Advanced Mission Management System for Unmanned Aerial Vehicles

The paper presents advanced mission management system (MMS) for unmanned aerial vehicles, based on integrated modular avionics (IMA) architecture. IMA architecture enables the MMS to host high end functions for autonomous navigation and attack. MMS is a collection of systems to execute the mission objectives. The system constitutes mission computer (MC), sensors and other sub-systems. The MMS-MC needs to execute advanced algorithms like terrain referenced navigation, vision-aided navigation, automatic target recognition, sensor fusion, online path planning, and tactical planning for autonomy and safety. This demands high-end architecture in terms of hardware, software, and communication. The MMS-MC is designed to exploit the benefits of IMA concepts such as open system architecture, hardware and software architecture catering for portability, technology transparency, scalability, system reconfigurability and fault tolerance. This paper investigates on advanced navigation methods for augmenting INS with terrain-referenced navigation and vision-aided navigation during GPS non-availability. This paper also includes approach to implement these methods and simulation results are provided accordingly, and also discusses in a limited way, the approach for implementing online path planning.Defence Science Journal, Vol. 64, No. 5, September 2014, pp.438-444, DOI:http://dx.doi.org/10.14429/dsj.64.599

A meta-analysis based modified unified theory of acceptance and use of technology (Meta-UTAUT): A review of emerging literature

YesOver the last more than four decades, several theoretical models have been developed to understand the acceptance and use of information systems. Realising the dilemma in selecting the appropriate theoretical model to assess the acceptance and use of technology and considering the pattern of using the Unified Theory of Acceptance and Use of Technology (UTAUT), a modified version (meta-UTAUT) has been developed based on the synthesis of results from 162 existing studies. The aim of this article is to review the emerging literature on meta-UTAUT and offer some future research recommendations. The analysis suggests that studies have started citing the relationships suggested by meta-UTAUT and researchers have reviewed it alongside other alternative models while analysing acceptance and use of technology

Social Media: The Good, the Bad, and the Ugly

Ye

Examining factors influencing Jordanian customers’ intentions and adoption of internet banking: Extending UTAUT2 with risk

YesThe key objective of this study is to propose and examine a conceptual model that best explains the key factors influencing Jordanian customers’ intentions and adoption of Internet banking. The conceptual model proposed was based on the extended Unified Theory of Acceptance and Use of Technology (UTAUT2). This was further extended by adding perceived risk as an external factor. Structural equation modelling (SEM) was conducted to analyse the data collected from the field survey questionnaires administered to a convenience sample of Jordanian banking customers. The results show that behavioural intention is significantly influenced by performance expectancy, effort expectancy, hedonic motivation, price value and perceived risk; however, social influence does not have a significant impact on behavioural intention. This study offers Jordanian banks some guidelines for designing and marketing such channel in order to enhance their acceptance by their customers

Re-examining the Unified Theory of Acceptance and Use of Technology (UTAUT): Towards a Revised Theoretical Model

YesBased on a critical review of the Unified Theory of Acceptance and Use of Technology (UTAUT), this study first formalized an alternative theoretical model for explaining the acceptance and use of information system (IS) and information technology (IT) innovations. The revised theoretical model was then empirically examined using a combination of meta-analysis and structural equation modelling (MASEM) techniques. The meta-analysis was based on 1600 observations on 21 relationships coded from 162 prior studies on IS/IT acceptance and use. The SEM analysis showed that attitude: was central to behavioural intentions and usage behaviours, partially mediated the effects of exogenous constructs on behavioural intentions, and had a direct influence on usage behaviours. A number of implications for theory and practice are derived based on the findings

Emerging role of quantitative imaging (radiomics) and artificial intelligence in precision oncology

Cancer is a fatal disease and the second most cause of death worldwide. Treatment of cancer is a complex process and requires a multi-modality-based approach. Cancer detection and treatment starts with screening/diagnosis and continues till the patient is alive. Screening/diagnosis of the disease is the beginning of cancer management and continued with the staging of the disease, planning and delivery of treatment, treatment monitoring, and ongoing monitoring and follow-up. Imaging plays an important role in all stages of cancer management. Conventional oncology practice considers that all patients are similar in a disease type, whereas biomarkers subgroup the patients in a disease type which leads to the development of precision oncology. The utilization of the radiomic process has facilitated the advancement of diverse imaging biomarkers that find application in precision oncology. The role of imaging biomarkers and artificial intelligence (AI) in oncology has been investigated by many researchers in the past. The existing literature is suggestive of the increasing role of imaging biomarkers and AI in oncology. However, the stability of radiomic features has also been questioned. The radiomic community has recognized that the instability of radiomic features poses a danger to the global generalization of radiomic-based prediction models. In order to establish radiomic-based imaging biomarkers in oncology, the robustness of radiomic features needs to be established on a priority basis. This is because radiomic models developed in one institution frequently perform poorly in other institutions, most likely due to radiomic feature instability. To generalize radiomic-based prediction models in oncology, a number of initiatives, including Quantitative Imaging Network (QIN), Quantitative Imaging Biomarkers Alliance (QIBA), and Image Biomarker Standardisation Initiative (IBSI), have been launched to stabilize the radiomic features

Identifying reputation collectors in community question answering (CQA) sites: Exploring the dark side of social media

YesThis research aims to identify users who are posting as well as encouraging others to post low-quality and duplicate contents on community question answering sites. The good guys called Caretakers and the bad guys called Reputation Collectors are characterised by their behaviour, answering pattern and reputation points. The proposed system is developed and analysed over publicly available Stack Exchange data dump. A graph based methodology is employed to derive the characteristic of Reputation Collectors and Caretakers. Results reveal that Reputation Collectors are primary sources of low-quality answers as well as answers to duplicate questions posted on the site. The Caretakers answer limited questions of challenging nature and fetches maximum reputation against those questions whereas Reputation Collectors answers have so many low-quality and duplicate questions to gain the reputation point. We have developed algorithms to identify the Caretakers and Reputation Collectors of the site. Our analysis finds that 1.05% of Reputation Collectors post 18.88% of low quality answers. This study extends previous research by identifying the Reputation Collectors and 2 how they collect their reputation points

Diffusion and Innovation Theory: Past, Present, and Future Contributions to Academia and Practice

Part 4: PanelInternational audienceThe field of information systems (IS) has throughout its history experienced extensive changes in technology, research, and education. These renewals will continue into the foreseeable future [10]. It is recognized that IS is a key force in the ongoing societal and organizational renewal and change [2, 8, 14]. For example, in the US business sector, IS continues yearly to consume about 30% of total investments made [5]. Recent research document that IS supports the creation of business value, with particular emphasis on an organization’s innovation and change capabilities [1, 3]. Traditionally, research in IS has been interdisciplinary in nature - since it draws on innovation theory, models of value creation, actors’ roles and behaviors, the creation and running of task oriented groups, and how these relate to organizational structures and mechanisms [24]. Throughout its history the question of benefits from investing in IS has been lively discussed

Mobile app stores from the user's perspectives

YesThe use of smartphones has become more prevalent in light of the boom in Internet services and Web 2.0 applications. Mobile stores (e.g., Apple’s App Store and Google Play) have been increasingly used by mobile users worldwide to download or purchase different kinds of applications. This has prompted mobile app practitioners to reconsider their mobile app stores in terms of design, features and functions in order to maintain their customers’ loyalty. Due to the lack of research on this context, this study aims to identify factors that may affect users’ satisfaction and continued intention toward using mobile stores. The proposed model includes various factors derived from information systems literature (i.e., usefulness, ease of use, perceived cost, privacy and security concerns) in addition to the dimensions of mobile interactivity (i.e. active control, mobility, and responsiveness). The study sets out 13 hypotheses that include mediating relationships (e.g., perceived usefulness mediates the influence of ease of use, active control, responsiveness and mobility; perceived ease of use mediates the influence of active control). As well as outlining the proposed research method, the research contributions, limitations and future research recommendations are also addressed