This document summarizes a research paper that aims to predict water quality using machine learning. It discusses how water quality is an important issue due to contamination negatively impacting human and environmental health. The researchers developed a machine learning model using artificial neural networks and time series analysis to forecast water quality index and categorization. They trained the model on historical water quality data from 2014 in the United States. The study aims to improve current techniques for managing water quality by developing a more effective, reliable and accurate prediction model.
Mining Frequent Patterns and Associations from the Smart meters using Bayesia...Eswar Publications
In today’s world migration of people from rural areas to urban areas is quite common. Health care services are one of the most challenging aspect that is must require to the people with abnormal health. Advancements in the technologies lead to build the smart homes, which contains various sensor or smart meter devices to automate the process of other electronic device. Additionally these smart meters can be able to capture the daily activities of the patients and also monitor the health conditions of the patients by mining the frequent patterns and
association rules generated from the smart meters. In this work we proposed a model that is able to monitor the activities of the patients in home and can send the daily activities to the corresponding doctor. We can extract the frequent patterns and association rules from the log data and can predict the health conditions of the patients and can give the suggestions according to the prediction. Our work is divided in to three stages. Firstly, we used to record the daily activities of the patient using a specific time period at three regular intervals. Secondly we applied the frequent pattern growth for extracting the association rules from the log file. Finally, we applied k means clustering for the input and applied Bayesian network model to predict the health behavior of the patient and precautions will be given accordingly.
Mining Frequent Patterns and Associations from the Smart meters using Bayesia...Eswar Publications
In today’s world migration of people from rural areas to urban areas is quite common. Health care services are one of the most challenging aspect that is must require to the people with abnormal health. Advancements in the technologies lead to build the smart homes, which contains various sensor or smart meter devices to automate the process of other electronic device. Additionally these smart meters can be able to capture the daily activities of the patients and also monitor the health conditions of the patients by mining the frequent patterns and
association rules generated from the smart meters. In this work we proposed a model that is able to monitor the activities of the patients in home and can send the daily activities to the corresponding doctor. We can extract the frequent patterns and association rules from the log data and can predict the health conditions of the patients and can give the suggestions according to the prediction. Our work is divided in to three stages. Firstly, we used to record the daily activities of the patient using a specific time period at three regular intervals. Secondly we applied the frequent pattern growth for extracting the association rules from the log file. Finally, we applied k means clustering for the input and applied Bayesian network model to predict the health behavior of the patient and precautions will be given accordingly.
A Comprehensive review of Conversational Agent and its prediction algorithmvivatechijri
There is an exponential increase in the use of conversational bots. Conversational bots can be
described as a platform that can chat with people using artificial intelligence. The recent advancement has
made A.I capable of learning from data and produce an output. This learning of data can be performed by using
various machine learning algorithm. Machine learning techniques involves construction of algorithms that can
learn for data and can predict the outcome. This paper reviews the efficiency of different machine learning
algorithm that are used in conversational bot.
A REVIEW ON PREDICTIVE ANALYTICS IN DATA MININGijccmsjournal
The data mining its main process is to collect, extract and store the valuable information and now-a-days it’s
done by many enterprises actively. In advanced analytics, Predictive analytics is the one of the branch which is
mainly used to make predictions about future events which are unknown. Predictive analytics which uses
various techniques from machine learning, statistics, data mining, modeling, and artificial intelligence for
analyzing the current data and to make predictions about future. The two main objectives of predictive
analytics are Regression and Classification. It is composed of various analytical and statistical techniques used
for developing models which predicts the future occurrence, probabilities or events. Predictive analytics deals
with both continuous changes and discontinuous changes. It provides a predictive score for each individual
(healthcare patient, product SKU, customer, component, machine, or other organizational unit, etc.) to
determine, or influence the organizational processes which pertain across huge numbers of individuals, like in
fraud detection, manufacturing, credit risk assessment, marketing, and government operations including law
enforcement.
A REVIEW ON PREDICTIVE ANALYTICS IN DATA MININGijccmsjournal
The data mining its main process is to collect, extract and store the valuable information and now-a-days it’s done by many enterprises actively. In advanced analytics, Predictive analytics is the one of the branch which is mainly used to make predictions about future events which are unknown. Predictive analytics which uses various techniques from machine learning, statistics, data mining, modeling, and artificial intelligence for
analyzing the current data and to make predictions about future. The two main objectives of predictive analytics are Regression and Classification. It is composed of various analytical and statistical techniques used for developing models which predicts the future occurrence, probabilities or events. Predictive analytics deals with both continuous changes and discontinuous changes. It provides a predictive score for each individual
(healthcare patient, product SKU, customer, component, machine, or other organizational unit, etc.) to determine, or influence the organizational processes which pertain across huge numbers of individuals, like in fraud detection, manufacturing, credit risk assessment, marketing, and government operations including law enforcement.
A REVIEW ON PREDICTIVE ANALYTICS IN DATA MININGijccmsjournal
The data mining its main process is to collect, extract and store the valuable information and now-a-days it’s
done by many enterprises actively. In advanced analytics, Predictive analytics is the one of the branch which is
mainly used to make predictions about future events which are unknown. Predictive analytics which uses
various techniques from machine learning, statistics, data mining, modeling, and artificial intelligence for
analyzing the current data and to make predictions about future. The two main objectives of predictive
analytics are Regression and Classification. It is composed of various analytical and statistical techniques used
for developing models which predicts the future occurrence, probabilities or events. Predictive analytics deals
with both continuous changes and discontinuous changes. It provides a predictive score for each individual
(healthcare patient, product SKU, customer, component, machine, or other organizational unit, etc.) to
determine, or influence the organizational processes which pertain across huge numbers of individuals, like in
fraud detection, manufacturing, credit risk assessment, marketing, and government operations including law
enforcement.
SCCAI- A Student Career Counselling Artificial Intelligencevivatechijri
As education is growing day by day, the competition has prompted a need for the student to
understand more about the educational field. Many times the counselor isn’t available all the time and
sometimes due to the lack of proper knowledge about some educational field. Due to this, it creates an issue of
misconception of that field. This creates a problem for the student to decide a proper educational trajectory and
guidance is not always useful. The proposed paper will overcome all these problem using machine learning
algorithm. Various algorithms are being considered and amongst them the best suitable for our project are used
here. There are 3 major problems that come across our path and they are solved using Random forest, Linear
regression and Searching algorithm using Google API. At first Searching algorithm solves the problem of
location by segregating the college’s location vice, then Random Forest provides the list of colleges by using
stream and range of percentage and finally Linear Regression predicts the current cutoff using previous years’
data. Rather than this, the proposed system also provides information regarding all fields of education helping
students to understand and know about their field of interest better. The following idea is a total fresh idea with
no existing projects of similar kind. This project will help students guide them throughout.
A REVIEW ON PREDICTIVE ANALYTICS IN DATA MININGijccmsjournal
The data mining its main process is to collect, extract and store the valuable information and now-a-days it’s
done by many enterprises actively. In advanced analytics, Predictive analytics is the one of the branch which is
mainly used to make predictions about future events which are unknown. Predictive analytics which uses
various techniques from machine learning, statistics, data mining, modeling, and artificial intelligence for
analyzing the current data and to make predictions about future. The two main objectives of predictive
analytics are Regression and Classification. It is composed of various analytical and statistical techniques used
for developing models which predicts the future occurrence, probabilities or events. Predictive analytics deals
with both continuous changes and discontinuous changes. It provides a predictive score for each individual
(healthcare patient, product SKU, customer, component, machine, or other organizational unit, etc.) to
determine, or influence the organizational processes which pertain across huge numbers of individuals, like in
fraud detection, manufacturing, credit risk assessment, marketing, and government operations including law
enforcement.
The data mining its main process is to collect, extract and store the valuable information and now-a-days it’s
done by many enterprises actively. In advanced analytics, Predictive analytics is the one of the branch which is
mainly used to make predictions about future events which are unknown. Predictive analytics which uses
various techniques from machine learning, statistics, data mining, modeling, and artificial intelligence for
analyzing the current data and to make predictions about future. The two main objectives of predictive
analytics are Regression and Classification. It is composed of various analytical and statistical techniques used
for developing models which predicts the future occurrence, probabilities or events. Predictive analytics deals
with both continuous changes and discontinuous changes. It provides a predictive score for each individual
(healthcare patient, product SKU, customer, component, machine, or other organizational unit, etc.) to
determine, or influence the organizational processes which pertain across huge numbers of individuals, like in
fraud detection, manufacturing, credit risk assessment, marketing, and government operations including law
enforcement.
A REVIEW ON PREDICTIVE ANALYTICS IN DATA MINING ijccmsjournal
The data mining its main process is to collect, extract and store the valuable information and now-a-days it’s
done by many enterprises actively. In advanced analytics, Predictive analytics is the one of the branch which is
mainly used to make predictions about future events which are unknown. Predictive analytics which uses
various techniques from machine learning, statistics, data mining, modeling, and artificial intelligence for
analyzing the current data and to make predictions about future. The two main objectives of predictive
analytics are Regression and Classification. It is composed of various analytical and statistical techniques used
for developing models which predicts the future occurrence, probabilities or events. Predictive analytics deals
with both continuous changes and discontinuous changes. It provides a predictive score for each individual
(healthcare patient, product SKU, customer, component, machine, or other organizational unit, etc.) to
determine, or influence the organizational processes which pertain across huge numbers of individuals, like in
fraud detection, manufacturing, credit risk assessment, marketing, and government operations including law
enforcement.
A REVIEW ON PREDICTIVE ANALYTICS IN DATA MININGijscai
The data mining its main process is to collect, extract and store the valuable information and now-a-days it’s
done by many enterprises actively. In advanced analytics, Predictive analytics is the one of the branch which is
mainly used to make predictions about future events which are unknown. Predictive analytics which uses
various techniques from machine learning, statistics, data mining, modeling, and artificial intelligence for
analyzing the current data and to make predictions about future. The two main objectives of predictive
analytics are Regression and Classification. It is composed of various analytical and statistical techniques used
for developing models which predicts the future occurrence, probabilities or events. Predictive analytics deals
with both continuous changes and discontinuous changes. It provides a predictive score for each individual
(healthcare patient, product SKU, customer, component, machine, or other organizational unit, etc.) to
determine, or influence the organizational processes which pertain across huge numbers of individuals, like in
fraud detection, manufacturing, credit risk assessment, marketing, and government operations including law
enforcement.
Application of machine learning in chemical engineering: outlook and perspect...IAESIJAI
Chemical engineers' formulation, development, and stance processes all heavily rely on models. The physical and economic consequences of these decisions can have disastrous effects. Attempts to employ a hybrid form of artificial intelligence for modeling in various disciplines. However, they fell short of expectations. Due to a rise in the amount of data and computational resources during the previous five years. A lot of recent work has gone into developing new data sources, indexes, chemical interface designs, and machine learning algorithms in an effort to facilitate the adoption of these techniques in the research community. However, there are some important downsides to machine learning gains. The most promising uses for machine learning are in time-critical tasks like real-time optimization and planning that require extreme precision and can build on models that can self-learn to recognize patterns, draw conclusions from data, and become more intelligent over time. Due to their limited exposure to computer science and data analysis, the majority of chemical engineers are potentially vulnerable to the development of artificial intelligence. But in the not-too-distant future, chemical engineers' modeling toolbox will include a reliable machine learning component.
RAINFALL PREDICTION USING DATA MINING TECHNIQUES - A SURVEYcsandit
Rainfall is considered as one of the major components of the hydrological process; it takes
significant part in evaluating drought and flooding events. Therefore, it is important to have an
accurate model for rainfall prediction. Recently, several data-driven modeling approaches have
been investigated to perform such forecasting tasks as multilayer perceptron neural networks
(MLP-NN). In fact, the rainfall time series modeling (SARIMA) involvesimportant temporal
dimensions. In order to evaluate the incomes of both models, statistical parameters were used to
make the comparison between the two models. These parameters include the Root Mean Square
Error RMSE, Mean Absolute Error MAE, Coefficient Of Correlation CC and BIAS. Two-Third
of the data was used for training the model and One-third for testing.
A Comprehensive review of Conversational Agent and its prediction algorithmvivatechijri
There is an exponential increase in the use of conversational bots. Conversational bots can be
described as a platform that can chat with people using artificial intelligence. The recent advancement has
made A.I capable of learning from data and produce an output. This learning of data can be performed by using
various machine learning algorithm. Machine learning techniques involves construction of algorithms that can
learn for data and can predict the outcome. This paper reviews the efficiency of different machine learning
algorithm that are used in conversational bot.
A REVIEW ON PREDICTIVE ANALYTICS IN DATA MININGijccmsjournal
The data mining its main process is to collect, extract and store the valuable information and now-a-days it’s
done by many enterprises actively. In advanced analytics, Predictive analytics is the one of the branch which is
mainly used to make predictions about future events which are unknown. Predictive analytics which uses
various techniques from machine learning, statistics, data mining, modeling, and artificial intelligence for
analyzing the current data and to make predictions about future. The two main objectives of predictive
analytics are Regression and Classification. It is composed of various analytical and statistical techniques used
for developing models which predicts the future occurrence, probabilities or events. Predictive analytics deals
with both continuous changes and discontinuous changes. It provides a predictive score for each individual
(healthcare patient, product SKU, customer, component, machine, or other organizational unit, etc.) to
determine, or influence the organizational processes which pertain across huge numbers of individuals, like in
fraud detection, manufacturing, credit risk assessment, marketing, and government operations including law
enforcement.
A REVIEW ON PREDICTIVE ANALYTICS IN DATA MININGijccmsjournal
The data mining its main process is to collect, extract and store the valuable information and now-a-days it’s done by many enterprises actively. In advanced analytics, Predictive analytics is the one of the branch which is mainly used to make predictions about future events which are unknown. Predictive analytics which uses various techniques from machine learning, statistics, data mining, modeling, and artificial intelligence for
analyzing the current data and to make predictions about future. The two main objectives of predictive analytics are Regression and Classification. It is composed of various analytical and statistical techniques used for developing models which predicts the future occurrence, probabilities or events. Predictive analytics deals with both continuous changes and discontinuous changes. It provides a predictive score for each individual
(healthcare patient, product SKU, customer, component, machine, or other organizational unit, etc.) to determine, or influence the organizational processes which pertain across huge numbers of individuals, like in fraud detection, manufacturing, credit risk assessment, marketing, and government operations including law enforcement.
A REVIEW ON PREDICTIVE ANALYTICS IN DATA MININGijccmsjournal
The data mining its main process is to collect, extract and store the valuable information and now-a-days it’s
done by many enterprises actively. In advanced analytics, Predictive analytics is the one of the branch which is
mainly used to make predictions about future events which are unknown. Predictive analytics which uses
various techniques from machine learning, statistics, data mining, modeling, and artificial intelligence for
analyzing the current data and to make predictions about future. The two main objectives of predictive
analytics are Regression and Classification. It is composed of various analytical and statistical techniques used
for developing models which predicts the future occurrence, probabilities or events. Predictive analytics deals
with both continuous changes and discontinuous changes. It provides a predictive score for each individual
(healthcare patient, product SKU, customer, component, machine, or other organizational unit, etc.) to
determine, or influence the organizational processes which pertain across huge numbers of individuals, like in
fraud detection, manufacturing, credit risk assessment, marketing, and government operations including law
enforcement.
SCCAI- A Student Career Counselling Artificial Intelligencevivatechijri
As education is growing day by day, the competition has prompted a need for the student to
understand more about the educational field. Many times the counselor isn’t available all the time and
sometimes due to the lack of proper knowledge about some educational field. Due to this, it creates an issue of
misconception of that field. This creates a problem for the student to decide a proper educational trajectory and
guidance is not always useful. The proposed paper will overcome all these problem using machine learning
algorithm. Various algorithms are being considered and amongst them the best suitable for our project are used
here. There are 3 major problems that come across our path and they are solved using Random forest, Linear
regression and Searching algorithm using Google API. At first Searching algorithm solves the problem of
location by segregating the college’s location vice, then Random Forest provides the list of colleges by using
stream and range of percentage and finally Linear Regression predicts the current cutoff using previous years’
data. Rather than this, the proposed system also provides information regarding all fields of education helping
students to understand and know about their field of interest better. The following idea is a total fresh idea with
no existing projects of similar kind. This project will help students guide them throughout.
A REVIEW ON PREDICTIVE ANALYTICS IN DATA MININGijccmsjournal
The data mining its main process is to collect, extract and store the valuable information and now-a-days it’s
done by many enterprises actively. In advanced analytics, Predictive analytics is the one of the branch which is
mainly used to make predictions about future events which are unknown. Predictive analytics which uses
various techniques from machine learning, statistics, data mining, modeling, and artificial intelligence for
analyzing the current data and to make predictions about future. The two main objectives of predictive
analytics are Regression and Classification. It is composed of various analytical and statistical techniques used
for developing models which predicts the future occurrence, probabilities or events. Predictive analytics deals
with both continuous changes and discontinuous changes. It provides a predictive score for each individual
(healthcare patient, product SKU, customer, component, machine, or other organizational unit, etc.) to
determine, or influence the organizational processes which pertain across huge numbers of individuals, like in
fraud detection, manufacturing, credit risk assessment, marketing, and government operations including law
enforcement.
The data mining its main process is to collect, extract and store the valuable information and now-a-days it’s
done by many enterprises actively. In advanced analytics, Predictive analytics is the one of the branch which is
mainly used to make predictions about future events which are unknown. Predictive analytics which uses
various techniques from machine learning, statistics, data mining, modeling, and artificial intelligence for
analyzing the current data and to make predictions about future. The two main objectives of predictive
analytics are Regression and Classification. It is composed of various analytical and statistical techniques used
for developing models which predicts the future occurrence, probabilities or events. Predictive analytics deals
with both continuous changes and discontinuous changes. It provides a predictive score for each individual
(healthcare patient, product SKU, customer, component, machine, or other organizational unit, etc.) to
determine, or influence the organizational processes which pertain across huge numbers of individuals, like in
fraud detection, manufacturing, credit risk assessment, marketing, and government operations including law
enforcement.
A REVIEW ON PREDICTIVE ANALYTICS IN DATA MINING ijccmsjournal
The data mining its main process is to collect, extract and store the valuable information and now-a-days it’s
done by many enterprises actively. In advanced analytics, Predictive analytics is the one of the branch which is
mainly used to make predictions about future events which are unknown. Predictive analytics which uses
various techniques from machine learning, statistics, data mining, modeling, and artificial intelligence for
analyzing the current data and to make predictions about future. The two main objectives of predictive
analytics are Regression and Classification. It is composed of various analytical and statistical techniques used
for developing models which predicts the future occurrence, probabilities or events. Predictive analytics deals
with both continuous changes and discontinuous changes. It provides a predictive score for each individual
(healthcare patient, product SKU, customer, component, machine, or other organizational unit, etc.) to
determine, or influence the organizational processes which pertain across huge numbers of individuals, like in
fraud detection, manufacturing, credit risk assessment, marketing, and government operations including law
enforcement.
A REVIEW ON PREDICTIVE ANALYTICS IN DATA MININGijscai
The data mining its main process is to collect, extract and store the valuable information and now-a-days it’s
done by many enterprises actively. In advanced analytics, Predictive analytics is the one of the branch which is
mainly used to make predictions about future events which are unknown. Predictive analytics which uses
various techniques from machine learning, statistics, data mining, modeling, and artificial intelligence for
analyzing the current data and to make predictions about future. The two main objectives of predictive
analytics are Regression and Classification. It is composed of various analytical and statistical techniques used
for developing models which predicts the future occurrence, probabilities or events. Predictive analytics deals
with both continuous changes and discontinuous changes. It provides a predictive score for each individual
(healthcare patient, product SKU, customer, component, machine, or other organizational unit, etc.) to
determine, or influence the organizational processes which pertain across huge numbers of individuals, like in
fraud detection, manufacturing, credit risk assessment, marketing, and government operations including law
enforcement.
Application of machine learning in chemical engineering: outlook and perspect...IAESIJAI
Chemical engineers' formulation, development, and stance processes all heavily rely on models. The physical and economic consequences of these decisions can have disastrous effects. Attempts to employ a hybrid form of artificial intelligence for modeling in various disciplines. However, they fell short of expectations. Due to a rise in the amount of data and computational resources during the previous five years. A lot of recent work has gone into developing new data sources, indexes, chemical interface designs, and machine learning algorithms in an effort to facilitate the adoption of these techniques in the research community. However, there are some important downsides to machine learning gains. The most promising uses for machine learning are in time-critical tasks like real-time optimization and planning that require extreme precision and can build on models that can self-learn to recognize patterns, draw conclusions from data, and become more intelligent over time. Due to their limited exposure to computer science and data analysis, the majority of chemical engineers are potentially vulnerable to the development of artificial intelligence. But in the not-too-distant future, chemical engineers' modeling toolbox will include a reliable machine learning component.
RAINFALL PREDICTION USING DATA MINING TECHNIQUES - A SURVEYcsandit
Rainfall is considered as one of the major components of the hydrological process; it takes
significant part in evaluating drought and flooding events. Therefore, it is important to have an
accurate model for rainfall prediction. Recently, several data-driven modeling approaches have
been investigated to perform such forecasting tasks as multilayer perceptron neural networks
(MLP-NN). In fact, the rainfall time series modeling (SARIMA) involvesimportant temporal
dimensions. In order to evaluate the incomes of both models, statistical parameters were used to
make the comparison between the two models. These parameters include the Root Mean Square
Error RMSE, Mean Absolute Error MAE, Coefficient Of Correlation CC and BIAS. Two-Third
of the data was used for training the model and One-third for testing.
Quality defects in TMT Bars, Possible causes and Potential Solutions.PrashantGoswami42
Maintaining high-quality standards in the production of TMT bars is crucial for ensuring structural integrity in construction. Addressing common defects through careful monitoring, standardized processes, and advanced technology can significantly improve the quality of TMT bars. Continuous training and adherence to quality control measures will also play a pivotal role in minimizing these defects.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
COLLEGE BUS MANAGEMENT SYSTEM PROJECT REPORT.pdfKamal Acharya
The College Bus Management system is completely developed by Visual Basic .NET Version. The application is connect with most secured database language MS SQL Server. The application is develop by using best combination of front-end and back-end languages. The application is totally design like flat user interface. This flat user interface is more attractive user interface in 2017. The application is gives more important to the system functionality. The application is to manage the student’s details, driver’s details, bus details, bus route details, bus fees details and more. The application has only one unit for admin. The admin can manage the entire application. The admin can login into the application by using username and password of the admin. The application is develop for big and small colleges. It is more user friendly for non-computer person. Even they can easily learn how to manage the application within hours. The application is more secure by the admin. The system will give an effective output for the VB.Net and SQL Server given as input to the system. The compiled java program given as input to the system, after scanning the program will generate different reports. The application generates the report for users. The admin can view and download the report of the data. The application deliver the excel format reports. Because, excel formatted reports is very easy to understand the income and expense of the college bus. This application is mainly develop for windows operating system users. In 2017, 73% of people enterprises are using windows operating system. So the application will easily install for all the windows operating system users. The application-developed size is very low. The application consumes very low space in disk. Therefore, the user can allocate very minimum local disk space for this application.
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...Amil Baba Dawood bangali
Contact with Dawood Bhai Just call on +92322-6382012 and we'll help you. We'll solve all your problems within 12 to 24 hours and with 101% guarantee and with astrology systematic. If you want to take any personal or professional advice then also you can call us on +92322-6382012 , ONLINE LOVE PROBLEM & Other all types of Daily Life Problem's.Then CALL or WHATSAPP us on +92322-6382012 and Get all these problems solutions here by Amil Baba DAWOOD BANGALI
#vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore#blackmagicformarriage #aamilbaba #kalajadu #kalailam #taweez #wazifaexpert #jadumantar #vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore #blackmagicforlove #blackmagicformarriage #aamilbaba #kalajadu #kalailam #taweez #wazifaexpert #jadumantar #vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore #Amilbabainuk #amilbabainspain #amilbabaindubai #Amilbabainnorway #amilbabainkrachi #amilbabainlahore #amilbabaingujranwalan #amilbabainislamabad
Automobile Management System Project Report.pdfKamal Acharya
The proposed project is developed to manage the automobile in the automobile dealer company. The main module in this project is login, automobile management, customer management, sales, complaints and reports. The first module is the login. The automobile showroom owner should login to the project for usage. The username and password are verified and if it is correct, next form opens. If the username and password are not correct, it shows the error message.
When a customer search for a automobile, if the automobile is available, they will be taken to a page that shows the details of the automobile including automobile name, automobile ID, quantity, price etc. “Automobile Management System” is useful for maintaining automobiles, customers effectively and hence helps for establishing good relation between customer and automobile organization. It contains various customized modules for effectively maintaining automobiles and stock information accurately and safely.
When the automobile is sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting automobiles for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
Also when the user tries to sale items which are not in stock, the system will prompt the user that the stock is not enough. Customers of this system can search for a automobile; can purchase a automobile easily by selecting fast. On the other hand the stock of automobiles can be maintained perfectly by the automobile shop manager overcoming the drawbacks of existing system.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.