scholarly journals Development of On-Device Machine Learning Tools for Medication Warning Label Recognition

2021 ◽  
Author(s):  
Virendra Singh Rathore ◽  
Sabah Mohammed
Keyword(s):  
Machine Learning ◽  
English Language ◽  
Language Barrier ◽  
Learning Tools ◽  
Warning Label ◽  
Warning Labels ◽  
The World

The world that we live in today has so many languages that we speak throughout. Out of more than the six thousand languages that are spoken around the world, the most common is the English language. But there are people who do not understand it. When we speak of medications, the language barrier becomes riskier. If consumers are not able to understand the warning labels on the medicines, it might prove fatal to life. So it seems important that there be a tool or an application that would help them recognize and decode the warnings and/ or the instructions that are printed the medication pill containers. This tool will prove very useful for patients across the world and also people who consume any kind of medication without understanding the procedures/ risks that are specific to those medications.

scholarly journals Development of On-Device Machine Learning Tools for Medication Warning Label Recognition

2021 ◽  
Author(s):  
Virendra Singh Rathore ◽  
Sabah Mohammed
Keyword(s):  
Machine Learning ◽  
English Language ◽  
Language Barrier ◽  
Learning Tools ◽  
Warning Label ◽  
Warning Labels ◽  
The World

The world that we live in today has so many languages that we speak throughout. Out of more than the six thousand languages that are spoken around the world, the most common is the English language. But there are people who do not understand it. When we speak of medications, the language barrier becomes riskier. If consumers are not able to understand the warning labels on the medicines, it might prove fatal to life. So it seems important that there be a tool or an application that would help them recognize and decode the warnings and/ or the instructions that are printed the medication pill containers. This tool will prove very useful for patients across the world and also people who consume any kind of medication without understanding the procedures/ risks that are specific to those medications.

scholarly journals Pelatihan Keterampilan Menulis dalam Korespondensi Berbahasa Inggris, Menerjemahkan serta Keterampilan Menggunakan Grammarly, Google Translate, dan Google Drive di Sekolah Menengah Kejuruan KSATRYA, Rawasari, Jakarta Pusat

2020 ◽  
Vol 2 (2) ◽  
pp. 118-126
Author(s):  
Elfa Setiawan ◽  
Dinda A Rahman ◽  
Rudi Kristanto
Keyword(s):  
High School Students ◽  
English Language ◽  
Learning Tools ◽  
Vocational High School ◽  
School Students ◽  
Business World ◽  
Translation Tools ◽  
The World ◽  
Training Activities ◽  
Google Drive

The development of the world of education in the 21st century is now entering an era marked by the onslaught of the information technology revolution and the formation of the economic order and global relations, thus demanding an output of educational outcomes and outcomes that are in line with the demands of the world of work. The ability to communicate both in Speaking and writing is one of the abilities that must be mastered by everyone.The purpose of this Community Service Activities is to provide understanding and skills to vocational students in improving English language skills, particularly written communication skills in the business world as well as practical skills in translating documents documents or articles in English. The achievements of this service are increasing knowledge, insight, and English correspondence skills among vocational high school students, optimizing the use of online-based English Learning Tools such as Google Translate, Grammarly and Google Drive. The training activity was held for 4 hours on October 30, 2019, in the form of lectures, question-answers, and hands-on practice using Translation Tools. There were 22 trainees, class XII students of SMK Ksatrya, Cempaka Putih Barat, Central Jakarta. Based on the feedback from the participants, the training activities are very good and beneficial for them.This activity is not only limited to the training but is expected to be the beginning of the collaboration between the STIAMI Institute and the Ksatrya Vocational School in the future, to conduct other English language training with different topics or themes.

scholarly journals Sentiment Analysis of Tweets in Brazilian Portuguese with Convolutional Neural Networks

2019 ◽  
Vol 7 (6) ◽  
pp. 29-41
Author(s):  
Juan Manuel Adán Coello ◽  
Armando Dalla Costa Neto
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Sentiment Analysis ◽  
Convolutional Neural Networks ◽  
Language Processing ◽  
English Language ◽  
Brazilian Portuguese ◽  
The World ◽  
Better Than ◽  
Natural Language Processing Task

Sentiment analysis of texts posted on Twitter is a natural language processing task whose importance has grown along with the increase in the number of users of the platform and the interest of organizations on the opinions of their employees, customers and users.Although Brazil is the sixth country in the world with most active users of Tweeter and Portuguese is the seventh most spoken language in the world, with 221 million speakers (200 million of them living in Brazil), the number of articles that discuss sentiment analysis approaches for Brazilian Portuguese is a small fraction of those that focus on the English language. On the other hand, few works use deep learning for this task when compared with other machine learning and lexical based methods. In this context, the work described in this article addresses the problem using Convolutional Neural Networks (CNN). The paper presents the results of an experimental evaluation that shows that a CNN with a relatively simple architecture can perform much better than a previous approach that uses ensembles of other machine learning classifiers combined with text preprocessing heuristics

scholarly journals Analyzing and Predicting The Success of Box Office Collection of a Movie Using Machine Learning

2021 ◽  
pp. 325-331
Author(s):  
Sanyam Jatale ◽  
Rohan Moze ◽  
Varsha Khandekar ◽  
Shubham Jain ◽  
Sanket Mokate
Keyword(s):  
Machine Learning ◽  
Social Networking ◽  
Motion Picture Industry ◽  
Learning Tools ◽  
Social Bookmarking ◽  
Business Decisions ◽  
Box Office ◽  
The World ◽  
Increased Activity ◽  
Movie Success

Our day-to-day life has always been influenced by what people think. Ideas and opinions of others have always affected our own opinions. The explosion of Web 2.0 has led to increased activity in Podcasting, Blogging, Tagging, Contributing to RSS, Social Bookmarking, and Social Networking. The motion picture industry is a multi-billion-dollar business, and there is a massive amount of data related to movies are available over the internet. The framework will foresee an estimated achievement pace of a film dependent on its productivity by dissecting verifiable information from various sources like IMDB, Rotten Tomato, Box Office Mojo and Metacritic. Utilizing distinctive AI calculations, Machine Learning Tools, and different procedures the framework will foresee a film box office benefits depending on certain highlights like caste, genre, budget, actors, and many more features. The number of movies produced in the world is growing at an exponential rate and success rate of movie is of utmost importance since billions of dollars are invested in the making of each of these movies. In such a scenario, prior knowledge about the success or failure of a particular movie and what factor affect the movie success will benefit the production houses since these predictions will give them a fair idea of how to go about with the advertising and campaigning, which itself is an expensive affair altogether. Thus, predicting the box-office will help this growing industry experts to imply some important business decisions in order to make the upcoming movie more successful.

scholarly journals A systematic review of the efficacy of alcohol warning labels

2018 ◽  
Vol 8 (3) ◽  
pp. 333-352 ◽  
Author(s):  
Louise M. Hassan ◽  
Edward Shiu
Keyword(s):  
Narrative Analysis ◽  
English Language ◽  
Web Of Science ◽  
Evidence Base ◽  
Quantitative Information ◽  
Alcoholic Beverages ◽  
Warning Label ◽  
Warning Labels ◽  
Content Type ◽  
Warning Messages

Purpose The placement of warning labels on alcoholic beverages is a policy area with renewed interest, yet a strong evidence base regarding the efficacy of text-based or pictorial warning labels has still to emerge. Increased interest by policymakers has spurred research into potential alcohol warning label designs and messages. The purpose of this article is to draw together recearch in the alcohol warnings literature. Design/methodology/approach The current study seeks to review research that has sought to examine the effectiveness of alcohol warning labels. Searches for English-language articles (since 2000) using the terms “alcohol” and “warning label*” were conducted in 2015 across four databases (Web of Science, PubMed, PsycInfo and Cochrane). Articles were included if they empirically assessed the effectiveness and/or design of alcohol warning labels. Only studies that addressed the targeted individual consumer (consistent with downstream social marketing) were included. A narrative analysis approach was used for the 15 articles identified. Findings Findings are reported on five themes covering the design of the warning, starting with the use of imagery or recommendations, followed by a focus on the warning messages and whether they are specific, use signal words and are based on qualitative or quantitative information. Research limitations/implications Overall, there was little consistency in approach and measures, with very limited research having explored the potential of pictorial warning labels. Numerous research gaps are identified; thus, much more research is needed in this area. The evidence base is weak and caution is needed by policymakers regarding the introduction and implementation of alcohol warning labels. Limitations are discussed. Originality/value The review provides a timely up-to-date evaluation of the alcohol warning labels literature that has seen a recent resurgence but has not been critically reviewed.

The Center for International Biomedical Communications Research

1966 ◽  
Vol 05 (03) ◽  
pp. 142-146
Author(s):  
A. Kent ◽  
P. J. Vinken
Keyword(s):  
Information Needs ◽  
English Language ◽  
Medical Information ◽  
Biomedical Literature ◽  
Information Storage ◽  
Control Mechanisms ◽  
University Of Pittsburgh ◽  
The World ◽  
The University ◽  
Excerpta Medica Foundation

A joint center has been established by the University of Pittsburgh and the Excerpta Medica Foundation. The basic objective of the Center is to seek ways in which the health sciences community may achieve increasingly convenient and economical access to scientific findings. The research center will make use of facilities and resources of both participating institutions. Cooperating from the University of Pittsburgh will be the School of Medicine, the Computation and Data Processing Center, and the Knowledge Availability Systems (KAS) Center. The KAS Center is an interdisciplinary organization engaging in research, operations, and teaching in the information sciences.Excerpta Medica Foundation, which is the largest international medical abstracting service in the world, with offices in Amsterdam, New York, London, Milan, Tokyo and Buenos Aires, will draw on its permanent medical staff of 54 specialists in charge of the 35 abstracting journals and other reference works prepared and published by the Foundation, the 700 eminent clinicians and researchers represented on its International Editorial Boards, and the 6,000 physicians who participate in its abstracting programs throughout the world. Excerpta Medica will also make available to the Center its long experience in the field, as well as its extensive resources of medical information accumulated during the Foundation’s twenty years of existence. These consist of over 1,300,000 English-language _abstract of the world’s biomedical literature, indexes to its abstracting journals, and the microfilm library in which complete original texts of all the 3,000 primary biomedical journals, monitored by Excerpta Medica in Amsterdam are stored since 1960.The objectives of the program of the combined Center include: (1) establishing a firm base of user relevance data; (2) developing improved vocabulary control mechanisms; (3) developing means of determining confidence limits of vocabulary control mechanisms in terms of user relevance data; 4. developing and field testing of new or improved media for providing medical literature to users; 5. developing methods for determining the relationship between learning and relevance in medical information storage and retrieval systems’; and (6) exploring automatic methods for retrospective searching of the specialized indexes of Excerpta Medica.The priority projects to be undertaken by the Center are (1) the investigation of the information needs of medical scientists, and (2) the development of a highly detailed Master List of Biomedical Indexing Terms. Excerpta Medica has already been at work on the latter project for several years.

Feature extraction and prediction of Dengue Outbreaks

2020 ◽  
pp. 216-222
Author(s):  
Kunal Parikh ◽  
Tanvi Makadia ◽  
Harshil Patel
Keyword(s):  
Public Health ◽  
Machine Learning ◽  
Developing Countries ◽  
Feature Extraction ◽  
Predictive Analytics ◽  
Learning Algorithm ◽  
Machine Learning Algorithm ◽  
Health Concerns ◽  
The World ◽  
Dengue Outbreaks

Dengue is unquestionably one of the biggest health concerns in India and for many other developing countries. Unfortunately, many people have lost their lives because of it. Every year, approximately 390 million dengue infections occur around the world among which 500,000 people are seriously infected and 25,000 people have died annually. Many factors could cause dengue such as temperature, humidity, precipitation, inadequate public health, and many others. In this paper, we are proposing a method to perform predictive analytics on dengue’s dataset using KNN: a machine-learning algorithm. This analysis would help in the prediction of future cases and we could save the lives of many.

Penerapan Rinfo Sebagai Media Pendukung Untuk Proses Pembelajaran Pada Perguruan Tinggi Raharja

CCIT Journal ◽  
2014 ◽  
Vol 8 (1) ◽  
pp. 101-115
Author(s):  
Untung Rahardja ◽  
Khanna Tiara ◽  
Ray Indra Taufik Wijaya
Keyword(s):  
Learning Process ◽  
Human Life ◽  
Learning Tools ◽  
Integrated Learning ◽  
Civilizing Process ◽  
The World ◽  
The Future ◽  
Two Factors ◽  
Life Education ◽  
New Generation

Education is an important factor in human life. According to Ki Hajar Dewantara, education is a civilizing process that a business gives high values ??to the new generation in a society that is not only maintenance but also with a view to promote and develop the culture of the nobility toward human life. Education is a human investment that can be used now and in the future. One other important factor in supporting human life in addition to education, which is technology. In this globalization era, technology has touched every joint of human life. The combination of these two factors will be a new innovation in the world of education. The innovation has been implemented by Raharja College, namely the use of the method iLearning (Integrated Learning) in the learning process. Where such learning has been online based. ILearning method consists of TPI (Ten Pillars of IT iLearning). Rinfo is one of the ten pillars, where it became an official email used by the whole community’s in Raharja College to communicate with each other. Rinfo is Gmail, which is adapted from the Google platform with typical raharja.info as its domain. This Rinfo is a medium of communication, as well as a tool to support the learning process in Raharja College. Because in addition to integrated with TPi, this Rinfo was connected also support with other learning tools, such as Docs, Drive, Sites, and other supporting tools.

Platform for Analysing and Encouraging Student Activity on Contest and E-learning Systems

2018 ◽  
Vol 12 ◽  
pp. 85-98
Author(s):  
Bojan Kostadinov ◽  
Mile Jovanov ◽  
Emil STANKOV
Keyword(s):  
Machine Learning ◽  
Data Collection ◽  
Educational Policy ◽  
Learning Systems ◽  
Data Sources ◽  
Or Education ◽  
Student Activity ◽  
The World ◽  
E Learning ◽  
Analyse Data

Data collection and machine learning are changing the world. Whether it is medicine, sports or education, companies and institutions are investing a lot of time and money in systems that gather, process and analyse data. Likewise, to improve competitiveness, a lot of countries are making changes to their educational policy by supporting STEM disciplines. Therefore, it’s important to put effort into using various data sources to help students succeed in STEM. In this paper, we present a platform that can analyse student’s activity on various contest and e-learning systems, combine and process the data, and then present it in various ways that are easy to understand. This in turn enables teachers and organizers to recognize talented and hardworking students, identify issues, and/or motivate students to practice and work on areas where they’re weaker.

Impact of Social Media on English Language: A Review

2015 ◽  
Vol 3 (3) ◽  
pp. 5
Author(s):  
Dr. Neha Sharma
Keyword(s):  
Social Media ◽  
Cultural Values ◽  
English Language ◽  
Major Influence ◽  
International Level ◽  
Class Society ◽  
The World ◽  
The Status ◽  
The Media ◽  
Subsequent Rise

Language being a potent vehicle of transmitting cultural values, norms and beliefs remains a central factor in determining the status of any nation. India is a multilingual country which tends to encourage people to use English at national and international level. Basically English in India owes its presence to the British but its subsequent rise is not fully attributable to the British. It has now become the language of wider communication which is now spoken by large number of people all over the world. It is influenced by many factors such as class, society, developments in science and technology etc. However the major influence on English language is and has been the media.

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