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Article
Publication date: 15 August 2016

Behzad Bayat, Julita Bermejo-Alonso, Joel Carbonera, Tullio Facchinetti, Sandro Fiorini, Paulo Goncalves, Vitor A.M. Jorge, Maki Habib, Alaa Khamis, Kamilo Melo, Bao Nguyen, Joanna Isabelle Olszewska, Liam Paull, Edson Prestes, Veera Ragavan, Sajad Saeedi, Ricardo Sanz, Mae Seto, Bruce Spencer, Amirkhosro Vosughi and Howard Li

IEEE Ontologies for Robotics and Automation Working Group were divided into subgroups that were in charge of studying industrial robotics, service robotics and autonomous…

992

Abstract

Purpose

IEEE Ontologies for Robotics and Automation Working Group were divided into subgroups that were in charge of studying industrial robotics, service robotics and autonomous robotics. This paper aims to present the work in-progress developed by the autonomous robotics (AuR) subgroup. This group aims to extend the core ontology for robotics and automation to represent more specific concepts and axioms that are commonly used in autonomous robots.

Design/methodology/approach

For autonomous robots, various concepts for aerial robots, underwater robots and ground robots are described. Components of an autonomous system are defined, such as robotic platforms, actuators, sensors, control, state estimation, path planning, perception and decision-making.

Findings

AuR has identified the core concepts and domains needed to create an ontology for autonomous robots.

Practical implications

AuR targets to create a standard ontology to represent the knowledge and reasoning needed to create autonomous systems that comprise robots that can operate in the air, ground and underwater environments. The concepts in the developed ontology will endow a robot with autonomy, that is, endow robots with the ability to perform desired tasks in unstructured environments without continuous explicit human guidance.

Originality/value

Creating a standard for knowledge representation and reasoning in autonomous robotics will have a significant impact on all R&A domains, such as on the knowledge transmission among agents, including autonomous robots and humans. This tends to facilitate the communication among them and also provide reasoning capabilities involving the knowledge of all elements using the ontology. This will result in improved autonomy of autonomous systems. The autonomy will have considerable impact on how robots interact with humans. As a result, the use of robots will further benefit our society. Many tedious tasks that currently can only be performed by humans will be performed by robots, which will further improve the quality of life. To the best of the authors’knowledge, AuR is the first group that adopts a systematic approach to develop ontologies consisting of specific concepts and axioms that are commonly used in autonomous robots.

Details

Industrial Robot: An International Journal, vol. 43 no. 5
Type: Research Article
ISSN: 0143-991X

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Article
Publication date: 16 January 2023

Joseph S. Nadan, Abram Walton, Behzad Tabaei, Charles Edward Bryant and Natalie Shah

This paper aims to propose an innovative method for deploying a personalized instructor-created software-aided assessment system, that will disrupt traditional learning…

247

Abstract

Purpose

This paper aims to propose an innovative method for deploying a personalized instructor-created software-aided assessment system, that will disrupt traditional learning environments by allowing students to confidentially and with indirect supervision from the instructor, assess their knowledge and ability to achieve the course outcomes.

Design/methodology/approach

Through empirical evaluation in real-world educational settings, the authors examine the impact of augmenting human activity in the classroom with an innovative software platform to transform the learning process.

Findings

Findings indicate that this software-aided assessment system effectively augments human interactivity by providing timely instructor-designed feedback to increase knowledge retention and skillsets.

Practical implications

This study has shown that incorporating disruptive innovation through the use of software-aided assessment systems increases the effectiveness of the faculty in the classroom and enhances student learning and retention. Thus, a transformative software-aided assessment system design that incorporates artificial intelligence into the learning pathway should be pursued. These software-aided assessments are disruptive innovation as they are formative, frequent and require little direct involvement from the instructor.

Originality/value

To the best of the authors’ knowledge, this study is the first of its kind to incorporate artificial intelligence into the assessment process by analyzing results of pilot programs at several universities. The results demonstrate how using software-aided transformative assessments in various courses have helped instructors assess students’ preparedness and track their learning progress. These software-aided systems are the first step in bringing disruptive innovation to the classroom as these software-aided assessment instruments rapidly assess learners’ knowledge and skills based on short, easily created, multiple-choice tests, with little direct engagement from the faculty.

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Article
Publication date: 15 January 2020

Maryam Zarif Sagheb, Behzad Ghasemi and Seyed Kamran Nourbakhsh

The purpose of this paper is to present the factors affecting purchase intention of foreign food products in the Iranian context.

1384

Abstract

Purpose

The purpose of this paper is to present the factors affecting purchase intention of foreign food products in the Iranian context.

Design/methodology/approach

The present study is a survey research and has a quantitative approach. According to Morgan’s table, 384 people were selected as sample size. Based on an in-depth review of previous literature, a comprehensive set of sub-factors related to customer’s purchase intention was extracted to design questionnaire. Then, exploratory factor analysis and confirmatory factor analysis were applied to identify and confirm the factors affecting purchase intention of foreign food products in Iran.

Findings

The obtained results illustrate 13 factors as follows: “corporate social responsibility,” “customer knowledge and awareness,” “perceived risk,” “retailer’s commercial image,” “customer’s personality characteristics,” “social identity,” “product features,” “attitude,” “country-of-origin,” “perceived value,” “subjective norm,” “loyalty” and “perceived behavioral control.”

Research limitations/implications

As the present research was carried out in the Iranian context, the generalization of the findings is limited and caution should be taken in this regard.

Practical implications

The identified factors could contribute to international food companies and retailers to understand customers’ expectations and to gain more market share in Iran.

Originality/value

The originality of this paper lies in identifying a comprehensive set of the factors affecting purchase intention of foreign food products and developing the theoretical literature in the field of the present research.

Details

British Food Journal, vol. 122 no. 5
Type: Research Article
ISSN: 0007-070X

Keywords

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Article
Publication date: 3 April 2018

Shohreh SeyyedHosseini, Asefeh Asemi, Ahmad Shabani and Mozafar CheshmehSohrabi

According to the studies conducted in Iran, the breast cancer is the most frequent type of cancer among women. This study aimed to explore the state of health information supply…

345

Abstract

Purpose

According to the studies conducted in Iran, the breast cancer is the most frequent type of cancer among women. This study aimed to explore the state of health information supply and demand on breast cancer among Iranian medical researchers and Iranian Web users from 2011 to 2015.

Design/methodology/approach

A mixed method research is conducted in this study. In qualitative part, a focus group interview is applied to the users to identify their selected keywords searched for breast cancer in Google. The collected data are analyzed using Open Code software. In quantitative part, data are synthesized using the R software in two parts. First, users’ internet information-seeking behavior (ISB) is analyzed using the Google Trends outputs from 2011 to 2015. Second, the scientific publication behavior of Iranian breast cancer specialists are surveyed using PubMed during the period of the study.

Findings

The results show that the search volume index of preferred keywords on breast cancer has increased from 4,119 in 2011 to 4,772 in 2015. Also, the findings reveal that Iranian scholars had 873 scientific papers on breast cancer in PubMed from 2011 to 2015. There was a significant and positive relationship between Iranian ISB in the Google Trends and SPB of Iranian scholars on breast cancer in PubMed.

Research limitations/implications

This study investigates only the state of health information supply and demand in PubMed and Google Trends and not additional databases often used for medical studies and treatment.

Originality/value

This study provides a road map for health policymakers in Iran to direct the breast cancer studies.

Details

The Electronic Library, vol. 36 no. 2
Type: Research Article
ISSN: 0264-0473

Keywords

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