A Simulation Study on Amplified WiMAX and WiFi Signal of Tikrit University

The limitation of WiFi coverage and free frequency create problems as well as weaken security and degrade quality of services. Therefore, a complementary wireless technology, WiMAX, is required. WiMAX and WiFi are chosen as both technology are the most highly popular by wireless network protocols usage in Iraq. Simulation on both of the network environments will be used to imitate the real situation in Tikrit University. This study provides a comprehensive field survey on wireless networking in Tikrit University of Iraq. Suitable wireless protocol, expanding coverage, performance of network will be included after the application of this study. The major benefits that have achieved as the outcome of this study are packet delivery ratio and throughput. Both WiFi scenarios achieved packet delivery ratios of 97.2% and 96.012% respectively, while WiMAX scenario scored 98.0% on packet delivery ratio. On the other hand, the throughput was found to produce interesting results and increased with packet size. WiMAX throughput had been discovered to be increasing linearly to the throughput. The maximum throughput achieved by WiMAX was 22.12 Mbps while the WiFi obtained throughputs of 22.46 Kbps and 11.61 Kbps for the different scenarios

Evaluation of Treatment Methods Used for Construction on Expansive Soils in Egypt

The soil formation in this arid area is sometimes an expansive problematic soil. Due to the lake of the construction experience on this problematic soil, many defects are appeared in the new buildings established in these arid areas. In this paper, a focusing on the treatment method using soil replacement for expansive soil formation. In the other hand, some case studies were illustrated to show the different types of problems appeared due to the different construction methods used. Finally, a conclusion about how to overcome these defects happened due to this treatment method for this problematic soil is mentioned. Some recommendations are given to civil engineers to be taken into consideration during establishing any constructions on this problematic soil

Role of Prostaglandin E2 in Cirrhotic Patients with Spontaneous Bacterial Peritonitis

Background: Spontaneous bacterial peritonitis (SBP) is the most frequent bacterial infection in patients who suffer from liver cirrhosis and ascites. Prostaglandin E2 (PGDE2) is considered a simple and accurate tool for diagnosing systemic inflammation and has a relevant impact on prognosis in cirrhotic patients.Objective: We tried to detect the role of PGDE2 in serum and ascitic fluid as a diagnostic marker for eradication of SBP.Patients and methods: This clinical-based prospective cohort study involved patients with liver cirrhosis, ascites and spontaneous bacterial peritonitis referred to the Internal Medicine Department, Faculty of Medicine, Zagazig University during the period from June 2020 to March2021. Patients with ascites were divided equally into: (a) case group included cirrhotic patients with SBP); and (b) control group included cirrhotic patients without SBP. All patients were subjected to complete clinical and laboratory examination. Serum and ascitic PGDE2 were estimated before and after five days of treatment. Results: There was statistically significant difference between the studied groups regarding Child score and presence of HCC. Serum and ascitic PGDE2 was elevated in all cirrhotic groups; both of case and control had more than normal. However, PGDE2 level was lower in case group before treatment in comparison with control group, and after treatment PGDE2 levels was elevated.Conclusion: Serum and ascitic fluid PGDE2 can be used as a diagnostic marker for SBP diagnosis and eradication. Serum PGDE2 is preferred due to its less invasiveness and minimal risk of complications

Performance Improvement of Photovoltaic Panels Using Dual Axis Sun Tracker

الطاقة المتجددة هي أكثر الطاقات المهمة في هذه الأيام. حيث انها نظيفة ومتوفرة بكثرة ويحصل عليها من الطبيعة بدون إعطاء أي تأثيرات سلبيه للبيئة. وهذا هو معاكس لما يعمله الوقود الاحفوري بانبعاث غاز ثنائي أوكسيد الكاربون الذي يسبب ضرر كبير للغلاف الجوي. الطاقة الشمسية هي واحده من الطاقات المتجددة ويمكن ان تصبح مصدر طاقة جيد وبديل لما موجود. الطاقة الشمسية يمكن الحصول عليها باستخدام الواح الطاقة الشمسية عن طريق تحويل الطاقة الشمسية الى طاقة كهربائية. منهجية هذه الورقة البحثية هو بناء متتبع ثنائي المحور ليتحكم باتجاه الالواح الشمسية للحصول على اعلى كفاءة خارجة. نظام التتبع الشمسي هذا يتكون من جزئين رئيسيين وهما جزء برمجي وأدوات ومعدات. المعدات متمثلة بمتحكم دقيق ومقاومات ضوئية لتحسس الضوء القادم من الشمس ومحرك تيار مستمر يعمل باتجاهين لتعديل اتجاه الخلية الشمسية. الجزء البرمجي متمثل بالبرنامج والشفرة البرمجية المستخدمة. نتائج البحث بينت ان المتتبع الثنائي المحور يتفوق على الخلايا الشمسية الثابتة وتم الحصول على طاقة اعلى التي سجلت باستخدام مسجل البيانات.Renewable energy is the most important type of energy sources nowadays. It’s clean, abundantly available and can be obtained from nature without giving any negative impact to the environment. This is the opposite of what fossil fuel does by giving the carbon dioxide (CO2) emission and makes a huge damage to the atmosphere. Solar energy is one type of renewable energy and is considered a good effective alternative source of energy. The solar energy can be collected using solar panels from emitted radiation from the sun.  The aim of this paper is building a dual-axis solar tracker to control the direction of the panels and get the highest output efficiency compared to the fixed panels. The sun tracker system consists of two main parts, hardware, and software. Hardware represented by using a microcontroller, Light Dependent Resistors (LDRs) to detect the light of the sun, servomotors use to adjust the direction of the solar panel (PV). The software represented by the application used and the codes. The results show that the dual axis tracking is more powerful than the fixed position solar cells and achieves better output power. The power measured were obtained by the data logger method

Tamoxifen for treatment of abnormal uterine bleeding in etonorgstrel implant users: a randomized clinical trial

Background: The current study aims to compare the use of tamoxifen and oral contraceptive pills in women using implanon and complain with irregular uterine bleeding.Methods: Women attended family planning clinic using implanon presented by bleeding were invited to participate in the study. They were randomized into two groups: Group A: 100 women received Tamoxifen 10 mg twice daily for 10 days taken at the onset of an episode of bleeding or spotting episode. Group B: 100 women received Combined oral contraceptive pills (microcept) once daily for 21 days take at the onset of an episode of bleeding or spotting episode.Results: No difference regarding the baseline criteria of both groups. No difference between both groups regarding the duration of irregular bleeding in the implanon users (p=0.090). Additionally, the number of bleeding days and spotting in the last month was similar in both groups (p=0.554). The percentage of women who stopped bleeding during the period of treatment is 84% in the tamoxifen group and 92% in the COCs group, but the COCs needs longer treatment time, where the mean of days required to stop bleeding is 5.03±1.8 days in the tamoxifen group and 6.5±2.5 in the COCs group. Headache and nausea were the most prominent adverse effects found in the COCs group (p=0.000).Conclusions: Oral administration of tamoxifen 10 mg twice daily for 10 days is effective on stopping bleeding attacks in implanon users

Evaluation of construction companies performance by using stepwise weight assessment ratio analysis

The extent to which the facility and the construction process meet and/or surpass a client's expectations is critical for client satisfaction. As a result, company evaluation is a well-established procedure in project management in the construction industry to ensure projects are performed in compliance with the contract documents and applicable laws and regulations. The purpose of this study is to present and debate certain criteria for evaluating the Iraqi construction sector companies’ performance based on Stepwise Weight Assessment Ratio Analysis (SWARA) to assess company responsibility and performance in support of future projects. The evaluation criteria of construction companies are studied in this paper. The criteria have been categorized into main groups: (a) organization and management; (b) time; (c) quality; (d) cost; (e) resource; (f) safety practices. The main criteria have been divided into forty-four sub criteria. The findings of this paper demonstrate that the most important criteria in evaluating the construction companies’ performance is cost, followed by time, quality, organization and management, resources, and lastly safety practices which ranked based on the weight of criteria (35.7%, 24.2%, 16.3%, 11.2%, 7.4%, 5.2% respectively) with the SWARA technique

Investigation of a COVID-19 outbreak in a University Cardio-Thoracic Hospital in Cairo: exploration of the risk to healthcare workers and patients

Background: Corona virus Disease 2019 (COVID-19) pandemic has posed a challenge to health sectors all over the world. The pandemic arrived in Egypt a few weeks after Europe and Asia, with rapidly rising numbers.  Health care workers (HCWs) are front liners sustaining a major risk of acquiring the infection. Aim: In this work, we analyse an outbreak of COVID-19 in a University hospital in Cairo involving HCWs of different categories, patients and patients’ accompanying relatives. Methods: Following the reporting of the first COVID-19 confirmed case; a 55-year-old nurse at the hospital, a total of 645 healthcare workers, patients and patients' accompanying relatives were tested for SARS-CoV-2 by real-time reverse transcription polymerase chain reaction (rRT-PCR) assay. Results: Twenty four out of 589 HCWs, 3 out of 42 patient and 4 out of 14 patients' accompanying relatives tested positive for COVID-19. No physicians, pharmacists or technicians were infected. Nursing staff and housekeeping staff were the most at risk of contracting the infection with a risk ratio of 4.99 (95%CI: 1.4-17.6) and 5.08 (95%CI: 1.4-18.4) respectively. Clustering of infected HCWs was observed in paediatrics’ ICU and in the 6th floor of the hospital. Conclusions: Nursing and housekeeping staff sustain a significantly higher risk of COVID-19 infection compared to other staff categories. The nature of their duties and the frequent unprotected contact between members of these categories may play a role in increasing their risk. &nbsp

Machine Learning Prediction Approach to Enhance Congestion Control in 5G IoT Environment

[EN] The 5G network is a next-generation wireless form of communication and the latest mobile technology. In practice, 5G utilizes the Internet of Things (IoT) to work in high-tra_ c networks with multiple nodes/ sensors in an attempt to transmit their packets to a destination simultaneously, which is a characteristic of IoT applications. Due to this, 5G o_ ers vast bandwidth, low delay, and extremely high data transfer speed. Thus, 5G presents opportunities and motivations for utilizing next-generation protocols, especially the stream control transmission protocol (SCTP). However, the congestion control mechanisms of the conventional SCTP negatively influence overall performance. Moreover, existing mechanisms contribute to reduce 5G and IoT performance. Thus, a new machine learning model based on a decision tree (DT) algorithm is proposed in this study to predict optimal enhancement of congestion control in the wireless sensors of 5G IoT networks. The model was implemented on a training dataset to determine the optimal parametric setting in a 5G environment. The dataset was used to train the machine learning model and enable the prediction of optimal alternatives that can enhance the performance of the congestion control approach. The DT approach can be used for other functions, especially prediction and classification. DT algorithms provide graphs that can be used by any user to understand the prediction approach. The DT C4.5 provided promising results, with more than 92% precision and recall.Najm, IA.; Hamoud, AK.; Lloret, J.; Bosch Roig, I. (2019). Machine Learning Prediction Approach to Enhance Congestion Control in 5G IoT Environment. Electronics. 8(6):1-23. https://doi.org/10.3390/electronics8060607S12386Rahem, A. A. T., Ismail, M., Najm, I. A., & Balfaqih, M. (2017). Topology sense and graph-based TSG: efficient wireless ad hoc routing protocol for WANET. Telecommunication Systems, 65(4), 739-754. doi:10.1007/s11235-016-0242-7Aalsalem, M. Y., Khan, W. Z., Gharibi, W., Khan, M. K., & Arshad, Q. (2018). Wireless Sensor Networks in oil and gas industry: Recent advances, taxonomy, requirements, and open challenges. Journal of Network and Computer Applications, 113, 87-97. doi:10.1016/j.jnca.2018.04.004Sunny, A., Panchal, S., Vidhani, N., Krishnasamy, S., Anand, S. V. R., Hegde, M., … Kumar, A. (2017). A generic controller for managing TCP transfers in IEEE 802.11 infrastructure WLANs. Journal of Network and Computer Applications, 93, 13-26. doi:10.1016/j.jnca.2017.05.006Jain, R. (1990). Congestion control in computer networks: issues and trends. IEEE Network, 4(3), 24-30. doi:10.1109/65.56532Kafi, M. A., Djenouri, D., Ben-Othman, J., & Badache, N. (2014). Congestion Control Protocols in Wireless Sensor Networks: A Survey. IEEE Communications Surveys & Tutorials, 16(3), 1369-1390. doi:10.1109/surv.2014.021714.00123Floyd, S. (2000). Congestion Control Principles. doi:10.17487/rfc2914Qazi, I. A., & Znati, T. (2011). On the design of load factor based congestion control protocols for next-generation networks. Computer Networks, 55(1), 45-60. doi:10.1016/j.comnet.2010.07.010Katabi, D., Handley, M., & Rohrs, C. (2002). Congestion control for high bandwidth-delay product networks. ACM SIGCOMM Computer Communication Review, 32(4), 89-102. doi:10.1145/964725.633035Wang, Y., Rozhnova, N., Narayanan, A., Oran, D., & Rhee, I. (2013). An improved hop-by-hop interest shaper for congestion control in named data networking. ACM SIGCOMM Computer Communication Review, 43(4), 55-60. doi:10.1145/2534169.2491233Mirza, M., Sommers, J., Barford, P., & Zhu, X. (2010). A Machine Learning Approach to TCP Throughput Prediction. IEEE/ACM Transactions on Networking, 18(4), 1026-1039. doi:10.1109/tnet.2009.2037812Taherkhani, N., & Pierre, S. (2016). Centralized and Localized Data Congestion Control Strategy for Vehicular Ad Hoc Networks Using a Machine Learning Clustering Algorithm. IEEE Transactions on Intelligent Transportation Systems, 17(11), 3275-3285. doi:10.1109/tits.2016.2546555Fadlullah, Z. M., Tang, F., Mao, B., Kato, N., Akashi, O., Inoue, T., & Mizutani, K. (2017). State-of-the-Art Deep Learning: Evolving Machine Intelligence Toward Tomorrow’s Intelligent Network Traffic Control Systems. IEEE Communications Surveys & Tutorials, 19(4), 2432-2455. doi:10.1109/comst.2017.2707140Gonzalez-Landero, F., Garcia-Magarino, I., Lacuesta, R., & Lloret, J. (2018). PriorityNet App: A Mobile Application for Establishing Priorities in the Context of 5G Ultra-Dense Networks. IEEE Access, 6, 14141-14150. doi:10.1109/access.2018.2811900Lloret, J., Parra, L., Taha, M., & Tomás, J. (2017). An architecture and protocol for smart continuous eHealth monitoring using 5G. Computer Networks, 129, 340-351. doi:10.1016/j.comnet.2017.05.018Khan, I., Zafar, M., Jan, M., Lloret, J., Basheri, M., & Singh, D. (2018). Spectral and Energy Efficient Low-Overhead Uplink and Downlink Channel Estimation for 5G Massive MIMO Systems. Entropy, 20(2), 92. doi:10.3390/e20020092Elappila, M., Chinara, S., & Parhi, D. R. (2018). Survivable Path Routing in WSN for IoT applications. Pervasive and Mobile Computing, 43, 49-63. doi:10.1016/j.pmcj.2017.11.004Singh, K., Singh, K., Son, L. H., & Aziz, A. (2018). Congestion control in wireless sensor networks by hybrid multi-objective optimization algorithm. Computer Networks, 138, 90-107. doi:10.1016/j.comnet.2018.03.023Shelke, M., Malhotra, A., & Mahalle, P. N. (2017). Congestion-Aware Opportunistic Routing Protocol in Wireless Sensor Networks. Smart Innovation, Systems and Technologies, 63-72. doi:10.1007/978-981-10-5544-7_7Godoy, P. D., Cayssials, R. L., & García Garino, C. G. (2018). Communication channel occupation and congestion in wireless sensor networks. Computers & Electrical Engineering, 72, 846-858. doi:10.1016/j.compeleceng.2017.12.049Najm, I. A., Ismail, M., Lloret, J., Ghafoor, K. Z., Zaidan, B. B., & Rahem, A. A. T. (2015). Improvement of SCTP congestion control in the LTE-A network. Journal of Network and Computer Applications, 58, 119-129. doi:10.1016/j.jnca.2015.09.003Najm, I. A., Ismail, M., & Abed, G. A. (2014). High-Performance Mobile Technology LTE-A using the Stream Control Transmission Protocol: A Systematic Review and Hands-on Analysis. Journal of Applied Sciences, 14(19), 2194-2218. doi:10.3923/jas.2014.2194.2218Katuwal, R., Suganthan, P. N., & Zhang, L. (2018). An ensemble of decision trees with random vector functional link networks for multi-class classification. Applied Soft Computing, 70, 1146-1153. doi:10.1016/j.asoc.2017.09.020Gómez, S. E., Martínez, B. C., Sánchez-Esguevillas, A. J., & Hernández Callejo, L. (2017). Ensemble network traffic classification: Algorithm comparison and novel ensemble scheme proposal. Computer Networks, 127, 68-80. doi:10.1016/j.comnet.2017.07.018Hasan, M., Hossain, E., & Niyato, D. (2013). Random access for machine-to-machine communication in LTE-advanced networks: issues and approaches. IEEE Communications Magazine, 51(6), 86-93. doi:10.1109/mcom.2013.6525600Liang, D., Zhang, Z., & Peng, M. (2015). Access Point Reselection and Adaptive Cluster Splitting-Based Indoor Localization in Wireless Local Area Networks. IEEE Internet of Things Journal, 2(6), 573-585. doi:10.1109/jiot.2015.2453419Park, H., Haghani, A., Samuel, S., & Knodler, M. A. (2018). Real-time prediction and avoidance of secondary crashes under unexpected traffic congestion. Accident Analysis & Prevention, 112, 39-49. doi:10.1016/j.aap.2017.11.025Shu, J., Liu, S., Liu, L., Zhan, L., & Hu, G. (2017). Research on Link Quality Estimation Mechanism for Wireless Sensor Networks Based on Support Vector Machine. Chinese Journal of Electronics, 26(2), 377-384. doi:10.1049/cje.2017.01.013Riekstin, A. C., Januário, G. C., Rodrigues, B. B., Nascimento, V. T., Carvalho, T. C. M. B., & Meirosu, C. (2016). Orchestration of energy efficiency capabilities in networks. Journal of Network and Computer Applications, 59, 74-87. doi:10.1016/j.jnca.2015.06.015Adi, E., Baig, Z., & Hingston, P. (2017). Stealthy Denial of Service (DoS) attack modelling and detection for HTTP/2 services. Journal of Network and Computer Applications, 91, 1-13. doi:10.1016/j.jnca.2017.04.015Stimpfling, T., Bélanger, N., Cherkaoui, O., Béliveau, A., Béliveau, L., & Savaria, Y. (2017). Extensions to decision-tree based packet classification algorithms to address new classification paradigms. Computer Networks, 122, 83-95. doi:10.1016/j.comnet.2017.04.021Singh, D., Nigam, S. P., Agrawal, V. P., & Kumar, M. (2016). Vehicular traffic noise prediction using soft computing approach. Journal of Environmental Management, 183, 59-66. doi:10.1016/j.jenvman.2016.08.053Xia, Y., Chen, W., Liu, X., Zhang, L., Li, X., & Xiang, Y. (2017). Adaptive Multimedia Data Forwarding for Privacy Preservation in Vehicular Ad-Hoc Networks. IEEE Transactions on Intelligent Transportation Systems, 18(10), 2629-2641. doi:10.1109/tits.2017.2653103Tariq, F., & Baig, S. (2017). Machine Learning Based Botnet Detection in Software Defined Networks. International Journal of Security and Its Applications, 11(11), 1-12. doi:10.14257/ijsia.2017.11.11.01Wu, T., Petrangeli, S., Huysegems, R., Bostoen, T., & De Turck, F. (2017). Network-based video freeze detection and prediction in HTTP adaptive streaming. Computer Communications, 99, 37-47. doi:10.1016/j.comcom.2016.08.005Pham, T. N. D., & Yeo, C. K. (2018). Adaptive trust and privacy management framework for vehicular networks. Vehicular Communications, 13, 1-12. doi:10.1016/j.vehcom.2018.04.006Mohamed, M. F., Shabayek, A. E.-R., El-Gayyar, M., & Nassar, H. (2019). An adaptive framework for real-time data reduction in AMI. Journal of King Saud University - Computer and Information Sciences, 31(3), 392-402. doi:10.1016/j.jksuci.2018.02.012Louvieris, P., Clewley, N., & Liu, X. (2013). Effects-based feature identification for network intrusion detection. Neurocomputing, 121, 265-273. doi:10.1016/j.neucom.2013.04.038Verma, P. K., Verma, R., Prakash, A., Agrawal, A., Naik, K., Tripathi, R., … Abogharaf, A. (2016). Machine-to-Machine (M2M) communications: A survey. Journal of Network and Computer Applications, 66, 83-105. doi:10.1016/j.jnca.2016.02.016Hamoud, A. K., Hashim, A. S., & Awadh, W. A. (2018). Predicting Student Performance in Higher Education Institutions Using Decision Tree Analysis. International Journal of Interactive Multimedia and Artificial Intelligence, 5(2), 26. doi:10.9781/ijimai.2018.02.004Lavanya, D. (2012). Ensemble Decision Tree Classifier For Breast Cancer Data. International Journal of Information Technology Convergence and Services, 2(1), 17-24. doi:10.5121/ijitcs.2012.2103Polat, K., & Güneş, S. (2007). Classification of epileptiform EEG using a hybrid system based on decision tree classifier and fast Fourier transform. Applied Mathematics and Computation, 187(2), 1017-1026. doi:10.1016/j.amc.2006.09.022Cayirci, E., Tezcan, H., Dogan, Y., & Coskun, V. (2006). Wireless sensor networks for underwater survelliance systems. Ad Hoc Networks, 4(4), 431-446. doi:10.1016/j.adhoc.2004.10.008Mezzavilla, M., Zhang, M., Polese, M., Ford, R., Dutta, S., Rangan, S., & Zorzi, M. (2018). End-to-End Simulation of 5G mmWave Networks. IEEE Communications Surveys & Tutorials, 20(3), 2237-2263. doi:10.1109/comst.2018.282888

معاييـر التفضيل الجمالى للنتاج المعمارى المعاصرTHE AESTHETIC PREFERENCES CRITERIA FOR CONTEMPORARY ARCHITECTURAL PRODUCTS

This Research paper seeks to present a different theoretical thesis to distinguish the different criteria and the constitutional foundations of the aesthetical message of the architect to the recipient which addresses his mind and sentiment. This research also considers the practice of the various aspects of the architectural design process, architectural evaluation, criticism and the architectural projects arbitration in order to know the assisting factors that urges the recipient to accept or reject architectural products. In addition, it recognizes the various indicators, within the recipient’s scope, for his preference of the architectural work and communicate with the recipient to obtain the reasons behind either the acceptance or rejection