Today, the science of artificial intelligence has become one of the most important sciences in creating intelligent computer programs that simulate the human mind. The goal of artificial intelligence in the medical field is to assist doctors and health care workers in diagnosing diseases and clinical treatment, reducing the rate of medical error, and saving lives of citizens. The main and widely used technologies are expert systems, machine learning and big data. In the article, a brief overview of the three mentioned techniques will be provided to make it easier for readers to understand these techniques and their importance.

With the vast usage of network services, Security became an important issue for all network types. Various techniques emerged to grant network security; among them is Network Intrusion Detection System (NIDS). Many extant NIDSs actively work against various intrusions, but there are still a number of performance issues including high false alarm rates, and numerous undetected attacks. To keep up with these attacks, some of the academic researchers turned towards machine learning (ML) techniques to create software that automatically predict intrusive and abnormal traffic, another approach is to utilize ML algorithms in enhancing Traditional NIDSs which is a more feasible solution since they are widely spread. To upgrade t

In most manufacturing processes, and in spite of statistical control, several process capability indices refer to non conformance of the true mean (µc ) from the target mean ( µT ), and the variation is also high. In this paper, data have been analyzed and studied for a blow molded plastic product (Zahi Bottle) (ZB). WinQSB software was used to facilitate the statistical process control, and process capability analysis and some of capability indices. The relationship between different process capability indices and the true mean of the process were represented, and then with the standard deviation (σ ), of achievement of process capability value that can reduce the standard deviation value and improve production out of theoretical con

The problem of the current research as the Iraqi Drilling Company suffers from the many challenges facing its work as a result of the current conditions in Iraq and the subsequent changes in the policies of the State Which left an impact on its activities and objectives, which created pressure on the importance of an organizational power capable of diagnosing the core competencies and development and maintain them to contribute to the raising and success in the performance of the company. The researchers adopted the method of analytical research and adopted the questionnaire as a main tool in the collection of research data and information . It was distributed to a community of (140) individuals from the low mana

A microbial desalination cell (MDC) is a new approach to bioelectrochemical systems. It provides a more sustainable way to electrical power production, saltwater desalination, and wastewater treatment at the same time. This study examined three operation modes of the MDC: chemical cathode, air cathode, and biocathode MDC, to give clear sight of this system's performance. The experimental work results for these three modes were recorded as power densities generation, saltwater desalination rates, and COD removal percentages. For the chemical cathode MDC, the power density was 96.8 mW/m², the desalination rate was 84.08 ppm/hr, and the COD removal percentage was 95.94%. The air cathode MDC results were different

In this paper, a FPGA model of intelligent traffic light system with power saving was built. The intelligent traffic light system consists of sensors placed on the side's ends of the intersection to sense the presence or absence of vehicles. This system reduces the waiting time when the traffic light is red, through the transition from traffic light state to the other state, when the first state spends a lot of time, because there are no more vehicles. The proposed system is built using VHDL, simulated using Xilinx ISE 9.2i package, and implemented using Spartan-3A XC3S700A FPGA kit. Implementation and Simulation behavioral model results show that the proposed intelligent traffic light system model satisfies the specified operational req

This paper includes a new life distribution referred to as the alpha power, which has three parameters and is constructed by fitting the two-parameter exponential Weibull distribution to the family of alpha power transformation. The new model named alpha power exponential Weibull distribution (APEWD) with three parameters (α, γ,and β). The basic functions of the distribution, such as the cumulative, probability density, survival, and hazard were presented, in addition to the statistical properties of the APEWD, which were included, as moments, moment generating, skewness, skewness, mode, and median. The parameters were estimated using the Maximum Likelihood Method (MLE). Real data is used to apply criteria such as AIC, BIC, and HQC to co