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The roles of adolescents’ emotional problems and social media addiction on their self-esteem
No full textAdolescents' emotional problems and excessive social media use could deteriorate their self-esteem. The aim of the present study was to investigate the contributions of adolescents' emotional problems and social media addiction to their self-esteem, with the particular interest of testing the mediating role of the social media addiction on the association between emotional problems and self-esteem. Participants were 221 adolescents (49.3% female) aging from 13 to 17 years (M = 15.86, SD = 0.91). Participants reported on their emotional problems, social media addiction, and self-esteem. Results from regression analyses showed that the higher levels of emotional problems and social media addiction were related to lower levels of self-esteem. In addition, social media addiction partiality mediated the association between emotional problems and self-esteem indicating that the adolescents with higher levels of emotional problems tended to report higher levels of social media addiction and, in turn this tendency was related to lower levels of self-esteem
Branch-and-price approach for robust parallel machine scheduling with sequence-dependent setup times
No full textThis paper studies a machine scheduling problem that minimizes the worst-case total tardiness for unrelated parallel machines with sequence-dependent setup and uncertain processing times. We propose a robust optimization reformulation of the related machine scheduling problem and discuss several important properties of the mathematical model and the reformulation approach. The proposed model generalizes robust parallel machine scheduling problems by including sequence-dependent setup times and ellipsoidal uncertainty sets. Another key contribution of the paper is to show that scheduling problems usually have alternative optimal solutions for the worst-case tardiness objective, whose performance under nominal processing times may vary or vice a versa. This issue has been addressed by studying the Pareto efficient extensions of the proposed robust optimization models to provide solutions that are immune to changes in processing times. A branch-and-price algorithm has been developed to solve realistically sized instances in less than one hour, which a commercial solver cannot achieve. Numerical results show the effectiveness of the proposed approach since realistically sized instances such as (4 machines, 32 jobs) and (150 machines, 300 jobs) can be solved to optimality within the time limit, and the (average) objective function value improvement made by the robust approach can get as high as 56% compared with the (nominal) optimal solutions that ignore uncertainty in problem data.Home Appliances Department of the Vestel Electronics Compan
DiBLIoT: A distributed blacklisting protocol for iot device classification using the hashgraph consensus algorithm
No full textIndustrial applications require highly reliable, secure, low-power and low-delay communications. However, wireless communication links in the industrial environment suffer from various channel impairments which can compromise the above requirements. This paper presents a new reliable blacklisting protocol for ensuring the Internet of Things (IoT) network security and mitigating the effects of interference caused by multipath Rayleigh fading using a distributed approach. The proposed blacklisting protocol is simulated over a distributed IoT network setup where flat Rayleigh fading disrupts Message Queuing Telemetry Transport (MQTT) communications. Distributed servers jointly decide in real-Time whether to blacklist a device after individually performing anomaly detection and submitting their results to the hashgraph network. The IoT devices are classified by a device fingerprinting method using various machine learning (ML) algorithms that are trained with real-Time packet capture data. The proposed blacklisting protocol is shown to increase the accuracy of blacklisting malignant devices from 42% to 82% as the number of servers increases from one to five for mixed attacks. It also achieves higher accuracies ranging between 47.2%-97.6% versus 47.4%-90.7% compared to the related work for Denial of Service (DoS) attacks. The proposed protocol is particularly suitable for the Industrial IoT (IIoT) in mitigating the effects of harsh communication environments in manufacturing facilities
A new calibration method for charm jet identification validated with proton-proton collision events at √s = 13 TeV
No full textMany measurements at the LHC require efficient identification of heavy-flavour jets, i.e. jets originating from bottom (b) or charm (c) quarks. An overview of the algorithms used to identify c jets is described and a novel method to calibrate them is presented. This new method adjusts the entire distributions of the outputs obtained when the algorithms are applied to jets of different flavours. It is based on an iterative approach exploiting three distinct control regions that are enriched with either b jets, c jets, or light-flavour and gluon jets. Results are presented in the form of correction factors evaluated using proton-proton collision data with an integrated luminosity of 41.5 fb−1 at √s = 13 TeV, collected by the CMS experiment in 2017. The closure of the method is tested by applying the measured correction factors on simulated data sets and checking the agreement between the adjusted simulation and collision data. Furthermore, a validation is performed by testing the method on pseudodata, which emulate various mismodelling conditions. The calibrated results enable the use of the full distributions of heavy-flavour identification algorithm outputs, e.g. as inputs to machine-learning models. Thus, they are expected to increase the sensitivity of future physics analyses.The Austrian Federal Ministry of Education, Science and Research and the Austrian Science Fund; the Belgian Fonds de la Recherche Scientifique, and Fonds voor Wetenschappel 1/4k Onderzoek; the Brazilian Funding Agencies (CNPq, CAPES, FAPERJ, FAPERGS, and FAPESP); the Bulgarian Ministry of Education and Science, and the Bulgarian National Science Fund; CERN; the Chinese Academy of Sciences, Ministry of Science and Technology, and National Natural Science Foundation of China; the Ministerio de Ciencia Tecnologia e Innovacion (MINCIENCIAS), Colombia; the Croatian Ministry of Science, Education and Sport, and the Croatian Science Foundation; the Research and Innovation Foundation, Cyprus; the Secretariat for Higher Education, Science, Technology and Innovation, Ecuador; the Ministry of Education and Research, Estonian Research Council via PRG780, PRG803 and PRG445 and European Regional Development Fund, Estonia; the Academy of Finland, Finnish Ministry of Education and Culture, and Helsinki Institute of Physics; the Institut National de Physique Nucleaire et de Physique des Particules/CNRS, and Commissariat a l'Energie Atomique et aux Energies Alternatives/CEA, France; the Bundesministerium fur Bildung und Forschung, the Deutsche Forschungsgemeinschaft (DFG), under Germany's Excellence Strategy EXC 2121 "Quantum Universe" -390833306, and under project number 400140256 - GRK2497, and Helmholtz-Gemeinschaft Deutscher Forschungszentren, Germany; the General Secretariat for Research and Innovation, Greece; the National Research, Development and Innovation Fund, Hungary; the Department of Atomic Energy and the Department of Science and Technology, India; the Institute for Studies in Theoretical Physics and Mathematics, Iran; the Science Foundation, Ireland; the Istituto Nazionale di Fisica Nucleare, Italy; the Ministry of Science, ICT and Future Planning, and National Research Foundation (NRF), Republic of Korea; the Ministry of Education and Science of the Republic of Latvia; the Lithuanian Academy of Sciences; the Ministry of Education, and University of Malaya (Malaysia); the Ministry of Science of Montenegro; the Mexican Funding Agencies (BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI); the Ministry of Business, Innovation and Employment, New Zealand; the Pakistan Atomic Energy Commission; the Ministry of Science and Higher Education and the National Science Centre, Poland; the Fundacao para a Ciencia e a Tecnologia, grants CERN/FIS-PAR/0025/2019 and CERN/FIS-INS/0032/2019, Portugal; JINR, Dubna; the Ministry of Education and Science of the Russian Federation, the Federal Agency of Atomic Energy of the Russian Federation, Russian Academy of Sciences, the Russian Foundation for Basic Research, and the National Research Center "Kurchatov Institute"; the Ministry of Education, Science and Technological Development of Serbia; the Secretaria de Estado de Investigacion, Desarrollo e Innovacion, Programa Consolider-Ingenio 2010, Plan Estatal de Investigacion Cientifica y Tecnica y de Innovacion 2017-2020, research project IDI-2018-000174 del Principado de Asturias, and Fondo Europeo de Desarrollo Regional, Spain; the Ministry of Science, Technology and Research, Sri Lanka; the Swiss Funding Agencies (ETH Board, ETH Zurich, PSI, SNF, UniZH, Canton Zurich, and SER); the Ministry of Science and Technology, Taipei; the Thailand Center of Excellence in P
hysics, the Institute for the Promotion of Teaching Science and Technology of Thailand, Special Task Force for Activating Research and the National Science and Technology Development Agency of Thailand; the Scientific and Technical Research Council of Turkey, and Turkish Atomic Energy Authority; the National Academy of Sciences of Ukraine; the Science and Technology Facilities Council, U.K.; the US Department of Energy, and the US National Science Foundation.
Individuals have received support from the Marie-Curie programme and the European Research Council and Horizon 2020 Grant, contract Nos. 675440, 724704, 752730, 758316, 765710, 824093, 884104, and COST Action CA16108 (European Union) the Leventis Foundation; the Alfred P. Sloan Foundation; the Alexander von Humboldt Foundation; the Belgian Federal Science Policy Office; the Fonds pour la Formation a la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); the F.R.S.-FNRS and FWO (Belgium) under the "Excellence of Science-EOS"-be.h project n. 30820817; the Be 1/4 ing Municipal Science & Technology Commission, No. Z191100007219010; the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Lendulet ("Momentum") Programme and the Janos Bolyai Research Scholarship of the Hungarian Academy of Sciences, the New National Excellence Program UNKP, the NKFIA research grants 123842, 123959, 124845, 124850, 125105, 128713, 128786, and 129058 (Hungary); the Council of Scientific and Industrial Research, India; the Latvian Council of Science; the National Science Center (Poland), contracts Opus 2014/15/B/ST2/03998 and 2015/19/B/ST2/02861; the Fundacao para a Ciencia e a Tecnologia, grant FCT CEECIND/01334/2018; the National Priorities Research Program by Qatar National Research Fund; the Ministry of Science and Higher Education, projects no. 14.W03.31.0026 and no. FSWW-2020-0008, and the Russian Foundation for Basic Research, project No.19-42-703014 (Russia); the Programa de Excelencia Maria de Maeztu, and the Programa Severo Ochoa del Principado de Asturias; the Stavros Niarchos Foundation (Greece); the Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University, and the Chulalongkorn Academic into Its 2nd Century Project Advancement Project (Thailand); the Kavli Foundation; the Nvidia Corporation; the SuperMicro Corporation; the Welch Foundation, contract C-1845; and the Weston Havens Foundation (U.S.A.).Publisher versio
A learning-based dependency to constituency conversion algorithm for the turkish language
No full textThis study aims to create the very first dependency-to-constituency conversion algorithm optimised for Turkish language. For this purpose, a state-of-the-art morphologic analyser (Yıldız et al., 2019) and a feature-based machine learning model was used. In order to enhance the performance of the conversion algorithm, bootstrap aggregating meta-algorithm was integrated. While creating the conversation algorithm, typological properties of Turkish were carefully considered. A comprehensive and manually annotated UD-style dependency treebank was the input, and constituency trees were the output of the conversion algorithm. A team of linguists manually annotated a set of constituency trees. These manually annotated trees were used as the gold standard to assess the performance of the algorithm. The conversion process yielded more than 8000 constituency trees whose UD-style dependency trees are also available on GitHub. In addition to its contribution to Turkish treebank resources, this study also offers a viable and easy-to-implement conversion algorithm that can be used to generate new constituency treebanks and training data for NLP resources like constituency parsers
A novel GBT-based approach for cross-channel fraud detection on real-world banking transactions
No full textThe most recent research on hundreds of financial institutions uncovered that only 26 % of them have a team assigned to detect cross-channel fraud. Due to the developing technologies, various fraud techniques have emerged and increased in digital environments. Fraud directly affects customer satisfaction. For instance, only in the UK, the total loss of fraud transactions was £1.26 billion in 2020. In this paper, we come up with a Gradient Boosting Tree (GBT)-based approach to efficiently detect cross-channel frauds. As part of our proposed approach, we also figured out a solution to generate training sets from imbalanced data, which also suffers from concept drift problems due to changing customer behaviors. We boost the performance of our GBT model by integrating additional demographic, economic, and behavioral features as a part of feature engineering. We evaluate the performance of our cross-channel fraud detection method on a real banking dataset which is highly imbalanced in terms of frauds which is another challenge in the fraud detection problem. We use our trained model to score real-time cross-channel transactions by a leading private bank in Turkey. As a result, our approach can catch almost 75 % of total fraud loss in a month with a low false-positive rate
Outage probability analysis of a vertical underwater wireless optical link subject to oceanic turbulence and pointing errors
No full textThe reliability of an underwater wireless optical communication (UWOC) network is seriously impacted by beam misalignment between transmitters (Txs) and receivers (Rxs). Also, the performance of UWOC systems can be affected by oceanic turbulence-induced fading due to fluctuations in the water refractive index as a result of variations in the pressure, water temperature, and salinity. In this work, we investigate the performance analysis of a vertical UWOC link subject to oceanic turbulence and pointing errors and further investigate the appropriate selection of link parameters to optimize link performance. This study is based on an accurate mathematical framework for link modeling while taking into account realistic Tx/Rx and channel parameters under different turbulence and beam misalignment conditions. We provide an analytical expression for calculating the link outage probability, whose accuracy is validated through numerical simulations. Last, the necessity of optimal Tx/Rx parameter selection to minimize the link outage is demonstrated. A laser beam is considered at the Tx, as well as an ultra-sensitive photodetector (silicon photo-multiplier) at the Rx to enable working at relatively long link ranges. The presented results give valuable insight into the practical aspects of deployment of UWOC networks.Alex Ekwueme Federal University Ndufu-Alike ; Fresnel Institute ; IMT-Atlantique ; Institut Français de Recherche pour l'Exploitation de la Mer ; European Cooperation in Science and Technolog
A semi-discrete numerical scheme for nonlocally regularized KdV-type equations
No full textA general class of KdV-type wave equations regularized with a convolution-type nonlocality in space is considered. The class differs from the class of the nonlinear nonlocal unidirectional wave equations previously studied by the addition of a linear convolution term involving third-order derivative. To solve the Cauchy problem we propose a semi-discrete numerical method based on a uniform spatial discretization, that is an extension of a previously published work of the present authors. We prove uniform convergence of the numerical method as the mesh size goes to zero. We also prove that the localization error resulting from localization to a finite domain is significantly less than a given threshold if the finite domain is large enough. To illustrate the theoretical results, some numerical experiments are carried out for the Rosenau-KdV equation, the Rosenau-BBM-KdV equation and a convolution-type integro-differential equation. The experiments conducted for three particular choices of the kernel function confirm the error estimates that we provide
Ottoman women's print network and their creative contribution to print culture in Turkey
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Success model of online food delivery system: The role of brand image in customer responses
No full textThere is a growing interest in understanding the factors affecting the success of online food delivery (OFD) systems because online food ordering has increased considerably in recent years. Hence, the purpose of this study is to investigate the effect of brand image on customer satisfaction and purchase intention based on the stimulus-organism-response (S-O-R) framework by adopting DeLone and McLean IS success model. A convenience sample of 251 respondents, who use the most popular OFD applications in 3 largest cities of Turkey, was surveyed by an online self-administered structured questionnaire. The results were first organized as descriptive statistics for observed variables and frequencies of demographic variables. In the second phase, confirmatory factor analysis (CFA) followed by structural equation modeling (SEM) was used to test the measurement and structural model. The results reveal that among OFD system success factors, only the system and service quality positively influence brand image, accounting for 46% of the variance. On the other hand, this study could not validate the proposed positive effect of information quality on brand image. For the role of brand image in customer responses, the findings evidence a significant positive effect of brand image on both customer satisfaction and intention to use. The variable explains 34% and 22% of the variance in satisfaction and purchase intention, respectively. In line with these results, this paper concludes that brand image can be introduced into the e-commerce success model as a new variable due to its partial mediating role and significant effects on customer responses.Publisher versio