Odisha : Travel details mandatory for air and train passengers without -ve reports

 

Odisha : Travel details mandatory for air and train passengers without -ve reports

 

* All Train and Air passengers without RT-PCR negative reports or vaccination reports or vaccination certificates would have to furnish their details at Bhubaneswar's Biju Patnaik International Airport and the city railway station , as per orders released from Monday .

 

* Following this , all the passengers have to register themselves following which exit passes would be issued to the registered passengers

 

* According to the orders and press release of the state government , the Bhubaneswar Municipal Corporation (BMC) will scrap the practice of spot RT-PCR testing

 

* Currently , any passenger arriving at the railway station has to produce an RTPCR negative report or a proof of the full dose of vaccine taken as a part of standard operating procedures released as standard protocol for allowing transit for the arriving passengers

 

* In case , a passenger fails to produce any of the above details , the passenger would have to go through the registration counter , fill in a form furnishing the details of the place .. they are from and the designated destination they are up to

 

* After the final registration process is over , the passenger would be provided with an exit pass which he/she would have to show at the place of exit where the Railway Police would be deployed to check

 

* For passengers belonging to Bhubaneswar , the BMC would be keeping their data for further tracking , monitoring and follow-up processes

 

* This data of the number of outbound passengers ( going to other different districts ) would be sent to the respective district adminsitrations over email

 

* The current footfall numbers recorded for Bhubaneswar is around 20,000 passengers per day with over 60 trains passing through Bhubaneswar on a daily basis

An article on Pesticide in Coconut Water (Bullet Points)

 

An article on Pesticide in Coconut Water (Bullet Points)

 

* Coconut farmers use a pesticide called " Monocrotophus " to kill pests and insects and obtain a good yield

 

* Most of the Coconut farmers wait for 45 day for harvest of their produce but some of the farmers harvest earlier for more money

 

* Kutch University in Rajasthan reports to have developed a reagent to detect chemical residue in a coconut or fruit water

 

* The chemical reagent can be used by extracting coconut peel or coconut water

 

* The colour of the coconut peel / coconut water would turn red if the coconut water contains any pesticide

 

* The varsity has planned to commercialise the discovered detection solution if it gets patent for its reagent

 

 

UpStox Stock broker farm hacking case , 25 lakhs customers data stolen from database

 

UpStox Stock broker farm hacking case , 25 lakhs customers data stolen from database

* Upstox , the country's second largest stock broker in terms of number of customers operating over the platform reported a major online security breach with hackers stealing the KYC and customers data .

 

* The data breach happened at a third party data warehouse and the collected data has been put / auctioned /sold over the dark web as per sources

 

* Dark Web is the place where illegal transaction of confidential data takes place between the parties involved in this criminal act .

 

* It is believed that such kind of data is leveraged by data brokers / data breachers to hack into the bank/demat accounts of the purported customers in order to steal money from them

 

* As you may be aware through some movies in which a hacker generally writes an automated code which would allow the hacker to creep into multiple accounts using the login information in an automated manner and deduct some token amount as mentioned in the program with respect to each of the accounts which forms as a adhoc database for the process . Following this , some amount/

all amount is auto deducted from the customers account and it is credited into the account of the program (here , its referred to as Malware) creator for the transaction process

News Article - PM Narendra Modi's call to the nation : " Tika Utsav is another beginning of another war against Covid "

 

PM Narendra Modi : " Tika Utsav is another beginning of another war against Covid "

 

* 4 day Tika Utsav (Vaccine Festival) started off on Sunday by Indian PM Narendra Modi at New Delhi

 

* Aimed at optimum utilisation of country's vaccination capacity

 

* Success over Covid can be determined by the country's awareness of the micro containment zone rules which is the home itself with strict adherence to protocols like not to leave the house premises when there is no need , when the eligible members of the house are vaccinated , when everyone adheres to rules for wearing of masks and adherence to other rules

 

* PM attributed the accelerated vaccination drive as the second round of the fight against Covid-19

 

* PM has coined a four point action plan

01) Each One , Vaccinate One

02) Each One , treat One

03) Each One , Save One

04) Enforcement of Micro Containment Zones guidelines

 

* This four day Vaccination Festival will conclude on the birthday of Dalit Reformer and Father of the Constitution of India Mr BhimRao Ambedkar

Working with Data in Machine Learning - An overview of methodology for working over Data/Datasets in Machine Learning using R and Python

 

        Working with Data in Machine Learning

 

* Machine Learning is one of the most appealing subjects because it allows machines to learn from real world examples such as sales records , signals from sensors and textual datastreaming from internet and then determine what such data would imply with the help of that subject

 

* The most common outputs that can commence from machine learning algorithms is prediction of the future , prescriptions and prescriptive knowledge for design and build up of applications etc

 

* Some of the common outputs that can come from machine learning algorithms is the following : prediction of the future , prescription to act on some given knowledge or information , creation of new knowledge in terms of examples categorised by groups

 

* Some of the applications which are already in place and have become a reality thanks to leveraging the use of such knowledge are the following things :

01) Diagnosing hard to find diseases

02) Discovering criminal behaviour and detecting criminals in action

03) Recommending the right product to the right person

04) Filtering and classifying data from internet at an big scale

05) Driving a car autonomously etc

 

* The mathematical and statistical basis of machine learning makes outputting such useful results possible

 

* One can use Math and Statistics over such accumulated data which could enable algorithms to understand anything with a numerical basis

 

* In order to begin the process of working with Data , one should represent the solution to the problem in the form of a number .

 

* For example , if one wants to diagnose a disease using a machine learning algorithm , one can make the response to a particular learning problem a 1 or 0 (binary response) which would inform about the illness of the person . A value of 1 would indicate that the person is ill , with a value of 1 stating that the person is ill or not .

Alternatively , one can use a number between the values 0 and 1 to convey an

MapReduce Jobs Execution

 

MapReduce Jobs Execution

 

* A MapReduce job is specified by a Map program and the Reduce program along with the data sets associated with a MapReduce Job

 

* There is another master program that resides and runs endlessly over a NameNode which is called as the "Job Tracker" which tracks the progress of MapReduce jobs from beginning to completion stage

 

* Hadoop moves the Map and Reduce computation logic to all the DataNodes which are hosting a fragment of data

 

* Communication between the nodes is accomplished using YARN , Hadoop's native resource manager

 

* The master machine (NameNode) is completely aware of the data stored over each of the worker machines (DataNodes)

 

* The Master Machine schedules the " Map / Reduce jobs " to Task Trackers with full awareness of the data location which means that Task Trackers residing within the hierarchial monitoring architecture being thoroughly aware of the residing data and their location .

By this the job tracker would be able to fully address the issue of mapping the requisite jobs to their job queues in the form of Job/Task tracker .

 

For example , if "node A" contains data (x,y,z) and "node B" contains data (a,b,c) , the job tracker schedules node B to perform map or Reduce Tasks on (a,b,c) and node A would be scheduled to perform Map or Reduce tasks on (x,y,z). This helps in reduction of the data traffic and subsequent choking of the network .

 

* Each DataNode within the MapReduce Jobs has a master program which is called the Task Tracker

 

Math behind Machine Learning - An introductory article on the usage of mathematics and statistics as the foundation of Machine Learning

 

        Math behind Machine Learning

 

* If one wants to implement existing machine learning algorithms from scratch or if someone wants to devise newer machine learning algorithms , then one would require a profound knowledge of probability , linear algebra , linear programming and multivariable calculus

 

* Along with that one may also need to translate math into a form of working code which means that one needs to have a good deal of sophisticated computing skills

 

* This article is an introduction which would help someone in understanding of the mechanics of machine learning and thereafter describe how to translate math basics into usable code

 

* If one would like to apply the existing machine learning knowledge for implementation of practical purposes and practical projects , then one can leverage the best of possibilities of machine learning over datasets using R language and Python language's software libraries using some basic knowledge of math , statistics and programming as Machine learning's core foundation is built upon skills in all of these languages

 

* Some of the things that can be accomplished with a clearer understanding and grasp over these languages is the following :

 

1) Performance of Machine Learning experiments using R and Python language

2) Knowledge upon Vectors , Variables and Matrices

3) Usage of Descriptive Statistics techniques

4) Knowledge of statistical methods like Mean , Median , Mode , Standard Deviation and other important parameters for judging or evaluating a model

5) Understanding the capabilities and methods in which Machine Learning could be put to work which would help in making better predictions etc