Existing leachate models over–or underestimates leachate generation by up to three orders of magnitude. Practical experiments show that channeled flow in waste leads to rapid discharge of large leachate volumes and heterogeneous moisture distribution. In order to more accurately predict leachate generation, leachate models must be improved. To predict moisture movement through waste, the two–domain PREFLO, are tested. Experimental waste and leachate flow values are compared with model predictions. When calibrated with experimental parameters, the PREFLO provides estimates of breakthrough time. In the short term, field capacity has to be reduced to 0.12 and effective storage and hydraulic conductivity of the waste must be increased to

shoulder joint by preparing special exercises for the youth-category wrestling, and through the researchers' follow-up to the wrestling game and their work in the field of rehabilitation and physical therapy, noticing that most of the wrestling players suffer from the shoulder joint pain despite their visit to the specialist doctor and take Treatment, so the researchers saw to study this problem and restore the recovery of the injured through special exercises and a suitable qualification program for the shoulder joint muscles, the goal of research in preparing special exercises and knowing its effect on the rehabilitation of the background muscle of the shoulder for the youth wrestling category. The researchers assumed that there are stati

The sports institutions in general are affected and contact with sport in particular the environmental factor, whether political or economic, which makes them in constant need to consider their administrative applications to increase the confidence of their employees because of their suitability or consistency with the new reality according to the sports activities that relate to it, The stalemate in administrative and technical aspects of the administrative work method in the majority of the Olympic sports federations makes the achievement of most of the goals far from the present reality, and the selection of suitable alternatives to achieve the objectives by those who disagree with the concepts of modern dictatorial standards It leads to

The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti

Total dissolved solids are at the top of the parameters list of water quality that requires investigations for planning and management, especially for irrigation and drinking purposes. If the quality of water is sufficiently predictable, then appropriate management is possible. In the current study, Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) models were used as indicators of water quality and for the prediction of Total Dissolved Solids (TDS) along the Tigris River, in Baghdad city. To build these models five water parameters were selected from the intakes of four water treatment plants on the Tigris River, for the period between 2013 and 2017. The selected water parameters were Total Dissolved Solids (TDS

Autorías: Suhair Meteab Munaf, Ali Abdulateef Ali, Mohannad Salman Dawood. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 4, 2022. Artículo de Revista en Dialnet.

     A new colorimetric-flow injection method has been developed and validated for the detection of Cefotaxime sodium in pharmaceutical formulations. This method stands out for its rapid and sensitive nature. The formation of a brown-colored complex between Cefotaxime sodium and the Biuret reagent in a highly alkaline environment serves as the basis for the detection. The intensity of this colored complex is measured using a custom-built Continuous Flow Injection Analyzer, enabling accurate quantification of Cefotaxime sodium. Optimization studies of the chemical and physical parameters such as dilution of Biuret reagent, effect of the medium basicity, flow rate, sample loop and others have been investigated. The calibration gra

Credit risk assessment has become an important topic in financial risk administration. Fuzzy clustering analysis has been applied in credit scoring. Gustafson-Kessel (GK) algorithm has been utilised to cluster creditworthy customers as against non-creditworthy ones. A good clustering analysis implemented by good Initial Centres of clusters should be selected. To overcome this problem of Gustafson-Kessel (GK) algorithm, we proposed a modified version of Kohonen Network (KN) algorithm to select the initial centres. Utilising similar degree between points to get similarity density, and then by means of maximum density points selecting; the modified Kohonen Network method generate clustering initial centres to get more reasonable clustering res

New membrane electrodes for determination of ciprofloxacin hydrochloride were prepared depending on ciprofloxacin hydrochloride - phosphotungstic acid (CFH-PT) as an active material and these electrodes were made with three plasticizers: Di-octylphenylphosphonate(DOPH), Di-butyl phosphate (DBP)Tri-n-butyl phosphate(TBP), in PVC matrix. One of the ciprofloxacin electrodes was gave Nernstian slope equal to 57.21 mV/ decade for DOPH membrane with concentration range from 1.5×10-5 to1.0×10-1 M, and detection limit equal to 1.5×10-6 M .Lifetime was 93 days. Non- Nernstian responses equal to 39.40 and 30.70 mV/ decade for membranes DBP, TBP, respectively. These electrodes were gave concentration range from 1.0× 10-5 to 1.0×10-2 and from 4.0

The purpose of this study is to investigate the research on artificial intelligence algorithms in football, specifically in relation to player performance prediction and injury prevention. To accomplish this goal, scholarly resources including Google Scholar, ResearchGate, Springer, and Scopus were used to provide a systematic examination of research done during the last ten years (2015–2025). Through a systematic procedure that included data collection, study selection based on predetermined criteria, categorisation based on AI applications in football, and assessment of major research problems, trends, and prospects, almost fifty papers were found and analysed. Summarising AI applications in football for performance and injury p