The Importance of Water use under Climate Change effects in Semi-Arid Agricultural Areas

Irresponsible use of water resources, hunger, drought, extinction of species, vegetation and soil destruction, pollution, global warming and climate change, the thinning of the ozone layer, the negative effects of greenhouse gases was the beginning of the process of global warming. Almost 90 percent of the irrigated agricultural production in our country is carried out by so-called wild irrigation flood irrigation method. To obtain abundant and high-quality forage from pastures, irrigation of this area is to solve the drainage problems, fertilization, weed the war and the various maintenance jobs are dependent on properly.With surface irrigation practices, fertile agricultural land becomes barren in the Southeastern Anatolian region. These lands are becoming agricultural production cannot be done in the future. Therefore, soil and agricultural production to continue in a healthy manner and informed water management practices must be done to protect the soil. The use of wastewater for this purpose irrigation, directing the arid areas of runoff, evaluating and storing rainwater farmers to promote modern irrigation methods, practices that save water and farmer training with consideration should be given to applications involving studies as to ensure its dissemination. We have to use irrigation water in our region with low rainfall. We must look for ways to benefit from rainwater. In this study, in order to ensure sustainable water management in our country under the influence of climate change on agricultural production, land and water use and it has consciously exploredin agriculture

DETERMINATION OF CONCENTRATION BY MEANS OF LIGHT SCATTERING AND DIGITAL IMAGE POSTPROCESSING

The main purpose of this research is to manage simultaneous measurement of velocity and concentration in large cross sections by recording and processing images of cloud structures. Stack gas dispersion in an atmospheric boundary layer (ABL), was chosen as the test case and investigated both experimentally and numerically. Large scale particle image velocimetry (LS-PIV), which records cloud structures instead of individual particles, was used to obtain the velocity field. Light scattering technique (LST) was employed to determine the concentration of the pollutant from the same set of images. In addition, aspiration probe concentration measurements were performed. The test case was also simulated using the CFD solver FLUENT. Comparison revealed that there is a good agreement between the aspiration probe measurements and the CFD results. For the LST measurements, a non-linear relation between concentration and light intensity was observed

Reprise fragments in English and Hungarian: further evidence for an in-situ Q-equivalence approach to clausal ellipsis

Theoretical and Experimental Linguistic

Spectrum Sensing and Signal Identification with Deep Learning based on Spectral Correlation Function

Spectrum sensing is one of the means of utilizing the scarce source of wireless spectrum efficiently. In this paper, a convolutional neural network (CNN) model employing spectral correlation function which is an effective characterization of cyclostationarity property, is proposed for wireless spectrum sensing and signal identification. The proposed method classifies wireless signals without a priori information and it is implemented in two different settings entitled CASE1 and CASE2. In CASE1, signals are jointly sensed and classified. In CASE2, sensing and classification are conducted in a sequential manner. In contrary to the classical spectrum sensing techniques, the proposed CNN method does not require a statistical decision process and does not need to know the distinct features of signals beforehand. Implementation of the method on the measured overthe-air real-world signals in cellular bands indicates important performance gains when compared to the signal classifying deep learning networks available in the literature and against classical sensing methods. Even though the implementation herein is over cellular signals, the proposed approach can be extended to the detection and classification of any signal that exhibits cyclostationary features. Finally, the measurement-based dataset which is utilized to validate the method is shared for the purposes of reproduction of the results and further research and development

Multifont Ottoman character recognition

Ottoman characters from three different fonts are used character recognition problem, broadly speaking, is transferring a page that contain symbols to the computer and matching these symbols with previously known or recognized symbols after extraction the features of these symbols via appropriate preprocessing methods. Because of silent features of the characters, implementing an Ottoman character recognition system is a difficult work. Different researchers have done lots of works for years to develop systems that would recognize Latin characters. Although almost one million people use Ottoman characters, great deal of whom has different native languages, the number of studies on this field is insufficient. In this study 28 different machine-printed to train the Artificial Neural Network and a %95 classification accuracy for the characters in these fonts and a %70 classification accuracy for a different font has been found. © 2000 IEEE

Computational comparison of five maximal covering models for locating ambulances

This article categorizes existing maximum coverage optimization models for locatingambulances based on whether the models incorporate uncertainty about (1) ambulanceavailability and (2) response times. Data from Edmonton, Alberta, Canada are used to test five different models, using the approximate hypercube model to compare solution quality between models. The basic maximum covering model, which ignores these two sources of uncertainty, generates solutions that perform far worse than those generated by more sophisticated models. For a specified number of ambulances, a model that incorporates both sources of uncertainty generates a configuration that covers up to 26% more of the demand than the configuration produced by the basic model.pre-prin

Kırka Boraks atıklarının soda liçi

Bor, çok geniş kullanım alanları ile, insanlığın bugünkü ve gelecekteki yaşamlarında, vazgeçilmez bir endüstriyel hammadde olarak önemini gittikçe arttıracaktır. Ülkemiz bu açıdan şanslı bir konumda olup, toplam dünya bor rezervlerinin yaklaşık %60 'mı içermektedir Bu nedenlerden dolayı, bor cevherlerimizin en verimli bir şekilde üretimi ülkemiz açısından çok fazla önem arz etmektedir. Kırka boraks konsantratöründe, her yıl yaklaşık %10-12 B2O3 tenörlü 250 bin ton yaş artık oluşmakta ve bunun yanında artık göletinde de benzer tenörlü yaklaşık 4 milyon ton birikmiş katı artık bulunmaktadır. Artıkların teknolojik koşullara uygun olarak değerlendirilmesi gerekmektedir. Bu çalışmada, kırka boraks artıklarının soda liçi ile değerlendirilmesinde etken olan parametreler ayrıntılı bir şekilde araştırılmıştır. Bu amaçla, boraks artıklarının Na2C03 ve NaHCC>3 liçi; değişik sıcaklık, çözücü"miktarları, katı/sıvı oranlan ve çözeltine sürelerinde denenmiş olup, düşük çözücü oranlarında, optimal sıcaklık ve sürede başarılı sonuçlar alınmıştır. Sonuçta, seyreltik soda çözeltisi ile yapılan deneylerde, artiklardaki boraks yüksek verimle çözünmüş ve elde edilen bulgulardan yararlanılarak, tesisin mevcut çalışma koşullarına uygun optimum öneri akım şemalan geliştirilmiştir. Aynca, bu yöntemle boraks artıklarının değerlendirilmesinde, çözücü olarak tronanın kullanılması ile ülkemizde büyük bir potansiyele sahip olan trona yataklan yem bir kullanım alam bulmuş olacaktır.Boron will continue its importance in the recent world and in the future as a very well-known and necessary industrial rawmaterial with common use areas. Our country is very advantegeous in this point and contains approximately 60 % of total world reserves of boron. Thus production of boron ores is greatly significant for our country. In the Kırka Tincal Concentrator, approximately 250 000 tons wet tailings with a grade of 10 -12 % are produced and separately 4 million tons tailings with similar grade are disposed. Beneficiation from the Kırka Tincal tailings is thereby necessary. In this study, the effective parameters m soda leaching of the Kırka Tincal tailings have been investigated in detail. For this aim, Na2CC>3 and NaHCC>3 leaching of the tailings at different temperature, concentration, solid/liquid ratio and leaching time were carried out. As a conclusion, in the experiments made with aqueous soda solutions, tincal were efficiently extracted and an optimum processing plant proposal was developed. Furthermore, with use of trona in this processing method of the tailings, the great trona deposits will find a different use

Effective spin physics in two-dimensional cavity QED arrays

We investigate a strongly correlated system of light and matter in two-dimensional cavity arrays. We formulate a multimode Tavis–Cummings (TC) Hamiltonian for two-level atoms coupled to cavity modes and driven by an external laser field which reduces to an effective spin Hamiltonian in the dispersive regime. In one-dimension we provide an exact analytical solution. In two-dimensions, we perform mean-field study and large scale quantum Monte Carlo simulations of both the TC and the effective spin models. We discuss the phase diagram and the parameter regime which gives rise to frustrated interactions between the spins. We provide a quantitative description of the phase transitions and correlation properties featured by the system and we discuss graph-theoretical properties of the ground states in terms of graph colourings using Pólya's enumeration theorem