Centralized Algorithms Based on Clustering with Self-tuning of Parameters for Cooperative Target Observation

Clustering on target positions is a class of centralized algorithms used to calculate the surveillance robots' displacements in the Cooperative Target Observation (CTO) problem. This work proposes and evaluates Fuzzy C-means (FCM) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) with K-means (DBSk) based self-tuning clustering centralized algorithms for the CTO problem and compares its performances with that of K-means. Two random motion patterns are adopted for the targets: in free space or on a grid. As a contribution, the work allows identifying ranges of problem configuration parameters in which each algorithm shows the highest average performance. As a first conclusion, in the challenging situation in which the relative speed of the targets is high, and the relative sensor range of the surveillance is low, for which the existing algorithms present a substantial drop in performance, the FCM algorithm proposed outperforms the others. Finally, the DBSk algorithm adapts very well in low execution frequency, showing promising results in this challenging situation

Thermal comfort based fuzzy logic control

Most heating, ventilation and air conditioning (HVAC) control systems are considered as temperature control problems. In this work, the predicted mean vote (PMV) is used to control the indoor temperature of a space by setting it at a point where the PMV index becomes zero and the predicted percentage of persons dissatisfied (PPD) achieves a maximum threshold of 5%. This is achieved through the use of a fuzzy logic controller that takes into account a range of human comfort criteria in the formulation of the control action that should be applied to the heating system to bring the space to comfort conditions. The resulting controller is free of the set up and tuning problems that hinder conventional HVAC controllers. Simulation results show that the proposed control strategy makes it possible to maximize the indoor thermal comfort and, correspondingly, a reduction in energy use of 20% was obtained for a typical 7-day winter period when compared with conventional control

Decision support for build-to-order supply chain management through multiobjective optimization

This paper aims to identify the gaps in decision-making support based on multiobjective optimization for build-to-order supply chain management (BTOSCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting multiobjective optimization (MOO) techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted and future research directions to better exploit the decision support capabilities of MOO are proposed

Decision support for build-to-order supply chain management through multiobjective optimization

This is the post-print version of the final paper published in International Journal of Production Economics. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2010 Elsevier B.V.This paper aims to identify the gaps in decision-making support based on multiobjective optimization (MOO) for build-to-order supply chain management (BTO-SCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting MOO techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted. Future research directions to better exploit the decision support capabilities of MOO are proposed. These include: reformulation of the extant optimization models with a MOO perspective, development of decision supports for interfaces not involving manufacturers, development of scenarios around service-based objectives, development of efficient solution tools, considering the interests of each supply chain party as a separate objective to account for fair treatment of their requirements, and applying the existing methodologies on real-life data sets.Brunel Research Initiative and Enterprise Fund (BRIEF

How to transfer discontinuous technology into radical innovation: Some evidence from three nanotech cases

In this paper the focus is on the strategy formulation processes, specifically supportive methods and structures, which address various managerial issues concerning discontinuous technologies and radical innovation in the early phase of strategic decision-making. In three in-depth case studies how companies proceeded with discontinuous technology and radical innovation ideas in strategy formulation was investigated ex-post. Based on literature and the analysis from the cases nine propositions are suggested for the design of an idealized strategy formulation process model for the simultaneous and differentiated strategic management of radical innovation and incremental innovation. The propositions are transformed into a visualized process model showing the interaction and arrangement of the latter. --discontinuous technology,radical innovation,strategic planning

Music information retrieval: conceptuel framework, annotation and user behaviour

Understanding music is a process both based on and influenced by the knowledge and experience of the listener. Although content-based music retrieval has been given increasing attention in recent years, much of the research still focuses on bottom-up retrieval techniques. In order to make a music information retrieval system appealing and useful to the user, more effort should be spent on constructing systems that both operate directly on the encoding of the physical energy of music and are flexible with respect to users’ experiences. This thesis is based on a user-centred approach, taking into account the mutual relationship between music as an acoustic phenomenon and as an expressive phenomenon. The issues it addresses are: the lack of a conceptual framework, the shortage of annotated musical audio databases, the lack of understanding of the behaviour of system users and shortage of user-dependent knowledge with respect to high-level features of music. In the theoretical part of this thesis, a conceptual framework for content-based music information retrieval is defined. The proposed conceptual framework - the first of its kind - is conceived as a coordinating structure between the automatic description of low-level music content, and the description of high-level content by the system users. A general framework for the manual annotation of musical audio is outlined as well. A new methodology for the manual annotation of musical audio is introduced and tested in case studies. The results from these studies show that manually annotated music files can be of great help in the development of accurate analysis tools for music information retrieval. Empirical investigation is the foundation on which the aforementioned theoretical framework is built. Two elaborate studies involving different experimental issues are presented. In the first study, elements of signification related to spontaneous user behaviour are clarified. In the second study, a global profile of music information retrieval system users is given and their description of high-level content is discussed. This study has uncovered relationships between the users’ demographical background and their perception of expressive and structural features of music. Such a multi-level approach is exceptional as it included a large sample of the population of real users of interactive music systems. Tests have shown that the findings of this study are representative of the targeted population. Finally, the multi-purpose material provided by the theoretical background and the results from empirical investigations are put into practice in three music information retrieval applications: a prototype of a user interface based on a taxonomy, an annotated database of experimental findings and a prototype semantic user recommender system. Results are presented and discussed for all methods used. They show that, if reliably generated, the use of knowledge on users can significantly improve the quality of music content analysis. This thesis demonstrates that an informed knowledge of human approaches to music information retrieval provides valuable insights, which may be of particular assistance in the development of user-friendly, content-based access to digital music collections

Mitigating security breaches through insurance: Logit and Probit models for quantifying e-risk

The common e-threats deterring ecommerce are identity theft, hacking, virus attack, graffiti, phishing, Denial of Service (DoS), sabotage by disgruntled employees, loss of laptop, financial fraud and telecom driven frauds. These discourage users from online transactions. Organizations spend millions of dollars to implement the latest perimeter and core security technologies, to deter malicious attackers and to ensure confidentiality, integrity and availability of data. Yet, security breaches are common. It results in loss of opportunity cost, market capitalization and brand equity for organizations. We propose e-risk insurance as a strategy to supplement the security technologies, and to mitigate these financial losses. In this paper, we propose two generalized linear models (GLM) namely Logit and Probit for quantification of the probability of an e-threat, using CSI/FBI data. We also compute the expected loss amount for organizations using collective risk model. Based on it, we ascertain the net premium to be accrued to the insurance companies

Generic system architecture for context-aware, distributed recommendation

In the existing literature on recommender systems, it is difficult to find an architecture for large-scale implementation. Often, the architectures proposed in papers are specific to an algorithm implementation or a domain. Thus, there is no clear architectural starting point for a new recommender system. This paper presents an architecture blueprint for a context-aware recommender system that provides scalability, availability, and security for its users. The architecture also contributes the dynamic ability to switch between single-device (offline), client-server (online), and fully distributed implementations. From this blueprint, a new recommender system could be built with minimal design and implementation effort regardless of the application.Electrical and Computer Engineerin

Beyond product architecture: Division of labour and competence accumulation in complex product development

This paper considers the trade-off between leveraging external sources of innovation by outsourcing design and engineering activities and the ability to develop internal product development competences. The trade-off arises because the division of labor within and across firms' boundaries has a crucial role in shaping competence development processes, especially because the division of labor also influences opportunities for learning by doing. In new product development projects, learning by doing appears to be both a key determinant of competence development and a difficult-to-substitute form of learning. While the division of development tasks is often considered as guided by product architecture, we show that by decoupling the decisions concerning the product architecture and the allocation of development tasks, firms can realize the benefits of outsourcing such tasks while developing new internal competences. Drawing on a longitudinal case study in the automotive industry, we also identify a new organizational lever for shaping competence development paths and for designing firm boundaries. This lever consists in alternating different task allocation schemes over time for different types of development projects. We show why this is a novel solution, what its underlying logic is, and how it enables alleviating the trade-off between the benefits of leveraging external sources of innovation and the opportunities for competence development provided by in-house design and engineering. We discuss implications for theories of organizational boundary design and innovation management.innovation management; organizational boundaries; outsourcing; product architecture; modularity; new product development; template process; automotive industry; Fiat