279 research outputs found
Creating a new Europe through contemporary art:Manifesta and its relation to art, society and politics
Manifesta - European Biennial of Contemporary Art is a nomadic biennial that takes place every two years in a different city of Europe. In this dissertation, I focus on Manifesta's political, economic, urban and artistic relationships with its host cities and regions as well as the changes that occur in its own goals, discourse and organization over time. I argue that Manifesta is one of the new institutions of neoliberal governance in the field of art in the post-Cold War era. During the dissertation, I evaluate each edition of the biennial within its own context, adopt theoretical approaches suitable for this context and compare editions to find common points. I identify three significant periods within the history of Manifesta. In its first period, namely from its birth as an idea in the early 90’s to the Ljubljana edition held in 2000, Manifesta aimed to reach to the post-communist regions. Later, until its ninth edition held in Genk - Limburg (2012), Manifesta shifted its attention from the East-West axis to the North-South axis within Europe and concentrated more on the promotion of regions than cities. In its last and on-going period that started in 2014 in St. Petersburg, it went beyond the EU zone after the global systemic crisis and acted pragmatically in terms of its discourse. By investigating each editions’ complex set of relations in detail, this dissertation contributes to a better understanding of both Manifesta and the phenomenon of contemporary art biennials
Antifungal and antibacterial effects of some acrocarpic mosses
In this study, the antifungal and antibacterial effect of 6 different acrocarpous mosses were tested in vitro aganist 8 different microorganisms. For the extraction, ethyl alcohol, methyl alcohol, acetone and chloroform were used as solvents. While the highest antimicrobial effect was seen in methyl alcohol extracts, extracts of chloroform showed the lowest level of antimicrobial effect. Grimmia anodon Bruch & Schimp. which is one of the acrocarp mosses used in this study, showed the highest activity in termsof the number of microorganism affected. Tortella tortuosa (Hedw.) Limpr. only has effect on Candida albicans ATCC 16231 strain. All the results were compared with standard antibiotic discs, ketoconazole (50 ìg), ampicillin (10 ìg), eritromycin (15 ìg) and vancomycin (30 ìg).Key words: Moss, acrocarpous, antimicrobial effect
Investigation of antimicrobial activity of some Turkish pleurocarpic mosses
In this study, the antimicrobial activities of different extracts from the five pleurocarpic mosses (Platyhypnidium riparioides (Hedw.) Dixon, Leucodon sciuroides (Hedw.) Schwägr., Hypnum cupressiforme Hedw., Homalothecium sericeum (Hedw.) Br.Eur., and Anomodon viticulosus (Hedw.) Hook & Taylor.) were tested aganist eight bacterial and fungal strains. For the extraction, four different solvents (ethyl alcohol, methyl alcohol, chloroform and acetone) were used. While methanolic extracts of P. riparioides showed the highest antibacterial effect against the Gram-negative bacterium Pseudomonas aeroginosa ATCC 27853, acetone extract of A. viticulosus showed the highest antifungal effect against the fungus Saccharomyces cerevisiae ATCC. All the results were compared with standard antibiotic discs: ketoconazole (50 μg), amphicillin (10 μg), eritromycin (15 μg), penicillin (10 μg) and vancomycin (30 μg).Key words: Moss, pleurocarpic, antimicrobial activity
CYCLE-GAN BASED FEATURE TRANSLATION FOR OPTICAL-SAR DATA IN BURNED AREA MAPPING
For the management of the forest and the assessment of impacts on ecosystems, post-fire burned area mapping is crucial for sustainable environment and forestry. While optical remote sensing data has been extensively used for monitoring forest fires due to its spatial and temporal resolutions, it is susceptible to limitations imposed by poor weather conditions. To overcome this challenge, the complementary use of optical and Synthetic Aperture Radar (SAR) data is beneficial, as SAR can penetrate clouds and capture images in all-weather conditions. However, SAR lacks the necessary spectral features for comprehensive forest fire monitoring and burned area mapping. To overcome these limitations, this study proposes a Cycle-Consistent Generative Adversarial Networks (Cycle-GAN) based deep feature translation method for burned area mapping by combining optical and SAR data. This approach allows for the retrieval of precise information of interest with a level of precision that cannot be achieved by either optical or SAR data alone. The Cycle-GAN uses a cyclic structure to transfer data from one domain (optical) to another domain (SAR) into the same feature space. As a result, it can maintain its spectral characteristics while providing ongoing and current information for monitoring forest fires. For this purpose, Burn Area Index (BAI), Mid Infrared Burn Index (MIRBI), Normalised Burn Ratio (NBR) were determined using optical data and image translation was performed with Cycle-GAN on SAR data. The accuracy of the fake BAI, MIRBI and NBR spectral burn indices determined from the SAR was established by correlating the original spectral burn indices determined from the optical data. The results demonstrate a significant correlation between the real and generated fake burn indices, particularly with a noteworthy correlation coefficient of 0.93 observed for the NBR index. In addition, the findings validate the effectiveness of the generated indices in accurately representing and quantifying the extent of burned areas
Modeling of the number of divorce in Turkey using the Generalized Poisson, Quasi-Poisson and Negative Binomial Regression
In this study, it has been aimed to model the numbers of divorce in Turkey between years 2001- 2009 using Generalized Poisson, Quasi-Poisson and Negative Binomial Regression methods. Data set of this study has been based on the data obtained from Turkish Statistical Institute (TUIK). Response variable-the annual rate of divorce- has been categorized into four groups with respect to the length of ex-married life of divorced couples. Explanatory variables have been designated as average age of the first marriage of men and women, the professional work life ratio of married women, the percentage of university graduates in both men and women. For Poisson models, overdispersion parameters have been detected respectively 32.413, 7.277, 16.158 and 26.361. Furthermore Pearson and G2 statistics have revealed that Poisson models are not appropriate for data set. When Quasi Poisson regression was employed, it has been detected that residual deviances are rather close to Poisson residuals. Finally, Negative binomial regression has been conducted.
Overdispersion is a common phenomenon in Poisson modeling. In such data sets certain generalizations of Poisson regression and negative binomial regression modeling are used. In present study negative binomial regression has been detected as approved method.Bu çalışmada, 2001-2009 yılları arasında Türkiye’deki boşanma sayılarının Genelleştirilmiş Poisson, Quasi Poisson ve Negatif Binomiyal Regresyon metotlarına gore modellenmesi amaçlanmıştır. Çalışmanın veri seti, Türk İstatistik Kurumu (TÜİK)’den elde edilmiştir. Cevap değişkeni olan yıllık boşanma sayısı, boşanmış çiftlerin evil kalma sürelerine göre dört gruba ayrılmıştır. Çalışmanın veri seti Türkiye İstatistik Kurumu (TÜİK)’ndan elde edilen bilgiler ile oluşturulmuştur. Cevap değişkeni olan yıllık boşanma sayısı, boşanan çiftlerin evli kalma sürelerine göre dört gruba ayrılmıştır. Açıklayıcı değişkenler olarak, erkek ve kadınların ilk evlilik yaşı ortalamaları, evli kadının iş hayatına katılma oranı, erkek ve kadınlarda yüksek okul mezunu olma oranları ele alınmıştır. Poisson modelleri için aşırı yayılım parametresi sırasıyla 32.413, 7.277, 16.158 ve 26.361 olarak belirlenmiştir. Ayrıca Pearson ve G2 istatistikleri de Poisson modellerinin veri seti için uygun olmadığını göstermiştir. Quasi Poisson uygulandığında ise artıkların dağılımı Poisson modellerine çok yakın çıkmıştır. Sonuç olarak Negatif Binomiyal Regresyon kullanılmıştır. Aşırıyayılım, Poisson modellemesinde yaygın bir fenomendir. Bu gibi veri setlerinde Poisson Regresyonun çeşitli genelleştirmeleri ve Negatif Binomiyal Regresyon kullanılır. Bu çalışmada Negatif Binomiyal Regresyonun uygun olduğuna karar verilmiştir
An Intelligent Approach for Predicting Mechanical Properties of High-Volume Fly Ash (HVFA) Concrete
Plastic waste (PW) is a major soild waste, which its generation continues to increase globally year in and year out. Proper management of the PW is still a challenge due to its non-biodegradable nature. One of the most convenient ways of managing plastic waste is by using it in concrete as a partial substitute for natural aggregate. However, the main shortcomings of adding plastic waste to concrete are a reduction in strength and durability. Hence, to reduce the undesirable impact of the PW in concrete, highly reactive additives are normally added. In this research, 240 experimental datasets were used to train an artificial neural network (ANN) model using Levenberg Marquadt algorithms for the prediction of the mechanical properties and durability of high-volume fly ash (HVFA) concrete containing fly ash and PW as partial substitutes for cement and coarse aggregate, respectively, and graphene nanoplatlets (GNP) as additives to cementitious materials. The optimized model structure has five input parameters, 17 hidden neurons, and one output layer for each of the physical parameters. The results were analyzed graphically and statistically. The obtained results revealed that the generated network model can forecast with deviations less than 0.48%. The efficiency of the ANN model in predicting concrete properties was compared with that of the SVR (support vector regression) and SWLR (stepwise regression) models. The ANN outperformed SVR and SWLR for all the models by up to 6% and 74% for SVR and SWLR, respectively, in the confirmation stage. The graphical analysis of the results further demonstrates the higher prediction ability of the ANN. Doi: 10.28991/CEJ-2023-09-09-04 Full Text: PD
Determination of fuel properties of wood pellet’s made from poplar wood resudies
Günümüzde iklim değişikliği küresel ölçekte ciddi bir tehdit olarak karşımıza çıkmaktadır. Fosil
yakıtların kullanımı sera gazı salınımlarını arttırmakta, bu da küresel ısınmaya neden olmaktadır. Her
geçen gün enerjiye olan talebin artmasına karşın; fosil yakıt rezervlerinin hızla tükenmesi, fosil yakıtlar
bakımından dışarıya bağımlı olmamız ve döviz kurlarındaki ani değişiklikler, fosil yakıtların çevresel
olarak ciddi hasarlara sebep olması yenilenebilir enerji kaynaklarına olan ihtiyacı daha da önemli
kılmaktadır. Orman atıkları, zirai atıklar ve bunun yanı sıra ülkemiz şartlarında kolaylıkla yetiştirilebilen
ve hızlı büyüyen türlerden olan kavak odun artıklarının biyoyakıt olarak kullanılması büyük öneme
sahiptir. Bu çalışmada; Bayburt yöresinden temin edilen karakavak (Populus nigra) atıkları KTÜ Orman
Endüstri Mühendisliği pilot tesislerinde yongalanarak uygun boyuta getirildikten sonra, Karadeniz
Tarımsal Araştırma Enstitüsü Müdürlüğü (KTAEM) biyokütle ünitesinde pelet üretimi
gerçekleştirilmiştir. Üretilen peletlerin; ısıl değer, kül içeriği, nem oranının belirlenmesi, baca gazı
emisyonlarının ölçülmesi ve elementel analizleri KTAEM. laboratuvarlarında yapılmıştır. Kavak odun
atıklarından elde edilen peletlerinin ısıl değeri ve kül yüzdesi sırasıyla 18.91 MJ/kg (4515 cal/g) ve
%2.59 dur. N, C, H, O miktarları sırasıyla %0.52, %47.44, %5.92 ve %46.11 olarak bulunmuştur. Baca
gazı emisyon değerleri; O2, CO2, CO, NO, NOx, SO2 sırasıyla %15.70, %5.06, 1279 ppm, 64 ppm, 66.67
ppm ve 23 ppm olarak tespit edilmiştir. Kavak odun atıklarından yapılan odun peleti; EN 14961-2’ye
göre; nem içeriği, kül içeriği, ısıl değer, S (%) ve N (%) parametreleri bakımından EN-B kategorisinde
yer almaktadır.Today, climate change is a serious threat on the global scale. The use of fossil fuels is one of the most
important causes of global warming. Despite the increasing demand for energy every day; rapid
depletion of fossil fuel reserves, in terms of its reliance on foreign fossil fuels and the need for
renewable energy sources becomes even more important as fossil fuels cause serious environmental
damage are making the need for renewable energy sources even more important. The use of poplar
wood residues, which are easily grown in our own conditions and fast growing species, as biofuels has
great importance. In this study; Poplar wood resudies were obtained from Bayburt. These materials
chipped in the appropriate size at pilot plant of KTU Faculty of Forestry, Forest Industry Engineering.
Pellets were produced in the biomass pellet production unit of the Black Sea Agriculture Research
Institute Directorate. The produced pellets; calorific value, ash content, to determine the moisture
content of the flue gas emission measurement and elemental analysis will be made in the Black Sea
Institute of Agricultural Waste Management laboratory. The thermal value and ash content of the
pellets obtained from poplar wood waste were 18.91 MJ/kg (4515 cal/g) and 2.59%respectively. The
amounts of N, C, H, O were 0.52%, 47.44%, 5.92%and 46.11%, respectively. The thermal value and ash
content of the pellets obtained from poplar wood waste were 18.91 MJ/kg (4515 cal/g) and
2.59%respectively. The amounts of N, C, H, O were 0.52%, 47.44%, 5.92%and 46.11%, respectively. The
emission values of the flue gas (O2, CO2, CO, NO, NOx, SO2) were also determined 15.70%, 5.06%, 1279
ppm, 64 ppm, 66.67 ppm and 23 ppm respectively. Wood pellets made of poplar wood waste;
According to EN 14961-2; moisture content, ash content, thermal value, S (%) and N (%) in terms of
parameters are in the EN-B category
Problematic online behaviors among adolescents and emerging adults: associations between cyberbullying perpetration, problematic social media use, and psychosocial factors
Over the past two decades, young people's engagement in online activities has grown markedly. The aim of the present study was to examine the relationship between two specific online behaviors (i.e., cyberbullying perpetration, problematic social media use) and their relationships with social connectedness, belongingness, depression, and self-esteem among high school and university students. Data were collected from two different study groups via two questionnaires that included the Cyberbullying Offending Scale, Social Media Use Questionnaire, Social Connectedness Scale, General Belongingness Scale, Short Depression-Happiness Scale, and Single Item Self-Esteem Scale. Study 1 comprised 804 high school students (48% female; mean age 16.20 years). Study 2 comprised 760 university students (60% female; mean age 21.48 years). Results indicated that problematic social media use and cyberbullying perpetration (which was stronger among high school students) were directly associated with each other. Belongingness (directly) and social connectedness (indirectly) were both associated with cyberbullying perpetration and problematic social media use. Path analysis demonstrated that while age was a significant direct predictor of problematic social media use and cyberbullying perpetration among university students, it was not significant among high school students. In both samples, depression was a direct predictor of problematic social media use and an indirect predictor of cyberbullying perpetration. However, majority of these associations were relatively weak. The present study significantly adds to the emerging body of literature concerning the associations between problematic social media use and cyberbullying perpetration
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