WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7150
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Article Citation - WoS: 40Citation - Scopus: 38Anisotropic and Outstanding Mechanical, Thermal Conduction, Optical, and Piezoelectric Responses in a Novel Semiconducting Bcn Monolayer Confirmed by First-Principles and Machine Learning(Elsevier, 2022) Mortazavi, Bohayra; Fazel Shojaei; Yağmurcukardeş, Mehmet; Alexander Shapeev; Xiaoying ZhuangGraphene-like nanomembranes made of the neighboring elements of boron, carbon and nitrogen elements, are well-known of showing outstanding physical properties. Herein, with the aid of density functional theory (DFT) calculations, various atomic configurations of the graphene-like BCN nanosheets are investigated. DFT results reveal that depending on the atomic arrangement, the BCN monolayers may display semimetallic Dirac cone or semiconducting electronic nature. BCN nanosheets are also found to exhibit high piezoelectricity and carrier mobilities with considerable in-plane anisotropy, depending on the atomic arrangement. For the predicted most stable BCN monolayer, thermal and mechanical properties are explored using machine learning interatomic potentials. The room temperature tensile strength and lattice thermal conductivity of the most stable BCN monolayer are estimated to be orientation-dependent and remarkably high, over 78 GPa and 290 W/m.K, respectively. In addition, the thermal expansion coefficient of the monolayer BCN at room temperature is estimated to be −3.2 × 10−6 K−1, which is close to that of the graphene. The piezoelectric response of the herein proposed BCN lattice is also predicted to be close to that of the h-BN monolayer. Presented results highlight outstanding physics of the BCN nanosheets.Conference Object Citation - WoS: 18Citation - Scopus: 25Adaptation and Use of Subjectivity Lexicons for Domain Dependent Sentiment Classification(Institute of Electrical and Electronics Engineers Inc., 2012) Dehkharghani, Rahim; Yanıkoğlu, Berrin; Tapucu, Dilek; Saygın, YücelSentiment analysis refers to the automatic extraction of sentiments from a natural language text. We study the effect of subjectivity-based features on sentiment classification on two lexicons and also propose new subjectivity-based features for sentiment classification. The subjectivity-based features we experiment with are based on the average word polarity and the new features that we propose are based on the occurrence of subjective words in review texts. Experimental results on hotel and movie reviews show an overall accuracy of about 84% and 71% in hotel and movie review domains respectively; improving the baseline using just the average word polarities by about 2% points. © 2012 IEEE.Conference Object Citation - WoS: 22Citation - Scopus: 29Learning Domain-Specific Polarity Lexicons(Institute of Electrical and Electronics Engineers Inc., 2012) Demiröz, Gülşen; Yanıkoğlu, Berrin; Tapucu, Dilek; Saygın, YücelSentiment analysis aims to automatically estimate the sentiment in a given text as positive or negative. Polarity lexicons, often used in sentiment analysis, indicate how positive or negative each term in the lexicon is. However, since creating domain-specific polarity lexicons is expensive and time-consuming, researchers often use a general purpose or domain-independent lexicon. In this work, we address the problem of adapting a general purpose polarity lexicon to a specific domain and propose a simple yet effective adaptation algorithm. We experimented with two sets of reviews from the hotel and movie domains and observed that while our adaptation techniques changed the polarity values for only a small set of words, the overall test accuracy increased significantly: 77% to 83% in the hotel dataset and 61% to 66% in the movie dataset. © 2012 IEEE.