Intents-based Service Discovery and Integration

With the proliferation of Web services, when developing a new application, it makes sense to seek and leverage existing Web services rather than implementing the corresponding components from scratch. Therefore, significant research efforts have been devoted to the techniques for service discovery and integration. However, most of the existing techniques are based on the ternary participant classification of the Web service architecture which only takes into consideration the involvement of service providers, service brokers, and application developers. The activities of application end users are usually ignored. This thesis presents an Intents-based service discovery and integration approach at the conceptual level inspired by two industrial protocols: Android Intents and Web Intents. The proposed approach is characterized by allowing application end users to participate in the process of service seeking. Instead of directly binding with remote services, application developers can set an intent which semantically represents their service goal. An Intents user agent can resolve the intent and generate a list of candidate services. Then application end users can choose a service as the ultimate working service. This thesis classifies intents into explicit intents, authoritative intents, and naïve intents, and examines in depth the issue of naïve intent resolution analytically and empirically. Based on the empirical analysis, an adaptive intent resolution approach is devised. This thesis also presents a design for the Intents user agent and demonstrates its proof-of-concept prototype. Finally, Intents and the Intents user agent are applied to integrate Web applications and native applications on mobile devices

Are black friday deals worth it? Mining twitter users' sentiment and behavior response

The Black Friday event has become a global opportunity for marketing and companies’ strategies aimed at increasing sales. The present study aims to understand consumer behavior through the analysis of user-generated content (UGC) on social media with respect to the Black Friday 2018 offers published by the 23 largest technology companies in Spain. To this end, we analyzed Twitter-based UGC about companies’ offers using a three-step data text mining process. First, a Latent Dirichlet Allocation Model (LDA) was used to divide the sample into topics related to Black Friday. In the next step, sentiment analysis (SA) using Python was carried out to determine the feelings towards the identified topics and offers published by the companies on Twitter. Thirdly and finally, a data-text mining process called textual analysis (TA) was performed to identify insights that could help companies to improve their promotion and marketing strategies as well as to better understand the customer behavior on social media. The results show that consumers had positive perceptions of such topics as exclusive promotions (EP) and smartphones (SM); by contrast, topics such as fraud (FA), insults and noise (IN), and customer support (CS) were negatively perceived by customers. Based on these results, we offer guidelines to practitioners to improve their social media communication. Our results also have theoretical implications that can promote further research in this area

MLaaS: A Cloud System for Mobile Micro Learning in MOOC

Mobile learning in massive open online course (MOOC) differs evidently from its traditional ways as it relies more on collaboration and becomes fragmented. We introduce a cloud-based system which can organize learners into a better teamwork context and customize micro learning resources in order to meet personal demands in real time. Particularly, a smart micro learning environment can be built by a newly designed SaaS, in which educational data mining techniques are mainly employed to understand learners' behaviors and recognize learning resource features

The Urban CoCreation Lab—An Integrated Platform for Remote and Simultaneous Collaborative Urban Planning and Design through Web-Based Desktop 3D Modeling, Head-Mounted Virtual Reality and Mobile Augmented Reality: Prototyping a Minimum Viable Product and Developing Specifications for a Minimum Marketable Product

Both policy and research highlight the importance of diverse stakeholder input in urban development processes but visualizing future built environments and creating two-way design communication for non-expert stakeholders are challenging. The present study develops an intuitive and simplified 3D modeling platform that integrates web-based desktop, virtual reality and mobile augmented reality technologies for remote simultaneous urban design collaboration. Through iterative prototyping, based on two series of workshops with stakeholders, the study resulted in such an integrated platform as a minimum viable product as well as specifications for a minimum marketable product to be used in real projects. Further study is required to evaluate the minimum level of detail in the 3D modeling necessary for good perception of scale and environmental impact simulation

Negotiation environment to support enterprise interoperability sustainability

Dissertation to obtain the Master degree in Electrical Engineering and Computer ScienceSpecialized and diversified global markets are facing a competitiveness that keeps pushing enterprises to abandon their traditional product centrism, where basically it is enough to concentrate their efforts in very narrow specialization fields and change their methods of work relying on networks of other providers that are able to fulfill their needs towards the development of complete solutions. These new methods of work, regarding the rapid change in markets and business organizations, requires new interoperability demands and complexity levels, from connection and syntax-oriented exchanges to semantic and model-oriented knowledge, which becomes very difficult for enterprises to cope with the pace of change. This dissertation proposes the implementation of a framework, based on agents and rules, to achieve solid and stable integration of solutions, via the use of a strong and formal negotiation mechanism, which will be the basis for increasing the enterprise interoperability in the supply chain for the development of solutions.European Commission through the funding of the FP7 ENSEMBLE, UNITE, MSEE and IMAGINE project

A Systematic Review of Data-Driven Attack Detection Trends in IoT

The Internet of Things is perhaps a concept that the world cannot be imagined without today, having become intertwined in our everyday lives in the domestic, corporate and industrial spheres. However, irrespective of the convenience, ease and connectivity provided by the Internet of Things, the security issues and attacks faced by this technological framework are equally alarming and undeniable. In order to address these various security issues, researchers race against evolving technology, trends and attacker expertise. Though much work has been carried out on network security to date, it is still seen to be lagging in the field of Internet of Things networks. This study surveys the latest trends used in security measures for threat detection, primarily focusing on the machine learning and deep learning techniques applied to Internet of Things datasets. It aims to provide an overview of the IoT datasets available today, trends in machine learning and deep learning usage, and the efficiencies of these algorithms on a variety of relevant datasets. The results of this comprehensive survey can serve as a guide and resource for identifying the various datasets, experiments carried out and future research directions in this field

An adjusted material flow cost accounting framework for process waste-reduction decisions in the South African Brewery industry

While contemporary environmental problems arise partly from increased industrial activities resulting in waste creation, the continued extraction and depletion of earth’s natural resources by organisations to meet consumers’ demand have led to unsustainable business practices (Jennings & Zandbergen 1995). Moreover, reversing the negative environmental impact caused by unsustainable business practices is the responsibility of the organisations whose activities cause harm to the environment (Ahuja & Khamba 2008). More importantly, managers require adequate and accurate financial and non-financial information on their unsustainable business practices to successfully manage both internal and external environmental effects of their actions (Schaltegger & Burritt 2000). But the lack of contemporary management accounting tools to capture waste information in the brewery process reduces the chance to improve waste-reduction decisions while opportunities for cost savings are also lost. Admittedly, Gale (2006:1231) argues that conventional management accounting Systems (MASs) do not have the ability to adequately monitor the increasing material costs and overheads in production processes with sufficient transparency. Nevertheless, this inability to provide adequate process waste information may likely limit organisations’ effort to implement and achieve desired waste-reduction strategies. As a result, it is imperative to integrate both physical and monetary waste information for sound decision-making. The main objective of this study is to adopt and adjust the existing MFCA framework to support and improve on managers’ process waste-reduction decisions in the South African brewery industry. In order to achieve this main objective, the study: • examines the extent to which conventional MASs provides process waste information to support waste-reduction decisions in a micro-brewery (Hope Brewery) and a large brewery (SAB Ltd); • assesses the impact of insufficient process waste information as provided by the conventional MASs on brewery waste-reduction decisions in a micro-brewery (Hope Brewery) and a large brewery (SAB Ltd); and • adjusts the existing MFCA framework to include waste categories subsumed or neglected in the provision of waste information to improve brewery waste-reduction decisions. vi The study adopted an exploratory multiple case study approach by means of in-depth interviews and a pilot study in two breweries- a micro-brewery and a large brewery to achieve the study objectives. Findings revealed that, while the use of technology is essential to reduce brewery process waste, there is lack of appropriate waste-capturing management accounting tool in both organisations. Besides it is essential for organisations to adopt appropriate management accounting tool to capture waste-related information for improved waste-reduction decisions and selection of appropriate waste management strategy. The study therefore suggests the adoption of an adjusted MFCA framework for a more robust approach to improve waste-reduction decisions since ‘what cannot be measured cannot be managed’.Management AccountingD. Comm. (Management Accounting