5862 research outputs found
Sort by
Elite Origins of Democracy and Development in the Muslim World
No full textUsing an elite consensus/conflict analytical frame, this book examines why some majority Muslim countries perform so much better at democracy and/or development than others, questioning received wisdoms that Islam, authoritarianism, and underdevelopment go together. Identifying four distinct democracy and development outcomes in the Muslim world, four case studies are interrogated to show that there is more variability in democracy and development outcomes in Muslim majority countries than macro-historical studies and aggregate data have shown. By demonstrating that democracy and development outcomes in Muslim countries are the consequence of elite conflict and elite consensus, rather than the precepts or institutions of Islam, the book places the competition for power among contending elites, rather than Islam, at the center of the story of democracy and development in the Muslim world. This book will be of key interest to scholars and students of political development/development studies, democratization and autocratization studies, democracy promotion, and more broadly comparative politics. © 2024 Michael T. Rock and Soli Özel
Touchscreen Use and Its Relation To Attention Development in Young Children
No full textMobil ekran cihazlarının kullanımı okul öncesi çocuklar arasında hızla artmaktadır. Pasif ekran kullanımı (yani televizyon ve video izleme) ile dikkat gelişimi arasındaki ilişki literatürde yaygın olarak çalışılmış olsa da, aktif ekran kullanımı, yani dokunmatik ekranda oyun oynama veya interaktif uygulamalar kullanma gibi mobil cihazları interaktif olarak kullanma konusunda sınırlı sayıda çalışma bulunmaktadır. Çalışma 1'de, çocukların aktif ve pasif ekran süresi ile dikkat sorunları ve dikkat becerileri arasındaki ilişki araştırılmıştır. Çalışmaya yaşları 3 ila 6 arasında değişen çocukları olan 89 ebeveyn katılmıştır. Çocukların dikkat sorunları Güçler ve Güçlükler Anketi'nin hiperaktivite alt ölçeği ile, dikkat becerileri ise Çocuk Davranış Anketi'nin dikkati odaklama alt ölçeği ile ölçülmüştür. Aktif ekran süresi daha yüksek olan çocukların dikkat sorunları daha yüksek ve dikkat odaklanma puanları daha düşük bulunmuştur. Çocukların pasif ekran süresi, ilk ekran kullanım yaşı ve arka planda televizyon maruziyeti dikkatle ilgili herhangi bir sonuçla ilişkili bulunmamıştır. Çalışma 2'de, aktif (oyun oynama) ve pasif (video izleme) dokunmatik ekran kullanımının çocukların dışsal ve içsel dikkati üzerindeki anlık etkisi araştırılmıştır. Deneye yaşları 4 ila 6 arasında değişen 146 çocuk katılmıştır. Çocukların dikkat kontrol performansı, görsel arama görevi ile ön ve son testlerde ölçülmüştür. Ön ve son testler arasında, oyun koşulundaki çocuklar tablet bilgisayarda bir boyama oyunu oynamış, izleme koşulundaki çocuklar ise aynı oyunu tablette izlemişlerdir. Bulgularımız, çocukların dışsal ve içsel dikkatlerinin ekranların aktif ve pasif kullanımına göre değişmediğini göstermiştir. Genel olarak, bu tez aktif ve pasif ekran kullanımının küçük çocukların dikkat gelişimi üzerindeki etkisine dair kanıtlar sunmaktadır. Anahtar Sözcükler: Dokunmatik Ekran Kullanımı, Pasif Ekran Süresi, Dikkat Gelişimi, Dışsal Dikkat, İçsel DikkatThe use of mobile screen devices is rapidly increasing among preschool children. Although the relationship between passive screen use (i.e., watching television and video) and attention development has been widely studied in the literature, there are limited studies on active screen use, in other words, using mobile devices interactively, such as playing a game on a touchscreen or using interactive apps. In Study 1, we investigated the relationship between children's active and passive screen time and attention problems, and attentional skills. Eighty-nine parents who had children aged between 3 and 6 participated in the study. We measured children's attention problems with the Strengths and Difficulties Questionnaire's hyperactivity subscale and attentional skills with the Child Behavior Questionnaire's attentional focusing subscale. Children with higher active screen time had higher attention problems and lower attentional focusing scores. Children's passive screen time, age of first screen use, and background television exposure were not related to any attention-related outcomes. In Study 2, we investigated the immediate effect of active (playing a game) and passive (watching a video) touchscreen use on children's exogenous and endogenous attention. One hundred forty-six children aged between 4 and 6 participated in the experiment. Children's attention control performance was measured with the visual search task in pre-and post-tests. In between the pre-and post-test, children in the playing condition played a coloring game on a tablet computer, and children in the watching condition watched the same game on the tablet. Our findings showed that children's exogenous and endogenous attention did not change according to active vs. passive use of screens. Overall, this thesis provides evidence for the impact of active and passive screen use on young children's attention. Keywords: Touchscreen Use, Passive Screen Time, Attention Development, Exogenous Attention, Endogenous Attentio
Modulated Relay Based Stable Election Protocol for Large-Scale Wireless Sensor Networks
No full textInternet of things (IoT) applications based on wireless sensor networks (WSNs) have recently gained vast momentum. These applications vary from health care, smart cities, and military applications to environmental monitoring and disaster prevention. As a result, energy consumption and network lifetime have become the most critical research area of WSNs. Through energy-efficient routing protocols, it is possible to reduce energy consumption and extend the network lifetime for WSNs. Using hybrid routing protocols that incorporate multiple transmission methods is an effective way to improve network performance. This paper proposes modulated R-SEP (MR-SEP) for large-scale WSN-based IoT applications. MR-SEP is based on the well-known stable election protocol (SEP). MR-SEP defines three initial energy levels for the nodes to improve the network energy distribution and establishes multi-hop communication between the cluster heads (CHs) and the base station (BS) through relay nodes (RNs) to reduce the energy consumption of the nodes to reach the BS. In addition, MR-SEP reduces the replacement frequency of CHs, which helps increase network lifetime and decrease power consumption. Simulation results show that MR-SEP outperforms SEP, LEACH, and DEEC protocols by 70.2%, 71.58%, and 74.3%, respectively, in terms of lifetime and by 86.53%, 86.68%, and 86.93% in terms of throughput
Turkey: Challenges and Strategies Toward De-Carbonization and Sustainable Development Under the Age of Finance
No full textThe aim of this paper is to present the key challenges and structural constraints as well as potential strategies toward de-carbonization and the green transformation in Turkey, and to argue that the current mode of global finance in many ways conspires to constrain Turkey’s quest for a sustainable and green industrial policy. I consider Turkey’s conundrum against the backdrop of its speculation-led growth patterns and ongoing fossil fuel-based production cycle and highlight the tradeoffs and dilemmas of the pursuit for green abatement policies, given the logic of financialization. © 2023 Taylor & Francis Group, LLC
Decision Support Model for Pv Integrated Shading System: Office Building Case
No full textYILMAZ, Yigit/0000-0001-8693-2789Office buildings have a high amount of internal heat, solar gain, daytime energy consumption and occupancy schedules. Therefore, the increment in the cooling energy demand highlights the shading systems to provide efficient energy retrofit for office buildings. Shading surfaces, to prevent the high amount of solar radiation, are suitable for the collection of solar energy and the integration of photovoltaic systems onto the building envelope. However, the impact of the shading surface on the cooling, heating, and lighting energy consumption and the amount of energy produced by the PV system is a great task as a decision-making problem with multiple independent and dependent variables. This study searches for the installation of a PV integrated shading system to an office building through a decision support methodology. Independent variables such as the shading surface area, and angle and the dependent variables such as the energy, embodied carbon, and cost indicators are analysed within the decision support methodology. The results provide a definitive structure for such decision-making problems. Moreover, findings highlight that although Mono-Si PV options are more efficient in terms of energy generation, Poly-Si PV options are found to be the ideal solutions, due to the lower cost and embodied carbon. (c) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under theCCBYlicense (http://creativecommons.org/licenses/by/4.0/).Science Citation Index Expanded - Conference Proceedings Citation Index - Scienc
Mesenchymal Stem Cell Diffusion Integrated Mechano- Biology Analysis of 3d Scaffolds
No full textTissue Engineering and Regenerative Medicine International Society (TERMIS) -- JUN 28-JUL 01, 2022 -- Krakow, POLAND[Abstract Not Available
Effective Health Communication Depends on the Interaction of Message Source and Content: Two Experiments on Adherence To Covid-19 Measures in Türkiye
No full textYilmaz, Onurcan/0000-0002-6094-7162ObjectiveFollowing the COVID-19 outbreak, authorities recommended preventive measures to reduce infection rates. However, adherence to calls varied between individuals and across cultures. To determine the characteristics of effective health communication, we investigated three key features: message source, content, and audience.MethodsUsing a pre-test and two experiments, we tested how message content (emphasizing personal or social benefit), audience (individual differences), message source (scientists or state officials), and their interaction influence adherence to preventive measures. Using fliers advocating preventive measures, Experiment 1 investigated the effects of message content and examined the moderator role of individual differences. Experiment 2 presented the messages using news articles and manipulated sources.ResultsStudy 1 found decreasing adherence over time, with no significant impact from message content or individual differences. Study 2 found messages emphasizing 'protect yourself' and 'protect your country' to increase intentions for adherence to preventive measures. It also revealed an interaction between message source and content whereby messages emphasizing personal benefit were more effective when they came from healthcare professionals than from state officials. However, message source and content did not affect vaccination intentions or donations for vaccine research.ConclusionEffective health communication requires simultaneous consideration of message source and content.Scientific and Technological Research Council of Tuerkiye [120K427]This work was supported by The Scientific and Technological Research Council of Tuerkiye under grant number 120K427
Breaking the Performance Gap of Fully and Semi-Supervised Learning in Electromagnetic Signature Recognition
No full textIntelligent electromagnetic signature recognition is one of the key technologies in Internet-of-Things (IoT) device connection, which can improve system security and speed up the authentication process. In practical scenarios, as the number of IoT devices increases, electromagnetic features such as fingerprint and modulation signals also increase substantially. However, since intelligent recognition technology, such as Automatic Modulation Classification (AMC), requires a large amount of labeled data to train the neural network classifier, it is challenging to collect so much labeled data. To address the performance degradation challenges with small training data, we propose an efficient semi-supervised electromagnetic recognition framework to break the performance gap with the fully supervised learning scheme. This framework can fully use the unlabeled electromagnetic data collected during the authentication process for self-training to improve the classifier’s performance. According to the idea of consistency regularization, we design a signal augmentation method and propose an ensemble pseudo-label design algorithm to improve confidence. Moreover, we perform a convex combination of electromagnetic features to smooth the model decision boundary while generalizing to unknown data distribution regions. Experimental results on the modulated data demonstrate the performance superiority of the proposed algorithm, i.e., use less than 5% of data with no more than 10% performance drop. IEE
An Online Diary Study Testing the Role of Functional and Dysfunctional Self-Licensing in Unhealthy Snacking
No full textIn the present study, we aimed to investigate how two types of self-licensing (functional and dysfunctional self-licensing) are related to unhealthy snack consumption. Self-licensing refers to the act of using justifications before gratifications and has been associated with higher snack consumption. Previous research has found that while functional self-licensing decreases unhealthy snack consumption, dysfunctional self-licensing increases the number of calories taken from unhealthy snacks. Building upon existing evidence, we addressed functional and dysfunctional self-licensing to investigate how self-licensing behaviors are associated with daily variables (i.e., stress and sleep) and unhealthy snacking habits. Participants (N = 124) were given a battery of measures at the start of the week and asked to send their snack consumption every night for a week via an online questionnaire, along with daily stress and sleep items. The data were analyzed with Hierarchical Linear Modelling. Neither self-licensing measures nor unhealthy snacking habits predicted unhealthy snack consumption. Daily stress was associated with lower unhealthy snack consumption. However, the interaction between daily stress and functional self-licensing was significant, suggesting that on stressful days functional self-licensers consume even fewer unhealthy snacks compared to less stressful days. Functional and dysfunctional self-licensing are rather new constructs which is why examining their effects is important for further research. However, in contrast to the existing evidence, we failed to find an effect of both types of self-licensing on snack consumption, suggesting the effect depends on potential contextual or individual-specific factors. Future research using a dieting sample is warranted for a better understanding of how functional and dysfunctional self-licensing operate. © 2022 Elsevier Lt
Predictive Maintenance Analysis for Industries
No full textBu çalışma Rastgele Orman, Karar Ağacı, Naive Bayes, Lojistik Regresyon, Destek Vektör Makinesi ve Uzun Kısa Süreli Bellek algoritmalarını kullanarak sensör verilerine yönelik hataları tahmin etmeyi amaçlamaktadır. Proje, olası hataları tespit edebilme ve sensör verilerini kullanarak arızaları tahmin edebilecek şekilde sensör parametreleri verilerinden sonuçlar çıkarmaya odaklandı. Arızayı öngören bu analiz, Kaggle'ın pompa sensörü veri seti aracılığıyla incelenmiştir. Bu bir ikili sınıflandırma problemidir ve gelecekteki gözlemleri tahmin etmek ve bunları pozitif bir etiket (normal) veya negatif bir etiket (broken) olarak sınıflandırmak için geçmiş pompa sensörü verilerini kullanarak zaman serisi analizi gerçekleştirir. Bir enerji santralinde çok sayıda pompa sistemi bulunur. Bunlar enerji üretiminin ana kaynaklarıdır. Sürekli güç beslemesini sağlamak için pompa sistemi mükemmel durumda tutulmalıdır. Sistemdeki pompalardan birinin arızalanması, elektrik üretiminde geçici bir düşüşe ve hatta tamamen kesintiye neden olabilir. Arızaların önceden öngörülmesi durumunda bu durum önlenebilir. Bu nedenle, büyük mali kayıpları önlemek için başarısızlığı erken tahmin etmek önemlidir. Bu nedenle bu tez, pompa sensörlerindeki kestirimci bakıma odaklanmıştır. Ayrıca amaç, en iyi algoritmayı seçmek için algoritmaların performansının karşılaştırılmasıdır. Kestirimci bakım, endüstrilerin bu hataları önlemesinde faydalıdır.This study aims to predict faults for sensor data using Random Forest, Decision Tree, Naive Bayes, Logistic Regression, Support Vector Machine, and Long Short Term Memory algorithms. The project focused on drawing conclusions from the sensor parameters' data in a way that can detect possible faults and predict failures from sensor data. This analysis which predicts the failure, has been examined through the pump sensor dataset from Kaggle. It is a binary classification problem, and it performs time series analysis using historical pump sensor data to predict future observations and classify them into a positive label (normal) or a negative label (broken). A power plant has several pump systems. These are the main resources of power generation. To ensure continuous power supply, the pump system must be kept in perfect condition. A failure of one of the pumps in the system can lead to a temporary drop in power generation and even a complete outage. This may be avoided if failures are anticipated in advance. Therefore, it is important to anticipate failure early to avoid large financial losses. Thus, this thesis focused on predictive maintenance on pump sensors. Also, the goal is the comparison of the performance of algorithms for choosing the best algorithm. Predictive maintenance is beneficial for industries to prevent these faults