Periodicals of Engineering and Natural Sciences (PEN - International University of Sarajevo)
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Corbels strengthened with CFRP under deferent loading
Get PDFShort cantilevers under loads are known as corbels, and they generally have a detrimental impact on the strength of concrete structural components by reducing their resistance to external loads. Strengthening with CFRP strips as an externally bounded approach is employed to raise that. The behavior and durability of strengthened corbels under (constant and incremental) loads are examined in this research. Twelve double corbels were cast and tested as part of the experimental program, with the dimensions of the corbels on all specimens remaining constant. While the other nine are left un-fortified as control corbels, nine of them are strengthened using CFRP strips in various patterns. The results indicate that the maximum load capacity of corbels is affected by both constant and incremental loads. In addition, the ultimate load and ultimate deflection of the legs subjected to five load cycles were less than those subjected to constant stress. The bull legs rein-forced with externally bonded CFRP strips demonstrated a significant increase in ultimate load under any ap-plied load but a reduction in ultimate deflection relative to the unreinforced bull legs under the same applied load. All failures of the bull limb were ascribed to the unbounded CFRP strips
Arabic fake news detection for Covid-19 using deep learning and machine learning
Get PDFWhen newspapers were the dominant form of conventional media, fake news was widespread. Due to the vast influence of such false news and the growing user reach of technical media sources (TV, Internet, social media, blogs). Humans have become more dependent on the news as they make daily decisions for ensuring the safety of their loved ones and themselves in the wake of COVID-19 becoming a pandemic which has impacted humans all over the world. Fake news, on the other hand, is on the verge of becoming a "second pandemic" or "infodemic," endangering the health of individuals all over the world. Previous research hasn\u27t used fake news detection to coronavirus in Arabic due to the fact that fake news connected to coronavirus is such a recent occurrence. A total of 4 versions of the datasets used in this study have been produced (D0, D1, D2, and D3). To understand the effects of deep learning (DL) and machine learning (ML) techniques on any dataset, a total of 4 datasets were created. Also, the research analyzes them with regard to ML and DL to determine the efficacy of preprocessing (D1), raw dataset (D0), light stemming (D3), and root stemming (D2). Dataset version zero (D0) is finished when creating an excel file. From the first version (D0), three more versions (D2, D1, and D3) were created. This study examines the detection of fake news articles con-cerning COVID-19 on Facebook with the use of DL approaches, like the Bidirectional Long Short-Term Memory Networks (Bi-LSTM), Bidirectional Encoder Representations from Transformers (BERT) and Ara-Bert of Arabic text and ML techniques Linear Support Vector Machines (SVM) and Random Forest (RF). On testing data-set (D0), BERT yields the greatest accuracy of 97.32%
 
Design and comparison of rectangular and cylindrical DRA antennas for enhanced efficiency and gain
Get PDFMany applications in lifestyle need to use some kinds of antenna especially in communication field. One of these antennas that is used in this field of communication is called dielectric resonator antenna (DRA). In this review, we will compare different kinds of DRA antennas, for example, cylindrical and rectangular DRA antennas, based on their S-parameters, gain, directivity, bandwidth, and voltage standing wave ratio (VSWR). After discovering the studies about characteristics of these antennas according, the technology of gain, bandwidth enhancements used in the literature will be explained in detail, such as using a high-dielectric-constant material, adjusting its resonant frequency, property of lensing of MTM cells. In practical experiments, the software CST (Computer Simulation Technology) is used for this purpose, to evaluate the above-mentioned parameters of DRA antennas. The advantages of DRA antennas are high radiation effi-ciency, small size, low profile, and lightweight after changing some elements or structure of DRA antenna, which makes the antenna have more attenuation. To enhance the S-parameters and gain magnitude, the suit-able design of DRA depends on the geometrical and material characteristics used for this purpose. This also enables us to achieve acceptable results with high efficiency. Therefore, the simulation of the antenna must consider beside these properties and characteristics, the effects of surface plasmon waves on the properties of DRA antenna. Adding layers of photonic crystal to the DRA antenna enhances the results and leads to higher gain
Proposing a model for the effect of performance-based budgeting on the qualities of higher education in Iraq
Get PDFNowadays, rivalry can be observed not just between businesses, but also between universities. Higher edu-cation institutions have been under increasing pressure from external factors including labor and education market rivalry to improve the quality of their programs by reevaluating their organizational structures and management practices. This study set out to determine how performance-based budgeting would affect the quality of Iraq\u27s postsecondary institutions. The statistical subjects of this study are those involved in per-formance-based budgeting in Iraqi universities, including the deans of the faculty and deputy deans, the director of the accounting department, and the financial and accounting staff. Morgan\u27s table suggests a minimum sample size of n=246. This is because 3519 individuals were sampled from the population of non-professional private higher education institutions in Iraq. A total of 198 completed surveys were submitted. The collected data from the questionnaire was analyzed using a structured equation model. The results indi-cated that performance-based budgeting benefited greatly from considering organizational commitment and rewards mechanisms. The results, however, showed that the competence of managers played no impact in the introduction of performance-based budgeting in Iraq\u27s higher education sector. However, the results showed that performance-based budgeting had no effect on the quality of higher education in Iraq, and nei-ther did the competency nor the organizational commitment of managers in these institutions, nor did re-ward schemes
Sustainability and environmental attitudes towards specific problems in Latin-American university students
Get PDFUniversity sustainability is a notion with tremendous transformative potential. Knowledge is essential to understand how colleges communicate it to their students in order to assess their potential for transfor-mation. The objective of this study was to assess the level of training in sustainability and associate it with environmental attitudes towards specific problems of university students in Latin-american. Through a quan-titative, correlational and cross-sectional design, two scales were applied to measure the study variables. The population consisted of 3456 university students from 15 public and private universities in Latin-american. Using the simple random probability sampling method with a confidence level of 95% and a margin of error of 5%, the sample consisted of 383 university students. It was found that there was a highly significant rela-tionship between training in sustainability and the environmental attitude towards specific problems of uni-versity students in Latin-american. Universities not only have an impact on the improvement of the quality of life of the university community, but they should also try to intervene in the spaces under a sustainable approach, understanding that students should be the main actors for environmental care
Algorithm for ensuring the minimum power consumption of the end node in the LoRaWAN network
Get PDFThe paper approves the relevance of the development of theoretically justified tools aimed at power con-sumption minimization in the data transmission network of the LoRa WAN standard. Such a network is used to monitor various objects in a distributed system of the Internet of things. LoRa WAN end nodes have au-tonomous power supplies, for which energy costs saving is important. The paper presents expressions for estimating the power consumption of a LoRa WAN end node. Based on the results of computational exper-iments, a database was formed containing signal attenuation values and their corresponding recommended values of transmitter power and spectrum spreading factor. This database is used in the algorithm for ensur-ing the minimum power consumption of the end node
Performance, exergy, and environmental analysis of blast furnace top pressure turbine in an iron-steel factory
Get PDFThe iron-steel industry, which has a large part of its energy consumption, strives to stay at the targeted level in the competition race and to hold on in the field in which it operates. For this purpose, production capacity turned to different energy saving methods due to the effort to reach the relevant standards and high quality low cost strategies. But, energy prices are constantly variable and energy costs are high. In this study, the Blast Furnace Top Pressure Turbine system (TRT), which is one of the important energy saving methods of the iron and steel industry, was examined. Considering the importance of the TRT system, operating condi-tions, operating parameters, and factors affecting energy recovery, the effect of various operating parameters on the operation of the TRT system was evaluated. Considering the annual operating time of 8000 hours, the annual production amount is 42400000 kWh, the value in terms of tons of oil equivalent is 3640 toe, the investment cost of the plant in 2018 is 2755900. The amount of carbon emission reduction due to this production amount was calculated as 10888 kgCO2/h on average, and this amount of carbon emission was prevented every year with the commissioning of the facility. When the cost and energy calculations related to the system are examined, the payback period of the project is calcu-lated as approximately 0.15 years. The obtained data showed that the TRT system is a suitable method for energy saving in the iron and steel industry
Digital citizenship for faculty of Iraqi universities
Get PDFDigital Citizenship (DC) is a set of rules, controls, standards, norms, ideas, and principles followed in the optimal and proper use of technology, which citizens, young and old, need to contribute to the progress of the nation. In short, it is guidance and protection, guidance to the benefits of modern technologies, and protection from their dangers. Or more precisely, it is the smart approach to technology. The concept of digital citizenship has a strong relationship with the education system, so academics in higher education and scientific research institutions must be the most experienced, and effective among their students in this field. Especially after the Corona pandemic and the trend that the universe has gone through towards using the internet in all areas of life, including education, especially integrated education, it has become very important for a citizen to be digital. This study dealt with a sample of university professors with (200) questionnaires. All the professors who belong to colleges with a scientific and human specialization possess digital citizenship. There are no differences between genders except in the education axis, which was in favor of the teaching staff male. In addition to the specialization, it was in favor of the colleges of science
Dynamic response of reinforced concrete beams subjected to low-velocity impact loads using nonlinear finite element analysis
Get PDFThe development of a nonlinear finite element method (FEM) for examining how reinforced concrete (RC) beams react to dynamic forces under the action of low-velocity impacting loads is presented in this article. The model was employed to analyze the stress distributions along with the time histories of impacting load and beam deflection, which were presented graphically. Comparisons with experimental data from previous-ly conducted studies have been performed to verify the precision of the studied model. The findings demon-strated that the developed model was acceptable. Furthermore, the study performed a detailed parametric analysis, focusing on various factors such as replacing conventional steel bars with FRP bars, increasing concrete compressive strength, changing the impact location, using different diameters of reinforcing bars, and changing the depth of the concrete beam. According to the findings, using FRP bars resulted in 36% less peak load due to the uplift pressure caused by the FRP bars\u27 high strength, while the maximum observed deflection of the beam reinforced with FRP bars decreased by approximately 9%. When the position of the impacting force was applied at one-third of the span of the beam, deflection was decreased by 12% when compared to the RC beam has been impacted at its midspan. In addition, the depth of the beams had a sig-nificant impact on the impacting load. These presented findings of the study may contribute to a better un-derstanding of how a structure made of concrete responds to impacting loading
A new technique for cataract eye disease diagnosis in deep learning
Get PDFAutomated diagnosis of eye diseases using fundus images is challenging because manual analysis is time-consuming, prone to errors, and complicated. Thus, computer-aided tools for automatically detecting various ocular disorders from fundus images are needed. Deep learning algorithms enable improved image classifi-cation, making automated targeted ocular disease detection feasible. This study employed state-of-the-art deep learning image classifiers, such as VGG-19, to categorize the highly imbalanced ODIR-5K (Ocular Disease Intelligent Recognition) dataset of 5000 fundus images across eight disease classes, including cata-ract, glaucoma, diabetic retinopathy, and age-related macular degeneration. To address this imbalance, the multiclass problem is converted into binary classification tasks with equal samples in each category. The dataset was preprocessed and augmented to generate balanced datasets. The binary classifiers were trained on flat data using the VGG-19 (Visual Geometry Group) model. This approach achieved an accuracy of 95% for distinguishing normal versus cataract cases in only 15 epochs, outperforming the previous methods. Precision and recall were high for both classes – Normal and Cataract, with F1 scores of 0.95-0.96. Balanc-ing the dataset and using deep VGG-19 classifiers significantly improved automated eye disease diagnosis accuracy from fundus images. With further research, this approach could lead to deploying AI (Artificial intelligence)-assisted tools for ophthalmologists to screen patients and support clinical decision-making