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

An attempt was made to evaluate the PV performance of one-axis daily tracking and fixed system for Baghdad, Iraq. Two experimental simulations were conducted on a PV module for that purpose. Measurements included incident solar radiation, load voltage and load current. The first experiment was carried out for six months of winter half of year to simulate the one-axis daily tracking. The azimuth angle was due south while the tilt angle was being set to optimum according to each day of simulation. The second experiment was done at one day to simulate the PV module of fixed angles. It is found that there is a significant power gain of 29.6% for the tracking system in respect to the fixed one. The one-axis daily tracking was much more effect

To ensure fault tolerance and distributed management, distributed protocols are employed as one of the major architectural concepts underlying the Internet. However, inefficiency, instability and fragility could be potentially overcome with the help of the novel networking architecture called software-defined networking (SDN). The main property of this architecture is the separation of the control and data planes. To reduce congestion and thus improve latency and throughput, there must be homogeneous distribution of the traffic load over the different network paths. This paper presents a smart flow steering agent (SFSA) for data flow routing based on current network conditions. To enhance throughput and minimize latency, the SFSA distrib

In some cases, researchers need to know the causal effect of the treatment in order to know the extent of the effect of the treatment on the sample in order to continue to give the treatment or stop the treatment because it is of no use. The local weighted least squares method was used to estimate the parameters of the fuzzy regression discontinuous model, and the local polynomial method was used to estimate the bandwidth. Data were generated with sample sizes (75,100,125,150 ) in repetition 1000. An experiment was conducted at the Innovation Institute for remedial lessons in 2021 for 72 students participating in the institute and data collection. Those who used the treatment had an increase in their score after

This study aims to develop a thermosensitive mucoadhesive periodontal in situ gel of secnidazole for local release of drug for treatment of periodontitis, in order to increase the drug residence time and to increase patient compliance while lowering the side effects of the drug.

Cold method was used to prepare 30 formulas of secnidazole periodontal in situ gel, using different concentrations of thermosensitive polymers (poloxamer407 alone or in combination with poloxamer 188) and methyl cellulose (MC ) or hydroxypropyl methylcellulose (HPMC K4M )in different concentrations used as mucoadhesive polymer and the resultant formulations were subjected to several tests such as   gelation temperature GT, appearance and pH value. The fo

This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number

lar water heating systems with heat pipes of three diameter groups of 16, 22 and 28.5 mm. The first and third groups had evaporator lengths of 1150, 1300 and 1550 mm. The second group had an additional length of 1800 mm. all heat pipes were of fixed condenser length of 200 mm. Ethanol at 50% fill charge ratio of the evaporator volume was used as the heat pipes working fluid. Each heat pipe condenser section was inserted in a storage tank and the evaporator section inserted into an evacuated glass tube of the Owens- Illinois type. The combined heat pipe and evacuated glass tube form an active solar collector of a unique design.
The resulting ten solar water heating systems were tested outdoors under the meteorological conditions of Bag