Search results

This paper presents a survey of research into interactive robotic systems for the purpose of identifying the state of the art capabilities as well as the extant gaps in this emerging field. Communication is multimodal. Multimodality is a representation of many modes chosen from rhetorical aspects for its communication potentials. The author seeks to define the available automation capabilities in communication using multimodalities that will support a proposed Interactive Robot System (IRS) as an AI mounted robotic platform to advance the speed and quality of military operational and tactical decision making.

This review will begin by presenting key developments in the robotic interaction field with the objective of identifying essential technological developments that set conditions for robotic platforms to function autonomously. After surveying the key aspects in Human Robot Interaction (HRI), Unmanned Autonomous System (UAS), visualization, Virtual Environment (VE) and prediction, the paper then proceeds to describe the gaps in the application areas that will require extension and integration to enable the prototyping of the IRS. A brief examination of other work in HRI-related fields concludes with a recapitulation of the IRS challenge that will set conditions for future success.

Using insights from a balanced cross section of sources from the government, academic, and commercial entities that contribute to HRI a multimodal IRS in military communication is introduced. Multimodal IRS (MIRS) in military communication has yet to be deployed.

Multimodal robotic interface for the MIRS is an interdisciplinary endeavour. This is not realistic that one can comprehend all expert and related knowledge and skills to design and develop such multimodal interactive robotic interface. In this brief preliminary survey, the author has discussed extant AI, robotics, NLP, CV, VDM, and VE applications that is directly related to multimodal interaction. Each mode of this multimodal communication is an active research area. Multimodal human/military robot communication is the ultimate goal of this research.

A multimodal autonomous robot in military communication using speech, images, gestures, VST and VE has yet to be deployed. Autonomous multimodal communication is expected to open wider possibilities for all armed forces. Given the density of the land domain, the army is in a position to exploit the opportunities for human–machine teaming (HMT) exposure. Naval and air forces will adopt platform specific suites for specially selected operators to integrate with and leverage this emerging technology. The possession of a flexible communications means that readily adapts to virtual training will enhance planning and mission rehearsals tremendously.

Interaction, perception, cognition and visualization based multimodal communication system is yet missing. Options to communicate, express and convey information in HMT setting with multiple options, suggestions and recommendations will certainly enhance military communication, strength, engagement, security, cognition, perception as well as the ability to act confidently for a successful mission.

The objective is to develop a multimodal autonomous interactive robot for military communications. This survey reports the state of the art, what exists and what is missing, what can be done and possibilities of extension that support the military in maintaining effective communication using multimodalities. There are some separate ongoing progresses, such as in machine-enabled speech, image recognition, tracking, visualizations for situational awareness, and virtual environments. At this time, there is no integrated approach for multimodal human robot interaction that proposes a flexible and agile communication. The report briefly introduces the research proposal about multimodal interactive robot in military communication.

This study aims to investigate the potential use of potato peel extracts as antibacterial finishes for cotton fabrics against Staphylococcus aureus and Escherichia coli. Potato peels are abundant as waste and provide a natural, cheaper and sustainable alternative means of preventing the spread of bacterial infections on cotton fabric.

This research included the characterization of potato peel extracts, application of the extract onto cotton fabric and efficacy testing of the treated cotton fabric against bacteria. Phytochemical screening, agar well diffusion antibacterial test, minimum inhibitory concentration and Fourier transform infrared (FTIR) tests were used to characterize the extract. Antibacterial efficacy of the treated fabric was determined qualitatively using the disc diffusion assay and quantitatively using the bacteria reduction test.

Phytochemical screening confirmed the presence of several secondary metabolites including phenols and flavonoids. Antibacterial tests revealed a positive response in Escherichia coli and Staphylococcus aureus with a zone of inhibition of 6.50 mm and 5.60 mm, respectively. Additional peaks on the FTIR spectroscopy confirmed the presence of potato peel extract on the treated cotton fabric. The treated cotton fabrics showed efficacy against Staphylococcus aureus and Escherichia coli up to 20 washes.

This study introduced the application of potato peel extracts onto cotton fabrics and assessment of the antibacterial properties before and after washing. Results of this study suggest that potato peel extracts can be used as an organic eco-friendly antibacterial finish for cotton fabrics.

The purpose of this study is to assess the influence of Al and Ag addition on thermal, mechanical and shape memory properties of Cu-Al-Ag alloy.

The material is synthesized in a controlled atmosphere to minimize the reaction of alloying elements with the atmosphere. Cast samples were homogenized, then subjected to hot rolling and further betatized, followed by step quenching. Eight samples were chosen for study among which first four samples varied in Al content, and the next set of four samples varied in Ag composition.

The testing yielded a result that the increase in binary alloying element decreased transformation temperature range but increased entropy and elastic energy values. It also improved the shape memory effect and mechanical properties (UTS and hardness). An increase in ternary alloying element increased transformation temperature range, entropy and elastic energy values. The shape memory effect and mechanical properties are enhanced by the increase in ternary alloying element. The study revealed that compositional variation of Al should be limited to a range of 8 to 14 Wt.% and Ag from 2 to 8 Wt.%. Microstructural and diffraction studies identified the ß’1 martensite as a desirable phase for enhancing shape memory properties.

Numerous studies have been made in exploring the transformation temperature and phase formation for similar Cu-Al-Ag shape memory alloys, but their influence on shape memory effect was not extensively studied. In the present work, the influence of Al and Ag content on shape memory characteristics is carried out to increase the design choice for engineering applications of shape memory alloy. These materials exhibit mechanical and shape memory properties within operating ranges similar to other copper-based shape memory alloys.

Coronavirus Disease 2019 (COVID-19) necessitated the need for “Hospital-at-home” improvisations that involve wearable technology to classify patients within households before visiting health institutions. Do-It-Yourself wearable devices allow for the collection of health data leading to the detection and/or prediction of the prevalence of the disease. The sensitive nature of health data requires safeguards to ensure patients’ privacy is not violated. The previous work utilized Hyperledger Fabric to verify transmitted data within Smart Homes, allowing for the possible implementation of legal restrictions through smart contracts in the future. This study aims to explore privacy-enhancing authentication schemes that are operated by multiple credential issuers and capable of integration into the Hyperledger ecosystem.

Design Science Research is the methodology that was used in this study. An architecture for ABC-privacy was developed and evaluated.

While the privacy-by-design architecture enhances data privacy through edge and fog computing architecture, there is a need to provide an additional privacy layer that limits the amount of data that patients disclose. Selective disclosure of credentials limits the number of information patients or devices divulge.

The evaluation of this study identified Coconut as the most suitable attribute-based credentials scheme for the Smart Homes Patients and Health Wearables use case Coconut user-centric architecture Hyperledger integration multi-party threshold authorities public and private attributes re-randomization and unlinkable revelation of selective attribute revelations.