Research Title: HR practices and turnover intention; the mediating role of organizational commitment in Tehran: a cross-sectional study

Author: Mohammad Khalel Ibrahim Okour, Published Year: 2022

F1000Research, 10:1130

Faculty: Business

Abstract: Background: Employees are increasingly being recognised as a valuable source of information, especially in knowledge-based businesses. Businesses, however, suffer financial and organisational memory losses related to re-hiring and training new staff, and lost productivity and intellectual property because of employee turnover. Hence, employee turnover should be considered an essential part of human resource management. Furthermore, employees’ trust in management and human resource (HR) practices substantially impact organisational commitment (OC). Thus, anticipating employee commitment and turnover intentions is crucial, as people are the sole source for knowledge-based firms to maintain their competitive advantage. In the context of selected Tehran Renewable Energy (RE) firms, this study investigated the mediating impact of OC on the relationship between HR practices (recruitment and selection; training and development opportunities; performance appraisal and evaluation; teamwork; compensation and pay; and job security) and employee turnover intention. Methods: This is a cross-sectional study in Tehran that involved 90 experts and knowledgeable employees from four of Tehran's top RE businesses. A questionnaire was distributed to collect data which was later analysed with correlation, regression and bootstrapping analyses. Results: All six dimensions of HR practices were discovered to have an indirect impact on turnover intention and a direct impact on OC. OC among employees has an indirect effect on turnover intention. It was also revealed that the training and development opportunity has the most considerable effect on OC and turnover intention. OC was not found as a mediator between HR practices and turnover intention. Conclusions: The outcomes of this study showed that both training and development opportunities; and pay and compensation structure were found to be two significant components of HR practices in the relationship with OC. RE managers should employ appropriate HR strategies, particularly in these two dimensions, to improve an individual's degree of OC and reduce turnover intention.

Keywords: HR practices, turnover intention, organisational commitment, learning organisations, renewable energy industry

Research Title: Strategic planning of human resources as an entrance to enhance marketing capabilities: A case study of King Abdullah II Center for Design and Development (KADDB)

Author: Mohammad Khalel Ibrahim Okour, Published Year: 2023

Problems and Perspectives in Management, Volume 21, Issue 1,

Faculty: Business

Abstract: The study aims to identify the impact of strategic planning of human resources in enhancing marketing capabilities at the King Abdullah II Center for Design and Development (KADDB). The descriptive and analytical methods were used to understand the effect of human resource planning in enhancing marketing capabilities. The research population includes all departments in the respective center. As for the sample, it consisted of 65 marketing and sales managers and workers in the marketing departments. A self-administered questionnaire was used to collect the research data. The results showed a significant effect of strategic planning for human resources in enhancing marketing capabilities at KADDB (R2 = 0.619, sig < 0.05). It was also found that strategic planning for human resources contributes to increasing the leader ability to do their work diligently and proficiently and improving the ability to organize work, distribute duties to subordinates, and coordinate efforts. Therefore, this study recommends giving strategic planning to human resources the importance it deserves for its active role in enhancing marketing capabilities at KADDB.

Keywords: strategic planning, human resources, marketing, capabilities, Jordan

Research Title: KIBRA Genetic Polymo A Cross Sectional Study on the Association of KIBRA Genetic Polymorphism with Episodic Memory in North Jordanian Adults"

Author: Raida W. Khalil, Published Year: 2023

Open Access Macedonian Journal of Medical Sciences.,

Faculty: Science

Abstract: BACKGROUND: Episodic memory is one of the cognitive processes most damaged by ageing and is thought to be the system most susceptible to neurodegenerative illnesses. Recently, episodic memory function has been linked to a single nucleotide polymorphism (rs17070145) in the ninth intron of the KIBRA gene (kidney and brain expressed gene). AIM: This study looked at the relationship between the KIBRA polymorphism (rs17070145) and the episodic memory abilities assessed by the Rey Auditory Verbal Learning Test and Rey Complex Figure Test at various time points (20-minute, 30-minute, 24-hours, and 6-month). METHODS:112 healthy adult Jordanians between the ages of 18 and 45 were included in the study, and the genotypes at the KIBRA (rs17070145) polymorphic site were identified using the PCR-RFLP method. RESULTS: The outcomes did not reveal any statistically significant assessment of verbal and visual episodic memory tests and the KIBRA polymorphism. The findings also indicated that KIBRA polymorphism had no statistically significant impact on short-term memory or learning capacity, indicating that KIBRA did not affect a person's ability to pay attention or concentrate. In the Jordanian population, the genotype percentages for KIBRA rs17070145 were: 10.7% for TT, 43.8% for TC, and 45.5% for CC, and the percentage of the T allele was 0.326. CONCLUSION: The current investigation discovered no statistically significant differences between the Jordanian population and either the European or the South Asian populations in terms of the percentages of alleles and genotypes of the KIBRA rs17070145 gene.

Keywords: Keywords: Episodic memory, immediate memory, KIBRA.

Research Title: Modelling of a Solar Heating System for Industrial Processes using Linear Fresnel Reflectors

Author: Yara Hilal Haddad, Published Year: 2023

Faculty: Engineering and Technology

Abstract: Thermal energy in industries has a significant share of the total energy consumed by different processes in the industrial sector. In solar energy rich countries, like Libya, this can be significantly provided by solar energy technologies. Dairy factories involve a number of processes requiring heat at different temperatures. Some processes even require steam at high temperatures. Pasteurization, sterilization, cleaning, washing, and evaporation are some of the operations in dairy processing plants. Concentrated solar power plants can provide such high temperatures using a number of technologies, specifically parabolic trough reflectors, linear Fresnel reflectors, parabolic dish, and the central receiver with a heliostat field. Libya is located in the sun belt and is pleasant with high levels of sun radiation. This paper investigates the techno-economic feasibility of a concentrated solar power plant utilizing linear Fresnel reflectors technology to provide heat for the pasteurizing process at a proposed milk processing diary. A production rate of 100,000 liters per day of milk was assumed. All of the parameters involved in the design process, such as the available area, solar energy available at the location, energy demand of the process, inlet and outlet temperatures, energy storage requirement, and cost per unit of electricity, were fed to the Ressspi platform, a solar simulator for industrial processes. Results showed that the system is highly feasible in terms of technical as well as economic aspects. The heat generated by the solar plant was 1260661.4 kWh, while that consumed by the process was 1321636.8 kWh and that represents 95.4% of the energy needed for the process. The solar utilization factor is 77.1% as a result of energy lost due to defocusing of the Fresnel reflectors. The payback period of the project was found to be 5 years with an internal rate of return of 23.88% and a levelized cost of energy of 0.03228 €/kWh.

Keywords: Solar energy, LFR, Industrial processes

Research Title: An Approach towards Goal-Oriented Requirements Ontology: Consistency and Completeness Based Requirements Analysis

Author: Mohammad Taye, Published Year: 2023

Journal of Software Engineering and Applications, Vol.16 No.2,

Faculty: Information Technology

Abstract: The paper presents a new approach to managing software requirement elicitation techniques with a high level of analyses based on domain ontology techniques, where we established a mapping between user scenario, structured requirement, and domain ontology techniques to improve many attributes such as requirement consistency, completeness and eliminating duplicate requirements to reduce risk of overrun time and budgets. One of the main targets of requirement engineering is to develop a requirement document with high quality. So, we proposed a user interface to collect all vital information about the project directly from the regular user and requirement engineering; After that, the proposal will generate an ontology based on semantic relations and rules. Requirements Engineering tries to keep requirements throughout a project’s life cycle consistent necessities clear, and up to date. This prototype allows mapping requirement scenarios into ontology elements for semantically interrupted. The general points of our prototype are to guarantee the identification requirements and improved nature of the Software Requirements Specification (SRS) by solving incomplete and conflicting information in the requirements specification.

Keywords: Requirements Engineering, Requirements Elicitation, Domain Ontology, Ontology

Research Title: Theoretical Understanding of Convolutional Neural Network: Concepts, Architectures, Applications, Future Directions

Author: Mohammad Taye, Published Year: 2023

Computation, 11

Faculty: Information Technology

Abstract: Convolutional neural networks (CNNs) are one of the main types of neural networks used for image recognition and classification. CNNs have several uses, some of which are object recognition, image processing, computer vision, and face recognition. Input for convolutional neural networks is provided through images. Convolutional neural networks are used to automatically learn a hierarchy of features that can then be utilized for classification, as opposed to manually creating features. In achieving this, a hierarchy of feature maps is constructed by iteratively convolving the input image with learned filters. Because of the hierarchical method, higher layers can learn more intricate features that are also distortion and translation invariant. The main goals of this study are to help academics understand where there are research gaps and to talk in-depth about CNN’s building blocks, their roles, and other vital issues.

Keywords: artificial intelligence (AI); deep learning (DL); machine learning (ML); convolution neural network (CNN); deep learning applications; image classification; supervised learning

Research Title: Polyethylene glycol and polyvinylpyrrolidone: potential green corrosion inhibitors for copper in H2SO4 solutions

Author: Adnan Dahadha, Published Year: 2023

International Journal of Corrosion and Scale Inhibition, 12

Faculty: Science

Abstract: Weight-loss, thermometric, and electrical conductance techniques were employed for the investigation of the influence of polyethylene glycol 400, 4000, and polyvinylpyrrolidone K15 as cost-effective, efficient, and eco-friendly inhibitors on the corrosion inhibition of copper in H2SO4 solution. The corrosion rates of copper in H2SO4 solutions increase with an increase in acid concentrations and temperatures in the absence of inhibitors. The addition of PEG 400, PEG 4000, and PVP K15 to the corrosive solutions was found to have a considerable inhibitory influence on the corrosion rates of copper at various temperatures. Consequently, the inhibition efficiency of PEG 400, PEG 4000 and PVP K15 increases with an increase in their concentrations. Remarkably, PVP K15 was a more efficient inhibitor than PEG 400, and PEG 4000, this effect might be attributed to the nature of the functional groups and the size of the PVP K15 chains. An evaluation of the temperature effect was studied to show that rising temperatures lead to an increased corrosion rate and lower inhibition efficiencies. However, PEG 400, PEG 4000, and PVP K15 inhibited copper corrosion by virtue of adsorption, which was found to accord with the Langmuir and Temkin adsorption isotherm models. Moreover, the thermodynamic aspects (ΔH0, ΔS0 and Ea) of the adsorption process were calculated and discussed

Keywords: corrosion inhibitor, copper, polyethylene glycol, polyvinylpyrrolidone, Temkin and Langmuir adsorption isotherms

Research Title: 5G Wireless Communications Performance Enhancement-Based VANET technology

Author: Qadri Jamal Al-Hamarsheh, Published Year: 2023

20th International Multi-Conference on Systems, Signals, and Devices (IEEE SSD’23) , Mahdia, Tunisia

Faculty: Engineering and Technology

Abstract: Orthogonal Frequency Division Multiplexing is considered as a powerful a technique that supports the needed recent technologies data rates. Thus, in this work it has been proposed to enhance the vehicular communications as a candidate in the 6G communication systems. The QoS for such system is a crucial factor; therefore, this work tackles the QoS from both of the power consumption point of view and of the latency enhancements. In this paper, the QoS modification has been made based on two stages; the reduction of the base stations latency and introducing the multiparalell processing stage. Accordingly, antenna deployment process has been proposed in addition to make use of Daubechies wavelet to overcome the peak to average power ratio problem. The efficiency of the proposed work will be compared to both of the literature work and our previously published work. An extensive simulation has been done, which shows he effectiveness of the proposed work. It outperforms the state-of the artwork and gives a 12% performance enhancement of our previously published work.

Keywords: OFDM, NB-IoT, Multiparalell Processing, Wavelets, and V2V

Research Title: An Artificial Neural Network Approach in Solving Inverse Kinematics of a 6 DOF KUKA Industrial Robot

Author: Qadri Jamal Al-Hamarsheh, Published Year: 2023

20th International Multi-Conference on Systems, Signals, and Devices (IEEE SSD’23), Mahdia, Tunisia

Faculty: Engineering and Technology

Abstract: Inverse kinematics is a mathematical method for computing the joint angles required to set the end effector of a robot in a particular position and orientation. The Inverse kinematics problem is challenging, especially for arm robots with several degrees of freedom. This paper provides two models of artificial neural networks for determining the Inverse kinematics solution of the KUKA KR/R900/SIXX 6 degrees of freedom manipulator. The Non-Linear Autoregressive Neural Network with Multiple Exogenous Variables Recurrent Model is used to create the first model. The second model, Adaptive Feedforward artificial neural networks is used to investigate the impact of several training methods with one hidden layer, changing numbers of neurons in the hidden layer, and measuring the artificial neural networks learning performance on the Inverse kinematics model learning of a 6-joint redundant robotic manipulator. The obtained results showed that the "Bayesian Regularization" training algorithm achieved the lowest mean square error score of 0.005 with a neuron number of 250.

Keywords: KUKA robot, ANN, NARX RNN, Inverse kinematics, Forward kinematics

Research Title: Narrowband Internet-of-Things to Enhance the Vehicular Communications Performance

Author: Qadri Jamal Al-Hamarsheh, Published Year: 2022

Future Internet, 15(1), 16

Faculty: Engineering and Technology

Abstract: The interest in vehicle-to-vehicle communication has gained a high demand in the last decade. This is due to the need for safe and robust smart communication, while this type of communication is vulnerable to latency and power. Therefore, this work proposes the Narrowband Internet-of-Things to enhance the robustness of the vehicular communication system. Accordingly, the system’s QoS is enhanced. This enhancement is based on proposing two parts to cover the latency and the harmonics issues, in addition to proposing a distributed antenna configuration for the moving vehicles under a machine learning benchmark, which uses the across-entropy algorithm. The proposed environment has been simulated and compared to the state-of-the-artwork performance. The simulation results verify the proposed work performance based on three different parameters; namely the latency, the mean squared error rate, and the transmitted signal block error rate. From these results, the proposed work outperforms the literature; at the probability of 10−3 , the proposed work reduces the peak power deficiency by almost 49%, an extra 23.5% enhancement has been attained from the self-interference cancellation side, and a bit error rate enhancement by a ratio of 31%

Keywords: OFDM; V2V; NBIoT; MIMO; harmonics wavelets; multiparallel processing