In this paper, we focus on designing feed forward neural network (FFNN) for solving Mixed Volterra – Fredholm Integral Equations (MVFIEs) of second kind in 2–dimensions. in our method, we present a multi – layers model consisting of a hidden layer which has five hidden units (neurons) and one linear output unit. Transfer function (Log – sigmoid) and training algorithm (Levenberg – Marquardt) are used as a sigmoid activation of each unit. A comparison between the results of numerical experiment and the analytic solution of some examples has been carried out in order to justify the efficiency and the accuracy of our method.

Simulation  of  the  Linguistic  Fuzzy Trust  Model  (LFTM)  over  oscillating  Wireless  Sensor Networks (WSNs) where the goodness of the servers belonging to them could change along the time is presented in this paper, and the comparison between the outcomes achieved with LFTM model over oscillating WSNs with the outcomes obtained by applying the model over static WSNs where the servers maintaining always the same goodness, in terms of the selection percentage of trustworthy servers (the accuracy of the model) and the average path length are also presented here. Also in this paper the comparison between the LFTM and the Bio-inspired Trust and Reputation Model for Wireless Sensor Network

In this study, we attempt to provide healthcare service to the pilgrims. This study describes how a multimedia courseware can be used in making the pilgrims aware of the common diseases that are present in Saudi Arabia during the pilgrimage. The multimedia courseware will also be used in providing some information about the symptoms of these diseases, and how each of them can be treated. The multimedia courseware contains a virtual representation of a hospital, some videos of actual cases of patients, and authentic learning activities intended to enhance health competencies during the pilgrimage. An examination of the courseware was conducted so as to study the manner in which the elements of the courseware are applied in real-time learn

The fact of having Journalism being open to people from different orientations professions, working as journalists requiring protection just to spread corruption, is one of the biggest threats faced by journalism.

Journalists noticed the spread of unprincipled journalists with no journalistic ethics amongst them, they tried to protect their profession from these corrupt outsiders who might annihilate the mighty of journalism. The principles of the journalism profession known as journalistic ethics, are one the most important formulations of the law concluded by the journalists and those concerned by the the profession, they were then published in public in order to prove their professionalism, especially for those who don’t und

In this paper, preliminary test Shrinkage estimator have been considered for estimating the shape parameter α of pareto distribution when the scale parameter equal to the smallest loss and when a prior estimate α0 of α is available as initial value from the past experiences or from quaintance cases. The proposed estimator is shown to have a smaller mean squared error in a region around α0 when comparison with usual and existing estimators.

Recent years have seen an explosion in graph data from a variety of scientific, social and technological fields. From these fields, emotion recognition is an interesting research area because it finds many applications in real life such as in effective social robotics to increase the interactivity of the robot with human, driver safety during driving, pain monitoring during surgery etc. A novel facial emotion recognition based on graph mining has been proposed in this paper to make a paradigm shift in the way of representing the face region, where the face region is represented as a graph of nodes and edges and the gSpan frequent sub-graphs mining algorithm is used to find the frequent sub-structures in the graph database of each emotion. T

              Automated clinical decision support system (CDSS) acts as new paradigm in medical services today. CDSSs are utilized to increment specialists (doctors) in their perplexing decision-making. Along these lines, a reasonable decision support system is built up dependent on doctors' knowledge and data mining derivation framework so as to help with the interest the board in the medical care gracefully to control the Corona Virus Disease (COVID-19) virus pandemic and, generally, to determine the class of infection and to provide a suitable protocol treatment depending on the symptoms of patient. Firstly, it needs to determine the three early symptoms of COVID-19 pandemic criteria (fever, tiredness, dry cough and breat

Diesel generators is widely used in Iraq for the purpose of maintaining electric power demand. Large number of operators engaged in this work encounters high level of noise generated by back pack type diesel generators used for this purpose. High level of noise exposure gives different kinds of ill effect on human operators. Exact nature of deteriorated work performance is not known., in present research , quastionaire was adsministered 86 repondents in Baghdad city were exposured to wide range of noise level (80-110) dB(A) with different ages and they have different skill discretion levels. Noise levels A-weigthed decibles dB(A) were measured over 8 weeks two times aday during the 2019 summer using a sound level meter.For predicting the wo

Diesel generators is widely used in Iraq for the purpose of maintaining electric power demand. Large number of operators engaged in this work encounters high level of noise generated by back pack type diesel generators used for this purpose. High level of noise exposure gives different kinds of ill effect on human operators. Exact nature of deteriorated work performance is not known., in present research , quastionaire was adsministered 86 repondents in Baghdad city were exposured to wide range of noise level (80-110) dB(A) with different ages and they have different skill discretion levels. Noise levels A-weigthed decibles dB(A) were measured over 8 weeks two times aday during the 2019 summer using a sound level meter.For predicting the wo

Most recognition system of human facial emotions are assessed solely on accuracy, even if other performance criteria are also thought to be important in the evaluation process such as sensitivity, precision, F-measure, and G-mean. Moreover, the most common problem that must be resolved in face emotion recognition systems is the feature extraction methods, which is comparable to traditional manual feature extraction methods. This traditional method is not able to extract features efficiently. In other words, there are redundant amount of features which are considered not significant, which affect the classification performance. In this work, a new system to recognize human facial emotions from images is proposed. The HOG (Histograms of Or