Locations In Jordan Research Articles

Air Quality Index Prediction Using DNN-Markov Modeling

ABSTRACT Air quality measurements contribute to diverse socio-economic sectors, including the environment and healthcare. Many methods are commonly applied to present air-quality levels, reflecting differing national standards. This study presents an air quality index prediction model, to measure air pollution levels for healthcare applications in congested areas. DNN-Markov modeling techniques are used to predict air quality, based on environmental conditions at peak hours. The developed model presents different approaches for highly accurate prediction of the air quality index for the next hour at a given location, under specific environmental conditions. This system could be used to support planning decisions related to the consequences of air quality. The study was conducted in selected locations in Jordan and England as a comparative model prediction accuracy study using different big-data sets of multivariate time series in traffic-heavy locations. The air quality index was represented using Neuro Fuzzy Logic as a method to contribute in air quality index predictions within blurry (boundary) values. The selected DNN-Markov hybrid model could predict air quality with accuracy of around (RMSE 7.86) for the location in England, and around (RMSE 15.27) for the one in Jordan.

Technical, Economic, and Environmental Investigation of Pumped Hydroelectric Energy Storage Integrated with Photovoltaic Systems in Jordan

In this study, the technical and economic feasibility of employing pumped hydroelectric energy storage (PHES) systems at potential locations in Jordan is investigated. In each location, a 1 MWp off-grid photovoltaic (PV) system was installed near the dam reservoir to drive pumps that transfer water up to an upper reservoir at a certain distance and elevation. PVsyst (Version 7.3.4) is implemented to simulate the water flow rate pumped to the upper reservoir at each location. The water in the upper reservoir is presumed to flow back into the dam reservoir through a turbine during peak hours at night to power a 1 MW load. Based on the water volume in the upper reservoir, the power generated through the turbine was estimated using HOMER Pro® (Version 3.15.3), and the power exported to the grid (when the power generated from the turbine is more than the power required by the driven load) was also determined. It is worth mentioning that scaling up the size of PV and hydropower systems is a straightforward approach considering the modular nature of such systems. However, the quantity of water in the dam reservoir that is allowed to be pumped is the main determinant for the size of a PHES system. The technical and economic results show that the potential of employing these locations to implement PHES systems is great. In addition, a study was conducted to estimate how much CO2 emissions were reduced by generating renewable energy compared to generating the same amount of energy from fossil fuels. These systems increase renewable energy in the energy mix in Jordan, stabilize the grid, and balance the loads, especially during peak periods. More importantly, PHES systems contribute to making the energy sector in Jordan more sustainable.

Tuning data preprocessing techniques for improved wind speed prediction

Accurate wind speed forecasting is crucial for efficiently integrating of wind power into the electrical grid and ensuring a stable power supply. However, wind speed is inherently noisy and unpredictable, making it challenging to forecast accurately. This study investigates the effects of hyperparameters of Discrete Wavelet Transform (DWT) and Singular Spectrum Analysis (SSA) on the accuracy of wind speed forecasting using various prediction models. Our proposed method focuses on the optimisation of hyperparameters within the existing models, suggesting that significant untapped potential remains. Our study examines a wide range of wavelet function orders for DWT and varying trend ratio parameter for SSA, and evaluates their impact on the prediction accuracy using real data from thirteen locations in Jordan. Particularly, our investigation reveals that high-order Daubechies wavelets in DWT outperform low-order wavelets. The study also illustrates that optimal hyperparameters must be modified when changing the prediction model and the combination of DWT and SSA enhances prediction performance when the trend ratio is set to 90%. Our results demonstrate that fine-tuning data preprocessing techniques is essential for accurate wind speed prediction since hyperparameter tuning results in greater improvements in prediction accuracy than sophisticated prediction models alone. Our findings underscore the importance of leveraging data preprocessing techniques and hyperparameter tuning for accurate wind speed forecasting.

Importance and Barriers of Establishing Educational/Training Programs in Electric Vehicles/Hybrid-Electric Vehicles in Jordan

Jordan has set priority plans to mitigate climate change impacts, where Jordan moves towards low emissions by promoting the Electric Vehicle and Hybrid-Electric Vehicle (EV/HEV) market. Therefore, there will be a pressing need for professionals in the field of maintenance and design of EV/HEVs. Accordingly, surveys were conducted to address the market needs in Jordan. The surveys targeted main stakeholders from different geographical locations in Jordan. This study was concerned with project partners, Academic staff, and students from eight universities located in Balqa’a, Irbid, Al-Karak, Tafilah, and the capital city Amman. The responses obtained are from 8, 140, and 799 project partners, academic staff, and students, respectively. The results, including surveys on teaching and training facilities, are analyzed and discussed. In conclusion, this study presents a crucial foundation for three specialized diploma programs (vocational diploma, technical diploma, and higher diploma) and a bachelor program tailored to Jordan’s EV/HEV market needs. Through a deliberate alignment of the curriculum with the evolving demands of the EV/HEV sector, the diploma programs will foster graduates who hold the essential knowledge and skills to excel in this rapidly expanding field. Furthermore, the programs address the distinct competencies and expertise that the local market requires, ensuring that graduates are well prepared to meet industry needs. The significance of this work serves as a bridge between academia and the market, resulting in graduates who possess the knowledge and skills, that are highly sought after by prospective employers.

Breaking the Silence: Understanding the Consequences of Intimate Partner Violence on Refugee Men, with Depression as a Key Outcome

ABSTRACT The primary objective of the present study was to investigate the association between exposure to intimate partner violence (IPV) and symptoms of depression among a sample of married refugee men. The study recruited a convenient sample of 539 married Syrian refugee men residing in refugee camps and other locations in Jordan between 2021-2022. A cross-sectional, correlational design was employed. IPV and symptoms of depression among the participants were assessed by the Revised Conflict Tactics Scale (CTS2) and the Patient Health Questionnaire, respectively. The findings of the study revealed a moderate prevalence of depression among the refugee men, with the most experienced types of IPV being the absence of negotiation with partners, psychological violence, physical violence, and injury. Significant positive correlations were observed between all types of IPV and symptoms of depression. It was determined that approximately 80% of the variation in symptoms of depression could be explained by the combination of the four types of IPV. Psychological violence was the strongest predictor for symptoms of depression followed by the absence of negotiation between partners and the occurrence of injury. Offering recommendations for interventions would aid in the development of effective strategies and support systems aimed at mitigating the adverse effects of IPV on the mental well-being of married refugee men.

Response of Wheat Crop to Potassium Fertilization Under Rain-fed Conditions in Semi-arid Regions

Wheat is regarded as one of the major field crops that is mainly grown under rain-fed conditions in Jordan. However, wheat productivity is relatively lower than the world average. This is primarily due to the prevailing drought conditions as a result of poor distribution and low amounts of rainfall. Research studies showed that K can markedly improve wheat yield and quality under water deficit conditions. The objective of the current study was to investigate the effect of soil-applied mineral potassium (K) fertilizer on the yield and growth parameters of two local durum wheat varieties under rain-fed conditions in Jordan. And to determine the rate of K needed to obtain the optimum wheat yield. Two field trials were conducted under rain-fed conditions in two locations in Jordan. Two local durum wheat varieties were grown during two successive growing seasons. Five different rates of K were applied at sowing time. A randomized complete block design with four replications was followed. The results showed that soil K application exhibited a significant effect on wheat crop grain and biological yields of both varieties at the two locations. However, an increasing trend in plant height, harvest index, and thousand-grain weight with increasing K application rate was noticed. Potassium application to soil can alleviate the adverse effects of drought stress on the wheat crop by improving growth and yield attributes.

Machine Learning Classification and Prediction of Wind Estimation Using Artificial Intelligence Techniques and Normal PDF

Estimating wind energy at a specific wind site depends on how well the real wind data in that area can be represented using an appropriate distribution function. In fact, wind sites differ in the extent to which their wind data can be represented from one region to another, despite the widespread use of the Weibull function in representing the wind speed in various wind locations in the world. In this study, a new probability distribution model (normal PDF) was tested to implement wind speed at several wind locations in Jordan. The results show high compatibility between this model and the wind resources in Jordan. Therefore, this model was used to estimate the values of the wind energy and the extracted energy of wind turbines compared to those obtained by the Weibull PDF. Several artificial intelligence techniques were used (GA, BFOA, SA, and a neuro-fuzzy method) to estimate and predict the parameters of both the normal and Weibull PDFs that were reflected in conjunction with the actual observed data of wind probabilities. Afterward, the goodness of fit was decided with the aid of two performance indicators (RMSE and MAE). Surprisingly, in this study, the normal probability distribution function (PDF) outstripped the Weibull PDF, and interestingly, BFOA and SA were the most accurate methods. In the last stage, machine learning was used to classify and predict the error level between the actual probability and the estimated probability based on the trained and tested data of the PDF parameters. The proposed novel methodology aims to predict the most accurate parameters, as the subsequent energy calculation phases of wind depend on the proper selection of these parameters. Hence, 24 classifier algorithms were used in this study. The medium tree classifier shows the best performance from the accuracy and training time points of view, while the ensemble-boosted trees classifier shows poor performance regarding providing correct predictions.

Information sources, attitudes, and practices of Self-Medication by Jordanian patients: A cross-sectional study

Background and ObjectiveSelf-medication (SM) has significantly increased worldwide in the past decades, which may have detrimental health consequences including antimicrobial resistance, adverse drug reactions, drug-drug interaction, and dependency. Although several studies have evaluated the extent of SM, such studies are still limited in Jordan. The aim of this study was to explore sources of SM information, attitudes toward SM and the practice of SM and its associated factors. MethodsThe data of this cross-sectional study was collected between February and July 2022. A validated questionnaire was distributed to patients attending pharmacies from different locations in Jordan. The survey evaluated sources of information and attitudes toward SM, extent of SM practice, and attitudes towards SM, symptoms that the participants treat with SM and those that usually requires medical doctor consolation, followed by questions about the classes of medications mostly used for SM and the reasons for SM. Results and DiscussionThe study enrolled 695 Jordanian adults. The most reported indications for SM included headache (86.9 %), flu (76.4 %), and fever (69.6 %). The most common causes for SM included previous knowledge about the diseases and its treatments (84.2 %), and full knowledge of the medicine to be purchased (55.2 %). Results of the ordinal regression showed that physician counseling frequency was positively and significantly associated with “not being on chronic medication” (p-value = 0.001), and having a positive SM attitude level (p-value = 0.019), while negatively correlated with being in medical field (p-value < 0.001), having no children (p-value = 0.009), and relaying on non-scientific sources to obtain information for SM (p-value = 0.014). The frequency of SM practice was positively associated with being in medical field (p-value < 0.001, having no insurance (p-value < 0.001), and relaying on nonscientific sources (p-value = 0.017). Lastly, having a positive SM attitude level (p-value < 0.001) and not being on chronic medications (p-value = 0.007) were associated with decreased SM practice. ConclusionThe study participants demonstrated increased SM practice due to the wrong perceptions toward SM and the reliance on non-scientific source of information about SM practice.

Assessment of Xenoestrogens in Jordanian Water System: Activity and Identification

Sex hormone disruptors (xenoestrogens) are a global concern due to their potential toxicity. However, to date, there has been no study to investigate the presence of xenoestrogen pollutants in the Jordanian water system. Samples in triplicates were collected from six locations in Jordan, including dams, surface water, tap or faucet water, and filtered water (drinking water-local company). Xenoestrogens were then extracted and evaluated with a yeast estrogen screen utilizing Saccharomyces cerevisiae. Later, possible pollutants were mined using ultrahigh-performance liquid chromatography (UPLC) coupled with a Bruker impact II Q-TOF-MS. Possible hits were identified using MetaboScape software (4000 compounds), which includes pesticide, pharmaceutical pollutant, veterinary drug, and toxic compound databases and a special library of 75 possible xenoestrogens. The presence of xenoestrogens in vegetable samples collected from two different locations was also investigated. The total estrogen equivalents according to the YES system were 2.9 ± 1.2, 9.5 ± 5, 2.5 ± 1.5, 1.4 ± 0.9 ng/L for King Talal Dam, As-Samra Wastewater Treatment Plant, King Abdullah Canal, and tap water, respectively. In Almujeb Dam and drinking water, the estrogenic activity was below the detection limit. Numbers of identified xenoestrogens were: As-Samra Wastewater Treatment Plant 27 pollutants, King Talal Dam 20 pollutants, Almujeb Dam 10 pollutants, King Abdullah Canal 16 pollutants, Irbid tap water 32 pollutants, Amman tap water 30 pollutants, drinking water 3 pollutants, and vegetables 7 pollutants. However, a large number of compounds remained unknown. Xenoestrogen pollutants were detected in all tested samples, but the total estrogenic capacities were within the acceptable range. The major source of xenoestrogen pollutants was agricultural resources. Risk evaluations for low xenoestrogen activity should be taken into account, and thorough pesticide monitoring systems and regular inspections should also be established.

Sonicated waves procedure effect on stabilizing expansive soil by nano-clay: Treat with cause

The use of hydrophilic bentonite nanoclay to improve the geotechnical properties of expansive soils was studied. Sonic waves and manual mixing for two expansive soils (taken from two different locations in Jordan) were studied; thereafter, a comparison between the results obtained from both methods was carried out. Different percentages of nanoclay were added to the two soils: 0, 0.1, 0.3, 0.5, 0.8, 1, 1.5, and 2.5% by dry weight of soil. Their impacts on compaction, unconfined compression strength (UCS), and free swell index (FSI) were investigated. For both methods of mixing, adding nanoclay to the soils resulted in a significant enhancement in strength and a reduction in swell properties of the soils. The UCS results of sonicated samples treated with 0.5% of nanoclay addition showed an increase of 27%–57% and a reduction in FSI by 41%–46.5%. Nevertheless, the UCS of non-sonicated samples treated with 1% of nanoclay showed an increase of 19.3–28.5% and a reduction in FSI by 37.3–44.3%.

Design and Techno-economic assessment of a new hybrid system of a solar dish Stirling engine instegrated with a horizontal axis wind turbine for microgrid power generation

The increasing interest in renewable microgrids have motivated the exploration of more sustainable alternatives to traditional energy supply. In this study, a novel hybrid renewable energy-based microgrid power system is proposed, designed and techno-economically assessed. The system consists of a concentrated parabolic solar dish Stirling engine and a horizontal axis wind turbine integrated with a battery bank. The novelty of the study lies in replacing conventional hybrid systems, such as a typical photovoltaic/wind assembly, with a novel solar dish/wind turbine system that has the potential to achieve higher efficiencies and financial competitiveness. The solar dish Stirling engine serves as the primary source of electrical power generation while the horizontal axis wind turbine, in conjunction with a battery bank, supplies backup electricity when the primary source of power is unavailable. The system has been designed through advanced modelling in the MATLAB/ Simulink® environment that efficiently integrates the individual energy technologies. A technical sensitivity analysis has been performed for all the units in order to reduce the respective design limits and identify optimum operational windows. Further, the performance of the model has been tested at two locations in Jordan, and a thorough techno-economic analysis of the integrated system has been conducted. The simulation results show that at the optimal design point the efficiency of the Stirling engine is 37% with a net output power of 1500 kWe. For the horizontal axis wind turbine, a module of 100 kWe with a power coefficient of 0.2–0.24 is suitable for operation in terms of cost, power, torque and farm size. Also, two economic indicators, namely, the levelised cost of electricity and hourly cost, have been calculated. The levelised cost of electricity lies between 0.13 and 0.15 $/kWh while the hourly cost is found to be around 4 $/h. Thus, the economic evaluation revealed that the proposed system is very competitive with other integrated renewable energy technologies.

Evaluation of Remotely Sensed Precipitation Estimates from the NASA POWER Project for Drought Detection Over Jordan

Droughts can cause devastating impacts on water and land resources and therefore monitoring these events forms an integral part of planning. The most common approach for detecting drought events and assessing their intensity is use of the Standardized Precipitation Index (SPI), which requires abundant precipitation records at good spatial distribution. This may restrict SPI usage in many regions around the world, particularly in areas with limited numbers of ground meteorological stations. Therefore, the use of remotely sensed derived data of precipitation can contribute to drought monitoring. In this study, remotely sensed precipitation estimates from the POWER/Agroclimatology archive of NASA and their derived SPI for different time intervals were evaluated against gauged observations of precipitation from 13 different stations in arid and semiarid locations in Jordan. Results showed significant correlations between remotely sensed and ground data with relatively high R values (0.67–0.91), particularly where seasonal precipitation exceeded 50 mm/year. For evaluation of remotely sensed data in SPI calculation, several objective functions were used; the results showed that SPI based on satellite estimates (SAT-SPI) showed good performance in detecting extreme droughts and indicating wet/dry conditions. However, SAT-SPI showed high tendency to overestimate drought intensity. Based on these findings, remotely sensed precipitation from the POWER/Agroclimatology archive showed good potential for use in detecting extreme meteorological drought with the provision of careful interpretation of the data. These types of studies are essential for evaluating the applicability of new drought monitoring information and tools to support decision-making at relevant scales.

Comparative study between measured and estimated wind energy yield

This paper proposes a power-speed (P-V) model of the wind turbine by assuming three different functions for the first performance region; cubic, quadratic and uncorrected cubic. These three functions have been compared with the manufacturer models of five different wind turbines which were installed in five different locations in Jordan; Tafila, Hofa, Fujeij, Al Rajef, and Deahan. The wind turbine of these wind farms are considered as large scale HAWT in the range of Mw. The generated P-V models are developed by applying a new method described in this paper which is basically based on generating a multiplier factor x. In this study, the quadratic model shows the highest correlation compared with the other models. The wind energy yield for the selected wind farms has been estimated by a mathematical modelling based on Rayleigh distribution function, derived in this paper. The energy yield using this mathematical model has been compared with the measured energy output of four wind farms, Tafila, Hofa, Al Rajef, and Deahan. The measured energy were provided by the operators of these wind farms which are: Jordan Wind Project Company(JWPC), Central Electricity Generation Company (CEGC), Green Watts Renewable Energy (GWRC)and Korean Southern Power Company(KOSPO). Results show that the estimated energy using the quadratic wind turbine model for all wind farms are very close to the actual output. Accuracy analysis for the quadratic model resulted in an error of less than 10% between the measured and estimated energy output for all wind farms. The capacity factors for the selected wind farms have been estimated using the quadratic P-V model. Results show that Tafila wind farm has the highest capacity factor which is around 47%.

21st Century Climate Change Projections of Precipitation and Temperature in Jordan

In this paper the climatic trends of the important climatic factors in Jordan mainly temperature and precipitation have been investigated, and the baseline scenarios (business as usual) of the climatic have been developed. Precipitation, maximum temperature, minimum temperature and mean temperature time series at selected eight climatic stations have been used to develop the business as usual (BAU) and the future climate scenarios in Jordan. Trend analysis revealed obvious decreasing trends in the precipitation time series of most of the stations, the decrease in precipitation started in the decade 1960’s. While temperatures showed increasing trends, the minimum temperature has increased more than the maximum temperature. Climate baseline scenarios of the daily maximum temperature, minimum temperature, mean temperature and precipitation at the 8 locations in Jordan have been generated for the 55 years baseline period 1961 – 2014 using the NCEP re-analysis data, Hadley General Circulation Model (HadCM3) and the Statistical Downscaling Model (SDSM). Two scenario periods, the 2050-2065, and the 2080-2099 were considered. Recent projections of global climate changes in response to increasing greenhouse gas concentrations in the atmosphere include warming in Jordan from about +2.5°C to +5°C by end of century. All projection scenarios indicate a reduction in annual precipitation range from 10% to about 37%. For precipitation, the analysis of the results from the SDSM does not lead to an identical conclusion among all stations.

Do the global lung function initiative reference equations reflect a sample of adult Middle Eastern population?

The global lung function initiative (GLI) 2012 introduced new multi-ethnic spirometry reference values for numerous ethnicities. The aim of this study was to investigate the suitability of the GLI reference values for the adult Jordanian population. About 1875 (1029 females and 846 males) healthy non-smoking adults were enrolled from several locations in Jordan. Spirometry tests were performed. z-scores and predicted normal values were calculated for each participant using GLI 2012 equations in addition to other local equations from the Middle East. Our results indicated that none of the GLI 2012 or other regional equations studied produced an acceptable fit to our data. A need to formulate a specific equation for the Jordanian population is urgently required to better evaluate their respiratory conditions.

Implications of Religion, Culture, and Legislation for Gender Equality at Work: Qualitative Insights from Jordan

With a view to consolidating the existing theory development and stimulating new conceptual thinking, this paper explores the implications of culture, religion (Islam), and the legal framework on women’s employment and their limited advancement in the hospitality industry, one of the important elements of the economy in Jordan. A related aim is to contrast the egalitarian Islamic approach to gender equality with gender discriminatory tribal traditions that restrict women’s employment and progression. Guided by religion, culture, and gender literature, this study uses a qualitative, content-based analysis. Drawing on open-ended questionnaires distributed to a diverse workforce across four tourist locations in Jordan, the results portray how tribalism and Bedouin customs embedded in the participants’ interpretation and practices of their religion (along with the existing legal framework) are maintaining gender gaps in employment and positions of power. The results also reveal that despite the Islamic guidelines towards fairness and justice (haqq and adl) in employment, the tribal and Bedouin traditions restrict women’s employment through patriarchal interpretations of Islam. Thus, the salient novelty and significance of this study were achieved through contributing to the theory development of the interrelations between religion, culture, and gender equality.

Assessment of Photovoltaic Energy Production at Different Locations in Jordan

Jordan is considered one of the sun-belt countries, which possesses high solar radiation on its horizontal surface. This work presents the energy output of photovoltaic (PV) module for three sites in Jordan; these three sites are Irbid (32° N and 35° E) in the northern Jordan, Amman (32° N and 36° E) in the central Jordan, and Aqaba (29° N and 35° E) in southern Jordan. The paper analyses the solar radiation data and ambient temperature to compare the PV energy output at these sites. The analysis showed that the Aqaba is the optimum location in term of PV energy production compared to the selected study locations. It is found that the annual energy production for a module with 340 W capacities is 502 kWh.

Awareness of Radon-222 and its Health Hazards in Jordan

&lt;p class="1Body"&gt;Many studies addressed radon (Rn&lt;sup&gt;222&lt;/sup&gt;) gas concentration levels in a number of locations in Jordan. But, none investigated the level of awareness of Jordanians of radon and its harmful effects on public health. In this study, a sample of 200 participants has been tested for their knowledge of radon and its effects on human health. The authors estimated that 63.1% are unaware of this gas and its respective effects on their health&lt;/p&gt;

Techno-economic analysis of wind power generation for selected locations in Jordan

The aim of the present work is to develop a simple model to assess the capacity factor and predicted costs of wind energy in pre-selected five locations in Jordan. The simulation model is based on calculating the Weibull parameters and the annual electrical energy generated using different commercial types of wind turbine generators (WTG). For each site, detailed analysis was conducted using the developed model to calculate the capacity factor and the final unit cost of electricity (COE) for different types of commercial wind turbines. By merging final values of both factors, the best location and most suitable wind turbine could be defined. The estimated cost of electricity produced by wind energy ranged between 0.0259 and 0.0498 US$/kWh for the best site. While for other sites and wind turbine models, the cost may reach 0.2220 US$/kWh, which is still far less than those incurred in Jordan during 2013 using conventional thermal power plants firing diesel and/or heavy fuel oil. The obtained results are comparable with those published in the open literature for the Middle East region and worldwide. It is believed that such results could benefit not only researchers in this field but also policy makers, developers and investors planning to harness wind energy sources within the Middle East region.

Assessing the efficiency of an innovative method for onsite greywater treatment: Drawer compacted sand filter – A case study in Jordan

This study evaluated the performance of a new treatment method for greywater called the Drawer Compacted Sand Filter (DCSF). This is a modified sand filter design in which the sand filter is broken down into several layers approximately 10cm high, each of which is placed in a movable drawer that is stacked vertically, with each drawer separated by 10cm of space. This treatment unit is seeking to overcome the problems commonly found in traditional sand filter designs, such as clogging, emission of bad odours and need for a large land area to house the filter. Nine pilot DCSF units were operated at different locations in Jordan during the period of 2011–2013. Composite water samples from the inlet and outlets of the DCSF over a period of 18 months were taken periodically and tested for BOD5, COD, TSS, pH, EC and E.coli. A socio-economic study was conducted to evaluate the validity and feasibility of the DCSF. The results showed that DCSF removed 78–96% of BOD5 and COD and 69–98% of TSS. E.coli removal was various across the DCSF units, ranging from 1 log to 6 logs. The focus group discussion and the analysis of economic benefits showed that DCSF unit was acceptable and feasible treatment method for greywater with minimal maintenance requirements.