Web Based E-Learning Solution for Quality Education

Nowadays computers education is necessary in every sector whether it is public or private. General applications like Word processor, Spread sheet, Presentations and email usage is demanded during hiring someone. Under development countries like Pakistan where literacy rate is already low, facing these challenges to produce a quality computer professional. Students have to pay huge amount to get a quality computer training away from their doorstep. Private sector is trying their best to fill this gap for professional education but they offered less quality that leads their efforts towards failure. Students have keen interest to get computers professional education that can help in their future life but they came back with frustration due to low quality of courses offered at high cost. In this situation the frustration can be reduced through Elearning Program. In this paper the author try to offer a web based E-learning solution according to current market requirements. This E-Learning solution may give some hope to those who are tired from current situations

Impact of Length and Percent Dosage of Recycled Steel Fibers on the Mechanical Properties of Concrete

The global rapid increase in waste tyres accumulation, as well as the looming social and environmental concerns, have become major threats in recent times. The use of Recycled Steel Fiber (RSF) extracted from waste tyres in fiber reinforced concrete can be of great profitable engineering applications however the choice of suitable length and volume fractions of RSF is presently the key challenge that requires research exploration. The present experimental work aims at investigating the influence of varying lengths (7.62 and 10.16 cm) and dosages (1, 1.5, 2, 2.5, 3, 3.5, and 4%) of RSF on the various mechanical properties and durability of concrete. Test results revealed that the varying lengths and dosages of RSF significantly affect the mechanical properties of concrete. The improvements in the compressive strength, splitting tensile strength, and Modulus of Rupture (MOR) of RSF reinforced concrete observed were about 26, 70, and 63%, respectively. Moreover, the RSF reinforced concrete showed an increase of about 20 and 15% in the yield load and ultimate load-carrying capacity, respectively. The durability test results showed a greater loss in compressive strength and modulus of elasticity and a smaller loss in concrete mass of SFRC. Based on the experimental findings of this study, the optimum dosages of RSF as 2.5 and 2% for the lengths 7.62 and 10.16 cm lengths, respectively are recommended for production of structural concrete. Doi: 10.28991/cej-2021-03091750 Full Text: PD

Learning-based Resource Allocation for Backscatter-aided Vehicular Networks

Heterogeneous backscatter networks are emerging as a promising solution to address the proliferating coverage and capacity demands of next-generation vehicular networks. However, despite its rapid evolution and significance, the optimization aspect of such networks has been overlooked due to their complexity and scale. Motivated by this discrepancy in the literature, this work sheds light on a novel learning-based optimization framework for heterogeneous backscatter vehicular networks. More specifically, the article presents a resource allocation and user association scheme for large-scale heterogeneous backscatter vehicular networks by considering a collaboration centric spectrum sharing mechanism. In the considered network setup, multiple network service providers (NSPs) own the resources to serve several legacy and backscatter vehicular users in the network. For each NSP, the legacy vehicle user operates under the macro cell, whereas, the backscatter vehicle user operates under small private cells using leased spectrum resources. A joint power allocation, user association, and spectrum sharing problem has been formulated with an objective to maximize the utility of NSPs. In order to overcome challenges of high dimensionality and non-convexity, the problem is divided into two subproblems. Subsequently, a reinforcement learning and a supervised deep learning approach have been used to solve both subproblems in an efficient and effective manner. To evaluate the benefits of the proposed scheme, extensive simulation studies are conducted and a comparison is provided with benchmark techniques. The performance evaluation demonstrates the utility of the presented system architecture and learning-based optimization framework

Assessment of risk factors and MACE rate among occluded and non-occluded NSTEMI patients undergoing coronary artery angiography: A retrospective cross-sectional study in Multan, Pakistan

Objectives: The prime focus of the present study was to evaluate the most occluded coronary artery (OCA) among non-ST elevated myocardial infarction (NSTEMI) patients, and risk factors associated with occluded and non-occluded NSTEMI. Also, major adverse cardiovascular event (MACE) were evaluated among patients during index hospitalization. Methods: A retrospective, cross-sectional study was conducted in Multan Institute of Cardiology, Pakistan between 1st February, 2017, and 31st September, 2017. The data were collected from medical records of the outpatients and inpatients who were index hospitalized. Data were analyzed by using Statistical Packages for Social Sciences (IBM SPSS Statistics for Windows, Version 21.0. Armonk, NY: IBM Corp.) And Microsoft Excel (MS Office 2010). Results: Among 624 patients, angiographic findings revealed that 63.9% were suffering from non-occlusive NSTEMI while 36.1% of the patients had occluded NSTEMI. In occluded NSTEMI patients, 30.3% were having single vessel occlusion while 5.8% were having multi-vessel occlusion. Also, 49.8% were having occlusion of right coronary artery (CA) while 44% were having occluded left anterior descending (LAD) artery. Multivariate analysis revealed that age (p=0.001) and left ventricular ejection fraction (LVEF) (p=0.001) had a statistically significant association. The incidence of MACE was high among non-OCA patients as compared to OCA patients but no statistically significant association was found (p=0.44). Conclusions: Angiography confirmed that most of the NSTEMI patients had OCA. But the MACE rate was not significantly differ among OCA and non-OCA patients. The risk factors associated with OCA were low LVEF and age

Evaluation of unexplained clinical features of hepatic diseases through biopsies among hospitalized children: A cross-sectional study in Lahore, Pakistan

Objectives: There are variations in therapeutic regimens of different liver diseases. The accurate diagnosis ensures prompt recovery from these diseases. The present study aimed to evaluate the underlying causes of unexplained signs and symptoms associated with liver diseases through biopsies. Methods: A retrospective study was conducted in a public child care specialty of Lahore, Pakistan. The data was collected from medical records of the patients who were index hospitalized with unexplained clinical presentation of liver disease between 1st July, 2017 and 31st December, 2017. Data were analyzed by using Statistical Packages for Social Sciences (IBM SPSS Statistics for Windows, Version 21.0. Armonk, NY: IBM Corp.), and Microsoft Excel (MS Office 2010). Results: Overall, the records of 53 patients were selected for the study. Most of them were 11 to 15 years of age. The patients were presented with unexplained hepatomegaly (60.4%) and jaundice (40.7%) during index hospitalization which made them eligible for liver biopsy (LB). The findings of LB revealed that the underlying causes of liver diseases in most of the cases were metabolic (33.9%) and inflammatory disorders (22.6%). Majority of the patients were ≤4 years of age, however cryptogenic cirrhosis (39.1%) was commonly found in >10 years of age. Although most of the patients were suffering from metabolic disorders (p-value=0.07) and liver cirrhosis (p-value=0.08) but these were not statistically significant. Conclusions: LB was beneficial in evaluating the etiologies of unexplained signs and symptoms of liver diseases. It was found that glycogen storage diseases and liver cirrhosis were the most common etiologies of liver diseases among pediatric patients. But etiologies like metabolic and inflammatory diseases were insignificantly associated with gender

Indo-Pak Relationship on Line of Control after Pakistan Inclusion in Afghan Soviet War 1979

Afghan’s invasion of the Soviet Union in 1979 created panic worldwide and proved a decisive moment in the international political scenario. Soviet expansionism policy when challenged the security of Pakistan, it appeared as a front - line country and the main route to provide aid for Afghan Mujahedin. This paper has analytically reviews the Pakistan’s decision to join 1979 Afghan war and evaluated how it benefited economic and defense conditions of Pakistan. Simultaneously, the article presents how this Afghan war posed grave threats to security (internal as well as external) of the country due to refugees flood that resulted not only in problematic scenario with respect to the economy, politics, and society but also produced ecological difficulties. Moreover, Afghan refugees caused deforestation for their food, eroded soil, propped up Kalashnikov culture, illegal drug trade, and other infinite law and order troubles. However, Pakistan had no better option except to take part in the Afghan wa

Attention-Based CNN-RNN Arabic Text Recognition from Natural Scene Images

According to statistics, there are 422 million speakers of the Arabic language. Islam is the second-largest religion in the world, and its followers constitute approximately 25% of the world’s population. Since the Holy Quran is in Arabic, nearly all Muslims understand the Arabic language per some analytical information. Many countries have Arabic as their native and official language as well. In recent years, the number of internet users speaking the Arabic language has been increased, but there is very little work on it due to some complications. It is challenging to build a robust recognition system (RS) for cursive nature languages such as Arabic. These challenges become more complex if there are variations in text size, fonts, colors, orientation, lighting conditions, noise within a dataset, etc. To deal with them, deep learning models show noticeable results on data modeling and can handle large datasets. Convolutional neural networks (CNNs) and recurrent neural networks (RNNs) can select good features and follow the sequential data learning technique. These two neural networks offer impressive results in many research areas such as text recognition, voice recognition, several tasks of Natural Language Processing (NLP), and others. This paper presents a CNN-RNN model with an attention mechanism for Arabic image text recognition. The model takes an input image and generates feature sequences through a CNN. These sequences are transferred to a bidirectional RNN to obtain feature sequences in order. The bidirectional RNN can miss some preprocessing of text segmentation. Therefore, a bidirectional RNN with an attention mechanism is used to generate output, enabling the model to select relevant information from the feature sequences. An attention mechanism implements end-to-end training through a standard backpropagation algorithm

INCORPORATION OF WHEAT STRAW ASH AS PARTIAL SAND REPLACEMENT FOR PRODUCTION OF ECO-FRIENDLY CONCRETE

The depletion of natural sand resources occurs due to excessive consumption of aggregate for concrete production. Continuous extraction of sand from riverbeds permanently depletes fine aggregate resources. At the same time, a major ecological challenge is the disposal of agricultural waste ash from biomass burning. In this study, an environmental friendly solution is proposed to investigate the incorporation of wheat straw ash (WSA) by replacing 0, 5, 10, 15, and 20% of sand in concrete. Characterization results of WSA revealed that it was well‐graded, free from organic impurities, and characterized by perforated and highly porous tubules attributed to its porous morphology. A decrease in fresh concrete density and an increase in slump values were attained by an increase in WSA replacement percentage. An increasing trend in compressive strength, hardened concrete density, and ultrasonic pulse velocity was observed, while a decrease was noticed in the values of water absorption with the increase in WSA replacement percentages and the curing age. The WSA incorporation at all replacement percentages yielded concrete compressive strength values over 21 MPa, which complies with the minimum strength requirement of structural concrete as specified in ACI 318‐19. Acid resistance of WSA incorporated concrete improved due to the formation of pozzolanic hydrates as evident in Chappelle activity and thermogravimetric analysis (TGA) results of WSA modified composites. Thus, the incorporation of WSA provides an environmentally friendly solution for its disposal. It helps in conserving natural aggregate resources by providing a suitable alternative to fine aggregate for the construction industry

Visual Object Tracking With Discriminative Filters and Siamese Networks: A Survey and Outlook

Accurate and robust visual object tracking is one of the most challenging and fundamental computer vision problems. It entails estimating the trajectory of the target in an image sequence, given only its initial location, and segmentation, or its rough approximation in the form of a bounding box. Discriminative Correlation Filters (DCFs) and deep Siamese Networks (SNs) have emerged as dominating tracking paradigms, which have led to significant progress. Following the rapid evolution of visual object tracking in the last decade, this survey presents a systematic and thorough review of more than 90 DCFs and Siamese trackers, based on results in nine tracking benchmarks. First, we present the background theory of both the DCF and Siamese tracking core formulations. Then, we distinguish and comprehensively review the shared as well as specific open research challenges in both these tracking paradigms. Furthermore, we thoroughly analyze the performance of DCF and Siamese trackers on nine benchmarks, covering different experimental aspects of visual tracking: datasets, evaluation metrics, performance, and speed comparisons. We finish the survey by presenting recommendations and suggestions for distinguished open challenges based on our analysis.Funding Agencies|Khalifa University of Science and Technology [FSU-2022-003, 84740 00401]; Research Center for Informatics Project [CZ.02.1.01/0.0/0.0/16_019/0000765]</p