Performance Analysis of Open Steam Power Cycle Powered by Concentrated Solar Energy

This study aims to develop a concentrated solar receiver designed to directly generate steam for driving a steam turbine within the steam power cycle of a carbon-free system. The solar power system consists of parabolic dishes, evaporation tanks, and a steam turbine, and the experimental setup was tested on different days, analyzing the measured parameters with the EES software. Results from the investigation indicate that, under the optimal conditions with a maximum recorded temperature and pressure of 143 ℃ and 2.5 bar, respectively, and a vaporized water mass of 100 grams, the manufactured turbine achieved a maximum isentropic efficiency of 92.48% and a power of 1.76 W. Notably, the evaporation tank and the mini steam turbine demonstrated the capability to generate steam and mechanical power, respectively, without relying on conventional energy

An Analytical Study of Gross Domestic Product Per Capita in United States Dollar for Selected Asian Countries

The world is divided into various countries. These countries have their own policy for economic development. There are various methods for determining economic development out of that one method or one measure is Gross Domestic Product (GDP). Every country has their own GDP which measure the performance of economy. For this study gross domestic product per capita in United States dollar has been analyzed with selected Asian countries based on respective nation's population as on 2021. The study period is considered from 2015 to 2021. For identify difference among per capita GDP of selected nations one way ANOVA tool has been used as statistical parameter. The major finding of the study indicated as China saw increasing trend of per capital GDP for selected time period. India indicated fluctuating trend of per capita GDP for the study period. Out of selected countries Pakistan indicated lowest per capital GDP from selected countries. On an average performance of Indonesia, Philippines and Vietnam in concern with per capita GDP was same during the study period. Japan indicated highest per capital GDP out of selected countries

Simulation of Three-Dimensional Flow Field around Unconventional Bridge Piers

The study presents a three-dimensional numerical simulation of turbulent flow field around unconventional bridge piers which are downstream-facing round- nosed (DS-FRNP) and upstreamfacing round- nosed (US-FRNP) and are compared with a circular pier in fixed-bed using the computational fluid dynamics (CFD). In this paper, the flow field passing around the bridge piers is predicted using k- standard turbulence model. The predicted flow velocity in x-direction and turbulent kinetic energy (TKE) are compared with the tested data. Simulated flow velocity and turbulent kinetic energy are in good agreement with experimental data. Numerical model predicts the flow features such as flow reversal upstream the pier, down flow upstream the pier and flow in wake region, the shape of vortices (horse shoe vortex and wake vortex) also captured by simulation. The discussion of the relation between bridge pier shape and turbulent kinetic energy in this study will help to control the scour around bridge piers

Optimal Deployment of Tethered Drones for Maximum Cellular Coverage in User Clusters

Unmanned aerial vehicle (UAV) assisted cellular communication is gaining significant interest recently. Although it offers several advantages over terrestrial communication, UAV communication suffers from two main shortcomings. The typical untethered UAV (uUAV) has a limited battery power supply and therefore limited flying time, and it needs an extra wireless backhaul link to connect users to the core network. In this paper, we propose the utilization of the tethered UAV (tUAV) to assist the cellular network, where the tether provides power supply and connects the tUAV to the core network through high capacity link. The tUAV however has a limited mobility due to the limited tether length. A stochastic geometry-based analysis is provided for the coverage probability of an UAV-assisted cellular network where the mobile users located within a circular hot-spot. For that setup, we analyze and compare two scenarios: (i) utilizing uUAV and (ii) utilizing tUAV, for offloading the terrestrial base station (TBS). We capture the aforementioned limitations of each of the uUAV and the tUAV in our analysis. A novel user association analysis is provided given the TBS and the UAV locations. Next, we study the optimal locations of the uUAV and the tUAV to maximize the coverage probability. Multiple useful insights are revealed. For instance, numerical results show that tUAVs outperform uUAVs when the tether length is above 75 m, given that the uUAV is available for 80% of the time due to its battery limitations.Comment: Accepted at the IEEE Transaction on Wireless Communication

Modeling Long-Term Temporal Variation of Dew Formation in Jordan and Its Link to Climate Change

In this study, we performed model simulations to investigate the spatial, seasonal, and annual dew yield during 40 years (1979–2018) at ten locations reflecting the variation of climate and environmental conditions in Jordan. In accordance with the climate zones in Jordan, the dew formation had distinguished characteristics features with respect to the yield, seasonal variation, and spatial variation. The highest water dew yield (an overall annual mean cumulative dew yield as high as 88 mm) was obtained for the Mountains Heights Plateau, which has a Mediterranean climate. The least dew yield (as low as 19 mm) was obtained in Badia, which has an arid climate. The dew yield had a decreasing trend in the past 40 years due to climate change impacts such as increased desertification and the potential of sand and dust storms in the region. In addition, increased anthropogenic air pollution slows down the conversion of vapor to liquid phase change, which also impacts the potential of dew formation. The dew yield showed three distinguished seasonal patterns reflecting the three climates in Jordan. The Mountains Heights Plateau (Mediterranean climate) has the highest potential for dew harvesting (especially during the summer) than Badia (semi-arid climate)

Nexus between Intellectual Capital and Financial Performance Sustainability: Evidence from Listed Jordanian Firms

Purpose: The authors observe the effect of exploring the reality of Intellectual Capital (IC) and its impact on the financial performance of Jordanian industrial firms in Amman Stock Exchange. This empirical research explores the effect of intellectual capital on financial performance using data from 36 Jordanian industrial firms listed in Amman Stock Exchange for the period 2016-2020. The Value-Added Intellectual coefficient (VAIC) was adopted to measure the intellectual capital, while the return on assets (ROA), return on equity (ROE), and earnings per share (EPS) were adopted as measures of the companys financial performance. The effect of IC was tested by using statistical analysis, dependent on the data obtained from annual financial statements. The results showed that the IC has a significant and positive effect on profitability due to its significant effect on ROA and EPS. However, it has not been proven that IC affects the ROE. This research extends the research on IC and aims to enrich studies in this field, especially in the Jordanian market. It reflects the reality of Intellectual Capital and its impact on industrial firms’ performance in Jordan as an example of developing countrie

Brain Tumors Classification by Using Gray Level Co-occurrence Matrix, Genetic Algorithm and Probabilistic Neural Network

Background:Brain tumors classification by MRI (Magnetic Resonance Imaging) is important in medical diagnosis because it provides information associated with anatomical structures as well as potential abnormal tissues necessary for treatment planning and patient's case follow-up. There are a number of techniques for medical image classification. In this paper brain tumors detection and classification system are developed into seven tumors types. The image processing techniques such as preprocessing by using a mean filter and feature extraction have been implemented for the detection of a brain tumor in the MRI images. In this paper, extraction of texture features using GLCM (Gray Level Co-occurrence Matrix). We used Probabilistic Neural Network Algorithm (PNNA) for image classification technique based on Genetic Algorithm (GA) and K-Nearest Neighbor (K-NN) classifier for feature selection is proposed in this paper. Objective: MRI brain tumors detection and classification system by using GA and PNN which able to diagnose different types of tumors in human brain. Patients and Methods: Medical image techniques are used to imaging the internal structures of the human body for medical diagnosis. Image processing is an effective field of research in the medical field. MRI dataset, obtained from the Atlas Website of Harvard University. Results: Brain Tumors are classified by using the genetic algorithm where the total number of features (20 features) has been reduced to 10 features as the strongest features in the classification. Conclusion: MRI brain image is one of the best methods in brain tumor detection and classification, by observing only MRI images the specialists are unable to keep up with diagnosing. Hence, the computer-based diagnosis is necessary for the correct brain tumor classification

Breast Cancer Screening

Breast cancer is a common malignancy worldwide. It is considered top cancer in women and about 13% of women in the general population will develop breast cancer sometimes during their lives, with a gradual increase in incidence as survival increases. Primary prevention of breast cancer is directed toward promoting a healthy lifestyle and reversing modifiable risk factors; these factors include smoking cessation, physical activity, alcohol, and dietary modification. Imaging plays an important role in the diagnosis and management of breast cancer, it is also considered the most valuable tool in screening breast cancer. Mammogram is the most widely used method; it is recommended by many societies and committees as a useful method for early detection of breast cancer. False-positive and over-diagnosis constitute a problem in using screening mammogram. The implementation of a screening program faces many issues that may adversely affect its success such as personal factors, social factors, and accessibility issues. These issues should be identified as the initial step in program implementation. The role of Magnetic Resonance Imaging and Ultrasound is mainly in high-risk patients. The introduction of Artificial Intelligence in Mammogram may add beneficial effects in time and efforts improving its efforts