@inproceedings{17370, abstract = {{ We consider a natural extension to the metric uncapacitated Facility Location Problem (FLP) in which requests ask for different commodities out of a finite set \( S \) of commodities. Ravi and Sinha (SODA 2004) introduced the model as the \emph{Multi-Commodity Facility Location Problem} (MFLP) and considered it an offline optimization problem. The model itself is similar to the FLP: i.e., requests are located at points of a finite metric space and the task of an algorithm is to construct facilities and assign requests to facilities while minimizing the construction cost and the sum over all assignment distances. In addition, requests and facilities are heterogeneous; they request or offer multiple commodities out of $S$. A request has to be connected to a set of facilities jointly offering the commodities demanded by it. In comparison to the FLP, an algorithm has to decide not only if and where to place facilities, but also which commodities to offer at each. To the best of our knowledge we are the first to study the problem in its online variant in which requests, their positions and their commodities are not known beforehand but revealed over time. We present results regarding the competitive ratio. On the one hand, we show that heterogeneity influences the competitive ratio by developing a lower bound on the competitive ratio for any randomized online algorithm of \( \Omega ( \sqrt{|S|} + \frac{\log n}{\log \log n} ) \) that already holds for simple line metrics. Here, \( n \) is the number of requests. On the other side, we establish a deterministic \( \mathcal{O}(\sqrt{|S|} \cdot \log n) \)-competitive algorithm and a randomized \( \mathcal{O}(\sqrt{|S|} \cdot \frac{\log n}{\log \log n} ) \)-competitive algorithm. Further, we show that when considering a more special class of cost functions for the construction cost of a facility, the competitive ratio decreases given by our deterministic algorithm depending on the function.}}, author = {{Castenow, Jannik and Feldkord, Björn and Knollmann, Till and Malatyali, Manuel and Meyer auf der Heide, Friedhelm}}, booktitle = {{Proceedings of the 32nd ACM Symposium on Parallelism in Algorithms and Architectures}}, isbn = {{9781450369350}}, keywords = {{Online Multi-Commodity Facility Location, Competitive Ratio, Online Optimization, Facility Location Problem}}, title = {{{The Online Multi-Commodity Facility Location Problem}}}, doi = {{10.1145/3350755.3400281}}, year = {{2020}}, } @inproceedings{16218, abstract = {{Despite recent progress in orchestration of Virtual Network Functions (VNFs) and in multi-technology SDN connectivity, the automated provisioning of end-to-end network services composed of virtual functions deployed across distributed compute locations remains an open challenge. This problem is especially relevant to support the deployment of future 5G networks, comprising virtual access and core network functions connected through a potentially multi-domain transport network. In this paper, we present and demonstrate the 5GOS, a lightweight end-to-end orchestration framework that enables the automated provisioning of virtual radio access network services. Using an experimental multi-domain testbed we demonstrate that the 5GOS can provision multi-domain virtual Wi-Fi and LTE services in less than three minutes.}}, author = {{Camps-Mur, Daniel and Canellas, Ferran and Machwe, Azahar and Paracuellos, Jorge and Choumas, Kostas and Giatsios, Dimitris and Korakis, Thanasis and Razzaghi Kouchaksaraei, Hadi}}, booktitle = {{the 6th IEEE International Conference on Network Softwarization (IEEE NetSoft 2020)}}, keywords = {{Orchestration, multi-domain, cellular network virtualization, SDN, 5G}}, location = {{Ghent, Belgium}}, title = {{{5GOS: Demonstrating multi-domain orchestration of end-to-end virtual RAN services}}}, year = {{2020}}, } @inproceedings{48845, abstract = {{In practice, e.g. in delivery and service scenarios, Vehicle-Routing-Problems (VRPs) often imply repeated decision making on dynamic customer requests. As in classical VRPs, tours have to be planned short while the number of serviced customers has to be maximized at the same time resulting in a multi-objective problem. Beyond that, however, dynamic requests lead to the need for re-planning of not yet realized tour parts, while already realized tour parts are irreversible. In this paper we study this type of bi-objective dynamic VRP including sequential decision making and concurrent realization of decisions. We adopt a recently proposed Dynamic Evolutionary Multi-Objective Algorithm (DEMOA) for a related VRP problem and extend it to the more realistic (here considered) scenario of multiple vehicles. We empirically show that our DEMOA is competitive with a multi-vehicle offline and clairvoyant variant of the proposed DEMOA as well as with the dynamic single-vehicle approach proposed earlier.}}, author = {{Bossek, Jakob and Grimme, Christian and Trautmann, Heike}}, booktitle = {{Proceedings of the Genetic and Evolutionary Computation Conference}}, isbn = {{978-1-4503-7128-5}}, keywords = {{decision making, dynamic optimization, evolutionary algorithms, multi-objective optimization, vehicle routing}}, pages = {{166–174}}, publisher = {{Association for Computing Machinery}}, title = {{{Dynamic Bi-Objective Routing of Multiple Vehicles}}}, doi = {{10.1145/3377930.3390146}}, year = {{2020}}, } @article{48848, abstract = {{We build upon a recently proposed multi-objective view onto performance measurement of single-objective stochastic solvers. The trade-off between the fraction of failed runs and the mean runtime of successful runs \textendash both to be minimized \textendash is directly analyzed based on a study on algorithm selection of inexact state-of-the-art solvers for the famous Traveling Salesperson Problem (TSP). Moreover, we adopt the hypervolume indicator (HV) commonly used in multi-objective optimization for simultaneously assessing both conflicting objectives and investigate relations to commonly used performance indicators, both theoretically and empirically. Next to Penalized Average Runtime (PAR) and Penalized Quantile Runtime (PQR), the HV measure is used as a core concept within the construction of per-instance algorithm selection models offering interesting insights into complementary behavior of inexact TSP solvers. \textbullet The multi-objective perspective is naturally generalizable to multiple objectives. \textbullet Proof of relationship between HV and the PAR in the considered bi-objective space. \textbullet New insights into complementary behavior of stochastic optimization algorithms.}}, author = {{Bossek, Jakob and Kerschke, Pascal and Trautmann, Heike}}, issn = {{1568-4946}}, journal = {{Applied Soft Computing}}, keywords = {{Algorithm selection, Combinatorial optimization, Multi-objective optimization, Performance measurement, Traveling Salesperson Problem}}, number = {{C}}, title = {{{A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms}}}, doi = {{10.1016/j.asoc.2019.105901}}, volume = {{88}}, year = {{2020}}, } @article{46334, abstract = {{We build upon a recently proposed multi-objective view onto performance measurement of single-objective stochastic solvers. The trade-off between the fraction of failed runs and the mean runtime of successful runs – both to be minimized – is directly analyzed based on a study on algorithm selection of inexact state-of-the-art solvers for the famous Traveling Salesperson Problem (TSP). Moreover, we adopt the hypervolume indicator (HV) commonly used in multi-objective optimization for simultaneously assessing both conflicting objectives and investigate relations to commonly used performance indicators, both theoretically and empirically. Next to Penalized Average Runtime (PAR) and Penalized Quantile Runtime (PQR), the HV measure is used as a core concept within the construction of per-instance algorithm selection models offering interesting insights into complementary behavior of inexact TSP solvers.}}, author = {{Bossek, Jakob and Kerschke, Pascal and Trautmann, Heike}}, issn = {{1568-4946}}, journal = {{Applied Soft Computing}}, keywords = {{Algorithm selection, Multi-objective optimization, Performance measurement, Combinatorial optimization, Traveling Salesperson Problem}}, pages = {{105901}}, title = {{{A multi-objective perspective on performance assessment and automated selection of single-objective optimization algorithms}}}, doi = {{https://doi.org/10.1016/j.asoc.2019.105901}}, volume = {{88}}, year = {{2020}}, } @article{19973, abstract = {{As a result of lightweight design, increased use is being made of high-strength steel and aluminium in car bodies. Self-piercing riveting is an established technique for joining these materials. The dissimilar properties of the two materials have led to a number of different rivet geometries in the past. Each rivet geometry fulfils the requirements of the materials within a limited range. In the present investigation, an improved rivet geometry is developed, which permits the reliable joining of two material combinations that could only be joined by two different rivet geometries up until now. Material combination 1 consists of high-strength steel on both sides, while material combination 2 comprises aluminium on the punch side and high-strength steel on the die side. The material flow and the stress and strain conditions prevailing during the joining process are analysed by means of numerical simulation. The rivet geometry is then improved step-by-step on the basis of this analysis. Finally, the improved rivet geometry is manufactured and the findings of the investigation are verified in experimental joining tests.}}, author = {{Uhe, Benedikt and Kuball, Clara-Maria and Merklein, Marion and Meschut, Gerson}}, journal = {{Production Engineering}}, keywords = {{Self-piercing riveting, Joining technology, Rivet geometry, Multi-material design, High-strength steel, Aluminium}}, pages = {{417--423}}, title = {{{Improvement of a rivet geometry for the self-piercing riveting of high-strength steel and multi-material joints}}}, doi = {{10.1007/s11740-020-00973-w}}, volume = {{14}}, year = {{2020}}, } @inproceedings{17667, abstract = {{Resolving distributed attacks benefits from collaboration between networks. We present three approaches for the same multi-domain defensive action that can be applied in such an alliance: 1) Counteract Everywhere, 2) Minimize Countermeasures, and 3) Minimize Propagation. First, we provide a formula to compute efficiency of a defense; then we use this formula to compute the efficiency of the approaches under various circumstances. Finally, we discuss how task execution order and timing influence defense efficiency. Our results show that the Minimize Propagation approach is the most efficient method when defending against the chosen attack.}}, author = {{Koning, Ralph and Polevoy, Gleb and Meijer, Lydia and de Laat, Cees and Grosso, Paola}}, booktitle = {{2019 6th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/ 2019 5th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom)}}, issn = {{null}}, keywords = {{computer network security, multinetwork environments, multidomain defensive action, task execution order, timing influence defense efficiency, distributed attacks, collaborative security defence approach, minimize propagation approach, minimize countermeasure approach, counteract everywhere approach, Conferences, Cloud computing, Computer crime, Edge computing, Security, Defense Approaches, Multi-Domain Defense, Collaborative Defense, Defense Algorithms, Computer Networks}}, pages = {{113--123}}, title = {{{Approaches for Collaborative Security Defences in Multi Network Environments}}}, doi = {{10.1109/CSCloud/EdgeCom.2019.000-9}}, year = {{2019}}, } @inproceedings{48841, abstract = {{We tackle a bi-objective dynamic orienteering problem where customer requests arise as time passes by. The goal is to minimize the tour length traveled by a single delivery vehicle while simultaneously keeping the number of dismissed dynamic customers to a minimum. We propose a dynamic Evolutionary Multi-Objective Algorithm which is grounded on insights gained from a previous series of work on an a-posteriori version of the problem, where all request times are known in advance. In our experiments, we simulate different decision maker strategies and evaluate the development of the Pareto-front approximations on exemplary problem instances. It turns out, that despite severely reduced computational budget and no oracle-knowledge of request times the dynamic EMOA is capable of producing approximations which partially dominate the results of the a-posteriori EMOA and dynamic integer linear programming strategies.}}, author = {{Bossek, Jakob and Grimme, Christian and Meisel, Stephan and Rudolph, Günter and Trautmann, Heike}}, booktitle = {{Evolutionary Multi-Criterion Optimization (EMO)}}, editor = {{Deb, Kalyanmoy and Goodman, Erik and Coello Coello, Carlos A. and Klamroth, Kathrin and Miettinen, Kaisa and Mostaghim, Sanaz and Reed, Patrick}}, isbn = {{978-3-030-12598-1}}, keywords = {{Combinatorial optimization, Dynamic optimization, Metaheuristics, Multi-objective optimization, Vehicle routing}}, pages = {{516–528}}, publisher = {{Springer International Publishing}}, title = {{{Bi-Objective Orienteering: Towards a Dynamic Multi-objective Evolutionary Algorithm}}}, doi = {{10.1007/978-3-030-12598-1_41}}, year = {{2019}}, } @inproceedings{48840, abstract = {{Research has shown that for many single-objective graph problems where optimum solutions are composed of low weight sub-graphs, such as the minimum spanning tree problem (MST), mutation operators favoring low weight edges show superior performance. Intuitively, similar observations should hold for multi-criteria variants of such problems. In this work, we focus on the multi-criteria MST problem. A thorough experimental study is conducted where we estimate the probability of edges being part of non-dominated spanning trees as a function of the edges’ non-domination level or domination count, respectively. Building on gained insights, we propose several biased one-edge-exchange mutation operators that differ in the used edge-selection probability distribution (biased towards edges of low rank). Our empirical analysis shows that among different graph types (dense and sparse) and edge weight types (both uniformly random and combinations of Euclidean and uniformly random) biased edge-selection strategies perform superior in contrast to the baseline uniform edge-selection. Our findings are in particular strong for dense graphs.}}, author = {{Bossek, Jakob and Grimme, Christian and Neumann, Frank}}, booktitle = {{Proceedings of the Genetic and Evolutionary Computation Conference}}, isbn = {{978-1-4503-6111-8}}, keywords = {{biased mutation, combinatorial optimization, minimum spanning tree, multi-objective optimization}}, pages = {{516–523}}, publisher = {{Association for Computing Machinery}}, title = {{{On the Benefits of Biased Edge-Exchange Mutation for the Multi-Criteria Spanning Tree Problem}}}, doi = {{10.1145/3321707.3321818}}, year = {{2019}}, } @article{10334, abstract = {{Ultrasonic joining is a common industrial process. In the electronics industry it is used to form electrical connections, including those of dissimilar materials. Multiple influencing factors in ultrasonic joining are known and extensively investigated; process parameters like ultrasonic power, bond force, and bonding frequency of the ultrasonic vibration are known to have a high impact on a reliable joining process and need to be adapted for each new application with different geometry or materials. This contribution is focused on increasing ultrasonic power transmitted to the interface and keeping mechanical stresses during ultrasonic bonding low by using a multi-dimensional ultrasonic transducer concept. Bonding results for a new designed connector pin in IGBT-modules achieved by multi- and one-dimensional bonding are discussed.}}, author = {{Schemmel, Reinhard and Hemsel, Tobias and Dymel, Collin and Hunstig, Matthias and Brökelmann, Michael and Sextro, Walter}}, issn = {{0924-4247}}, journal = {{Sensors and Actuators A: Physical}}, keywords = {{Ultrasonic bonding, Ultrasonic welding, Multi-dimensional bonding, Complex vibration, Multi-frequent, Two-dimensional friction model}}, pages = {{653 -- 662}}, title = {{{Using complex multi-dimensional vibration trajectories in ultrasonic bonding and welding}}}, doi = {{10.1016/j.sna.2019.04.025}}, volume = {{295}}, year = {{2019}}, } @inproceedings{9999, abstract = {{Ultrasonic wire bonding is an indispensable process in the industrial manufacturing of semiconductor devices. Copper wire is increasingly replacing the well-established aluminium wire because of its superior electrical, thermal and mechanical properties. Copper wire processes differ significantly from aluminium processes and are more sensitive to disturbances, which reduces the range of parameter values suitable for a stable process. Disturbances can be compensated by an adaption of process parameters, but finding suitable parameters manually is difficult and time-consuming. This paper presents a physical model of the ultrasonic wire bonding process including the friction contact between tool and wire. This model yields novel insights into the process. A prototype of a multi-objective optimizing bonding machine (MOBM) is presented. It uses multi-objective optimization, based on the complete process model, to automatically select the best operating point as a compromise of concurrent objectives.}}, author = {{Unger, Andreas and Hunstig, Matthias and Meyer, Tobias and Brökelmann, Michael and Sextro, Walter}}, booktitle = {{In Proceedings of IMAPS 2018 – 51st Symposium on Microelectronics, Pasadena, CA, 2018}}, keywords = {{wire bonding, multi-objective optimization, process model, copper wire, self-optimization}}, title = {{{Intelligent Production of Wire Bonds using Multi-Objective Optimization – Insights, Opportunities and Challenges}}}, doi = {{10.4071/2380-4505-2018.1.000572}}, volume = {{Vol. 2018, No. 1, pp. 000572-000577.}}, year = {{2018}}, } @inproceedings{4375, abstract = {{We present a peer-to-peer network that supports the efficient processing of orthogonal range queries $R=\bigtimes_{i=1}^{d}[a_i,\,b_i]$ in a $d$-dimensional point space.\\ The network is the same for each dimension, namely a distance halving network like the one introduced by Naor and Wieder (ACM TALG'07). We show how to execute such range queries using $\mathcal{O}\left(2^{d'}d\,\log m + d\,|R|\right)$ hops (and the same number of messages) in total. Here $[m]^d$ is the ground set, $|R|$ is the size and $d'$ the dimension of the queried range. Furthermore, if the peers form a distributed network, the query can be answered in $\mathcal{O}\left(d\,\log m + d\,\sum_{i=1}^{d}(b_i-a_i+1)\right)$ communication rounds. Our algorithms are based on a mapping of the Hilbert Curve through $[m]^d$ to the peers.}}, author = {{Benter, Markus and Knollmann, Till and Meyer auf der Heide, Friedhelm and Setzer, Alexander and Sundermeier, Jannik}}, booktitle = {{Proceedings of the 4th International Symposium on Algorithmic Aspects of Cloud Computing (ALGOCLOUD)}}, keywords = {{Distributed Storage, Multi-Dimensional Range Queries, Peer-to-Peer, Hilbert Curve}}, location = {{Helsinki}}, title = {{{A Peer-to-Peer based Cloud Storage supporting orthogonal Range Queries of arbitrary Dimension}}}, doi = {{10.1007/978-3-030-19759-9_4}}, year = {{2018}}, } @inproceedings{48839, abstract = {{We analyze the effects of including local search techniques into a multi-objective evolutionary algorithm for solving a bi-objective orienteering problem with a single vehicle while the two conflicting objectives are minimization of travel time and maximization of the number of visited customer locations. Experiments are based on a large set of specifically designed problem instances with different characteristics and it is shown that local search techniques focusing on one of the objectives only improve the performance of the evolutionary algorithm in terms of both objectives. The analysis also shows that local search techniques are capable of sending locally optimal solutions to foremost fronts of the multi-objective optimization process, and that these solutions then become the leading factors of the evolutionary process.}}, author = {{Bossek, Jakob and Grimme, Christian and Meisel, Stephan and Rudolph, Günter and Trautmann, Heike}}, booktitle = {{Proceedings of the Genetic and Evolutionary Computation Conference}}, isbn = {{978-1-4503-5618-3}}, keywords = {{combinatorial optimization, metaheuristics, multi-objective optimization, orienteering, transportation}}, pages = {{585–592}}, publisher = {{Association for Computing Machinery}}, title = {{{Local Search Effects in Bi-Objective Orienteering}}}, doi = {{10.1145/3205455.3205548}}, year = {{2018}}, } @inproceedings{5588, abstract = {{The protection of information technology (IT) has become and is predicted to remain a key economic challenge for organizations. While research on IT security investment is fast growing, it lacks a theoretical basis for structuring research, explaining economic-technological phenomena and guide future research. We address this shortcoming by suggesting a new theoretical model emerging from a multi-theoretical perspective adopt-ing the Resource-Based View and the Organizational Learning Theory. The joint appli-cation of these theories allows to conceptualize in one theoretical model the organiza-tional learning effects that occur when the protection of organizational resources through IT security countermeasures develops over time. We use this model of IT security invest-ments to synthesize findings of a large body of literature and to derive research gaps. We also discuss managerial implications of (closing) these gaps by providing practical ex-amples.}}, author = {{Weishäupl, Eva and Yasasin, Emrah and Schryen, Guido}}, booktitle = {{International Conference on Information Systems}}, keywords = {{Information Security, Investment, Literature review, Resource-based View, Organi-zational Learning Theory, Multi-theoretical Perspective}}, title = {{{A Multi-Theoretical Literature Review on Information Security Investments using the Resource-Based View and the Organizational Learning Theory}}}, year = {{2015}}, } @inproceedings{29973, abstract = {{Haushaltsgeräte aus der Klasse der "Weißen Ware" tragen mit etwa einem Drittel ($34,2%$ \citeBDEW2013) zum privaten Energieverbrauch bei. Diese Veröffentlichung präsentiert eine Struktur und die dafür notwendige optimale Betriebsstrategie für Weiße Ware in einer Umgebung mit Strompreisen, die wegen der Volatilität der Regenerativen Energien stark fluktuieren. Das vorgeschlagene Konzept nutzt dafür ein dezentrales Energiemanagementsystem, das über drei Hierarchieebenen verteilt ist: die Geräteebene, die Haushaltsebene und die Ortsnetzebene. Auf der Geräteebene nutzt dieses Konzept zusätzlich Betriebsflexibilitäten der Haushaltsgeräte aus.}}, author = {{Stille, Karl Stephan Christian and Böcker, Joachim and Bettentrup, Ralf and Kaiser, Ingo}}, booktitle = {{ETG-Fachtagung "Von Smart Grids zu Smart Markets"}}, keywords = {{Energy management, hybrid energy storage system, self-optimization, multi-objective optimization, adaptive systems, pareto set, SFB614-D1, SFB614-D2, LEA-Publikation, Eigene}}, publisher = {{VDE}}, title = {{{Hierarchisches Optimierungskonzept für die Laststeuerung von Haushaltsgeräten}}}, year = {{2015}}, } @inproceedings{48887, abstract = {{We evaluate the performance of a multi-objective evolutionary algorithm on a class of dynamic routing problems with a single vehicle. In particular we focus on relating algorithmic performance to the most prominent characteristics of problem instances. The routing problem considers two types of customers: mandatory customers must be visited whereas optional customers do not necessarily have to be visited. Moreover, mandatory customers are known prior to the start of the tour whereas optional customers request for service at later points in time with the vehicle already being on its way. The multi-objective optimization problem then results as maximizing the number of visited customers while simultaneously minimizing total travel time. As an a-posteriori evaluation tool, the evolutionary algorithm aims at approximating the related Pareto set for specifically designed benchmarking instances differing in terms of number of customers, geographical layout, fraction of mandatory customers, and request times of optional customers. Conceptional and experimental comparisons to online heuristic procedures are provided.}}, author = {{Meisel, Stephan and Grimme, Christian and Bossek, Jakob and Wölck, Martin and Rudolph, Günter and Trautmann, Heike}}, booktitle = {{Proceedings of the Genetic and Evolutionary Computation Conference }}, isbn = {{978-1-4503-3472-3}}, keywords = {{combinatorial optimization, metaheuristics, multi-objective optimization, online algorithms, transportation}}, pages = {{425–432}}, publisher = {{Association for Computing Machinery}}, title = {{{Evaluation of a Multi-Objective EA on Benchmark Instances for Dynamic Routing of a Vehicle}}}, doi = {{10.1145/2739480.2754705}}, year = {{2015}}, } @article{9885, abstract = {{Intelligent mechatronic systems, such as self-optimizing systems, allow an adaptation of the system behavior at runtime based on the current situation. To do so, they generally select among several pre-defined working points. A common method to determine working points for a mechatronic system is to use model-based multiobjective optimization. It allows finding compromises among conflicting objectives, called objective functions, by adapting parameters. To evaluate the system behavior for different parameter sets, a model of the system behavior is included in the objective functions and is evaluated during each function call. Intelligent mechatronic systems also have the ability to adapt their behavior based on their current reliability, thus increasing their availability, or on changed safety requirements; all of which are summed up by the common term dependability. To allow this adaptation, dependability can be considered in multiobjective optimization by including dependability-related objective functions. However, whereas performance-related objective functions are easily found, formulation of dependability-related objective functions is highly system-specific and not intuitive, making it complex and error-prone. Since each mechatronic system is different, individual failure modes have to be taken into account, which need to be found using common methods such as Failure-Modes and Effects Analysis or Fault Tree Analysis. Using component degradation models, which again are specific to the system at hand, the main loading factors can be determined. By including these in the model of the system behavior, the relation between working point and dependability can be formulated as an objective function. In our work, this approach is presented in more detail. It is exemplified using an actively actuated single plate dry clutch system. Results show that this approach is suitable for formulating dependability-related objective functions and that these can be used to extend system lifetime by adapting system behavior.}}, author = {{Meyer , Tobias and Sondermann-Wölke, Christoph and Sextro, Walter}}, journal = {{Conference Proceedings of the 2nd International Conference on System-Integrated Intelligence}}, keywords = {{Self-optimization, multiobjective optimization, objective function, dependability, intelligent system, behavior adaptation}}, pages = {{46--53}}, title = {{{Method to Identify Dependability Objectives in Multiobjective Optimization Problem}}}, doi = {{10.1016/j.protcy.2014.09.033}}, volume = {{15}}, year = {{2014}}, } @inproceedings{13324, abstract = {{The new technological enhancements and the accessibility to varieties of online applications, enable users to collect personal data and perform self-evaluation through test, comparison and experimentation. The sparked interest in numbers and numbers as self-representative visualisations is prominent in social networking sites, which are the empirical setting for the present study. This paper sets out to establish a multi-theoretical framework which enables the investigation of emerging phenomena of the role of numbers in social networking sites. The proposed framework rests on three theoretical pillars: self-determination theory, heuristic decision making and behavioural economics. A discussion departs from these convictions to investigate user reactions and behaviour when faced with numerical representations in the SNS.}}, author = {{Sjöklint, Mimmi and Constantiou, Ioanna and Trier, Matthias}}, booktitle = {{ECIS 2013 Proceedings}}, isbn = {{9783834924421}}, keywords = {{User Behaviour, Social Networking Sites, Numerical Representations, Multi-Theoretical Framework, Quantified Self, Pointification}}, publisher = {{Association for Information Systems. AIS Electronic Library (AISeL)}}, title = {{{Numerical Representations and User Behaviour in Social Networking Sites: Towards a Multi- Theoretical Research Framework}}}, year = {{2013}}, } @inproceedings{36920, abstract = {{In the electronic system development, energy consumption is clearly becoming one of the most important design concerns. From the system level point of view, Dynamic Power Management (DPM) and Dynamic Voltage and Frequency Scaling (DVFS) are two mostly applied techniques to adjust the tradeoff between the performance and power dissipation at runtime. In this paper, we study the problem of combined application of both techniques with regard to hard real-time systems running on cluster-based multi-core processors. To optimize the processor energy consumption, a heuristic based on simulated annealing with efficient termination criterion is proposed. The experiment results show that the proposed algorithm outperforms the existing approaches in terms of the energy reduction. }}, author = {{He, Da and Müller, Wolfgang}}, booktitle = {{Proceedings of the International Conference on Applied Computing (AC)}}, editor = {{Weghorn, Hans}}, isbn = {{978-989-8533-20-3 }}, keywords = {{Dynamic Power Management, Dynamic Voltage and Frequency Scaling, Hard Real-Time, Multi-core Processor}}, title = {{{An Energy-Efficient Heuristic for Hard Real-Time System on Multi-Core Processors}}}, year = {{2013}}, } @article{46411, abstract = {{The paper presents a framework to optimise the design of work roll based on the cooling performance. The framework develops meta-models from a set of finite element analyses (FEA) of the roll cooling. A design of experiment technique is used to identify the FEA runs. The research also identifies sources of uncertainties in the design process. A robust evolutionary multi-objective evaluation technique is applied to the design optimisation in constrained problems with real life uncertainty. The approach handles uncertainties associated both with design variables and fitness functions. Constraints violation within the neighbourhood of a design is considered as part of a measurement for degree of feasibility and robustness of a solution.}}, author = {{Azene, Y.T. and Roy, R. and Farrugia, D. and Onisa, C. and Mehnen, J. and Trautmann, Heike}}, issn = {{1755-5817}}, journal = {{CIRP Journal of Manufacturing Science and Technology}}, keywords = {{Roll cooling design, Uncertainty, Design optimisation, Multi-objective optimisation, Constraint in design}}, number = {{4}}, pages = {{290--298}}, title = {{{Work roll cooling system design optimisation in presence of uncertainty and constrains}}}, doi = {{https://doi.org/10.1016/j.cirpj.2010.06.001}}, volume = {{2}}, year = {{2010}}, }