The Role of the Islamic Waqf in the Equitable Distribution of Wealth in Jordan (2015-2020)

This study aims to shed light on the role of the Islamic Waqf in the equitable distribution of wealth in Jordan between 2015 and 2020. It is the role of the Ministry of Awqaaf and Islamic Affairs as the official government body responsible for the Islamic Waqf in Jordan whose endowment funds directed to mosques, health, education, needy and public sector. The results showed that a disproportionate percentage of spending was directed to the mosques, and the need for the Islamic Waqf to allocate the funds raised from the rich people to support the poor people, and vulnerable population as well as the relevant health education services

Economic Level Of Real Water Losses In Water Distribution System Using Minimum Night Flow Statistical Model

Minimum night flow (MNF) is a common method used to evaluate water loss in a water network. In 2011, the average percentage of non-revenue water (NRW) for the state of Perak in Malaysia was 30.4 %, a figure which resulted in major financial, supply, and pressure losses, as well as excessive energy consumption. In this study, the appropriate time band of MNF and the actual water loss or amount of NRW for the district of Kinta in Perak, Malaysia were investigated. Flow and pressure for 361 zones were monitored for 24 h by the Perak Water Board (Lembaga Air Perak, LAP) using PrimeWorks software (version: 1.5.57.0). Ninety study zones were randomly selected from 361 zones. The 90 study zones were divided into three groups, with each group having 30 zones. Data on the minimum value of flow in 2010 were screened within the time band of 1:00 am to 5:00 am. The frequency of MNF occurrences was analysed every 15 minutes. Results of the study revealed that the majority (85%) of MNF frequencies in the 90 study areas were found at the time band 2:30 am to 4:30 am, whereas 95% of the frequencies were at time band 1:45 am to 4:45 am; therefore, the mean MNF for each zone in 2010 was determined to be between 1:00 am and 5:00 am. Furthermore, a statistical analysis of the characteristic of water distribution network and a modelling of MNF were carried out to estimate water loss in Kinta District, Perak. Factors for physical, hydraulic, and operational variables were selected and correlated with MNF (L/s)

Generalization of Faradays Law of Induction: Some Examples

The induced electromotive force and Faradays law of induction, due to a time-dependant magnetic field, are more conveniently written on the covering space. In this paper, we consider the induced electromotive force in the loop on a covering space which is generated by them time derivative the external magnetic field enclosed that loop.  The total induced electromotive force is derived by summing over all the contributions coming from the infinite winding numbers on the covering space. Illustrative examples of different time-dependent magnetic field are examined and analytical closed form expressions for the total induced electromotive force are derived. Our results, for all these examples, show the explicit dependence of the electromotive force on the ratio between the self-inductance and the resistance of the loop and they reduce to the well-known result when the limit of this ratio gpoes to zero

Time-dependent discrete network design frameworks considering land use

This article proposes optimization frameworks for discrete road network design considering the land-use transport interaction over time. Unlike existing models, the optimization frameworks can determine the optimal designs automatically without trial-and-error once the objective(s) is/are clearly defined. Moreover, these frameworks allow the evaluation of the impacts of the optimal designs on the related parties including landowners, toll road operators, transit operators, and road users, and help network planners and profit-makers with decision making by eliminating many alternative designs. A numerical study is set up to examine road network design's effects on these related parties under three road construction schemes: exact cost recovery, build-operate-transfer, and cross-subsidization. The results show that the changes in landowner profits are not the same after implementing any scheme. These unequal changes raise the issue of the landowner equity. This implies that the government has to consider trade-offs between parties' objectives carefully. © 2010 Computer-Aided Civil and Infrastructure Engineering.postprin

Customer service performance of a public university library in Bangladesh

The study aims to identify the users’ perceptions regarding customer service performance of Dhaka University Library. Questionnaire based survey was done to collect respondents’ demographic information and their responses to items were based on 7-point Likert-type scale. The findings reveal that users are somewhat satisfied with the ‘physical setup’ only, and dissatisfied with the other dimensions. The study suggests customer service personnel of Dhaka University Library need to give personal attention to users’ queries, accepting and redressing user complaints and communicate with the users about library services

Domestic thermoelectric cogeneration system optimization analysis, energy consumption and CO 2 emissions reduction

In this paper, a domestic thermoelectric cogeneration system (DCS) is suggested. This system permits to use the lost heat of exhaust gases to simultaneously heat water and produce electricity via thermoelectric generators (TEG). To proceed, the concept of the system is drawn and the corresponding thermal modeling is developed. An optimization analysis, based on the position of the thermoelectric generators within the system, is carried out using the thermal modeling. The TEGs are places on the inner or outer walls of the tank or the pipe (cases 2–5), or on all of them (case 6). Results show that water can be heated to up to 97 °C, when TEGs are located on the inner wall of the tank. More the TEGs are nearer to the exhaust gases, higher is the total power produced by the TEGs and lower is the water temperature. The power produced by one TEG in direct contact with the exhaust gases is 0.35 W and the water temperature is 76 °C. Also, a DCS with TEG located at all layers can generate up to 52 W and 81 °C hot water, however this configuration has high initial cost. An economic and environmental concerns are considered. Results show that DCS with TEGs located on the inner wall of the pipe has a payback period of 1 year and 8 months when water is heated 60 times per month. In addition to that, it was shown that the location of TEGs do not affect the amount of CO2 gas reduced which is about 6 tons yearly. Finally, this study shows that the configuration where TEGs are placed at the inner wall of the pipe is the most cost-effective energy recovery configuration

AIS for Malware Detection in a Realistic IoT System: Challenges and Opportunities

With the expansion of the digital world, the number of Internet of things (IoT) devices is evolving dramatically. IoT devices have limited computational power and a small memory. Consequently, existing and complex security methods are not suitable to detect unknown malware attacks in IoT networks. This has become a major concern in the advent of increasingly unpredictable and innovative cyberattacks. In this context, artificial immune systems (AISs) have emerged as an effective malware detection mechanism with low requirements for computation and memory. In this research, we first validate the malware detection results of a recent AIS solution using multiple datasets with different types of malware attacks. Next, we examine the potential gains and limitations of promising AIS solutions under realistic implementation scenarios. We design a realistic IoT framework mimicking real-life IoT system architectures. The objective is to evaluate the AIS solutions’ performance with regard to the system constraints. We demonstrate that AIS solutions succeed in detecting unknown malware in the most challenging conditions. Furthermore, the systemic results with different system architectures reveal the AIS solutions’ ability to transfer learning between IoT devices. Transfer learning is a pivotal feature in the presence of highly constrained devices in the network. More importantly, this work highlights that previously published AIS performance results, which were obtained in a simulation environment, cannot be taken at face value. In reality, AIS’s malware detection accuracy for IoT systems is 91% in the most restricted designed system compared to the 99% accuracy rate reported in the simulation experiment

Learning With Imbalanced Data in Smart Manufacturing: A Comparative Analysis

The Internet of Things (IoT) paradigm is revolutionising the world of manufacturing into what is known as Smart Manufacturing or Industry 4.0. The main pillar in smart manufacturing looks at harnessing IoT data and leveraging machine learning (ML) to automate the prediction of faults, thus cutting maintenance time and cost and improving the product quality. However, faults in real industries are overwhelmingly outweighed by instances of good performance (faultless samples); this bias is reflected in the data captured by IoT devices. Imbalanced data limits the success of ML in predicting faults, thus presents a significant hindrance in the progress of smart manufacturing. Although various techniques have been proposed to tackle this challenge in general, this work is the first to present a framework for evaluating the effectiveness of these remedies in the context of manufacturing. We present a comprehensive comparative analysis in which we apply our proposed framework to benchmark the performance of different combinations of algorithm components using a real-world manufacturing dataset. We draw key insights into the effectiveness of each component and inter-relatedness between the dataset, the application context, and the design of the ML algorithm