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The Marketplace Maturity Model by @McFadyenDigital

The Marketplace Maturity Model by @McFadyenDigital | technologies blog | Scoop.it

The Marketplace Maturity Model SM (MMM) is an industry-first model for Ecommerce operators to providing a reliable guide for implementing or iterating an online marketplace.
The Maturity Model is comprised of 5 major stages, within each stage are actionable steps across advisory, technology, and business considerations. 


Via Farid Mheir
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Farid Mheir's curator insight, October 24, 3:16 PM

WHY IT MATTERS: looks like marketplaces have become a "thing" and merit their own maturity model. Given inherent complexity I guess this is warranted. Plus McFadyen are most experienced, they should know.

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The best Linux apps for Chromebooks

The best Linux apps for Chromebooks | technologies blog | Scoop.it
Make your Chromebook even more capable with this carefully selected set of Linux apps for expanding Chrome OS's potential as a business tool....
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How to get exponential growth in a shorter period of time?

  How to get exponential growth in a shorter period of time? Introduction The breach among the digital, physical and biological worlds is dwindling rapidly. The technologies are shifting faster than ever. These are the two reasons which make difference between Third and Fourth Industrial Revolution. Technology is constantly evolving & changing which is challenging traditional business models, and it is now happening at a quicker pace and in ways that can be difficult to anticipate & visualize. Next wave of industry 4.0 It would be along with unstoppable forces that disrupt everything. We are passing through the 2nd wave (2016-2025) of industry 4.0. We will have to embrace the following ongoing trend of technologies’ Artificial intelligence The Artificial intelligence (AI) is validated through machines different from the natural intelligence demonstrated by humans. This is skill of system to rightly understand the data, to acquire from such data and to practice those studies to attain exact objectives and jobs. Several AI algorithms are accomplished of learning from data. AI techniques have practiced recovery next parallel developments in computer supremacy, big amounts of data, and hypothetical understanding. The AI techniques have become an important share of the technology industry. It helps to resolve various challenging problems in software engineering, computer science, and operations research. Block chain The Block chain is strength for new type of Internet. It is a just a digital ledger of financial transactions which may be automatic to record not fair monetary transactions but nearly everything of value. This shows a rising list of record called blocks that are linked using cryptography. Today’s most industries like IoT, insurance, education record, voting, charity, government, health care, and retail may be disrupted by the Block chain. Block chain was the means and the decentralization was the idea. Quantum computing The Quantum computing practices definite algebraic methods to improve algorithms for computations. These algebraic methods are the ones or in parallel to the ones that are useful in quantum mechanics. Quantum reproduction could also be used to pretend the behavior of atoms and particles at uncommon conditions such as the reactions inside a collider. Cloud Computing It is the availability of computer system resources particularly the data storage. Data centers for users are available on internet so the term is used to describe those data centers. The cloud computing believe on sharing of resources to accomplish unity and thrifts of scale. The aim of cloud computing is to permits users to take advantage from all of these technologies, without the necessity for bottomless information about or knowledge with each one of them. The Cloud computing practices concepts from service computing to provide metrics for the services used. The Cloud computing goes to address quality of service and reliability problems of other grid computing models H2M Robotics Robots are machines skilled of functioning automatically for a compound series of actions. The H2M Robotics in future, by developing the robot, EPCOs will utilize it on live high voltage line to (1) decrease the power outage, as well as operation and care costs, (2) save resources and time, (3) prevent the electrical interruptions caused by contacting trees and animals with overhead lines and (4) increase the power network reliability, significantly. Energy storage This is the detention of energy formed at one time to consume at a future time. Technologies provide short-term and long term solution for Energy storage. Energy storage contains changing energy from systems that are tough to store to more suitably or carefully storable forms. The control of waterways to drive water mills for processing grain or powering machinery is a classic application of energy storage before the industrial revolution. Developed countries have made a great progress by embracing these technologies to boost their economies. We are way behind the developed countries. Mark Frissora, Ex-CEO The Hertz Corporation truly said "When a new technology emerges, companies need to decide almost immediately whether to adopt it or they could risk being destroyed by it." Issue and Concerns Various authorities advise for a "winner-take-all economy," where high-skilled employees are salaried with high pay, and the rest of workers are left behind. Investment firm UBS report in 2018 established tycoons have determined nearly 80 percent of the 40 main development innovations over the past four decades. Schwab forecast in 2016, disparity would be the utmost societal concern connected with the Fourth Industrial Revolution. Industry 4.0 strategy for developing countries Andrew Ng (Computer scientist, businessman and writer) has suggested a brightest strategy for developing countries that have dropped behind in the technology competition. The idea is to skip over the intermediary technologies and leapfrog into the future by implementing technologies of industry 4.0.. It is quite possible to attain exponential growth in a shorter period of time with this approach. Leap frogging strategy Actually it was a military strategy during World War II working by the Allies in the Pacific War against the Empire of Japan and the Axis powers. The significant idea is to bypass deeply encouraged enemy islands instead of trying to capture every island sequential en route to a final target. The reasoning is that those islands may just be removed from their supply chains rather than demanding to be overcome by larger force, therefore acceleration the development and reducing losses of troops and substantial. Leapfrogging strategy would permit the United States militaries to extent Japan rapidly and not spend the time, manpower, and supplies to capture every Japanese-held island on the way.
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Industry 4.0: Robotic vacuum cleaner

Industrial Internet of Things (IIoT) The industrial internet of Things (IIoT) states to connected instruments, sensors, and other devices interacted together with computers' industrial applications, including manufacturing and energy management. This interconnection permits for data collection, exchange, and analysis, possibly easing developments in productivity and efficiency as well as other economic benefits. Technologies empowered IIoT The technologies which empowered IIoT are included: Cyber-physical system, cloud computing, edge computing, machine-to-machine, 3D-printing, robotics, Big Data, Artificial intelligence and machine learning. Layered modular architecture The IIoT systems are commonly perceived as a layered modular architecture of digital technology. The Content layer consists of User interface devices for example screens, tablets, smart glasses. The service layer refers to the applications, software to analyze data and transform it into information. The Network layer comprises on communications protocols, WiFi and cloud computing. Final layer called Device layer consists on Hardware: CPS, machines and sensors. Frameworks and standards The Internet of Things frameworks benefit provision the communication between objects and consent for more complex structures like distributed computing and the development of distributed applications. MQTT MQTT is a publish/subscribe protocol particularly suited to IoT applications thanks to its small footprint, real-time guarantees, and suitability for use in high-latency, low-throughput, and unreliable networks. It is designed for connections with remote locations where a "small code footprint" is required or the network bandwidth is limited. The publish-subscribe messaging pattern requires a message broker. Kafka Based on a publish/subscribe model, Kafka is one of the most widely used platforms to process and distribute real-time data streams. It is used for building real-time data pipe lines and streaming apps. It is horizontally scalable, fault-tolerant, wicked fast, and runs in production in thousands of companies IBM IBM has announced cognitive IoT, which combines traditional IoT with machine intelligence and learning, contextual information, industry-specific models and natural language processing. Node-RED This is open source software designed by IBM to connect APIs, hardware, and online services. OPC This is a series of standards designed by the OPC Foundation to connect computer systems to automated devices. Benefits of IIoT • Efficient and cost-effective production. • Likely of growth by implementing IIoT is predicted to generate $15 trillion of global GDP by 2030. • Technical Optimization • Reduced Wastage • Better Business Decision Applications Car manufacturing: Use of IIoT in Automotive industry indicates the digitalization of all elements of production. Customization of vehicles is also enabled by IIoT due to the modularity and connectivity of this technology. IIoT makes conceivable to connect production plants to each other for automotive manufacturers companies. Oil and gas industry Big volumes of raw data can be stored and sent by the drilling gear and research stations for cloud storage and analysis with the care of IIoT. The oil and gas industry has the ability to connect machines, devices, sensors, and people through interconnectivity, which can help companies’ better address fluctuations in demand and pricing, address cyber security, and minimize environmental impact with the help of IIoT technologies. The IIoT can progress the maintenance process, the overall safety, and connectivity. Drones may be used to detect oil & gas leak and to identify weak spots in complex networks of pipelines with built-in thermal imaging systems. Agriculture The IIoT benefits farmers to make decisions about when to harvest. Sensors collect data about soil and weather conditions and propose schedules for fertilizing and irrigating. Microchips into animals are being implanted by some livestock farms to trace their animals and pull up information about the lineage, weight, or health. Robot Vacuum Cleaner Using IIOT & AI Technologies Robotic vacuum cleaner has intelligent programming and a limited vacuum floor cleaning system. The unique design included manual operation via remote control and a "self-drive" mode which is suitable for machine to clean freely without human control. Some designs use spinning brushes to reach tight corners, and some include a number of cleaning features along with the vacuuming feature. Robotic vacuum cleaners are more suitable to use because they can vacuum on their own as compare to a regular vacuum cleaner. There handling is also very easy as they can be kept under beds or desks or in storerooms. Main features of robotic vacuum cleaner • A fully autonomous robot vacuum cleaner which can navigate inside any building using IIOT sensors & AI technologies. • The robot can be configured using a tablet PC. • In 2015, Dyson and iRobot together familiarized camera based mapping. • CEO iRobot Corporation of America claimed that 20% of vacuum cleaners sales worldwide were robots in 2016. Cleaning modes Generally, robotic vacuum has following different types of cleaning modes; Auto: This mode is helpful for general cleaning. Usually, the mode cleans a space until the battery runs out. Spot: with the help of this mode, the vacuum focus on a particular dirty zone. Turbo: This mode is used to clean and pick up the most dirt and dust, but it may create noise. Edge: This mode helps to clean edges & corners. Quiet: The mode helps to reduce noise levels while cleaning. It's helpful when you are at home. Remote control: It allows the user to control the direction of the vacuum. Wet cleaning Some models may also mop for wet cleaning, autonomously vacuuming and wet-mopping a floor in one pass (sweep and mop combo). A Robot Wipe can tackle multi surfaces and comes with a variety of different cleaning modes giving you options of sweeping, vacuuming and mopping damp or wet floors. The Robot Mop score better on hard floors surface and are ideally suited for hardwood, laminate and tile flooring types. Mapping The refined models include mapping ability. The unit can use gyro, camera, radar, and laser (laser distance sensor or LDS) guided systems to create a floor plan, which can be permanently stored for more efficiency, and updated with information on areas which have been (or have not been) cleaned. Thus, the cleaning efficiency is greatly improved and the repetition rate is reduced significantly. Models with a multiple floor plan feature can store numerous floor plans.
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What is Big Data?

An arena of Big Data gives means and methods to examine, logically extract information and deal with large & complex data sets by traditional data-processing application software. • Big data analytics means to systematically extract & analyze facts from large volumes of data that is too large to be analyzed manually by human beings using pen & paper. • US computer scientist and entrepreneur John R. Mashey popularized the term Big Data in 1990. Key Concept • Big data was originally linked with three key concepts: volume, variety, and velocity. • Currently, the following 10-Vs are most popularly associated with Big Data. 1. Velocity: Speed at which data is being generated and transferred to the destination. 2. Volume: Quantity of collected and stored data. 3. Variety : Different forms of data structured and unstructured 4. Variability: Dynamic evolving behavior in Data source 5. Value: Business value derived using data 6. Veracity: Quality or trustworthiness of the data 7. Validity: Correctness or accuracy of the data used to extract result in the form of information. 8. Virality: Rate at which the data is spread by a user and received by different users. 9. Volatility: Duration of usefulness of data 10. Visualization: Representation of data to trigger a decision. • American businessman, software engineer and Google CEO (2001-2011) explain the Data Volume In The Era Of Data Centers as “There were 5 exabytes of information created from the dawn of civilization till 2003.Now in the era of data centers, big data & digital technologies – 5 exabytes information is created every 2 days. “ Big Data Analytics Broad Description Big data analytics includes capturing data, data storage, data analysis, search, visualization, querying & updating data & using AI software to do automatic analysis. Analysis of big data sets is used to find correlations, historical trends, find unusual data anomalies & use this information to take corrective actions. Big data is now gathered using Industry 4.0 technologies including IOT sensors, Smart Phones, aerial drones (remote sensing), cameras, radio-frequency identification (RFID) sensors and wireless sensor networks. A Key Difference from Industry 3.0 Viz-A-Vis Real Time Data Gathering • In Industry 3.0 data was gathered by cables. In Industry 4.0 data has totally changed including the following. • Data gathering by cables sensors as well as Wi-Fi sensors • Data can be sent in real time to any data center in the world at light speed • This data can be analyzed using big data analytics algorithms in a data center • Real time diagnostics by AI software to do self-correction or suggest 2-3 options to the engineers for solving the problem Applications • Big data has increased the demand of data management specialists such a lot in order that Software AG, Oracle Corporation, IBM, Microsoft, SAP, EMC, HP and Dell have spent quite $15 billion on software firms specializing in data management and analytics. • In 2010, this industry was worth quite $100 billion and was growing at almost 10 percent a year: about twice as fast because the software business as an entire. Developed economies increasingly use data-intensive technologies. There are 4.6 billion mobile-phone subscriptions worldwide, and between 1 billion and a couple of billion people accessing the web. • Between 1990 and 2005, quite 1 billion people worldwide entered the center class, which suggests more people became more literate, which successively led to information growth. The world's effective capacity to exchange information through telecommunication networks was 281 petabytes in 1986, 471 petabytes in 1993, 2.2 exabytes in 2000, 65 exabytes in 2007 and predictions put the quantity of internet traffic at 667 exabytes annually by 2014. • Consistent with one estimate, one-third of the globally stored information is within the sort of alphanumeric text and still image data, which is that the format most useful for many big data applications. This also shows the potential of yet unused data (i.e. Within the sort of video and audio content). • While many vendors offer off-the-shelf solutions for giant data, experts recommend the event of in-house solutions custom-tailored to unravel the corporate’s problem at hand if the company has sufficient technical capabilities. How Data storage started? • Data storage started with vinyl records storing songs in 1880. Vinyl record could store 200 MB of data – but could not rewrite the data & was for one time use only. • First magnetic tape data storage came in 1947. The tape could store 60 MB of data – data could be rewritten multiple times on the same magnetic tape. • First hard disk drive came in 1957 named IBM 305 RAMAC. It could store 4 MB data and weighed 900 K.G. The hard drive could write & rewrite data in real time. • First solid state disk drive came in 1991 with 20 MB data storage capacity. This drive had no moving parts & had only electronic circuits to write & rewrite data endless times. • Today biggest available hard disk drive capacity is 16,000 GB & biggest solid state disk drive available is 8,000 GB capacity. Their size is 3.5 inch * 2 inch & weight is only 500 grams (Half K.G) • The capacity of 20 MB in 1991 versus 16,000 GB in 2020 - is only 0.12 % of data storage capacity. • Due to such massive data storage capacities available today – high speed internet, YouTube videos, Industry 4.0, AI & machine learning technologies have become possible. Google Data Centres Google has such 15 data centers globally with following features; • Each data center uses 200 MW electrical powers. • Each data center covers 500 acres of covered buildings • Huge installation of air conditioning for cooling as servers produce a lot of heat • For air conditioning – installation of chillers, cooling towers, heat exchangers, water pumps, RO plants – all these equipment is connected to Google’s own machine learning systems to optimize the use of all these utilities • UPS systems of 20-50 MW for back up electrical power. Facebook & big data Technology • Facebook uses the most advanced technologies viz-a-vis Machine Learning, AI, Advance Software Algorithms & Industry 4.0 Technologies. • Facebook has 12 data centers globally which are as big as Google data centers. • Facebook machine learning software operates at light speed (terabits/second) & “learns” the back ground of every user in the world including his age, profession, likes he does on Facebook, city of living, types of friends he has, types of pages he is following. • Facebook even “knows” from which city each user is using Facebook and using big data analytics knows which person stays in which area and which person travels to foreign countries. • Within a time line of 3 months Facebook AI software has learned the basic habits of every person including likes & dislikes, types & back ground of friends, pages each person follows, chats & subjects of chats of each person. • Based on this massive data – Facebook big data analytics & machine learning software gives tailor made individualized suggestions designed for each individual separately – including types of friends, new pages & products. • Such technology is impossible to deploy by using manual sheets of paper, telephone lines, what's app, SMS, excel worksheets.
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What is Edge Computing?

What is Edge Computing? | technologies blog | Scoop.it
• Edge computing is a circulated computing model which conveys computer data processing and storage nearer to the location where it is desirable. • It pushes applications, services, data and computing power outside centralized points to locations closer to the consumer. • As a replacement of taking a central, remote cloud organizes all the function. • The data is controlled and put in storage nearby, i.e. on the IoT device itself or at the adjacent network node. • In edge computing the main computation is completed on distributed device nodes. • Edge computing does not need contact with any centralized cloud, although it may interact with one. • Edge application services decrease the volumes of data that must be relocated, the resulting traffic, and the distance the data must travel. That delivers lower potential and decreases transmission costs. Overview • Edge computing is a revolution in Industry 4.0. • The increase of IoT devices at the edge of the cloud network is producing a massive amount of data to be computed at data centers, pushing network bandwidth requirements to the limit. • Despite the improvements in network technology - data centers cannot guarantee acceptable transfer rates and response times ~ which could be a critical requirement for many real time applications. • Edge computing applications include connected cars, autonomous cars, smart cities, Industry 4.0 industrial manufacturing applications. • Edge computing is the new generation industrial management technologies which are now a must for industrial manufacturing plants. • Next equipment coming from Siemens, ABB, GE etc. is all designed & enabled for edge computing. • These edge devices will communicate in real time with data centers and update operating software, operating conditions on the equipment in real time. • This will reduce manpower use and cut man hours use by 50 %. It will also reduce breakdowns and improve equipment efficiency to a very high level. Edge Devices and Field Gateways • A field gateway (edge) is a specialized device-appliance or general-purpose software that acts as a communication enabler and, potentially, as a local device control system and device data processing hub. • A field gateway can perform local processing and control functions toward the devices; on the other side it can filter or aggregate the device telemetry and thus reduce the amount of data being transferred to the cloud backend. • Gateways in this context may assist in device provisioning, data filtering, batching and aggregation, buffering of data, protocol translation, and event rules processing. Drawbacks of pure Cloud Computing when it comes to IoT • Data security threats. Data is constantly being transmitted back and forth between the cloud and a device, and as such, the risk of privacy violation is heightened. • Performance issues. IoT applications rely heavily on real-time actions. Yet, the processing speed of your cloud-based app often depends on the actual distance between the device itself and the server location. • Operational costs coincidentally grow as the amount of data produced and shared increases. • On top of that, most data sourced to the cloud often bears no practical value and is never used. How does edge computing work? • Every IoT sensor produces tons of data every second. In the case of cloud computing, the data is instantly transferred to the central, unified cloud database where it’s processed and stored. • If there’s any action required, the central server will send its response back to the device upon receiving and analyzing the acquired data. • While the whole process typically takes less than a second to complete, there might be situations when the response may be delayed or interrupted. This can happen due to a network glitch, weak internet connection, or simply because the data center is located too far from the device. • Now, in case of edge computing, you don’t need to send the data acquired by the IoT sensors anywhere. The device itself or the nearest network node (e.g. the router) is responsible for data processing and can respond in a proper manner if action is required. Edge Computing makes it possible that the IoT device is no longer dependent on the internet connection and can function as a standalone network node Benefits for edge computing in IoT 1. Increased data security 2. Better app performance 3. Reduced operational costs 4. Improved business efficiency and reliability 5. Unlimited scalability 6. Reliability as edge computing systems provide actions to recover from a failure Edge Computing Use Cases Industries with the most edge computing use cases are: • Travel, transportation, and logistics • Energy • Retail • Healthcare • Utilities Efficiency • Due to the proximity of the analytical resources to the end users, sophisticated analytical tools and Artificial Intelligence tools can run on the edge of the system. • This placement at the edge helps to increase operational efficiency and contributes many advantages to the system. • Additionally, the usage of edge computing as an intermediate stage between client devices and the wider internet results in efficiency savings that can be demonstrated in the following example: • A client device requires computationally intensive processing on video files to be performed on external servers. By using servers located on a local edge network to perform those computations, the video files only need to be transmitted in the local network. Avoiding transmission over the internet results in significant bandwidth savings and therefore increases efficiency. Cloud Computing and 5G • Transporters are deploying 5G wireless technologies all over the world. • It ensures the benefits of high bandwidth and low latency for applications. • Many transporters are working edge-computing strategies into their 5G deployments in order to offer faster real time processing, especially for mobile devices, connected cars and self-driving cars. • Researchers foretell the 5G will be a catalyst for edge-computing. • Applications using 5G technologies will change traffic demand patterns, providing the biggest driver for edge computing in mobile cellular networks. • 5G speeds will range from ~50 Mbit/s to over a gigabit/s. The fastest 5G is known as mmWave. There is dire need for on-demand compute and real-time application engagements which would play a role in driving the growth of edge computing in 2020. • The advance of real-time applications that require local processing and storage capabilities will drive the technology forward over the coming years.
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What is Python List?

• In Python, a list is a mutable, means the values that it contain can be modified. • A list is a variable that can have a sequence of values assigned to it. • In a list, these values are known as elements or members. • It is collection which is ordered, changeable and allows duplicate members. Defining a List • We define a list this way: fruits = ["Mango", "Apple", "Orange”, “Banana", "Grapes"] • In Python lists are written with square brackets. • We define a list by enclosing everything to the right of the equal sign in square brackets. • Each element or member is separated by a comma and a space. • The first element in a list always has an index of 0, the second element an index of 1, and so on. • A list element can be assigned any type of value that we can assign to ordinary variables, for example a string or a number. • We can even mix the different types of values in the same list. • For example: collection = [“5”,”Abdulmomin”,”Where is”] • In this example, collection [0] has a numerical value of 5, collection [1] has a value of "Abdulmomin", and collection [2] has a value of "Where is". All the time remember that: • The first element in a list always has an index of 0, not 1. This means that if the last element in the list has an index of 9, there are 10 items in the list. • The same naming rules we learned for ordinary variables apply. • Only letters, numbers, and underscores are legal. The first character can't be a number. No spaces. • It's a good idea to make list names plural—fruits instead of fruit, for example—since a list usually contains multiple things. Add items • We use the append () method to add an item to the end of the list. • If we want to add "Straw berry", in the end of the list fruits it will be as fruits = ["Mango", "Apple", "Orange”, “Banana", "Grapes", "Straw berry"] • The statement begins with the list name:fruits.append("Straw berry") • Next there's a dot: fruits.append("Straw berry") • Then the keyword append: fruits. append("Straw berry") • Instead of appending an element to the end of a list, we can insert it into the list where we want it. • We use the insert () method to add an item at the specified index. Delete and remove elements There are several methods to remove items from a list. • We can delete any list element by specifying its index number. • The remove () method removes the specified item. • The pop () method removes the specified index. We can pop an element off a list and append it or insert it to another list. • The del keyword removes the specified index. It can also delete the list completely. • Similarly, the clear () method empties the list. Slicing • We can copy consecutive elements of a list to build another list. • The first number inside the brackets targets the first element in the slice. List Length • Use the len () function to determine how many items in a list. Example: Print the number of items in the list: fruits = ["Mango", "Apple", "Orange”, “Banana", "Grapes", "Straw berry"] print(len(fruits)) Result: 6 Concatenation of the list • In Python, two or more lists can be joined or concatenate. • One of the easiest ways are by using the + operator. Example: Join two list: List4 = ["x", "y" , "z"] List5 = [5, 6, 7] List6 = list4 + list5 print(list6) • Result: [ “x”.”y”.”z”,5,6,7] • We can join two lists by appending all the items from list4 into list5, one by one. • We can also use the extend () method, which purpose is to add elements from one list to another list. List Methods We can use on lists the following set of Python built-in Method. Method Description append() Adds an element at the end of the list insert() Adds an element at the specified position extend() Add the elements of a list to the end of the current list pop() Removes the element at the specified position remove() Removes the item with the specified value clear() Removes all the elements from the list count() Returns the number of elements with the specified value copy() Returns a copy of the list index() Returns the index of the first element with the specified value reverse() Reverses the order of the list
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What are Python Dictionaries?

A dictionary is a series of pairs of things. It is a collection which is unordered, changeable and indexed. Each pair contains a key—"firstname", "last name" etc.—and a value—"Mansoor", "Ahmed", etc To pick something out of a dictionary, we specify a particular key and ask what value is paired with it Dictionaries are written with curly brackets, and they have keys and values. In a dictionary, each chunk is a paired key and value. Notice that the key is followed by a colon: the variable name is singular, not plural All the values are strings, enclosed in quotation marks, and so are all the keys Dictionary’s purpose is to store information that we can later lay our hands on. For example, if someone wants to know the address of "Mansoor Ahmed" how does he will find it? In a dictionary, we pick out an element by specifying its key: address_of_customer = customer_12345 ["address"] print (address_of_customer) The keys can be strings and numbers. To pick out a value, we use the number Values can be numbers, too : To pick out a value, we use the key, a string in this case We can mix strings and numbers any way we want https://www.technologiesinindustry4.com/2020/10/AI-Python-Range-Function.html#more https://www.technologiesinindustry4.com/2020/10/ethereum-erc20.html How to add a key-value pair to a dictionary Let us see we have dictionary customer_12345 = {"first name": "Mansoor", "last name": "Ahmed", "address": "H.No.3 Ibrahim Fibres Ltd Colony"} We can add a new pair by writing customer_12345["city"]= "Faisalabad" We can define an empty dictionary, a dictionary with no key-value pairs: things_to_remember = {} Later, we can fill the dictionary with pairs, adding one at a time things_to_remember[1000] ="highest number" thing_to_remember["last name"]= "Ahmed" How to delete an element from dictionary: del customer_12345["address"] It begins with the same keyword: Then comes the name of the dictionary. And the particular piece of information we're after is specified by the key (in the dictionary), in square brackets Then the assignment of the new value. Looping through a values: customer_12345 = {"first name": "Mansoor", "last name": "Ahmed", "address": "H.No.3 Ibrahim Fibres Ltd Colony"} for each_value in customer_12345.value(): print (each_valuve) The loop begins with the familiar for: Next comes a variable to store the value for each iteration. Next, the keyword in followed by the name of the dictionary, customer_12345 Then a dot… Then the keyword values… then empty parentheses and colon Looping through keys: This is a dictionary customer_12345 = {"first name": "Mansoor", "last name": "Ahmed", "address": "H.No.3 Ibrahim Fibres Ltd Colony"} This is the loop: for each_key in customer_12345.keys(): print(each_key) Python displays: first name last name address Looping through key-value pairs: This is the dictionary we've been working with: customer_12345 = {"first name": "Mansoor", "last name": "Ahmed", "address": "H.No.3 Ibrahim Fibres Ltd Colony"} Here's the code for looping through the dictionary and printing all the keys and values: for each_key,each_value in customer_12345.items(): print("The_customer’s" + each_key + " is" + each_value) Following the instructions above, Python displays: The customer's first name is Mansoor The customer's last name is Ahmed The customer's address is H.No.3 Ibrahim Fibres Ltd Colony Length of Dictionary: To determine how many items (key-value pairs) a dictionary has, use the len () function. Example: Print the number of items in the dictionary: print(len(thisdict)) How to append a new dictionary to a list of dictionaries: To learn how many dictionaries are in the list, we measure the list's length using the keyword len, for length, we write new_customer_id = len(customers) We can create the new dictionary new_dictionary = {"customer id": new_customer_id,"first name new_first_name, "last name": new_last_name,"address": new_address,} Finally, we append this new dictionary to the list: customers.append(new_dictionary)
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Persistent Volume in Kuberenetes

Persistent Volume in Kuberenetes Volumes were great as they saves us from data lost in case of container restart. Volumes hold data at a pod level but question may be asked what if for any reason Kuberenetes terminates the pod e.g rescheduling the pod. In the case of pod termination data in the volumes will be lost. To solve this issue Kuberenetes provides us option for Persistent Volume. Persistent Volume add a volume at a cluster level instead pod level. We create a Persistent Volume resource in which we offer cluster level volume that can be used by any pod. Any pod can use that Persistent Volume by using another resource Persistent Volume claims. It remains available outside of the pod life cycle. That means volume will remain even after the pod is deleted. This volume will be available to claim by another pod if required, and the data is retained. POD → Persistent Volume claim → Persistent Volume Persistent Volume Claim It is a kind of formal request from user for claiming a persistent volume. A persistent volume claim describes the amount and characteristics of the storage required by the pod. Based on requirement from user PVC finds any matching Persistent Volumes and claims it. Depending on the configuration options used for Persistent Volume resource, these PV resouce can later be used/claim by other pods. https://www.technologiesinindustry4.com/2020/10/ethereum-erc20.html Understanding Persistent Volume Specs Types of access Modes ReadWriteOnce (Only a single node can mount the volume for reading and writing) ReadOnlyMany (Multiple nodes can mount the volume for reading) ReadWriteMany (Multiple nodes can mount the volume for both reading and writing) RWO,ROX, and RWX pertain to the number of worker nodes that can use the volume at the same time, not to the number of pods ! Persistent Volume Reclaim Policy We have learned that depending on the configuration options used for Persistent Volume resource, these PV resource can later be used/claim by other pods. The lifetime of a Persistent Volume is determined by its reclaim policy. Reclaim policy controls the action the cluster will take when a pod releases its ownership of the storage. Persistent Volume Reclaim Policy tag can be used in YAML configuration file at the time of creating PV. Reclaim Policy can be set to Delete (Persistent Volume will be deleted when the PVC is deleted but data will persist) Recycle (Volume's content will be deleted,persistent volume will be available to be claimed again) Retain (Default) If persistent volume Reclaim Policy not provided, Retain is default. Kubernetes will retain the volume and its contents after it's released from its claim. To make persistent volume available again for claims can be done by delete and recreate the persistent volume resource manually. Underlying storage can either delete of left to be reused by the next pod.
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9 Best Outro Makers + How to Make an Outro [2020]

9 Best Outro Makers + How to Make an Outro [2020] | technologies blog | Scoop.it
Outro maker is a tool that helps every video creator to create an unforgettable outro for their video. Here detail 9 excellent makers and how to make an outro.

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Kubernetes Readiness Probes

We already know about liveness probes and how they help keep our apps healthy by ensuring unhealthy containers are restarted automatically. Similar to liveness probes, Kubernetes allows us to also define a readiness probe for our pod. The readiness probe is invoked periodically and determines whether the specific pod should receive client requests or not. When a container’s readiness probe returns success, it’s signaling that the container is ready to accept requests. This notion of being ready is obviously something that’s specific to each container. Same as liveness probe Kubernetes sends requests to container and based on the result either successful or unsuccessful response it decides container is ready to take traffic or still getting ready for that. Unlike liveness probes, if a container fails the readiness check, it won’t be killed or restarted. It is good practice to always add readiness probe even it’s a simplest app in the container. Readiness Probe Types There are three types of Readiness Probe. HTTP GET This type of probe send request on the container’s IP address, a port and path we specify. Probe is considered a failure and container will be treated as not ready and no traffic will get diverted to it. TCP SOCKET TCP Socket probe tries to open a TCP connection to the specified port of the container. If the connection is established successfully, container will marked as ready and it will receive traffic. Otherwise, Kubernetes will wait and runs the probe to check the status again. EXEC Probe An EXEC probe executes some commands you provide inside the container and checks the command’s exit status code. If the status code is 0, the probe is successful. All other codes are considered failures. Readiness Probe Examples my-rn-exec.yaml Kind: Pod apiversion: v1 metadata: name: myapp-rn-exc Spec: Containers: -name: my app image: ahmedmansoor/hi Ports: -containerPort: 80 Readiness Probe: exec: command: -ls -/tmp/ready my-rn-tcp.yaml Kind: Pod apiversion: v1 metadata: name: myapp-rn-tcp Spec: Containers: -name: my app image: ahmedmansoor/hi Ports: -containerPort: 80 Readiness Probe: tcpSocket Port : 8080 my-rn-http.yaml Kind: Pod apiversion: v1 metadata: name:myapp-rn-http Spec: Containers: -name: my app image: ahmedmansoor/hi Ports: -containerPort:80 Readiness Probe: http Get: Port: 80 path:/
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What is Artificial Narrow Intelligence?

There are two types of Artificial Intelligence. ANI (Artificial Narrow Intelligence): There is lot of progress in Artificial Narrow Intelligence like smart speakers, self driving cars, AI to do web search and AI application in farming and factory. The rapid progress in ANI has caused people to conclude that there's a lot of progress in AI, which is true. But that has caused people to falsely think that there might be a lot of progress in AGI as well which is leading to some irrational fears about evil clever robots coming over to take over humanity anytime now. AGI (Artificial General Intelligence): There is almost no progress in Artificial General intelligence. It is the goal to build AI and do anything a human can do. AGI is an exciting goal for researchers to work on, but it requires many technological break through before we get there. It may be decades or hundreds of years or even thousands of years away. What is most important idea in AI? Machine learning is the most essential idea in Artificial intelligence. It is a sub set of AI. Machine learning is a scientific study of algorithms and scientific models that computer system use to perform a specific task without using explicit instructions Arthur Samuel (1959) has explained the machine learning as " Field of study that gives computers the ability to learn without being explicitly programmed". Running AI System: A software which automatically returns output B for input A. If we have an AI system running ,serving dozens or hundreds of thousands or millions of users, that's usually a machine learning system. Types of Machine Learning There are three types of Machine Learning. Supervised Learning Unsupervised Learning Reinforcement Learning Supervised Learning It is the task of learning a function that maps an input to an output based on example input-output pairs. On one hand,input to output, A to B it seems quite limiting.But when, we find a right application scenario,this can be incredibly value able. It infers a function from labeled training data consisting of a set of training examples. In supervised learning, each example is a pair consisting of an input object (typically a vector) and a desired output value (also called the supervisory signal). A supervised learning algorithm analyzes the training data and produces an inferred function, which can be used for mapping new examples. Examples A to B mappings Input (A) → Output (B) Applications email → Spam Spam filtering Audio → Text Transcript Speech recognition English → Chinese Machine translation image of phone → Defect Visual inspection Unsupervised Learning In contrast to supervised learning it is a type of machine learning that looks for previously undetected patterns in a data set with no pre-existing labels and with a minimum of human supervision. Unsupervised learning, allows for modeling of probabilities densities over inputs. Reinforcement Learning It is an area of concerned with how software agents ought to take actions in an environment in order to maximize the notion of cumulative reward. Reinforcement learning is one of three basic machine learning paradigms. What enables machine learning to work so well? Data enables the machine learning to work so well. The out put of a data science project is a set of insights that can help us to make business decisions. Data is often unique to our business. We can acquire data by manual labeling,from observing behaviors of humans,from observing behaviors of machine and downloading from websites. Don't throw data at on AI team and assume it will be valuable. Once you have started collecting data, go ahead and start showing it or feeding it to an AI team. Then the AI team can give feed back to your IT team and what type of data to collect and what type of IT infrastructure to keep on building. If we have bad data, then the AI will learn inaccurate things.
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How to Download Lens Flare and Add it to Your Video

How to Download Lens Flare and Add it to Your Video | technologies blog | Scoop.it
What is lens flare and where to download it? How to add lens flare to your video projects and motion graphic designs? All the questions will be answered here.

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Adobe MAX Is Creativity Conference for the World, Says CEO

Adobe MAX Is Creativity Conference for the World, Says CEO | technologies blog | Scoop.it
Technology in Business

Shantanu Narayen, chief executive officer, president and chairman of Adobe Inc., discusses how the company's annual conference event, Adobe MAX, will differ.



Credit Bloomberg Technology

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What is the Role of Augmented Reality in Industry 4.0?

What is the Role of Augmented Reality in Industry 4.0? Augmented Reality (AR) The shared knowledge of a real-world situation where the substances that exist in are boosted by computer-generated perceptual information is called Augmented Reality (AR). The consumer is delivered with extra computer generated information in Augmented Reality that improves their insight of reality. It was developed by Ivan Sutherland in 1968. It realizes three basic types: Mixture of real and virtual worlds Real-time interaction Correct 3D registration of virtual and real objects. The prime worth of augmented reality is the way in which components of the digital world compose into individual's perception of the real world. This is not possible simply showing of data. It is only possible over the addition of immersive feelings, which seem as natural portions of a location. The portion of the adjoining environment in AR is really 'real' and impartial addition of covers of virtual objects to the real environment. Technologies Used in AR Diffractive waveguides Reflective waveguides Hardware components Processor Display (Monitors, optical projection systems, touched devices and displays system that worn on the human body). HMD (Head Mounted Display) is a display device that worn on the forehead. It may give customers of Augmented Reality with mobile and cooperative involvements. HUD (Head up Display) is a clear display that grants data without needful customers to look away from their usual viewpoints. VRD (Virtual Retinal Display) is skimmed directly onto the retina of a viewer's eye. Sensors and input devices Eyeglasses/smart glasses/Eye taps and contact lenses Projectors, input devices, computers, Tracking and networking. Applications There are numerous means of applications of augmented reality ranging from entertainment and gaming to medication, education and commerce. Below are instances of outstanding applications of augmented reality. Archeological research The main application of AR is in research work of archeology. It permits the archaeologists to articulate likely site shapes to after existing buildings. The virtual copies of remains, landscapes and buildings have been used in archaeological AR applications. Building projects The augmented reality provides assistance to visualize the architecture work. Before the physical building construction the virtual pictures of a building may be overlaid onto a real-life local view of stuff. Designing & planning of Urban Development The AR systems are getting used as cooperative tools for design and planning inside the constructed environment. It used frequently to create augmented reality buildings; maps and data feeds Design options are regularly voiced on site, and seem nearer to reality than old-style desktop devices like 2D maps and 3d models. Education The application of AR in Education is very helpful for student’s real-time graphics and environment. AR technologies benefit beginners involve in true search within the world, and computer-generated objects. The students may contribute and intermingle with information more genuinely. The visualization of diverse systems of physical body in three dimensions is easier for students due to the augmented reality. Industrial business The augmented reality is working to standby paper handbooks with digital instructions. It results machine maintenance well-organized because it gives operators direct access to a machine's maintenance history. The operator’s safety can be increased by digital instructions. It may enhance feeling of safety in operators when working near high-load industrial machinery by giving operators additional information on a machine's status and safety purposes. Trade and commerce AR is employed to mix print and video marketing. Printed marketing material is frequently designed with sure "activate" images. Old-styled print-only publications are using augmented reality to assign contrary types of media. It may increase product previews which permits customer to see at what is inside a packaging without opening it. The augmented reality is also very useful in choosing products from a catalog or through a stall. It is becoming often useful for online advertising. Additionally the furniture shops like Houzz, IKEA and Wayfaire are being employed by AR technology. The merchants bid apps that let customers to look at their products in their home earlier buying anything. Benefits of Augmented Reality There are several benefits to using AR that may develop our business right now. AR Continues the Store to the Customer: The companies like IKEA’s furniture are a unique experience to be able to place a virtual piece of furniture in our home, and see what it would look like if it were actually there. AR Assists Exclusive Chances for Immersive Reality.: Some business models, like WallaMe, are engaging people during a way that gets them out into the planet in search of AR experiences, in much an equivalent way that Pokemon GO did several years ago. AR Delivers Children With New Levels of Collaborative Experiences.: European grocery and general retail brand Tesco partnered with Disney to bring Disney's Frozen-branded products sold in Tesco stores to entire new level, enabling parents and their children to explore a Frozen-branded sticker book and take selfies of their kids with their favorite Frozen characters. AR Suggests Safety Technology for Automobiles: Jaguar's Virtual Windscreen uses head-up-display technology, along with software-enhanced effects to show the driver real-time data that is able to interact with physical things that may be seen through the windshield of the automobile. AR Lets Staff Training Without Risk: The U.S. Army is using HoloLens technology for training. The Mercedes-Benz Global Training center in Stuttgart, Germany is by HoloLens to visually inspect the inside of cars as they work on them, using the transparency provided by AR to see details that would otherwise be hidden from view. Improve the Industry 4.0 operations by Augmented Reality Attainable Benefits Approximately goodbye to loads of paper on the shop floor Regulate events crossways the business Train labors on the ground more proficiently Time saving and costs reducing Normally mobile devices have more presentation restrictions related to dominant desktop or notebook computers. Thus preparing a 3D model for mobile A.R. needs a specific degree of optimization. Making AR content for end users means handling a potentially substantial amount of numerous devices. The current 3D modeling software allows the user to do sure operations which would create the model more suitable for Augmented Reality. Trimble SketchUp, Autodesk 3ds Max, Autodesk Maya, Blender, and similar software, are all pertinent options to realize the specified level of 3D models’ optimization. How to prepare 3D models for Augmented Reality? There are lots of optimizations a user may do to a 3D model to form it do better in real-time Augmented Reality applications. Generally it’s sufficient to act on three areas of intervention to urge a suitable level of optimization. Complexity This is dynamic to model our project professionally in our reference 3D modeling software. By efficiency we mean keeping the count of polygons as low as possible, avoiding to model parts of the thing the user will never be ready to see and appreciate. If we're counting on one among the various online 3D repositories, confirm to see if the model is optimized for real-time. Textures One more part of optimization concerns the way textures are managed. Attempt to use only one texture and bake texture so as to enhance the graphic rendering, for instance just in case we would like to feature ambient blocking or static shadows on the model. Also assign a typical material (ambient, diffuse, specular colors and eventually a shininess/specular power value. Export Once the model is prepared export it within the binary .FBX file format. It’ll include textures and animations, if any. Nearly all the 3D modeling software provides a choice to export within the FBX format.
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What is the role of Voice Revolution in Industry 4.0?

What is the role of Voice Revolution in Industry 4.0? Industry 4.0: Voice Revolution Introduction of Voice User Interface (VUI) A new kind of User Interface is voice user interface. It creates spoken human interaction with computers likely with speech recognition to recognize spoken instructions and to show an answer. The device organized with a voice user interface is known as a voice command device (VCD). The speaker-independent new VCDs have been introduced which may answer to many voices irrespective of pronunciation or dialectal effects. They are skillful of answering to numerous commands at once. They are similarly able to provide proper feedback, sorting out vocal messages and precisely reproducing a natural conversation. AI Assistants allow us to control things like our thermostat, garage door and other connected devices just by speaking. Most suitable uses of Voice control in IoT Home automation, home appliances like washing machines, television remote controls and microwave ovens. IoT devices are a integral part of the bigger concept of home automation. Automobiles: VUI have been added in Cars and vehicles. Voice command for cars should permit a driver to issue directions and not be diverted. Health Care: IoT devices may be used to assist remote health monitoring and emergency notification system. The advanced hearing aids are a best example of health monitoring device Entertainment: A smart speaker having touch screen is a smart Bluetooth device. It adds conversational user interface with display screens to increase voice interaction with images and video. Voice Assistants Are Taking Over Consumer IoT More than Consumer IoT (CIoT), no industry felt the heat of the voice assistant battle in which voice assistant integrations became the primary focus for any CIoT product-centric company. Imagine a future in which every command is at the tip of our tongue. When we wake up our bathroom mirror can report us schedule for the day. During breakfast, we can ask the coffee machine for a latte, extra foam. On the train, our watch will tell us just how late we’ll be to work. In the office, our printer will pipe up, asking for more ink, please. Entry point into the IoT The entry point into the Internet of Things has been Amazon and Google’s smart speakers for several consumers. Voice control is one of the main drivers of smart home market development with the number of home voice devices predictable to reach 275 million by 2023 in USA alone. Visions of dialogue from science fiction Hal "2001: A Space Odyssey" (1968) Naturally conversing computer Star Trek (original 1966) Natural language command and control Her (2013) A virtual partner with natural dialogue capabilities Digital Assistants are So Hot German company major in market and consumer data named Satista describe that the market for AI-driven personal assistants and bots will almost double in 2020, reaching more than $14 billion by 2022 with 1.8 billion active users. Attractive greatly today every tech giant is making digital agents for their customers. Amazon’s Alexa, Microsoft’s, Apple’s Siri and Google’s Assistant are prominent digital mediators. Causes for being So Hot Natural language is more spontaneous than web or mobile interfaces, which commonly entail certain degree of a learning curve. Boosted productivity Personalization drives far beyond voice recognition. They pay machine learning to refine their replies and bring only applicable options built on customer likings. Personal assistants may contact a huge variety of data AI-aided assistants and innovations in the IoT get a entire new level of communication between devices, people, and companies. AI Voice Assistants AI voice assistants generally take input by voice. A lot of them listen continuously for a prompt word, which makes hands-free use possible. If that’s not likely, we simple tap an icon to say our piece. We’ll find them in smartphones, smart speaker, smart TVs and other "smart" internet-connected devices. The Google Assistants is a powerful AI that’s available on just about every Android device on the market. Most people allow the voice Assistants for internet searches, media playback, message dictation, scheduling and alarms. We may even control things like volume, Bluetooth and WiFi. Examples Apple’s Siri 2011 Microsoft’s Cortana 2014 Amazon’s Alexa 2014 Google’s Assistant 2016 Samsung’s Bixby 2017 What is a Bot? A Bot is a conversation based UI. The conversation is based on language. It takes place on a general canvas. The canvas can be: Chat Client: Skype, Team, Slack, Messenger Voice: Echo, Cortana Skills, Siri, Google Now App: Website, App Scenario’s for Bots Question and Answers Systematize Helpdesk, Handoff to human if besides difficult Product selection and ordering Task Automation Proactive Assistance & Monitoring Expert Systems Embedded devices with dialogue capabilities Amazon Echo (2014) – home assistant device: It plays music with voice commands. Have a capability to Question answering, get weather, news. It reply more complex questions, like "how many spoons are in a cup? Other types include setting timer and manage TODO lists. The Voice Activated Smart Clock: The unique features of voice activated smart clock are answering the questions, sets time, thermostat and device control & queries Dialogs are for bots like screens are for appsTraditional Application They distinct fears and organize flows, correctly the same way: Traditional Application Main Screen New Order Screen Product Search Screen Bot Root Dialog New Order Dialog Product Search Dialog Google Assistant coming soon …. Google is locating its Assistant on wide-ranging third-party hardware. It has declared that it’s going to be setting the Assistant on partner speakers, appliances, connected cameras, and much more. It is already on the iPhone. Google wants to ‘see’ as well as ‘hear’ our surroundings. For this purpose it developed Google Lens that is an image recognition technology. How to develop for the Google Assistant platform? https://developers.google.com/actions/ Developer platform of Google is known as Google actions that lets us make software to cover the functionality of the Google Assistant, Google’s virtual personal assistant, across in excess of 500 million devices, with TVs, headphones, watches, smart speakers, phones, cars, and more. We can build smart home Actions that let users control Internet of Things (IoT) devices through the Google Assistant. Building smart home Actions lets us connect, query, and control devices through our existing cloud infrastructure.
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How To Learn Industry 4.0?

How To Learn Industry 4.0? The industry 4.0 is the usage of fresh smart technologies for the enduring automation of outdated manufacturing and industrial practices. The internet of Things (IoT), cloud computing, artificial intelligence and machine-to-machine communication (M2M) are all integrated at large scale for increased automation. This whole process may analyze and diagnose problems without the need for human intervention. Technologies like Artificial intelligence, machine learning, cloud computing, data base technologies, big data analytics etc. are now a core requirement for industrial manufacturing companies. History German engineer, economist and executive chairman of the World Economic Forum, Klaus Martin Schwab first introduced the phrase Fourth Industrial Revolution (Industry 4.0) in 2015-16. Industry 1.0 It was steam production & driving machines with steam power. From 1770 – 1870 steam power drove flour mills to grind wheat & other small factories. Industry 2.0 It was electrical power production & driving machines with electrical power. Machines were crude & “manual” with simple pressure, temperature gauges installed on the machines for reading the data locally on the equipment. Industry 3.0 It was DCS system, data gathering by remote sensors connected by cables. The inventions of the semiconductor, pc and therefore the personal computer and the internet marked the Third Industrial Revolution starting in the 1960s. This is also mentioned because the "Digital Revolution”. Industry 4.0 IT technologies have been changed manufacturing systems from simple steam engine in 1700’s to today’s AI & machine learning based manufacturing where equipment communicates with each other using software technologies. Key components of Industry 4.0 • Mobile devices – laptop, iPad, Smart Phone • Location detection technologies including sensors on the production floor • Smart sensors on machines giving real time data • Big data analytics & advanced algorithms including artificial intelligence & machine learning • Lights out manufacturing ~ minimum head count on production floor with maximum automation • Augmented reality / wearable headsets with video screens for training Four design principles of Industry 4.0 1. Interconnection (Connection and communication ability of machines, sensors, and people through IoT and IoP) 2. Transparency of information (Collection of vast amounts of data and information from all points in the manufacturing process by operators to improve functionality) 3. Technical assistance (The ability to assist human with hard tasks) 4. Decentralized decisions (The ability of cyber physical systems to form decisions on their own and try to do their tasks as autonomously as possible) Industry 4.0 & Team Dynamics– Organizational Structure & Teams In Modern Manufacturing Organization One of the top organizational chart components is “team” and the related concept of team development & team building. Teams can be both horizontal and vertical in the organization chart. While an organization consists of multiple sets of people who combine their individual skill sets, management know how & competencies to work together - the quality of organization chart ultimately depends on the combined competencies of the persons working in teams. Any organization having more than 500 persons cannot function without task based teams – and without clear team structure and assignments based teams – the industrial manufacturing company will collapse and shut down. 'Digital Twins' Technology Deployment For Vaccines & New Medicines Development Digital Twin technology has long played a role in medical research, specifically in the area of clinical trials, where they can help measure the effectiveness of a therapy by applying a control to one of a genetically-similar pair. A new company founded by a former principal scientist at Pfizer, has developed a way of digitizing this concept through the use of AI. Unlearn.AI, has built a machine learning platform that builds “digital twin” profiles of patients that become the controls in clinical trials. Unlearn approaches the thought of building these digital twins as a classic machine learning problem, using “clinical trial datasets from thousands of patients to create the disease-specific machine learning models used to create Digital Twins and their corresponding virtual medical records.” These are quite simple medical profiles - they match people consistent with demographics, lab tests and biomarkers. The idea is that by building AI-based twins, there’s less of a requirement to seek out similar actual pairs of individuals — actual twins, even — to run tests. Google Ad Words Using Neural Networks, Machine Learning & Advance Algorithms Google advertisement system is based on software cookies and on keywords requested by selling companies which want to advertise on Google. It uses these search words to prioritize & place relevant advertising on pages where Google’s advanced algorithms & AI software determines the highest relevance. Clients companies of Google pay to Google when each user clicks on the Google searched & suggested company to the selling company portal. The Google Ads covers the entire world & includes local, national, and international sellers ~ based on the user’s location on the planet. Google's text advertisements are precise, focused, 95 % accurate ~ consisting of three headlines with a maximum of 30 characters each, 2 descriptions with a maximum of 90 characters, and a display two web sites links of 15 characters each. Industry 4.0 technologies being deployed in India 1 - CtrlS CtrlS is ranked as Asia Pacific’s largest Tier-4 data center and managed services provider. It’s five world scale datacenters in Hyderabad, Mumbai, Noida, Bangalore, and Chennai. The corporate has over 3,500 Indian companies and global multinationals as customers. Its Mumbai facility has 5,000 racks with 200,000 sq. ft. of space and 30 MW of power capacity. The data center in Mumbai is a million sq. ft. which has the capacity to host 50,000 racks and uses 100 MW electrical powers. 2 - ESDS ESDS has its presence within the subsequent industry verticals – Banking & Finance, Manufacturing, Education, Energy & Utilities, Healthcare, ecommerce, Agriculture, IT, Entertainment & Media, Telecom, Government and Travel & Tourism. 3 - GPX Global Systems Inc. GPX has one 30,000 square feet data center in Mumbai & second data center in Mumbai is 60,000 square feet with 16 MW total electric power use. GPX’s customers include Telcos, Cloud Service Providers, Internet Service Providers, CDNs, e-businesses and enterprise clients. 4 - Netmagic (NTT Communications Company) Netmagic, a wholly-owned subsidiary of NTT Communications Japan, may be a leading managed hosting and multi-cloud hybrid it solution provider with 9 carrier-neutral, state-of-the-art hyperscale and high-density data centers. From India it serves quite 2,000 enterprises globally including NTT Communication’s customers across Americas, Europe and Asia-Pacific region. 5 - NxtGen NxtGen enables its customers to make their digital business without investing and managing complex IT infrastructure, by leveraging its hyper-converged infrastructure. NxtGen deploys and offers IT infrastructure services from both or a mix of on-premise resources and its own facilities – Infinite DatacenterTM, empowering its customers to adopt the newest hybrid computing model. Oracle eAM – AI & Machine Learning Systems Integration Into Oracle eAM For Industry 4.0 • Artificial intelligence & machine learning integration into Oracle eAM • Oracle eAM to use AI to predict maintenance schedules • Oracle eAM to use AI to predict breakdown • Oracle eAM to urge data direct from apps like Emerson Delta V smart phone app for updating its data base Industry 4.0 implementation challenges There are challenges being faced during implementation of Industry 4.0 such as; political • Lack of regulation, standards and sorts of certifications • Unclear legal issues and data security), Social • Privacy concerns • Surveillance and distrust Economic • High economic costs • Business model adaptation Organizational • IT security issues • Reliability and stability needed for critical machine-to-machine communication (M2M), including very short and stable latency times • Need to take care of the integrity of production processes • Need to avoid any IT snags, as those would cause expensive production outages • Need to guard industrial know-how. Lack of adequate skill-sets to expedite the transition towards a fourth technological revolution • Low top management commitment • Insufficient qualification of employees
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What is Internet of Things (IoT)?

  The internet of Things, or IoT, refers to the billions of physical devices around the world that are now connected to the online , collecting, sharing and analyses of data . It describes the network of physical objects that are embedded with sensors, software, and other technologies for the aim of connecting and exchanging data with other devices and systems over the online. Because of cheap processors and wireless networks, it's possible to point out anything, from a pill to an aero plane to a self-driving car into a neighborhood of the IoT. Overview IoT will control the Fourth industrial revolution. The Fourth industrial revolution is changing the very software-defined automation allows manufacturers to link all stages of the price chain, rapidly adapt to changing markets, and make highly personalized products on a mass scale. The opportunities presented by this revolution are incredible. According to McKinsey, the economic impact of smart factories could reach up to $2.3 trillion once a year by 2025. At the center of the Fourth industrial revolution is that the Internet of Things (IoT), which uses digital technology to connect sensors, actuators, and machines to each other and to factory workers. Definition The web of Things is that the network of physical devices that combine IP connectivity with software, sensors, actuators, and other electronics to directly integrate the physical world into our computer-based systems, resulting in efficiency improvements and economic benefits. Simpler Definition: the web of Things could also be a network of Internet connected devices that communicate embedded sensor data to the cloud for centralized processing. Applications The extensive set of applications for IoT device is typically divided into consumer, commercial, industrial, and infrastructure spaces. Consumer applications A growing portion of IoT devices are created for consumer use, including connected vehicles, home automation, wearable technology, connected health, and appliances with remote monitoring capabilities. Smart home IoT devices are an area of the larger concept of home automation, which can include lighting, heating and air conditioning , media and security systems and camera systems. Long-term benefits could include energy savings by automatically ensuring lights and electronics are turned off or by making the residents within the home aware of usage. Smart Planet (Green environment) Environmental sensors. Water power leak detection Pollution, weather monitoring Smart cities (Connected communities) Lighting, water management Monitoring and security control Smart Energy (Electric grid) Voltage and power sensors Meters and breakers Fault detection Smart Transport Electric mobility EVs and HEVs High speed trains Infrastructure ,V21, V2v,V21+1 Smart Industry (Industrial environment) Lightening, security, actuators, production control, Robotics Elder care One key application of a wise house is to provide assistance for those with disabilities and elderly individuals. These home systems use assistive technology to accommodate an owner's specific disabilities. Voice control can assist users with sight and mobility limitations while alert systems are often connected on to cochlear implants worn by hearing-impaired users. They can also be equipped with additional safety features. These features can include sensors that monitor for medical emergencies like falls or seizures. Smart home technology applied during this way can provide users with more freedom and a far better quality of life. The term "Enterprise IoT" refers to devices utilized in business and company settings. By 2019, it's estimated that the EIoT will account for 9.1 billion devices The Current and Future Impact of IoT The IEEE has compiled data and makes the next claims about its current and future impact: In 2015, the worldwide wearables market had already increased 223% from the previous year (and data on Statista shows it increasing by another 243% between 2015 and 2022) By 2020, 250 million vehicles are getting to be connected to the online IoT will add 15 trillion dollars to the worldwide economy over subsequent 20 years There are getting to be 50 billion Internet-connected devices by the year 2020. Benefits of IoT The interconnection of these multiple embedded devices are getting to be resulting in automation in nearly all fields and also enabling advanced applications. this is often often resulting in improved accuracy, efficiency and economic benefit with reduced human intervention. the most benefits of IoT are: Improved Customer Engagement Technical Optimization Reduced Wastage Integrate and Adapt Business Model Better Business Decision IoT Enabling Factors Miniaturization Connectivity Advanced power sources and power management Inexpensive processors, sensors, and actuators Cloud-based processing Ubiquitous computing Challenges to IoT Security, Privacy and compliance. Market fragmentation Legacy infrastructure LAWN/WAN Connectivity Underutilized data Interoperability and Standards IoT Devices vs Computers IoT Device features a main function break free Computation Cars drive, Phone make calls, TVs displays shows Computation could also be a means to an end Computers main function is to compute, they're general purpose machines IoT Devices are Special Purpose Devices, software and hardware are efficient for the task - but inefficient for other tasks Technological Trends that cause IoT Cost of hardware has decreased allowing to be added to devices Smaller size and lesser weight needed to incorporate computation into devices Computation ability has increased tremendously Internet is out there everywhere Wireless Access (4G, Wi-Fi) has become cheap and ubiquitous, 5G on the way (No physical cables required) Data transmission cost is fairly low, internet bandwidth is high Cloud computing is getting used extensively (IoT devices are a window to those cloud services) Rise of Open Source Software (Rust, Web Assembly, Docker, Kubernetes, etc.) Environmental sustainability impact A priority regarding Internet-of-things technologies pertains to the environmental impacts of the manufacture, use, and eventual disposal of of those semiconductor-rich devices. Modern electronics are replete with an honest sort of heavy metals and rare-earth metals, also as highly toxic synthetic chemicals. This makes them extremely difficult to properly recycle. Electronic components are often incinerated or placed in regular landfills. Furthermore, the human and environmental cost of mining the rare-earth metals that are integral to modern electronic components continues to grow. Although IoT devices can help in some cases to reduce the energy consumption of certain applications, the impact of getting billions of devices connected and consuming power from batteries and from the grid will have a huge impact on energy consumption and CO2 emissions.
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Best Sites to Download Outro Music for Videos in 2020 [Free]

Best Sites to Download Outro Music for Videos in 2020 [Free] | technologies blog | Scoop.it
Where can I find high-quality and free outro music for my videos? Here are 5 outro music download sites for your reference.

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Enduring and emergent technologies of industry 4.0

Enduring and emergent technologies of industry 4.0 | technologies blog | Scoop.it
Posts & articles about emerging technologies of Industry 4.0 as Artificial intelligence, IoT, Cloud native computing and Block chain
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Tesla Erupts in Chaos After Senior Execs Leave, Musk Smokes Weed

Tesla Erupts in Chaos After Senior Execs Leave, Musk Smokes Weed | technologies blog | Scoop.it
The turmoil at Tesla Inc. has reached a fever pitch, with the news that two senior executives are leaving Elon Musk’s electric-car maker emerging hours after he smoked marijuana during a podcast interview streamed live online.

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The turmoil at Tesla Inc. has reached a fever pitch, with the news that two senior executives are leaving Elon Musk’s electric-car maker emerging hours after he smoked marijuana during a podcast interview streamed live online.  Chief Accounting Officer Dave Morton gave notice Tuesday that he was resigning less than a month into the job, according to a Friday filing. Tesla’s stock plunged, then extended declines after Gabrielle Toledano, the head of human resources who’s been on a leave of absence, told Bloomberg News that she won’t rejoin the company. Tesla has long struggled with high turnover involving its senior executives, and its finance team in particular has gone through a period of significant tumult. In the first quarter of this year, the company lost Morton’s predecessor, Eric Branderiz, and Susan Repo, who was treasurer and vice president of finance. CFO Deepak Ahuja retired in 2015, only to return last year when his successor, Jason Wheeler, quit after just 15 months.  In leaving the accounting chief job, Morton walked away from a $10 million new-hire equity grant that would have vested over four years. Friday was also slated to be the last day for Sarah O’Brien, Tesla’s vice president of communications, whose departure was announced last month.

 
 

Up in Smoke

Musk, 47, sipped whiskey during a more than 2 1/2-hour podcast interview with comedian Joe Rogan late Thursday that touched on topics from flame throwers and artificial intelligence to the end of the universe. While Musk said he was “not a regular smoker of weed,” he took a drag from what Rogan said was as a joint containing tobacco mixed with marijuana, which is legal in California.  “It’s quite hard to run companies. Especially car companies,” Musk said. “It’s very difficult to keep a car company alive.”  Philippe Houchois, an analyst at Jefferies Group LLC with a hold rating on Tesla shares, said that Musk “seems to be on a slightly self-destructive bent.” In an interview with Bloomberg Television, he called for the company to split up the chairman and CEO jobs. Musk has served both roles since October 2008, and shareholders rejected a proposal calling for an independent chairman earlier this year.  “The team, the skill set that have been phenomenal to create Tesla are not the ones we need for the next stage,” said Houchois, who has a $360 price target on the stock. “There’s a skill set that needs to be added at the top that Mr. Musk doesn’t have.”

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String Reference in Python

In python,there are a lot of things you can do with strings.Following are the most common string operations and string methods String Reference in Python String operations len(string)Returns the length of the string For character in string Iterates pver each character in the string If substring in string Checks whether the substring is part of the string string i Accesses the character at index i of the string,starting at zero string i:j Accesses the substring at index i,ending at index j-1.If i is omitted,its 0 by default.If j is omitted,its lens(string) by default. https://www.technologiesinindustry4.com/2020/10/ethereum-erc20.html String methods string.lower()/string.upper()Returns a copy of the string with all lower/upper case characters string.Istrip()/string.rstrip()/string.strip()Returns a copy of the string without left/right/left or right whitespace string.count(substring)Returns the number of times substring is present in the string string.isnumeric()Returns true if there are only numeric characters in the string.If not,returns False. string.isalpha()Returns True if there are only alphabetic characters in the string.If not,returns False. String.split()/string.split(delimiter) Returns a list of substrings that were separated by whitespace / delimiter. String.replace(old,new) Returns a new string where all occurrences of old have been replaced by new. delimte r.join(list of strings) Returns a new string with all the strings joined by the delimiter.
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How Fix Borderlands General Protection Fault Error [2020 Update]

How Fix Borderlands General Protection Fault Error [2020 Update] | technologies blog | Scoop.it
A lot of users reported that they encountered the Borderlands General protection fault error. This post will provide you with several troubleshooting methods.

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What is Rust Ownership?

Ownership concept Memory and Allocation In Rust, data can be stored either in stack or heap memory. Memory Types Stack Memory Heap Memory Stack and Heap Both are parts of memory to be used at runtime, but they are structured in different ways. Stack Stack rust ownership It stores values in the order it get them and removes the values in the opposite order. Referred to as Last In, First Out (LIFO). Stack: Think of a stack of plates Stack rust ownership When you add more plates,you put them on the top of the pile, and when you need a plate, you take one off the top. Adding or removing plates from the middle or bottom wouldn't work as well. Adding data is called pushing onto the stack, Removing data is called popping off the stack. Stack memory is an organized memory. It is faster than the heap memory because of the way it accesses the memory. All data stored on the stack must have a known, fixed size Stack Push and Pop Example: Stack rust ownership Stack rust ownership Stack: in action Stack rust ownership Stack: How it works? When code calls a function, the values passed into the function (including, potentially, pointers to data on the heap) and the function’s local variables get pushed onto the stack. When the function is over, those values get popped off the stack. Heap The Heap is Less Organized. Requested from OS. Slower. Follow pointer. large amount...take time to mange data in the heap. Data with a size that is unknown at compile time or a size that might change must be stored on the heap. Heap rust ownership Heap: Allocation When you put data on the heap, you ask for some amount of space from OS. The operating system finds an empty spot in the heap that is big enough, marks it as being in use, and returns a pointer, which is the address of that location. Why pushing to the stack is faster than allocating on the heap ? Because the operating system never has to search for place to store new data;that location is always at the top of the stack. Why accessing data in the heap is slower than on the stack ? Allocating space on the heap requires more work,because you ask for some amount of space to operating system every time. OS has to follow the pointer every time. Ownership All programs have to manage the way they use a computer’s memory while running. Some languages have garbage collection that constantly looks for no longer used memory as the program runs. In other languages, the programmer must explicitly allocate and free the memory. Rust uses a third approach wherein memory is managed through a system of ownership. Ownership is managed with a set of rules that the compiler checks at compile time. None of the ownership features slow down your program while it’s running. In simple words for understanding purpose…… Ownership is the transfer of currently possessed entity to another party which causes the previous owner to no longer have access to the object that is being transferred. In Rust, there are very clear rules about which piece of code owns a resource. In the simplest case, it’s the block of code that created the object representing the resource. At the end of the block the object is destroyed and the resource is released. Example fn main() {// s is not valid here, it’s not yet declared let s = "hello"; // s is valid from this point forward // do stuff with s println!("{}", s); }// this scope is now over, and s is no longer valid In the above example the letter or variable “s” is the owner of the word “hello” and is valid from the point of declaration after the start of the parenthesis “{“ and remains valid until the end of the parenthesis “}”. Ownership is Rust’s most unique feature, and it enables Rust to make memory safety guarantees without needing a garbage collector. Why Ownership Keeping track of what parts of code are using what data on the heap, minimizing the amount of duplicate data on the heap, and cleaning up unused data on the heap so you don’t run out of space are all problems that ownership addresses. All primitive data types (integers, booleans, string literals) and pointers (address of heap data) are stored on stack whereas for more complicated data types we have heap. Ownership Rules Rule # 1 Each value in Rust has a variable that's called its owner. Example let a = “Hello world!”; ↙ ↘ Variable Value In the above example the variable i.e "a" is also the owner of the value "Hello world!". Rule # 2 There can only be one owner at a time Example let a = String::from(“Hello”); –> here variable “a” is the owner let b = a; –> here the value of “a” is moved to variable “b” which now becomes the owner of “Hello” Considering both variables “a” and “b” are within the same scope. Rule # 3 When the owner goes out of scope, so does the value Example fn main() { { –> “a” is not valid here, it’s not yet declared let a = “Hello"; –> “a” is valid from this point forward –> do stuff with “a” } –> this scope is now over and “a” is no longer valid } For more detail click
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Why Algorithms shape what we see Online

Why Algorithms shape what we see Online | technologies blog | Scoop.it
Technology

Whether it's suggesting what video to watch next or items you might be interested in buying online, algorithms have incredible influence and power in our everyday lives.



Credit Forbes

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Windows Defender Firewall Has Blocked Some Features of This App

Windows Defender Firewall Has Blocked Some Features of This App | technologies blog | Scoop.it
This post will show you how to remove the Windows Defender Firewall has blocked some features of this app alert on your Windows computer.

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