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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 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 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.Publication Open Access Distinguishing genuine Imperial Qing Dynasty porcelain from ancient replicas by on-site non-invasive XRF and Raman spectroscopy(Multidisciplinary Digital Publishing Institute (MDPI), 2022) Colomban, P.; Gironda, M.; d'Abrigeon, P.; Franci, Gülsu Şimşek; Researcher; Koç University Surface Science and Technology Center (KUYTAM) / Koç Üniversitesi Yüzey Teknolojileri Araştırmaları Merkezi (KUYTAM)The combined use of non-invasive on-site portable techniques, Raman microscopy, and X-ray fluorescence spectroscopy on seven imperial bowls and two decorated dishes, attributed to the reigns of the Kangxi, Yongzheng, Qianlong, and Daoguang emperors (Qing Dynasty), allows the identification of the coloring agents/opacifiers and composition types of the glazes and painted enamels. Particular attention is paid to the analysis of the elements used in the (blue) marks and those found in the blue, yellow, red, and honey/gilded backgrounds on which, or in reserve, a floral motif is principally drawn. The honey-colored background is made with gold nanoparticles associated with a lead- and arsenic-based flux. One of the red backgrounds is also based on gold nanoparticles, the second containing copper nanoparticles, both in lead-based silicate enamels like the blue and yellow backgrounds. Tin and arsenic are observed, but cassiterite (SnO2) is clearly observed in one of the painted decors (dish) and in A676 yellow, whereas lead (calcium/potassium) arsenate is identified in most of the enamels. Yellow color is achieved with Pb-Sn-Sb pyrochlore (Naples yellow) with various Sb contents, although green color is mainly based on lead-tin oxide mixed with blue enamel. The technical solutions appear very different from one object to another, which leads one to think that each bowl is really a unique object and not an item produced in small series. The visual examination of some marks shows that they were made in overglaze (A608, A616, A630, A672). It is obvious that different types of cobalt sources were used for the imprinting of the marks: cobalt rich in manganese for bowl A615 (Yongzheng reign), cobalt rich in arsenic for bowl A613 (but not the blue mark), cobalt with copper (A616), and cobalt rich in arsenic and copper (A672). Thus, we have a variety of cobalt sources/mixtures. The high purity of cobalt used for A677 bowl indicates a production after similar to 1830-1850.Publication Open Access Online failure diagnosis in interdependent networks(Springer Nature, 2021) Akbari, Vahid; N/A; Shiri, Davood; PhD Student; Graduate School of Sciences and EngineeringIn interdependent networks, nodes are connected to each other with respect to their failure dependency relations. As a result of this dependency, a failure in one of the nodes of one of the networks within a system of several interdependent networks can cause the failure of the entire system. Diagnosing the initial source of the failure in a collapsed system of interdependent networks is an important problem to be addressed. We study an online failure diagnosis problem defined on a collapsed system of interdependent networks where the source of the failure is at an unknown node (v). In this problem, each node of the system has a positive inspection cost and the source of the failure is diagnosed when v is inspected. The objective is to provide an online algorithm which considers dependency relations between nodes and diagnoses v with minimum total inspection cost. We address this problem from worst-case competitive analysis perspective for the first time. In this approach, solutions which are provided under incomplete information are compared with the best solution that is provided in presence of complete information using the competitive ratio (CR) notion. We give a lower bound of the CR for deterministic online algorithms and prove its tightness by providing an optimal deterministic online algorithm. Furthermore, we provide a lower bound on the expected CR of randomized online algorithms and prove its tightness by presenting an optimal randomized online algorithm. We prove that randomized algorithms are able to obtain better CR compared to deterministic algorithms in the expected sense for this online problem.Publication Open Access Impact of rehabilitation on fatigue in post-Covid-19 patients: a systematic review and meta-analysis(Multidisciplinary Digital Publishing Institute (MDPI), 2022) de Sire, Alessandro; Moggio, Lucrezia; Marotta, Nicola; Agostini, Francesco; Tasselli, Anna; Ferrante, Vera Drago; Curci, Claudio; Calafiore, Dario; Ferraro, Francesco; Bernetti, Andrea; Ammendolia, Antonio; Taşkıran, Özden Özyemişçi; Faculty Member; School of Medicine; 133091The post-COVID-19 syndrome may affect patients after the COVID-19 post-acute phase. In particular, the 69% of patients reported persistent fatigue at the discharge. To date, no clear data are available regarding the most effective rehabilitative approaches for the treatment of this condition. Thus, this systematic review aimed to evaluate the rehabilitation treatment's efficacy on fatigue in post-COVID-19 patients. We systematically searched PubMed, Scopus, and Web of Science databases to find longitudinal study designs presenting: post-COVID-19 patients as participants; a rehabilitative approach aimed to reduce post-COVID-19 syndrome as intervention; and fatigue intensity assessed through an evaluation tool that quantified the perceived exertion (i.e., fatigue severity scale, FSS; Borg Scale (BS); Borg Category Ratio 10, CR10; Checklist Individual Strength (CIS) fatigue scale; FACIT (Functional Assessment of Chronic Illness Therapy) fatigue scale). The present systematic review protocol was registered on PROSPERO (registration number CRD42021284058). Out of 704 articles, 6 studies were included. Nearly all patients showed COVID-19-related fatigue, and after the rehabilitation treatment, only 17% of subjects reported the persistency of symptoms. The overall effect size reported a -1.40 decrease in Borg Category Ratio 10 with a SE of 0.05 and a 95% CI between -1.50 and -1.30 (p < 0.001). The present systematic review and meta-analysis underlines the rehabilitation role in the fatigue reduction in patients affected by post-COVID-19 syndrome.Publication Open Access Self-supervised monocular scene decomposition and depth estimation(IEEE Computer Society, 2021) Department of Computer Engineering; N/A; Güney, Fatma; Safadoust, Sadra; 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 Engineering; Graduate School of Sciences and Engineering; 187939; N/ASelf-supervised monocular depth estimation approaches either ignore independently moving objects in the scene or need a separate segmentation step to identify them. We propose MonoDepthSeg to jointly estimate depth and segment moving objects from monocular video without using any ground-truth labels. We decompose the scene into a fixed number of components where each component corresponds to a region on the image with its own transformation matrix representing its motion. We estimate both the mask and the motion of each component efficiently with a shared encoder. We evaluate our method on three driving datasets and show that our model clearly improves depth estimation while decomposing the scene into separately moving components.Publication Open Access A diversity combination model incorporating an inward bias for interaural time-level difference cue integration in sound lateralization(Multidisciplinary Digital Publishing Institute (MDPI), 2020) N/A; Department of Computer Engineering; Mojtahedi, Sina; Erzin, Engin; Ungan, Pekcan; Faculty Member; Faculty Member; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; School of Medicine; N/A; 34503; N/AA sound source with non-zero azimuth leads to interaural time level differences (ITD and ILD). Studies on hearing system imply that these cues are encoded in different parts of the brain, but combined to produce a single lateralization percept as evidenced by experiments indicating trading between them. According to the duplex theory of sound lateralization, ITD and ILD play a more significant role in low-frequency and high-frequency stimulations, respectively. In this study, ITD and ILD, which were extracted from a generic head-related transfer functions, were imposed on a complex sound consisting of two low- and seven high-frequency tones. Two-alternative forced-choice behavioral tests were employed to assess the accuracy in identifying a change in lateralization. Based on a diversity combination model and using the error rate data obtained from the tests, the weights of the ITD and ILD cues in their integration were determined by incorporating a bias observed for inward shifts. The weights of the two cues were found to change with the azimuth of the sound source. While the ILD appears to be the optimal cue for the azimuths near the midline, the ITD and ILD weights turn to be balanced for the azimuths far from the midline.