The evolution of the Internet of things (IoT) led to connect billions of heterogeneous physical devices together to improve the quality of human life by collecting data from their environment. However, there is a need to store huge data in big storage and high computational capabilities.   Cloud computing can be used to store big data.  The data of IoT devices is transferred using two types of protocols: Message Queuing Telemetry Transport (MQTT) and Hypertext Transfer Protocol (HTTP). This paper aims to make a high performance and more reliable system through efficient use of resources. Thus, load balancing in cloud computing is used to dynamically distribute the workload across nodes to avoid overloading any individual r

Progression in Computer networks and emerging of new technologies in this field helps to find out new protocols and frameworks that provides new computer network-based services. E-government services, a modernized version of conventional government, are created through the steady evolution of technology in addition to the growing need of societies for numerous services. Government services are deeply related to citizens’ daily lives; therefore, it is important to evolve with technological developments—it is necessary to move from the traditional methods of managing government work to cutting-edge technical approaches that improve the effectiveness of government systems for providing services to citizens. Blockchain technology is amon

Segmented regression consists of several sections separated by different points of membership, showing the heterogeneity arising from the process of separating the segments within the research sample. This research is concerned with estimating the location of the change point between segments and estimating model parameters, and proposing a robust estimation method and compare it with some other methods that used in the segmented regression. One of the traditional methods (Muggeo method) has been used to find the maximum likelihood estimator in an iterative approach for the model and the change point as well. Moreover, a robust estimation method (IRW method) has used which depends on the use of the robust M-estimator technique in

      An experimental and computational study is conducted to analyze the thermal performance of heat sinks and to pick up more profound information in this imperative field in the electronic cooling. One important approach to improve the heat transfer on the air-side of the heat exchanger is to adjust the fin geometry. Experiments are conducted to explore the impact of the changing of diverse operational and geometrical parameters on the heat sink thermal
performance. The working fluid used is air. Operational parameters includes: air Reynolds number (from 23597 to 3848.9) and heat flux (from 3954 to 38357 W/m
2 ). Conformational parameters includes: change the direction of air flow and the area of conduct

Climate change is one of the global issues that is receiving wide attention due to its clear impact on all living organisms. This is essential for Iraq since it was classified as the fifth most vulnerable country to climate change. One of the manifestations of these changes in Iraq is the increasing frequency and severity of dust storms. In this study, the Normalized Difference Dust Index (NDDI) spectral index for Moderate Resolution Imaging Spectroradiometer (MODIS) sensor bands was used to measure and track the dust storm that occurred on May 16, 2022, as well as to test the validity of one of the daily products of this sensor, MOD11A1, to measure surface temperature and emissivity before and after the storm. It was found that the MOD0

Roof in the Iraqi houses normally flattening by a concrete panel. This concrete panel has poor thermal properties. The usage of materials with low thermal conductivity and high specific heat gives a good improvements to the thermal properties of the concrete panel, thus, the indoor room temperature improves. A Mathcad program based on a mathematical model employing complex Fourier series built for a single room building. The model input data are the ambient temperature, solar radiation, and sol-air temperature, which have been treated as a periodic function of time. While, the room construction is constant due to their materials made of it, except the roof properties are taken as a variable generated practically from the

This study presents an adaptive control scheme based on synergetic control theory for suppressing the vibration of building structures due to earthquake. The control key for the proposed controller is based on a magneto-rheological (MR) damper, which supports the building. According to Lyapunov-based stability analysis, an adaptive synergetic control (ASC) strategy was established under variation of the stiffness and viscosity coefficients in the vibrated building. The control and adaptive laws of the ASC were developed to ensure the stability of the controlled structure. The proposed controller addresses the suppression problem of a single-degree-of-freedom (SDOF) building model, and an earthquake control scenario was conducted and simulat

The unconventional techniques called “the quick look techniques”, have been developed to present well log data calculations, so that they may be scanned easily to identify the zones that warrant a more detailed analysis, these techniques have been generated by service companies at the well site which are among the useful, they provide the elements of information needed for making decisions quickly when time is of essence^. The techniques used in this paper are:

• Apparent resistivity R_wa
• R_xo /R_t

   The above two methods had been used to evaluate Nasiriyah oil field formations (well-NS-3) to discover the hydrocarbon bearing formations. A compu

Classification of imbalanced data is an important issue. Many algorithms have been developed for classification, such as Back Propagation (BP) neural networks, decision tree, Bayesian networks etc., and have been used repeatedly in many fields. These algorithms speak of the problem of imbalanced data, where there are situations that belong to more classes than others. Imbalanced data result in poor performance and bias to a class without other classes. In this paper, we proposed three techniques based on the Over-Sampling (O.S.) technique for processing imbalanced dataset and redistributing it and converting it into balanced dataset. These techniques are (Improved Synthetic Minority Over-Sampling Technique (Improved SMOTE),  Border