FREE COURSES IN MACHINE LEARNING

In our aim of sharing our delights with you all, while continuing with our theme of Machine Learning and the Artificial Intelligence Revolution, OMNITEKK is enthused to imbue our fellow technophiles with free courses on the foundations of Machine Learning. 

And for all interested, we sure hope you enjoy the journey.

Until our next I.T. adventure my friends, OMNITEKK says be well.

Machine Learning Regression And Classification

https://www.coursera.org/learn/machine-learning

Introduction To Machine Learning

https://www.classcentral.com/course/youtube-introduction-to-machine-learning-dmitry-kobak-2020-21-46773

Statistical Machine Learning

https://www.classcentral.com/course/youtube-statistical-machine-learning-ulrike-von-luxburg-2020-46771

Mathematics For Machine Learning

https://www.classcentral.com/course/youtube-mathematics-for-machine-learning-ulrike-von-luxburg-2020-21-46772

DATA SCIENCE

The means by which we categorize and classify data streams of structural inputs is at the heart of the Data Science revolution.

As such, Data Science and its explorations, help us to gain critical insights into statistical attributes pertaining to the fields of social sciences and human behavioral trends, patternistic archaeological inferences and deductions within the animal world, as well as helping us to discover breakthrough advances in healthcare and the pharmaceutical industry, in effort to support human longevity.

Likewise, there are a few key trends in the field that help data scientists working with larger data-sets organize and make efficient use of the information gathered, so as to advance the field, and utilize the  proficiencies gained within structured data models, to better understand the evolutionary progressions of our species and our world.

These Trends Include -

WEB SCRAPING AND DATA MINING 

in effort to develop statistical trends and deep attributional correlations between seemingly disjointed information. 

If we seek to deduce an assertion from within a particular attribute of interest, the larger the data set or volume of information we collect, the greater the chance of doing so becomes. 

Data mining and data collection is an essential area of data science in that it is the foundational source of information and digital data statistical deduction.

DATA ANALYSIS 

We come to know things based on the means by which we classify and define them.

Data analysis helps us accomplish this, through a series of hypothetical assertions and tests that allow scientists, mathematicians, programmers, statisticians and even philosophers alike, to determine the critical or prevalent attributes of a thing, so as to satisfy a specific or particular categorization and determination surrounding it. 

Data analysis includes gathering pertinent key information from a collection of data sources whether clustered, structured or unstructured to be used in such a determination.

INFERENTIAL INDUCTION AND DEDUCTION

Most of the information we collect is usually geared toward discovering an inferred hypothesis or deducing the refutation thereof. 

The process of drawing correlations between data stores, allow such inferences to be either proved or disproved upon gaining a better understanding of the trends that either affirm or disprove inferences of observation that serve as the foundational learning curves in discovering how certain attributes connect with critical theories, or the lack thereof.

MACHINE LEARNING 

Once critical analytical derivations have commenced, the definitive classification of either a model of regression or progression pertaining to a specific data sample, either serves as a dimensionality attribute of an existing data model or the foundational key attribute of the deep learning required to successfully classify a new one through attributional clustering.

In essence, machine learning is the attributional process of either creating, adjoining or declassifying data such that definitive categorizations and determinations of recognition might be made upon future interaction with it, based on inferential statistical and mathematical calculations of correlation or contrast.

DATA VISUALIZATION 

A key vestige in the world of Data Science lie in being able to convey technical or otherwise complex structural data concepts in easy to understand ways. 

This my friends, is where data visualization models come in to play.

Data visualization is the process of pictorially showcasing statistical attributional findings, so as to convey significance or minimizations pertaining to a specific concept, field, or area of study. 

Graphs, Data Decision Trees, Charts and even Videographical Data Displays, are all frequently used data visualization tools.

ACCUMULATIVE INSIGHTS OF ATTRIBUTIONAL EVOLUTION 

Once each of the stages in the data science process commences, the means by which attributional evolutionary variations across the classification spectrum is structured, should be continually measured or quantified, to record classification progression.

Here variances are traced, analyzed, and re-categorized where necessary, to maintain integrity in categorical attributional accuracy.

It's no secret that our world has vastly become a data-driven machine where the answer to some of our most pressing phenomena might be enclosed within the deep vestiges of digital data structures.

As such, Data Science field progressions once considered difficult and cumbersome to gauge attributional certainty in, now prove quite effortless, albeit tools such as machine learners and information access leverages of usable structured and unstructured data, that help us advance in understanding our world and the esoteric wonders within it...

...all thanks to improved Data Science measures.

We sure hope you've enjoyed our walk down Data Science Lane, and until our next I.T. adventure my friends, OMNITEKK says be well.

CYBERCRIME

The INTERNET OF THINGS has made way for the invaluable vestiges of e-commerce, global connectedness, as well as productivity to increase demonstrably, as collaborative and convenience solutions are right at our fingertips.

Likewise, the evolution of such avenues have also allowed CYBER CRIMINALS to utilize these dais in effort to carry out harmful aim against unsuspecting machine users in undeniable fashion, spawning the exponential emergence of crime prevention measures.

CYBERCRIME includes any and all acts to steal, deceive, and terrorize both personal and organizational machine users alike, in effort to cause significant harm...

...to include -

Spoofing identifying machine information to garner trust and gain unauthorized access to someone's machine and machine resources.

Stealing personal information to use illicitly, such as banking information, passports and other identifying information to commit cyber crimes.

Using Spyware to acquire the 'Digital Fingerprint' of machine users for the purposes of illegally tracking internet activity.

Cyber Espionage to elicit brute force attacks by way of preventing access to resources by machine owners to ransom monies or other leverages.

Cyber Terrorism serving as machine owner harassing hubs by breaking valuable resources in effort to garner complicity or to prevent productivity and proficient resource utilization, through acts of cyber violences.

As the means by which our world becomes more connected enhances, so too does the methods criminals have at their disposal to engage in stealthy illegal activities.

Further, the array of faceless and nameless cyber criminals hiding behind machines while using them to steal, terrorize, and force modes of espionage onto unsuspecting targets have far greater aim in absconding their activities from the law, as internet traffic and ports of origin and destination aren't as easily tracked as we might believe, making it an arduous task for cyber crime prevention efforts to successfully identify criminal origins.

As such, one of the best things we can do as machine users is to seek the help of cybersecurity professionals upon observing resource compromisation when first recognized.

Likewise, OMNITEKK suggests keeping a dossier of any and all anomalous circumstances so as to help bring awareness of trends in what you may be facing.

And lastly, it is central to note that even the craftiest cyber criminals eventually get caught.

So be sure to continue your due diligence in helping maintain a safe and secure computing experience for us all.

And until our next I.T. adventure my friends, OMNITEKK says be well.

 

 

LEARNING MACHINES

Computer programs, once sequenced as the functional output of human directives manifesting lightning speed result-sets, have shape-shifted in their nature, as advanced machine processing methods encompass the technological ebbs and flow of machine learning.

The machines of new, given the desired result-set of a given function, now have the "intelligence" to design the relative data inputs themselves to satisfy it.

ARTIFICIAL INTELLIGENCE and MACHINE LEARNING have made way not only for immense productivity levels in our workflows to commence, but have likewise spawned a new era of computing, with the machine itself now having the ability to transform its own instruction sets to accomplish imperceptible successive aim in data mining models, such that our means of both organizing and relating collections of seemingly disjointed information might be used in meaningful ways as we bear witness to the 5th generation of digital networking.

As such, OMNITEKK found a few phenomenal videos to help you understand the key concepts within computational autonomy and the world of MACHINE LEARNING.

Enjoy!

And until our next I.T. adventure my friends, OMNITEKK says be well.

RISE OF THE MACHINE

It's no secret that within just a short span, the boom of brilliance on display from some of our most prized developers, have allowed us to witness leaps and bounds within the TECH INDUSTRY.

 

Likewise, successive automations, from the simple, to those of immense intricacy and complexity, have dawned a new era of engineering ambitions that have far surpassed what most critics deemed possible years ago.

And as we continue to improve upon these themes, there are certainly a few questions to be asked - such as how might they affect the future of human employability in the field.

This rings especially true, as the evolution of autonomous developments, such as NEURAL NETWORKS and advanced DATA MINING trends take shape, spawning a surge in the emergence of machine-automata and refactoring methods that now make it possible to subvert developer efforts in favor of self-modifiable codes instead of requiring human programming efforts within key production processes.

If designs then, such as the GOOGLE WORLD BRAIN and other ARTIFICIAL INTELLIGENCE ambitions, have the ability to enhance productivity efforts in such a way that the need for human-machine interaction declines, the developer, programmer and software architect's efforts and future necessity within the field also declines, with the very real threat of programmer obsoletion looming.

The emergence of collective data mining practices allow data sharing in more connected pathways, through an increase in collaborative interfaces, but they also pose the very real threat of phasing out human efforts as well.

We are now witnessing the residual effects of such industry trends, as the I.T. Giants TWITTER, GOOGLE, and MICROSOFT, have begun widespread layoffs within their family of workers, with our predictions forecasting other tech giants to follow in the near future.

Likewise, as aspiring S.T.E.M FIELD contributors continue to grow in both education and industry ambition, OMNITEKK suggests these exploration areas to increase your chances of employability within the market.

DATA SECURITY

Security breaches of sensitive data, whether by malicious intent or harmless virtue, pose significant threats to data security and privacy, and must constantly be maintained and supported, such that the viability of tech implementations along with the safety and security of sensitive data maintain their integrity.

Hence, there shall always be a need for securing information and maintaining data obsfuscation trends within the industry.

HARDWARE DESIGN AND MAINTENANCE

With the emergence of self-learning machines, the need for workers who design and build the hardware to ensure the successful integration of both hardware and software, shall prove immense necessity within development processes. 

Hardware engineers and hardware maintenance workers should find sustainability within the field, procuring their rightful place amongst the dwindling tech jobs on the market, as the need for software designers is on the decline.

BIG DATA

Of all the types of developers on the market, a thorough expertise in understanding DATA STRUCTURES and DATA COLLECTION and ORGANIZATION TRENDS, that foster the utilization of otherwise disconnected information to be used in meaningful applications, make way for what we consider the big boom of employability and productivity trends within the market.

CREATIVE VISION AND TECH INGENUITY

The pioneer has always proven a very necessary commodity in the tech arena, and there has never been a greater time to evoke one's own creativity flows, so as to find lacking vestiges in the field, to apply ingenuity within those processes, just as the industry titans of old have done.

As such, the tech visionary is always of good use. 

SEE A NEED FILL A NEED.

INDUSTRY SPECIALIZATION

The era of the JACK OF ALL TRADES, MASTER OF NONE is long gone, and the I.T. arena now calls for the highly specialized tech connoisseur who is well vested in know-how within methods, language and practicality of use.

And with the latest tech trends in I.T. seeming to employ the culmination of MACHINE -AUTONOMY - from self-driving cars, to self-flying aircraft and even to self-coding codes - the culmination of our relevance in the field should be BUILD, SECURE and MAINTAIN.

May these words help you on your journey to OMNITEKK GREATNESS as you master your craft.

And until our next I.T. adventure my friends, OMNITEKK says be well.

NUMBER CONVERSIONS

A great deal of the tasks the developers of new engage in, require on some level, the structural converting from one number base to some other, as our natural counting bases differ from those coveted 1's and 0's, amongst others, used in our machines, to dish out the glorious codes serving to simplify both our workflows, and the means by which we interact with and automate the world around us.

And without further ado, OMNITEKK presents our rendition of NUMBER CONVERSIONS, to help you along the way to becoming the I.T. rock stars we know you all have the proclivity to be.

BASE 10 TO BINARY

While we each of us have 10 fingers and 10 toes - well most of us anyway... giving ode to the representation and relevance of our base 10 numbering system, the machines we use in our processing tasks do not.

Fact is, the innerworkings of the human readable inputs and outputs of machine processes we recognize, prove vastly different within the machines themselves, consisting only of the simplicity of low to high voltage representations of data sequences, signified by either a 1, to show a HIGH VOLTAGE or ON position of a RELAY, TRANSISTOR or SWITCH along with 0, indicating LOW VOLTAGES or OFF positions.

These are the foundational attributes of what we come to know of as the BASE 2, or BINARY numbering system.

So instead of trekking between 10 numbers to represent the culmination of data or information, our machines accomplish almost whimsical feats, by combining and grouping, masking and converting just two numbers, namely 1's and 0's. 

It's all quite fantastical if you consider it.

Likewise, converting from BASE 10, our natural counting BASE, to BASE 2, the computer's natural counting BASE, consists of multiplication and division to represent clusters of binary information.

Here's how...

Let us take the BASE 10 DECIMAL number 1 2 3 4 5 for instance. 

We simply divide the number by 2, while keeping only the remainder, in reverse order, as our BINARY number conversion result.

So, 1 2 3 4 5 becomes 0011 0000 0011 1001 in BINARY.

Likewise, to convert a BINARY number to DECIMAL, simply utilize the inverse operation of multiplying the BINARY number by 2 with increased exponentiation ranging from 0 to the BINARY number length minus 1, to retrieve its BASE 10 number equivalent, only calculating the addition of the degree values where the result is 1 or ON.

00(1*8192)+(1*5096)+  0000  00(1*32)+(1*16)+  (1* 8)+00(1*1)

BASE 8 TO BINARY

Suppose instead of having 10 fingers and toes, we instead have only 8.

In this instance, instead of counting from 0 to 9 before our number increases in degree, we only count from 0 to 7.

So counting 20 in our new number base looks like 0, 1, 2, 3, 4 ,5, 6, 7, 10, 11, 12, 13, 14, 15, 16, 17, 20 and so on.

Thing is, we still have to represent a BASE 2 number. 

To do so, we simply utilize the same process of multiplication and division from our initial BASE to our desired BASE.

 In this instance, to retrieve the BINARY equivalent of the OCTAL value 30071, we simply process the OCTAL number by its individual numbers, and divide each of those number values by 2, discarding all but the remainder values in reverse to retrieve our BINARY equivalent in groups of 3.

So 3  0  0  7  1 in OCTAL becomes 011 000 000 111 001 in our BINARY conversion.

Likewise, to retrieve the OCTAL equivalent from our BINARY value, we simply perform the inverse  operation on our binary groups of 3, and convert each number group to their OCTAL equivalent.

0(1*2)+(1*1)   000   000   (1*4)+(1*2)+(1*1)  00(1*1)

BASE 16 TO BINARY

Now, keeping up with convention, suppose instead of having 10 fingers and toes or even eight of them, we instead have 16.

While such a conception might seem both foreign and of unpleasant inconvenience, this is the measure of our hexadecimal (hex for short), or BASE 16 numbering system - introducing instead of only the DECIMAL numbers 0 through 9, the culmination of the alphabetical letters A to F also, for total of 16 number counts before increasing the degree of the actual number.

For instance, instead of 0 1 2 3 4 5 6 7 8 9, we now have 0 1 2 3 4 5 6 7 8 9 A B C D E and F, with A having the equivalence of a BASE 10 10, B of 11, C of 12 and so on.

To convert a HEXADECIMAL number to BINARY, we simply divide the number in it's individual number values by its BASE conversion factor of 2, grouping the result by groups of 4.

So the HEXADECIMAL value ABCD  becomes 1010 1011 1100 1101.

To compute its inverse, we simply compute each group of BINARY digits to their HEX equivalent, multiplying each BINARY digit by 2 in increasing exponent order from 0, only keeping the ON or 1 values in reverse as our result.

(1*8)+0(1*2)0   (1*8)+0(1*2)+(1*1)   (1*8)+(1*4)00   (1*8)+(1*4)+0(1*1)

And that's it folks, NUMBER CONVERSIONS served!

Until our next I T. adventure my friends...OMNITEKK says be well.

BEST OF THE BEST

 The Pioneers Of I.T And Computing

As self-proclaimed technophiles, we here at OMNITEKK believe it is our duty to give reverence to some of the founding fathers of computing, as they have helped pioneer some of the most prolific technological phenomena we know of.

And without further ado- THE BEST OF THE BEST PIONEERS OF COMPUTING AND TECHNOLOGY

Samuel Finley Breese Morse (1791-1872)

Our dearly beloved Samuel Morris developed the foundational tenets of coded language, namely Morse Code, the precursor to both the telegram and the internal hardware of the modern-day machines of new.

Morse Code utilized combinations of dots and dashes to represent alphabetical and alphanumerical codes of language, which would later become known in the computer world as a series of binary codes.

Alan M Turing (1912-1954)

Turing, who pioneered the concept of computations and computability, is best known as the man who cracked the German "ENIGMA" coding machines during world war II.

Alan is also known for writing two influential papers on the concept of what computers can I can't do, as well as designing the abstract model of what has been coined The Turing Machine.

Norbert Wiener (1894-1964)

Wiener, a mathematician from Harvard coined the term Cybernetics, hailed as the defining attributes of similarity between control and communication channels within the animal and machine (1948).

This concept laid the foundational descriptors of the relation between the biological processes in humans and animals relative to the theoretical mechanics of modern-day computers, robots and cobots.

John Borden (1908-1991) and Walter Brattan (1902-1987)

This dynamic duo, is best known for the construction of the amplifier - manufactured from slabs of germanium - the semiconductor material, which allows an electrical signal to be strengthened across communicatory channels.

This revolutionary invention, coined the most important invention of the 20th century, took us from the modern-day relay of old, to the transistors of new, which in today's microchip and graphical processing units, easily comprise hundreds of thousands, or even millions of units.

Jack Kilby (1923) and Robert Noyce (1927-1990)

Jack and Robert are famously revered as the co- inventors of the integrated circuit, commonly called the chip. (yeah folks, OMNITEKK means the microchip.

With the two major classes of microchips in use today being the  Complementary MOSFET CMOS ( pronounced Sea Moss), and  Transistor Transistor Logic chips or TTL (pronounced Tee Tee Ell ) integrated circuits.

These folks are certainly worthy of note, and we  especially hope our introduction to them has spawned further interest and exploration.

And until our next I.T. adventure my friends, OMNITEKK says be well.

Oh No...The Big O

 Developing software is the means by which we solve some of our most pressing real world phenomena, through pathways of automated solutions.

 The goal then of the industrious developer, worthy of such a task, isn't simply to automate them, but to express and quantify the culmination of their interworkings, as concisely and to the point as possible.

And here my friends, in hope of quantitative aim and pristine precision, enlie those algorithm analysis techniques making their famed debut, in helping us understand the behavior of an algorithmic process, as its functional data inputs either grow or shrink, contingent on its implementation.

Further, since our most prized innovators and makers of all the world's fancy, have leanings towards nomenclature mania - the glorious world of computer science, has coined such a feat, BIG O ANALYSIS - the algorithmic quantification of a program completion time scenario, pertinent to all processing of functional inputs, and algorithm design trends.

Simply put, in the grand scheme of things, Big Oh algorithm analysis is our best means yet, of forecasting a runtime approximation of an algorithm, hence allowing the seasoned and savvy developer to determine, in comparison to all possible algorithmic solutions, the best suited for a particular task over some other.

This process requires that we not only know both the preliminary and consequential steps involved in an algorithm design process, but that we also know the implications of efficiency within the resources consumed within its process as well - birthing what's commonly known as an algorithmic rate of growth.

Rates of growth help us determine whether the problem size of a number of functional inputs, are either growing or shrinking, doubling or being reduced, linearly, exponentially or even quadratically by some quantitative value, as the application is run successively - or in other words, helps us determine the runtime bound curves for which the program is run.

And since Big O runtimes signify mathematical worst case runtime algorithm scenarios, their derivations can be deduced by mathematical notation, as a function of input size n.

For example, we might say that 

BIG O 0<=f(n)<=Of(g)

Symbolizing  that the O (Big O), upper bound, or worst-case scenario of function f(n), is greater than the function f(n) itself, having an initial program run sequence greater than 0...for wouldn't it prove a challenge to run an application with 0 inputs or even 0 times?... OMNITEKK affirms such a quandary.

Likewise, we can't always consider or prepare for worst case scenarios now can we?...

Not to worry friends,  our mathematical symbologists have devised a few other runtime quantifications to best explain run time bounds as well - namely OMEGA, signifying the best case or lower bound for an algorithm growth rate, and THETA, an expression denoting average rates of growth, or convergences somewhere between Big O and OMEGA, which may be asymptotically written as -

OMEGA Ω =>  Ω 0<=f(g(n))<=f(n)

THETA θ   =>   θ f(n)<=f(n)<=Of(n)

We say that THETA is both OMEGA and BIG O since it's run time rate of growth indicates an average subset rate of values within a set of upper bound and lower bound runtime values.

For instance, if O(f ) = (n² ) and Ω(f) = (n) , then  θ  =  n², since n is also within the set of n² , and higher bounds reflect a greater degree of efficiency in evaluating  runtime values. 

As such, we prove either an upper bound,  average bound,  or lower bound growth rate from a variation of possibilities, by finding at least one initial input value n and constant c that proves for any subsequent values greater than or equal to those initial values, the upper bound, average or lower bound scenario is true.

 

We might then prove  that Of(n) = O(n) using the following example

f(n) 100n+5=O(n) 

by simply applying the asymptotic formula

0<=f(n)<=f(O(n)) n0>=0, and c1>= 105

=>100n + 5<= 100n+5n=105n <=105n<=105n,

for all n>=1, and c>=105.

We are equipped to determine the bounds of our application run times.

Similar methods of deduction can be used to find both OMEGA and THETA as well.

Likewise, we tend to prove average bounds by proving both upper and lower bounds within an application, with a subsequent representation of average case growth as the worst case, since both the average and best possible bounds are encapsulated within it, and we are usually concerned with worse growth rates anyways...with the exception of amortization or amortized growth rates, that prove asymptotic bounds in clusters of program functionality as opposed to analyzing their characteristics disjointly.

It should be noted that such an expedition is of rarity, so we usually only deal with BIG O runtime in analyzing algorithm bounds, besides select specialty applications.

And there you have it folks OMNITEKK'S rendition of Oh No, The Big O.

We hope you've enjoyed it, and until our next it adventures my friends, OMNITEKK says be well. 

POINTERS AND HANDLES

Where things are and how to access them, is of the essence in both the practical machine world of programming and technology, as well as within conceptualization of I.T. methodologies.

As such, HANDLES and POINTER addressing - not those Turkish delights stuffed inside your Thanksgiving bird, but rather, the method by which programmers utilize structural mnemonics within machines to allow for the assignment, accessibility, and processing of data to be performed as painlessly as possible, render some of our most prized automations.

So OMNITEKK, just what are POINTERS and HANDLES, and how do they work?

So glad you asked my friend... Let's "undress" such a concept shall we.

In the world of both functional and object oriented programming, POINTERS or object addresses, serve as the indexing means of accessing and computing or processing data values, both primitive, and user - defined, within your development environment.

These objects, or values might be functions, data types, structures, as well as volatile instances of file addresses declared, both at program run time or compilation.

So essentially, just as our neighbor's or family members know us by our name, POINTERS act as both explicit and implicit naming conventions, adorned with accessing and communicating with data objects within an application.

Likewise, each time an application runs, while the internal or programmer designated naming conventions of objects  - POINTERS also, appear the same, the machine compilations of programmer defined names, are assigned new or different addresses, giving credence to the commonality of POINTERS being coined DYNAMIC ADDRESSING MODES.

Now on to the fun stuff - handler or HANDLE addressing -  and no, OMNITEKK isn't referring to the ones from your run of the mill Friday night Martin Scorsese film, although the effects of such an I.T. concept prove oddly similar...

...however we digress, so let us continue shall we?

The main difference between POINTER addressing and HANDLES, is that HANDLES are usually static addressing methods, designed to access objects whose positional location within machines, or on storage medium doesn't necessarily prove itinerant, such as with files stored on tapes, hard drives, or disks, along with all other machine hardware storing information whose locational attributes prove a higher level of finality as opposed to volatility.

For instance, the addressing schemes of select data functions and variables within your application are dynamic, as each run iteration of your program assigns the internal program data structures new addresses, while the addresses of your actual stored program itself, is accessed by a HANDLE, as - while the attributes of the program, such as program file size, might grow or shrink as the program is modified, the housed file location of the application on disk remains the same, thus giving credence to the notion of a HANDLE accessor, versus a POINTER accessor.

A few take aways of note on POINTERS and HANDLES in helping you differentiate between the two is -

POINTERS are known as dynamic accessor types, while HANDLES are known as static types.

POINTERS usually reference things like data whose objects prove volatile, such as the assignment of data value objects which are destroyed upon program end, like structure addresses, and function addresses, while HANDLES typically reference static objects, such as data stored on tapes, drives, or disks, such as those rendered by your file system's page tables, or some other internal addressing scheme to access objects or data members where their accessor means prove higher permanence.

And there you have it folks, OMNITEKK'S rendition of the essential data access object definitions of I.T's glorious POINTERS and HANDLES.

And until our next I.T. adventure my friends, OMNITEKK says be well.

NOISE

 While OMNITEKK enjoys the sound of all things techy, there are a few sounds that pose significant conundrum or anomaly within the I.T. arena, especially where file processing and communicatory applications, as well as audio and telemetrical signal processing is of note.

The folks here bent on veracity of  nomenclature, like to call  such a phenomenon, NOISE -  a generalized term for anomalous or otherwise scrupulous interceptions within a machine's electronic data capture, storage, transmission processing, or conversion operations.

NOISE within most basic data processing operations prove significant risk towards both the predictability and usefulness of a machine to transport reliable information from hosts to target machines, terminals or processes.

And while there are several types of radio interferences or NOISES, a few of the most familiar ones are -

ADDITIVE NOISE - OR GAUSSIAN NOISE signals that obscure and even mimic the original or designed signal to be processed.

WHITE NOISE - A random signal or data packet having a variation of frequency at specified signal strength, such as in acoustic engineering telecommunications and statistical forecasting trends.

BLACK NOISE -  A significant random signal interference, like white noise, with the exception of a variation in signal strength within a specified frequency.

BURST NOISE - A type of electronic noise frequently used in semiconductors and microchips, along with gate oxides, and is also known as Random Telegraph Noise or Random Telegraph Signals as well as Popcorn Noise.

Burst Noise is commonly invoked by the trapping and release of charge or voltage carriers within relays or transistors, signifying defects within the hardware components within the manufacturing process, as opposed to the software processes, such as in grey noise phenomena.

So if your machine isn't functioning as it should, the culprit might just be NOISE, causing interference within your signal processing efforts.

In fact, almost all anomalous behavior within the machines of new where functioning is concerned, can be considered NOISE of some sort.

And there you have it folks, a new word to add to your library of technomenclature

YOU'RE WELCOME.

And until our next it Adventure my friends, OMNITEKK says Be well.

BEST OF THE BEST

 OMNITEKK just loves to help our technophile community thrive.

As such, we've compiled our best of the best "IT REFERENCE BOOKS EDITION", because who doesn't like the benefit of a good read doused in an array of "know how"...

And without further ado...

ENCYCLOPEDIA OF COMPUTER SCIENCE AND TECHNOLOGY

Charles Platt

Definitely OMNITEKK approved. This gem is seething with an array of I.T. and technical nomenclature, that all from the novice to the seasoned I.T. professional alike can make use of on their journey toward I.T. technophilia.

ENCYCLOPEDIA OF ELECTRONICS COMPONENTS

Harry Henderson

For all our electrical and hardware technicians needing to develop and sharpen their keen electronics jargon (pun intended), or even use this handy dandy book as a reference guide to their PC "know how" to troubleshoot common hardware anomalies, this book is for you.

MAKE ELECTRONICS 

Charles Platt

"Wowzers" to the makers of Make Electronics. This two - volume set is jam-packed with an array of nifty projects designed to help the twiddler, tinkerer, and creator of all things electronics on their way to innovation and creativity.

ARDUINO

Maik Schmidt

Everything from robotics to visual sensory machine projects can be created with this well-written and vividly crafted c-like Arduino reference book to help readers embark on an interesting journey of creativity and wherewithal.

POWERSHELL IN DEPTH

Don Jones

As the name implies, this reference book takes readers on an interesting journey of utilizing powershell command prompt directives to do just about anything in your windows environment, from database administration to simple, yet elegant task scheduling and more. Definitely a keeper and necessity amongst techies and I.T. administrators in the it field.

And there you have it - I.T. REFERENCE BOOKS SERVED.

So until our next I.T. adventure my friends, OMNITEKK says be well.

TWIDDLE ME THIS

 Time, or should we say clock ticks, are certainly of the essence where your programming tasks call for low-level rapid processing, such as in embedded and distributed systems tasks, along with all other performance critical software manufacturing projects.

As such, a sure-fire way to utilize or make use of your programming projects in the best way, is to use the omnipotence of bit twiddling hacks, along with a low-level language, like C++ or Assembly language.

This method of processing data within your programming tasks, allow for an array of integrated development environment (IDE) abstractions, that otherwise cause longer program run times to be constructed and run with significantly reduced instructions per cycle or instruction revolutions, making them cult favorites amongst industries ranging from Wall Street to the Artificial Intelligence boom alike.

Real-world bit twiddling applications can be found in cryptography projects, computer graphics, data compression algorithms, hash functions, and digital photo processing, as well as in aim of designing your very own low-level virtual machines.

So here OMNITEKK presents an array of useful bit-twiddling hacks to help you along the way.

 

http://graphics.stanford.edu/~seander/bithacks.html

Your Welcome...

And until our next IT Adventure my friends, OMNITEKK says be well.

BATTLE OF THE FLEXES

 Stacks Vs. Queues

To be or not to be, is the most pressing question when choosing a supporting data infrastructure as an accompanying module within your programming tasks.

And while both STACKS and QUEUES, certainly have their advantages and shortcomings, here are a few of OMNITEKK'S tips and tricks for utilizing either of them in your IT projects.

A few questions should be answered - namely

What Type Of Application Are You Designing?

While with a few tweaks here or there, either STACK or QUEUE data structure accompanyments can be used as possible solutions in your project's processing aim, each structure has its very own usage strengths.

For instance, we might use with efficiency, STACKS as a means of balancing symbols in infix to prefix conversions or vice versa, function call implementations, or in finding both spans or maxims within our projects or application. STACKS might even be used in page visited histories of web browser tasks.  

However, they aren't well suited to make the cut on auxiliary tasks such as in simulating first come first serve applications like job scheduling, ticket counter scenarios, or even the dreadful asynchronous data processes, tasked by most jaugernauts in IT, who use QUEUE data structures in such an aim.

Which Order Does Your Application Retrieve And Store Data?

STACK operation processes are used as LAST-IN-FIRST-OUT, or LIFO ( pronounced lye - fo) data structures by creating STACKS for processing, utilizing the infamous PUSH and POP operations, for such data tasks. 

So if your project or program is designed to retrieve the last file or process, or even program addresses stored within your coding tasks in reverse input order, then STACKS might serve you well to use.

However, if your application requires that information be processed in the same order placed, then QUEUES might prove best to use, as these are FIRST-IN-FIRST-OUT or FIFO (pronounced fy - fo) data structures, utilizing the ENQUEUE and DEQUEUE operations to store, handle and process information in sequential or priority of order.

And lastly, but certainly not the least - 

What Are The Performance Costs?

While both STACKS and QUEUES each have similar performance application processing times, they each of them present their unique sets of difficulties, given the program structure, along with all encompassing application factors as well.

Considerations such as the type of data being processed, or contingency of other nominal application factors, should all be factored within your program run times - which, while they mightn't necessarily increase the data structural run times for your application per say, they might certainly impact your overall program design within the culmination of context used within your application.

So do be sure to consider these facets when structuring your application, in determining whether to use either the LIFO structure of STACK operations, or those of QUEUES or FIFO  structures, when developing your next IT project.

And while you do, here's a few resources to help you along the way.

ALGS4.CS.PRINCETON.EDU/13STACKS

WEB.STANFORD.EDU/CLASS/ARCHIVE/CS/CS106B.1226/LECTURES/05-STACK-QUEUE/

And as always, until our next it adventure, my friends, OMNITEKK says be well.

HACKER'S DELIGHT...THE BAD AND THE GOOD

 Finding new and innovative ways to process information and automate tasks certainly has its rewards where ordinary computational tasks align with the eccentric enthusiast, who has developed the means of bringing both efficacy and industriousness to otherwise dull or autonomous processes, by invigorating them with the audacity of new.

However, we all know what happens when the urge to push innovation causes significant harm in the creativity process, whether unintentionally or by foe.

So here, OMNITEKK provides a few surefire ways to avoid crossing the lines between the bad and the good when using creative or otherwise 'out of the norm' methods of automating tasks.

Always follow language and protocol guidelines when engaging in design methods. This ensures that your automations are in compliance and inherence to all quality of standards within your specifications. Likewise, using codes and design principles outside of prescribed uses mightn't prove the best, as there might be legal ramifications or anomalous behavior in your prototypes or final designs.

When in doubt, leave it out. If you are unsure as to whether your design or prototype might cause unwarranted or unwanted adversity, either contact the provisional manufacturers and creators, so as to obtain the necessary licensures or simply leave it out. After all, a hack or tweak in a process proving unfit is sure to prove disadvantageous at some point, so save yourself the trouble and process any doubt by leaving it out.

If your design or automation stands to encroach on the liberties or freedom of someone else, such as an instances of unwarranted hacking, spying, or causing mischief otherwise, then you probably shouldn't be doing it. 

And while there are certainly ethical hackers, who serve to increase security measures, utilizing hacking and exploitative simulations that serve as pertinent means of improving functionality within some automations, doing so with malevolent intentions or desires might land you in vestiges you don't want, like in jail.

Give credit where credit is due. Even if you've utilized someone else's automation or design as the foundational principles of your creation, it is always best to give citation of reference to any and all authors or creators and manufacturers alike, who helped in the design of your project, even if only an inspiration thereof.

Have fun! As with all facets within the tech arena, The knack for innovation and creativity calls forth only the light-hearted and whimsical to utilize their means of cultivating quality craftsmanship of freakish oddity. 

So, OMNITEKK encourages you to have a little fun while seeking out and engaging in interesting ways to develop your prized designs.

And there you have it, A Hackers Delight has been served.

So that's it folks, until our next it adventure, OMNITEKK says be well.

THE FUTURE OF A.I.

The primary attributes of Technological Evolution -  namely Automations, Big Data, A.I. and Global Connectivity have helped shape our world in ways imperceptible, as we shift further from the manual vestiges of workflows to the automations of new, imbuing us with higher efficiency productivity workflows, and most of all, more connectedness.

So we here at OMNITEKK present an IT delight to all our technophiles, both near and far, with keen curiosity of the future of automation and its implications in the years to come...enjoy!

And until our next IT adventure, OMNITEKK says be well.

Round And Round

Death To Reduncy should always be the aim of the programmers of new, who seek to transform not only the ways in which to write sufficient code, but who seek to write great code, in an effort toward becoming the IT Rock Stars OMNITEKK is sure they are.

Recursion then, is an essential factor in this process, as it reduces both the time and complexity within the application development process, while also allowing designers to reuse programming functionality in the best way possible.

The primary tenets of recursive programming techniques, include utilizing either a single thread or likewise, some variation of threads within a program to carry out a specific function.

These threads communicate critical information back to the originating thread or function, to utilize it a number of times until some base case is reached, usually signifying program or function end.

In essence, recursive solutions carry out a set of instructions by back tracking within the same function.

This technique is especially useful in simplifying repetitive tasks or tasks that require the same functionality and actions to be executed within a program.

Likewise, each rendition solves the automated process by calling itself with a slightly simpler version of the original problem within a sequence or subset of functionality.

Recursive Programming Solutions are typically shorter to write and easier to read than programs designed with repetitive functions or those constructed using iterative methods, with both practicality and usefulness in solving the following types of solutions - 

Fibonacci Series and Factorial Finding

Merge Sort and QuickSort Sorting Functions

Binary Searches

In - Order, Pre-Order, and Post Order Tree Traversals

Depth First Search and Breath First Search Graph Traversals

Dynamic Programming Algorithms

Divide And Conquer Algorithms

Backtracking Algorithms

So why not declutter your applications by utilizing the power of Recursion, to both simplify and add a level of efficiency to your projects.

As you do, you'll know that recursion is everything in solving your repetitive tasks.

 

And that's it folks, The Power Of Recursion has been served.

Until our next it adventure my friends, OMNITEKK says be well.

The Strength Of One

 There are so many different languages, protocols, and likewise specifications to be rendered within the IT world of new, that if we aren't careful, we mightn't have the chance to procure our rightful place amongst the subject matter experts within our field, and instead, hold rank amongst the 'jack of all trades, master of none' communities of developers who never quite make the cut where technical expertise is required.

As such, instead of perusing the web or even your local newspaper, in search of the latest tech fad, language structure, or workforce requirement in hopes of landing your next it adventure, OMNITEKK suggests that you hold on to those 'Oldies but Goodies' in the poly-functional programming arena, so as to develop a well-rounded understanding of a single tool so you might utilize the very same core principles within an array of applications. 

Here's Why...

Whether we know or care to even quandary, there are very few changes within the structural and functional facets of today's machines, giving credence to the 'tried and true' principles of both application design, and the developmental foundations handed down to us by the founding fathers of IT.

 So all the new languages, technologies, techniques and specifications alike, can confuse and regress  even The savvy-ist developer, as we take aim in learning or satisfying all the technical jargon out there.

 

To avoid such a fate, we suggest you learn one primary poly-purpose programming language and learn it well!

 

This serves two-fold to help you grasp the key concepts of specificity within the language, while also serving to help you develop the technical talents necessary to master the competitive specialized areas in both functional and object oriented development alike, so as to apply these principles, once fully understood, to a new language or specification later on.

Development principles such as the various protocols and layers within our machine's developer environments function pretty much the same way they were originally designed to, with miniscule exception in capacities of hardware.

So languages and the frills of technical jargon, can cause us to get lost in translation if we focus too much on them, as opposed to the underlying protocols involved in developing our programming talents.

Further, to master anything you simply have to go through the till and toil, not just to learn the essential programming core principles, but to learn them well.

There is simply no way around this one my friends.

For we've encountered plenty of 'copy and paste' developers (we were once them ourselves), who fall short in developing their tech talents, as they haven't really taken the time to learn what is needed to become the IT Rockstars they have the potential to become.

So, while there are certainly a plethora of IT know-how on the web, and shortcuts in the learning process to be had, YOU MUST DO TO LEARN.

And once you've chosen your poly-purpose language of choice, why not take it to new heights, by using it to delve into each layer within the OSI model (granted you've chosen your language wisely), to fully immerse yourself in its capabilities.

This will help you in ways imperceptible, as you gain the advantage of, not only utilizing a language that can handle just about any processing task your creative workflows might entail, but you also gain advantage in learning the specific techniques involved in utilizing your language in all its designations.

Oh yeah, and do be sure to learn with due diligence those pesky Data Structures. 

We promise you'll thank us later.

So get programming our friends, and do have a bit of fun while you do, because what's in the doing if we can't have a little fun while doing it... right?

And that's it folks, The Strength Of Learning One Language Well has been served! 

Until our next IT Adventure,  OMNITEKK says be well.

BEST OF THE BEST

 While it is certainly true that the famed all out technology books of new and old, encompass an immeasurable sum of invaluable information, there are lesser known truths of hidden pearls to be found within the deep vestiges of those good reads with seemingly entertainment attributes, imbued with the surprising benefit of educational facets.

And that brings us to yet another rendition of our 5 BEST OF THE BEST delights - AUDIOBOOK EDITION.

And without further Ado.

Dan Brown - ORIGIN

While most fictional books enthrall readers with a surprisingly vivid aire of fantastical adventure in their story lines, a favorite author of OMNITEKK, Dan Brown, supplies readers with a pleasant culmination of both fact and fiction, which proves quite educational to the unsuspecting listener.

Origin sets both the stage and our unending interest in the IT world of Artificial Intelligence in this hit thriller.

So be sure to check it out as it is definitely a cult fave.

Marcus Du Sautoy - THE CREATIVITY CODE

If you love numbers like OMNITEKK does, then this books for you!

The Creativy Code takes an introspective delve into the world of pattern recognition and algorithmic programming from a quite surprising and eloquently woven fabric of exploratory research on the subject of new age IT concepts. So do read,,or shall we say 'listen' on.

Gerard O' Regan - A BRIEF HISTORY OF COMPUTING

ABHOC takes listeners on an intricate journey down computer lane with both the detailed origins of the machine along with a few other interesting facts of how we derived from the manual processes of old to the automated computational processes of new. ABHOC is certainly OMNITEKK approved.

Neil Postman - TECHNOPOLY

A true gem, Technopoly is a listen for the ages. 

This book is shroud with some of the most phenomenal facts there is surrounding the Artificial Intelligence revolution.

It seemlessly helps listeners connect the dots regarding all the AI concepts necessary to gain both a well rounded understanding of our most pressing AI phenomena, along with a few trivia points on some of the jaugernauts in the IT world.

David Auerbach - BITWISE

If you're a bit sketchy on some of the specificities of specific fields in conjunction with IT and Technology, then BW might be for you.

This book is sure to take listeners on a bumpy ride into the technological arena from the prospective of the author's venue of creativity and base of understanding.

And that's it folks, we hope you' ve enjoyed our walk down IT AudioBook Lane, and until our next IT adventure my friends, OMNITEKK says be well.

Developing Algorithmic Processes

If someone asks you how your day was, you daren't simply say only "was" or "it"... in answer right?

..well my friends, in the complex simplicity of Algorithmic Processes, it becomes this trend of specificity in how we shape, like our answers to the questions of others, both our thinking around the solutionary means we use in solving some of our most complex algorithmic puzzles and likewise, the chronology of steps taken to derive at such a course of action.

The Algorithmic Processes we use to solve our most pressing computational phenomena, require that we observe with precision and stringency the instructions involved in formulating solutions to our automation tasks, such that, we ensure the step by step instructions, produce our aim in outcome.

Otherwise, we might find that even our most well intended efforts fail to yield the functional outputs of our programmatic inputs....and unbeknownst to us we've officiated the unintended production of what I like to call, gobbly gook...warranting hours upon hours of refactoring what we believed to be the solutionary algorithm to what we were trying to accomplish when in fact it proved sketchy at best.

And here fellow technophiles, enlies the critical nature of developing algorithmic thinking, or those definitively outlined sets of instructions and processes used to program 'the machine'.

And as you sharpen these talents, here's a few pointers to help you along the way.....

Pontificate... Pontificate... Pontificate

We each of us speak and function from within the realm of our thinking trends, so a good measure to be taken with aim to improve our problem solving, information processing and algorithmic derivation talents, is in none other than the way we speak.

Hence, we should aim to always speak with precision and in verbose chronologically modulated  ways. 

This helps us to develop the knack for our thought to speech and subsequently, functional productions of interpreting, processing and developing algorithmic methods in our programming tasks.

Write...Write...and Write Therein

Some of us programmers, OMNITEKK included, fail time and time again to write down the processes involved in solving our IT tasks. 

We can't express enough how imperative it is to develop the habit of writing down, even if only using pseudo code, the step by step processes taken to develop your algorithm.

This helps even the most seasoned programmers to utilize trends and functional processes in writing your codes.

So we task each of you with developing the wise and prudent ways of some of the best to ever do it in the IT world, by writing down the steps taken on your algorithmic journey.

Reading Is Definitely An Essential Cornerstone

There is so much to be had in reading and learning the ways of efficiency in algorithmic puzzle solving from the juggernauts in coding, who might certainly imbue us with a few tricks of the trade in developing structural solutions to our automation tasks.

There is no reason to reinvent the wheel if we don't have to.

As such, so many of our most pressing programming tasks have already been explored, with some even proving to encompass a few prized techniques and interesting solutions to be explored, used, and dare I say, improved upon hidden within the deep vestiges of books.

So do read and read quite often to improve upon your problem solving and algorithm developing talents.

Join Online Support Communities

We are currently in the information age - although, being the audacious and brightly lit tech community you are,  we're quite sure you already knew this.

So do take full advantage of all there is to be had in the online Communities of Techies and IT Enthusiasts, along with their arsenal of information on some of your most pressing programming tasks.

There's an overflowing supply of solutions and fully constructed applications and even live folks who can help you along the way in developing your algorithmic tasks.

Fail and Fail Til You Get It Right

None of us are perfect in what we do. As such, one of the best ways of improving upon our talents lie in the process of learning from our failures.

For if at first we don't succeed, we must try and try, and try again.

It is in this process that we learn all the ways that what we are trying to accomplish simply doesn't work.

And while you do, OMNITEKK suggests you utilize the previously listed tasks to help you along the way.

And that's it folks....

.... we hope you've enjoyed our walk down Developing Algorithmic Processes Lane. 

And until our next IT adventure my friends, OMNITEKK says be well.

Decision Trees

To be or not to be is the primary question to be asked when constructing the glorious Decision Trees that help with the processes involved in deterministic statistical decisions based on branches taken from attributional qualities of population or sample data.

 

As functional inputs are processed within an algorithm to determine a probability of distribution, the key constitutional factors of specificity within the sample are used to branch on the likeness of an attribute or quality.

 

For instance, given the defining attributes of an item compared with some other item of distinct, yet similar qualities, the decision tree algorithm is designed to utilize differential groupings to branch either left or right to associative nodes or leaf representations of specificity.

 

Where there is otherwise redundancy or ambiguity in the selection process, the algorithm must then be pruned to ensure the integrity within the branching and algorithmic decision taking.

 

Decision trees have significant use in Search Engine Optimization (SEO), Categorical Determinism, and Finding Similarities and Trends within groups of information such as in fields of Artificial Intelligence as well.

Source 

The primary structural attributes of Decision Trees are as follows….

 

Nodes – Nodes are the attributional qualities of a distribution of variation. They entail the defining characteristics within a decision or branch to be taken.

 

Branching – Each decision to be made pertinent to a specific attribute, is the culmination of branches within the sample. For instance, from the picture, we can easily determine each branch or decision as either a left or right…yes or no traversal for each item of variation.

 

Splitting – The attributional qualities to be chosen within a sample are the qualities which are split to best differentiate the accrual of specificity within the sample.  predecessor data relative to successor nodes are disintegrated so as to distribute key structural characteristics within the item or distribution.

 

Stopping – Leveling of tree information is essential to subverting over-complexity within tree structures. As such, designers must vigorously construct the decision levels in such a way as to preserve the integrity of data representations. This is where the concept of stopping or leveling is best implemented.

 

Pruning – As trees are constructed, information or branch redundancy might actualize, effectively decreasing both efficacy and precision within the tree structure. The notion of pruning, or restructuring nodes, and branches where necessary serve to maintain data and attributional tree integrity.

 

As the digital information age advances, the uses of Decision Trees gain further uses within IT as well as mathematical and statistical fields. They allow staticians, programmers, data miners, and data enthusiasts alike, to effectively group, differentiate, and determine viable connections between the vast collections of information being processed, serving to forge higher efficacy in both structural data collection and methods in developing analytical tools.

OMNITEKK hopes you've enjoyed our walk down Decision Tree Lane, and until our next IT adventure friends, be well.

 References

 

SOFTWARE DATA COLLECTION TRENDS

In the glorious world of IT and computing, programmers must always find efficient ways to collect application data, such that software, hardware or interface errors, can be easily and efficiently subverted, essentially allowing the application to function as designed. 

Efficacy in methods for software improvements are also a very necessary attribute of the software development life cycle.

And while there are a significant number of data collection and reporting methods that serve to seamlessly allow developers to recognize and report anomalous behavior, there are certainly a few surefire ways to make the best use of such trends...

...Let's have a look at OMNITEKK's faves shall we.

Application Services

One of the best ways, your PC ensures that applications run as they should, enlie in the background processes that run alongside your most sophisticated applications, serving as a primary means of tracking anamalous behavior, serving as a proficient data reporting mechanism, and an applications recovery mechanism as well.

We've all faced those pesky software anamalies, where our application's built in recovery methods saved the day in our aim of data and workload recovery...haven't we?...

...this my friends was none other than your applications background manager and software services at work.

Manual  User- To- Designer Messaging

While some of the best to ever do it in the marvelous world of applications development, have devised efficient ways to ensure that your software application functions as designed, even the brightest of developers don't always account for all anamalous behavior.

And this my friends, is where avenues for end,- user manual data and application reporting reign supreme.

A well designed application should always have a manual method of data collection and reporting, that allow for both atypical applications behavioral trends, along with evolutionary provisions in the development life cycle process to provision pertinent data messaging to be sent to applications administrators where necessary.

The art of elegant  software design, such as in  manual user developer communicatory methods, not only help with applications improvement methods, but they also take your application from good to great in your design techniques.

Data and Application Recovery

An applications ability to recover from anomalous behavior, by way of either autonomous data save methods or even server- side cloud data storage facilities, allow end users the luxury of worry free data recovery methods in the event of anomaly or application fault.

Interactive Troubleshooting

A sure fire way to narrow down anomalous applications behavior lie in your software's means of either an autonomous design process of specificity, such that your application itself can provide detailed information where necessary, or by way of end-user provisional question-answer (Q&A) methods that allow for time efficient precision troubleshooting to commence.

Data Analysis and Metrics 

An application's Development Lifecycle Process (DLP), should almost always contain some sort of data trend methods that allow for software improvements to occur seamlessly.

This is where data analysis and software expansion measures work best.

They essentially take the guesswork out of those  critical data trends that help developers improve their  software design aim, thus allowing the  autonomy of statistical processes to highlight data  use-case  scenerios.

An application is only as good as it's measures of staying above the curve in the evolutionary process from concept to design, to end of life and rebirth in functionality and version.

As such, it becomes a critical measure in the software design process to ensure that your application can utilize efficient data collection methods to ease the process of improving software functionality, as it is our aim to help our technophile community take your design projects from good to great.

We hope you've enjoyed your walk with us down Data Collection Trends Lane...

..and until our next IT adventure OMNITEKK says be well.

AND THEN THERE WAS THE COMMAND LINE

How easy it is for the programmers of new, who daren't delve into the complexities involved in the deep of the command line, instead opting for the ready-made applications compilers and enhanced linker functionality pre packaged within most Integrated Development Environments (IDEs), such as Visual Studio, NetBeans, and JCreator, to name a few.

And while there is certainly a level of ease and flexibility in allowing your IDE to compile, link and parse the necessary libraries and files for you, so your best creations can come to life, it has always proven talent enhancing when developers and end users alike, utilize the, dare I say, plush features of the command line along with utilities like PowerShell, the Linux Shell and MakeFiles to manually link, compile and access interface free application functionality to process most of your software design needs.

So here's a few tips on navigating your way around the glorious command line in manufacturing application executables as well as utilizing most all functionality that can be accessed using Software Development Tools and Graphical User Interfaces.

Compiling And Linking Software Programs

The command line and it's application integrations should be your best friend when it comes to utilizing it's functionality to compile and link your software projects. 

And while there is certainly a learning curve involved, the reward of learning how to utilize command line arguments to process your programing projects, far outweigh the time it takes in learning them.

Most Integrated development environments include an abundance of command line tools that allow programmers to test, debug and run projects same as the visual controls within your most prized application user interfaces.

You can usually find your software application's developer manuals, containing instructions for command line parsing on the manufacturers official website.

Applications Administrative Tasks

The command line, along with your operating systems shell command application can be used to install software,  access system and disk information, schedule administrative tasks, as well as delve into application accessibility functions, and the utilization of specific disk and User Account Control (UAC) tasks also. 

Worthy of note is that most of them are also imbued with a few 'easter eggs' also...making OMNITEKK'S technophile explorers quite pleased in their finds of undocumented machine functionality.... So Happy Hunting.

Interprocess Communication(IPC)

Unbeknownst to most entry level developers and PC casual users, most software applications provide comprehensive functionality and integration tools that allow them to be seemlessly consumed within differing application ecosystems, all from using command prompt IPC directives.

Interprocess Communication tasks allow seasoned developers and enthusiastic learners alike, to utilize all there is to be had in integrating the richness of functionality within most of your prized applications in other software environments.

So be sure to visit your software application's website for the latest information and tutorials, along with developer manuals for your project design needs.

As self-proclaimed technophiles, we encourage our OMNITEKK community to explore the vastness of your PC and application's functionality. So, again do have a look at your applications developer site for up to date information and all the vainglorious how-to's therein.

And until our next IT adventure my friends... OMNITEKK says Be well.

CODE REFACTORING

In the glorious world of applications and software development relative to the DEVELOPMENT LIFE CYCLE, most software is only as good as it's ability to keep up with the times, or in other words, it's expansion and evolutionary processes of improved functioning.

And if you're wondering how best to accomplish such an aim... OMNITEKK believes applying CODE REFACTORING principles is the sure way to go.

A development project's ability to be transformed into a higher efficiency or expandable solution is the quintessential pearl of code reusability, as use cases and user requirements take shape in the evolutionary design process.

Likewise, in improving our application project's efficiency and expansion capabilities, whether it be in aim of user interface improvements, connectivity enhancements, or simply a measure of ease of use or some other task of increased efficiency, we could never go wrong in applying those tried and true principles adopted by all the greats, in the world of software design, who have standardized the processes of code improvements.

So here's a few pointers on best practices for improving your development projects.

APPLY USE CASE SCENERIOS

It's always a good idea to create use case scenerios which signify your projects usage goals for both end user and designer or administrator data input and extraction tasks.

Employing use cases as your project requirements change, allows for concise application of your design objectives to commence in expansion of your projects, to seamlessly integrate with those modules that might already be there.

USE MODULAR CONSTRUCTION

Code should always be constructed in modular fashion, such that all major functionality, is provisioned in such a way that refactoring or code improvement efforts serve easier to engage in and manage, by breaking down your project scope into its lesser chunks of functionality.

This is especially pertinent if a specific task or function is used more than a few times.

DOCUMENTATION IS YOUR FRIEND

All code segments should be well documented, especially If you've written fairly large projects or if it'll be months long intermissions between commencing your workload, as picking up where you left off can be a challenge. 

Chances are you won't even recognize most of what you've written, much less every nook and cranny relative to it's functionality, if you've neglected to work on your projects for months at a time.

So it's always a good idea to document code and keep concisely defined project attributes relative to code functionality...such as variable names and uses, any special definitions as well as any and all module functionality or methods use or purpose.

OMNITEKK recommends you do get used to documenting and the art of documenting well.

MAINTAIN REVISION HISTORY

We've all dealt with the delightful bug hunting journey in delving into our most pressing software projects, haven't we...

As such, it is critical that we can seamlessly revert any upgrades or project changes commenced, in the event that something goes awry. So be sure subversion ALL revisions. 

Have a look at our article on SUBVERSIONING APPLICATIONS which can be found here.

THINK SIMPLICITY

When it comes to code reuse and refactoring or enhancements, less complexity in design might prove best.

Simplicity in design ensures that your projects aren't overly complicated. This is especially critical if the application or project is a group effort.

As we learn to design elegant, yet simple application solutions, it allows the refactoring process to commence with ease and efficacy.

And after all, who doesn't just love development projects that are simple in understanding and programming style, even if complex in functionality...

And that's it folks, OMNITEKK'S sure fire way to effectively apply code refactoring principles to your projects, both small and large alike.

So until our next IT adventure my friends, OMNITEKK says Be well.

THE BEST OF BOTH WORLDS

As we bear witness to what some are hailing as the 4th industrial revolution, OMNITEKK proclaiming rightly so, the noteworthy advances being actualized within the technological arena are vastly shaping the world as we know it.

With personal aim in both ease of use and practicality of application in our daily tasks, the world of technology has allowed for the manifestation of some of our greatest achievements yet.

Likewise, without the specialized contributions of those well noted programmers, developers, staticians and mathematicians alike, we mightn’t have ever made the strides we have in such fields as 3D  Printing, Virtualization, Manufacturing and Industrialization, Automation, Astronomy and Astro-Theology, Agriculture, Aviation, Weapons and Defense, Communications, Transportation, and the list goes on and on.

And it is without a doubt the collection of value to be found in the prized contributions of our programmer communities in developing the sophisticated algorithmic solutions used in the technologies of new, that have allowed products like the IBM Watson, Utility Robots or even the dynamic duo of collaborative effort between human and robot being witnessed within Cobot productivity tasks, amongst all others, to even exist. 

And although we are witnessing the brilliance of today’s innovators in tech, there are certainly a few questions to be answered relative to how such advances will ultimately affect our human evolution...5 years...20 years or even a century from now, and how best we can prepare for such an affect now. 

For just as the industriousness of old has been widely known to strengthen human productivity efforts, the  strides made in such fields as industrial  manufacturing, for instance, also gave way to higher CO2 emissions, as well as an overabundance of waste and waste materials, causing imperceptible eco-systemic pollution and subsequently both an adverse effect within human mortality rates along with an overall imbalance within nature's cycle of functioning.

As such, many argue that as advances in technology increase, the obsoletion of human contributions, namely within manual labor fields, will decrease significantly, ultimately making those labor practices repurposed through the use of technology, ineffective in the aim of big business and the enterprise, phasing out all those who haven't the talents necessary to successfully apply the required adroits to supply the evolution of workforce demand.

Let us take a deep dive in considering both the effectual benefits and possible anomalies surrounding such advances, namely collaboration and integration versus comprehensive automated solutions in fostering human productivity efforts and ease shall we.

The Primary Areas Of Recognized Benefit

Productivity Enhancing 

The formation, creation and human productivity enhancements realized from advances in technology have allowed us to work smarter, not harder.

With some of the most effective discoveries, and thus, significant contributions to the aforementioned fields, advances in automation and technology have allowed our human family to realize successes unfathomable in both our personal and professional productivity tasks.

Technology have allowed us to better understand the world around us, through land air and sea exploration.

Through the use of technology, we have acquired access to knowledge and information, as well as the keen ability to draw inferences, correlations and connections never to be done before, as the brilliance of our most talented, have devised the means to centralize pertinent findings, research and innovations, so as to help us progress in our human understanding and solutionary application to some of our greatest quandaries.

Human Risk Subversive 

The use of technological apperatus, such as robots and various other technical devices have allowed man to accomplish the once deemed impossible by successfully thwarting risk factors by substituting machinery where human anomaly once proved evident.

Technology has all allowed for significant advances in science to persist in the face of well known hazzard by utilizing the efficiency of mechanics in achieving scientific breakthroughs in both health data metrics and analytics, along with advanced methods of enhancing mortality, and thus, human longevity.

Technological Affect 

Diminishes Human Functioning

While the uses of technology and artificial intelligence means have certainly allowed for significant strides in both human innovation and productivity, it has been pontificated that over reliance on automation has made man lazy. It becomes the overuse and subsequently, the imbalance in using human mechanics to replace those human autonomous tasks necessary to maintain our own human abilities and efficiency attributes, that pose significant risk. 

For instance, while it is possible to store information, now in the yottabytes for later retrieval, heavily relying on electronics to do miniscule repetive tasks is known to have adverse affect on our own  inherent data storage and retrieval efficiency.

To prevent such anomaly, it is always best to utilize our own process of derivation where necessary to maintain efficiency in functioning.

Diminishes Manual Labor Efforts

All those from the generation x era who are either entering the workforce or in process of making contributions therein, might face significant learning curves, as the age with which the workforce demand was best suited for their talents, are vastly becoming obsolete, making manual labor talents within certain fields fairly difficult to obtain employability within.

The new age workmanship and worker necessity is in fields that demand an enhanced aptitude for technological savant in place of routine manual labor talent, making it far more difficult for older generations, who typically have less practical knowledge in STEM fields to attain the levels of success of the millennials who do.

So to bring us full circle, on the question of whether collaboration and integration in the world of AI should be implemented moreso than comprehensive automated solutions, OMNITEKK affirmatively votes for the collaboration of human automation hybrids as opposed to extensive uses of automations in a given field. 

It not only prevents the effectual phasing out of human manual contributions to the workforce, but it allows us to use the technology in ways that enhance the benefits of both worlds...the culmination of efficiency and prowess within the technological arena and also the tangible  human side of accomplishing both our personal and professional productivity aim.

In short... OMNITEKK supports the implemention of COBOTS that work alongside human productivity efforts within the workforce as we advance by leaps and bounds in STEM fields. 

And until our next IT adventure friends... OMNITEKK says Be Well.