value.
- Release the pin from GPIOTE control. (If we do not do these, this column will not be useable in the display driver)
- Move onto the next channel.
After these two phases have occurred, the display will now once again be available for regular usage until the next interleave is signaled by the display.
Message Bus ID¶
Message Bus Events¶
API¶
Constructor¶
MicroBitLightSensor( const MatrixMap & map)¶
Description¶
Constructor.
Create a representation of the light sensor.
map
The mapping information that relates pin inputs/outputs to physical screen coordinates. Defaults to microbitMatrixMap, defined in MicroBitMatrixMaps.h .
Parameters¶
const MatrixMap &map - The mapping information that relates pin inputs/outputs to physical screen coordinates. Defaults to microbitMatrixMap, defined in MicroBitMatrixMaps.h .
read¶
int read()¶
Description¶
This method returns a summed average of the three sections of the display.
A section is defined as:
| 1 | | 2 | | 3 |
___
___
2 3 1
___
___
3 1 2
___
Where each number represents a different section on the 5 x 5 matrix display.
Returns¶
returns a value in the range 0 - 255 where 0 is dark, and 255 is very bright
startSensing¶
void startSensing( MicroBitEvent )¶
Description¶
The method that is invoked by sending MICROBIT_DISPLAY_EVT_LIGHT_SENSE using the id MICROBIT_ID_DISPLAY.
Parameters¶
MicroBitEvent
Note
this can be manually driven by calling this member function, with a MicroBitEvent using the CREATE_ONLY option of the MicroBitEvent constructor.


A cell being "populated" means that the BMS is expecting to see voltage on that particular cell (meaning it will process it as a real cell). An unpopulated cell is disregarded by the BMS and skipped.
| < Pack SOH (State of Health) | On-Board Diagnostics II (OBD2) > |


Table of Contents |
CIDD consistes of two principle display panels; one of plan view and one for
cross sectional data views. In addition a set of control sub panels are used to select products,
add or change attributes of products in the images, control movie looping, etc.
Many of the most frequently used operations such
as selecting different products, heights or time of interest can be performed
with one keystoke or mouse click in the display window, or popup panels. Side by side comparisions
of plan view or cross sectional data are accomplished by running multiple instances of CIDD.
There is a CLone button/function available in the menu bar.
Directly below the menu bar is the time and flight level information bar. This
bar shows:
The margins contain the following:
The view menu allows you to adjust the zoom state to pre-defined domains. There are also buttons that allow you to save custom zoom states and return to the saved states.
Using Zoom¡GUse the click and drag method for zooming (with the left-mouse button) to get a user-defined region. This user-defined region becomes the current zoom and will cause the 'Current' button to be selected. Unzoom by choosing one of the pre-defined domains.
Panning¡GYou can pan or move the image with the middle mouse button: click on a point and drag it to the desired location, then release.
Saving zoom states¡GTo save the current zoom, click on 'Save 1', 'Save 2', or 'Save 3'. To go back to the saved view, click on 'Goto 1', 'Goto 2', or 'Goto 3'.
| The 'Field or Page' menu (see left Fig.) is a pop-up menu for selecting a desired data set page. Select the desired page by clicking on the appropriate button. Click on 'FIeld/Page' again in the menu bar to remove the menu. |
| The view menu (see left Fig.) allows you to adjust the zoom state to pre-defined domains. Clicking on the View button activates a pull-down menu of selectable items. "Save1", "Save2", and "Save3" are the buttons that allow you to save custom zoom states. "Goto1", "Goto2", and "Goto3" are the buttons that allow you to return to the saved states. (See Section 5.3.4 for descriptions on "zooming and saving zoom states".) |
| The Maps... button activates a pull-down menu (see left Fig.) showing the available maps. Clicking on an item toggles it on/off. On startup, a default set of maps is turned on and the remaining maps are off. |
| The Product...button activates a pull-down menu (see left Fig.) and toggles the overlay products on/off. Clicking once turns all the products on and clicking again turns all the products off. The available overlay products are: |
The movie control panel has two main sections. The upper half of the panel contains a number of buttons, sliders and text entry areas. The lower half of the panel is a graphical display. Note that the display must render each movie frame, which takes a few seconds for each frame, so patience is required. After all frames have been rendered, the display will cycle rapidly through the frames with a delay at the end of the loop.
: You can stop the movie by clicking this button. You can step through the movie
by clickingand then
selecting the desired frame in the movie bar . You can also step through the
frames by hitting the left arrow key (go back) or right arrow key (go forward)
on the keyboard.
For this to work, the pointer must be in the main MDS window.
:
Click on this button in the Movie Panel will start the movie.¡C
:
The display may be run in 'Realtime' or 'Archive' mode. In realtime mode, new
data is added to the end of the movie loop as it arrives and the loop advancer
as time passes. Realtime mode is the default behavior of a live system such
as the AOAWS. To loop in realtime mode, you can either selec
then click on in the
Movie Panel or toggle the 'Loop' menu button on the main menu bar (see Section
<IP_ADDRESS>).
: In archive mode, the movie loop remains static, does not move as time passes,
and the display does not check for new data. Archive mode is used for viewing
old data for analysis purposes. To set the display to archive mode, click on
the button, before
click on the button,
set the desired movie start time in the top text box that reads 'Movie Loop
Starts at:' The data entered is:hour:minute month/day/year. You can
either use the format presented in the time text box, or you can just enter
numbers separated by spaces.(Remember to hit "Enter" when you are done.)
¡GYou
can change the number of movie frames in three ways:
- Enter the number of frames at the relevant text entry point
(please note: for all text entries, you MUST hit "Enter" on the
keyboard after entering text);
- Click on the up/down arrows next to the 'Number of Frames'entry box;
or
- Drag either the start or finish solid triangles, at either end of the movie
bar, to change its start or finish time.
Sweep Button¡GUse
the Sweep Button to enter sweep mode. In sweep mode the movie goes forwards
and backwards in sequence, instead of just forwards.
Movie Loop Start
Time¡GSet the desired movie start time in the top text box that reads 'Movie
Loop Starts at:' The data entered is: hour:minute month/day/year.
You can either use the format presented in the time text box, or you can just
enter numbers separated by spaces. (Remember to hit "Enter" when you are
done.) To return to realtime mode, click on the
button on the movie panel or the
button in the main menu (Fig. <IP_ADDRESS>-1).
Movie Frame Interval¡GYou
may change the movie frame interval. To do so, enter the number of minutes per
frame at the "Movie Frame Interval" text box. (Remember to hit "Enter"
when you are done.)
Speed Slider Bar¡GUse
the 'Speed' slider bar in the Movie Control Panel to control the speed of the
loop. Move the slider further to the right side to increase the speed.
Delay Slider Bar¡GUse
the 'Delay' slider bars in the Movie Control Panel to control the length of
the end delay. Move the slider further to the right side indicating a longer
delay.
Data Availability¡GThe
lower half of the panel is a graphical display which shows, from top to bottom,
the "movie bar", a bar showing the current movie extent, the available data
with lines for symbolic data and dots for gridded data, and a time scale. The
denser the lines or dots indicate a larger data volume.
Time Axis¡GThis
shows time of the current movie loop and amount of data displayed.
Movie Bar¡GDrag
either the start or finish solid triangles, at either end of the movie bar,
to change the start or finish time.
Text, Symbolic
Data¡GThis shows the current movie extent and the available data with lines
for symbolic data, each line representing one record of data.
Change Start
Time¡GDrag the start solid triangles, at the left end of the movie bar, to
change the start time.
Change
Finish Time¡GDrag the finish solid triangles, at the right end of the
movie bar, to change the finish time.
| The"Past"button brings up a pop-up menu, which allows you to select a past time of interest, relative tobutton. For example, if you pick '-6 hrs' it will move the display time, and the end of the movie loop, to approximately 6 hours in the past. Doing so will put the display into 'Past' mode, and data in the past will be displayed. Selectingfrom the same menu will revert to Realtime mode. This is the same as selecting thebutton in the main menu bar (see Section <IP_ADDRESS>). |
| Thebutton brings up a pop-up menu, which allows you to select a forecast time of interest, relative to the button. For example, if you pick '+6 hrs' it will move the display time, and the end of the movie loop, to approximately 6 hours in the future. Doing so will put the display into 'Forecast' mode, and data in the future will be displayed. Selecting from the same menu will revert to Realtime modes. This is the same as selecting the button in the main menu bar (see Section <IP_ADDRESS>). |
The terrain along the route is depicted in solid brown, overlaying the data field. To change to a different field, right-click in the vertical section window and select the field from the menu that appears. The flight level scale appears in the left margin.
Fig. <IP_ADDRESS>-1 shows a user-selected route in plan view. The route is shown as a bold yellow line. The waypoints are labeled by the closest navigational fix (way point, VHF navaid or airport) within 20 nm of the selected point. If no navigational fix lies within a 20 nm radius, the point will be marked with a number indicating its position on the route. For example, the first point will be labeled "1", the third point "3", and so on.
Figure <IP_ADDRESS>-2 shows the corresponding vertical section. The selected field
(in this case turbulence probability) is shown with the color scale legend on
the right. As mentioned above, you may select a route by clicking and dragging
in plan view. You may also select a route from a pre-defined list of routes.
On Figure <IP_ADDRESS>-2, you will see the button marked 'Routes ...'. Clicking
on this button will bring up a list of pre-defined routes. You may click on
any of these to select it. The latest route you entered by clicking and dragging
may be retrieved by using the 'Custom' button on that menu.
The 'Label Waypoints' is one of the check-boxes that toggle the waypoint labels
on and off, in case they are obscuring data. If waypoint labels is on, the navigational
fix lies within a 20 nm radius will be marked. Otherwise, they will not.
The 'Show Winds Text' is the other check-box that toggles the segment route
with values on and off. See Figure <IP_ADDRESS>-3 for an example with the route
winds on. The mean wind for segments along the flight is shown plotted at the
mid-point of the segment.
The 'Average wind' label located directly under the window title bar displays
the average wind along the entire flight route.
The 'Turbulence and/or icing warnings' label located under 'Average wind' label,
in red, warns if a route goes through an area of turbulence or icing, or both.
Otherwise it is empty. (In the example, it shows "Mod Turb" indicating the route
passes through an area with a moderate probability of turbulence.)
The selected flight level is depicted by the dashed horizontal line.
The distance along the route in nautical miles is shown along the bottom axis,
with the starting point on the left.
The waypoints are plotted as vertical dashed lines, with the waypoint name at
the bottom. (The navigational fix lies within a 20 nm radius will be marked.)
Use the 'Dismiss' button to remove the vertical section from the screen. Toggling thebutton on the main menu may also be used for this purpose.
This pop-up windowallows you to select from a list of URLs. Netscape is started (if required) and is set to point to the requested URL. Iconify Netscape when done.
The following URLs are available:
- AOAWS WMDS - web-based MDS
- Winds/Temps aloft - tables of winds and temperature aloft forecasts for a selected set of airports.
- AOAWS MM5 - the MM5 model display.
- USA ADDS - the site for the USA National Weather Service Aviation Weather Center Aviation Digital Data Service (ADDS).
Refer to Figure 5.4-1. The decoded METAR text program (MetarSelect) displays metar data, sorted by distance from the click point. If configured for real-time operation, the program will display the latest data available. In archive mode, the program will use information from CIDD to obtain the time of interest and will gather data appropriate for that time.
To update the window, select the desired METAR station by clicking in the main display window close to the METAR station of interest. The METAR text window will be updated with the latest reporting METAR information for that station and nearby stations. The closest station will appear at the top of the list. The data is in time-reverse order with the latest observations at the top.
You can change the size of the font by holding down the control key, putting the cursor in the window and then clicking the right mouse button. A font menu will appear. Select the desired font. Select the 'Default' option to use the original font.
Refer to Figure 5.10-1 This program shows the time history for METAR stations. To change the field, right-click and select the desired field in the pop-up menu that appears. The active fields are: temperature, humidity, wind speed, pressure and wind direction. Alternatively, you can select a station of interest in the pop-up menu, which shows all the fields for that station.
Refer to Figure 5.5-1. The winds/temps aloft window appears in the middle of the screen at the right hand side.
To update the window, click in the main window at the point of interest. The text in the winds/temps aloft window will show a vertical profile of the forecasted (MM5 model) wind speed, direction, temperature, dew-point and relative humidity for the location at which you clicked. The time on the panel is the forecast valid time. To change the forecast time, select a different time on the time scale bar in the main window. The location (Lat, Lon) of the vertical profile is also provided in the widow. Also, the name of the closest navigational point within 50 nm is printed below the lat/lon location. Data will not be displayed if you click outside the MM5 data area.
Occasionally you will see data fields containing "xxxx" instead of a number. This indicates missing data for that field and is usually caused by the fact that the relevant flight level is below the terrain at the selected point.
NOT DONE.


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Caught on Camera: Parade Balloon Knocks Down Marcher
NEW YORK, NY. (CBS) - Marcher in NYC Thanksgiving Parade knocked down while trying to wrangle the "Nutcracker" balloon.
City and parade officials had considered grounding the giant iconic balloons given the wind conditions and forecast but were cleared for flight shortly before the start of the parade.