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Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395

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End date: 2019Publisher: search.filters.publisher.IEEE

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Now showing 1 - 10 of 26
  • Conference Object
    Citation - WoS: 30
    Citation - Scopus: 38
    Software Defined Communication Framework for Smart Grid to Meet Energy Demands in Smart Cities
    (IEEE, 2019-04) Faheem, Muhammad; Umar, Muhammad; Butt, Rizwan Aslam; Raza, Basit; Ngadi, Md. Asri; Gungor, Vehbi Cagri
    In smart cities, the electricity is an essential component since it preserves a certain level of residents' life quality and provisions the entire spectrum of their economic activities. Thus, a smart way is essential to develop cities without disregarding energy issues. In this scope, the smart grid paradigm offers power supply in an efficient, sustainable and economical manner with minimal impact on the environment and can meet the future energy demands. However, real-time monitoring and control of the smart grid (SG) for continuous and quality-aware power supply in smart cities (SCs) is challenging and requires an advanced quality of service (QoS)-aware communication framework. In this context, this research aims to present a novel data-gathering scheme by using the Internet of software-defined mobile sinks (SDMSs) and wireless sensor networks (WSNs) in the smart grid. The extensive simulation results conducted through the EstiNet9.0 indicate that the designed scheme outperforms existing approaches and achieves its defined goals for events-drive applications in the SG.
  • Conference Object
    Citation - WoS: 11
    Citation - Scopus: 20
    ROI Detection in Mammogram Images Using Wavelet-Based Haralick and Hog Features
    (IEEE, 2018-12) Tasdemir, Sena Busra Yengec; Tasdemir, Kasim; Aydin, Zafer; Yengec Tasdemir, Sena Busra
    Digital mammography is a widespread medical imaging technique that is used for early detection and diagnosis of breast cancer. Detecting the region of interest (ROI) helps to locate the abnormal areas, which may be analyzed further by a radiologist or a CAD system. In this paper, a new classification method is proposed for ROI detection in mammography images. Features are extracted using Wavelet transform, Haralick and HOG descriptors. To reduce the number of dimensions and eliminate irrelevant features, a wrapper-based feature selection method is implemented. Several feature extraction methods and machine learning classifiers are compared by performing a leave-one-image-out cross-validation experiment on a difficult dataset. The proposed feature extraction method provides the best accuracy of 87.5% and the second-best area under curve (AUC) score of 84% when employed in a random forest classifier.
  • Conference Object
    Citation - Scopus: 2
    Planar MEMS Variable Optical Attenuators (VOAs) With Linear Attenuation-Voltage Characteristics
    (IEEE, 2019-05) Hah, Dooyoung
    Variable optical attenuators (VOAs) are essential components in wavelength division multiplexing (WDM) networks, light waveform generators, and optical fiber test equipment. Among various types of planar MEMS VOAs, a shutter type and a reflective type have been most frequently studied so far. In a shutter type, a knife-edge-like beam blocker is inserted in between the butt-coupled input and output fibers, partially obstructing the coupling between the fibers. In a reflective type, a mirror that is placed in the optical path controls the alignment between the fibers to result in attenuation. The movement of the shutter or the mirror is controlled by MEMS actuators, such as comb-drive actuators. In most of the planar MEMS VOAs reported, the relationship between the attenuation and the control voltage has been highly nonlinear. This nonlinearity results in uneven resolution throughout the attenuation range. Although this nonlinearity can be addressed by employing a control system, a structure-based solution is preferred, which can curtail the requirement of power consumption, and prevent control instability issues. In this study, shaped-finger comb-drive actuators are used to obtain a linear relationship between the control voltage and the attenuation in planar MEMS VOAs. Two types, i.e. shutter-type and reflective-type, of VOAs are examined. First, the objective differential equation is established based on attenuation-displacement relationships, electrostatic/mechanical force balance equation, and the design objective (linearity) equation. Then, the differential equation (in terms of 2-D comb capacitance) is solved by using the Euler's method, and the finger gaps are calculated by using a conformal mapping method. When a single comb-drive actuator is used, an excluded zone needs to be introduced around the region of small displacement. Effects of the width of the excluded zone to the device characteristics are studied. The issue of zone exclusion can be addressed by adopting dual (control and bias) combs. The effects of design parameters to the VOA performances are studied. It is shown that the planar MEMS VOAs with linear attenuation-voltage relationships can be designed successfully by using the proposed method.
  • Conference Object
    Citation - WoS: 18
    Citation - Scopus: 19
    Optimal Energy Management and Scheduling of a Microgrid in Grid-Connected and Islanded Modes
    (IEEE, 2019-09) Zacharia, L.; Tziovani, L.; Savva, M.; Hadjidemetriou, L.; Kyriakides, E.; Bintoudi, A. D.; Al-Agtash, S.
    Microgrids are becoming one of the main components of future smart grids. Ensuring their optimal and stable operation is of crucial importance and can be a challenging task. In this paper, two optimization algorithms are implemented for scheduling the microgrid operation in grid-connected and islanded modes, according to the priorities and objectives in each mode. For achieving an optimal operation at each mode, the proposed scheme is able to shed loads, define the generation level of the photovoltaics and regulate the charging/ discharging level of the Energy Storage System (ESS). The effectiveness of the proposed scheduling is demonstrated through an analytical real-time simulation, where various transitions between the grid-connected and islanded modes are considered. The results indicate that the proposed scheme is able to regulate successfully the energy flows of the microgrid even under various transitions.
  • Conference Object
    Multivariate Pseudo Wigner Ville Distribution Based Emotion Detection From Electrical Activity of Brain
    (IEEE, 2017) Ozel, Pinar; Akan, Aydin; Yilmaz, Bulent
    Recently, there has been a rapid development in multivariate signal analysis to determine joint oscillations for multiple data channels. The emotion elicitation in an electroencephalogram (EEG) is a novel area to evaluate methods for emotional differences from brain signals. In this paper, utilizing the idea of joint instantaneous frequency of multivariate data, a multivariate extension of pseudo Wigner distribution is used for emotion recognition from EEG signals, in which different window sizes are employed to interpret the results. As a preliminary study, the best results are obtained as 90%, 75%, 65% in terms of valence, arousal and dominance scale respectively for larger window size.
  • Conference Object
    Citation - WoS: 3
    Citation - Scopus: 8
    Mol-Eye: A New Metric for the Performance Evaluation of a Molecular Signal
    (IEEE, 2018-04) Turan, Meric; Kuran, Mehmet Sukru; Yilmaz, H. Birkan; Chae, Chan-Byoung; Tugcu, Tuna
    Inspired by the eye diagram in classical radio frequency (RF) based communications, the MOL-Eye diagram is proposed for the performance evaluation of a molecular signal within the context of molecular communication. Utilizing various features of this diagram, three new metrics for the performance evaluation of a molecular signal, namely the maximum eye height, standard deviation of received molecules, and counting SNR (CSNR) are introduced. The applicability of these performance metrics in this domain is verified by comparing the performance of binary concentration shift keying (BCSK) and BCSK with consecutive power adjustment (BCSK-CPA) modulation techniques in a vessel-like environment with laminar flow. The results show that, in addition to classical performance metrics such as bit-error rate and channel capacity, these performance metrics can also be used to show the advantage of an efficient modulation technique over a simpler one.
  • Conference Object
    Integral-Equation Study of Ray Effects and Natural-Mode Resonances in a 2-D Dielectric Prism
    (IEEE, 2015) Sukharevsky, Ilya O.; Altintas, Ayhan
    We analyze the interplay of two different types of electromagnetic behavior demonstrated by a 2-D dielectric prism: Geometrical Optics and resonance. As it is shown, the first is responsible, for instance, for enhanced reflection from an isosceles 90-degree prism of arbitrary epsilon and size, if illuminated from the base. The second is responsible for the peaks in the total scattering and absorption cross-sections (RCS) at the natural-mode frequencies. The numerical model is based on Nystrom discretization of Muller-type integral equations that provides guarantied convergence.
  • Conference Object
    Citation - WoS: 2
    Citation - Scopus: 1
    Feature Selection for Protein Dihedral Angle Prediction
    (IEEE, 2017) Aydin, Zafer; Kaynar, Oguz; Gormez, Yasin
    Three-dimensional structure prediction has crucial importance for bioinformatics and theoretical chemistry. One of the main steps of three-dimensional structure prediction is dihedral (torsion) angle prediction. As new feature extraction methods are developed the dimension of the input space increases considerably yielding longer model training and less accurate models due to noisy or redundant features. In this study, feature selection is employed for dimensionality reduction on one of the established benchmarks of protein 1D structure prediction. Experimental results show that the feature selection improves the accuracy of protein dihedral angle class prediction by 2% and can eliminate up to %82 of the features when random forest classifier is used. Accurate prediction of dihedral angles will eventually contribute to protein structure prediction.
  • Conference Object
    Citation - WoS: 1
    Citation - Scopus: 3
    Emotional State Analysis From EEG Signals via Noise-Assisted Multivariate Empirical Mode Decomposition Method
    (IEEE, 2017) Ozel, Pinar; Akan, Aydin; Yilmaz, Bulent
    Emotional state analysis is an interdisciplinary arena because of the many parameters that encompass the complex neural structure and electrical signals of the brain and in terms of emotional state differences. In recent years, emotional state data have been examined by using data-driven methods such as Empirical Mode Decomposition as well as classical time-frequency methods. Although Empirical Mode Decomposition has many advantages, it has disadvantages such as being designed for univariate data, prone to mode mixing, and providing signal via a sufficient number of the local extrema. To overcome these disadvantages, in this study, the Noise-Assisted Multivariate Empirical Mode Decomposition has been shown to classify the emotional state using electroencephalographic signals.
  • Conference Object
    Citation - WoS: 23
    Citation - Scopus: 25
    Designing and Modelling Selective Replication for Fault-Tolerant HPC Applications
    (IEEE, 2017-05) Subasi, Omer; Yalcin, Gulay; Zyulkyarov, Ferad; Unsal, Osman; Labarta, Jesus
    Fail-stop errors and Silent Data Corruptions (SDCs) are the most common failure modes for High Performance Computing (HPC) applications. There are studies that address fail-stop errors and studies that address SDCs. However few studies address both types of errors together. In this paper we propose a software-based selective replication technique for HPC applications for both fail-stop errors and SDCs. Since complete replication of applications can be costly in terms of resources, we develop a runtime-based technique for selective replication. Selective replication provides an opportunity to meet HPC reliability targets while decreasing resource costs. Our technique is low-overhead, automatic and completely transparent to the user.