İstinye Üniversitesi Kurumsal Akademik Arşivi
DSpace@İstinye, İstinye Üniversitesi tarafından doğrudan ve dolaylı olarak yayınlanan; kitap, makale, tez, bildiri, rapor, araştırma verisi gibi tüm akademik kaynakları uluslararası standartlarda dijital ortamda depolar, Üniversitenin akademik performansını izlemeye aracılık eder, kaynakları uzun süreli saklar ve telif haklarına uygun olarak Açık Erişime sunar.
Güncel Gönderiler
Test of CP-invariance of the Higgs boson in vector-boson fusion production and in its decay into four leptons
(Springer science and business media deutschland GmbH, 2024) Aad, G.; Abbott, B.; Beddall, Andrew John; Çetin, Serkant Ali; Öztürk, Sertaç; Şimşek, Sinem
A search for CP violation in the decay kinematics and vector-boson fusion production of the Higgs boson is performed in the H → ZZ* → 4ℓ (ℓ = e, μ) decay channel. The results are based on proton-proton collision data produced at the LHC at a centre-of-mass energy of 13 TeV and recorded by the ATLAS detector from 2015 to 2018, corresponding to an integrated luminosity of 139 fb−1. Matrix element-based optimal observables are used to constrain CP-odd couplings beyond the Standard Model in the framework of Standard Model effective field theory expressed in the Warsaw and Higgs bases. Differential fiducial cross-section measurements of the optimal observables are also performed, and a new fiducial cross-section measurement for vector-boson-fusion production is provided. All measurements are in agreement with the Standard Model prediction of a CP-even Higgs boson.
The ATLAS trigger system for LHC Run 3 and trigger performance in 2022
(Institute of physics, 2024) Aad, G.; Abbott, B.; Beddall, Andrew John; Çetin, Serkant Ali; Öztürk, Sertaç; Şimşek, Sinem; Uysal, Zekeriya
The ATLAS trigger system is a crucial component of the ATLAS experiment at the LHC. It is responsible for selecting events in line with the ATLAS physics programme. This paper presents an overview of the changes to the trigger and data acquisition system during the second long shutdown of the LHC, and shows the performance of the trigger system and its components in the proton-proton collisions during the 2022 commissioning period as well as its expected performance in proton-proton and heavy-ion collisions for the remainder of the third LHC data-taking period (2022–2025).
Clustering interval and triangular granular data: modeling, execution, and assessment
(Institute of electrical and electronics engineers inc., 2024) Tang, Yiming; Wu, Wenbin; Pedrycz, Witold; Gao, Jianwei; Hu, Xianghui; Deng, Zhaohong; Chen, Rui
In current granular clustering algorithms, numeric representatives were selected by users or an ordinary strategy, which seemed simple; meanwhile, weight settings for granular data could not adequately express their structural characteristics. Aiming at these problems, in this study, a new scheme called a granular weighted kernel fuzzy clustering (GWKFC) algorithm is put forward. We propose the representative selection and granularity generation (RSGG) algorithm enlightened by the density peak clustering (DPC) algorithm. We build interval and triangular granular data on the strength of numeric representatives obtained by RSGG under the principle of justifiable granularity (PJG), in which we establish some combinations of functions and boundary constraints and prove their properties. Furthermore, we present a novel distance formula via the kernel function for granular data and design new weights to affect the coverage and specificity of granular data. In addition, based upon these factors, we come up with the GWKFC algorithm of granular clustering, and its performance with different granularity is assessed. To sum up, a macro framework involving granular modeling, granular clustering, and assessment has been set up. Lastly, the GWKFC algorithm and ten other granular clustering algorithms are compared by experiments on some artificial and UCI datasets together with datasets with large data or those of high dimensionality. It is found that the GWKFC algorithm can provide better granular clustering results by contrast with other algorithms. The originality is embodied as follows. First, we improve the previous density radius and present the RSGG algorithm to acquire numeric representatives. Second, we propose a new strategy to determine granular data boundaries and further obtain novel weights enlightened by the idea of volume. Lastly, we employ the kernel function to calculate the distance between granular data, which has a stronger spatial division ability than the previous Euclidean distance.
Circular-sustainable-reliable waste management system design: a possibilistic multi-objective mixed-integer linear programming model
(Multidisciplinary digital publishing institute (MDPI), 2024) Tirkolaee, Erfan Babaee
Waste management involves the systematic collection, transportation, processing, and treatment of waste materials generated by human activities. It entails a variety of strategies and technologies to diminish environmental impacts, protect public health, and conserve resources. Consequently, providing an effective and comprehensive optimization approach plays a critical role in minimizing waste generation, maximizing recycling and reuse, and safely disposing of waste. This work develops a novel Possibilistic Multi-Objective Mixed-Integer Linear Programming (PMOMILP) model in order to formulate the problem and design a circular-sustainable-reliable waste management network, under uncertainty. The possibility of recycling and recovery are considered across incineration and disposal processes to address the main circular-economy principles. The objectives are to address sustainable development throughout minimizing the total cost, minimizing the environmental impact, and maximizing the reliability of the Waste Management System (WMS). The Lp-metric technique is then implemented into the model to tackle the multi-objectiveness. Several benchmarks are adapted from the literature in order to validate the efficacy of the proposed methodology, and are treated by CPLEX solver/GAMS software in less than 174.70 s, on average. Moreover, a set of sensitivity analyses is performed to appraise different scenarios and explore utilitarian managerial implications and decision aids. It is demonstrated that the configured WMS network is highly sensitive to the specific time period wherein the WMS does not fail.
Chemical composition and antimicrobial activity of essential oils obtained from inula germanica l.
(ACG publications, 2024) Güleç, Meltem; Yazıcı-Tütüniş, Seçil; İşçan, Gökalp; Demirci, Betül; Tan, Emir; Miski, Mahmut; Tan, Nur
The genus Inula (Asteraceae), consisting of over 100 species predominantly found in Asia, Europe, and Africa, is recognized for its antimicrobial properties. This study explores the chemical composition and antimicrobial activity of essential oils obtained from the aerial parts of Inula germanica L. through conventional (T) and modified (M1, M2) hydrodistillation methods. Using gas chromatography and gas chromatography-mass spectrometry, the conventional method (T) yielded alpha-bisabolol (30.1%) and 12-carboxyeudesma-3,11(13)-diene (14.9%) as major compounds. The modified method fraction M1 enriched monoterpenes such as trans-verbenol (9.5%), 1,8-cineole (9.5%), and cis-chrysanthenyl acetate (9.3%), whereas M2 was characterized by higher levels of sesquiterpenes like 12-carboxyeudesma-3,11(13)-diene (24.3%) and alpha-bisabolol (11.7%). The essential oils exhibited moderate to weak antimicrobial activity against tested bacterial and Candida strains, with minimum inhibitory concentrations (MICs) ranging from 125 to 2000 mu g/mL. Among all studied samples, M1 showed the best antimicrobial activity against Candida strains in the MIC range of 125-500 mu g/mL.
