Python Programming

As smart phones, tablets and many other portable devices are getting closer and closer to the humankind, many technologies are being released day by day. Among them, security has been one major aspect where much research has been done. Though modern vehicle security systems have been developed, there are certain limitations which are experienced in the practical usage of such applications. We realized that though many such systems were available, not many had the capability of providing a video feed via an IP along with triggering an alarm and so forth using a mobile device. The present systems in the market are quite expensive and use too advanced technologies which require specialist installation and maintenance. Mobile integration is also not as optimized as it should be. Therefore our main goal in this research was to “integrate” all these features and build a coherent mobile car security system with a centralized administration. The basic underlying idea of this project therefore is to provide a “practical” and a “cost effective” car security system to the general public. In this project, we provide a camera feed (via IP) of the vehicle to the vehicle owner to his / her mobile device and then enable the user to control the system remotely. It also can detect any human activity, using the switches and report it to the owner via an auto generated sms notification. We have used a web camera which is connected to a Raspberry Pi chipset and powered using a power bank, switches, LED bulbs, 2 speakers and a Wi-Fi adaptor to build the system. When someone tends to open the door lock of the vehicle, a switch which is situated under the door lock of the vehicle, will trigger giving a signal to activate the chipset and send a sms notification to the owner. Then the owner can get an instant view of the situation (on his mobile), and if he wishes to, he can take necessary steps to protect his vehicle from any danger. We have tested the implementation under lab conditions and the results have been quite satisfactory. We were able to achieve the main goals which we wanted to achieve. However it needs to be noted that if this is to be implemented commercially we would have to develop our system to use “port forwarding” (so that the owner may view the video from anywhere in the world), and a city-wide Wi-Fi network or a high-bandwidth data connection would be necessary (HSDPA / WCDMA) for the system to work smoothly.

Viele Dissertationen in der Archäologie enthalten am Ende der Arbeit einen Katalog, in dem die untersuchten Daten in einem bestimmten System aufgeschlüsselt präsentiert werden. In diesem Beitrag wird eine effiziente Gestaltung eines Kataloges und dessen Einbindung in den Fließtext vorgestellt.

'El Diario de Juárez' is a local newspaper in a city of 1.5 million Spanish-speaking inhabitants that publishes texts of which citizens read them on both a website and an RSS (Really Simple Syndication) service. This research applies natural-language-processing and machine-learning algorithms to the news provided by the RSS service in order to classify them based on whether they are about a traffic incident or not, with the final intention of notifying citizens where such accidents occur. The classification process explores the bag-of-words technique with five learners (Classification and Regression Tree (CART), Naïve Bayes, kNN, Random Forest, and Support Vector Machine (SVM)) on a class-imbalanced benchmark; this challenging issue is dealt with via five sampling algorithms: synthetic minority oversampling technique (SMOTE), borderline SMOTE, adaptive synthetic sampling, random oversampling, and random undersampling. Consequently, our final classifier reaches a sensitivity of 0.86 and an area under the precision-recall curve of 0.86, which is an acceptable performance when considering the complexity of analyzing unstructured texts in Spanish.

To buy this project in ONLINE, Contact:
Email: [email protected],
Website: https://www.jpinfotech.org

Location Inference for Non-geotagged Tweets in User Timelines

Social media like Twitter have become globally popular in the past decade. Thanks to the high penetration of smartphones, social media users are increasingly going mobile. This trend has contributed to foster various location based services deployed on social media, the success of which heavily depends on the availability and accuracy of users' location information. However, only a very small fraction of tweets in Twitter are geo-tagged. Therefore, it is necessary to infer locations for tweets in order to attain the purpose of those location based services. In this paper, we tackle this problem by scrutinizing Twitter user timelines in a novel fashion. First of all, we split each user's tweet timeline temporally into a number of clusters, each tending to imply a distinct location. Subsequently, we adapt two machine learning models to our setting and design classifiers that classify each tweet cluster into one of the pre-defined location classes at the city level. The Bayes based model focuses on the information gain of words with location implications in the user-generated contents. The convolutional LSTM model treats user-generated contents and their associated locations as sequences and employs bidirectional LSTM and convolution operation to make location inferences. The two models are evaluated on a large set of real Twitter data. The experimental results suggest that our models are effective at inferring locations for non-geotagged tweets and the models outperform the state-of-the-art and alternative approaches significantly in terms of inference accuracy. SYSTEM REQUIREMENTS: HARDWARE REQUIREMENTS:

Man Eating Chicken ( মানুষ মুরগী খায় ) এবং Man-eating Chicken (মানুষখেকো মুরগী )

শুধু মাত্র একটা “-” ( ড্যাশ ) ব্যবহারের কারণে, উপরের বাক্য দুটির মধ্যে যে সম্পূর্ণ বিপরীতধর্মী অর্থ বহন করছে, তা আমরা মানুষেরা বুঝলেও, কম্পিউটার বোঝে না কারন সে একটা বোকা বাক্স। প্রথম ক্ষেত্রে, অর্থটা দাড়ায় “মানুষ মুরগী খায়”, দ্বিতীয় ক্ষেত্রে “মুরগীটি নরখাদক”। এক ড্যাশ দ্বারা সৃষ্ট দুটি ভিন্ন অর্থ মানুষের পক্ষে বোঝাটা সহজ হলেও, কম্পিউটার এই ধরণের অনিশ্চয়তা সামাল দিতে পারে না। কম্পিউটার কোডের অর্থ অনুমান করে না। কোডের অর্থ বোঝার জন্য কম্পিউটারের প্রয়োজন স্পষ্ট দিকনির্দেশ এবং বিবৃতি।

আপনি যখন কোড লিখছেন, আপনার ব্যবহৃত function অথবা variable এর নামগুলির জন্য আপনি নিজেই সমস্যার সম্মুখীন হতে পারেন।

Source: https://journal.stacklearner.com/python-identifiers
Source: https://courses.stackschool.co/

Viele Dissertationen in der Archäologie enthalten am Ende der Arbeit einen Katalog, in dem die untersuchten Daten in einem bestimmten System aufgeschlüsselt präsentiert werden. In diesem Beitrag wird eine effiziente Gestaltung eines Kataloges und dessen Einbindung in den Fließtext vorgestellt.

Some studies suggest that more than 25% of the tech companies are now using or considering Python in their technology stack. Building healthcare solutions with Python enables companies to make the best use of data.
Checkout blog on Why use Python for building a Healthcare Application: https://www.botreetechnologies.com/blog/python-in-healthcare-application/

Hire Python developers from BoTree Technologies for high-performance healthcare apps:
https://www.botreetechnologies.com/python-development

— Availability of mining machines plays a significant role in mine production. Dragline's reliability has a great impact on sustaining economic feasibility of open cast coal mining projects. In that sense, reliability of draglines and optimizing its preventive maintenance are key issues to be addressed. The objective of this study is to apply machine learning methodologies for classifying failure types of a dragline based on a real data. The mean time between failure data was acquired from an operating open cast coal mine in Turkey. Three modified form of K-Nearest Neighbors algorithms have been used as a predictor for failure classification. An approximation function has been generated based on the time to failure and breakdown type. In case of parameter tuning, cross validation method has been utilized. This caused more reliable evaluation of the test sample, so average testing performance has been used for test data estimation. The basic model was for parameter tuning; Moreover, for achieving more efficient parameter Grid Search method was utilized. Since, usage of the algorithm is computationally expensive, so Randomized Search method has been carried out in order to figure out the functionality of modeled function in the high dimension datasets. The results of the study revealed that the application of K-Nearest Neighbors method reached the Regression Analysis of 73 percent. Thus, the higher accuracy of prediction of failure type can be helpful in prognostic of dragline's procedure. The main novelty of this study is utilization of machine learning approach for dragline maintenance for the first time.

K-Means, PCA, and Dendrogram on the Animals with Attributes Dataset

To download the dataset, go to:
https://attributes.kyb.tuebingen.mpg.de/AwA-base.tar.bz2

This Document is also available in ipython notebook format at:
https://github.com/mGalarnyk/DSE210_Probability_Statistics_Python/blob/master/K-Means%2C%20PCA%2C%20and%20Dendrogram%20on%20the%20Animals%20with%20Attributes%20Dataset.ipynb

About the dataset: This is a small dataset that has information on about 50 animals. The animals are listed in classes.txt. For each animal, the information consists of values for 85 features: does the animal have a tail, is it slow, does it have tusks, etc. The details of the features are in the predicates.txt. The full data consists of a 50 x 85 matrix of real values, in predicate-matrix-continuous.txt. There is also a binarized version of this data, in predicate-matrix-binary.txt.

This document goes over K-Means, PCA, and Hierarchical Clustering of the Animals with Attributes Dataset.

В статье рассматриваются перспективы внедрения дисциплины «Профессионально ориентированное программирование» при обучении лингвистов-преподавателей; указывается на ее соответствие ФГОС ВО по направлениям подготовки «45.03.02 Лингвистика» и «45.04.02 Лингвистика»; в качестве предмета изучения выбираются языки программирования HTML (включая CSS и JavaScript) и Python (включая PyQt5 и web2py); дается краткий обзор двух учебных пособий по новой дисциплине.
Выходные данные: Горожанов А. И. Дисциплина «профессионально ориентированное программирование» для лингвистов – потенциальных авторов электронных учебников // Труды международного института языков государств – участников СНГ и института регионоведения консорциума гуманитарных университетов государств – членов ШОС. – М.: ФГБОУ ВО МГЛУ, 2015. – 190 с. (Сетевое электронное научное издание «Вестн. Моск. гос. лингвист. ун-та»; вып. 25 (736). Серия Языкознание и литературоведение). – С. 147–156. – ISSN 2309-9208. – СМИ Эл. № ФС 77-59634.

A lawnmower is a machine that uses a revolving blade or blades to cut a lawn grass. Many designs have been made, each suited to a particular purpose. Manual grass cutter has environmental issues regarding pollution's and also require the need of man power to operate and has a great maintenance to its engine. This robot is design to be environment friendly and operated by a rechargeable battery and can be describe as an intelligent robot because the micro-controller receives information from several sensors (PIR, Humidity and Bumper switches) connected to it in avoiding obstacle to ensure a neat pattern of cut and use the information to actuate the left and right motors driving the wheels and the center motor driving blade and at the same time it obeys all parameters of work and its program database. The result obtained from the test and analysis carried out shows that our development of the autonomous lawn mower from locally sourced materials is highly recommended because it is safer to use, environmental friendly, easy to operate, and fully automated.

ABSTRACTThe growth of the telecommunication industry is fast-paced with ground-breaking engineering achievements. Notwithstanding the technological advancement in the industry, it had continued to cope with the phenomenon ofresource constraint in portable mobile telecommunication devices compared to fixed and tethered devices. Portable mobile handheld devices have very low computational, storage and energy carrying capacity occasioned by the needs to satisfy portability, very small form factor, ergonomics, style and trends. Solutions such as cloudlets, cyber foraging, mobile cloud computing (MCC), and more recently but most applicable, multi-access edge computing (MEC) have been proffered with different application methodologies including computational offloading, distributed computing, thin clients, middleware, mobile environment cloning as well as representational state transfer. There is a need to satisfy requirements of new and emerging use cases, especially the deployments of 5...

This master project report titled, ‘Document Management Software Tool for Safety-related Application (ISO 26262)’ was prepared because it represents a certain evaluation grade for the master course on Functional Safety Engineering at the University of Kassel, Hessen, Germany.
This report consists of the ideas and demonstrations on the document management software tool designed for creating highly technical documentation (work products) for ISO 26262 compliant electrical and/or electronic (E/E) safety-related system or sub-system, automatically, repeatedly, efficiently, and quickly. The software tool was designed using the graphical user interface (GUI) library, Tkinter, from the Python programming language and the codes were written in the PyCharm, which is an integrated development environment (IDE) suitable for executing the Python programming language.
This report has been organized to highlight some of the fundamental concepts of functional safety, relevant information on documentations mentioned in the generic functional safety standard series IEC 61508, also in functional safety standard series for road vehicles ISO 26262. Followed by the approach and methodology of the document management software tool designed for this master course project. All the relevant documentation templates used by the software tool is provided in the annex, and in the reference section of this report all the information used in writing this report, as well as designing the software interface are provided for further understanding on any particular topic. The source code used for developing the document management software tool is not included in this report but could be made available on request.
Towards the end of the report, in the future work section, a discussion on the potential improvement points of this software tool is emphasized, which could be used as a guide for the future works in the similar topic. Finally, the project report ends with the conclusion section which summarizes the important points of this project report as a quick recap.

Numpy est une bibliothèque phyton très importante pour les travaux en machine learning, deeplearnig,..
Avec Numpy, on dispose d'un objet très important qu'on appelle NDArray qui nous permettra de créer et de manipuler des tableaux à une dimension, 02 dimensions, .., n dimensions. De plus grâce à Numpy, vous aurez plusieurs méthodes qui vous faciliterons la vie.

https://towardsdatascience.com/data-smoothing-for-data-science-visualization-the-goldilocks-trio-part-1-867765050615

Making peace with piecewise. We've all heard that information is beautiful. But then life happens, and we find ourselves trying to prettify the mess that often is reality…

To buy this project in ONLINE, Contact:
Email: [email protected],
Website: https://www.jpinfotech.org

SentiDiff: Combining Textual Information andSentiment Diffusion Patterns for TwitterSentiment Analysis

Twitter sentiment analysis has become a hot research topic in recent years. Most of existing solutions to Twitter sentimentanalysis basically only consider textual information of Twitter messages, and struggle to perform well when facing short and ambiguousTwitter messages. Recent studies show that sentiment diffusion patterns on Twitter have close relationships with sentiment polarities ofTwitter messages. Therefore, in this paper we focus on how to fuse textual information of Twitter messages and sentiment diffusionpatterns to obtain better performance of sentiment analysis on Twitter data. To this end, we first analyze sentiment diffusion byinvestigating a phenomenon called sentiment reversal, and find some interesting properties of sentiment reversals. Then we considerthe inter-relationships between textual information of Twitter messages and sentiment diffusion patterns, and propose an iterativealgorithm called SentiDiff to predict sentiment polarities expressed in Twitter messages. To the best of our knowledge, this work is thefirst to utilize sentiment diffusion patterns to help improve Twitter sentiment analysis. Extensive experiments on real-world datasetdemonstrate that compared with state-of-the-art textual information based sentiment analysis algorithms, our proposed algorithmyields PR-AUC improvements between 5:09% and 8:38% on Twitter sentiment classification tasks.

IRIS data set analysis using python (Multivariate Gaussian Classifier, PCA, Python)
Download the IRIS data set from: https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data
This is a data set of 150 points in R4, with three classes; refer to the website for more details of the
features and classes.
(a) Use a PCA projection to 2d to visualize the entire data set. You should plot different classes using
different colors/shapes. Do the classes seem well-separated from each other? (b) Now build a classifier for this data set, based on a generative model.

<p>The necessity of sustainable development for landscapes has emerged as an important theme in recent decades. Moreover, past landscape reconstruction enables a better understanding of human resilience to climatic and environmental changes in different periods and locations, and illustrates examples of sustainable development in the past. Free and open-source (FOSS) datasets of satellite imagery offer considerable opportunities for landscape heritage stakeholders both for recording and monitoring activities. In this research, a completely FOSS-cloud procedure to enhance the detection of palaeo-landscape features is presented. Sentinel - 2 satellite imagery has been retrieved in the Google Earth Engine dataset collection and analysed through a Python script code realized in Google Colaboratory. A multi-temporal approach has been adopted to investigate the potential of satellite imagery to detect buried features along with Spectral Index (i.e., RGB, False Short Wave Infrared Colour and Bare Soil Index) and Spectral Decomposition analysis (i.e., Hue, Saturation and Value, Tasselled Cap Transformation and Principal Component Analysis). This procedure has been tested in the Po Plain (Northern Italy), chosen because it is characterized by human-landscape interaction since the Mid-Holocene. Thanks to its complex settlement and land-management history, the Po Plain represents an ideal laboratory to assess the potentiality of satellite imagery to enhance riverscapes’ palaeo-features.  The outputs obtained can be visualized directly in the Google Colaboratory browser or downloaded via Google Drive for further graphical applications or spatial analysis. The buried features detected have been checked through the available geomorphological and archaeological literature; published case studies interpreting the occurrence of buried features served as a benchmark to validate the script code developed. This research represents one of the first applications of the GEE Python API in landscape studies. The main advantages of this procedure consist of: i) being FOSS, all the software used here are open-licensed; ii) working in cloud, no powerful hardware is necessary to run the script code; iii) high adaptability, changing the ROI is possible to calculate SI and SD outputs for any area of the world; iv) very basic coding skills are required to adapt the code to a ROI with different environmental characteristics. The development of FOSS-cloud procedures could support the identification, conservation and management of cultural and natural heritage anywhere around the world. In remote areas or where local heritage is threatened as a result of political instability, climate change or other factors, FOSS-cloud protocols can facilitate the application of new scientific methods and enable the dissemination of and access to scientific information.</p>

We introduce in this paper an application developed in the Python programming language that can be used to generate digital signals with known frequencies and amplitudes. These digital signals, since have known parameters, can be used to create benchmarks for test and numerical simulation.

Optimization algorithms are search system where the target is to get a good solvency of a problem. The knowledge of animals and insects have a counted models of swarm intelligence. Swarm intelligence has become a powerful technique for solving many tough optimization problem.in our thesis paper we propose some existing meta-heuristic method named as Ant colony Optimization, Bat algorithm and bee algorithm. After a detailed explanation, we compared them with each other and tried to show which one is better and further studies are also discussed.

Abstract This study uses a novel approach to describe modern English academic texts in terms of the amount and distribution of syntactic subordination, coordination and phrasal structures. Inconsistent results have been reported in previous scholarship regarding the trajectory of syntactic complexification based on English language backgrounds and linguistic proficiency of writers. For the first time, a combination of two predictive statistical modelling methods of mixed-effects modelling and supervised machine learning modelling with random forest is used to examine the extent to which the type, amount, and distribution of these syntactic structures can be attributed to a text-intrinsic feature (sub-genres or rhetorical sections of academic register) and a text-extrinsic factor (English language background based on academic context) in a corpus of master’s dissertations. To revisit the theories of English L1 vs. L2 texts, strong predictors of syntactic complexity across academic writings of EFL, ESL, and English L1 postgraduate students were identified. The findings show that EFL texts are dominantly subordinate in nature, English L1’s dominantly phrasal, and the ESL dissertations exhibited similar amounts of subordination and phrasal structures. Distinct syntactic structures also characterise rhetorical sections: abstracts are predominantly phrasal, literature reviews distinctly subordinate, and conclusion sections have noticeable amounts of verb phrases.

Skin cancer is the most common among all cancers and its early diagnosis increases the patient's chances of healing. One of the ways to make this diagnosis is through dermatoscopy. Dermatoscopy is a technique that consists of recognizing structures present in the skin, not visible to the naked eye. Therefore, for assisting the use of dermatoscopy by health professionals, this work presents a device to support skin cancer recognition using the histogram of oriented gradients and machine learning, based on the ABCDE rule.

Object-Z is an object-oriented specification language which extends the Z language with classes, objects, inheritance and polymorphism that can be used to represent the specification of a complex system as collections of objects. There are a number of existing works that mapped Object-Z to C++ and Java programming languages. Since Python and Object-Z share many similarities, both are object-oriented paradigm, support set theory and predicate calculus moreover, Python is a functional programming language which is naturally closer to formal specifications, we propose a mapping from Object-Z specifications to Python code that covers some Object-Z constructs and express its specifications in Python to validate these specifications. The validations are used in the mapping covered preconditions, post-conditions, and invariants that are built using lambda function and Python's decorator. This work has found Python is an excellent language for developing libraries to map Object-Z specif...

In this research, we do a software writing in Python to calculate the efforts, bending moments and deformations in beams of different materials. This computational tool, that we developed, is of great help in area of computational physical, more exactly in resistance of materials, which serves as support for researchers and teachers especially in physics and civil engineering, of the part of statics, who wish to carry out the modeling of the functions, involved in the calculation of resistance in beams in a practical and simple way, using the software presented in this article. In order to carry out this software, we are going to use the following methods: the double-integration method and the conjugate-beam method, which will serve as the basis of calculation to find the mathematical expressions involved in the analysis of resistance in beams, then we will perform the implementation of the aforementioned methods, using Python as the programming language. As a final step in this project, the graphical interface of said calculation tool will be made using the Python 3.0 Tkinter library. In this work, we show the results of the graphs of the stress profiles, bending moments and deformations, for the case of different types of beams, load and force distributions applied to them. Where we were also able to conclude that a calculation software was successfully built, dedicated to the analysis of efforts and deformations in beams made of different materials.

Modeling and predicting snow-related power loss is important to economic calculations, load management and system optimization for all scales of photovoltaic (PV) power plants. This paper describes a new method for measuring snow shedding from fielded modules and also describes the application of this method to a commercial scale PV power plant in Vermont with two subsystems , one with modules in portrait orientation and the other in landscape. The method relies on time-series images taken at 5 minute intervals to capture the dynamics of module-level snow accumulation and shedding. Module-level images extracted from the full-field view are binarized into snow and clear areas, allowing for the quantification of percentage snow coverage, estimation of resulting module power output, and temporal changes in snow coverage. Preliminary data from the Vermont case study suggests that framed modules in portrait orientation outperform their framed counterparts in landscape orientation by as much as 24% energy yield during a single shedding event. While these data reflect a single event, and do not capture snow shedding behavior across diverse temperature and other climatic conditions, the study nonetheless demonstrates that 1) module orientation and position in the array influence shedding patterns; 2) the start of power production and bypass diode activation differ for portrait and landscape module orientations at similar percentages and orientations of snow coverage; and 3) system design is an important factor in snow mitigation and increased system efficiency in snowy climates.

DETECCIÓN DE ROSTROS EN IMAGENES, CON Python y "opencv". Es sabido que una de las posibilidades que nos ofrece la librería "opencv" es la de detectar distintos tipos de elementos en una imagen, vídeo, grabación.., mediante el uso de clasificadores, los cuales, consisten, basicamente en archivos "xml", que contienen el dataset que se encargará de ir analizando cada región de la imagen, y determinando (mediante sucesivas pruebas) si la información de dicha región se corresponde con el elemento a detectar. Así, existen, ya creados, clasificadores, diseñados específicamente, para detectar elementos muy variados (personas, ojos, manos, vehículos, matriculas, animales…etc). En esta ocasión vamos a aplicar un clasificador orientado a la detección de rostros humanos en una imagen, el cual aplicaremos sobre un archivo llamado "abba.png", que mostramos a continuación:

Millions of people utilise social networking services all over the world. Users' interactions with social media sites like Twitter and Facebook have a huge impact on daily life, with some unfavourable consequences. Spammers have converted popular social networking sites into a target platform for disseminating a large number of irrelevant and harmful information. Twitter, for example, has grown to be one of the most widely utilised platforms of all time, allowing for an excessive amount of spam. Fake users send unwanted tweets to users in order to advertise services or websites, which not only harm actual users but also waste resources. Furthermore, the ability of spreading false information to users via fake identities has grown, resulting in the spread of hazardous materials. The detection of spammers and the identification of fraudulent users on Twitter has recently been a popular research topic in today's online social networks (OSNs).

A simplicidade de Python permite que você se torne produtivo rapidamente, porém isso muitas vezes significa que você não estará usando tudo que ela tem a oferecer. Com este guia prático, você aprenderá a escrever um código Python eficiente e idiomático aproveitando seus melhores recursos – alguns deles, pouco conhecidos. O autor Luciano Ramalho apresenta os recursos essenciais da linguagem e bibliotecas de Python mostrando como você pode tornar o seu código mais conciso, mais rápido e mais legível ao mesmo tempo.

Muitos programadores experientes tentam dobrar o Python para que ele se enquadre em padrões aprendidos com outras linguagens e jamais descobrem os recursos do Python que estão além de sua experiência. Com este livro, esses programadores Python aprenderão a ser totalmente proficientes em Python 3.

งานวิจัยนี้เป็นการศึกษาการพัฒนาภาษาไพธอน (Python) สำหรับวิเคราะห์, ออกแบบ และ เขียนแบบก่อสร้างชิ้นส่วนคานคอนกรีตเสริมเหล็ก โดยมีจุดมุ่งหมายในการใช้ภาษาไพธอนที่เป็นภาษารหัสเปิด เป็นภาษาสำหรับวิเคราะห์ และออกแบบ  แล้วสร้างรายละเอียดหน้าตัดคาน โดยอาศัยภาษาเอสวีจี (SVG) ในการแสดงผลลัพธ์ 
ผลจากการศึกษาพบว่าการพัฒนาชุดแพ็คเก็จภาษาไพธอน สำหรับใช้ในการวิเคราะห์, ออกแบบ และเขียนแบบรายละเอียดคานคอนกรีตเสริมเหล็ก สามารถแสดงผลลัพธ์เป็นแผนภาพแรงเฉือน และโมเมนต์ดัด และนำค่าที่ไปไปใช้งานโมดูลสำหรับออกแบบหน้าตัดคานด้วยวิธีกำลัง และใช้งานโมดูลส่วนช่วยเขียนรายละเอียดการเสริมเหล็กในหน้าตัดคาน

The dataset has a good mix of categorical independent variables, and a continuous dependent variable (price). This dataset contains house sale prices for King County, which includes Seattle. It includes homes sold from May 2014 to May 2015. It is a useful dataset for evaluating simple regression models. In this dataset, I predict the sales price of houses in King County, Seattle. It includes homes sold between May 2014 and May 2015.  The most significant obstacle I encountered was while cleaning our original dataset. Initially, the data I planned to use was from data.boston.gov. Based on professor recommendation, I replaced the data set. The old dataset needs a large amount of work, not enough variables, and data is old. I chose newly cleaned data-set to work on instead of Boston city data-set. The new data-set for “King County” in Washington state.

Course Duration 45 Days – Weekdays 2 Hrs

Demo Classes: Available At Your Convenience

Course Days : Weekdays Only – Morning Batch

Course Timings: 6:30 AM To 8:30 AM

Contact Details : 08885515041 ,

Email : [email protected]

ADDRESS : Beside Satyam Theatre , Ameerpet , Hyderabad.

Training Fees : 14000₹

Trainer Name : RajKumar

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Machine learning is one of the fast growing aspect in current world. Machine learning (ML) and Artificial Neural Network (ANN) are helpful in detection and diagnosis of various heart diseases. Naïve Bayes Classification is a vital approach of classification in machine learning. The heart disease consists of set of range disorders affecting the heart. It includes blood vessel problems such as irregular heart beat issues, weak heart muscles, congenital heart defects, cardio vascular disease and coronary artery disease. Coronary heart disorder is a familiar type of heart disease. It reduces the blood flow to the heart leading to a heart attack. In this paper the UCI machine learning repository data set consisting of patients suffering from heart disease is analyzed using Naïve Bayes classification and support vector machines. The classification accuracy of the patients suffering from heart disease is predicted using Naïve Bayes classification and support vector machines. Implementation is done using R language.

The project involves creating a chatbot to be used in healthcare treatment. The app uses Artificial Intelligence and can help in diagnosing various diseases and providing necessary details about the patient’s disease or illness. It helps in reducing the cost of healthcare and improving access to healthcare services. It also enhances the user to chat and know about their medical status and issues.

DESENVOLVIMENTO DE UM SISTEMA DE IDENTIFICAÇÃO E AUTENTICAÇÃO BIOMÉTRICA RECONHECIMENTO FACIAL Atividade prática supervisionada e apresentada ao curso Ciência da Computação, para fins de conhecimento na área. Orientador: Rafael do Espírito Santo. SÃO PAULO 2018 RESUMO Biometria é o uso de características biológicas em mecanismos de identificação. Entre essas características tem-se a íris (parte colorida do olho), a retina (membrana interna do globo ocular), a impressão digital, a voz, o formato do rosto e a geometria da mão. O uso de características biológicas para identificação se mostra como uma idéia viável porque cada pessoa possui as características mencionadas diferentes das outras. Com a biometria, o problema de roubo de senhas ou cartões com chips é extinto ou, pelo menos, amenizado. Embora nada impeça os dispositivos de identificação biométrica de serem enganados, é muito difícil copiar uma característica física e, dependendo do que é usado na identificação, a cópia é impossível (como a íris do olho).