The Role of Computers in the Development of Odia Language

Any language computer can be useful if the above two requirements are met. But we can only accept such behavior as a modern writing system. In other words, in the past we used to write with palm leaves and pencils, then we used to write on paper, then we used typewriters and typewriters. Now we can write via computer. This is the best way to write and print. This requirement is available in almost all languages, this requirement has been met by the Odia language since the 180s, which means that this year we have been able to type the letters of the Odia language on the computer and print it on the printer. This is the first step in using a computer language. The second step in making a language useful to a computer is: understanding the computer. Computers understand a language through a variety of programs. This requires connecting the operating system to a new language. It is imperative that the language be integrated into the Unicode system. Unicode has provided a code for the scripts of the world's most computer-friendly languages. This code can be understood by the operating system. As a result, it is possible to Unicode the computer by naming that language, sorting it from scratch, searching for a file or folder named in that language, deleting any incorrect word koji, and so on. Fortunately, the Odia language scripts were included in the Unicode in 2006. Odia is the third largest Indian language in this regard. Keywords: typewriters, computer, languages, Unicode, folder, deleting, scripts, Odia, Indian language,

FACIAL RECOGNITON BASED DOOR LOCKING AND UNLOCKING MECHANISM BASED ON IOT

Now a days Security Has Become an Important Issue to Be Resolved. So, We Are Solving That Matter by Using Updated Technology. This Project “Face Recognition Based Door Unlocking System” deals with The Conception to Protect Locking Mechanism Utilizing IoT for Door Unlocking Process to Give Essential Security to Our House, Bank Lockers and others. In This Project We Look into the Accuracy of The Face Recognition Algorithms Using OpenCV And Python Computer Language. Local Binary Pattern Histogram Algorithm Is Used for Face Recognition. Training and Identification Is Done in Raspberry pi.

Prophecy on Programming Language using Machine Learning Algorithms

A programming language is a computer language developers use to develop software programs, scripts, or other sets of instruction for computers to execute. It is difficult to determine which programming language is widely used. In our work, I have analyzed and compared the classification results of various machine learning models and find out which programming language is widely used by developers. I have used Support Vector Machine (SVM), K neighbor classifier (KNN),Decision Tree Classifier(CART) for our comparative study. My task is to analyze different data and to classify them for the efficiency of each algorithm in terms of accuracy, precision, recall, and F1 Score. My best accuracy was 94.29% percent which was found using SVM. These techniques are coded in python and executed in Jupyter NoteBook, the Scientific Python Development Environment. Our experiments have shown that SVM is the best for predictive analysis and from our study that SVM is the well-suited algorithm for the prediction of the most widely used programming language.

Adaptive vector greedy splitting algorithm

We introduce a new transform through a construction that we have called the Adaptive Vector Greedy Splitting algorithm. The main idea behind this algorithm is an optimization step based on the simple Bathtub Principle. We use the Vector Greedy Splitting algorithm to build orthonormal bases for a given vector of random variables (also called signals). A particular basis constructed in this way may be used for signal coompression, audio pattern recognition and other applications of signal processing. We compare performance of the Vector Greedy Splitting algorithm with the Haar wavelet transform applied to the same vector of input signals. The implementation of the algorithms and statistics accumulation are made using the ANSI C computer language and Matlab. The work uses advanced methods of Computer Engineering and Digital Signal Processing.

Adaptive vector greedy splitting algorithm

We introduce a new transform through a construction that we have called the Adaptive Vector Greedy Splitting algorithm. The main idea behind this algorithm is an optimization step based on the simple Bathtub Principle. We use the Vector Greedy Splitting algorithm to build orthonormal bases for a given vector of random variables (also called signals). A particular basis constructed in this way may be used for signal coompression, audio pattern recognition and other applications of signal processing. We compare performance of the Vector Greedy Splitting algorithm with the Haar wavelet transform applied to the same vector of input signals. The implementation of the algorithms and statistics accumulation are made using the ANSI C computer language and Matlab. The work uses advanced methods of Computer Engineering and Digital Signal Processing.

Financial Transactions Using FINTECH during the Covid-19 Crisis in Bulgaria

In the context of current crises following COVID-19 and growing global economic uncertainties, the issues regarding financial transactions with FINTECH are increasingly apparent. Consequently, in our opinion, the utilization of FINTECH financial transactions leads to а risk-reduction approach when in contact with other people. Moreover, financial transactions with FINTECH can save up customers’ pecuniary funds. Therefore, during crises, FINTECH applications can be perceived as more competitive than the traditional banking system. All the above have provoked us to conduct research related to the utilization of financial transactions with FINTECH before and after the COVID-19 crisis outbreak. The aim of the article is to present a survey analysis of FINTECH utilization of individual customers before and after the crisis in Bulgaria. The methodology includes a questionnaire survey of 242 individual respondents. For the data processing, we implemented statistical measures and quantitative methods, including two-sample paired t-tests, Levene’s test, and ANOVAs performed through the computer language Python in a web-based interactive computing environment for creating documents, Jupyter Notebook. The findings bring out the main issues related to the implementation of financial transactions with FINTECH under the conditions of the crisis. The findings include the identification of problems related to FINTECH transactions during the COVID-19 crisis in Bulgaria.

Programming as Language and Manipulative for Second-Grade Mathematics

This article reports on an exploration of how second-graders can learn mathematics through programming. We started from the theory that a suitably designed programming language can serve children as a language for expressing and experimenting with mathematical ideas and processes in order to do mathematics and thereby, with appropriate tasks and teaching, learn and enjoy the subject. This is very different from using the computer as a teaching app or a digital medium for exploration. Children tackled genuine puzzles – problems for which they did not already have a pre-learned solution. So far, we have built four microworlds for second-graders and tested them with a diverse population of well over three hundred children. The microworlds focus on the most critical second-grade mathematical content (as mandated in state standards), let children pick up all key programming ideas in contexts that make them ‘obvious’ (to maintain focus on the mathematics) and suppress all other distractions to minimize overhead for teachers or students using the microworlds. Because children see the results of the actions they articulate (in the computer language, Snap!), they can evaluate their methods and solutions themselves. The feedback is purely the outcome, not happy or sad sounds from the computer. Notably, nearly all children showed intense engagement, some choosing microworlds even outside of mathematics time. Teachers spontaneously reported this as well, with special mention of children whom they found hard to engage in regular lessons. We report our experiments and observations in the spirit of sharing the ideas and promoting more research.

Can Students’ Computer Programming Learning Motivation and Effectiveness Be Enhanced by Learning Python Language? A Multi-Group Analysis

Python language has become the most popular computer language. Python is widely adopted in computer courses. However, Python language’s effects on the college and university students’ learning performance, motivations, computer programming self-efficacy, and maladaptive cognition have still not been widely examined. The main objective of this study is to explore the effects of learning Python on students’ programming learning. The junior students of two classes in a college are the research participants. One class was taught Java language and the other class was taught Python language. The learning performance, motivations, and maladaptive cognition in the two classes were compared to evaluate the differences. The results showed that the motivations, computer programming self-efficacy, and maladaptive cognition on the learning performance were significant in the Python class. The results and findings of this study can be used in Python course arrangement and development.