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Statistical Analysis and Forecasting of Rainfall Patterns and Trends in Gombe North-Eastern Nigeria
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Rainfall in Nigeria is highly dynamic and variable on a temporal and spatial scale. This has taken a more pronounced dimension due to climate change. In this study, Standard Precipitation Index (SPI) and Mann-Kendall test statistical tools were employed to analyze rainfall trends and patterns in Gombe metropolis between 1990 and 2020 and the ARIMA model was used for making the forecast for ten (10) years. Daily rainfall data of 31 years obtained from Nigerian Meteorological Agency, (NIMET) was used for the study. The daily rainfall data was subjected to several analyses. Standard precipitation index showed that alternation of wet and dry period conditions had been witnessed in the study area. The result obtained showed that there is an upward trend in the annual rainfall amount received in Gombe over the last 31 years at a rate of 3.98 mm/year. The results for the forecast shows that the annual rainfall to be received in Gombe continues in a range above the mean which serves as an indication that the decade will experience more wet years than dry years. The study concludes that the pattern of rainfall in Gombe is a cyclic pattern. The current trend may affect soil moisture, flooding and subsequently lead to ecological change. The study recommends that inhabitants of the study areas should plan their cropping season based on climatic information of their area.

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Publication Date
Wed Jan 01 2025
Journal Name
Springer Proceedings In Humanities And Social Sciences
Language Globalization and the Russian Language: Impact and Trends-العولمة اللغوية واللغة الروسية :التأثير والاتجاهات
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Publication Date
Wed Jan 01 2020
Journal Name
Advances In Intelligent Systems And Computing
Forecasting by Using the Optimal Time Series Method
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Publication Date
Sat Oct 19 2024
Journal Name
Iraqi Statisticians Journal
Forecasting Gold prices by hybrid ANFIS-based algorithm
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In this article, the high accuracy and effectiveness of forecasting global gold prices are verified using a hybrid machine learning algorithm incorporating an Adaptive Neuro-Fuzzy Inference System (ANFIS) model with Particle Swarm Optimization (PSO) and Gray Wolf Optimizer (GWO). The hybrid approach had successes that enabled it to be a good strategy for practical use. The ARIMA-ANFIS hybrid methodology was used to forecast global gold prices. The ARIMA model is implemented on real data, and then its nonlinear residuals are predicted by ANFIS, ANFIS-PSO, and ANFIS-GWO. The results indicate that hybrid models improve the accuracy of single ARIMA and ANFIS models in forecasting. Finally, a comparison was made between the hybrid foreca

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Publication Date
Tue Dec 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Using Artificial Neural Network Models For Forecasting & Comparison
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The Artificial Neural Network methodology is a very important & new subjects that build's the models for Analyzing, Data Evaluation, Forecasting & Controlling without depending on an old model or classic statistic method that describe the behavior of statistic phenomenon, the methodology works by simulating the data to reach a robust optimum model that represent the statistic phenomenon & we can use the model in any time & states, we used the Box-Jenkins (ARMAX) approach for comparing, in this paper depends on the received power to build a robust model for forecasting, analyzing & controlling in the sod power, the received power come from

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Publication Date
Sun Jul 02 2017
Journal Name
Journal Of Educational And Psychological Researches
Prevalence of Posttraumatic Stress Symptomatology and Distribution of Attachment Patterns 1 and 5 Months after a Terrorist Attack
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As a consequence of a terrorist attack, people may experience posttraumatic stress disorder (PTSD) and lack of feeling secure in relationships. This longitudinal study aimed to examine the prevalence of PTSD symptoms over time, the relationship between adult attachment styles and PTSD, as well as their association with degree of exposure, and finally to consider the distribution and the trajectory of attachment styles. The sample consisted of 235 students (M=125, F=110) who were exposed to different levels of trauma intensity in response to a bombing attack. Participants were recruited and assessed approximately 1 month and 5 months after the attack using a battery of questionnaires. Findings revealed, as expected, that 79.5% of the part

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Publication Date
Mon Jun 30 2025
Journal Name
Babcock University Medical Journal
Microbial Diversity and Antibiotic Resistance Patterns in Burn and Wound Infections: A Study from the Al-Kindy Teaching Hospital, Iraq
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Objective: Comprehending microbial diversity and antibiotic resistance patterns is essential for efficient treatment protocols. This study sought to determine the incidence of bacterial and fungal pathogens responsible for burn and wound infections and their antibiotic susceptibility profiles. Methods: This cross-sectional study involved 140 patients with burn or wound infections. Sterile swabs and pus aspiration were employed to collect samples, which were subsequently processed using standard microbiological procedures. Antibiotic resistance was determined using the Kirby-Bauer disc diffusion method, following Clinical and Laboratory Standards Institute (CLSI) guidelines. Data was analysed using IBM SPSS version 25.0, and the Chi-

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Publication Date
Thu Nov 21 2019
Journal Name
Al-kindy College Medical Journal
Prevalence And Antimicrobial Susceptibility Patterns Of Bacteria Isolated From Urinary Tract Infections (UTIs) In Children At Children Hospital In Baghdad
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Background: First six to twelve months after initial urinary tract infection, most infections are caused by Escherichiacoli, although in the first year of life Klebsiella pneumoniae, Pseudomonas, Enterobacter spp andEnterococcus spp, are more frequent than later in life, and there is a higher risk of urosepsis compared with adulthood

Objectives: To determine the prevalence of bacterial isolates from Urinary Tract Infections of children at a children hospital in Baghdad and their antimicrobial susceptibility patterns.

Type of the study: Cross-sectional study.

Methods: During six months of study (1 June to 31 Dece

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Publication Date
Wed Jan 01 2014
Journal Name
The Saudi Journal For Dental Research
Oral cancer trends in Iraq from 2000 to 2008
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Abstract Background The aim of this study was to identify differences in oral cancer incidence among sexes, age groups and oral sites over time in Iraqi population. Methods Data was obtained from Iraqi cancer registry, differences and trends were assessed with the Wilcoxon matched-pairs signed-ranks test and Regression test, respectively. Results In Iraq from 2000 to 2008, there were 1787 new cases of oral cancer registered, 1035 in men and 752 in women. Cancer at all oral sites affected men more than women. The Tongue other (ICD-02) is the most frequent site follow by lip (ICD-00). Conclusion The decrease in the percent of oral cancer incidence in Iraq not compatible with the high percent of exposure to the risk factors, Iraqi cancer regis

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Publication Date
Fri Feb 28 2025
Journal Name
Energies
Synergizing Machine Learning and Physical Models for Enhanced Gas Production Forecasting: A Comparative Study of Short- and Long-Term Feasibility
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Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

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Publication Date
Wed Oct 20 2021
Journal Name
Journal Of Engineering Research
Effect of several patterns of floating stone columns on the bearing capacity and porewater pressure in saturated soft soil
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One of the common geotechnical problems is the construction on soft soil and the improvement of its geotechnical properties to meet the design requirements. A stone column is one of the well-known techniques used to improve the geotechnical properties of soft soils. Sometimes thick layers of soft soil imposed the designer to use floating stone columns for improvement of such soil; in this case, the designer will be lost the end bearing of the stone column. In this study, the effects of several patterns of floating stone columns distribution under footing on the bearing capacity of soil and the distribution of excess porewater pressure are investigated. The soft soil used in this study has a very low undrained shear strength (cu) of

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