scholarly journals Prediction of Symptom Based Health Cautionary by using Machine Learning

2021 ◽  
Vol 4 (1) ◽  
pp. 221-225
Author(s):  
Vijay Kumar Sinha ◽  
Meenakshi Jaiswal ◽  
Gurmeet Kaur ◽  
Shyam Lal
Keyword(s):  
Machine Learning ◽  
Information Science ◽  
Web Based ◽  
Number Of Patients ◽  
Media Applications ◽  
The Web

Conceptual - Machine learning is the subset of man-made reasoning that goes under information science. Without expressly customized, getting PCs to learn is a science known as Machine Learning. The proposal frameworks present in the market are believed to be working in popular applications like YouTube web-based media applications like Facebook, Instagram or item based applications like Flipkart. Essentially, these frameworks help to focus on data that is concerned or valuable for a specific client. One area where such frameworks can be exceptionally helpful is infection cautioning system. In light of an illness the client contributions to the framework, that he thinks they are inclined to or they are experiencing they will be proposed top 5 or top 3 sicknesses they are generally inclined to dependent on the likeness between the infection client inputted and the illness client is being suggested for this situation being cautioned. As of now, everything is accessible on the web, each infection and its data around there. Specialists are there yet at the same time the tally of sicknesses, number of patients for an illness is expanding. An individual has one sickness then there are chances they will get another. Illness include among youngsters in this age bunch is expanding at a huge rate. There is the fix of sicknesses or possibly not however shouldn't something be said about notice. On the off chance that we caution somebody before they are really experiencing an infection. It will make him/her much more mindful than previously. This paper analyzes existing recommender frameworks and furthermore features the disadvantages of such frameworks. Disadvantages can be versatility, cold beginning and sparsely. The proposed framework enjoys its benefits however isn't yet accessible on the lookout. Examination has been done on how this infection cautioning framework utilizing content-based suggestion under AI is removing highlights from dataset and how this framework presents highlights like client autonomy, straightforwardness and no virus start.

scholarly journals Developing an automatic identification and early warning and monitoring web based system of fall army worm based on machine learning in developing countries

2019 ◽  
Vol 3 (1) ◽  
pp. 13-20
Author(s):  
Francis Chulu ◽  
Jackson Phiri ◽  
Mayumbo Nyirenda ◽  
Monica M. Kabemba ◽  
Phillip Nkunika ◽  
...  
Keyword(s):  
Machine Learning ◽  
Data Collection ◽  
Negative Impact ◽  
Automatic Identification ◽  
Web Based ◽  
Collection Process ◽  
Data Collection Process ◽  
World Food Security ◽  
Army Worm ◽  
The Web

To combat the fall Army worm (FAW-Spodoptera frugiperda) pest which has a negative impact on world food security, there is need to come up with methods that can be used alongside conventional methods of spraying. Therefore this paper proposes a machine learning based system for automatic identification and monitoring of Fall Army worm Moths. The system will aim to address challenges that are associated with trap based FAW monitoring such as manual data collection as the system will automate the data collection process. The study will aim to automate the data collection process by developing a machine learning algorithm for FAW moth identification. The study will develop web and mobile applications integrated with Geographic information system (GIS) technology in addition to trap automation. The tools developed in this study will aim to improve the accuracy and efficiency of FAW monitoring by reducing the aspect of human intervention. At the time of writing this paper, only the web based tool prototype has been developed, therefore this paper mostly focuses on the design of the web based tool. The paper also provides a brief quantification of the chosen machine learning technique to be used in the study.

THE ARIADNE APPROACH TO WEB-BASED INFORMATION INTEGRATION

2001 ◽  
Vol 10 (01n02) ◽  
pp. 145-169 ◽  
Author(s):  
CRAIG A. KNOBLOCK ◽  
STEVEN MINTON ◽  
JOSE LUIS AMBITE ◽  
NAVEEN ASHISH ◽  
ION MUSLEA ◽  
...  
Keyword(s):  
Machine Learning ◽  
Knowledge Representation ◽  
Information Integration ◽  
Automated Planning ◽  
Multiple Sources ◽  
Web Based ◽  
Information Agents ◽  
New Information ◽  
Integrate Data ◽  
The Web

The Web is based on a browsing paradigm that makes it difficult to retrieve and integrate data from multiple sites. Today, the only way to do this is to build specialized applications, which are time-consuming to develop and difficult to maintain. We have addressed this problem by creating the technology and tools for rapidly constructing information agents that extract, query, and integrate data from web sources. Our approach is based on a uniform representation that makes it simple and efficient to integrate multiple sources. Instead of building specialized algorithms for handling web sources, we have developed methods for mapping web sources into this uniform representation. This approach builds on work from knowledge representation, databases, machine learning and automated planning. The resulting system, called Ariadne, makes it fast and easy to build new information agents that access existing web sources. Ariadne also makes it easy to maintain these agents and incorporate new sources as they become available.

OpenColab Project: OpenSim in Google Colaboratory to Explore Biomechanics on the Web

2021 ◽  
Author(s):  
Hossein Mokhtarzadeh ◽  
Fangwei Jiang ◽  
Shengzhe Zhao ◽  
Fatemeh Malekipour
Keyword(s):  
Machine Learning ◽  
Inverse Problem ◽  
Smart Phone ◽  
The Internet ◽  
Biomechanical Modeling ◽  
Cloud Platform ◽  
Web Based ◽  
Wide Range ◽  
Almost All ◽  
The Web

We aim to demystify the development of neuro-biomechanical modeling in OpenSim with zero configuration, easy to share models while accessing to free GPUs on a web-based platform of Google Colaboratory. OpenSim is an open-source biomechanical package. OpenSim is used in a variety of applications and developed in C++; however, it is available for a wide range of users with bindings in MATLAB, Python, Jython and Java via OpenSim Application Programing Interface (API). OpenSim installation on a personal computer is well described by the developers but its implementation may still be time-consuming and challenging for the new users. Cloud-based computing is expanding in almost all engineering domains with zero configuration, though it is in its early stages within biomechanics community. In this study, we aim to access OpenSim functionality on the Google cloud platform. The methods can also be used in other cloud-based platforms. We installed OpenSim on the Google Colab via Anaconda cloud and named it OpenColab. To use OpenColab, one requires only a connection to the internet and a Gmail account. Moreover, such a platform enables the users to access vast libraries of machine learning available within free Google products e.g., TensorFlow. OpenColab takes advantage of zero configuration of cloud-based platforms even on a smart phone, provides access to free GPUs and enables users to share and reproduce modeling approaches for further validation. Finally, we performed inverse problem in biomechanics and compared OpenColab results with OpenSim GUI’s for validation. Step-by-step installation processes and examples can be found freely at: https://simtk.org/projects/opencolab.

scholarly journals Machine Learning Algorithms for Spam Detection in Social Networks

2019 ◽  
Vol 8 (S3) ◽  
pp. 41-44
Author(s):  
K. Nagaramani ◽  
K. Vandanarao ◽  
B. Mamatha
Keyword(s):  
Machine Learning ◽  
Social Networks ◽  
Social Systems ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Spam Detection ◽  
Web Based ◽  
The Times ◽  
The Web

Most of the web based social systems like Face book, twitter, other mailing systems and social networks are developed for users to share their information, to interact and engage with the community. Most of the times these social networks will give some troubles to the users by spam messages, threaten messages, hackers and so on.. Many of the researchers worked on this and gave several approaches to detect the spam, hackers and other trouble shoots. In this paper we are discussing some tools to detect the spam messages in social networks. Here we are using RF, SVM, KNN and MLP machine learning algorithms across rapid miner and WEKA. It gives the better results when compared with other tools.

scholarly journals Behavior Prophecy of Stock Trader using Machine Learning Techniques

2019 ◽  
Vol 8 (11) ◽  
pp. 3620-3624
Keyword(s):  
Machine Learning ◽  
Human Behavior ◽  
User Behavior ◽  
Machine Learning Techniques ◽  
Web Based ◽  
Learning Techniques ◽  
Prediction Technique ◽  
Irregular Behavior ◽  
The Web ◽  
Unique Application

The web utilization by users is expanding very rapidly. Users are getting to data and administrations effectively through different media like social correspondence, sight and sound substance, web based trading, banking administrations and so forth. It winds up provoking undertaking to precisely recognize and separate typical and suspicious human behavior conduct. Every unique application need to predict user behavior to forecast and upgrade their administration quality. This work gives the examination of stock trader conduct recognition and expectation. Many Machine Learning (ML) methods and recognizable proof strategies are looked at and examined for stock trader behavior analysis. Their parameters are considered and enhancements are recommended. The proposed procedure portrays stock trader conduct discovery framework. The vital segment examination is the classification and prediction technique used to recognize and understand the typical and irregular behavior of the stock trader.

PENERAPAN METODE PROTOTYPING PADA PERANCANGAN APLIKASI SPPD KPPN MEDAN II BERBASIS WEBSITE

2019 ◽  
Vol 11 (1) ◽  
pp. 8-19
Author(s):  
Crystal Jelita Lumban Tobing
Keyword(s):  
Time Saving ◽  
Web Based ◽  
Government Organization ◽  
Manual Method ◽  
Microsoft Word ◽  
Ministry Of Finance ◽  
The Government ◽  
The City ◽  
Employee Data ◽  
The Web

 KPPN Medan II is one of the government organization units at the Ministry of Finance. Where leaders and employees who work at KPPN Medan II always carry out official trips between cities and outside the city. With these conditions, making SPPD documents experiencing the intensity of official travel activities carried out by employees of KPPN Medan II can be said frequently. So that in making SPPD in KPPN Medan II is still using the manual method that is recording through Microsoft Word which in the sense is less effective and efficient. In naming employees who get official assignments, officers manually entering employee data that receives official travel letters are prone to being lost because data is manually written. The web-based SPPD application is built by applying this prototyping method which is expected to facilitate SPPD KPPN Medan II management officers in making SPPD that is effective, efficient, accurate, time-saving, and not prone to losing SPPD data of KPPN Medan II employees who will has made official trips due to the existence of a special database to accommodate all SPPD files.

Rancang Bangun Sistem Penerimaan Dan Mutasi Barang Pada PDAM Tirta Kerta Raharja

Sensi Journal ◽  
2020 ◽  
Vol 6 (2) ◽  
pp. 236-246
Author(s):  
Ilamsyah Ilamsyah ◽  
Yulianto Yulianto ◽  
Tri Vita Febriani
Keyword(s):  
System Analysis ◽  
Object Oriented ◽  
Analysis Method ◽  
Web Based ◽  
Visual Modeling ◽  
Long Time ◽  
The Right ◽  
And Control ◽  
Web Based System ◽  
The Web

The right and appropriate system of receiving and transferring goods is needed by the company. In the process of receiving and transferring goods from the central warehouse to the branch warehouse at PDAM Tirta Kerta Raharja, Tangerang Regency, which is currently done manually is still ineffective and inaccurate because the Head of Subdivision uses receipt documents, namely PPBP and mutation of goods, namely MPPW in the form of paper as a submission media. The Head of Subdivision enters the data of receipt and mutation of goods manually and requires a relatively long time because at the time of demand for the transfer of goods the Head of Subdivision must check the inventory of goods in the central warehouse first. Therefore, it is necessary to hold a design of information systems for the receipt and transfer of goods from the central warehouse to a web-based branch warehouse that is already database so that it is more effective, efficient and accurate. With the web-based system of receiving and transferring goods that are already datatabed, it can facilitate the Head of Subdivision in inputing data on the receipt and transfer of goods and control of stock inventory so that the Sub Head of Subdivision can do it periodically to make it more effective, efficient and accurate. The method of data collection is done by observing, interviewing and studying literature from various previous studies, while the system analysis method uses the Waterfall method which aims to solve a problem and uses design methods with visual modeling that is object oriented with UML while programming using PHP and MySQL as a database.

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