scholarly journals How Artificial Intelligence is Transforming the Banking Industry: Data Analysis Review

2021 ◽  
pp. 76-81
Author(s):  
Akash Yadav
Keyword(s):  
Artificial Intelligence ◽  
Data Analysis ◽  
Research Paper ◽  
Survey Study ◽  
Financial Industry ◽  
Banking And Finance ◽  
Manual Intervention ◽  
Paper Document ◽  
Potential Impact ◽  
Better Than

AI or Artificial Intelligence, is one of the foremost technologies, which has its potential impact on almost every field. It is an immensely integral component of Computer Science. A technology that intends to provide computer systems and machines the ability to carry out and execute tasks without manual intervention, it simply enables them to work smartly. In simple words, we can say that Artificial Intelligence is about giving human intelligence to machines. This is one of the most noteworthy and remarkable aspects of AI. It plays a significant role in making machines capable of making decisions and that too, faster and better than humans. And all these decisions are data-driven. Artificial Intelligence (AI) is a prominent technology that is continuously evolving day by day, due to which it has become so much prevalent. It is beneficial in diverse fields such as education. business, marketing, healthcare, medicine, agriculture, automobiles, robotics, etc. AI is also quite predominant in the banking and finance industries. AI technology facilitates banking processes as it helps automating most of the tasks, if not entirely, minimizing manual requirements. In this research paper, we will see how implementation of artificial intelligence is assisting the banking and financial industry by improving their operational efficiency and enhancing their productivity. The research paper document also consists of a survey study done through data analysis domain for determining the use of artificial intelligence in banks who have adopted the technology.

Motilitas dan Vabilitas Spermatozoa Ayam Kampung pada Suhu 5°C Menggunakan Pengencer dan Lama Simpan yang Berbeda

2018 ◽  
Vol 5 (2) ◽  
pp. 102
Author(s):  
Enike Dwi Kusumawati ◽  
Selvinus Lawu Woli ◽  
Aju Tjatur Nugroho Krisnaningsih ◽  
Waluyo Edi Susanto ◽  
Syam Rahadi
Keyword(s):  
Data Analysis ◽  
Storage Temperature ◽  
Coconut Water ◽  
Laboratory Research ◽  
Ringer Lactate ◽  
Randomized Design ◽  
Native Chicken ◽  
Lactate Solution ◽  
Better Than

ABSTRAKPenelitian ini dilakukan untuk mengetahui motilitas dan viabilitas spermatozoa ayam kampung pada suhu 5oC menggunakan pengencer dan lama simpan yang berbeda. Metode yang digunakan dalam penelitian ini adalah penelitian laboratorium menggunakan Rancangan Acak Lengkap (RAL) Faktorial dengan pengencer ringer lactat solution, air kelapa dan tanpa pengencer serta lama simpan 0, 3, 6, 9, 12, 15, 18, 21, 24, 27, 30, masing-masing diulang 10 kali. Variabel yang diamati yaitu motilitas dan viabilitas spermatozoa. Analisa data yang digunakan adalah analisis varian. Hasil analisis data menunjukkan bahwa motilitas dan viabilitas spermatozoa menggunakan pengencer ringer lactat solution lebih tinggi (P<0,01) serta dapat bertahan sampai lama simpan 24 jam dibandingkan air kelapa dan tanpa pengencer. Adapun nilai motilitas ringer lactat solution, air kelapa dan tanpa pengencer pada lama simpan 24 jam masing-masing sebesar 43,5±17,17%; 8±4,83%; 6,5±2,4%, sedangkan nilai viabilitasnya sebesar 83,2±7,25%; 64,6±3,20%; dan 63,1±2,33%. Kesimpulan dari hasil penelitian ini adalah ringer lactat solution lebih baik dibandingkan air kelapa dan tanpa pengencer dalam mempertahankan kualitas semen ayam kampung pada suhu simpan 5oC sampai lama simpan 24 jam.Kata Kunci : air kelapa, ayam kampung, motilitas, spermatozoa, viabilitas  ABSTRACTThis study was conducted to determine the motility and viability of spermatozoa of Native chickens at 5oC using different diluents and time storage. The method used in this study was laboratory research using Factorial Completely Randomized Design with ringer lactate solution, coconut water and without diluent at 0, 3, 6, 9, 12, 15, 18, 21, 24, 27, 30 hours of time storage each repeated 10 times. The variables observed were motility and viability of sperm. Data analysis used is variance analysis. The results of data analysis showed that the motility and viability of spermatozoa using ringer lactate solution diluents was higher (P <0.05) than coconut water and without diluents. The motility values of ringer lactat solution, coconut water and without diluents were 43,5±17,17%; 8±4,83%; 6,5±2,4% respectively, while the viability values were 83,2±7,25%; 64,6±3,20% and 63,1±2,33%. The conclusion of this study is that ringer lactat solution is better than coconut water an without diluents in maintaining the quality of Native chicken semen at a storage temperature of 5oC until 24 hours.Keywords: coconut water, motility, native chicken, sperm, viability

Computing Possible Futures

2019 ◽  
Author(s):  
William B. Rouse
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Computational Modeling ◽  
Mental Model ◽  
Data Analytics ◽  
Computational Models ◽  
Senior Managers ◽  
Interactive Visualizations ◽  
Use Of Models ◽  
Better Than

This book discusses the use of models and interactive visualizations to explore designs of systems and policies in determining whether such designs would be effective. Executives and senior managers are very interested in what “data analytics” can do for them and, quite recently, what the prospects are for artificial intelligence and machine learning. They want to understand and then invest wisely. They are reasonably skeptical, having experienced overselling and under-delivery. They ask about reasonable and realistic expectations. Their concern is with the futurity of decisions they are currently entertaining. They cannot fully address this concern empirically. Thus, they need some way to make predictions. The problem is that one rarely can predict exactly what will happen, only what might happen. To overcome this limitation, executives can be provided predictions of possible futures and the conditions under which each scenario is likely to emerge. Models can help them to understand these possible futures. Most executives find such candor refreshing, perhaps even liberating. Their job becomes one of imagining and designing a portfolio of possible futures, assisted by interactive computational models. Understanding and managing uncertainty is central to their job. Indeed, doing this better than competitors is a hallmark of success. This book is intended to help them understand what fundamentally needs to be done, why it needs to be done, and how to do it. The hope is that readers will discuss this book and develop a “shared mental model” of computational modeling in the process, which will greatly enhance their chances of success.

scholarly journals Why a Virtual Assistant for Moral Enhancement When We Could have a Socrates?

2021 ◽  
Vol 27 (4) ◽  
Author(s):  
Francisco Lara
Keyword(s):  
Artificial Intelligence ◽  
Virtual Reality ◽  
New Technologies ◽  
Personal Autonomy ◽  
Moral Enhancement ◽  
Moral Decisions ◽  
Educational Methodology ◽  
Better Than

AbstractCan Artificial Intelligence (AI) be more effective than human instruction for the moral enhancement of people? The author argues that it only would be if the use of this technology were aimed at increasing the individual's capacity to reflectively decide for themselves, rather than at directly influencing behaviour. To support this, it is shown how a disregard for personal autonomy, in particular, invalidates the main proposals for applying new technologies, both biomedical and AI-based, to moral enhancement. As an alternative to these proposals, this article proposes a virtual assistant that, through dialogue, neutrality and virtual reality technologies, can teach users to make better moral decisions on their own. The author concludes that, as long as certain precautions are taken in its design, such an assistant could do this better than a human instructor adopting the same educational methodology.

scholarly journals Predictors of Coping With Expectation Violation: An Integrative Review

2021 ◽  
pp. 108926802110241
Author(s):  
Martin Pinquart ◽  
Adrian Rothers ◽  
Mario Gollwitzer ◽  
Zahra Khosrowtaj ◽  
Martin Pietzsch ◽  
...  
Keyword(s):  
Empirical Support ◽  
Healthy People ◽  
Personality Characteristics ◽  
Integrative Review ◽  
Present Review ◽  
Relative Impact ◽  
Situational Characteristics ◽  
Potential Impact ◽  
Better Than

The present review investigates factors that predict three processes that lead to persistence versus change of expectations after confrontation with expectation violations, based on the violated expectation (ViolEx) model and related models. We address four groups of predictors: (a) characteristics of the expectation, (b) characteristics of the expectation-violating event(s), (c) broader situational characteristics, and (d) personality characteristics. The bulk of studies conducted in this area looked at expectation change in the direction of the experienced violation (accommodation) as their central dependent variable. The strongest empirical support was found for accommodation being less likely and minimizing of the potential impact of the discrepant information (immunization) being more likely to occur (a) after the reality turns out to be worse rather than better than expected, (b) if disconfirming events are more ambiguous, and (c) if depressed rather than healthy people are confronted with better-than-expected events. Given the high heterogeneity between studies on assessed predictors, we recommend a more comprehensive and unifying approach that tests the relative impact and the interplay of the whole range of predictors across paradigms.

scholarly journals Artificial Intelligence in Education (AIEd): a high-level academic and industry note 2021

AI and Ethics ◽  
2021 ◽  
Author(s):  
Muhammad Ali Chaudhry ◽  
Emre Kazim
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Tutoring Systems ◽  
Policy Makers ◽  
Tutoring Systems ◽  
Research And Practice ◽  
The Past ◽  
Artificial Intelligence In Education ◽  
Potential Impact ◽  
High Level ◽  
Contextualized Learning

AbstractIn the past few decades, technology has completely transformed the world around us. Indeed, experts believe that the next big digital transformation in how we live, communicate, work, trade and learn will be driven by Artificial Intelligence (AI) [83]. This paper presents a high-level industrial and academic overview of AI in Education (AIEd). It presents the focus of latest research in AIEd on reducing teachers’ workload, contextualized learning for students, revolutionizing assessments and developments in intelligent tutoring systems. It also discusses the ethical dimension of AIEd and the potential impact of the Covid-19 pandemic on the future of AIEd’s research and practice. The intended readership of this article is policy makers and institutional leaders who are looking for an introductory state of play in AIEd.

scholarly journals Applications of Robotics, AI, and Digital Technologies During COVID-19: A Review

2021 ◽  
pp. 1-23
Author(s):  
Zhuo Zhao ◽  
Yangmyung Ma ◽  
Adeel Mushtaq ◽  
Abdul M. Azam Rajper ◽  
Mahmoud Shehab ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Technology Adoption ◽  
Digital Technology ◽  
Digital Technologies ◽  
Rapid Diagnosis ◽  
Quick Response ◽  
Virus Spread ◽  
Future Directions ◽  
Public Areas ◽  
Potential Impact

Abstract Many countries have enacted a quick response to the unexpected COVID-19 pandemic by utilizing existing technologies. For example, robotics, artificial intelligence, and digital technology have been deployed in hospitals and public areas for maintaining social distancing, reducing person-to-person contact, enabling rapid diagnosis, tracking virus spread, and providing sanitation. In this paper, 163 news articles and scientific reports on COVID-19-related technology adoption were screened, shortlisted, categorized by application scenario, and reviewed for functionality. Technologies related to robots, artificial intelligence, and digital technology were selected from the pool of candidates, yielding a total of 50 applications for review. Each case was analyzed for its engineering characteristics and potential impact on the COVID-19 pandemic. Finally, challenges and future directions regarding the response to this pandemic and future pandemics were summarized and discussed.

Civil Aeroengine Fault Diagnosis Based on Fuzzy Least Square Support Vector Machine

2011 ◽  
Vol 130-134 ◽  
pp. 2047-2050 ◽  
Author(s):  
Hong Chun Qu ◽  
Xie Bin Ding
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Support Vector Machine ◽  
Fault Diagnosis ◽  
Coefficient Matrix ◽  
Least Square ◽  
Support Vector ◽  
Influence Coefficient ◽  
Structural Risk ◽  
Better Than

SVM(Support Vector Machine) is a new artificial intelligence methodolgy, basing on structural risk mininization principle, which has better generalization than the traditional machine learning and SVM shows powerfulability in learning with limited samples. To solve the problem of lack of engine fault samples, FLS-SVM theory, an improved SVM, which is a method is applied. 10 common engine faults are trained and recognized in the paper.The simulated datas are generated from PW4000-94 engine influence coefficient matrix at cruise, and the results show that the diagnostic accuracy of FLS-SVM is better than LS-SVM.

An Artificial Intelligence Tool for Image Simulation in Rhinoplasty

2021 ◽  
Author(s):  
Hernan Chinsk ◽  
Ricardo Lerch ◽  
Damián Tournour ◽  
Luis Chinski ◽  
Diego Caruso
Keyword(s):  
Artificial Intelligence ◽  
Survey Study ◽  
P Value ◽  
Cross Sectional Survey ◽  
Simulated Image ◽  
Level Of Evidence ◽  
Cross Sectional ◽  
Partial Agreement ◽  
Aesthetic Rhinoplasty ◽  
Level Of Agreement

AbstractDuring rhinoplasty consultations, surgeons typically create a computer simulation of the expected result. An artificial intelligence model (AIM) can learn a surgeon's style and criteria and generate the simulation automatically. The objective of this study is to determine if an AIM is capable of imitating a surgeon's criteria to generate simulated images of an aesthetic rhinoplasty surgery. This is a cross-sectional survey study of resident and specialist doctors in otolaryngology conducted in the month of November 2019 during a rhinoplasty conference. Sequential images of rhinoplasty simulations created by a surgeon and by an AIM were shown at random. Participants used a seven-point Likert scale to evaluate their level of agreement with the simulation images they were shown, with 1 indicating total disagreement and 7 total agreement. Ninety-seven of 122 doctors agreed to participate in the survey. The median level of agreement between the participant and the surgeon was 6 (interquartile range or IQR 5–7); between the participant and the AIM it was 5 (IQR 4–6), p-value < 0.0001. The evaluators were in total or partial agreement with the results of the AIM's simulation 68.4% of the time (95% confidence interval or CI 64.9–71.7). They were in total or partial agreement with the surgeon's simulation 77.3% of the time (95% CI 74.2–80.3). An AIM can emulate a surgeon's aesthetic criteria to generate a computer-simulated image of rhinoplasty. This can allow patients to have a realistic approximation of the possible results of a rhinoplasty ahead of an in-person consultation. The level of evidence of the study is 4.

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