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

Channel estimation (CE) is essential for wireless links but becomes progressively onerous as Fifth Generation (5G) Multi-Input Multi-Output (MIMO) systems and extensive fading expand the search space and increase latency. This study redefines CE support as the process of learning to deduce channel type and signal-tonoise ratio (SNR) directly from per-tone Orthogonal Frequency-Division Multiplexing (OFDM) observations,with blind channel state information (CSI). We trained a dual deep model that combined Convolutional Neural Networks (CNNs) with Bidirectional Recurrent Neural Networks (BRNNs). We used a lookup table (LUT) label for channel type (class indices instead of per-tap values) and ordinal supervision for SNR (0–20 dB,5-dB steps). T

The research aims to achieve a set of the most important objectives of the review of the role of creative administrative leadership in achieving aspects of economic reform in various government institutions and indicate the role of supervisory awareness of administrative leadership in the revitalization of the role of the internal control system to achieve the best use of available resources. This paper deals with three problems is the loss of financial resources of the state as a result of the growing phenomenon of administrative and financial corruption in the majority of government institutions, and the weakness of the role of the internal control system in the province on the resources available and to achieve the best use of these reso

       Canonical correlation analysis is one of the common methods for analyzing data and know the relationship between two sets of variables under study, as it depends on the process of analyzing the variance matrix or the correlation matrix. Researchers resort to the use of many methods to estimate canonical correlation (CC); some are biased for outliers, and others are resistant to those values; in addition, there are standards that check the efficiency of estimation methods.

In our research, we dealt with robust estimation methods that depend on the correlation matrix in the analysis process to obtain a robust canonical correlation coefficient, which is the method of Biwe

Anomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the

This research attempts to evaluate the role of the information system by highlighting its importance in providing date and information to the tax administration the process of tax accounting for those who are subject to income tax whether they are individuals or companies where the effective information system provides accurate and reliable information in a timely manner.

At the theoretical part of the research, the research approaches the problem of the research represented in that whether the information system, applied in the General Commission for Taxes, is capable of achieving its role in reducing the phenomenon of tax evasion. The existence of a set of things which in the Commission may lead to increase tax evasion by taxpa

The power of the state in Iraq has been influenced by legitimacy, which may have resembled the belt of transmission, affecting the rule of law and social cohesion. The emergence of the political system may have come about as a result of balancing the competing forces within society today as a basis for collective action. The country's march in Iraq was not a result of a series of gradual transitions such as the established ones. For almost a century, there was an extraordinary succession of succession. At each of the three stages of the state there was an internal or external change. They change or disintegrate and others appear. Social and economic conditions may change or the society is exposed to external invasion or our ideas are imp

This study had succeeded in producing a new graphical representation of James abacus called nested chain abacus. Nested chain abacus provides a unique mathematical expression to encode each tile (image) using a partition theory where each form or shape of tile will be associated with exactly one partition.Furthermore, an algorithm of nested chain abacus movement will be constructed, which can be applied in tiling theory.

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a