55,419 research outputs found

    A Phone Learning Model for Enhancing Productivity of Visually Impaired Civil Servants

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    Phone-based learning in civil service is the use of voice technologies to deliver learning and capacity building training services to government employees. The Internet revolution and advancement in Information and Communications Technology (ICT) have given rise to online and remote staff training for the purpose of enhancing workers productivity. The need for civil servants in Nigeria to develop capacity that will enhance knowledge is a key requirement to having competitive advantage in the work place. Existing online learning platforms (such as web-based learning, mobile learning, etc) did not consider the plight of the visually impaired. These platforms provide graphical interfaces that require sight to access. The visually impaired civil servants require auditory access to functionalities that exist in learning management system on the Internet. Thus a gap exist between the able-bodied and visually impaired civil servants on accessibility to e-learning platform. The objective of this paper is to provide a personalized telephone learning model and a prototype application that will enhance the productivity of the visually impaired workers in Government establishments in Nigeria. The model was designed using Unified Modeling Language (UML) diagram. The prototype application was implemented and evaluated. With the proposed model and application, the visually and mobility impaired worker are able to participate in routine staff training and consequently enhances their productivity just like their able-bodied counterparts. The prototype application also serves as an alternative training platform for the able-bodied workers. Future research direction for this study will include biometric authentication of learners accessing the applicatio

    A Phone Learning Model for Enhancing Productivity of Visually Impaired Civil Servants

    Get PDF
    Phone-based learning in civil service is the use of voice technologies to deliver learning and capacity building training services to government employees. The Internet revolution and advancement in Information and Communications Technology (ICT) have given rise to online and remote staff training for the purpose of enhancing workers productivity. The need for civil servants in Nigeria to develop capacity that will enhance knowledge is a key requirement to having competitive advantage in the work place. Existing online learning platforms (such as web-based learning, mobile learning, etc) did not consider the plight of the visually impaired. These platforms provide graphical interfaces that require sight to access. The visually impaired civil servants require auditory access to functionalities that exist in learning management system on the Internet. Thus a gap exist between the able-bodied and visually impaired civil servants on accessibility to e-learning platform. The objective of this paper is to provide a personalized telephone learning model and a prototype application that will enhance the productivity of the visually impaired workers in Government establishments in Nigeria. The model was designed using Unified Modeling Language (UML) diagram. The prototype application was implemented and evaluated. With the proposed model and application, the visually and mobility impaired worker are able to participate in routine staff training and consequently enhances their productivity just like their able-bodied counterparts. The prototype application also serves as an alternative training platform for the able-bodied workers. Future research direction for this study will include biometric authentication of learners accessing the applicatio

    SeMA: A Design Methodology for Building Secure Android Apps

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    UX (user experience) designers visually capture the UX of an app via storyboards. This method is also used in Android app development to conceptualize and design apps. Recently, security has become an integral part of Android app UX because mobile apps are used to perform critical activities such as banking, communication, and health. Therefore, securing user information is imperative in mobile apps. In this context, storyboarding tools offer limited capabilities to capture and reason about security requirements of an app. Consequently, security cannot be baked into the app at design time. Hence, vulnerabilities stemming from design flaws can often occur in apps. To address this concern, in this paper, we propose a storyboard based design methodology to enable the specification and verification of security properties of an Android app at design time.Comment: Updates based on AMobile 2019 review

    The Need to Support of Data Flow Graph Visualization of Forensic Lucid Programs, Forensic Evidence, and their Evaluation by GIPSY

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    Lucid programs are data-flow programs and can be visually represented as data flow graphs (DFGs) and composed visually. Forensic Lucid, a Lucid dialect, is a language to specify and reason about cyberforensic cases. It includes the encoding of the evidence (representing the context of evaluation) and the crime scene modeling in order to validate claims against the model and perform event reconstruction, potentially within large swaths of digital evidence. To aid investigators to model the scene and evaluate it, instead of typing a Forensic Lucid program, we propose to expand the design and implementation of the Lucid DFG programming onto Forensic Lucid case modeling and specification to enhance the usability of the language and the system and its behavior. We briefly discuss the related work on visual programming an DFG modeling in an attempt to define and select one approach or a composition of approaches for Forensic Lucid based on various criteria such as previous implementation, wide use, formal backing in terms of semantics and translation. In the end, we solicit the readers' constructive, opinions, feedback, comments, and recommendations within the context of this short discussion.Comment: 11 pages, 7 figures, index; extended abstract presented at VizSec'10 at http://www.vizsec2010.org/posters ; short paper accepted at PST'1

    Collected notes from the Benchmarks and Metrics Workshop

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    In recent years there has been a proliferation of proposals in the artificial intelligence (AI) literature for integrated agent architectures. Each architecture offers an approach to the general problem of constructing an integrated agent. Unfortunately, the ways in which one architecture might be considered better than another are not always clear. There has been a growing realization that many of the positive and negative aspects of an architecture become apparent only when experimental evaluation is performed and that to progress as a discipline, we must develop rigorous experimental methods. In addition to the intrinsic intellectual interest of experimentation, rigorous performance evaluation of systems is also a crucial practical concern to our research sponsors. DARPA, NASA, and AFOSR (among others) are actively searching for better ways of experimentally evaluating alternative approaches to building intelligent agents. One tool for experimental evaluation involves testing systems on benchmark tasks in order to assess their relative performance. As part of a joint DARPA and NASA funded project, NASA-Ames and Teleos Research are carrying out a research effort to establish a set of benchmark tasks and evaluation metrics by which the performance of agent architectures may be determined. As part of this project, we held a workshop on Benchmarks and Metrics at the NASA Ames Research Center on June 25, 1990. The objective of the workshop was to foster early discussion on this important topic. We did not achieve a consensus, nor did we expect to. Collected here is some of the information that was exchanged at the workshop. Given here is an outline of the workshop, a list of the participants, notes taken on the white-board during open discussions, position papers/notes from some participants, and copies of slides used in the presentations

    GECKA3D: A 3D Game Engine for Commonsense Knowledge Acquisition

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    Commonsense knowledge representation and reasoning is key for tasks such as artificial intelligence and natural language understanding. Since commonsense consists of information that humans take for granted, gathering it is an extremely difficult task. In this paper, we introduce a novel 3D game engine for commonsense knowledge acquisition (GECKA3D) which aims to collect commonsense from game designers through the development of serious games. GECKA3D integrates the potential of serious games and games with a purpose. This provides a platform for the acquisition of re-usable and multi-purpose knowledge, and also enables the development of games that can provide entertainment value and teach players something meaningful about the actual world they live in

    A study on the effect of a web-based teaching module and gender on accounting students’ ethical judgements

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    Accounting educators face the increasingly important task of teaching ethics. Yet, there is little empirical evidence on the effectiveness of different ethics instructional methods on accounting students’ ethical judgements. This study examines whether the ethical decision making of accounting students differs (1) between those instructed through a web-based teaching module and those adopting a more traditional textbook-focused approach, and (2) between gender. A total of 156 students from a second-year financial accounting course participated in the study, with 90 students utilising the web-based module which was designed based on Rest’s (1979) model on ethics development. The other 66 students were instructed through a more traditional teaching approach based on regular class discussions using the ethical problems presented in the textbook. Subsequently, when presented with a whistle-blowing situation, the results of the study suggest that the attitudes and judgements of students instructed through the web-based module were more ethical than those utilising the traditional textbook module. Further, gender was found to impact ethical judgements but only among students who were exposed to the web-based module. The implications of the findings on accounting ethics education are discussed
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