Abstract
Saline water irrigation has been used in date palm (
Phoenix dactylifera
L.) agriculture as an alternative to non-saline water due to water scarcity in hyper-arid environments. However, the ...knowledge pertaining to saline water irrigation impact on the root-associated bacterial communities of arid agroecosystems is scarce. In this study, we investigated the effect of irrigation sources (non-saline freshwater vs saline groundwater) on date palm root-associated bacterial communities using 16S rDNA metabarcoding. The bacterial richness, Shannon diversity and evenness didn’t differ significantly between the irrigation sources. Soil electrical conductivity (EC) and irrigation water pH were negatively related to Shannon diversity and evenness respectively, while soil organic matter displayed a positive correlation with Shannon diversity. 40.5% of total Operational Taxonomic Units were unique to non-saline freshwater irrigation, while 26% were unique to saline groundwater irrigation. The multivariate analyses displayed strong structuring of bacterial communities according to irrigation sources, and both soil EC and irrigation water pH were the major factors affecting bacterial communities. The genera
Bacillus
,
Micromonospora
and
Mycobacterium
were dominated while saline water irrigation whereas contrasting pattern was observed for
Rhizobium
,
Streptomyces
and
Acidibacter
. Taken together, we suggest that date-palm roots select specific bacterial taxa under saline groundwater irrigation, which possibly help in alleviating salinity stress and promote growth of the host plant.
E-hailing applications are becoming popular around the globe. However, the motivations and barriers to use these applications may differ in different countries. Therefore, the aim of current work is ...to explore noteworthy factors affecting the acceptance of the e-hailing application 'Careem' in the context of Saudi Arabia. Due to recent driving permission given to women in Saudi Arabia and the lesser acceptance of public transport in Saudi Arabia, this study is of fundamental importance. To achieve the purpose of this study, the technology acceptance model is extended by adding external variables: perceived convenience, perceived accessibility and confirmation. Careem application users participated in a survey that was created and circulated to acquire measurement of the factors. The data gathered from 428 users are analysed using structural equation modelling. The findings show that perceived usability, perceived ease of use, perceived usefulness and perceived convenience are crucial and direct predictors of intention to use e-hailing applications, while confirmation and perceived accessibility are discovered to be factors that have an impact on the intention to use e-hailing applications. The findings of the study highlight the significant contributing factors in the adoption and usage of e-hailing applications. Also, these factors can assist designers and developers of these applications to develop applications having high acceptance and usage.
Radio propagation models (RPMs) are generally employed in Vehicular Ad Hoc Networks (VANETs) to predict path loss in multiple operating environments (e.g. modern road infrastructure such as flyovers, ...underpasses and road tunnels). For example, different RPMs have been developed to predict propagation behaviour in road tunnels. However, most existing RPMs for road tunnels are computationally complex and are based on field measurements in frequency band not suitable for VANET deployment. Furthermore, in tunnel applications, consequences of moving radio obstacles, such as large buses and delivery trucks, are generally not considered in existing RPMs. This paper proposes a computationally inexpensive RPM with minimal set of parameters to predict path loss in an acceptable range for road tunnels. The proposed RPM utilizes geometric properties of the tunnel, such as height and width along with the distance between sender and receiver, to predict the path loss. The proposed RPM also considers the additional attenuation caused by the moving radio obstacles in road tunnels, while requiring a negligible overhead in terms of computational complexity. To demonstrate the utility of our proposed RPM, we conduct a comparative summary and evaluate its performance. Specifically, an extensive data gathering campaign is carried out in order to evaluate the proposed RPM. The field measurements use the 5 GHz frequency band, which is suitable for vehicular communication. The results demonstrate that a close match exists between the predicted values and measured values of path loss. In particular, an average accuracy of 94% is found with R2 = 0.86.
► The study explored Facebook motives and psychological symptoms among students. ► Based on Uses and Gratifications Theory and Brown’s Addiction Framework. ► Motives: Social Networking, Psychological ...Benefits, Entertainment, Self Presentation, Skill Enhancement. ► Addictions: Salience, Loss of Control, Withdrawal and Relapse and Reinstatement.
Malaysians were reported to have the most number of Facebook friends, spend more time on Facebook and might be addicted to Facebook as well. This paper explored Facebook usage pattern, motivations and psychological/behavioural factors affecting the users. A focus group study was first conducted to explore motives to use Facebook and symptoms related to excessive Facebook usage. The themes emerging from this were then used in addition to Uses and Gratifications theory and Brown’s Addiction framework to further explore Facebook usage pattern, motivations and behavioural issues among a large group of students. Results show that Malaysian students use Facebook actively, similar to other studies done worldwide. Factor analyses yielded five motives to use Facebook: Social Networking, Psychological Benefits, Entertainment, Self Presentation and Skill Enhancement. As for the behavioural symptoms, Salience, Loss of Control, Withdrawal and Relapse and Reinstatement emerged as the four main symptoms. These results show that in general Malaysian students use Facebook for similar motives as reported in literature. However, it is interesting to note that they also exhibited behavioural symptoms, such as Salience, Loss of Control, Withdrawal and Relapse and Reinstatement due to excessive Facebook usage.
Mobile applications are getting a great deal of interest among researchers due to their proliferation and pervasiveness, especially in the context of digital libraries of educational institutes. ...However, their low acceptance and usage are observed, hence, in-depth investigations are required in order to understand the factors behind low acceptance and intention to use mobile library application (MLA). Therefore, the aim of this work is to empirically explore the acceptance of MLA with a proposed model that is evolved from the technology acceptance model (TAM). The study objects to deliver empirical provision on acceptance of MLA. A self-administrated cross-sectional survey-based study was conducted to gather data from 340 users of MLA. Structural equation model (SEM) with an analysis of moment structure (AMOS) software was conducted to examine quantitative data. Results revealed that perceived usefulness and perceived ease of use are direct significant predictors with the intention to use MLA whereas system quality and habit are the influencing factors toward the usage intention of MLA. The findings help as a guide for effective decision in the design and development of MLA. Further, the outcomes can be utilized in the resource allocation process for ensuring the success of the library's vision and mission.
•Study on initial acceptance of mobile library application for Pakistani context.•Model integrates external factors, habit and system quality in technology acceptance model.•Habit and system quality have strong indirect impact on behavioural intention toward mobile library application.•Perceived ease of use and perceived usefulness have strong mediating effect on mobile library application usage.•Over all, model shows the strong initial acceptance of mobile library application in Pakistan.
With the evolution of data mining systems, the acquisition of timely insights from unstructured text is an organizational demand which is gradually increasing. The existing opinion mining systems ...have a variety of properties, such as the ranking of products’ features and feature level visualizations; however, organizations require decision-making based upon customer feedback. Therefore, an opinion mining system is proposed in this work that ranks reviews and features based on novel ranking schemes with innovative opinion-strength-based feature-level visualization, which are tightly coupled to empower users to spot imperative product features and their ranking from enormous reviews. Enhancements are made at different phases of the opinion mining pipeline, such as innovative ways to evaluate review quality, rank product features and visualize opinion-strength-based feature-level summary. The target user groups of the proposed system are business analysts and customers who want to explore customer comments to gauge business strategies and purchase decisions. Finally, the proposed system is evaluated on a real dataset, and a usability study is conducted for the proposed visualization. The results demonstrate that the incorporation of review and feature ranking can improve the decision-making process.
The increasing use and ubiquity of the Internet facilitate dissemination of word-of-mouth through blogs, online forums, newsgroups, and consumer’s reviews. Online consumer’s reviews present ...tremendous opportunities and challenges for consumers and marketers. One of the challenges is to develop interactive marketing practices for making connections with target consumers that capitalize consumer-to-consumer communications for generating product adoption. Opinion mining is employed in marketing to help consumers and enterprises in the analysis of online consumers’ reviews by highlighting the strengths and weaknesses of the products. This paper describes an opinion mining system based on novel review and feature ranking methods to empower consumers and enterprises for identifying critical product features from enormous consumers’ reviews. Consumers and business analysts are the main target group for the proposed system who want to explore consumers’ feedback for determining purchase decisions and enterprise strategies. We evaluate the proposed system on real dataset. Results show that integration of review and feature-ranking methods improves the decision making processes significantly.
The exponential growth of technology in the e-learning sector has reshaped the traditional way of learning because of its efficient and flexible nature. However, e-learning is still in the ...rudimentary phase of progress in developing countries at schools and universities. It needs to investigate the critical features behind the embracing of e-learning systems in developing countries. This study targeted the schools by investigating the critical factors towards the acceptance of an e-learning system i.e., e-Learn Punjab (e-LP) in Pakistan. Further, this study provided empirical support for acceptance of e-LP, with the proposed model based on the technology acceptance model (TAM). The model integrates factors such as self-efficacy, training, and task technology fit with TAM for inquiring about the user attitude toward e-LP. A cross-sectional survey-based study with self-administration was conducted to collect data from 310 teachers at different government schools in Punjab, a province of Pakistan. The data were analyzed with the structural equation model (SEM) by using analysis of moment structure (AMOS) software. Fallout revealed the direct effect of self-efficacy on ease of use with strong influence of training on both core constructs of TAM. The non-significant influence of self-efficacy and task technology fit was also observed on usefulness.
•In MCS, the GPS embedded vehicles and motorist mobiles are used to sense and collect the vehicular data.•MCS-DTEF mechanism is applied to assign time slot and allocate fastest path dynamically to ...every vehicle to minimize traffic congestions.•MCS-DTEF strategy demonstrates significantly improved traffic flow performance in terms of reducing time and fuel consumption.
Mobile Crowd Sensing (MCS) is a developing category of Internet of Things applications that are used in Intelligent Transportation System to improve the transport system. In today’s metropolitan life, traffic congestion in busy hours is the main problem due to which many commuters are unable to reach their destination on time, motorist time and extra fuel are wasted. In this paper, the MCS-based Dynamic Traffic Efficiency Framework (MCS-DTEF) for traffic congestion control is presented. The basic characteristics of MCS-DTEF are: traffic detection can be performed without deploying sensor devices on both sides of the road. The traffic data can be collected in real time, traffic flow can be predicted and managed according to current situations which reducing fuel consumption and driving time. Simulation of Urban Mobility simulator is used for evaluation. Meaningful and reliable statistical data is obtained by the traffic flow which is built according to Normal Traffic Conditions (NTC’s) in the first scenario. In the second simulation scenario, the MCS-DTEF mechanism is applied to assign a time slot to a requested vehicle and dynamically allocate the fastest path to each vehicle which is introduced to avoid traffic congestion. To validate the results of the proposed framework technique by comparing with NTC’s and real-world traffic flow in three different situations morning, afternoon and evening are examined and tested to explore the traffic usage parameter. The results show that the MCS-DTEF strategy demonstrates significantly improved traffic flow performance in terms of reducing time to destination, fuel consumption and increased vehicle average speed.
The latest developments in mobile computing technology have changed user preferences for computing. However, in spite of all the advancements in the recent years, Smart Mobile Devices (SMDs) are ...still low potential computing devices which are limited in memory capacity, CPU speed and battery power lifetime. Therefore, Mobile Cloud Computing (MCC) employs computational offloading for enabling computationally intensive mobile applications on SMDs. However, state-of-the-art computational offloading frameworks lack of considering the additional overhead of components migration at runtime. Therefore resources intensive and energy consuming distributed application execution platform is established. This paper proposes a novel distributed Energy Efficient Computational Offloading Framework (EECOF) for the processing of intensive mobile applications in MCC. The framework focuses on leveraging application processing services of cloud datacenters with minimal instances of computationally intensive component migration at runtime. As a result, the size of data transmission and energy consumption cost is reduced in computational offloading for MCC. We evaluate the proposed framework by benchmarking prototype application in the real MCC environment. Analysis of the results show that by employing EECOF the size of data transmission over the wireless network medium is reduced by 84 % and energy consumption cost is reduced by 69.9 % in offloading different components of the prototype application. Hence, EECOF provides an energy efficient application layer solution for computational offloading in MCC.
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