Solution of Multi-order Fractional Differential Equation Based on Conformable Derivative by Shifted Legendre Polynomial

The aim of this article is the way for finding approximation solution of multi-order fractional differential equation with conformable sense with use approximated function by shifted Legendre polynomial, the method is easy and powerful for get our results of the linear and non-linear equation, the background idea behind this method is finding system of algebra after achieving messing variable is that mean obtain approximate solution, a few examples illustrates for presented how much our method is capable.

A Comparison between Brown’s and Holt’s Double Exponential Smoothing for Forecasting Applied Generation Electrical Energies in Kurdistan Region

The process of producing electricity from sources of energy is known as electricity production. Electric also isn't freely accessible in environment, thus it should be "manufactured" (i.e., converting another kinds of energy to electrical energy) by utilities with in electricity industry (transportation, distributing, and so on).Moreover, the objective of this study is to compared of Brown’s as well as Holt’s Double Exponential Smoothing also build a best forecasting time series model among two smoothing model forecasting, as well as focuses on optimizing characteristics to use the golden section technique. This exponential smoothing approach has been one of the time series forecasting methods that would be used to forecast (Generation Electrical) with in Kurdistan area. The issue that arises with this technique is determining the appropriate parameters to reduce predict inaccuracy. In addition, Data used in this paper are (Generation Electrical) in Kurdistan region for (132) months from 2010 to 2020. The study revealed that such data is trending modeled, indicating that a double exponential smoothing (DES) approach from Brown & Holt can be used with the (Stratigraphic & Minitab) software. There are the same results but the Result of analysis more depend on the R-program. The difference among the forecast findings acquired with optimum parameters as well as the assaying data was utilized to assess the feasibility of the forecast by completing normality and randomness tests. Ultimately, the outcomes of parameterization show that the optimal value of α that in DES Brown is (0.22) as well as the optimal MAPE is 9.23616 percent, whereas in DES Holt the optimal is (0.95) as well as the optimal β is (0.05) via the optimal MAPE of 8.08586 percent. This MAPE of a DES Brown technique is greater than the MAPE of a DES Holt approach. Feasibility experiments revealed that both approaches are capable of predicting. Depending on the value of MAPE as well as evaluation process, DES Holt's was recognized as the main prediction model.

Enhancing Wireless Sensor Networks Routing Protocols based on Cross Layer Interaction

Wireless sensor networks aim to develop a smart city based on sensing environment. The routing protocols of wireless sensor networks is important to transfer the data in smart cities since sensor nodes have limited power and transmission range. The aim of this research is to enhance wireless sensor networks routing protocols based on proposed cross-layer interaction between physical layer and network layer also a proposed routing table information of wireless sensor nodes is developed to consider the transmission power of neighbor’s nodes to determine the next hop. Cross-layer interaction provides a useful information and effective adaptation for WSN routing protocols. As a result, the proposed routing protocol shows an improvement in network performance when number of intermediate nodes are minimized.

Automatic Classification of Covid-19 Chest X-Ray Images Using Local Binary Pattern and Binary Particle Swarm Optimization for Feature Selection

Novel Coronavirus disease 2019 (COVID-19) is a type of pandemic viruses that cause respiratory tract infection in humans. The clinical imaging of Chest X-Ray (CXR) by Computer Aided Diagnosis (CAD) plays an important role to identify the patients who infected by COVID-19. The objective of this paper presents a Computer Aided Diagnosis (CAD) method for automatically classify 110 frontal CXR images of contagious people according to Normal and COVID-19 infection. The proposed method contains of four phases: image enhancement, feature extraction, feature selection and classification. Gaussian filter is performed to de-noise the images and Adaptive Histogram Equalization (AHE) for image enhancement in pre-processing step for better decision-making process. Local Binary Pattern (LBP) features set are extracted from the dataset. Binary Particle Swarm Optimization (BPSO) is considered to select the clinically relevant features and developing the robust model. The successive features are fed to Support Vector Machine (SVM) and K-Nearest Neighbor (KNN) classifiers. The experimental results show that the system robustness in classification COVID-19 from Normal images with average accuracy 94.6%, sensitivity 96.2% and specificity 93%.

A Comparison Between New Modification of ANWK and Classical ANWK Methods in Nonparametric Regression

Nonparametric kernel estimators are mostly used in a variety of statistical research fields. Nadaraya-Watson kernel estimator (NWK) is one of the most important nonparametric kernel estimator that is often used in regression models with a fixed bandwidth. In this article, we consider the four new Proposed Adaptive Nadaraya-Watson Kernel Regression Estimators (Interquartile Range, Standard Deviation, Mean Absolute Devotion, and Median Absolute Deviation) rather than (Fixed Bandwidth, Adaptive Geometric, Adaptive Mean, Adaptive Range, and Adaptive Median). The outcomes in both simulation and actual data in Leukemia Cancer show that the four new ANW Kernel Estimators (Interquartile Range, Standard Deviation, Mean Absolute devotion, and Median Absolute Deviation) is more effective than the kernel estimations with fixed bandwidth in previous studies using Mean Square Error (MSE) Criterion.

Simulation of Moving Target Indication Radar System Based on VisSim/Comm Application

Moving target indication (MTI) is mainly designed to detect moving targets and while unmoving targets are filtered out. It focuses on the technique of the modern stationary target indication (STI), by using directly the signal details to determine the reflecting object’s mechanical properties, after that it becomes easier to find moving or non-moving targets. This paper presents the simulation design of the MTI radar system. The main purpose of this design is to help students in understanding the radar system subject and help teachers to explain this subject in a simpler approach. Both students and teachers need to know how the signals inside the MTI radar processor are working and how they are generated and related to each other. This paper introduces a method of simulation of MTI radar signals including, A-scope radar display, transmitted and returned radar pulses with constant and multiple PRF, n-delay line cancellers.

The Estimation of (Covid-19) Cases in Kurdistan Region Using Nelson Aalen Estimator

It is described how the Nelson–Aalen estimator may be used to control the rate of a nonparametric estimate of the cumulative hazard rate function based on right censored as well as left condensed survival data, furthermore how the Nelson–Aalen estimator can be utilized to estimate various amounts. This technique is mostly applied to survival data and product quality data similar to the incorporated relative mortality in a multiplicative model with outer rates and the cumulative infection rate in a straightforward epidemic model. It is shown that tallying measures produce a structure that permits to a brought together treatment of all these different conditions, and the main little and massive sample properties of the assessor are summarized. This estimator is a weighted average of the Nelson-Aalen reliability estimates over two time periods. The suggested estimator's suitability and utility in model selection are reviewed. And a real-world dataset is evaluated to demonstrate the proposed estimator's suitability and utility. This work proposes a simple and nearly unbiased estimator to fill this gap. The information was gathered from the Ministry of Health's website between October 1, 2020, and February 28, 2021. The results of the Nelson Allen Estimator demonstrated that the odds of surviving were higher during a short period of time after being exposed to the virus. As time passes, the possibilities become slimmer. The closer the estimate comes to value 1 from 0.5 upward, the greater the chances of surviving the infection.

HIV, HBS and HCV in Dump Site Workers of Erbil Governorate

This research targeted eighty-nine males working in Kany Qrzhala, dumpsite. Age and gender comparable apparently healthy subjects were selected as healthy controls, and both of the groups were obliged to fill the study's questionnaire. Further, venous blood samples were collected from each individual for serum collection. The accumulated sera reserved for the sero-prevalence for antibodies tests of Human Immunodeficiency Virus, Hepatitis B Surface Antigen and Hepatitis C Virus, (HIV), (HBS), (HCV) respectively. The automated immunoassay analyzer Cobas E411 facilitated the conducting of the mentioned tests. The serum concentration of HIV and HBS antibodies of dumpsite workers revealed a significant increase when compared to the healthy group, while the HCV antibody serum concentration presented no significant alteration when comparing dumpsite workers to the healthy controls. The antibodies presence in the sera that belonged to workers is an indicator of exposure to the viruses due to unsanitary health conditions. This may pose a public health risk to the workers themselves, in addition to the people they are in contact with, including their families.

Analysis the Structures of Some Symmetric Cipher Algorithms Suitable for the Security of IoT Devices

In the past years, the Internet of Things (IoT) used in different applications and very wide range of fields (e.g. cloud services, smart environments, logistics, social and personal domains, and healthcare services). The IoT included a variety of components and devices such as RFID devices, wireless sensors, actuators, and wireless networks. Also, the IoT with smart devices adopted in various companies, organizations and public services systems. For instance, some devices like Notebooks and smartphones have been used to perform different management activities and duties. These smart devices relied on data exchange and data storage resources in clouds computing services. In this context, the saved data and exchanged data required protection against hacking operations, transferred with more secure communications channels, and safe storage environment in the clouds and local storage systems. In this paper, we proposed some encryption algorithms to tackle the issue of data confidentiality in the IoT applications. This research provided analysis and investigation of these encryption algorithms in light of components of the designs, versions of these algorithms, encryption keys, block size, round functions and the techniques used in the designs.

Occupational Exposures and Associated Health Effects among Dumpsite Workers

Eighty-nine male workers from the landfill site in (Kany Qrzhala), Erbil, Iraq, aged from 12-65 years were investigated in this study. Each one had filled out a questionnaire sheet. Plus, a 7 ml of venous blood samples were collected from them. Total IgE and Syphilis antibodies were detected. Thus, CBC was conducted on each sample. The results recorded 92.13% of the workers lived in rural areas, while 7.87% lived in urban areas. Further, there were 58.43% smokers and 41.57% non-smokers. Furthermore, the research sample contained 38.20% single, and 61.80% married people. As education illustrated, 37.08% had no schooling, primary school education 40.45%, less than 20% had secondary school education, 2.25% acquired a diploma, and a B.Sc. degree. The serum concentration of total IgE of dumpsite workers revealed a significant increase when compared to the healthy group. None of the workers' sera revealed Syphilis antibodies except one case which was positive; however, it shows non-significant difference between both groups. WBC count was soared significantly in dumpsite workers when compared to the healthy individuals, yet, lymphocyte and granulocyte numbers showed non-significant increment, while monocyte number showed an insignificant rise in workers as compared to healthy group. The number of RBC's and Hb level of the Landfill workers exhibited a substantial increase. Even though, both groups' platelets did not show significant variance. The rise in WBC counts and IgE levels may be due to the exposure of these workers to allergens at the dumpsites as for allergies are the common consequence when exposed to waste and garbage.