Özean, E.

Conference Object | 2005 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)3733 LNCS , pp.482 - 492

Nurse rostering problems represent a subclass of scheduling problems that are hard to solve. The goal is finding high quality shift and resource assignments, satisfying the needs and requirements of employees as well as the employers in healthcare institutions. In this paper, a real case of a nurse rostering problem is introduced. Memetic Algorithms utilizing different type of promising genetic operators and a self adaptive violation directed hierarchical hill climbing method are presented based on a previously proposed framework. © Springer-Verlag Berlin Heidelberg 2005.

Ünal, V.Ü. | Gülçat, Ü.

Article | 2003 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)2659 , pp.622 - 631

Parallel implicit solution of the incompressible Navier-Stokes equations based on two fractional steps in time and Finite Element discretization in space is presented. The accuracy of the scheme is second order in both time and space domains. Large time step sizes, with CFL numbers much larger than unity, are taken. The Domain Decomposition Technique is implemented for parallel solution of the problem with matching and non-overlapping sub domains. The segregate solution to tempereature field is obtained for the flow case where the forced convection is one order of magnitude higher than the free convection. © Springer-Verlag Berlin H . . .eidelberg 2003 Daha fazlası Daha az

Bilgin, B. | Özcan, E. | Korkmaz, E.E.

Conference Object | 2006 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)3867 LNCS , pp.394 - 412

Hyper-heuristics are proposed as a higher level of abstraction as compared to the metaheuristics. Hyper-heuristic methods deploy a set of simple heuristics and use only non-problem-specific data, such as fitness change or heuristic execution time. A typical iteration of a hyper-heuristic algorithm consists of two phases: the heuristic selection method and move acceptance. In this paper, heuristic selection mechanisms and move acceptance criteria in hyper-heuristics are analyzed in depth. Seven heuristic selection methods and five acceptance criteria are implemented. The performance of each selection and acceptance mechanism pair is . . .evaluated on 14 well-known benchmark functions and 21 exam timetabling problem instances. © Springer-Verlag Berlin Heidelberg 2007 Daha fazlası Daha az

Özean, E. | Bilgin, B. | Korkmaz, E.E.

Conference Object | 2006 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)4193 LNCS , pp.202 - 211

Hyperheuristics are single candidate solution based and simple to maintain mechanisms used in optimization. At each iteration, as a higher level of abstraction, a hyperheuristic chooses and applies one of the heuristics to a candidate solution. In this study, the performance contribution of hill climbing operators along with the mutational heuristics are analyzed in depth in four different hyperheuristic frameworks. Four different hill climbing operators and three mutational operators are used during the experiments. Various subsets of the heuristics are evaluated on fourteen well-known benchmark functions. © Springer-Verlag Berlin . . .Heidelberg 2006 Daha fazlası Daha az

Sertel, O. | Ünsalan, Cem

Conference Object | 2006 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)4105 LNCS , pp.745 - 752

In this study, we focus on model reconstruction for 3D objects using range images. We propose a crude range image alignment method to overcome the initial estimation problem of the iterative closest point (ICP) algorithm using edge points of range images. Different from previous edge detection methods, we first obtain a function representation of the range image in spherical coordinates. This representation allows detecting smooth edges on the object surface easily by a zero crossing edge detector. We use ICP on these edges to align patches in a crude manner. Then, we apply ICP to the whole point set and obtain the final alignment. . . .This dual operation is performed extremely fast compared to directly aligning the point sets. We also obtain the edges of the 3D object model while registering it. These edge points may be of use in 3D object recognition and classification. © Springer-Verlag Berlin Heidelberg 2006 Daha fazlası Daha az

Ülker, Ö. | Korkmaz, E.E. | Özcan, E.

Conference Object | 2008 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)5199 LNCS , pp.1140 - 1149

Linear Linkage Encoding (LLE) is a representation method proposed for grouping problems. It has already been used in solving data clustering, graph coloring and timetabling problems based on multi-objective genetic algorithms. In this study, this novel encoding scheme is investigated on bin packing again using a genetic algorithm. Bin packing benchmark problem instances are used to compare the performance of traditional recombination operators and custom made LLE crossover operators which are hybridized with parametrized placement heuristics. The results denote that LLE is a viable candidate for bin packing problem whenever appropri . . .ate genetic operators are chosen. © 2008 Springer-Verlag Berlin Heidelberg Daha fazlası Daha az

Küçük, G. | Başaran, C.

Conference Object | 2006 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)4263 LNCS , pp.655 - 664

Today, wireless sensor networks (WSNs) enable us to run a new range of applications from habitat monitoring, to military and medical applications. A typical WSN node is composed of several sensors, a radio communication interface, a microprocessor, and a limited power supply. In many WSN applications, such as forest fire monitoring or intruder detection, user intervention and battery replenishment is not possible. Since the battery lifetime is directly related to the amount of processing and communication involved in these nodes, optimal resource usage becomes a major issue. A typical WSN application may sense and process very close . . . or constant data values for long durations, when the environmental conditions are stable. This is a common behavior that can be exploited to reduce the power consumption of WSN nodes. This study combines two orthogonal techniques to reduce the energy dissipation of the processor component of the sensor nodes. First, we briefly discuss silent-store filtering MoteCache. Second, we utilize Content-Aware Data MAnagement (CADMA) on top of MoteCache architecture to achieve further energy savings and performance improvements. The complexity increase introduced by CADMA is also compensated by further complexity reduction in MoteCache. Our optimal configuration reduces the total node energy, and hence increases the node lifetime, by 19.4% on the average across a wide variety of simulated sensor benchmarks. Our complexity-aware configuration with a minimum MoteCache size achieves not only energy savings up to 16.2% but also performance improvements up to 4.3%, on the average. © Springer-Verlag Berlin Heidelberg 2006 Daha fazlası Daha az

Ülker, Ö. | Özcan, E. | Korkmaz, E.E.

Conference Object | 2006 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)3867 LNCS , pp.347 - 363

Linear Linkage Encoding (LLE) is a recently proposed representation scheme for evolutionary algorithms. This representation has been used only in data clustering. However, it is also suitable for grouping problems. In this paper, we investigate LLE on two grouping problems; graph coloring and exam timetabling. Two crossover operators suitable for LLE are proposed and compared to the existing ones. Initial results show that LLE is a viable candidate for grouping problems whenever appropriate genetic operators are used. © Springer-Verlag Berlin Heidelberg 2007.

Toktaş, A.O. | Serif, T.

Conference Object | 2019 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)11673 LNCS , pp.294 - 307

With an ever-increasing number of technological tools and gadgets in our life, people have become familiar with multiple kinds of user interaction interfaces and devices. Day in, day out people interact with various devices that follow different user interaction paradigms, such as when they are using a mobile phone, smart TV or a gaming console. Although these devices have various forms among themselves, the interaction method used to control them can make a significant difference in usability. Gaming consoles have become a huge area of the computer entertainment business in years. With every new generation of gaming consoles, the t . . .echnologies behind it improve dramatically. Most of the time, the improvements are about the graphics and interaction devices. It can be clearly said that even though the graphics have improved in the last two generations of gaming consoles, the interaction paradigms and approaches were not up to the users’ expectations. This is especially the case for a first-person shooter and real-time strategy (RTS) games. Accordingly, bearing in mind the above as a motivation, the aim of this work is to develop a prototype game controller that will improve the usability and gameplay experience of the first-person shooter games. © 2019, Springer Nature Switzerland AG Daha fazlası Daha az

Kucuk, G. | Uslu, G. | Yesil, C.

Conference Object | 2014 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)8488 LNCS , pp.187 - 198

In a Simultaneous Multi-Threaded (SMT) processor environment, threads share datapath resources, and resource allocation policy directly affects the throughput metric. As a way of explicit resource management, resource requirements of threads are estimated based on several runtime statistics, such as cache miss counts, Issue Queue usage and efficiency metrics. Controlling processor resources indirectly by means of a fetch policy is also targeted in many recent studies. A successful technique, Speculative Instruction Window Weighting (SIWW), which speculates the weights of instructions in Issue Queue to indirectly manage SMT resource . . .usage, is recently proposed. SIWW promises better peformance results compared to the well-accepted ICOUNT fetch policy. In this study, we propose an alternative fetch policy that implements SIWW-like logic using a history-based prediction mechanism, History-based Predictive Instruction Window Weighting (HPIWW), avoiding any types of speculation hardware and its inherent complexity. As a result, we show that HPIWW outperforms SIWW by 3% on the average across all simulated workloads, and dissipates 2.5 times less power than its rival. © Springer International Publishing Switzerland 2014 Daha fazlası Daha az

Helvaci, S. | Senova, A. | Kar, G. | Gören, S.

Conference Object | 2018 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)10995 LNCS , pp.193 - 204

This work proposes a gamification approach to measure the driving behavior using the in-vehicle data and score drivers. Existing work largely focus on one functionality: either displaying vehicular info or scoring the driver. And some other work just provides navigation or Point of Interest (POI). In our work, we combine these features with minimal distraction for the driver. With this goal, we consider a system that interfaces to the vehicle bus and find the errors of the driver during the drive using multiple criteria. Furthermore, by providing achievements and leader boards, the driver is motivated to have a good score while driv . . .ing. To facilitate this analysis and to evaluate the system, we recorded two trips in real traffic. The results show that we achieve more than 95% accuracy between real-world scenario and the simulation. We also present POI feature that finds nearest preferred locations which are restaurants, hospitals, gas stations, pharmacies, car repair shops. © Springer International Publishing AG, part of Springer Nature 2018 Daha fazlası Daha az

Özcan, E.

Conference Object | 2006 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)3867 LNCS , pp.85 - 104

This paper presents an empirical study on memetic algorithms in two parts. In the first part, the details of the memetic algorithm experiments with a set of well known benchmark functions are described. In the second part, a heuristic template is introduced for solving timetabling problems. Two adaptive heuristics that utilize a set of constraint-based hill climbers in a co-operative manner are designed based on this template. A hyper-heuristic is a mechanism used for managing a set of low-level heuristics. At each step, an appropriate heuristic is chosen and applied to a candidate solution. Both adaptive heuristics can be considere . . .d as hyper-heuristics. Memetic algorithms employing each hyper-heuristic separately as a single hill climber are experimented on a set of randomly generated nurse rostering problem instances. Moreover, the standard genetic algorithm and two self-generating multimeme memetic algorithms are compared to the proposed memetic algorithms and a previous study. © Springer-Verlag Berlin Heidelberg 2007 Daha fazlası Daha az