An Agent-Based Approach for a Smart Transport System

This paper presents a proposal for a Smart Transport System which is an application that facilitates the interconnection between people (citizens, tourists) and transport providers (Bus, metro, trains, trams), defining the services that everyone can request or offer. The system has been defined as a virtual organization where agents (representing actors of the transport system) can enter or leave into the system consuming or offering services. Due to the fact that modern urban public transport is increasingly an important service used by citizens in current cities, the proposed system will improve the use of resources while also ensuring time flexible mobility solutions for citizens

Machine Translation for Nko: Tools, Corpora and Baseline Results

Currently, there is no usable machine translation system for Nko, a language spoken by tens of millions of people across multiple West African countries, which holds significant cultural and educational value. To address this issue, we present a set of tools, resources, and baseline results aimed towards the development of usable machine translation systems for Nko and other languages that do not currently have sufficiently large parallel text corpora available. (1) Fria$\parallel$el: A novel collaborative parallel text curation software that incorporates quality control through copyedit-based workflows. (2) Expansion of the FLoRes-200 and NLLB-Seed corpora with 2,009 and 6,193 high-quality Nko translations in parallel with 204 and 40 other languages. (3) nicolingua-0005: A collection of trilingual and bilingual corpora with 130,850 parallel segments and monolingual corpora containing over 3 million Nko words. (4) Baseline bilingual and multilingual neural machine translation results with the best model scoring 30.83 English-Nko chrF++ on FLoRes-devtest

Using Artificial Intelligence to Circumvent the Teacher Shortage in Special Education: A Phenomenological Investigation

The purpose of this hermeneutic phenomenological research study was to understand district technology leaders’ receptivity to employing artificial co-teachers, based on their lived experiences with Artificial Intelligence (AI). Facing a problematic teacher shortage in special education, the Jade County School District was not readily employing available AI technologies such as IBM’s WATSON and MIT Media Lab’s TEGA, to aide in filling the instructional voids caused by special education teacher attrition. Veblen’s theory of technological determinism provided the necessary framework for this study, which focused on how district technology leaders described their willingness or apprehension to employ autonomous machines to independently instruct students with disabilities in the classroom. This research study was carried out in a large public-school district with a high number of special education teacher vacancies. Purposeful sampling was used to recruit 11 district-level technology leaders who were responsible for developing and sharing a vision for how new technology could be employed to support the needs of students. The principal researcher applied hermeneutic phenomenology to interpret data from photo-elicitations, audio-recorded focus groups, and individual interviews

Usability of disaster apps : understanding the perspectives of the public as end-users : a dissertation presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Emergency Management at Massey University, Wellington, New Zealand

Listed in 2020 Dean's List of Exceptional ThesesMultiple smartphone applications (apps) exist that can enhance the public’s resilience to disasters. Despite the capabilities of these apps, they can only be effective if users find them usable. Availability does not automatically translate to usability nor does it guarantee continued usage by the target users. A disaster app will be of little or no value if a user abandons it after the initial download. It is, therefore, essential to understand the users’ perspectives on the usability of disaster apps. In the context of disaster apps, usability entails providing the elements that effectively facilitate users in retrieving critical information, and thus enabling them to make decisions during crises. Establishing good usability for effective systems relies upon focussing on the user whereby technological solutions match the user’s needs and expectations. However, most studies on the usability of disaster context technologies have been conducted with emergency responders, and only a few have investigated the publics’ perspectives as end-users. This doctoral project, written within a ‘PhD-thesis-with-publication’ format, addresses this gap by investigating the usability of disaster apps through the perspectives of the public end-users. The investigation takes an explicitly perceived usability standpoint where the experiences of the end-users are prioritised. Data analysis involved user-centric information to understand the public’s context and the mechanisms of disaster app usability. A mixed methods approach incorporates the qualitative analysis of app store data of 1,405 user reviews from 58 existing disaster apps, the quantitative analysis of 271 survey responses from actual disaster app users, and the qualitative analysis of usability inquiries with 18 members of the public. Insights gathered from this doctoral project highlight that end-users do not anticipate using disaster apps frequently, which poses particular challenges. Furthermore, despite the anticipated low frequency of use, because of the life-safety association of disasters apps, end-users have an expectation that the apps can operate with adequate usability when needed. This doctoral project provides focussed outcomes that consider such user perspectives. First, an app store analysis investigating user reviews identified new usability concerns particular to disaster apps. It highlighted users’ opinion on phone resource usage and relevance of content, among others. More importantly, it defined a new usability factor, app dependability, relating to the life-safety context of disaster apps. App dependability is the degree to which users’ perceive that an app can operate dependably during critical scenarios. Second, the quantitative results from this research have contributed towards producing a usability-continuance model, highlighting the usability factors that affect end-users’ intention to keep or uninstall a disaster app. The key influences for users’ intention to keep disaster apps are: (1) users’ perceptions as to whether the app delivers its function (app utility), (2) whether it does so dependably (app dependability), and (3) whether it presents information that can be easily understood (user-interface output). Subsequently, too much focus on (4) user-interface graphics and (5) user-interface input can encourage users to uninstall apps. Third, the results from the qualitative analysis of the inquiry data provide a basis for developing guidelines for disaster app usability. In the expectation of low level of engagement with disaster app users, the guidelines list recommendations addressing information salience, cognitive load, and trust. This doctoral project provides several contributions to the body of knowledge for usability and disaster apps. It reiterates the importance of investigating the usability of technological products for disasters and showcases the value of user-centric data in understanding usability. It has investigated usability with particular attention to the end-users’ perspectives on the context of disaster apps and, thus, produces a theoretical usability-continuance model to advance disaster app usability research and usability guidelines to encourage responsible design in practice

Bioinspired metaheuristic algorithms for global optimization

This paper presents concise comparison study of newly developed bioinspired algorithms for global optimization problems. Three different metaheuristic techniques, namely Accelerated Particle Swarm Optimization (APSO), Firefly Algorithm (FA), and Grey Wolf Optimizer (GWO) are investigated and implemented in Matlab environment. These methods are compared on four unimodal and multimodal nonlinear functions in order to find global optimum values. Computational results indicate that GWO outperforms other intelligent techniques, and that all aforementioned algorithms can be successfully used for optimization of continuous functions

Experimental Evaluation of Growing and Pruning Hyper Basis Function Neural Networks Trained with Extended Information Filter

In this paper we test Extended Information Filter (EIF) for sequential training of Hyper Basis Function Neural Networks with growing and pruning ability (HBF-GP). The HBF neuron allows different scaling of input dimensions to provide better generalization property when dealing with complex nonlinear problems in engineering practice. The main intuition behind HBF is in generalization of Gaussian type of neuron that applies Mahalanobis-like distance as a distance metrics between input training sample and prototype vector. We exploit concept of neuron’s significance and allow growing and pruning of HBF neurons during sequential learning process. From engineer’s perspective, EIF is attractive for training of neural networks because it allows a designer to have scarce initial knowledge of the system/problem. Extensive experimental study shows that HBF neural network trained with EIF achieves same prediction error and compactness of network topology when compared to EKF, but without the need to know initial state uncertainty, which is its main advantage over EKF

An Industry of Indies: The New Cultural Economy of Digital Game Production

An Industry of Indies builds upon foundational questions concerned with the constitution, operations, changes, disruptions, and borders of the global digital games industry. Although scholars have engaged with the dynamics of the video game industry, few have analyzed the emergence of indie games over the last decade and the impact of these small games on the always already shifting terrain of this industry. During this period, the video game industry has been confronting a wave of changes wrought by continually emerging technologies, player expectations, and a generation of small game developers who have challenged particular industry practices and dogmas, even as they also provide value to the industry’s largest video game publishers and platform holders. An Industry of Indies examines a range of independent, marginal, and alternative digital game production cultures across the globe, from commercial indie games to radical avant-garde games, and delineates the cultural and economic relationship of each to the global economy of digital game production and consumption. This dissertation argues that despite the desire for real subversion amongst various indie development communities, an underlying neoliberal logic drives many of their entrepreneurial business practices. Even as many commercial indie developers distinguish their workplace practices, design approaches, and development ethos from the mainstream, corporate industry, most still rely on the same ideologies of bootstrap individualism and free market politics that undergird the dominant industry. Furthermore, even those developers who distance themselves from the industry, usually accompanied by a feminist and/or Marxist critique of industry practices or output, necessarily have to rely on venture capital funded startup companies like Patreon in order to connect with their fans and earn a living within a capitalist system with which they disagree – a sad irony not lost on them. Within this greater context, the indie developer becomes a point of struggle between notions of the counter-hegemonic creative artist and the idea of the success-driven technology startup company, with the concepts of passion, art, and sustainability suturing the two perspectives together. This project employs a middle-range media industries approach to describe and analyze the operations of indie developers within the global digital games industry, specifically an approach that combines interdisciplinary elements of cultural studies, discourse analysis, political economy, and feminist media studies. That is, this dissertation articulates the organization, operations, and agents of the commercial video game industry, in its largest and smallest forms, in order to describe how independent and alternative development cultures fit within larger systems of capital exchange, from commercial shops to solitary producers. It offers three significant interventions, primarily in the areas of media industries studies and game studies. An Industry of Indies examines indie games not only as alternative art or politics but as cultural products within complex, global ecologies of exchange; it focuses on the industry’s smallest companies rather than its largest corporations; and it interrogates the boundary-policing strategies within media industries, arguing that commonly conceived barriers between amateur and professional media producers are, in fact, fluid and wavering, dependent on constantly shifting discourses and industrial practices, policies, and standards

Semantic location extraction from crowdsourced data

Crowdsourced Data (CSD) has recently received increased attention in many application areas including disaster management. Convenience of production and use, data currency and abundancy are some of the key reasons for attracting this high interest. Conversely, quality issues like incompleteness, credibility and relevancy prevent the direct use of such data in important applications like disaster management. Moreover, location information availability of CSD is problematic as it remains very low in many crowd sourced platforms such as Twitter. Also, this recorded location is mostly related to the mobile device or user location and often does not represent the event location. In CSD, event location is discussed descriptively in the comments in addition to the recorded location (which is generated by means of mobile device's GPS or mobile communication network). This study attempts to semantically extract the CSD location information with the help of an ontological Gazetteer and other available resources. 2011 Queensland flood tweets and Ushahidi Crowd Map data were semantically analysed to extract the location information with the support of Queensland Gazetteer which is converted to an ontological gazetteer and a global gazetteer. Some preliminary results show that the use of ontologies and semantics can improve the accuracy of place name identification of CSD and the process of location information extraction