The idea of this research is the basis of the role exercised by the dimensions of performance management (Performance Planning- performance evaluation- improve the performance and development- feedback - Review and Performance Monitor) In order to achieve the success Organizational Is through the (strategic vision- the operational activity- development of the company- selection of personnel- the company's culture- Leadership and Management- Personal Development - Assessment and Review).And The research aims to identify the extent of the responsibility of performance management in achieving success  Organizational through main hypotheses branched out by the sub-hypotheses to knowing out the&nbs

The power generation of solar photovoltaic (PV) technology is being implemented in every nation worldwide due to its environmentally clean characteristics. Therefore, PV technology is significantly growing in the present applications and usage of PV power systems. Despite the strength of the PV arrays in power systems, the arrays remain susceptible to certain faults. An effective supply requires economic returns, the security of the equipment and humans, precise fault identification, diagnosis, and interruption tools. Meanwhile, the faults in unidentified arc lead to serious fire hazards to commercial, residential, and utility-scale PV systems. To ensure secure and dependable distribution of electricity, the detection of such ha

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

The research aims to identify the availability of some basic competencies that are required to be available to workers in digital agricultural Extension from the point of view of senior management, middle management, and, employees with Post-graduate education degrees, represented by the following: Transition to digital agricultural Extension for sustainable and smart family farms, benefiting from international expertise and experiences in applying for Digital agricultural Extension, preparing and implementing Extension messages through platforms, factors affecting the effectiveness of digital agricultural Extension and its platforms, following up and evaluating the activities and programs of the digital Extension platform. The research pop

Several studies have indicated that more than 600 cities in the world (intermas of rapid growth and development) will generate about 60% of international economic growth between 2010 and 2025 . by 2025 , 66% of the worlds population will live in urban areas the management of cities will face challenges that accompany this increase in the population which requires preparing to face these challenges and problems and the need to provide the aim of the research to know the readiness of Baghdad city to implement the strategies of urban management throught on asmple representing the ( Advisiry group for the comprechnsive development plan for the city of Baghdad 2030 and its supporters ) in the municipality of Baghdad and the number of

In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.

In this paper, the memorization capability of a multilayer interpolative neural network is exploited to estimate a mobile position based on three angles of arrival. The neural network is trained with ideal angles-position patterns distributed uniformly throughout the region. This approach is compared with two other analytical methods, the average-position method which relies on finding the average position of the vertices of the uncertainty triangular region and the optimal position method which relies on finding the nearest ideal angles-position pattern to the measured angles. Simulation results based on estimations of the mobile position of particles moving along a nonlinear path show that the interpolative neural network approach outperf