The bit record is a part from the daily drilling report which is contain information about the type and the number of the bit that is used to drill the well, also contain data about  the used weight on bit  WOB ,revolution per minute RPM , rate of penetration ROP, pump pressure ,footage drilled and bit dull grade. Generally we can say that the bit record is a rich brief about the bit life in the hole. The main purpose of this research is to select the suitable bit to drill the next oil wells because the right bit selection avoid us more than one problems, on the other hand, the wrong bit selection cause more than one problem. Many methods are related to bit selection, this research is familiar with four of thos

This paper offers a systemic review of the deep learning methods to detect violence on campus, which is a critical issue in intelligent surveillance to improve the student safety and prompt cut off of violent accidents. The review reviews studies published 2018-2025, concentrating on model structure to detect fights, bullying, vandalism, and aggressive behavior on problematic campuses due to occlusion and light variations and complicated human interactions. The research design includes a comparative study of different deep learning networks, such as CNNs, RNNs, 3D CNNs, attention-based networks, transformers, graph neural networks, neuro-fuzzy, and multimodal systems and federated learning methods. The paper also assesses benchmark

  The research explain the developments in the structure of government Expenditure for the period (1990-2014), this period include tow different periods in terms of the conditions, the first period (1990-2002)characterized by imposing the economic sanctions and deny the Iraqi economy from the oil revenues, while the second period (2003-2014) marked by abundance resource rents as a result of lifting the ban on oil exports, (autoregressive Distributed lag Model) has been used to measure the impact of government Expenditure in both side current and investment in the oil-GDP (gross domestic product) and non oil-GDP, the stady found that there is no significant relationship between current Expenditure in non-oil and oil-GDP in bo

This paper includes a comparison between denoising techniques by using statistical approach, principal component analysis with local pixel grouping (PCA-LPG), this procedure is iterated second time to further improve the denoising performance, and other enhancement filters were used. Like adaptive Wiener low pass-filter to a grayscale image that has been degraded by constant power additive noise, based on statistics estimated from a local neighborhood of each pixel. Performs Median filter of the input noisy image, each output pixel contains the Median value in the M-by-N neighborhood around the corresponding pixel in the input image, Gaussian low pass-filter and Order-statistic filter also be used.

Experimental results shows LPG-

   In this paper , two method which deal with finding the optimal value for adaptive smoothing constant, are compared .This constant is used in adaptive Single Exponential Smoothing (ASES).

The comparing is between a method uses time domain and another uses frequency domain when the data contain outlier value for autoregressive model of order one AR(1) , or Markov Model, when the time series are stationary and non stationary with deferent samples .    

Tax governance is a set of legal means that directs the tax administration to deal in good faith with taxpayers based on transparency, integrity and accountability while ensuring the achievement of tax justice and works to introduce advanced means by which it deals with all stakeholders.

      In this study, we try to explain its rooting and legal nature by shedding light on the position of some international organizations and their internal legislation in the context of public finance.

المستخلص يهدف هذا البحث الى تجاوز مشكلة البعدية من خلال طرائق الانحدار اللامعلمي والتي تعمل على تقليل جذر متوسط الخطأ التربيعي (RMSE) , أذ تم  استعمال طريقة انحدار الاسقاطات المتلاحقة  (PPR)    ,والتي تعتبر احدى طرائق اختزال الابعاد التي تعمل على تجاوز مشكلة البعدية (curse of dimensionality) , وان طريقة (PPR) من التقنيات الاحصائية التي تهتم بأيجاد الاسقاطات الاكثر أهمية في البيانات المتعددة الابعاد , ومع ايجاد كل اسقاط

The need for participants’ performance assessments in academia and industry has been a growing concern. It has attendance, among other metrics, is a key factor in engendering a holistic approach to decision-making. For institutions or organizations where managing people is an important yet challenging task, attendance tracking and management could be employed to improve this seemingly time-consuming process while keeping an accurate attendance record. The manual/quasi-analog approach of taking attendance in some institutions could be unreliable and inefficient, leading to inaccurate computation of attendance rates and data loss. This work, therefore, proposes a system that employs embedded technology and a biometric/ w

This paper includes a comparison between denoising techniques by using statistical approach, principal component analysis with local pixel grouping (PCA-LPG), this procedure is iterated second time to further improve the denoising performance, and other enhancement filters were used. Like adaptive Wiener low pass-filter to a grayscale image that has been degraded by constant power additive noise, based on statistics estimated from a local neighborhood of each pixel. Performs Median filter of the input noisy image, each output pixel contains the Median value in the M-by-N neighborhood around the corresponding pixel in the input image, Gaussian low pass-filter and Order-statistic filter also be used. Experimental results shows LPG-PCA method

Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l