scholarly journals "Making AI Work for Cyber Defense: The Accuracy-Robustness Tradeoff "

2021 ◽  
Author(s):  
Wyatt Hoffman
Keyword(s):  
Artificial Intelligence ◽  
Cyber Defense ◽  
Trade Offs ◽  
The Face

Artificial intelligence will play an increasingly important role in cyber defense, but vulnerabilities in AI systems call into question their reliability in the face of evolving offensive campaigns. Because securing AI systems can require trade-offs based on the types of threats, defenders are often caught in a constant balancing act. This report explores the challenges in AI security and their implications for deploying AI-enabled cyber defenses at scale.

A Novel Artificial Face Mask based Nanofibers with Special Intelligent Engineered Nanocomposite Against Covid-19

2021 ◽  
pp. PP. 21-22
Author(s):  
Ahmed A. Elngar ◽  
◽  
◽  
S.I. El El-Dek
Keyword(s):  
Artificial Intelligence ◽  
Resource Allocation ◽  
Pattern Recognition ◽  
Disease Management ◽  
Face Mask ◽  
Vital Role ◽  
Mobile Unit ◽  
Disease Clusters ◽  
Infected People ◽  
The Face

We introduce our idea about a new face mask against Covid-19. Herein our novel face mask is a polymeric matrix of nanofibers. These nanofibers are decorated with special engineered nanocomposite. The later possesses antiviral, antimicrobial. A well-established IR temperature biosensor will be implanted in the face mask and connected to the mobile phone using App (Seek thermal) to allow temperature monitoring. Artificial Intelligence can play a vital role in the fight against COVID-19. AI is being successfully used in the identification of disease clusters, monitoring of cases, prediction of the future outbreaks, mortality risk, diagnosis of COVID-19, disease management by resource allocation, facilitating training, record maintenance and pattern recognition for studying the disease trend. Therefore, AI is used as a type of alarm which be connected through Global Position System (GPS) to a central networking system to monitor the crowded areas of probable infections. In this case, the hospital in this neighborhood will be charged to let a mobile unit of assessment travel quickly to the infected people areas.

Novel Application of Artificial Intelligence with Potential to Transform Well Planning Workflows on the Norwegian Continental Shelf

2021 ◽  
Author(s):  
Jon Gustav Vabø ◽  
Evan Thomas Delaney ◽  
Tom Savel ◽  
Norbert Dolle
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Continental Shelf ◽  
Data Science ◽  
Search Algorithm ◽  
Solution Space ◽  
Good Decision ◽  
Trade Offs ◽  
Well Trajectory ◽  
Norwegian Continental Shelf

Abstract This paper describes the transformational application of Artificial Intelligence (AI) in Equinor's annual well planning and maturation process. Well planning is a complex decision-making process, like many other processes in the industry. There are thousands of choices, conflicting business drivers, lots of uncertainty, and hidden bias. These complexities all add up, which makes good decision making very hard. In this application, AI has been used for automated and unbiased evaluation of the full solution space, with the objective to optimize the selection of drilling campaigns while taking into account complex issues such as anti-collision with existing wells, drilling hazards and trade-offs between cost, value and risk. Designing drillable well trajectories involves a sequence of decisions, which makes the process very suitable for AI algorithms. Different solver architectures, or algorithms, can be used to play this game. This is similar to how companies such as Google-owned DeepMind develop customized solvers for games such as Go and StarCraft. The chosen method is a Tree Search algorithm with an evolutionary layer on top, providing a good balance in terms of performance (i.e., speed) vs. exploration capability (i.e., it looks "wide" in the option space). The algorithm has been deployed in a full stack web-based application that allows users to follow an end-2-end workflow: from defining well trajectory design rules and constraints to running the AI engine and evaluating results to the optimization of multi-well drilling campaigns based on risk, value and cost objectives. The full-size paper describes different Norwegian Continental Shelf (NCS) use cases of this AI assisted well trajectory planning. Results to-date indicate significant CAPEX savings potential and step-change improvements in decision speed (months to days) compared to routine manual workflows. There are very limited real transformative examples of Artificial Intelligence in multi- disciplinary workflows. This paper therefore gives a unique insight how a combination of data science, domain expertise and end user feedback can lead to powerful and transformative AI solutions – implemented at scale within an existing organization.

scholarly journals Are Artificial Intelligence (AI) And Machine Learning (ML) Having An Effective Role In Helping Humanity Address The New Coronavirus Pandemic?

2020 ◽  
Vol 17 ◽  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Disease Outbreaks ◽  
Hospital Capacity ◽  
Data Engineering ◽  
Clinical Presentations ◽  
The Face ◽  
Effective Role ◽  
Using Data ◽  
The Right

COVID-19 has become a pandemic affecting the most of countries in the world. One of the most difficult decisions doctors face during the Covid-19 epidemic is determining which patients will stay in hospital, and which are safe to recover at home. In the face of overcrowded hospital capacity and an entirely new disease with little data-based evidence for diagnosis and treatment, the old rules for determining which patients should be admitted have proven ineffective. But machine learning can help make the right decision early, save lives and lower healthcare costs. So, there is therefore an urgent and imperative need to collect data describing clinical presentations, risks, epidemiology and outcomes. On the other side, artificial intelligence(AI) and machine learning(ML) are considered a strong firewall against outbreaks of diseases and epidemics due to its ability to quickly detect, examine and diagnose these diseases and epidemics.AI is being used as a tool to support the fight against the epidemic that swept the entire world since the beginning of 2020.. This paper presents the potential for using data engineering, ML and AI to confront the Coronavirus, predict the evolution of disease outbreaks, and conduct research in order to develop a vaccine or effective treatment that protects humanity from these deadly diseases.

scholarly journals Artificial Intelligence and Bank Soundness: A Done Deal? - Part 1

2021 ◽  
Author(s):  
Charmele Ayadurai ◽  
Sina Joneidy
Keyword(s):  
Artificial Intelligence ◽  
Significant Role ◽  
Crucial Role ◽  
Significant Contribution ◽  
Economic Prosperity ◽  
Bank Stability ◽  
The Face ◽  
Main Strand ◽  
Bank Soundness ◽  
The Way

Banks soundness plays a crucial role in determining economic prosperity. As such, banks are under intense scrutiny to make wise decisions that enhances bank stability. Artificial Intelligence (AI) plays a significant role in changing the way banks operate and service their customers. Banks are becoming more modern and relevant in people’s life as a result. The most significant contribution of AI is it provides a lifeline for bank’s survival. The chapter provides a taxonomy of bank soundness in the face of AI through the lens of CAMELS where C (Capital), A(Asset), M(Management), E(Earnings), L(Liquidity), S(Sensitivity). The taxonomy partitions opportunities from the main strand of CAMELS into distinct categories of 1 (C), 6(A), 17(M), 16 (E), 3(L), 6(S). It is highly evident that banks will soon extinct if they do not embed AI into their operations. As such, AI is a done deal for banks. Yet will AI contribute to bank soundness remains to be seen.

scholarly journals Dynamic & Intelligent Student Attendance Maintenance Based on Face Recognition

2020 ◽  
Vol 9 (5) ◽  
pp. 399-403
Keyword(s):  
Artificial Intelligence ◽  
Face Recognition ◽  
Face Detection ◽  
Student Attendance ◽  
Teachers And Students ◽  
The Face ◽  
Monitoring Camera ◽  
On Line

The proposed system generally results a solution to some of the problems which occurs in colleges and schools by providing a monitoring camera with the help of “Artificial Intelligence (AI)” . The main problem which can be occurred is wastage of time in taking the attendance manually or through any biometric sensors. The next problem which can be solved is to control the usage of electricity in classrooms when students are not in class. When the videos are getting recorded with the help of monitoring cameras, at the same time the head counting and face detection of the students present will also be done. When the strength of the class is zero ,the head counting also results to zero. The electricity can also be saved at the same time when people are not present in the classroom. The face recognition is the easiest process which can be done for marking the attendance, where the attendance is marked automatically. This process also helps to prevent the fake attendance. Face recognition and detection is generally based on line edge mapping to attain the identity of the student and also meets the wants of attendance in the universities and schools. The image of the student is to be captured and checked with the database simultaneously and marks the attendance of the particular student. The video gets recorded all the time and checks whether the student remains in class for the entire period.The attendance marking system with the help of technology is very essential for both the teachers and students.

Artificial Intelligence in the Banking Sector: Opportunities and Challenges

2021 ◽  
pp. 81-97
Author(s):  
Galina Semeko ◽  
Keyword(s):  
Artificial Intelligence ◽  
Banking Sector ◽  
High Tech ◽  
The World ◽  
The Face

The article deals with the problems of using artificial intelligence technologies in the banking sector in the world in general and in Russia in particular. Characterizes the potential of artificial intelligence technologies and their role in increasing the competitiveness of banks in the face of in Creasing competition from new high-tech financial providers. Presentes an analysis of the factors hampering the introduction of artificial intelligence technologies in banks.

Analysis of Sustainable Development Path for Green Finance

2019 ◽  
pp. 62-83
Author(s):  
Hsu Chao Feng ◽  
Lee Bi Ru
Keyword(s):  
Sustainable Development ◽  
Environmental Protection ◽  
National Development ◽  
Development Project ◽  
Market Society ◽  
Rapid Economic Growth ◽  
Trade Offs ◽  
Green Finance ◽  
The Face ◽  
The Government

The development of green finance is a global trend in the current era. At present, developing the green finance has been included as an important national development project by the Chinese government. With the rapid economic growth, the priorities or trade-offs between the economic development and the natural environment have also aroused different contradictions and problems. With the improvement of people's quality of life, they start to pay more attention to the pollution of the surrounding environment. Therefore, the government should properly intervene and propose effective measures, and green finance is an excellent tool to reconcile social economy and environmental protection and transform the physical investment, thus guiding the social resources towards the environmental protection industry and reaching an optimal interests allocation among the market, society, and government. Consequently, in the face of such a situation, it is necessary to propose a series of models and paths that suit the needs of the Chinese society and promote sustainable development.

scholarly journals Using Artificial Intelligence to classify Jobseekers: The Accuracy-Equity Trade-off

2020 ◽  
pp. 1-19
Author(s):  
SAM DESIERE ◽  
LUDO STRUYVEN
Keyword(s):  
Artificial Intelligence ◽  
Maximum Level ◽  
Employment Services ◽  
Trade Off ◽  
The Public ◽  
Foreign Origin ◽  
Trade Offs ◽  
Graphical Tool ◽  
The Cost

Abstract Artificial intelligence (AI) is increasingly popular in the public sector to improve the cost-efficiency of service delivery. One example is AI-based profiling models in public employment services (PES), which predict a jobseeker’s probability of finding work and are used to segment jobseekers in groups. Profiling models hold the potential to improve identification of jobseekers at-risk of becoming long-term unemployed, but also induce discrimination. Using a recently developed AI-based profiling model of the Flemish PES, we assess to what extent AI-based profiling ‘discriminates’ against jobseekers of foreign origin compared to traditional rule-based profiling approaches. At a maximum level of accuracy, jobseekers of foreign origin who ultimately find a job are 2.6 times more likely to be misclassified as ‘high-risk’ jobseekers. We argue that it is critical that policymakers and caseworkers understand the inherent trade-offs of profiling models, and consider the limitations when integrating these models in daily operations. We develop a graphical tool to visualize the accuracy-equity trade-off in order to facilitate policy discussions.

scholarly journals Sustainability in the Canadian Egg Industry—Learning from the Past, Navigating the Present, Planning for the Future

2018 ◽  
Vol 10 (10) ◽  
pp. 3524 ◽  
Author(s):  
Nathan Pelletier ◽  
Maurice Doyon ◽  
Bruce Muirhead ◽  
Tina Widowski ◽  
Jodey Nurse-Gupta ◽  
...  
Keyword(s):  
Animal Welfare ◽  
Value Chain ◽  
Housing Systems ◽  
The Past ◽  
Trade Offs ◽  
The Face ◽  
Effective Decision Making ◽  
And Shifts ◽  
Societal Expectations ◽  
Management Changes

Like other livestock sectors, the Canadian egg industry has evolved substantially over time and will likely experience similarly significant change looking forward, with many of these changes determining the sustainability implications of and for the industry. Influencing factors include: technological and management changes at farm level and along the value chain resulting in greater production efficiencies and improved life cycle resource efficiency and environmental performance; a changing policy/regulatory environment; and shifts in societal expectations and associated market dynamics, including increased attention to animal welfare outcomes—especially in regard to changes in housing systems for laying hens. In the face of this change, effective decision-making is needed to ensure the sustainability of the Canadian egg industry. Attention both to lessons from the past and to the emerging challenges that will shape its future is required and multi- and interdisciplinary perspectives are needed to understand synergies and potential trade-offs between alternative courses of action across multiple aspects of sustainability. Here, we consider the past, present and potential futures for this industry through the lenses of environmental, institutional (i.e., regulatory), and socio-economic sustainability, with an emphasis on animal welfare as an important emergent social consideration. Our analysis identifies preferred pathways, potential pitfalls, and outstanding cross-disciplinary research questions.

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