scholarly journals DiversiNews: Surfacing Diversity in Online News

AI Magazine ◽  
2015 ◽  
Vol 36 (4) ◽  
pp. 87-104 ◽  
Author(s):  
Mitja Trampuš ◽  
Flavio Fuart ◽  
Daniele Pighin ◽  
Tadej Štajner ◽  
Jan Berčič ◽  
...  
Keyword(s):  
User Interface ◽  
Real Time ◽  
Online News ◽  
Multiple Perspectives ◽  
Multiple Sources ◽  
Time News ◽  
News Events ◽  
Event Based ◽  
Positive Results ◽  
Ranked List

For most events of at least moderate significance, there are likely tens, often hundreds or thousands of online articles reporting on it, each from a slightly different perspective. If we want to understand an event in depth, from multiple perspectives, we need to aggregate multiple sources and understand the relations between them. However, current news aggregators do not offer this kind of functionality. As a step towards a solution, we propose DiversiNews, a real-time news aggregation and exploration platfom whose main feature is a novel set of controls that allow users to contrast reports of a selected event based on topical emphases, sentiment differences and/or publisher geolocation. News events are presented in the form of a ranked list of articles pertaining to the event and an automatically generated summary. Both the ranking and the summary are interactive and respond in real time to user’s change of controls. We validated the concept and the user interface through user tests with positive results.

Isolation and identification of Marek’s disease virus (MDV) from feather follicle epithelium and internal organs of diseased chickens in Dakahlia Governorate, Egypt

2019 ◽  
Vol 20 (2) ◽  
pp. 6-11
Author(s):  
Aly El-Kenawy ◽  
Mohamed El-Tholoth ◽  
Emad A
Keyword(s):  
Real Time ◽  
Disease Virus ◽  
Real Time Pcr ◽  
Marek's Disease Virus ◽  
Marek's Disease ◽  
Marek’S Disease Virus ◽  
Marek’S Disease ◽  
Field Samples ◽  
Feather Follicle ◽  
Positive Results

In the present study, a total of 16 samples including feather follicle epithelium, ovary, spleen and kidney (4 samples for each organ) were collected from diseased chicken flocks suspected to be infected with Marek’s disease virus (MDV) at Dakahlia Governorate, Egypt during the period from October 2016 to October 2017. Each sample was pooled randomly from three to five birds (90 to 360 days old). The isolation of the suspected virus from the collected samples was carried out via chorioallantoic membranes (CAMs) of 12 days old embryonated chicken eggs (ECEs). Three egg passages were carried out for each sample. Hyperimmune serum was prepared against standard MDV. MDV in both field and egg passaged samples (after 3rd passage) was identified by agar gel precipitation test (AGPT) and indirect fluorescence antibody test (IFAT). Molecular identification of virus was carried out by conventional polymerase chain reaction (PCR) and real- time PCR in four selected samples. The results revealed that 14 samples (87.5%) including 4 (100%) samples from feather follicle epithelium, ovary and kidney and 2 (50%) samples from spleen, showed positive results in virus isolation after 3rd passage. The positive results percentage by AGPT for field samples were 50% (8 out of 16 samples), while after the 3rd passage in ECEs were 37.5% (6 out of 16 samples) and the positive results percentage by IFAT for field samples were 62.5% (10 out of 16 samples), while after the 3rd passage in ECEs were 81.25 % (13 out of 16 samples). Viral nucleic acid was detected in all selected samples by conventional and real- time PCR. The results indicate that feather follicle epithelium is the best organ for MDV detection. IFAT is superior over AGPT in virus detection. Conventional and real - time PCR could be efficiently used for molecular detection of the virus.

scholarly journals DAViS: a unified solution for data collection, analyzation, and visualization in real-time stock market prediction

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Suppawong Tuarob ◽  
Poom Wettayakorn ◽  
Ponpat Phetchai ◽  
Siripong Traivijitkhun ◽  
Sunghoon Lim ◽  
...  
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Data Collection ◽  
Stock Market ◽  
Real Time ◽  
Stock Prices ◽  
Contextual Information ◽  
Online News ◽  
Stock Prediction ◽  
Stock Market Prediction

AbstractThe explosion of online information with the recent advent of digital technology in information processing, information storing, information sharing, natural language processing, and text mining techniques has enabled stock investors to uncover market movement and volatility from heterogeneous content. For example, a typical stock market investor reads the news, explores market sentiment, and analyzes technical details in order to make a sound decision prior to purchasing or selling a particular company’s stock. However, capturing a dynamic stock market trend is challenging owing to high fluctuation and the non-stationary nature of the stock market. Although existing studies have attempted to enhance stock prediction, few have provided a complete decision-support system for investors to retrieve real-time data from multiple sources and extract insightful information for sound decision-making. To address the above challenge, we propose a unified solution for data collection, analysis, and visualization in real-time stock market prediction to retrieve and process relevant financial data from news articles, social media, and company technical information. We aim to provide not only useful information for stock investors but also meaningful visualization that enables investors to effectively interpret storyline events affecting stock prices. Specifically, we utilize an ensemble stacking of diversified machine-learning-based estimators and innovative contextual feature engineering to predict the next day’s stock prices. Experiment results show that our proposed stock forecasting method outperforms a traditional baseline with an average mean absolute percentage error of 0.93. Our findings confirm that leveraging an ensemble scheme of machine learning methods with contextual information improves stock prediction performance. Finally, our study could be further extended to a wide variety of innovative financial applications that seek to incorporate external insight from contextual information such as large-scale online news articles and social media data.

scholarly journals An Augmented Warning System for Pedestrians: User Interface Design and Algorithm Development

2021 ◽  
Vol 11 (16) ◽  
pp. 7197
Author(s):  
Yourui Tong ◽  
Bochen Jia ◽  
Shan Bao
Keyword(s):  
User Interface ◽  
Real Time ◽  
Interface Design ◽  
Situational Awareness ◽  
Warning System ◽  
User Interface Design ◽  
Warning Systems ◽  
Projection Algorithms ◽  
Time Projection ◽  
Timely Warning

Warning pedestrians of oncoming vehicles is critical to improving pedestrian safety. Due to the limitations of a pedestrian’s carrying capacity, it is crucial to find an effective solution to provide warnings to pedestrians in real-time. Limited numbers of studies focused on warning pedestrians of oncoming vehicles. Few studies focused on developing visual warning systems for pedestrians through wearable devices. In this study, various real-time projection algorithms were developed to provide accurate warning information in a timely way. A pilot study was completed to test the algorithm and the user interface design. The projection algorithms can update the warning information and correctly fit it into an easy-to-understand interface. By using this system, timely warning information can be sent to those pedestrians who have lower situational awareness or obstructed view to protect them from potential collisions. It can work well when the sightline is blocked by obstructions.

scholarly journals The CNN effect: can the news media drive foreign policy?

1999 ◽  
Vol 25 (2) ◽  
pp. 301-309 ◽  
Author(s):  
PIERS ROBINSON
Keyword(s):  
Foreign Policy ◽  
Real Time ◽  
News Media ◽  
New Technologies ◽  
Berlin Wall ◽  
Policy Makers ◽  
Tiananmen Square ◽  
Time News ◽  
Tv News ◽  
The Cold War

During the 1980s the proliferation of new technologies transformed the potential of the news media to provide a constant flow of global real-time news. Tiananmen Square and the collapse of communism symbolised by the fall of the Berlin Wall became major media events communicated to Western audiences instantaneously via TV news media. By the end of the decade the question was being asked as to what extent this ‘media pervasiveness’ had impacted upon government – particularly the process of foreign policy making. The new technologies appeared to reduce the scope for calm deliberation over policy, forcing policy-makers to respond to whatever issue journalists focused on. This perception was in turn reinforced by the end of the bipolar order and what many viewed as the collapse of the old anti-communist consensus which – it was argued – had led to the creation of an ideological bond uniting policy makers and journalists. Released from the ‘prism of the Cold War’ journalists were, it was presumed, freer not just to cover the stories they wanted but to criticise US foreign policy as well. The phrase ‘CNN effect’ encapsulated the idea that real-time communications technology could provoke major responses from domestic audiences and political elites to global events.

scholarly journals A modular approach to integrating multiple data sources into real-time clinical prediction for pediatric diarrhea

2020 ◽  
Author(s):  
Ben J. Brintz ◽  
Benjamin Haaland ◽  
Joel Howard ◽  
Dennis L. Chao ◽  
Joshua L. Proctor ◽  
...  
Keyword(s):  
Real Time ◽  
Prediction Models ◽  
Predictive Performance ◽  
Data Availability ◽  
Clinical Prediction ◽  
Multiple Sources ◽  
Statistical Framework ◽  
Multiple Data ◽  
Post Test ◽  
The Individual

AbstractTraditional clinical prediction models focus on parameters of the individual patient. For infectious diseases, sources external to the patient, including characteristics of prior patients and seasonal factors, may improve predictive performance. We describe the development of a predictive model that integrates multiple sources of data in a principled statistical framework using a post-test odds formulation. Our method enables electronic real-time updating and flexibility, such that components can be included or excluded according to data availability. We apply this method to the prediction of etiology of pediatric diarrhea, where “pre-test” epidemiologic data may be highly informative. Diarrhea has a high burden in low-resource settings, and antibiotics are often over-prescribed. We demonstrate that our integrative method outperforms traditional prediction in accurately identifying cases with a viral etiology, and show that its clinical application, especially when used with an additional diagnostic test, could result in a 61% reduction in inappropriately prescribed antibiotics.

scholarly journals Online Food Ordering Management System

2021 ◽  
Vol 9 (VII) ◽  
pp. 2096-2107
Author(s):  
Karan Dhiman
Keyword(s):  
User Interface ◽  
Real Time ◽  
Management System ◽  
Food Item ◽  
Service Industry ◽  
Food Service ◽  
Wide Range ◽  
Ordering Systems

The main purpose of the Online Food Ordering Management System is to use it in the food-service industry. This feature helps hotels and restaurants to increase their online food ordering systems. Customers can choose from a wide range of food menu items within just a few minutes. In today’s modern food business, it's also able to deliver fast and easily to a customer’s place. The work presented as Online Food Ordering Management System simplifies the ordering process. The proposed solution presents a user interface and changes the menu to include all available options, creating customer work easier. Allows customers to order any item that they like and adjust the quantity of the food item. The order confirmation is displayed to the customer on the Homepage of the website. The order is put to the queue, updated across both the database and the admin panel, and provided in real-time. This system aids the staff with checking over orders in real-time and executing them effectively and easily with few errors. Here, the customer can also reserve a table at a restaurant of his/her choice and will get the confirmation of their reserved table on the homepage of our website.

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