This research dealt with the analysis of murder crime data in Iraq in its temporal and spatial dimensions, then it focused on building a new model with an algorithm that combines the characteristics associated with time and spatial series so that this model can predict more accurately than other models by comparing them with this model, which we called the Combined Regression model (CR), which consists of merging two models, the time series regression model with the spatial regression model, and making them one model that can analyze data in its temporal and spatial dimensions. Several models were used for comparison with the integrated model, namely Multiple Linear Regression (MLR), Decision Tree Regression (DTR), Random Forest Regression (RFR) and Neural Network Regression (NNR). The data used is about the monthly numbers of murder crimes for the police directorates in Baghdad and the governorates during the period from January 2015 to June 2023. The data was analyzed and then divided into two sets, a training and testing set, to perform these models in prediction. The accuracy of each modsl’s performance was evaluated using two statistical measures: RMSE and in order to determine the best and most accurate performing model among the selected models. An important result was obtained in the comparison between these models, as the combined model obtained the most accurate performance than the other models, based on the values of the performance accuracy metrics for each model in relation to the data used in the murder crimes.
In this golden age of rapid development surgeons realized that AI could contribute to healthcare in all aspects, especially in surgery. The aim of the study will incorporate the use of Convolutional Neural Network and Constrained Local Models (CNN-CLM) which can make improvement for the assessment of Laparoscopic Cholecystectomy (LC) surgery not only bring opportunities for surgery but also bring challenges on the way forward by using the edge cutting technology. The problem with the current method of surgery is the lack of safety and specific complications and problems associated with safety in each laparoscopic cholecystectomy procedure. When CLM is utilize into CNN models, it is effective at predicting time series tasks like iden
... Show MoreThe other day in the Holy Quran and the four Gospels
New microphotometer was constructed in our Laboratory Which deals with the determination of Molybdenum (VI) through its Catalysis effect on Hydrogen peroxide and potasum iodide Reaction in acid medium H2SO4 0.01 mM. Linearity of 97.3% for the range 5- 100 ppm. The repeatability of result was better than 0.8 % 0.5 ppm was obtanined as L.U. (The method applied for the determination of Molybdenum (VI) in medicinal Sample (centrum). The determination was compared well with the developed method the conventional method.
Future generations of wireless networks are expected to heavily rely on unmanned aerial vehicles (UAVs). UAV networks have extraordinary features like high mobility, frequent topology change, tolerance to link failure, and extending the coverage area by adding external UAVs. UAV network provides several advantages for civilian, commercial, search and rescue applications. A realistic mobility model must be used to assess the dependability and effectiveness of UAV protocols and algorithms. In this research paper, the performance of the Gauss Markov (GM) and Random Waypoint (RWP) mobility models in multi-UAV networks for a search and rescue scenario is analyzed and evaluated. Additionally, the two mobility models GM and RWP are descr
... Show MoreIn this paper solar radiation was studied over a region of Baghdad (Latitude 33.3o and longitude 44.4o). The two parts of global solar radiation: diffuse and direct solar radiation were estimated depending on the clearance index of measured data (Average Monthly mean global solar radiation). Metrological data of measured (average monthly mean diffuse and direct solar radiation) were used to comparison the results and show the agreement between them. Results are determined by applying Liu and Jordan two models (1960). Excel 2007program is used in calculation, graphics and comparison the results.
يعد تحليل العلاقات الكمية بين البنية والممتلكات/النشاط (QSPR/QSAR) أمرًا بالغ الأهمية لفهم خصائص المركبات المرتبطة بالمخدرات، خاصة في علاج مرض الزهايمر. في هذه الدراسة، هدفنا هو استخدام أساليب مبتكرة بما في ذلك استخدام المؤشرات الطوبولوجية -درجة و- درجة ، المستمدة من نظرية الرسم البياني، لتقييم الخصائص والخصائص الفيزيائية والكيميائية لخمسة أدوية لمرض الزهايمر: تاكرين، دونيبيزيل، ريفيستيجمين، جالانتامي
... Show MoreThe manual classification of oranges according to their ripeness or flavor takes a long time; furthermore, the classification of ripeness or sweetness by the intensity of the fruit’s color is not uniform between fruit varieties. Sweetness and color are important factors in evaluating the fruits, the fruit’s color may affect the perception of its sweetness. This article aims to study the possibility of predicting the sweetness of orange fruits based on artificial intelligence technology by studying the relationship between the RGB values of orange fruits and the sweetness of those fruits by using the Orange data mining tool. The experiment has applied machine learning algorithms to an orange fruit image dataset and performed a co
... Show MoreThe university Service employee is considered one of the categories of public employees, However, The academic and administrative tasks duties that undertakes have made him a special importance and a distinguished legal status, Therefore, we find That the Iraqi legislatures assigned this category a special Law, it is the university Service law No (23) of 2008 as amended who dealt with some aspects related to serving this category, such as duties, right, condition for appointment and award of academic titles, and financial allocation, such as university service allocation, academic title allocations, and some other Provisions leaving other matters to the general service laws and employee discipline, among the matters that the legislator negl
... Show MoreWireless sensor networks (WSNs) represent one of the key technologies in internet of things (IoTs) networks. Since WSNs have finite energy sources, there is ongoing research work to develop new strategies for minimizing power consumption or enhancing traditional techniques. In this paper, a novel Gaussian mixture models (GMMs) algorithm is proposed for mobile wireless sensor networks (MWSNs) for energy saving. Performance evaluation of the clustering process with the GMM algorithm shows a remarkable energy saving in the network of up to 92%. In addition, a comparison with another clustering strategy that uses the K-means algorithm has been made, and the developed method has outperformed K-means with superior performance, saving ener
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