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 predictions, predicting injuries and analysing related risks, and evaluating player performance using AI models are the three main topics highlighted in the study. This study highlights the use of AI algorithms in the sports field to predict injuries and predict team or player performance, especially in football.
The subject of the research seeks to indicate the level of influence of emotional intelligence in the empowerment of workers in the Ministry of Industry and Minerals General Company for Food Products. The research problem is illustrated by knowing all of the following:
- The level of the relationship between emotional intelligence in promoting the empowerment of employees of the Ministry of Industry and Minerals.
- The impact of emotional intelligence on the empowerment of workers in the ministry.
- Recognize the interest of the management of the Ministry of Industry and Minerals in emotional intelligence and the
Background : The kidneys may be injured in abdominal trauma, both blunt & penetrating. Renal trauma may manifest in a dramatic fashion for both the patient and the clinician. Objectives: To evaluate the incidence, management, morbidity &mortality of renal injury in blunt & penetrating abdominal trauma.
Results:The majority o f patients were males (35= 77.8%), the rest were females (10= 22.2%). The average age was 37 years (range= 18-56 years). The most common grades were grade1, grade2 and grade3 (40=88.9%), while 5 patients (11.1%) were grades 4 and 5.The most common associated injuries were liver, spleen, small & large bowels and diaphragm. The mortality was 20% (9 patients). The most common cause of death was multip
The aim of this paper is to identify Nano-particles that have been used in diagnosis and treatment of leishmaniasis in Iraq. All experiments conducted in this field were based on the following nanoparticles: gold nanoparticles, silver nanoparticles, zinc nanoparticles, and sodium chloride nanoparticles. Most of these experiments were reviewed in terms of differences in the concentrations of nanoparticles and the method that was used in the experiments whether it was in vivo or in vitro. These particles used in most experiments succeeded in inhibiting the growth of Leishmania parasites.
In addition to the primary treatment, biological treatment is used to reduce inorganic and organic components in the wastewater. The separation of biomass from treated wastewater is usually important to meet the effluent disposal requirements, so the MBBR system has been one of the most important modern technologies that use plastic tankers to transport biomass with wastewater, which works in pure biofilm, at low concentrations of suspended solids. However, biological treatment has been developed using the active sludge mixing process with MBBR. Turbo4bio was established as a sustainable and cost-effective solution for wastewater treatment plants in the early 1990s and ran on minimal sludge, and is easy to maintain. This
... Show MoreSensibly highlighting the hidden structures of many real-world networks has attracted growing interest and triggered a vast array of techniques on what is called nowadays community detection (CD) problem. Non-deterministic metaheuristics are proved to competitively transcending the limits of the counterpart deterministic heuristics in solving community detection problem. Despite the increasing interest, most of the existing metaheuristic based community detection (MCD) algorithms reflect one traditional language. Generally, they tend to explicitly project some features of real communities into different definitions of single or multi-objective optimization functions. The design of other operators, however, remains canonical lacking any inte
... Show MoreBackground: The spleen is the most common solid
organ injured in patients who had sustained abdominal
trauma. Such injuries to the spleen represent
approximately one quarter of all blunt injuries of the
abdominal viscera.
Due to its remarkable vasculature and its fragile
structure, splenic rupture is the most widespread cause
of intra-abdominal hemorrhage.
Objective: To assess the magnitude of splenic injury,
the management of splenic injury, and to evaluate the
postoperative complications.
Methods: A prospective study of 57 cases of splenic
injury was performed in Al-Kadhimiya Teaching
Hospital during the period between the 1st of October
2004 and the 1st of October 2006. Statistical analysis
Accurate prediction and optimization of morphological traits in Roselle are essential for enhancing crop productivity and adaptability to diverse environments. In the present study, a machine learning framework was developed using Random Forest and Multi-layer Perceptron algorithms to model and predict key morphological traits, branch number, growth period, boll number, and seed number per plant, based on genotype and planting date. The dataset was generated from a field experiment involving ten Roselle genotypes and five planting dates. Both RF and MLP exhibited robust predictive capabilities; however, RF (R² = 0.84) demonstrated superior performance compared to MLP (R² = 0.80), underscoring its efficacy in capturing the nonlinear genoty
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