The proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.

In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete

Manual fruit picking is labor-intensive and can damage fruit. Fully mechanized picking is efficient, but it also risks fruit damage. Therefore, semi-automated tools are needed to improve bitter orange picking. This paper presents a smart manual picker designed to facilitate picking while predicting fruit maturity based on picking force as well as various chemical and physical parameters using machine learning (ML). The study methodology consists of five stages: (1) manufacturing the smart picker, (2) picking 50 bitter orange samples, (3) measuring the characteristics of the bitter oranges in the laboratory, (4) training different ML models, and (5) identifying the most accurate model for predicting fruit maturity. The results indicate that

Irak Türkmen edebiyatının divan şiirlerinde büyük simalardan sayılan , ve

Irak Türklerinin en içli şairi olan Osman Mazlum .Şiirleri yalnızlık hem ve kederle

dolu olan şairin , her zaman büyük bir üzüntüye kablandığı için bunun tüm

şiirlerinde yansıtmıştır . Her zaman kaderden şikayetci olan şiirlerinde (Mazlum)

mahlasını kullanmıştır . Şairin klasik edebiyatında önemli bir yeri vardır . Hoyrat

yoluyla edebiyata giren mazlum'un gönül yarası bu aşıkla dolunca feyizlenmeye

ve türlü nağmelerle seslenmeğe başladı . İşte bu güne kadar yazmış olduğu şiirler

o sesler hep ahang , terennüm ve tesavırıdır . Bende bu araştırmada i

   It is challenging to remove antibiotics from water bodies, as they are among the most widespread contaminants in the environment, particularly with conventional wastewater treatment methods, due to their persistence and low biodegradability. The current study examined the use of nanoscale zero-valent iron to remove antibiotics. Conocarpus leaf extract, which is primarily composed of polyphenols like flavonoids and tannins, was employed as a green source to prepare Fe/Cu nanoparticles, which can act as an eco-friendly reducing agent. The nanoparticles were immobilized onto silica sand (SS), forming SS-Fe/Cu nanocomposite to remove tetracycline (TC) and ciprofloxacin (CIP) from aqueous solutions. The structural characteristics

   There is a growing imperative to extract oil not only through primary and secondary means but also via tertiary recovery methods to meet the escalating global energy demands. Consequently, Enhanced Oil Recovery (EOR) is slated to increase significance in the oil industry in the coming years. The amalgamation of low salinity water (LSW) with chemicals to augment oil recovery has gained substantial traction in recent years owing to its demonstrated effectiveness. In this study, a systematic investigation utilizing contact angle measurements to elucidate the underlying mechanisms was undertaken. The results reveal that the contact angle (CA) demonstrated the effectiveness of the combined fluid in altering the wettability from oil-