Abstract: The proliferation in the development of mobile learning (m-learning) has played a vital role in the rapidly growing electronic learning market. This relatively new technology can help to encourage the development of in learning and to aid knowledge transfer a number of areas, by familiarizing students with innovative information and communications technologies (ICT). M-learning plays a substantial role in the deployment of learning methods for nursing students by using the Internet and portable devices to access learning resources ‘anytime and anywhere’. However, acceptance of m-learning by students is critical to the successful use of m-learning systems. Thus, there is a need to study the factors that influence student’s intention to use m-learning. This paper addresses this issue. It outlines the outcomes of a study that evaluates the unified theory of acceptance and use of technology (UTAUT) model as applied to the subject of user acceptance in relation to m-learning activity in nurse education. The model integrates the significant components across eight prominent user acceptance models. Therefore, a standard measure is introduced with core determinants of user behavioural intention. The research model extends the UTAUT in the context of m-learning acceptance by modifying and adding individual innovativeness (II) and quality of service (QoS) to the original structure of UTAUT. The paper goes on to add the factors of previous experience (of using mobile devices in similar applications) and the nursing students’ readiness (to use the technology) to influence their behavioural intentions to use m-learning. This study uses a technique called ‘convenience sampling’ which involves student volunteers as participants in order to collect numerical data. A quantitative method of data collection was selected and involves an online survey using a questionnaire form. This form contains 33 questions to measure the six constructs, using a 5-point Likert scale. A total of 42 respondents participated, all from the Nursing Institute at the Armed Forces Hospital in Saudi Arabia. The gathered data were then tested using a research model that employs the structural equation modelling (SEM), including confirmatory factor analysis (CFA). The results of the CFA show that the UTAUT model has the ability to predict student behavioural intention and to adapt m-learning activity to the specific learning activities. It also demonstrates satisfactory, dependable and valid scales of the model constructs. This suggests further analysis to confirm the model as a valuable instrument in order to evaluate the user acceptance of m-learning activity.
Abstract: Natural gas is the most popular fossil fuel in the
current era and future as well. Natural gas is existed in underground
reservoirs so it may contain many of non-hydrocarbon components
for instance, hydrogen sulfide, nitrogen and water vapor. These
impurities are undesirable compounds and cause several technical
problems for example, corrosion and environment pollution.
Therefore, these impurities should be reduce or removed from natural
gas stream. Khurmala dome is located in southwest Erbil-Kurdistan
region. The Kurdistan region government has paid great attention for
this dome to provide the fuel for Kurdistan region. However, the
Khurmala associated natural gas is currently flaring at the field.
Moreover, nowadays there is a plan to recover and trade this gas and
to use it either as feedstock to power station or to sell it in global
market. However, the laboratory analysis has showed that the
Khurmala sour gas has huge quantities of H2S about (5.3%) and CO2
about (4.4%). Indeed, Khurmala gas sweetening process has been
removed in previous study by using Aspen HYSYS. However,
Khurmala sweet gas still contents some quintets of water about 23
ppm in sweet gas stream. This amount of water should be removed or
reduced. Indeed, water content in natural gas cause several technical
problems such as hydrates and corrosion. Therefore, this study aims
to simulate the prospective Khurmala gas dehydration process by
using Aspen HYSYS V. 7.3 program. Moreover, the simulation
process succeeded in reducing the water content to less than 0.1ppm.
In addition, the simulation work is also achieved process
optimization by using several desiccant types for example, TEG and
DEG and it also study the relationship between absorbents type and
its circulation rate with HCs losses from glycol regenerator tower.