scholarly journals ARTIFICIAL INTELLIGENCE IN INDIAN BANKING SECTOR: CHALLENGES AND OPPORTUNITIES.

2019 ◽  
Vol 7 (4) ◽  
pp. 1581-1587
Author(s):  
C Vijai ◽  
Keyword(s):  
Artificial Intelligence ◽  
Banking Sector ◽  
Challenges And Opportunities

The Power of Matrix Factorization: Methods for Deconvoluting Genetic Heterogeneous Data at Expression Level

2021 ◽  
Vol 15 (8) ◽  
pp. 841-853
Author(s):  
Yuan Liu ◽  
Zhining Wen ◽  
Menglong Li
Keyword(s):  
Artificial Intelligence ◽  
Matrix Factorization ◽  
In Silico ◽  
Genetic Data ◽  
Heterogeneous Data ◽  
Expression Level ◽  
Mathematical Methods ◽  
Challenges And Opportunities ◽  
Factorization Methods ◽  
Genetic Profiles

Background:: The utilization of genetic data to investigate biological problems has recently become a vital approach. However, it is undeniable that the heterogeneity of original samples at the biological level is usually ignored when utilizing genetic data. Different cell-constitutions of a sample could differentiate the expression profile, and set considerable biases for downstream research. Matrix factorization (MF) which originated as a set of mathematical methods, has contributed massively to deconvoluting genetic profiles in silico, especially at the expression level. Objective: With the development of artificial intelligence algorithms and machine learning, the number of computational methods for solving heterogeneous problems is also rapidly abundant. However, a structural view from the angle of using MF to deconvolute genetic data is quite limited. This study was conducted to review the usages of MF methods on heterogeneous problems of genetic data on expression level. Methods: MF methods involved in deconvolution were reviewed according to their individual strengths. The demonstration is presented separately into three sections: application scenarios, method categories and summarization for tools. Specifically, application scenarios defined deconvoluting problem with applying scenarios. Method categories summarized MF algorithms contributed to different scenarios. Summarization for tools listed functions and developed web-servers over the latest decade. Additionally, challenges and opportunities of relative fields are discussed. Results and Conclusion: Based on the investigation, this study aims to present a relatively global picture to assist researchers to achieve a quicker access of deconvoluting genetic data in silico, further to help researchers in selecting suitable MF methods based on the different scenarios.

EMERGING TRENDS IN BANKING SECTOR - ITS CHALLENGES AND OPPORTUNITIES

2018 ◽  
Vol 6 (26) ◽  
Author(s):  
Karigoleshwar .
Keyword(s):  
Banking Sector ◽  
Banking Industry ◽  
Banking System ◽  
Major Change ◽  
Commercial Banking ◽  
Foreign Banks ◽  
Emerging Trends ◽  
Reserve Bank ◽  
Challenges And Opportunities ◽  
Multiple Regions

In financial sector the banking industry is the largest player, has also been undergoing a major change. Today the banking industry is stronger and capable of withstanding the pressures of competition. Today, we are having a fairly well developed banking system with different classes of banks – public sector banks, foreign banks, private sector banks – both old and new generation, regional rural banks and co-operative banks with the Reserve Bank of India as the fountain Head of the system. In the banking field, there has been an unprecedented growth and diversification of banking industry has been so stupendous that it has no parallel in the annals of banking anywhere in the world. The banking industry has experienced a series of significant transformations in the last few decades. Among the most important of them is the change in the type of organizations that dominate the landscape. Since the eighties, banks have increased the scope and scale of their activities and several banks have become very large institutions with a presence in multiple regions of the country.' The paper examines the new trends in commercial banking. The present era the cashless transactions, E-cheques, mobile wallets. The paper attempts to present the emerging trends and its challenges that recently emerged in the banking sector with special emphasis on digitization. It will be useful to the academicians, banking and insurance personnel, students and researchers. Common readers also know the latest innovations in banking sector

Artificial intelligence research in agriculture: a review

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Amit Sood ◽  
Rajendra Kumar Sharma ◽  
Amit Kumar Bhardwaj
Keyword(s):  
Artificial Intelligence ◽  
Peer Review ◽  
Diffusion Of Innovation ◽  
Comprehensive Review ◽  
Content Type ◽  
Design Elements ◽  
Extant Literature ◽  
Use Of Technology ◽  
Challenges And Opportunities ◽  
Market Factors

PurposeThe purpose of this paper is to provide a comprehensive review on the academic journey of artificial intelligence (AI) in agriculture and to highlight the challenges and opportunities in adopting AI-based advancement in agricultural systems and processes.Design/methodology/approachThe authors conducted a bibliometric analysis of the extant literature on AI in agriculture to understand the status of development in this domain. Further, the authors proposed a framework based on two popular theories, namely, diffusion of innovation (DOI) and the unified theory of acceptance and use of technology (UTAUT), to identify the factors influencing the adoption of AI in agriculture.FindingsFour factors were identified, i.e. institutional factors, market factors, technology factors and stakeholder perception, which influence adopting AI in agriculture. Further, the authors indicated challenges under environmental, operational, technological, economical and social categories with opportunities in this area of research and business.Research limitations/implicationsThe proposed conceptual model needs empirical validation across countries or states to understand the effectiveness and relevance.Practical implicationsPractitioners and researchers can use these inputs to develop technology and business solutions with specific design elements to gain benefit of this technology at larger scale for increasing agriculture production.Social implicationsThis paper brings new developed methods and practices in agriculture for betterment of society.Originality/valueThis paper provides a comprehensive review of extant literature and presents a theoretical framework for researchers to further examine the interaction of independent variables responsible for adoption of AI in agriculture.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-10-2020-0448

Effects of Deep Learning Technologies on Employment in the Field of Digital Communication Systems

2021 ◽  
Vol 12 (4) ◽  
pp. 35-42
Author(s):  
Thomas Alan Woolman ◽  
Philip Lee
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Communication Systems ◽  
Digital Communication ◽  
The United States ◽  
Learning Technologies ◽  
Technological Unemployment ◽  
Current State ◽  
Challenges And Opportunities ◽  
Digital Communication Systems

There are significant challenges and opportunities facing the economies of the United States in the coming decades of the 21st century that are being driven by elements of technological unemployment. Deep learning systems, an advanced form of machine learning that is often referred to as artificial intelligence, is presently reshaping many aspects of traditional digital communication technology employment, primarily network system administration and network security system design and maintenance. This paper provides an overview of the current state-of-the-art developments associated with deep learning and artificial intelligence and the ongoing revolutions that this technology is having not only on the field of digital communication systems but also related technology fields. This paper will also explore issues and concerns related to past technological unemployment challenges, as well as opportunities that may be present as a result of these ongoing technological upheavals.

scholarly journals Reports of the AAAI 2016 Spring Symposium Series

AI Magazine ◽  
2017 ◽  
Vol 37 (4) ◽  
pp. 83-88
Author(s):  
Christopher Amato ◽  
Ofra Amir ◽  
Joanna Bryson ◽  
Barbara Grosz ◽  
Bipin Indurkhya ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Systems ◽  
Observational Studies ◽  
Human Error ◽  
Well Being ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Symposium Series ◽  
Research Platform ◽  
Challenges And Opportunities

The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford University's Department of Computer Science, presented the 2016 Spring Symposium Series on Monday through Wednesday, March 21-23, 2016 at Stanford University. The titles of the seven symposia were (1) AI and the Mitigation of Human Error: Anomalies, Team Metrics and Thermodynamics; (2) Challenges and Opportunities in Multiagent Learning for the Real World (3) Enabling Computing Research in Socially Intelligent Human-Robot Interaction: A Community-Driven Modular Research Platform; (4) Ethical and Moral Considerations in Non-Human Agents; (5) Intelligent Systems for Supporting Distributed Human Teamwork; (6) Observational Studies through Social Media and Other Human-Generated Content, and (7) Well-Being Computing: AI Meets Health and Happiness Science.

scholarly journals Digitalization and Artificial Intelligence in Migration and Mobility: Transnational Implications of the COVID-19 Pandemic

Societies ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 135
Author(s):  
Marie McAuliffe ◽  
Jenna Blower ◽  
Ana Beduschi
Keyword(s):  
Artificial Intelligence ◽  
Human Rights ◽  
International Development ◽  
Digital Technology ◽  
Design Development ◽  
Systemic Risks ◽  
Challenges And Opportunities ◽  
The Subject ◽  
And Migration ◽  
Migration Systems

Digitalization and artificial intelligence (AI) technologies in migration and mobility have incrementally expanded over recent years. Iterative approaches to AI deployment experienced a surge during 2020 and into 2021, largely due to COVID-19 forcing greater reliance on advanced digital technology to monitor, inform and respond to the pandemic. This paper critically examines the implications of intensifying digitalization and AI for migration and mobility systems for a post-COVID transnational context. First, it situates digitalization and AI in migration by analyzing its uptake throughout the Migration Cycle. Second, the article evaluates the current challenges and, opportunities to migrants and migration systems brought about by deepening digitalization due to COVID-19, finding that while these expanding technologies can bolster human rights and support international development, potential gains can and are being eroded because of design, development and implementation aspects. Through a critical review of available literature on the subject, this paper argues that recent changes brought about by COVID-19 highlight that computational advances need to incorporate human rights throughout design and development stages, extending well beyond technical feasibility. This also extends beyond tech company references to inclusivity and transparency and requires analysis of systemic risks to migration and mobility regimes arising from advances in AI and related technologies.

Sign in / Sign up

Export Citation Format

Share Document