Crime is a threat to any nation’s security administration and jurisdiction. Therefore, crime analysis becomes increasingly important because it assigns the time and place based on the collected spatial and temporal data. However, old techniques, such as paperwork, investigative judges, and statistical analysis, are not efficient enough to predict the accurate time and location where the crime had taken place. But when machine learning and data mining methods were deployed in crime analysis, crime analysis and predication accuracy increased dramatically. In this study, various types of criminal analysis and prediction using several machine learning and data mining techniques, based o
ABSTRACT— In primary teeth, root canal treatment is a time consuming and challenging procedure, particularly during the most important step in endodontic treatment which is the preparation of the canal. Pulpectomy is the treatment of choice in all the necrotic primary teeth. For better treatment protocol, advancing technology brought the rotary system to reduce the manual dexterity and improve the quality of treatment for pulpectomy. This study aimed to compare and assess the efficacy of cleaning and the time required for the instrumentation during the preparation of root canals of the primary molars using the rotary and the manual (conventional) systems. Thirty root canals of primary teeth were selected. These teeth submitted to a
... Show MoreBackground Solar irradiance is a nonlinear and intermittent function, which makes accurate forecasting of solar power generation a challenge. The high variability of meteorological conditions is not well represented by conventional atmospheric models, thus hampering forecasting skill and model robustness. In this work, an advanced hybridization of multi-population cuckoo search (HMPCS) algorithm with machine learning (ML) methods is developed to enhance the prediction performance of photovoltaic (PV) power forecasting with more reliability. Methods In this study, a hybrid modeling framework is proposed, called HMPCS–ML framework which captures the global search capacity of HMPCS and predictive power of sophisti
... Show MoreIraq faces persistent challenges in achieving sustainable development due to decades of conflict, political instability, and infrastructural degradation. These challenges are particularly evident in critical sectors such as energy, water, healthcare, education, and governance, which significantly influence human well-being, social equity, and quality of life. This study proposes an AI-driven, ethically guided, and human-centric sustainability framework to support resilient urban transformation in Iraq.
This research explores the use of solid polymer electrolytes (SPEs) as a conductive medium for sodium ions in sodium‐ion batteries, presenting a possible alternative to traditional lithium‐ion battery technology. The researchers prepare SPEs with varying molecular weight ratios of polyacrylonitrile (PAN) and sodium tetrafluoroborate (NaBF4) using a solution casting method with dimethyl formamide as the solvent. Through optical absorbance measurements, we identified the PAN:NaBF4 (80:20) SPE composition as having the lowest energy band gap value (4.48 eV). This composition also exhibits high thermal stability based on thermogravimetric analysis results.
Green areas are an essential component of city planning, as they serve as an outlet for them to spend their free time, in addition to the environmental role that these green areas play in improving the city’s climate by purifying the air and beautifying the city. The study’s problem is summarized in identifying the appropriateness of the current spatial distribution of green areas in the city of Najaf with the current population densities and the pattern in which green areas are distributed using GIS and knowing the per capita share of those green areas in the city, the research assumes that the inconsistency of spaces between regions Green and residential neighbourhoods need to c
The CdSe pure films and doping with Cu (0.5, 1.5, 2.5, 4.0wt%) of thickness 0.9μm have been prepared by thermal evaporation technique on glass substrate. Annealing for all the prepared films have been achieved at 523K in vacuum to get good properties of the films. The effect of Cu concentration on some of the electrical properties such as D.C conductivity and Hall effect has been studied.
It has been found that the increase in Cu concentration caused increase in d.c conductivity for pure CdSe 3.75×10-4(Ω.cm)-1 at room temperatures to maximum value of 0.769(Ω.cm)-1 for 4wt%Cu.All films have shown two activation energies, where these value decreases with increasing doping ratio. The maximum value of activation energy was (0.319)eV f
Films of CdSe have been prepared by evaporation technique with thickness 1µm. Doping with Cu was achieved using annealing under argon atmosphere . The Structure properties of these films are investigated by X-ray diffraction analysis. The effect of Cu doping on the orientation , relative intensity, grain size and the lattice constant has been studied. The pure CdSe films have been found consist of amorphous structure with very small peak at (002) plane. The films were polycrystalline for doped CdSe with (1&2wt%) Cu contents and with lattice constant (a=3.741,c=7.096)A°, and it has better crystallinty as the Cu contents increased to (3&5wt%) Cu. The reflections from [(002), (102). (110), (112), and (201)]planes are more prominen
... Show MoreCurrent research aims to find out:
- Effect of using the active learning in the achievement of third grade intermediate students in mathematics.
- Effect of using of active learning in the tendency towards the study of mathematics for students of third grade intermediate.
In order to achieve the goals of the research, the researcher formulated the following two hypotheses null:
- There is no difference statistically significant at the level of significance (0.05) between two average of degrees to achievement
