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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.

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.

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

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.

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.

The purpose of this paper is to present a localization and mapping data set acquired by a fixed-wing unmanned aerial vehicle (UAV). The data set was collected for educational and research purposes: to save time in dealing with hardware and to compare the results with a benchmark data set. The data were collected in standard Robot Operating System (ROS) format. The environment, fixed-wing, and sensor configuration are explained in detail. GPS coordinates of the fixed-wing are also available as ground truth. The data set is available for download (www.ece.unb.ca/COBRA/open_source.htm).

The data were collected in standard ROS format. The environment, fixed-wing, and sensor configuration are explained in detail.

The data set can be used for target localization and mapping. The data were collected to assist algorithm developments and help researchers to compare their results. Robotic data sets are specifically important when they are related to unmanned systems such as fixed-wing aircraft.

The Robotics Data Set Repository (RADISH) by A. Howard and N. Roy hosts 41 well-known data sets with different sensors; however, there is no fixed-wing data set in RADISH. This work presents two data sets collected by a fixed-wing aircraft using ROS standards. The data sets can be used for target localization and SLAM.

The purpose of this study was to examine the dimensions of athletic star power associated with Generation Y sports consumption. Multivariate analyses revealed that athletic star power factors (Professional Trustworthiness, Likeable Personality, Athletic Expertise, Social Attractiveness and Characteristic Style) were positively (p < .05) predictive of the sport consumption factors (Event Consumption and Merchandise Consumption).

The criticisms put forward against economic impact studies lead to a key question: “Is it possible to measure the impact of sporting properties and events in a holistic, conservative, and reliable way?” This research endeavors to build on the academic literature to add to the scope and rigor of economic impact research by proposing an impact assessment process model for practitioners that facilitates employment of a holistic, conservative and reliable impact study and seeks to address these concerns.

Using seven identified key realities that highlight the challenges facing impact studies, and adopting a collaborative self-ethnographic methodological approach, the work highlights lessons learned from four empirical economic impact studies undertaken by the authors over a five-year period.

The study provides a broad view of impact studies, which extend beyond financial implications and provides a more inclusive methodology. Particularly, the proposed impact assessment process model seeks to improve the credibility of impact studies by facilitating a holistic approach that incorporates direct, indirect and intangible impacts.

The proposed model has value to researchers and is designed to improve the overall credibility of economic impact methodology. It also provides a more accurate measure of direct impact while considering intangible and indirect impacts, including social/community impacts.

The proposed model has value to and practitioners and is designed to improve the overall credibility of economic impact methodology. It also provides a more accurate measure of direct impact while considering intangible and indirect impacts, including social/community impacts.

The proposed process model to measure the impact of a sports event is a needed element in the world of funding, managing and implementing events of all sizes.

The use of plagiarism detection software such as Turnitin or SafeAssign has become common in higher education. While frequently used to catch plagiarism, some institutions have used it as a learning tool to help students better understand plagiarism and the conventions of academic writing. In an international branch campus in the Middle East, a survey was given to undergraduate students, primarily second language students, on the use of Turnitin to help with their writing. Most participants found that the software helped them improve their paraphrasing skills, understand the use of citations, avoid plagiarism and, to a lesser extent, improve their language skills.

أﺻﺑ ﺢ ا ﺳﺗ ﺧدام ﺑ رﻧﺎﻣﺞ اﻟﻛﺷ ف ﻋن ا ﻻﻧﺗ ﺣﺎ ل ﻣﺛ ل Turnitin أو SafeAssign ﺷ ﺎ ﺋ ﻌًﺎ ﻓ ﻲ ا ﻟ ﺗ ﻌ ﻠ ﯾ م ا ﻟ ﻌ ﺎ ﻟ ﻲ . ﻋ ﻠ ﻰ ا ﻟ ر ﻏ م ﻣ ن ا ﺳ ﺗ ﺧ د ا ﻣ ﮭ ﺎ ﺑ ﺷ ﻛ ل ﻣﺗ ﻛرر ﻟﻠﻘﺑ ض ﻋﻠ ﻰ ا ﻻﻧﺗ ﺣﺎ ل ، ﻓﻘد ا ﺳﺗ ﺧدﻣﺗ ﮫ ﺑ ﻌ ض اﻟ ﻣؤﺳﺳﺎ ت ﻛﺄداة ﺗ ﻌﻠﯾ ﻣﯾ ﺔ ﻟ ﻣ ﺳﺎ ﻋدة اﻟ طﻼب ﻋﻠ ﻰ ﻓ ﮭم ا ﻻﻧﺗ ﺣﺎ ل ﺑ ﺷﻛل أﻓ ﺿ ل واﺗﻔﺎ ﻗﯾﺎ ت اﻟﻛﺗﺎﺑ ﺔ ا ﻷ ﻛﺎدﯾ ﻣﯾ ﺔ. ﻓ ﻲ ﺣ ر م ﻓ ر ع دو ﻟ ﻲ ﻓ ﻲ اﻟﺷ ر ق ا ﻷ و ﺳ ط ، ﺗم إ ﺟ ر ا ء د ر ا ﺳ ﺔ ا ﺳ ﺗﻘ ﺻ ﺎﺋﯾ ﺔ ﻟ ط ﻼ ب اﻟﻣر ﺣ ﻠ ﺔ اﻟﺟ ﺎ ﻣﻌﯾ ﺔ ، و ﺧ ﺎ ﺻ ﺔ ط ﻼ ب اﻟﻠ ﻐﺔ اﻟ ﺛﺎﻧﯾ ﺔ ، ﺣ و ل ا ﺳ ﺗ ﺧ دا م Turnitin ﻟﻠﻣ ﺳ ﺎ ﻋ دة ﻓ ﻲ ﻛﺗﺎﺑﺎﺗ ﮭم. و ﺟ د ﻣﻌ ظ م اﻟﻣ ﺷ ﺎ ر ﻛﯾ ن أ ن اﻟ ﺑ ر ﻧﺎ ﻣ ﺞ ﺳ ﺎ ﻋ دھ م ﻋ ﻠ ﻰ ﺗ ﺣ ﺳ ﯾ ن ﻣﮭﺎ ر ا ت إ ﻋ ﺎدة اﻟ ﺻ ﯾﺎ ﻏ ﺔ وﻓ ﮭم ا ﺳﺗ ﺧدام ا ﻻﺳﺗ ﺷﮭﺎدا ت وﺗ ﺟﻧ ب ا ﻻﻧﺗ ﺣﺎ ل وﺗ ﺣﺳﯾ ن ﻣﮭﺎ راﺗ ﮭم اﻟﻠ ﻐوﯾﺔ إﻟ ﻰ ﺣد أﻗ ل.

Automated driving systems (ADSs) are being developed to avoid human error and improve driving safety. However, limited focus has been given to the fallback behavior of automated vehicles, which act as a fail-safe mechanism to deal with safety issues resulting from sensor failure. Therefore, this study aims to establish a fallback control approach aimed at driving an automated vehicle to a safe parking lane under perceptive sensor malfunction.

Owing to an undetected area resulting from a front sensor malfunction, the proposed ADS first creates virtual vehicles to replace existing vehicles in the undetected area. Afterward, the virtual vehicles are assumed to perform the most hazardous driving behavior toward the host vehicle; an adaptive model predictive control algorithm is then presented to optimize the control task during the fallback procedure, avoiding potential collisions with surrounding vehicles. This fallback approach was tested in typical cases related to car-following and lane changes.

It is confirmed that the host vehicle avoid collision with the surrounding vehicles during the fallback procedure, revealing that the proposed method is effective for the test scenarios.

This study presents a model for the path-planning problem regarding an automated vehicle under perceptive sensor failure, and it proposes an original path-planning approach based on virtual vehicle scheme to improve the safety of an automated vehicle during a fallback procedure. This proposal gives a different view on the fallback safety problem from the normal strategy, in which the mode is switched to manual if a driver is available or the vehicle is instantly stopped.

Man has been seeking an ideal existence for a very long time. In this existence, justice, love, and peace are no longer words, but actual experiences. How ever, with the American preemptive invasion and occupation of Afghanistan and Iraq and the subsequent prisoner abuse, such an existence seems to be farther and farther away from reality. The purpose of this work is to stop this dangerous trend by promoting justice, love, and peace through a change of the paradigm that is inconsistent with justice, love, and peace. The strong paradigm that created the strong nation like the U.S. and the strong man like George W. Bush have been the culprit, rather than the contributor, of the above three universal ideals. Thus, rather than justice, love, and peace, the strong paradigm resulted in in justice, hatred, and violence. In order to remove these three and related evils, what the world needs in the beginning of the third millenium is the weak paradigm. Through the acceptance of the latter paradigm, the golden mean or middle paradigm can be formulated, which is a synergy of the weak and the strong paradigm. In order to understand properly the meaning of these paradigms, however, some digression appears necessary.

Man has been seeking an ideal existence for a very long time. In this existence, justice, love, and peace are no longer words, but actual experiences. How ever, with the American preemptive invasion and occupation of Afghanistan and Iraq and the subsequent prisoner abuse, such an existence seems to be farther and farther away from reality. The purpose of this work is to stop this dangerous trend by promoting justice, love, and peace through a change of the paradigm that is inconsistent with justice, love, and peace. The strong paradigm that created the strong nation like the U.S. and the strong man like George W. Bush have been the culprit, rather than the contributor, of the above three universal ideals. Thus, rather than justice, love, and peace, the strong paradigm resulted in in justice, hatred, and violence. In order to remove these three and related evils, what the world needs in the beginning of the third millenium is the weak paradigm. Through the acceptance of the latter paradigm, the golden mean or middle paradigm can be formulated, which is a synergy of the weak and the strong paradigm. In order to understand properly the meaning of these paradigms, however, some digression appears necessary.

The complexity and interdisciplinarity of healthcare industry problems make this industry one of the attention centers of computer-based simulation studies to provide a proper tool for interaction between decision-makers and experts. The purpose of this study is to present a metamodel-based simulation optimization in an emergency department (ED) to allocate human resources in the best way to minimize door to doctor time subject to the problem constraints which are capacity and budget.

To obtain the objective of this research, first the data are collected from a public hospital ED in Brazil, and then an agent-based simulation is designed and constructed. Afterwards, three machine-learning approaches, namely, adaptive neuro-fuzzy inference system (ANFIS), feed forward neural network (FNN) and recurrent neural network (RNN), are used to build an ensemble metamodel through adaptive boosting. Finally, the results from the metamodel are applied in a discrete imperialist competitive algorithm (ICA) for optimization.

Analyzing the results shows that the yellow zone section is considered as a potential bottleneck of the ED. After 100 executions of the algorithm, the results show a reduction of 24.82 per cent in the door to doctor time with a success rate of 59 per cent.

This study fulfils an identified need to optimize human resources in an ED with less computational time.