Psychosocial Alienation is a modern concept that arises from the capitalist and materialistic conceptions of individuals. The evergrowing competitive nature of domestic societies crystallised the concept in its modern form. The intensity of the rapid changes in the urbanised societies prevents the individuals from exploring their inner selves. Thus, a new generation is created with an alienation crisis which is reflected inward towards the self and outwards toward society. Alan Ayckbourn (1939), A British playwright, presents Alienated characters inspired by his life on and off stage. He explores their Alienation and their path toward recovery and self-realization. A Brief History of Women (2017) Ayckbourn explores the depth of the individu

The research is Concerned the Relationship between Self Management which is a modern administrative term and its dimensions "Self Control, Trust, and Conscientiousness" with the Hardiness and its dimensions "Challenge, Commitment, and Control". And the impact of the first variable on the second in The Hospital of Alshaheed Gaze Alharery.

The Questionnaire used and distributed on sample (60) Persons, contain from (40) Doctor, and (20) Employees from the total society (103).

The statistical methods have been used for testing the hypothesis is the mean, standard deviation correlation coefficient.

    The resea

The objective of this study was tointroduce a recursive least squares (RLS) parameter estimatorenhanced by using a neural network (NN) to facilitate the computing of a bit error rate (BER) (error reduction) during channels estimation of a multiple input-multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system over a Rayleigh multipath fading channel.Recursive least square is an efficient approach to neural network training:first, the neural network estimator learns to adapt to the channel variations then it estimates the channel frequency response. Simulation results show that the proposed method has better performance compared to the conventional methods least square (LS) and the original RLS and it is more robust a

ANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data

Software Defined Networking (SDN) with centralized control provides a global view and achieves efficient network resources management. However, using centralized controllers has several limitations related to scalability and performance, especially with the exponential growth of 5G communication. This paper proposes a novel traffic scheduling algorithm to avoid congestion in the control plane. The Packet-In messages received from different 5G devices are classified into two classes: critical and non-critical 5G communication by adopting Dual-Spike Neural Networks (DSNN) classifier and implementing it on a Virtualized Network Function (VNF). Dual spikes identify each class to increase the reliability of the classification

Seven fish species were collected from the drainage network at Al-Madaen region, south of
Baghdad with the aid of a cast net during the period from March to August 1993. These fishes
were infected with 22 parasite species (seven sporozoans, three ciliated protozoans, seven
monogeneans, two nematodes, one acanthocephalan and two crustaceans) and one fungus
species. Among such parasites, Chloromyxum wardi and Cystidicola sp. are reported here for
the first time in Iraq. In addition, 11 new host records are added to the list of parasites of
fishes of Iraq.

In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

Deep submicron technologies continue to develop according to Moore’s law allowing hundreds of processing elements and memory modules to be integrated on a single chip forming multi/many-processor systems-on-chip (MPSoCs). Network on chip (NoC) arose as an interconnection for this large number of processing modules. However, the aggressive scaling of transistors makes NoC more vulnerable to both permanent and transient faults. Permanent faults persistently affect the circuit functionality from the time of their occurrence. The router represents the heart of the NoC. Thus, this research focuses on tolerating permanent faults in the router’s input buffer component, particularly the virtual channel state fields. These fields track packets f

Purpose/ to build clear perceptions about the level of the effects of organizational failures on the competitiveness of dairy factories and the role of dynamic knowledge capabilities in minimizing these impacts

Mythology/ Design approach Use deduction approach, the research was conducted in four dairy factories in Baghdad (Abu Ghraib, Agriculture, Halal and Ayon Al-Rafidain). It was applied to a sample of (155) individuals representing a sample of the research community from factory owners, managers, Engineers, technicians and experienced workers in the dairy industry. The questionnaire was used as a main tool for collecting data, information and statistical tools in the extraction, testing and analysis o