Design, Analysis, and Optimization of Traffic Engineering for Software Defined Networks

Network traffic has been growing exponentially due to the rapid development of applications and communications technologies. Conventional routing protocols, such as Open-Shortest Path First (OSPF), do not provide optimal routing and result in weak network resources. Optimal traffic engineering (TE) is not applicable in practice due to operational constraints such as limited memory on the forwarding devices and routes oscillation. Recently, a new way of centralized management of networks enabled by Software-Defined Networking (SDN) made it easy to apply most traffic engineering ideas in practice. \par Toward creating an applicable traffic engineering system, we created a TE simulator for experimenting with TE and evaluating TE systems efficiently as this tool employs parallel processing to achieve high efficiency. The purpose of the simulator is two aspects: (1) We use it to understand traffic engineering, (2) we use it to formulate a new traffic engineering algorithm that is near-optimal and applicable in practice. We study the design of some important aspects of any TE system. In particular, the consequences of achieving optimal TE by solving the multi-commodity flow problem (MCF) and the consequences of choosing single-path routing over multi-path routing. With the help of the TE simulator, we compare many TE systems constructed by combining different paths selection techniques with two objective functions for rate adaptations: load balancing (LB) and average delay (AD). The results confirm that paths selected based on the theoretical approach known as Oblivious Routing combined with AD objective function can significantly increase the performance in terms of throughput, congestion, and delay.\par However, the new proposed system comes with a cost. The AD function has a higher complexity than the LB function. We show that this problem can be tackled by training deep learning models. We trained two models with two different neural network architectures: Multilayer Perceptron (MLP) and Long-Short Term Memory (LSTM), to get a responsive traffic engineering system. The input training data is based on synthetic data obtained from the simulator. The output of the two models is the split ratios that the SDN controller uses to instruct the switching devices about how to forward traffic in the network. The result confirms that both models are effective and can be used to forward traffic in an optimal or near-optimal way. The LSTM model has shown a slightly better result than MLP due to its ability to predict a longer output sequence

Water treatment of selected water wells of Al- Muqdadiyah town-Iraq using burned initiated bentonite as a granulated Natural ion- exchanger via columnar method.

The aim of this study was to find a general method, cheap and easy to deal with water wells. Treatment of selected water wells of  Al – Muqdadiyah town was carried out at (25­± 0.1) ºC, using natural granulated Iraqi  Na – montmorillonite clay ( initiated burned bentonite), in known flow packed columns. The Na – montmorillonite clay mineral was characterized by FT – IR spectroscopy. [Total dissolved solids (TDS), Electrical conductivity (EC), Total hardness (T.H.CaCo3), Ca+2, Mg+2, Na+, and pH] quantification was done before and after treatment of water samples using (MI – 180 Multi – Bench meter MARTINI – Instruments). Calcium Ca+2, Magnesium Mg+2, and Sodium Na+ were measured using flame photometer [PFP7 flame photo meter from (JENWAY)], Total Hardness was measured using titration method using UniVer1 hardness reagent. The results indicated that the values of these parameters are within or lower than the international drinking  water supplies average, , and Iraq drinking water standards. Keywords: natural ion exchanger, wells water treatment, burned Na – montmorillonite clay, packed column

SMS Security by Elliptic Curve and Chaotic Encryption Algorithms

Short message services (SMS) represent one of the components of the global communications network and are one of the important developments in communication technologies and communications technology. SMS messages without a password are stored in the SMS server. For the purpose of review and dispute resolution. The security of SMS content cannot be protected because it is transmitted in plain text and is accessible to network operators and employees. Therefore, the end-to-end key is based on encryption and decryption technology can provide SMS security. The security protocols used for SMS security on contemporary mobile devices were examined in this study. SMS security system encryption time affects how well mobile devices work. This shows that security technologies take longer to generate keys and encrypt keys as the key size increases. Due to the limited processing power of mobile devices, large-scale algorithms such as DES, AES, RC4, and Blowfish are not suitable for SMS encryption. SMS may be encrypted using the elliptic curve technique because it provides great security with a smaller key on devices with limited resources, such as mobile phones. And chaotic theory, encryption is simple, fast and secure data encryption. As a result, a combination of elliptic curve algorithm and chaotic encryption algorithm is proposed to achieve a high level of security. In this paper, several tests have been done to compare the algorithms in terms of throughput, power consumption, SMS size, encoding time, and decoding time. The results indicate that the proposed method is better than the comparison method.

Synthesis and characterization of a Nano-adsorbent derivative derived from grape seeds for Cadmium ion removal in an aqueous solution

Grape seeds were utilized as a source for nanoparticle adsorbents. The objective of this work was to prepare a nano adsorbent from grape seeds (GS) and FeCl2. The physical and chemical properties of grape seed ferrous oxide nanoparticles (GS-IONPs) were investigated. Batch adsorption was used to investigate the adsorption of cadmium from industrial water with different initial concentrations, solution pH and contact time. The adsorption isotherm data for Cd(II) on GS-IONPs were fitted to the Langmuir, Freundlich, and Temkin isotherm models. The data fit the Langmuir model well, with a maximum cadmium uptake of 16.3 mg/g. It was found that %removal of cadmium decreased from 98.0% to 88.0% as the initial concentration increased. The results revealed that the prepared adsorbent was effective in Cd(II) removal

Prediction of Pregnancy Outcome Using HCG, CA125 and Progesterone in Cases of Habitual Abortions

Background: Although CA125 is a valuable tumor marker of ovarian carcinoma but it may be have a value to assess the risk of miscarriage at the early stages of pregnancy for woman with history of recurrent pregnancy loss either alone or in combination with other biochemical marker. Objective: To predict pregnancy outcome by studying the level of serum β HCG, progesterone and CA125 at different gestational age in the first trimester for predicting pregnancy loss. Patient and Methods: This study was conducted in Al-Batool Teaching Hospital (in the center of Diyala governorate by studying the patient records as a prospective trail in period from Jan. 2010 to Jan. 2011. The study carried out on 90 pregnant women with a history of recurrent pregnancy loss in there first trimester of pregnancy divided in 3 groups (30 women with no history of abortion as control group, 30 women with history of recurrent pregnancy loss, 30 women who failed to complete their pregnancy in the first trimester during the study. Serial maternal B-HCG, progesterone and CA125 were determined. Results: Serum B-HCG showed a sensitivity of 97%, a specificity of 53%, a PPV (positive predictive value) of 56% and a NPV (negative predictive value) of 97%. Serum progesterone showed a sensitivity of 27%, a specificity of 79%, a PPV of 38% and a NPV of 69%, while serum CA125 showed a sensitivity of 8%, a specificity of 60%, a PPV of 10% and a NPV of 70%. Conclusion: the value of CA125 in recurrent abortions is still unclear and cannot be recommended on routine basis. On the other hand, β-HCG is 97% sensitive with a 53% NPV as a single serum measurement for the prediction of pregnancy outcome

Prevalence and correlates of diastolic dysfunction in patients with hypertension: a cross-sectional study from in The Kingdom of Saudi Arabia

Introduction: diastolic dysfunction refers to impaired ventricular relaxation or filling regardless of ejection fraction and symptoms. It accounts for 8% and 25% in the hospitalized and general population, respectively. The present study was conducted to determine the prevalence and correlates of diastolic dysfunction in hypertensive patients living in Saudi Arabia. Methods: a multicentric, cross-sectional study was conducted from February 2019 to February 2020 at King Khalid Hospital and Prince Sultan Center for Health Services, Prince Sattam Bin Abdulaziz University hospital in Al Kharj, and Al Kharj Military Industries Corporation hospital, KSA. All patients with hypertension who underwent an echocardiography were included in the study. Logistic regression analysis was performed to determine factors associated with left ventricular diastolic dysfunction (LVDD). Results: the study included a total of 104 participants, where 51.9% were females andthe mean age of the patients was 48.01±12.81 years.Most patients had an abnormal echocardiography finding (64.4%, n = 67). The most common abnormalities were left ventricular (LV) hypertrophy (44.2%, n = 46), and diastolic dysfunction, (35.6%, n = 37). The study revealed that age (aOR: 6.1, 95% CI 1.17-31.3; p = 0.032) and dyslipidemia (aOR: 3.45, 95% CI 1.16-10.24; p = 0.026) have significant association with LVDD in the patients with hypertension. Conclusion: in conclusion, diastolic dysfunction is prevalent among older hypertensive patients and those with dyslipidaemia. Age and dyslipidaemia were non-modifiable and modifiable factors associated with LVDD in hypertensive patients, respectively

The Association of Lymphocyte count, CRP, D-Dimer, and LDH with Severe Coronavirus Disease 2019 (COVID-19): A Meta-Analysis

Background: The rapid progression of Coronavirus disease 2019 (COVID-19) and its increasing burden on health systems necessitate the identification of parameters of severe infection to help in monitoring, prognoses and development of treatment algorithms. Objectives: This review aims to investigate the association of lymphocyte count, CRP, LDH, and D-Dimer with the severity of COVID-19. Methods: This review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The databases of MEDLINE/PubMed, WHO-Virtual Health Library (VHL), and ScienceDirect were used for the systematic search. Random effects model was used to estimate the pooled standardized mean differences (SMD) with the corresponding 95% confidence interval (CI), using OpenMeta Analyst software. Results: A total of 11 studies, with 2437 COVID-19 patients, which fulfilled the eligibility criteria were included in the meta-analysis. The analysis revealed that lymphocyte count was significantly lower in patients with the severe form of COVID-19 (SMD = - 1.025, P value <.001). Also, the analysis of SMD showed that patients with severe COVID-19 have a significantly higher serum levels of CRP (SMD = 3.363, P value <.001), D-Dimer (SMD = 1.073, P value <.001), and LDH (SMD = 3.345, P value <.001). Conclusion: Low lymphocyte count and high levels of CRP, LDH, and D-Dimer are associated with severe COVID-19. These laboratory markers could be used as clinical indicators of worsening illness and poor prognosis of COVID-19