Artificial Intelligence Services in Steel Production — On Premises and in the Cloud

2020 ◽  
Author(s):  
G. Hohenbichler ◽  
J. Reidetschlaeger ◽  
M. Sattler ◽  
P. Krahwinkler ◽  
S. Strasser
Keyword(s):  
Artificial Intelligence ◽  
Steel Production ◽  
Intelligence Services

scholarly journals Integration of Artificial Intelligence Technology Towards E-Services Among Online Clothing Websites

2019 ◽  
Vol 9 (2) ◽  
pp. 1562-1567
Keyword(s):  
Artificial Intelligence ◽  
Customer Satisfaction ◽  
Customer Service ◽  
Tamil Nadu ◽  
Customer Relationship ◽  
Snowball Sampling ◽  
Customer Experience Management ◽  
Intelligence Services ◽  
Artificial Intelligence Technology ◽  
Tamil Nadu State

Online Apparel Industry is one of the growing industries among many other online markets. The industry is moving towards a major technological shift due to new and innovative tools such as Artificial Intelligence (AI), Virtual Reality (VR) and Augmented Reality (AR). Customer Experience Management is highly influenced by gaining customer satisfaction via integrated AI technology for providing efficient customer service. This study emphasizes the intervention of AI technology with online clothing websites such as Jabong and Myntra. The findings explore that Customer Relationship Management (CRM) Services, Personalization services, Visual Assistance and Fit Intelligence Services are enhanced from AI tools that lead to Customer Satisfaction and Customer Retention. The research utilized non-probability Judgmental Sampling and snowball sampling where the respondents belong to Tamil Nadu State and were genuine online customers who purchase clothes from online clothing websites

Exploring Visual Representation of #ShoutYourAbortion Hashtag Movement and the Public’s Responses on Instagram: Descriptive and Infodemiology Study (Preprint)

2021 ◽  
Author(s):  
Sunmi ‍Lee ◽  
Yunhwan Kim
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Social Media ◽  
Neural Network Model ◽  
Predictive Analytics ◽  
Visual Representation ◽  
Point Of View ◽  
The Public ◽  
Intelligence Services ◽  
Human Faces

BACKGROUND Hashtag movement has become one of the major ways of online movement, but few studies have examined how social media photos were used for the movement. Also, it has not been actively investigated how photo features were related to the public’s responses in hashtag movements. OBJECTIVE The aim of the present research was to explore Instagram photos with #ShoutYourAbortion hashtag, as an example of hashtag movements via photos, in terms of their visual representation and the relationships between photo features and the public’s responses to the photos. METHODS Instagram photos with #ShoutYourAbortion hashtag, 11,176 in total, were downloaded, and their content and embedded texts were analyzed using online artificial intelligence services. The photos were clustered into subgroups based on the features extracted using a pretrained convolutional neural network model. The resulting clusters were compared in terms of their content tags, embedded texts, and photo features which were manually extracted at the content and pixel levels. The public’s responses were measured by engagement and comment sentiment. Correlational analysis and predictive analytics were conducted to examine the relationships between photo features and the public’s responses. RESULTS It was found that the photos in the text category took the largest share (57.19%), and the embedded texts were mainly about stories told in first person point of view as a woman. A possible evidence of hashtag hijacking was observed. The photos were grouped into two clusters; the first cluster comprised photos which exhibit text materials on them, while the second cluster consisted of photos which contain human faces with texts. The photos in the first cluster were brighter, while the photos in the second cluster were more colorful than the others. And public responses were found to be related to photo features such as size of faces, happy emotion, and share of warm colors. Engagement was predicted from the photo features with an acceptable level of accuracy, while comment sentiment was not. CONCLUSIONS This This study has shown the visual representation of #ShoutYourAbortion hashtag movement. It has also shown how photo features at content and pixel levels were related to the public’s responses to the photos. The results are expected to contribute to the understanding of hashtag movements via photos and making photos in hashtag movements more appealing to the public. CLINICALTRIAL Not Applicable

System Design and Development

2022 ◽  
pp. 72-86
Keyword(s):  
Artificial Intelligence ◽  
Natural Language ◽  
System Design ◽  
Development Process ◽  
Service Providers ◽  
Design And Development ◽  
Language Processor ◽  
Intelligence Services ◽  
Intelligence Service

This chapter presents the Socrates DigitalTM system's design and development process. It describes the four phases of design and development: understand, explore, materialize, and realize. The completion of these four phases results in a Socrates DigitalTM system that leverages artificial intelligence services. The artificial intelligence services include a natural language processor provided by several artificial intelligence service providers, including Apple, Microsoft, Google, IBM, and Amazon.

scholarly journals Artificial Intelligence Models for Crime Prediction in Urban Spaces

2020 ◽  
Vol 8 (1) ◽  
pp. 1-13
Author(s):  
Ana Laura Lira Cortes ◽  
Carlos Fuentes Silva
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Urban Areas ◽  
Urban Context ◽  
Criminal Records ◽  
Legal Information ◽  
Legal Advice ◽  
Intelligence Services ◽  
Artificial Intelligence Models ◽  
The Government

This work presents research based on evidence with neural networks for the development of predictive crime models, finding the data sets used are focused on historical crime data, crime classification, types of theft at different scales of space and time, counting crime and conflict points in urban areas. Among some results, 81% precision is observed in the prediction of the Neural Network algorithm and ranges in the prediction of crime occurrence at a space-time point between 75% and 90% using LSTM (Long-ShortSpace-Time). It is also observed in this review, that in the field of justice, systems based on intelligent technologies have been incorporated, to carry out activities such as legal advice, prediction and decisionmaking, national and international cooperation in the fight against crime, police and intelligence services, control systems with facial recognition, search and processing of legal information, predictive surveillance, the definition of criminal models under the criteria of criminal records, history of incidents in different regions of the city, location of the police force, established businesses, etc., that is, they make predictions in the urban context of public security and justice. Finally, the ethical considerations and principles related to predictive developments based on artificial intelligence are presented, which seek to guarantee aspects such as privacy, privacy and the impartiality of the algorithms, as well as avoid the processing of data under biases or distinctions. Therefore, it is concluded that the scenario for the development, research, and operation of predictive crime solutions with neural networks and artificial intelligence in urban contexts, is viable and necessary in Mexico, representing an innovative and effective alternative that contributes to the attention of insecurity, since according to the indices of intentional homicides, the crime rates of organized crime and violence with firearms, according to statistics from INEGI, the Global Peace Index and the Government of Mexico, remain in increase.

Recent and Future Innovative Artificial Intelligence Services and Fields

2021 ◽  
Author(s):  
Mohammed Saeed Jawad ◽  
Hairulnizam Mahdin ◽  
Nayef Abdulwahab Mohammed Alduais ◽  
Mohammed Hlayel ◽  
Salama A. Mostafa ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Intelligence Services

scholarly journals Artificial Intelligence – A Revolutionizing Factor in E-Commerce

2020 ◽  
Vol 06 (9S) ◽  
pp. 14-19
Author(s):  
Prof. Saravanan K and Pooja Shri K
Keyword(s):  
Artificial Intelligence ◽  
Customer Service ◽  
Time Saving ◽  
Effective Utilization ◽  
Intelligence Services ◽  
Trend Forecasting ◽  
Financial Decision ◽  
Customer Services ◽  
Using Data ◽  
Near Future

The future of industries is currently more dependent upon its presence on online platforms. This online presence not only visualizes, promotes, or advertises your brand but also helps in gaining huge customers. Also, customers are now gradually turning their interests towards online shopping which are easier, time-saving, and more personalized compared to the conventional practice of visiting physical stores. So one of the most popularizing and crucial tools used by e-commerce brands to attract people is through their artificial intelligence services. AI is constantly changing and updating the world of e-commerce in terms of its customer service and experience. Effective utilization of AI can aid in identifying concealed insights, trend forecasting, and beneficial financial decision making. AI has influenced the traditional way of replenishment and merchandising by simply using data analytics to indicate which product has to be replenished and which has to be discounted. According to a recent report of "Business Insider" predicts that about 85% of the customer services will be handled by AI-powered bots which can immediately respond to calls, chats, and emails with almost no human intervention. This paper encompasses the various AI tools empowered by the e-retail brands to attract their customers, the various ways by which AI influences both the retailer and the customer, and successful e-retail brands that employed AI for their advancement. In addition to this, the paper discusses how AI is going to dominate the e-commerce venture in the near future.

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