Automation, per se, is not job elimination: How artificial intelligence forwards cooperative human-machine coexistence

Hamid, Oussama H.; Smith, Norris Lee; Barzanji, Amin

doi:10.1109/indin.2017.8104891

Cited by 33 publications

(19 citation statements)

References 12 publications

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“…Specifically, activating, analysing, and summarising unstructured data and structured data helps executive teams to make scientific decisions, improve the company's competitive advantage in the same industry, and thereby increase the overall revenue of the company. A machine learning research (Hamid et al, 2017) indicates: artificial intelligence and machine learning are developing in the direction of "human-machine coexistence"; that is, intelligent machines obtain certain insights through work and integrate them with human thinking, combining ideas to improve people's ability to judge and make decisions about things. This is an efficient professional interaction, which prompts both parties to do what they do best.…”

Section: Smart Data a The Concept Of Smart Datamentioning

confidence: 99%

A Discussion on How to Apply Smart Data for Precision Marketing in the Global Economy: Asian Context

Zhu

2021

economit

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The aim of the research is to provide support for the application of smart data, precision marketing, and business analysis and in so doing, it is aimed to contribute to the further sustainable development of the economy. At present, intelligent technologies such as artificial intelligence and big data are developing in full swing, and various application scenarios are gradually being launched. Smart data is a new sort of database in combination with artificial intelligence and big data technology, which makes artificial intelligence technology and big data the core concepts and the foundation of digital smart data. With smart data, companies could apply precision marketing to better reach their target consumers, push notifications at the right time, advertise the products and services consumers are interested in, and establish personalised marketing communication with each consumer in order to increase marketing efficiency. Undoubtedly, precision marketing has become the top priority in the development of the digital marketing industry, and it is becoming increasingly popular. The paper is based on this perspective and starts with an overview of smart data. The definition and development status of smart data are first reviewed, followed by an analysis of the application of smart data technology and precision marketing in digital marketing.

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Section: Smart Data a The Concept Of Smart Datamentioning

confidence: 99%

A Discussion on How to Apply Smart Data for Precision Marketing in the Global Economy: Asian Context

Zhu

2021

economit

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“…Internationally renowned Internet giants, such as Google, IBM, Alibaba, Baidu and Tencent, have applied AI to analyze various financial services. Well-known financial industry names, such as JPMorgan Chase, Goldman Sachs, and accounting firms, such as PWC and Ernst & Young [11], have all followed this technological wave, and many have invested heavily in the AI field.…”

Section: Motivationmentioning

confidence: 99%

Novel Financial Capital Flow Forecast Framework Using Time Series Theory and Deep Learning: A Case Study Analysis of Yu’e Bao Transaction Data

et al. 2019

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Appropriate monetary liquidity is important for financial institutions. When institutions lack adequate cash flow for customer redemption, their income will decrease, their reputation will be affected, and they may even go bankrupt. However, the opposite extreme in which more cash is reserved than needed may result in lost opportunities to make successful investments. This study uses Yu'e Bao transaction data to investigate a method for forecasting financial capital flow. Yu'e Bao, which is a financial product launched by Alibaba, faces the core challenge of maximizing commercial profits to reduce investment risks. Liquidity risk is considered the main factor in Yu'e Bao's investment strategy. First, a linear model called YEB_ARIMA is proposed by determining the autocorrelation (ACF) and partial autocorrelation (PACF) parameters, which are optimized by the grid search method. Second, a deep learning model called YEB_LSTM is introduced to strengthen the expressiveness of the model that yields nonlinear transaction features. Then, a hybrid learning method called YEB_Hybrid is applied to improve the original weak classifiers. This model includes both a linear combination and logistic regression learning. Third, a set of experiments and analyses are conducted based on subscription and redemption datasets to demonstrate that the hybrid model achieves an accuracy of 84.39% and 84.36%, respectively, under a variety of evaluation indexes. Finally, various proposed fund reserve ratios are provided based on capital forecasts.INDEX TERMS Liquidity risk, ARIMA, LSTM, time series, capital flow prediction, big data financial analysis.

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“…Automated systems are an inevitable futuristic vision of human societal development [1][2][3]. A vital determinant of any innovative infrastructure in such a vision [4] is the incorporation of autonomous guided vehicles (AGVs).…”

Section: Introductionmentioning

confidence: 99%

A cost-effective GPS-aided autonomous guided vehicle for global path planning

2021

Self Cite

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This paper presents a robotic platform of a cost-effective GPS-aided autonomous guided vehicle (AGV) for global path planning. The platform is made of a mechanical radio controlled (RC) rover and an Arduino Uno microcontroller. An installed magnetic digital compass helps determine the right direction of the RC rover by continuously synchronising the heading and bearing of the vehicle. To ensure effective monitoring of the vehicle’s position as well as track the corresponding path, an LCD keypad shield was, further, used. The contribution of the work is that the designed GPS-aided AGV can successfully navigate its way towards a destination point in an obstacle-free outdoor environment by solely relying on its calculation of the shortest path and utilising the corresponding GPS data. This result is achieved with a minimum error possible that lies within a circle of one meter radius around the given destination, allowing the devised GPS-aided AGV to be used in a variety of applications such as landmine detection and removal.

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Automation, per se, is not job elimination: How artificial intelligence forwards cooperative human-machine coexistence

Cited by 33 publications

References 12 publications

A Discussion on How to Apply Smart Data for Precision Marketing in the Global Economy: Asian Context

A Discussion on How to Apply Smart Data for Precision Marketing in the Global Economy: Asian Context

Novel Financial Capital Flow Forecast Framework Using Time Series Theory and Deep Learning: A Case Study Analysis of Yu’e Bao Transaction Data

A cost-effective GPS-aided autonomous guided vehicle for global path planning

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