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Publication Open Access 3D face recognition by projection based methods(Society of Photo-optical Instrumentation Engineers (SPIE), 2006) Dutaǧaci, Helin; Sankur, Bülent; Department of Computer Engineering; Yemez, Yücel; Faculty Member; Department of Computer Engineering; College of EngineeringIn this paper, we investigate recognition performances of various projection-based features applied on registered 3D scans of faces. Some features are data driven, such as ICA-based features or NNMF-based features. Other features are obtained using DFT or DCT-based schemes. We apply the feature extraction techniques to three different representations of registered faces, namely, 3D point clouds, 2D depth images and 3D voxel. We consider both global and local features. Global features are extracted from the whole face data, whereas local features are computed over the blocks partitioned from 2D depth images. The block-based local features are fused both at feature level and at decision level. The resulting feature vectors are matched using Linear Discriminant Analysis. Experiments using different combinations of representation types and feature vectors are conducted on the 3D-RMA dataset.
Publication Metadata only A bi-criteria optimization model to analyze the impacts of electric vehicles on costs and emissions(Elsevier, 2017) N/A; N/A; Department of Industrial Engineering; Kabatepe, Bora; Türkay, Metin; Master Student; Faculty Member; Department of Industrial Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 24956Electric vehicles (EV) are emerging as a mobility solution to reduce emissions in the transportation sector. The studies environmental impact analysis of EVs in the literature are based on the average energy mix or pre-defined generation scenarios and construct policy recommendations with a cost minimization objective. However, the environmental performance of EVs depends on the source of the marginal electricity provided to the grid and single objective models do not provide a thorough analysis on the economic and environmental impacts of EVs. In this paper, these gaps are addressed by a four step methodology that analyzes the effects of EVs under different charging and market penetration scenarios. The methodology includes a bi-criteria optimization model representing the electricity market operations. The results from a real-life case analysis show that EVs decrease costs and emissions significantly compared to conventional vehicles.Publication Open Access A hierarchical solution approach for a multicommodity distribution problem under a special cost structure(Elsevier, 2012) Koca, Esra; Department of Industrial Engineering; Yıldırım, Emre Alper; Faculty Member; Department of Industrial Engineering; College of EngineeringMotivated by the spare parts distribution system of a major automotive manufacturer in Turkey, we consider a multicommodity distribution problem from a central depot to a number of geographically dispersed demand points. The distribution of the items is carried out by a set of identical vehicles. The demand of each demand point can be satisfied by several vehicles and a single vehicle is allowed to serve multiple demand points. For a given vehicle, the cost structure is dictated by the farthest demand point from the depot among all demand points served by that vehicle. The objective is to satisfy the demand of each demand point with the minimum total distribution cost. We present a novel integer linear programming formulation of the problem as a variant of the network design problem. The resulting optimization problem becomes computationally infeasible for real-life problems due to the large number of integer variables. In an attempt to circumvent this disadvantage of using the direct formulation especially for larger problems, we propose a Hierarchical Approach that is aimed at solving the problem in two stages using partial demand aggregation followed by a disaggregation scheme. We study the properties of the solution returned by the Hierarchical Approach. We perform computational studies on a data set adapted from a major automotive manufacturer in Turkey. Our results reveal that the Hierarchical Approach significantly outperforms the direct formulation approach in terms of both the running time and the quality of the resulting solution especially on large instances.Publication Open Access A method for estimating stock-out-based substitution rates by using point-of-sale data(Taylor _ Francis, 2009) Öztürk, Ömer Cem; Department of Business Administration; Tan, Barış; Karabatı, Selçuk; Faculty Member; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 28600; 38819Empirical studies in retailing suggest that stock-out rates are quite high in many product categories. Stock-outs result in demand spillover, or substitution, among items within a product category. Product assortment and inventory management decisions can be improved when the substitution rates are known. In this paper, a method is presented to estimate product substitution rates by using only Point-Of-Sale (POS) data. The approach clusters POS intervals into states where each state corresponds to a specific substitution scenario. Then available POS data for each state is consolidated and the substitution rates are estimated using the consolidated information. An extensive computational analysis of the proposed substitution rate estimation method is provided. The computational analysis and comparisons with an estimation method from the literature show that the proposed estimation method performs satisfactorily with limited information.Publication Open Access A novel haptic feature set for the classification of interactive motor behaviors in collaborative object transfer(Institute of Electrical and Electronics Engineers (IEEE), 2021) Küçükyılmaz, Ayşe; Department of Mechanical Engineering; Başdoğan, Çağatay; Şirintuna, Doğanay; Al-Saadi, Zaid Rassim Mohammed; Faculty Member; Department of Mechanical Engineering; College of Engineering; Graduate School of Sciences and Engineering; 125489; N/A; N/AHaptics provides a natural and intuitive channel of communication during the interaction of two humans in complex physical tasks, such as joint object transportation. However, despite the utmost importance of touch in physical interactions, the use of haptics is under-represented when developing intelligent systems. This article explores the prominence of haptic data to extract information about underlying interaction patterns within physical human-human interaction (pHHI). We work on a joint object transportation scenario involving two human partners, and show that haptic features, based on force/torque information, suffice to identify human interactive behavior patterns. We categorize the interaction into four discrete behavior classes. These classes describe whether the partners work in harmony or face conflicts while jointly transporting an object through translational or rotational movements. In an experimental study, we collect data from 12 human dyads and verify the salience of haptic features by achieving a correct classification rate over 91% using a Random Forest classifier.Publication Metadata only A novel reconfigurable intelligent surface-supported code index modulation-based receive spatial modulation system(IEEE-Institute of Electrical and Electronics Engineers, 2024) Ozden, Burak Ahmet; Cogen, Fatih; Aydin, Erdogan; Ilhan, Haci; Wen, Miaowen; Department of Electrical and Electronics Engineering; Başar, Ertuğrul; Department of Electrical and Electronics Engineering; College of EngineeringToday's wireless communication networks have many requirements such as high data rate, high reliability, low latency, low error data transmission, and high energy efficiency. High-performance index modulation (IM) techniques and reconfigurable intelligent surface (RIS) technology, which has recently attracted the attention of researchers, are strong candidates to meet these requirements. This paper introduces a novel RIS-supported code IM-based receive spatial modulation (RIS-CIM-RSM) system. The proposed RIS-CIM-RSM system uses quadrature amplitude modulation (QAM) symbols, receive antenna indices, and spreading code indices for wireless data transmission. In the proposed system, an RIS applies a phase rotation that maximizes signal-to-noise ratio (SNR) to the signals coming to the reflecting elements and directs them to the selected receive antenna. Performance analyses of the proposed RIS-CIM-RSM system such as data rate, throughput, and energy saving are obtained. The results obtained show that the proposed RIS-CIM-RSM system is superior to the counterpart RIS-based IM systems in the literature in terms of data rate, throughput, energy saving, and error performance.Publication Metadata only AffectON: Incorporating affect into dialog generation(IEEE-Inst Electrical Electronics Engineers Inc, 2023) Bucinca, Zana; Department of Computer Engineering; Yemez, Yücel; Erzin, Engin; Sezgin, Tevfik Metin; Department of Computer Engineering; Koç Üniversitesi İş Bankası Yapay Zeka Uygulama ve Araştırma Merkezi (KUIS AI)/ Koç University İş Bank Artificial Intelligence Center (KUIS AI); College of EngineeringDue to its expressivity, natural language is paramount for explicit and implicit affective state communication among humans. The same linguistic inquiry (e.g., How are you?) might induce responses with different affects depending on the affective state of the conversational partner(s) and the context of the conversation. Yet, most dialog systems do not consider affect as constitutive aspect of response generation. In this article, we introduce AffectON, an approach for generating affective responses during inference. For generating language in a targeted affect, our approach leverages a probabilistic language model and an affective space. AffectON is language model agnostic, since it can work with probabilities generated by any language model (e.g., sequence-to-sequence models, neural language models, n-grams). Hence, it can be employed for both affective dialog and affective language generation. We experimented with affective dialog generation and evaluated the generated text objectively and subjectively. For the subjective part of the evaluation, we designed a custom user interface for rating and provided recommendations for the design of such interfaces. The results, both subjective and objective demonstrate that our approach is successful in pulling the generated language toward the targeted affect, with little sacrifice in syntactic coherence.Publication Metadata only An analytical framework for self-organizing peer-to-peer anti-entropy algorithms(Elsevier, 2010) N/A; Department of Computer Engineering; Department of Mathematics; Department of Mathematics; Department of Mathematics; Özkasap, Öznur; Çağlar, Mine; Yazıcı, Emine Şule; Küçükçifçi, Selda; Faculty Member; Faculty Member; Faculty Member; Faculty Member; Department of Computer Engineering; Department of Mathematics; College of Engineering; College of Sciences; College of Sciences; College of Sciences; 113507; 105131; 27432; 105252An analytical framework is developed for establishing exact performance measures for peer-to-peer (P2P) anti-entropy paradigms used in biologically inspired epidemic data dissemination. Major benefits of these paradigms are that they are fully distributed, self-organizing, utilize local data only via pair-wise interactions, and provide eventual consistency, reliability and scalability. We derive exact expressions for infection probabilities through elaborated counting techniques on a digraph. Considering the first passage times of a Markov chain based on these probabilities, we find the expected message delay experienced by each peer and its overall mean as a function of initial number of infectious peers. Further delay and overhead analysis is given through simulations and the analytical framework. The number of contacted peers at each round of the anti-entropy approach is an important parameter for both delay and overhead. These exact performance measures and theoretical results would be beneficial when utilizing the models in several P2P distributed system and network services Such as replicated servers, multicast protocols, loss recovery, failure detection and group membership management.Publication Open Access B-tensor: brain connectome tensor factorization for Alzheimer's disease(Institute of Electrical and Electronics Engineers (IEEE), 2021) Durusoy, Göktekin; Yıldırım, Zerrin; Dal, Demet Yüksel; Ulaşoğlu-Yıldız, Çiğdem; Kurt, Elif; Bayır, Güneş; Özacar, Erhan; Özarslan, Evren; Demirtaş-Tatlıdede, Aslı; Bilgiç, Başar; Demiralp, Tamer; Gürvit, Hakan; Acar, Burak; Department of Physics; Kabakçıoğlu, Alkan; Faculty Member; Department of Physics; College of Sciences; 49854AD is the highly severe part of the dementia spectrum and impairs cognitive abilities of individuals, bringing economic, societal and psychological burdens beyond the diseased. A promising approach in AD research is the analysis of structural and functional brain connectomes, i.e., sNETs and fNETs, respectively. We propose to use tensor representation (B-tensor) of uni-modal and multi-modal brain connectomes to define a low-dimensional space via tensor factorization. We show on a cohort of 47 subjects, spanning the spectrum of dementia, that diagnosis with an accuracy of 77% to 100% is achievable in a 5D connectome space using different structural and functional connectome constructions in a uni-modal and multi-modal fashion. We further show that multi-modal tensor factorization improves the results suggesting complementary information in structure and function. A neurological assessment of the connectivity patterns identified largely agrees with prior knowledge, yet also suggests new associations that may play a role in the disease progress.Publication Open Access Bilevel programming for generating discrete representations in multiobjective optimization(Springer, 2018) Kirlik, Gökhan; Department of Business Administration; Sayın, Serpil; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 6755The solution to a multiobjective optimization problem consists of the nondominated set that portrays all relevant trade-off information. The ultimate goal is to identify a Decision Maker's most preferred solution without generating the entire set of nondominated solutions. We propose a bilevel programming formulation that can be used to this end. The bilevel program is capable of delivering an efficient solution that maps into a given set, provided that one exits. If the Decision Maker's preferences are known a priori, they can be used to specify the given set. Alternatively, we propose a method to obtain a representation of the nondominated set when the Decision Maker's preferences are not available. This requires a thorough search of the outcome space. The search can be facilitated by a partitioning scheme similar to the ones used in global optimization. Since the bilevel programming formulation either finds a nondominated solution in a given partition element or determines that there is none, a representation with a specified coverage error level can be found in a finite number of iterations. While building a discrete representation, the algorithm also generates an approximation of the nondominated set within the specified error factor. We illustrate the algorithm on the multiobjective linear programming problem.