A comparison of several techniques for designing controllers of uncertain dynamic systems

In recent years, a number of techniques have been developed for the design of linear, constant gain feedback controllers for systems with imprecisely Known parameters. In this paper, several of these techniques are compared in the context of the design of a lateral autopilot for a rudderless remotely piloted vehicle with uncertain aerodynamic coefficients. Properties of the design techniques on which the comparison is based include closed-loop system performance at nominal and off-nominal parameter values, computational cost and complexity, ease of implementation in a real system, and generality of the parameter uncertainty which can be dealt with

Tropical vertical greenery systems: Irrigation systems, biophysical characteristics, and influential criteria

Recent studies on vertical greenery systems (VGS) mainly focus on thermal performance, acoustics effects, energy savings and environmental sustainability. There are very few studies on tropical VGS irrigation systems, plants’ characteristics, and favorable installation locations, indicating that architectural professionals may lack sufficient guidance to support their design work. Through two descriptive case studies and a questionnaire survey of VGS-related professionals including gardeners, mechanical and electrical engineers, consultants, contractors, and developers, this research developed a knowledgebase for tropical vertical greenery systems irrigation systems and determined the suitability of different types of vertical greenery systems according to the biophysical characteristics of plants. The suitability for various plant characteristics has been identified to help potential users while considering vertical greenery systems irrigation systems. Suitable locations, orientations and microclimatic conditions for vertical greenery systems irrigation systems to prevent system failure have been determined. Further research focused on establishing the technical requirements for irrigation scheduling is recommended to improve the application efficiency

Design Perspective on the Role of Advanced Bots for Self-Guided Learning

Virtual worlds are rapidly gaining acceptance in educational settings; with bots play an important role in these environments to help learners. Authentic learning can be significantly supported by bots to help self-guided learning in authentic tasks. in this paper, we investigate what is stopping educators from making more use of bots as a valuable resource and how these barriers can be overcome. This exploratory research uses interviews with six educators, who use educational bots. We show that while the experts have 'big plans' for bot use, the current educational implementations are 'low-level' and restrictive in their application. There is further confusion about appropriate pedagogical models and how to use them effectively as more than 'prompters' or 'extras'. While creation- and control-technologies are advancing, allowing use of bots as a 'hard technology' to guide learners through routine procedures; there is a lack of resources for automation as intelligence technologies are slower to develop and may required future partnerships with external parties before they are available useable by general educators

Think Exogenous to Excel: Alternative Supply Chain Data to Improve Transparency and Decisions

Efficient decisions along the supply chain have traditionally demanded sophisticated information sharing processes. Even with decades of research on theoretical and practical developments on integrating systems and stakeholders, in practice, we still seem to struggle to achieve full transparency and mitigate inefficiency challenges. We explore the emerging sentiment analysis technique to augment sales and operations planning (S&OP) with currently unavailable exogenous information. Even though sentiment analysis has gained traction, a comprehensive application in supply chains has not yet been attempted. Relevant topics are reviewed to allow an examination of the key relationships in a process framework, grounded in dual-process and bullwhip effect theory. Our proposed conceptual framework extends our conception of sentiment analysis integration to improve supply chain decisions and performance. The framework addresses managers interested in developing additional analytical capabilities and researchers to initiate further empirical research on the potential held by sentiment analysis in supply chain research

Design and Construction of Semantic Document Networks Using Concept Extraction

Processing of unstructured documents according to their content is required in many disciplines; e.g., machine translation, text analysis and mining, and information extraction and retrieval. Whilst research in fields like text analysis, conceptualisation, or design of semantic networks progressed crucially over the last years, we still observe gaps between state-of-the-art algorithms to extract concepts from documents and how these concepts are linked effective and efficiently. This paper proposes a framework to store processed documents in a specialised semantic network database to enhance retrieval and analysis of common concepts in documents. We apply natural language reduction to calculate semantic cores for the concept-based indexing of stored documents. The developed prototype demonstrates an advanced document storage as well as a fast (semantical) retrieval of documents based on given key concepts

Expanding Sales and Operations Planning using Sentiment Analysis: Demand and Sales Clarity from Social Media

We outline the use of sentiment analysis as a tool for demand planning in sales and operations planning (S&OP). First, we explain how S&OP functions and the reliance on cooperation or collaboration with other firms to gain information. We introduce sentiment analysis and show its value in determining marketplace-changes which feed into supply chains. We show how sentiment analysis supports data acquisition independent of other firms in the supply chain; incorporated into S&OP, these data can support preparation for changing requirements. While demonstrated in marketing, this concept remains unproven in supply chain research. We believe this is the first assertion and examination of how sentiment analysis can support effective S&OP but further empirical research is required to validate this concept

Experimental study on consumer-technology supported authentic immersion in virtual worlds for education and vocational training

Despite significant and rapid technology improvements, educators have frequently failed to make use of the new opportunities to create more authentic learning scenarios. Virtual worlds offer an attractive proposition to create 3D representations of real business environments to provide an authentic learning activity for higher education students to take part in. However, the controls and displays are still clunky and unnatural, reducing the opportunity for students to immerse themselves in the event and focus on experiential learning. To overcome this challenge we examine the role of using a headset display that allows the user to change perspective with a flick of the head, improving their ability to ‘feel’ part of the environment, and thus increase their immersion in the activities that they are engaged in through more realistic control and improved perspective in the virtual environment. A series of experiments are conducted comparing the technology to established technologies and the level of control exerted by the learner (e.g., they either ‘control’ or they ‘passively observe’ as someone else controls). These experiments provide evidence that consumer-technology can improve immersion and equip educators with an affordable instrument to present classes that learners ‘take more seriously’

Information System Articulated Logistics and Supply Chains and their Spatial-Temporal Modelling and Management

The logistics and supply chains have affected worldwide businesses, particularly in pandemic locations and periods, unsettling supply and demand pursuits. Logistics of global markets have been irregular, with poorly aligned superstore outlets in different geographies. Businesses and their alliances have affected spatial-temporal dimensions. The research explores the significance of Information System (IS) articulations and how IS artefacts can motivate connecting global companies and boost market values. The study aims to improve the Logistics and Supply Chains (LSC) between companies and organizations through evaluable IS artefacts in industry scenarios. The use and reuse of IS articulations are investigated in spatial-temporal dimensions for LSC knowledge management. Further, the IS artefacts are assessed through the logistics performance in geographic dimensions using the Attribute Journey Mapping and Modelling (AJMM) method. The ability to track and trace the supply chain consignments is inferred proportional to attributes of quality of trade and transport systems

On Big Data guided Unconventional Digital Ecosystems and their Knowledge Management

Establishing the reservoir connections is paramount in exploration and exploitation of unconventional petroleum systems and their reservoirs. In Big Data scale, multiple petroleum systems hold volumes and varieties of data sources. The connectivity between petroleum reservoirs and their existence in a single petroleum ecosystem is often ambiguously interpreted. They are heterogeneous and unstructured in multiple domains. They need better data integration methods to interpret the interplay between elements and processes of petroleum systems. Largescale infrastructure is needed to build data relationships between different petroleum systems. The purpose of the research is to establish the connectivity between petroleum systems through resource data management and visual analytics. We articulate a Design Science Information System (DSIS) approach, bringing various artefacts together from multiple domains of petroleum provinces. The DSIS emerges as a knowledge-based digital ecosystem innovation, justifying its need, connecting geographically controlled petroleum systems and building knowledge of oil and gas prospects

On Developing Sustainable Digital Ecosystems and their Spatial-temporal Knowledge Management

The research aims to assess the sustainment of multiple ecosystems with viable and adaptable models. We propose an Information System (IS) modelling approach and examine the sustainment between ecosystems through connectable multidimensional IS artefacts. For example, humans survive in healthy and hassle-free environments for long-term economic benefits. We conceptualize human, healthcare, and environmental ecosystems are connectable, and the interconnectivity depends on how the ecologies are supportive together and with each other. The ecosystems emerge and grow with data heterogeneity challenges, which can disorganize ecological connectivity, impeding the implementation of resilient digital ecosystems. The development of multidimensional repositories is added motivation to explore connectivity, for which Attribute Journey Mapping and Modelling (AJMM) method is sought. Map views are computed to successfully interpret and establish connectivity, including coherency between attributes of multiple digital ecosystems. Besides, Big Data has changed the ecological research direction with which the coexistence between human-healthcare-environment ecosystems is assessed