Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm

Attention has recently been given to finding alternative and sustainable raw material sources for wood and metal adhesives, such as polyvinyl alcohol (PVA), corn starch (CS), arabic gum (AG), and dextrins (D). Modifying polymer dispersion using unique substances, such as modifying reactive elastomer liquid (EL) using PVA, CS, AG, or D results in sufficiently moisture-resistant adhesive joins. In the present study, the physical characteristics of EL/blended with the natural polymers PVA, CS, AG, and D, based on high-density fiberboard (HDF) wood and aluminum (Al) adhesives and coatings, were investigated and compared to those of pure EL. The EL was blended with PVA, CS, AG, or D at a ratio of 60/40 (w/w) to form EL/blends. The che

Abstract

 A surface fitting model is developed based on calorimeter data for two famous brands of household compressors. Correlation equations of ten coefficient polynomials were found as a function of refrigerant saturating and evaporating temperatures in range of (-35℃ to -10℃) using Matlab software for cooling capacity, power consumption, and refrigerant mass flow rate.

Additional correlations equations for these variables as a quick choice selection for a proper compressor use at ASHRAE standard that cover a range of swept volume range (2.24-11.15) cm³.

The result indicated that these surface fitting models are accurate with in ± 15% for 72 compressors model of cooling cap

Sewer systems are used to convey sewage and/or storm water to sewage treatment plants for disposal by a network of buried sewer pipes, gutters, manholes and pits. Unfortunately, the sewer pipe deteriorates with time leading to the collapsing of the pipe with traffic disruption or clogging of the pipe causing flooding and environmental pollution. Thus, the management and maintenance of the buried pipes are important tasks that require information about the changes of the current and future sewer pipes conditions. In this research, the study was carried on in Baghdad, Iraq and two deteriorations model's multinomial logistic regression and neural network deterioration model NNDM are used to predict sewers future conditions. The results of the

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

Sodium adsorption ratio (SAR) is considered as a measure of the water suitability for irrigation usage. This study examines the effect of the physicochemical parameters on water quality and SAR, which included Calcium(Ca+2), Magnesium(Mg+2), Sodium (Na+), Potassium (K), Chloride (Cl-), Sulfate(SO4-2), Carbonate (CO3-2), Bicarbonate (HCO3-), Nitrate (NO3-), Total Hardness (TH), Total Dissolved Salts (TDS), Electrical Conductivity (EC), degree of reaction (DR), Boron (B) and the monthly and annually flow discharge (Q). The water samples were collected from three stations across the Tigris River in Iraq, which flows through Samarra city (upstream), Baghdad city (central) and the end of Kut city (downstream) for the periods of 2016-201

Diversity has become one of the required phenomena to be available within public organizations, in light of the changes taking place in the global and international environment and in various fields. Therefore, it was imperative to study the impact of this phenomenon in various institutions, especially public ones, in most developing countries, including Iraq. The current research aims to analyze the relationship between The demographic diversity and institutional effectiveness of a sample of workers in public institutions included (500) respondents. The questionnaires were distributed to them randomly. Diversity is considered an independent variable and institutional effectiveness a dependent variable. The researcher used interview tools a

The research aims to diagnose the shortcomings and weaknesses in applying the dimensions of the quality of work life and the extent of their impact on employees’ attitudes and behaviors, and thus their relationship to enhancing their core competencies. The scientific value of the research stems from highlighting the importance of the dimensions of the quality of professional life in improving the productive efficiency of workers in the public sector and raising the level of organizational performance. Because the quality of working life plays an important role in enhancing the core competencies of employees in the public sector, it can also be an incentive or a disincentive for any employee by adapting to the economic and social condition