Sürdürülebilir Yeşil Kampüs Koleksiyonu / Sustainable Green Campus Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7755
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Article Citation - WoS: 16Citation - Scopus: 20Groundwater Recharge Estimation Using Hydrus 1d Model in Alaşehir Sub-Basin of Gediz Basin in Turkey(Springer Verlag, 2019) Tonkul, Serhat; Baba, Alper; Şimşek, Celalettin; Durukan, Seda; Demirkesen, Ali Can; Tayfur, GökmenGediz Basin, located in the western part of Turkey constituting 2% land of the country, has an important groundwater potential in the area. Alasehir sub-basin, located in the southeast of the Gediz Basin and subject to the extensive withdrawal for the irrigation, constitutes the study area. Natural recharge to the sub-basin due to precipitation is numerically investigated in this study. For this purpose, 25 research wells, whose depths range from 20 to 50 m, were drilled to observe the recharge and collect the necessary field data for the numerical model. Meteorological data were collected from 3 weather stations installed in the study area. The numerical model HYDRUS was calibrated using the field water content data. Soil characterization was done on the core samples; the aquifer characterization was performed, and the alluvial aquifer recharge due to precipitation was calculated. As a result, the computed recharge value ranges from 21.78 to 68.52 mm, with an average value of 43.09 mm. According to the numerical model, this amount of recharge corresponds to 10% of the amount of annual rainfall.Article Citation - WoS: 19Citation - Scopus: 29Modeling of an Activated Sludge Process for Effluent Prediction—a Comparative Study Using Anfis and Glm Regression(Springer Verlag, 2018) Araromi, Dauda Olurotimi; Majekodunmi, Olukayode Titus; Adeniran, Jamiu Adetayo; Salawudeen, Taofeeq OlalekanIn this paper, nonlinear system identification of the activated sludge process in an industrial wastewater treatment plant was completed using adaptive neuro-fuzzy inference system (ANFIS) and generalized linear model (GLM) regression. Predictive models of the effluent chemical and 5-day biochemical oxygen demands were developed from measured past inputs and outputs. From a set of candidates, least absolute shrinkage and selection operator (LASSO), and a fuzzy brute-force search were utilized in selecting the best combination of regressors for the GLMs and ANFIS models respectively. Root mean square error (RMSE) and Pearson’s correlation coefficient (R-value) served as metrics in assessing the predicting performance of the models. Contrasted with the GLM predictions, the obtained modeling results show that the ANFIS models provide better predictions of the studied effluent variables. The results of the empirical search for the dominant regressors indicate the models have an enormous potential in the estimation of the time lag before a desired effluent quality can be realized, and preempting process disturbances. Hence, the models can be used in developing a software tool that will facilitate the effective management of the treatment operation.Article Citation - WoS: 3Citation - Scopus: 3Channel and Queue Aware Joint Relay Selection and Resource Allocation for Miso-Ofdma Based User-Relay Assisted Cellular Networks(Springer Verlag, 2018) Baştürk, İlhan; Özbek, BernaUser-relay assisted orthogonal frequency division multiple access (OFDMA) networks are cost-effective solutions to meet the growing capacity and coverage demands of the next generation cellular networks. These networks can be used with multiple antennas technology in order to obtain a diversity gain to combat signal fading and to obtain more capacity gain without increasing the bandwidth or transmit power. Efficient relay selection and resource allocation are crucial in such a multi-user, multi-relay and multi-antenna environment to fully exploit the benefits of the combination of user-relaying and multiple antennas technology. Thus, we propose a channel and queue aware joint relay selection and resource allocation algorithm for multiple-input single-output (MISO)-OFDMA based user-relay assisted downlink cellular networks. Since, the proposed algorithm is not only channel but also queue-aware, the system resources are allocated efficiently among the users. The proposed algorithm for the MISO-OFDMA based user-relay assisted scheme is compared to existing MISO-OFDMA based non-relaying and fixed relay assisted schemes and it is also compared with the existing single-input single-output (SISO)-OFDMA based user-relay assisted scheme. Simulation results revealed that the proposed scheme outperforms the existing schemes in terms of cell-edge users’ total data rate, average backlog and average delay.Article Citation - WoS: 2Citation - Scopus: 4Removal of Metals and Metalloids From Acidic Mining Lake (aml) Using Olive Oil Solid Waste (osw)(Springer Verlag, 2019) İlay, Remzi; Baba, Alper; Kavdır, YaseminThe acidic mining lakes have low pH values and high metal and metalloid concentrations. In this study, the ability of low-cost olive oil solid waste (OSW) to remove Al, As, Cd, Fe, B and Ti ions from aqueous solutions in short term has been evaluated. Adsorption capacities (mg g−1) of OSW (1:5–1:10 w/v) were 764.06–411.75 for Al, 0.26 for As, 0.07–0.14 for Cd, 2181.5–2406.5 for Fe, 23.70–82.50 for B and 0.12–0.0.34 for Ti. OSW addition increased acidic mine water (AMW) pH from 2.41 to 3.2 with 1:5 and from 2.41 to 2.7 to 1:10 mixing ratio, respectively, after 10 min. The best gradual decrease has been observed with different ratio of OSW applications on B and Ti concentrations. OSW adsorbs 32.41% and 62.68% of B at the ratio of 1:5 and 1:10 and 55.29% and 83.04% of Ti at the ratio of 1:5 and 1:10 (OSW:AMW) mixtures, respectively. The results show that OSW has great potential for metal removal from acidic mine water.Article Citation - WoS: 11Citation - Scopus: 14Categorization of Species Based on Their Micrornas Employing Sequence Motifs, Information-Theoretic Sequence Feature Extraction, and K-Mers(Springer Verlag, 2017) Yousef, Malik; Nigatu, Dawit; Levy, Dalit; Allmer, Jens; Henkel, WernerBackground: Diseases like cancer can manifest themselves through changes in protein abundance, and microRNAs (miRNAs) play a key role in the modulation of protein quantity. MicroRNAs are used throughout all kingdoms and have been shown to be exploited by viruses to modulate their host environment. Since the experimental detection of miRNAs is difficult, computational methods have been developed. Many such tools employ machine learning for pre-miRNA detection, and many features for miRNA parameterization have been proposed. To train machine learning models, negative data is of importance yet hard to come by; therefore, we recently started to employ pre-miRNAs from one species as positive data versus another species’ pre-miRNAs as negative examples based on sequence motifs and k-mers. Here, we introduce the additional usage of information-theoretic (IT) features. Results: Pre-miRNAs from one species were used as positive and another species’ pre-miRNAs as negative training data for machine learning. The categorization capability of IT and k-mer features was investigated. Both feature sets and their combinations yielded a very high accuracy, which is as good as the previously suggested sequence motif and k-mer based method. However, for obtaining a high performance, a sufficiently large phylogenetic distance between the species and sufficiently high number of pre-miRNAs in the training set is required. To examine the contribution of the IT and k-mer features, an information gain-based feature ranking was performed. Although the top 3 are IT features, 80% of the top 100 features are k-mers. The comparison of all three individual approaches (motifs, IT, and k-mers) shows that the distinction of species based on their pre-miRNAs k-mers are sufficient. Conclusions: IT sequence feature extraction enables the distinction among species and is less computationally expensive than motif calculations. However, since IT features need larger amounts of data to have enough statistics for producing highly accurate results, future categorization into species can be effectively done using k-mers only. The biological reasoning for this is the existence of a codon bias between species which can, at least, be observed in exonic miRNAs. Future work in this direction will be the ab initio detection of pre-miRNA. In addition, prediction of pre-miRNA from RNA-seq can be done.Article Citation - WoS: 20Citation - Scopus: 22Modeling of Seawater Intrusion in a Coastal Aquifer of Karaburun Peninsula, Western Turkey(Springer Verlag, 2017) Mansour, Ahmed Y. S.; Baba, Alper; Gündüz, Orhan; Şimşek, Celalettin; Elçi, Alper; Murathan, Alim; Sözbilir, HasanSeawater intrusion is a major problem to freshwater resources especially in coastal areas where fresh groundwater is surrounded and could be easily influenced by seawater. This study presents the development of a conceptual and numerical model for the coastal aquifer of Karareis region (Karaburun Peninsula) in the western part of Turkey. The study also presents the interpretation and the analysis of the time series data of groundwater levels recorded by data loggers. The SEAWAT model is used in this study to solve the density-dependent flow field and seawater intrusion in the coastal aquifer that is under excessive pumping particularly during summer months. The model was calibrated using the average values of a 1-year dataset and further verified by the average values of another year. Five potential scenarios were analyzed to understand the effects of pumping and climate change on groundwater levels and the extent of seawater intrusion in the next 10 years. The result of the analysis demonstrated high levels of electrical conductivity and chloride along the coastal part of the study area. As a result of the numerical model, seawater intrusion is simulated to move about 420 m toward the land in the next 10 years under “increased pumping” scenario, while a slight change in water level and TDS concentrations was observed in “climate change” scenario. Results also revealed that a reduction in the pumping rate from Karareis wells will be necessary to protect fresh groundwater from contamination by seawater.Article Citation - WoS: 5Citation - Scopus: 5Tannery Wastewater Sediments Produced by Clinoptiolite/Polyacrylamide-aided Flocculation as a Clay Additive in Brick Making(Springer Verlag, 2017) Köseoğlu, Kemal; Cengizler, H.; İsrail, L. İ.; Polat, HürriyetToxic tannery wastewater(s) (TWW) pose(s) a great risk to the environment. This study explores the potential of mitigating the harmful effects of TWW through sedimentation using clinoptiolite in the presence of various anionic, cationic and non-ionic flocculants with different molecular weights and charge densities followed by encapsulation in a brick structure for stability. Compressive strength (CS), size reduction after firing (SRAF), water absorption (WA) and colouring parameters of bricks were determined. X-Ray diffraction (XRD) and scanning electron microscopy (SEM)-energy dispersive X-ray (EDX) analyses were conducted on brick bodies. Kinetic leaching experiments were conducted for possible heavy metal release from the bricks. Bricks containing 10 wt% leather waste and 5 wt% clinoptiolite sintered at 800 °C instead of 920 °C possessed similar properties to the standard brick (SB).Article Citation - WoS: 39Citation - Scopus: 47Quality of Groundwater Resources in Afghanistan(Springer Verlag, 2017) Hayat, Ehsanullah; Baba, AlperWater is the main source of energy production and economy in Afghanistan where agriculture accounts for more than 50% of the country’s gross domestic product (GDP). Access to safe drinking water is still a problem in the country, which has caused different health issues and even child mortality especially in rural areas. Groundwater is the main source of drinking water in the country. However, little knowledge is available about the quality of groundwater throughout the entire country, and its quality has not been investigated extensively yet like in other countries in the world. While most people think that consuming groundwater is a reliable and safe source of drinking water for health, the United Nations (UN) agencies report various kinds of waterborne diseases and even child mortalities due to drinking water quality in the country. In this article, significant geogenic and anthropogenic factors that play a vital role in groundwater contamination of the country are identified and explained. Different geogenic contaminations such as arsenic, fluoride, sulfate, and boron occur in several areas of Afghanistan that have a direct effect on human health. The water quality mapping for Afghanistan is completed for half of the country, which shows that groundwater is plagued by high levels of fluoride and arsenic in some areas. The water quality mapping of the other half of the country cannot be completed due to security concerns currently. Also, there are different kinds of waterborne diseases such as diarrhea, cholera, and dysentery that can be seen in different parts of the country because of anthropogenic activities which continuously deteriorate groundwater.Article Citation - WoS: 33Citation - Scopus: 34Exploitation of Agricultural Wastes and By-Products for Production of Aureobasidium Pullulans Y-2311 Xylanase: Screening, Bioprocess Optimization and Scale Up(Springer Verlag, 2017) Yeğin, Sırma; Büyükkileci, Ali Oğuz; Sargın, Sayıt; Göksungur, YektaThe potential of several agricultural wastes and by-products (wheat bran, oat bran, corn cob, brewer’s spent grain, malt sprout, artichoke stem, sugar beet pulp, olive seed, cotton stalk and hazelnut skin) was examined as the substrate for xylanase production by Aureobasidium pullulans Y-2311-1. Based on the screening studies, wheat bran was selected as the best substrate for further optimization studies. The effects of initial medium pH, temperature and incubation time on xylanase production in shake flask system were optimized by response surface methodology (RSM). The optimum levels of the process variables defined by the model (initial medium pH, 4.24; temperature, 30.27 °C; and incubation time 126.67 h) resulted in production of 85.19 U/ml xylanase. Taking the RSM optimized parameters in shake-flask scale into consideration; xylanase production was scaled up to bioreactor system with a working volume of 1.5 l. The peak of enzyme production was achieved after 126 h incubation that has previously been determined by RSM studies at shake flask level. Furthermore, the optimum levels of agitation and aeration in bioreactor system was found as 200 rpm and 1.5 vvm. Maximum enzyme production was close to 85 kU/l which could be translated into a productivity of 0.68 kU/l/h. No previous work considered the statistical optimization of xylanase production by A. pullulans on wheat bran and scale up of the bioprocess to a bioreactor systemArticle Citation - WoS: 9Citation - Scopus: 12Compositing Climate Change Vulnerability of a Mediterranean Region Using Spatiotemporally Dynamic Proxies for Ecological and Socioeconomic Impacts and Stabilities(Springer Verlag, 2017) Demirkesen, Ali Can; Evrendilek, FatihThe study presents a new methodology to quantify spatiotemporal dynamics of climate change vulnerability at a regional scale adopting a new conceptual model of vulnerability as a function of climate change impacts, ecological stability, and socioeconomic stability. Spatiotemporal trends of equally weighted proxy variables for the three vulnerability components were generated to develop a composite climate change vulnerability index (CCVI) for a Mediterranean region of Turkey combining Landsat time series data, digital elevation model (DEM)-derived data, ordinary kriging, and geographical information system. Climate change impact was based on spatiotemporal trends of August land surface temperature (LST) between 1987 and 2016. Ecological stability was based on DEM, slope, aspect, and spatiotemporal trends of normalized difference vegetation index (NDVI), while socioeconomic stability was quantified as a function of spatiotemporal trends of land cover, population density, per capita gross domestic product, and illiteracy. The zones ranked on the five classes of no-to-extreme vulnerability were identified where highly and moderately vulnerable lands covered 0.02% (12 km2) and 11.8% (6374 km2) of the study region, respectively, mostly occurring in the interior central part. The adoption of this composite CCVI approach is expected to lead to spatiotemporally dynamic policy recommendations towards sustainability and tailor preventive and mitigative measures to locally specific characteristics of coupled ecological–socioeconomic systems.
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