@article {1172, title = {On the minimum and maximum selective graph coloring problems in some graph classes}, journal = {Discrete Applied Mathematics}, volume = {204}, year = {2016}, pages = {77{\textendash}89}, author = {Demange, Marc and Ekim, Tinaz and Ries, Bernard} } @article {1063, title = {Time series representation and similarity based on local autopatterns}, journal = {Data Mining and Knowledge Discovery}, volume = {30}, year = {2016}, month = {03/2016}, pages = {476{\textendash}509}, abstract = {

Time series data mining has received much greater interest along with the increase in temporal data sets from different domains such as medicine, finance, multimedia, etc. Representations are important to reduce dimensionality and generate useful similarity measures. High-level representations such as Fourier transforms, wavelets, piecewise polynomial models, etc., were considered previously. Recently, autoregressive kernels were introduced to reflect the similarity of the time series. We introduce a novel approach to model the dependency structure in time series that generalizes the concept of autoregression to local autopatterns. Our approach generates a pattern-based representation along with a similarity measure called learned pattern similarity (LPS). A tree-based ensemble-learning strategy that is fast and insensitive to parameter settings is the basis for the approach. Then, a robust similarity measure based on the learned patterns is presented. This unsupervised approach to represent and measure the similarity between time series generally applies to a number of data mining tasks (e.g., clustering, anomaly detection, classification). Furthermore, an embedded learning of the representation avoids pre-defined features and an extraction step which is common in some feature-based approaches. The method generalizes in a straightforward manner to multivariate time series. The effectiveness of LPS is evaluated on time series classification problems from various domains. We compare LPS to eleven well-known similarity measures. Our experimental results show that LPS provides fast and competitive results on benchmark datasets from several domains. Furthermore, LPS provides a research direction and template approach that breaks from the linear dependency models to potentially foster other promising nonlinear approaches.

}, issn = {1573-756X}, author = {Mustafa Gokce Baydogan and Runger, George} } @article {657, title = {Learning a symbolic representation for multivariate time series classification}, journal = {Data Mining and Knowledge Discovery}, volume = {29}, year = {2015}, month = {03/2015}, pages = {400-422}, publisher = {Springer US}, abstract = {

Multivariate time series (MTS) classification has gained importance with the increase in the number of temporal datasets in different domains (such as medicine, finance, multimedia, etc.). Similarity-based approaches, such as nearest-neighbor classifiers, are often used for univariate time series, but MTS are characterized not only by individual attributes, but also by their relationships. Here we provide a classifier based on a new symbolic representation for MTS (denoted as SMTS) with several important elements. SMTS considers all attributes of MTS simultaneously, rather than separately, to extract information contained in the relationships. Symbols are learned from a supervised algorithm that does not require pre-defined intervals, nor features. An elementary representation is used that consists of the time index, and the values (and first differences for numerical attributes) of the individual time series as columns. That is, there is essentially no feature extraction (aside from first differences) and the local series values are fused to time position through the time index. The initial representation of raw data is quite simple conceptually and operationally. Still, a tree-based ensemble can detect interactions in the space of the time index and time values and this is exploited to generate a high-dimensional codebook from the terminal nodes of the trees. Because the time index is included as an attribute, each MTS is learned to be segmented by time, or by the value of one of its attributes. The codebook is processed with a second ensemble where now implicit feature selection is exploited to handle the high-dimensional input. The constituent properties produce a distinctly different algorithm. Moreover, MTS with nominal and missing values are handled efficiently with tree learners. Experiments demonstrate the effectiveness of the proposed approach in terms of accuracy and computation times in a large collection multivariate (and univariate) datasets.

}, keywords = {codebook, Decision trees, supervised learning}, issn = {1384-5810}, doi = {10.1007/s10618-014-0349-y}, url = {http://dx.doi.org/10.1007/s10618-014-0349-y}, author = {Mustafa Gokce Baydogan and Runger, George} } @article {1511, title = {On some applications of the selective graph coloring problem}, journal = {European Journal of Operational Research}, volume = {240}, year = {2015}, pages = {307-314}, abstract = {

In this paper we present the Selective Graph Coloring Problem, a generalization of the standard graph coloring problem as well as several of its possible applications. Given a graph with a partition of its vertex set into several clusters, we want to select one vertex per cluster such that the chromatic number of the subgraph induced by the selected vertices is minimum. This problem appeared in the literature under different names for specific models and its complexity has recently been studied for different classes of graphs. Here, we describe different models {\textendash} some already discussed in previous papers and some new ones {\textendash} in very different contexts under a unified framework based on this graph problem. We point out similarities between these models, offering a new approach to solve them, and show some generic situations where the selective graph coloring problem may be used. We focus on specific graph classes motivated by each model, and we briefly discuss the complexity of the selective graph coloring problem in each one of these graph classes and point out interesting future research directions.

}, keywords = {Combinatorial optimization, Computational complexity, Graph theory, partition coloring, Selective coloring}, issn = {0377-2217}, doi = {https://doi.org/10.1016/j.ejor.2014.05.011}, url = {https://www.sciencedirect.com/science/article/pii/S0377221714004184}, author = {Marc Demange and Ekim, Tinaz and Bernard Ries and Cerasela Tanasescu} } @article {35, title = {SMT: Sparse multivariate tree}, journal = {Statistical Analysis and Data Mining}, volume = {7}, year = {2014}, month = {02/2014}, pages = {53-69}, abstract = {

A multivariate decision tree attempts to improve upon the single variable split in a traditional tree. With the increase in datasets with many features and a small number of labeled instances in a variety of domains (bioinformatics, text mining, etc.), a traditional tree-based approach with a greedy variable selection at a node may omit important information. Therefore, the recursive partitioning idea of a simple decision tree combined with the intrinsic feature selection of L1 regularized logistic regression (LR) at each node is a natural choice for a multivariate tree model that is simple, but broadly applicable. This natural solution leads to the sparse multivariate tree (SMT) considered here. SMT can naturally handle non-time-series data and is extended to handle time-series classification problems with the power of extracting interpretable temporal patterns (e.g., means, slopes, and deviations). Binary L1 regularized LR models are used here for binary classification problems. However, SMT may be extended to solve multiclass problems with multinomial LR models. The accuracy and computational efficiency of SMT is compared to a large number of competitors on time series and non-time-series data.

}, keywords = {decision tree, feature extraction, fused Lasso, Lasso, time series classification}, issn = {1932-1872}, doi = {10.1002/sam.11208}, url = {http://dx.doi.org/10.1002/sam.11208}, author = {Houtao Deng and Mustafa Gokce Baydogan and George Runger} } @article {33, title = {A Bag-of-Features Framework to Classify Time Series}, journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {35}, year = {2013}, pages = {2796-2802}, abstract = {

Time series classification is an important task with many challenging applications. A nearest neighbor (NN) classifier with dynamic time warping (DTW) distance is a strong solution in this context. On the other hand, feature-based approaches have been proposed as both classifiers and to provide insight into the series, but these approaches have problems handling translations and dilations in local patterns. Considering these shortcomings, we present a framework to classify time series based on a bag-of-features representation (TSBF). Multiple subsequences selected from random locations and of random lengths are partitioned into shorter intervals to capture the local information. Consequently, features computed from these subsequences measure properties at different locations and dilations when viewed from the original series. This provides a feature-based approach that can handle warping (although differently from DTW). Moreover, a supervised learner (that handles mixed data types, different units, etc.) integrates location information into a compact codebook through class probability estimates. Additionally, relevant global features can easily supplement the codebook. TSBF is compared to NN classifiers and other alternatives (bag-of-words strategies, sparse spatial sample kernels, shapelets). Our experimental results show that TSBF provides better results than competitive methods on benchmark datasets from the UCR time series database.

}, keywords = {codebook, feature extraction, supervised learning}, issn = {0162-8828}, doi = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2013.72}, author = {Mustafa Gokce Baydogan and George Runger and Eugene Tuv} } @article {eksioglu2013hand, title = {Hand torque strength of female population of Turkey and the effects of various factors}, journal = {Occupational Safety and Hygiene}, year = {2013}, pages = {37}, publisher = {CRC Press}, author = {Mahmut Ek{\c s}io{\u g}lu and Recep, Z} } @article {bonomo2013perfectness, title = {Perfectness of clustered graphs}, journal = {Discrete Optimization}, volume = {10}, number = {4}, year = {2013}, pages = {296{\textendash}303}, publisher = {Elsevier}, author = {Bonomo, Flavia and Cornaz, Denis and Ekim, Tinaz and Ries, Bernard} } @article {TaskinEtAl2012, title = {Mixed-Integer Programming Techniques for Decomposing IMRT Fluence Maps Using Rectangular Apertures}, journal = {Annals of Operations Research}, volume = {196(1)}, year = {2012}, pages = {799-818}, doi = {http://dx.doi.org/10.1007/s10479-010-0767-1}, author = {Z C Ta{\c s}k{\i}n and J. Cole Smith and H. Edwin Romeijn} } @article {TaskinEtAl2010a, title = {Optimal Multileaf Collimator Leaf Sequencing in IMRT Treatment Planning}, journal = {Operations Research}, volume = {58}, number = {3}, year = {2010}, pages = {674{\textendash}690}, doi = {http://dx.doi.org/10.1287/opre.1090.0759}, author = {Z C Ta{\c s}k{\i}n and J. Cole Smith and H. Edwin Romeijn and James F. Dempsey} } @article {ekim2010split, title = {Split-critical and uniquely split-colorable graphs}, journal = {Discrete Mathematics and Theoretical Computer Science}, volume = {12}, number = {5}, year = {2010}, pages = {1{\textendash}24}, author = {Ekim, Tinaz and Ries, Bernard and de Werra, Dominique and others} } @article {34, title = {Toward Development of Adaptive Service-Based Software Systems}, journal = {IEEE Transactions on Services Computing}, volume = {2}, year = {2009}, pages = {247-260}, abstract = {

The rapid adoption of service-oriented architecture (SOA) in many large-scale distributed applications requires the development of adaptive service-based software systems (ASBS) with the capability of monitoring the changing system status, analyzing, and controlling tradeoffs among various quality-of-service (QoS) aspects, and adapting service configurations to satisfy multiple QoS requirements simultaneously. In this paper, our results toward the development of adaptive service-based software systems are presented. The formulation of activity-state-QoS (ASQ) models and how to use the data from controlled experiments to establish ASQ models for capturing the cause-effect dynamics among service activities, system resource states, and QoS in service-based systems are presented. Then, QoS monitoring modules based on ASQ models and SOA-compliant simulation models are developed to support the validation of the ASBS design. The main idea for developing QoS adaptation modules based on ASQ models is discussed. An experiment based on a voice communication service is used to illustrate our results.

}, keywords = {Design concepts, distributed/Internet-based software engineering tools and techniques, methodologies, modeling methodologies, quality of services, services systems}, issn = {1939-1374}, doi = {http://doi.ieeecomputersociety.org/10.1109/TSC.2009.17}, author = {Stephen S. Yau and Nong Ye and Hessam S. Sarjoughian and Dazhi Huang and Auttawut Roontiva and Mustafa Gokce Baydogan and Mohammed A. Muqsith} } @article {MenEtAl2007, title = {An Exact Approach to Direct Aperture Optimization in IMRT Treatment Planning}, journal = {Physics in Medicine and Biology}, volume = {52}, number = {24}, year = {2007}, pages = {7333-7352}, doi = {http://dx.doi.org/10.1088/0031-9155/52/24/009}, author = {Chunhua Men and H. Edwin Romeijn and Z C Ta{\c s}k{\i}n and James F. Dempsey} } @article {de2006construction, title = {Construction of sports schedules with multiple venues}, journal = {Discrete Applied Mathematics}, volume = {154}, number = {1}, year = {2006}, pages = {47{\textendash}58}, publisher = {North-Holland}, author = {de Werra, Dominique and Ekim, Tinaz and Raess, C} } @conference {ekcsiouglu2005ergonomic, title = {Ergonomic Evaluation Of OCS Audit Station}, booktitle = {Proceedings of XIX Annual International Occupational Ergonomics and Safety Conference (CD-ROM)}, year = {2005}, pages = {403{\textendash}409}, author = {Mahmut Ek{\c s}io{\u g}lu and Lammers, E and Dye, S and Raftery, R} } @article {ray2005optimal, title = {Optimal prices and trade-in rebates for durable, remanufacturable products}, journal = {Manufacturing \& Service Operations Management}, volume = {7}, number = {3}, year = {2005}, pages = {208{\textendash}228}, publisher = {INFORMS}, author = {Ray, Saibal and Boyaci, Tamer and Necati Aras} }