Hom-Lie-Hopf algebras

We studied both the double cross product and the bicrossproduct constructions for the Hom-Hopf algebras of general $(\alpha,\beta)$-type. This allows us to consider the universal enveloping Hom-Hopf algebras of Hom-Lie algebras, which are of $(\alpha,{\rm Id})$-type. We show that the universal enveloping Hom-Hopf algebras of a matched pair of Hom-Lie algebras form a matched pair of Hom-Hopf algebras. We observe also that, the semi-dualization of a double cross product Hom-Hopf algebra is a bicrossproduct Hom-Hopf algebra. In particular, we apply this result to the universal enveloping Hom-Hopf algebras of a matched pair of Hom-Lie algebras to obtain Hom-Lie-Hopf algebras

Self-training Guided Adversarial Domain Adaptation For Thermal Imagery

Deep models trained on large-scale RGB image datasets have shown tremendous success. It is important to apply such deep models to real-world problems. However, these models suffer from a performance bottleneck under illumination changes. Thermal IR cameras are more robust against such changes, and thus can be very useful for the real-world problems. In order to investigate efficacy of combining feature-rich visible spectrum and thermal image modalities, we propose an unsupervised domain adaptation method which does not require RGB-to-thermal image pairs. We employ large-scale RGB dataset MS-COCO as source domain and thermal dataset FLIR ADAS as target domain to demonstrate results of our method. Although adversarial domain adaptation methods aim to align the distributions of source and target domains, simply aligning the distributions cannot guarantee perfect generalization to the target domain. To this end, we propose a self-training guided adversarial domain adaptation method to promote generalization capabilities of adversarial domain adaptation methods. To perform self-training, pseudo labels are assigned to the samples on the target thermal domain to learn more generalized representations for the target domain. Extensive experimental analyses show that our proposed method achieves better results than the state-of-the-art adversarial domain adaptation methods. The code and models are publicly available.Comment: Accepted to CVPR 2021 Perception Beyond the Visible Spectrum (PBVS) worksho

HUMAN CAPITAL HETEROGENEITY AND ORGANIZATIONAL PERFORMANCE ANALYSIS: AN EMPIRICAL STUDY ABOUT INTERNATIONAL HOTEL CHAINS IN TURKEY

Today, workforce diversity is not only a legal requirement for organizations, but it is also a must to survive in a highly competitive business environment. The prime motive for this study is to investigate the relationship between workforce diversity and perception of discrimination. The basic hypothesis of the study is that as the workforce diversity increases, the perception of discrimination decreases. In order to test the hypothesis, a survey is carried out international hotel chains in Istanbul. There are 19 international hotel chains in Turkey. In this study research is designed to understand human capital heterogeneity pattern of international chains of hotel industry and how this contribute organizational culture strategically that help to manage organizational performance much more efficiently with cross sectional data. Globalization of markets, changing demographics in the labor market, new business strategies requiring team work and the shift from a manufacturing to a service economy are the prime reasons for human capital heterogeneity (HCH). HCH improves the organizational capabilities in terms of flexibility, creativity, problem solving and competitive advantage. Especially in the service sector, in order to gain competitive advantage, organizations need a diverse workforce for both understanding the diverse needs of customers and answering to these needs in a prompt and proper way

Kitlesel Açık Çevrimiçi Kurslardaki Katılımcı Profillerinin Yapay Sinir Agı Kullanılarak Sınıflandırılması (Classification of Participants Profiles in MOOCs Using Neural Networks [in Turkish])

Son yıllarda, özellikle bilgisayar mühendisligi egitimi alanında, kitlesel açık çevrimiçi kurslara (KAÇK) artan bir ilgi söz konusudur. Bu ilgi bireylerin davranısları, özellikleri ve tercihlerinin anlasılması öneminin altını çizmektedir. Böyle bir anlayıs gelistirmek, sıklıkla oyun gelistirme alanında kullanılan kisilik profilleme gibi yenilikçi teknikleri uyarlayarak KAÇK tasarım sürecini gelistirmek için çesitli yollar gerektirmektedir. Bu çalısma, bir kisilik referansı olarak Myers-Briggs Tip Göstergesi (MBTG) kullanılarak katılımcıları (özellikle eksik veri durumlarında) sınıflandırmak için bir yöntem önermektedir. Amaç, KAÇK izleyicileri hakkında ayrıstırıcı bir bakıs sunmak için KAÇK katılımcı profillerini MBTG kullanarak arastırmaktır. Bu amaçla, bir bilgisayar mühendisligi kursunda 20 soruluk bir çevrimiçi anket kullanılmıstır: Muhatapların (N=75) cevapları yardımıyla katılımcıların kisilik tipleri belirlenmistir. Dahası, bir makine ögrenimi modeli bireylerin sınıflandırması için önerilmistir. Sonuçlar, geri yayılımlı (GY) yapay sinir agının hem egitim süreci (performans=%100) hem de test süreci için (performans=%93,3) uygun oldugunu göstermistir. Bu bilgilerin ısıgında, yaklasımımızın MBTG açısından KAÇK katılımcılarının sınıflandırılabilirliklerini arastırmak için kullanılabilecek özgün bir yaklasım olarak kabul edilebilir

Evaluation of the hematologic system as a marker of subclinical inflammation in hyperemesis gravidarum: a case control study

Objectives: Current evidence suggests that subclinical inflammation plays a significant role in the development of hyperemesis gravidarum (HEG). Simple hematological markers, such as mean platelet volume (MPV), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR), have been shown to reflect inflammatory burden and disease activity in several disorders. This study aimed to determine the diagnostic value of these hematological parameters for HEG. Material and methods: A total of 54 HEG patients and 58 age- and gestational-age-matched control subjects were studied. NLR, MPV, PLR, platelet distribution width (PDW), and red cell distribution width (RDW) values in all patients were calculated and recorded from complete blood cell counts. Results: For HEG patients, the median NLR was 3.2 (1.6–7.1), and the median PLR was 143.7 (78.1–334.6); for control subjects, the values were 2.1 (1.0–4.7) and 93.1 (47.3–194.7), respectively. Although both the NLR and PLR of HEG patients were found to be significantly higher than in the controls, no significant difference was found between the study groups in terms of MPV, RDW, or PDW. Correlation analysis revealed a significant correlation between NLR and CRP (r = 0.872, p < 0.001). Conclusions: Our results show that peripheral blood NLR and PLR values can reflect inflammatory burden in HEG patients and can be used as markers for HEG