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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/6
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Publication Open Access Evolutionary multiobjective feature selection for sentiment analysis(Institute of Electrical and Electronics Engineers (IEEE), 2021) Pelin Angın; Deniz, Ayça; Department of International Relations; Angın, Merih; Faculty Member; Department of International Relations; College of Administrative Sciences and Economics; 308500Sentiment analysis is one of the prominent research areas in data mining and knowledge discovery, which has proven to be an effective technique for monitoring public opinion. The big data era with a high volume of data generated by a variety of sources has provided enhanced opportunities for utilizing sentiment analysis in various domains. In order to take best advantage of the high volume of data for accurate sentiment analysis, it is essential to clean the data before the analysis, as irrelevant or redundant data will hinder extracting valuable information. In this paper, we propose a hybrid feature selection algorithm to improve the performance of sentiment analysis tasks. Our proposed sentiment analysis approach builds a binary classification model based on two feature selection techniques: an entropy-based metric and an evolutionary algorithm. We have performed comprehensive experiments in two different domains using a benchmark dataset, Stanford Sentiment Treebank, and a real-world dataset we have created based on World Health Organization (WHO) public speeches regarding COVID-19. The proposed feature selection model is shown to achieve significant performance improvements in both datasets, increasing classification accuracy for all utilized machine learning and text representation technique combinations. Moreover, it achieves over 70% reduction in feature size, which provides efficiency in computation time and space.Publication Open Access On the capacity of diffusion-based molecular communications with SiNW FET-based receiver(Institute of Electrical and Electronics Engineers (IEEE), 2016) Department of Electrical and Electronics Engineering; Kuşcu, Murat; Akan, Özgür Barış; Faculty Member; Department of Electrical and Electronics Engineering; College of EngineeringMolecular communication (MC) is a bio-inspired communication method based on the exchange of molecules for information transfer among nanoscale devices. Although MC has been extensively studied from various aspects, limitations imposed by the physical design of transceiving units have been largely neglected in the literature. Recently, we have proposed a nanobioelectronic MC receiver architecture based on the nanoscale field effect transistor-based biosensor (bioFET) technology, providing noninvasive and sensitive molecular detection at nanoscale while producing electrical signals at the output. In this paper, we derive analytical closed-form expressions for the capacity and capacity-achieving input distribution for a memoryless MC channel with a silicon nanowire (SiNW) FET-based MC receiver. The resulting expressions could be used to optimize the information flow in MC systems equipped with nanobioelectronic receivers.Publication Open Access Quantum state transfer among crystallographic groups of N-V centers in diamond(Society of Photo-optical Instrumentation Engineers (SPIE), 2011) Department of Physics; Müstecaplıoğlu, Özgür Esat; Faculty Member; Department of Physics; College of Sciences; 1674We investigate collections of Nitrogen-Vacancy (N-V) Centers in diamond crystals coupled to a circuit QED system of a coplanar waveguide (CPWG) resonator. Our analysis reveals that different symmetry axes oriented N-V centers in the diamond host can be grouped into bosonic modes of collective quasi-spin wave excitations so that the hybrid system can be described as an analog of an exciton-polariton type cavity QED model. We examine such model for quantum state transfer among distinct crystallographic groups of N-V centers in a single diamond as well as two spatially distant diamonds. Rabi oscillations, mode entanglement, possible use of N-V classes as spin ensemble qubits and an implementation of continuous-time quantum random walk are discussed.Publication Open Access Power performance of a continuous-wave Cr2+:ZnSe laser at 2.4 7 ?m(Optica Publishing Group, 2000) Pollock, C.R.; Department of Physics; Sennaroğlu, Alphan; Konca, Ali Özgün; Faculty Member; Undergraduate Student; Department of Physics; College of Sciences; 23851; N/AContinuous-wave power performance of a Cr2+:znSe laser was investigated at 2.474 ?m. End pumped by a 1.583-?m NaCl:OH- laser, the resonator with a 3% transmitting output coupler produced as high as 250 mW of output power with a slope efficiency of 24.2%. Analysis of the laser efficiency data shows that the magnitude of the excited-state absorption cross section is less than 5% of the emission cross section in agreement with spectroscopic results. Numerical calculations further predict the optimum crystal length and absorption coefficient to be 2.5 cm and 0.49 cm-1, respectively, for continuous-wave operation.Publication Open Access Thiophene-based trimers for in vivo electronic functionalization of tissues(American Chemical Society (ACS), 2020) Mantione, Daniele; Dufil, Gwennael; Vallan, Lorenzo; Parker, Daniela; Brochon, Cyril; Cloutet, Eric; Hadziioannou, Georges; Berggren, Magnus; Stavrinidou, Eleni; Pavlopoulou, Eleni; Department of Mechanical Engineering; İstif, Emin; Faculty Member; Master Student; Department of Mechanical Engineering; College of EngineeringElectronic materials that can self-organize in vivo and form functional components along the tissue of interest can result in a seamless integration of the bioelectronic interface. Previously, we presented in vivo polymerization of the conjugated oligomer ETE-S in plants, forming conductors along the plant structure. The EDOT-thiophene-EDOT trimer with a sulfonate side group polymerized due to the native enzymatic activity of the plant and integrated within the plant cell wall. Here, we present the synthesis of three different conjugated trimers based on thiophene and EDOT or purely EDOT trimers that are able to polymerize enzymatically in physiological pH in vitro as well as in vivo along the roots of living plants. We show that by modulating the backbone and the side chain, we can tune the electronic properties of the resulting polymers as well as their localization and penetration within the root. Our work paves the way for the rational design of electronic materials that can self-organize in vivo for spatially controlled electronic functionalization of living tissue.Publication Open Access Minimum energy coding for wireless nanosensor networks(Institute of Electrical and Electronics Engineers (IEEE), 2012) Kocaoğlu, Murat; Akan, Özgür Barış; Faculty Member; College of EngineeringWireless nanosensor networks (WNSNs), which are collections of nanosensors with communication units, can be used for sensing and data collection with extremely high resolution and low power consumption for various applications. In order to realize WNSNs, it is essential to develop energy-efficient communication techniques, since nanonodes are severely energy-constrained. In this paper, a novel minimum energy coding scheme (MEC) is proposed to achieve energy-efficiency in WNSNs. Unlike the existing minimum energy codes, MEC maintains the desired Hamming distance, while minimizing energy, in order to provide reliability. It is analytically shown that, with MEC, codewords can be decoded perfectly for large code distance, if source set cardinality, M is less than inverse of symbol error probability, 1/ps. Performance analysis shows that MEC outperforms popular codes such as Hamming, Reed-Solomon and Golay in average energy per codeword sense.Publication Open Access Large-scale computational screening of MOF membranes and MOF-based polymer membranes for H2/N2 separations(American Chemical Society (ACS), 2019) Department of Chemical and Biological Engineering; Azar, Ayda Nemati Vesali; Velioğlu, Sadiye; Keskin, Seda; Department of Chemical and Biological Engineering; Graduate School of Sciences and Engineering; N/A; 200650; 40548Several thousands of metal organic frameworks (MOFs) have been reported to date, but the information on H-2/N-2 separation performances of MOF membranes is currently very limited in the literature. We report the first large-scale computational screening study that combines state-of-the-art molecular simulations, grand canonical Monte Carlo (GCMC) and molecular dynamics (MD), to predict H-2 permeability and H-2/N-2 selectivity of 3765 different types of MOF membranes. Results showed that MOF membranes offer very high H-2 permeabilities, 2.5 x 10(3) to 1.7 x 10(6) Barrer, and moderate H-2/N-2 membrane selectivities up to 7. The top 20 MOF membranes that exceed the polymeric membranes' upper bound for H-2/N-2 separation were identified based on the results of initial screening performed at infinite dilution condition. Molecular simulations were then carried out considering binary H-2/N-2 and quaternary H-2/N-2/CO2/CO mixtures to evaluate the separation performance of MOF membranes under industrial operating conditions. Lower H-2 permeabilities and higher N-2 permeabilities were obtained at binary mixture conditions compared to the ones obtained at infinite dilution due to the absence of multicomponent mixture effects in the latter. Structure performance relations of MOFs were also explored to provide molecular-level insights into the development of new MOF membranes that can offer both high H-2 permeability and high H-2/N-2 selectivity. Results showed that the most promising MOF membranes generally have large pore sizes (>6 A) as well as high surface areas (>3500 m(2)/g) and high pore volumes (>1 cm(3)/g). We finally examined H-2/N-2 separation potentials of the mixed matrix membranes (MMMs) in which the best MOF materials identified from our high-throughput screening were used as fillers in various polymers. Results showed that incorporation of MOFs into polymers almost doubles H-2 permeabilities and slightly enhances H-2/N-2 selectivities of polymer membranes, which can advance the current membrane technology for efficient H-2 purification.Publication Open Access Introduction to noise radar and its waveforms(Multidisciplinary Digital Publishing Institute (MDPI), 2020) De Palo, Francesco; Galati, Gaspare; Pavan, Gabriele; Wasserzier, Christoph; Department of Electrical and Electronics Engineering; Savcı, Kubilay; Department of Electrical and Electronics Engineering; Graduate School of Sciences and EngineeringIn the system-level design for both conventional radars and noise radars, a fundamental element is the use of waveforms suited to the particular application. In the military arena, low probability of intercept (LPI) and of exploitation (LPE) by the enemy are required, while in the civil context, the spectrum occupancy is a more and more important requirement, because of the growing request by non-radar applications; hence, a plurality of nearby radars may be obliged to transmit in the same band. All these requirements are satisfied by noise radar technology. After an overview of the main noise radar features and design problems, this paper summarizes recent developments in "tailoring" pseudo-random sequences plus a novel tailoring method aiming for an increase of detection performance whilst enabling to produce a (virtually) unlimited number of noise-like waveforms usable in different applications.Publication Open Access Leveraging frequency based salient spatial sound localization to improve 360 degrees video saliency prediction(Institute of Electrical and Electronics Engineers (IEEE), 2021) Çökelek, Mert; İmamoğlu, Nevrez; Özçınar, Çağrı; Department of Computer Engineering; Erdem, Aykut; Faculty Member; Department of Computer Engineering; College of Engineering; 20331Virtual and augmented reality (VR/AR) systems dramatically gained in popularity with various application areas such as gaming, social media, and communication. It is therefore a crucial task to have the knowhow to efficiently utilize, store or deliver 360° videos for end-users. Towards this aim, researchers have been developing deep neural network models for 360° multimedia processing and computer vision fields. In this line of work, an important research direction is to build models that can learn and predict the observers' attention on 360° videos to obtain so-called saliency maps computationally. Although there are a few saliency models proposed for this purpose, these models generally consider only visual cues in video frames by neglecting audio cues from sound sources. In this study, an unsupervised frequency-based saliency model is presented for predicting the strength and location of saliency in spatial audio. The prediction of salient audio cues is then used as audio bias on the video saliency predictions of state-of-the-art models. Our experiments yield promising results and show that integrating the proposed spatial audio bias into the existing video saliency models consistently improves their performance.Publication Open Access Uplink achievable rate maximization for reconfigurable intelligent surface aided millimeter wave systems with resolution-adaptive ADCs(Institute of Electrical and Electronics Engineers (IEEE), 2021) Xiu, Yue; Zhao, Jun; Di Renzo, Marco; Sun, Wei; Gui, Guan; Wei, Ning; Department of Electrical and Electronics Engineering; Başar, Ertuğrul; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; 149116In this letter, we investigate the uplink of a reconfigurable intelligent surface (RIS)-aided millimeter-wave (mmWave) multi-user system. In the considered system, however, problems with hardware cost and power consumption arise when massive antenna arrays coupled with power-demanding analog-todigital converters (ADCs) are employed. To account for practical hardware complexity, we consider that the access point (AP) is equipped with resolution-adaptive analog-to-digital converters (RADCs). We maximize the achievable rate under hardware constraints by jointly optimizing the ADC quantization bits, the RIS phase shifts, and the beam selection matrix. The formulated problem is non-convex. To efficiently tackle this problem, a block coordinated descent (BCD)-based algorithm is proposed. Simulations demonstrate that an RIS can mitigate the hardware loss due to the use of RADCs, and that the proposed BCD-based algorithm outperforms state-of-the-art algorithms.