Correcting and complementing freeway traffic accident data using Mahalanobis distance based outlier detection

Arhivirana je ogromna količina podataka o prometu koji bi se mogli koristiti za dobivanje specifičnih podataka. Međutim, oni se u potpunosti ne koriste zbog nepostojanja točnih podataka o prometu (oznaka). U ovom radu poboljšavamo algoritam zasnovan na Mahalanobis udaljenosti za procjenu promjena toka prometa i otkrivanje nesreća i primjenjujemo ga kod ispravljanja i dopunjavanja informacija o nesreći. Algoritam za otkrivanje outliera (netipičnih vrijednosti) pruža točne podatke o vremenu događanja nesreće, trajanju i smjeru. Razvijamo i sustav s interaktivnim sučeljem korisnika u svrhu ostvarenja ovog postupka. Predlažu se tri načina za manipulaciju podacima. Najprije, za otkrivanje outliera u prometu predlažemo uporabu multi-metričkih podataka o prometu umjesto jedno metričkih. Nadalje, predlažemo praktičnu metodu za organizaciju prometnih podataka i evaluaciju organizacije Mahalanobis udaljenosti. Kao treće, dajemo opis opće metode za modifikaciju algoritama Mahalanobis udaljenosti kako bi se mogli ažurirati.A huge amount of traffic data is archived which can be used in data mining especially supervised learning. However, it is not being fully used due to lack of accurate accident information (labels). In this study, we improve a Mahalanobis distance based algorithm to be able to handle differential data to estimate flow fluctuations and detect accidents and use it to support correcting and complementing accident information. The outlier detection algorithm provides accurate suggestions for accident occurring time, duration and direction. We also develop a system with interactive user interface to realize this procedure. There are three contributions for data handling. Firstly, we propose to use multi-metric traffic data instead of single metric for traffic outlier detection. Secondly, we present a practical method to organise traffic data and to evaluate the organisation for Mahalanobis distance. Thirdly, we describe a general method to modify Mahalanobis distance algorithms to be updatable

Smart specialisation for regional economic transformation

The aim of this paper is to provide a quick yet comprehensive understanding of the nature and logic of smart specialisation as a place-based strategy for economic transformation and development. The origin and characteristics of the smart specialisation approach in the European Union are presented together with the main challenges for a successful implementation. Smart specialisation is about identifying and pursuing sub-sectoral and inter-sectoral activities, which can be explored by existing but also new entrant firms, where technology can facilitate either radical innovation, or the incremental utilisation of existing skills/strengths in new niches, fostering regional and national technology-savvy economic transformation. Stakeholder involvement through an entrepreneurial discovery process is a defining feature of this approach.JRC.J.2-Knowledge for Growt

Quality of Service Aware Data Stream Processing for Highly Dynamic and Scalable Applications

Huge amounts of georeferenced data streams are arriving daily to data stream management systems that are deployed for serving highly scalable and dynamic applications. There are innumerable ways at which those loads can be exploited to gain deep insights in various domains. Decision makers require an interactive visualization of such data in the form of maps and dashboards for decision making and strategic planning. Data streams normally exhibit fluctuation and oscillation in arrival rates and skewness. Those are the two predominant factors that greatly impact the overall quality of service. This requires data stream management systems to be attuned to those factors in addition to the spatial shape of the data that may exaggerate the negative impact of those factors. Current systems do not natively support services with quality guarantees for dynamic scenarios, leaving the handling of those logistics to the user which is challenging and cumbersome. Three workloads are predominant for any data stream, batch processing, scalable storage and stream processing. In this thesis, we have designed a quality of service aware system, SpatialDSMS, that constitutes several subsystems that are covering those loads and any mixed load that results from intermixing them. Most importantly, we natively have incorporated quality of service optimizations for processing avalanches of geo-referenced data streams in highly dynamic application scenarios. This has been achieved transparently on top of the codebases of emerging de facto standard best-in-class representatives, thus relieving the overburdened shoulders of the users in the presentation layer from having to reason about those services. Instead, users express their queries with quality goals and our system optimizers compiles that down into query plans with an embedded quality guarantee and leaves logistic handling to the underlying layers. We have developed standard compliant prototypes for all the subsystems that constitutes SpatialDSMS

Agile Knowledge Management; A Review, Reconceptualization, and Extension to Military Applications

The purpose of this research is to explore the conceptual background of agility in knowledge management, re-conceptualize it and extend it to military applications with a special focus on Counterinsurgency (COIN). An initial qualitative exploration of agility in knowledge management was performed. Three different concepts and their interrelationships were analyzed: (1) knowledge management, (2) agility in operations, and (3) military organizations in the COIN environment. Findings from this initial qualitative analysis were used to inductively redefine, re-conceptualize and extend the concept of Agile Knowledge Management (AKM), as well as, to compare and adapt the AKM concept to the military environment of COIN. An additional qualitative analysis was performed to validate the extended concept of AKM. While this study is mainly focused on AKM in dynamic multinational and joint military environment of COIN, conclusions may be applicable in a broader context. The results of this research can be used by engineering managers and knowledge management practitioners and academics with particular focus on the military environment as foundation for (a) further research and development in agile knowledge management (b) developing customized agile knowledge management education programs and (c) extending the concept of AKM and its application to other environments

An inter-domain supervision framework for collaborative clustering of data with mixed types.

We propose an Inter-Domain Supervision (IDS) clustering framework to discover clusters within diverse data formats, mixed-type attributes and different sources of data. This approach can be used for combined clustering of diverse representations of the data, in particular where data comes from different sources, some of which may be unreliable or uncertain, or for exploiting optional external concept set labels to guide the clustering of the main data set in its original domain. We additionally take into account possible incompatibilities in the data via an automated inter-domain compatibility analysis. Our results in clustering real data sets with mixed numerical, categorical, visual and text attributes show that the proposed IDS clustering framework gives improved clustering results compared to conventional methods, over a wide range of parameters. Thus the automatically extracted knowledge, in the form of seeds or constraints, obtained from clustering one domain, can provide additional knowledge to guide the clustering in another domain. Additional empirical evaluations further show that our approach, especially when using selective mutual guidance between domains, outperforms common baselines such as clustering either domain on its own or clustering all domains converted to a single target domain. Our approach also outperforms other specialized multiple clustering methods, such as the fully independent ensemble clustering and the tightly coupled multiview clustering, after they were adapted to the task of clustering mixed data. Finally, we present a real life application of our IDS approach to the cluster-based automated image annotation problem and present evaluation results on a benchmark data set, consisting of images described with their visual content along with noisy text descriptions, generated by users on the social media sharing website, Flickr

Strategies for Increased Productivity Through Control of Process Constraints

In Nigeria, manufacturing businesses play a vital role in the industrial growth of the nation and have many dynamic benefits crucial for the growth of a sustainable economy. The manufacturing sector has added substantially to the gross domestic products of many countries. Nonetheless, 50% of manufacturing firms in Nigeria experience a decline in production capacity utilization and profitability because of inefficient production processes. The purpose of this qualitative multiple case study was to explore strategies leaders of manufacturing firms in Nigeria use to support efficient manufacturing operations. The theory of constraints served as the conceptual framework for this study. Eight participants from two manufacturing firms in Nigeria who had strategies to support efficient manufacturing operations participated in this study. Data sources included semistructured interviews and the review of organizational documents consisting of corporate quality policy, quality objectives, and mission statements. Analysis involved data compilation, data coding by breaking it down into categories, and reassembling the data into emergent themes. Member checking and methodological triangulation strengthened the credibility of the findings. Four major themes emerged: strategic planning, continuous process improvement, strategic equipment maintenance, and strategic capacity expansion. The findings from this research might provide the basis for developing an advanced manufacturing practice for some Nigerian manufacturing firms that could contribute to social change by improving production efficiency, local consumption, and sustainable economic growth

Trouble in paradise : contradictions in platform capitalism and the production of surplus by Airbnb hosts in regional tourist towns : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Sociology at Massey University, Albany, New Zealand

A tendency toward crisis in social reproduction characterizes digital capitalism. Increasingly, the economic system shows itself unable to generate subjectivities and social processes for addressing the physical and psychical need required for its reproduction. Emblematic of that contradiction is the individualism of digital capitalism which compels people to commodify themselves beyond the ‘normal’ state of abstracted labour power associated with capitalism, to become ‘entrepreneurs of the self’. An extreme form of commodification of the self is evident in a new form of capitalism termed ‘platform capitalism’ which manifests through organizations such as Airbnb. Like the notion of the ‘entrepreneur of the self’, this kind of commodified self is increasingly too thin and too instrumental to be self-sustaining. The commodification of people and of private spaces result in shifts of subjectivity as a response to the production of surplus-meaning and surplus-enjoyment and indicates capture of a new sphere for capitalist activities at the expense of social reproduction. This research explores the construction of Airbnb hosts’ subjectivities across four tourist towns in New Zealand (Picton, Wanaka, Paihia and Whitianga). Placed within the context of global capitalism, tourism is a major economic contributor to the New Zealand economy, estimated at $24 billion annually. Concurrently, regional areas of New Zealand are experiencing challenges relating to economic stagnation, ageing populations and changes to population numbers. Common across people living in these regional towns is a political imperative to commodify their life-worlds for the tourist market. Increasingly, the mechanisms that are synonymous with platform capitalist ventures, of Airbnb in this instance, are becoming significant means through which, the realization of this political imperative occurs. Using a qualitative research framework, in-depth semi-structured interviews were conducted with 28 Airbnb hosts, then analyzed using an inductive and iterative thematic analysis. The emerging themes presented here are commodification, biopolitics and the intensification of time and space. Collectively, the themes demonstrate how the contradictions of surplus and of social reproduction manifest within the digital platform of Airbnb. The research informs issues and debates in contemporary theory on capital’s tendency towards crises of social reproduction

Pacific Symposium on Biocomputing 2023

The Pacific Symposium on Biocomputing (PSB) 2023 is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. Presentations are rigorously peer reviewed and are published in an archival proceedings volume. PSB 2023 will be held on January 3-7, 2023 in Kohala Coast, Hawaii. Tutorials and workshops will be offered prior to the start of the conference.PSB 2023 will bring together top researchers from the US, the Asian Pacific nations, and around the world to exchange research results and address open issues in all aspects of computational biology. It is a forum for the presentation of work in databases, algorithms, interfaces, visualization, modeling, and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology.The PSB has been designed to be responsive to the need for critical mass in sub-disciplines within biocomputing. For that reason, it is the only meeting whose sessions are defined dynamically each year in response to specific proposals. PSB sessions are organized by leaders of research in biocomputing's 'hot topics.' In this way, the meeting provides an early forum for serious examination of emerging methods and approaches in this rapidly changing field

Composing abstractions? General musical behaviours in five new works for humans and computer

This written thesis supports a portfolio of composition work. This portfolio was composed to study ‘music systems’ - things that I intentionally design in order to make music happen in future. As a composer of works for computers and humans, music technology is an inherent requirement of my practice. However, I have noticed a tendency to spend a lot of time working on the technological components of these systems, but little time making music. It is easy to conflate the task of composing music with the process of using technology. I argue that this is a matter of ‘analytical framing’. A purely technological framing of what music is, and how it can be worked on, is clearly reductive. To present experiment with different framings, I identify a set of systems that were used to compose my portfolio and ask what they are made of. I produce technical, temporal, communicative, social and ethical answers to this question; each of these new analytical framings respectively unpacked in a specific chapter of this thesis. This reveals that my compositional practice, as a total structure made manifest through the content of my portfolio, can be framed as a complex music system in itself. Crucially, this system is populated by general musical behaviours that are consistent across multiple different framings of what my practice is. My primary argument is that interesting things happen when these abstract behaviours are identified, sorted and instantiated into new works of music. As a contribution to contemporary music discourse, my portfolio documents a novel set of approaches to working with music and systems. From a theoretical standpoint, my multi-framed definition of ‘music system’ helps sidestep a commonly encountered problem in electronic music studies: an over-fixation on technicity which elides social and cultural context. Moreover, this project helps ingrain a practice-orientated understanding of music systems design, by concluding that music systems exist most significantly (i.e. most practically) as iterative, playful and emergent processes of modulating sound perception through time