Enhancement of QoS in voice-enabled networks using combination of MPLS and DiffServ

At its beginnings, the Internet Protocol was not meant for real-time applications such as voice and video. These conventional IP networks were limited to providing only best-effort QoS model which implies no QoS. Now voice traffic has been transmitted to IP-based networks instead of the conventional Public Switched Telephone Network (PSTN). Therefore, early adopters of this technology have noticed that for voice traffic to function as well as on conventional IP-based network as in PSTN, the transport techniques used by the IP-based network needed some additional policies and technique in place to accommodate the requirements of real-time data traffic. DiffServ is another QoS model used in IP networks, which differentiates IP traffic into classes each with certain priority. Implementing DiffServ, alone, can meet the SLA requirement in term of providing different QoS techniques based on the traffic type, but cannot ensure bandwidth, perapplication basis, so congested path may cause jitter, end to end delay or packet loss. MPLS was developed to combine the advantages of the connectionless layer 3 routing and the connection-oriented layer 2 forwarding, and provides per-hop data forwarding where it uses the label swapping rather than the layer 3 complex lookups in a routing table. Implementing MPLS, alone creates an end to end path with bandwidth reservations which guarantees the availability of resources to carry traffic of volume less than or equal to the reserved bandwidth, but MPLS is not aware of the DiffServ classes which considered as a disadvantage. This research project demonstrated the usefulness of combining DiffServ and MPLS in voice-enabled network to enhance voice quality by reducing end to end delay, jitter, and packet loss and proposed a method for analyzing voice applications’ requirements based in DiffServ-aware MPLS network

Factors determining intention to use mobile banking among clients within Yemeni banks / Ahmed Mohammed Mutahar Almadhwahi

A wide range of business opportunities are created via mobile technologies and services. Notwithstanding the availability of technologically advanced mobile devices, mobile banking services have not been widely accepted by banks’ clients. This study aims to examine the major factors that contribute towards clients’ intention to accept and use mobile banking as one of the e-financial services among Yemeni banks. Financial Institutions around the world are looking for the development and keep up to date with emerging technology to stay in the competition range. Banking is one of the sectors that are influenced by the mobile technological advancement. Many researchers have studied and proposed theories and models of technology usage and acceptance in order to predict and explain user behavior with technology considering the rapid change in both technologies and their environments. Based on Technology Acceptance Model (TAM), and integrating The Mental Accounting Theory (MAT), Hierarchy of Effects Model (HOE), Perceived Risk, this study developed and validated a multi-dimensional model, Mobile Banking Technology Model (MBTM), to better understand intention to use mobile banking service among clients within banks in Yemen. Questionnaire survey method was used to collect primary data from individuals who are non-user of mobile banking services in Yemeni banks. Four hundred and eighty-two valid responses were received. Structural Equation Modelling (SEM) via AMOS software was utilized to determine the importance levels of associations and interactions between the factors tested. This research proposed model developed with seven core constructs; perceived risk , perceived ease of use, perceived usefulness, self-efficacy, awareness as independent variables, intention as the dependent variable, perceived value as mediator variables

Towards a better understanding of the Organizational Characteristics that affect Acceptance of Big Data Platforms for Academic Teaching

In today's era of information, data has been growing at an exponential rate to become big data, and it needs platforms to allow users to govern, access, deliver, analyze, and use these huge databases. Academics in higher education need to utilize these platforms in teaching to enrich and empower the educational experience of their students of these institutions. The purpose of the current study is to investigate the impact of organizational characteristics on the acceptance of big data platforms for academic teaching among higher education institutes in Malaysia. 143 respondents participated to examine the effect of organizational characteristics (Management Drive, Bandwagon Pressure, and Training) on the acceptance of big data platforms for academic teaching. Besides, examining the moderating role of task technology fit. The results illustrate that management drive, bandwagon pressure has a significant impact on the acceptance, with an insignificant impact of training on the acceptance. However, task technology fit has not moderated any of the proposed relationships. This study would give insight for the higher education institutes managements to improve their academics acceptance of the big data platforms in teaching and therefore drive them to use the aforementioned platforms

Investigating and Enhancing Willingness to Communicate and Motivational Self-System of Yemeni Rural EFL Learners

A major problem in second language (L2) learning and teaching is learners’ low willingness to communicate (WTC). WTC refers to the extent to which an individual is ready to initiate communication with others. Some L2 researchers have argued that enhancing L2 WTC should be the fundamental goal of the L2 learning process. However, although previous studies have identified some factors that influence WTC, most, if not all, did not go beyond exploring the factors to promoting WTC through interventions. This thesis has two main aims: to understand the factors that influence the WTC of Yemeni rural secondary school English students and to promote their WTC based on understanding the factors that influence it. These two aims were achieved in a mixed methods project of four studies in which the factors influencing WTC were first identified in three studies, and then based on those factors, an intervention program to enhance students’ WTC was conducted in a fourth study. The first study used a large survey of 564 students. Quantitative data analysis indicated that L2 WTC inside the classroom was predicted by L1 WTC, ideal L2 self, L2 learning experience, L2 intended learning effort, and gender. Study two was an observational study of twelve students who had participated in study one. Data were collected through weekly classroom observations in L1 and L2 classrooms. Quantitative data analysis confirmed the significant relationship between L1 and L2 WTC found in study one and revealed significant gender difference in L2 observed WTC, with males demonstrating higher WTC. However, no significant relationship between self-reported WTC and observed WTC was found in both L1 and L2. The self, learning experience, and learning effort appeared to influence students’ observed WTC. Study three focused on students’ perceptions of their L2 WTC inside the classroom. It involved the same students from study two, but data were collected through interviews and weekly journals. Qualitative data analysis revealed three types of factors that influenced WTC: contextual, affective, and cognitive. The ideal self most influenced WTC through the mediation of topics related to students’ future careers. Study four was an intervention that promoted WTC and its four predictors–ideal self, learning experience, learning effort, and linguistic self-confidence–over a six-week period. Two-hundred six students were assigned to either an experimental group (N= 104) or a control group (N = 102). The experimental group received one forty-five minute visualization and goal-setting lesson a week, whereas the control group received a regular lesson. Quantitative and qualitative data analysis indicated that the intervention enhanced WTC and its predictors. The thesis concludes with three contributions. Theoretically, it shows that WTC can be influenced by the ideal self, learning experience, intended learning effort, and gender. Methodologically, it shows that mixed methods research leads to a deeper understanding of WTC and how to promote it. Pedagogically, the intervention practically shows English teachers how visualization and goal-setting activities can enhance students’ WTC and its predictors

Investigating and Enhancing Willingness to Communicate and Motivational Self-System of Yemeni Rural EFL Learners

A major problem in second language (L2) learning and teaching is learners’ low willingness to communicate (WTC). WTC refers to the extent to which an individual is ready to initiate communication with others. Some L2 researchers have argued that enhancing L2 WTC should be the fundamental goal of the L2 learning process. However, although previous studies have identified some factors that influence WTC, most, if not all, did not go beyond exploring the factors to promoting WTC through interventions. This thesis has two main aims: to understand the factors that influence the WTC of Yemeni rural secondary school English students and to promote their WTC based on understanding the factors that influence it. These two aims were achieved in a mixed methods project of four studies in which the factors influencing WTC were first identified in three studies, and then based on those factors, an intervention program to enhance students’ WTC was conducted in a fourth study. The first study used a large survey of 564 students. Quantitative data analysis indicated that L2 WTC inside the classroom was predicted by L1 WTC, ideal L2 self, L2 learning experience, L2 intended learning effort, and gender. Study two was an observational study of twelve students who had participated in study one. Data were collected through weekly classroom observations in L1 and L2 classrooms. Quantitative data analysis confirmed the significant relationship between L1 and L2 WTC found in study one and revealed significant gender difference in L2 observed WTC, with males demonstrating higher WTC. However, no significant relationship between self-reported WTC and observed WTC was found in both L1 and L2. The self, learning experience, and learning effort appeared to influence students’ observed WTC. Study three focused on students’ perceptions of their L2 WTC inside the classroom. It involved the same students from study two, but data were collected through interviews and weekly journals. Qualitative data analysis revealed three types of factors that influenced WTC: contextual, affective, and cognitive. The ideal self most influenced WTC through the mediation of topics related to students’ future careers. Study four was an intervention that promoted WTC and its four predictors–ideal self, learning experience, learning effort, and linguistic self-confidence–over a six-week period. Two-hundred six students were assigned to either an experimental group (N= 104) or a control group (N = 102). The experimental group received one forty-five minute visualization and goal-setting lesson a week, whereas the control group received a regular lesson. Quantitative and qualitative data analysis indicated that the intervention enhanced WTC and its predictors. The thesis concludes with three contributions. Theoretically, it shows that WTC can be influenced by the ideal self, learning experience, intended learning effort, and gender. Methodologically, it shows that mixed methods research leads to a deeper understanding of WTC and how to promote it. Pedagogically, the intervention practically shows English teachers how visualization and goal-setting activities can enhance students’ WTC and its predictors

The Mediating Role of Trust in the Relationship Between Corporate Image, Security, Word of Mouth and Loyalty in M-Banking Using among the Millennial Generation in Indonesia

Millennials have a lifestyle that is different from previous generations. Millennial Generation lives and grows together with rapid technological growth and currently dominates the population in Indonesia. The purpose of this study is to empirically determine the factors that influence the millennial generation’s loyalty to mobile banking applications. Elements used to analyze the millennial generation’s loyalty are corporate image, application security, word of mouth (WoM), and trust. Data collected through questionnaires from a sample of 395mobile banking users in Indonesia. The study uses structural equation modeling (SEM) to test the hypotheses with Amos 24 as the analysis tool. The results of the study proved that all predictions are proven significant. The trust in mobile banking mediates the effects of corporate image, application security, and word of mouth on millennial’s loyalty. The respondent of the research was millennial mobile banking users in Indonesia. Therefore, the model should be replicated among other mobile banking users in other countries. Banks have to maintain an excellent corporate image and get a positive transmission because, in this digitalization era, information can spread very quickly between friends, relatives, family, or through the internet, digital media, and social media. Banking also needs to include a guaranteed level of application security in the mobile banking application provided to gain the trust of users and be able to foster and increase their loyalty. However, there are still other factors that can influence millennial’s loyalty to a mobile banking application

Optimized ANFIS Model Using Aquila Optimizer for Oil Production Forecasting

Oil production forecasting is one of the essential processes for organizations and governments to make necessary economic plans. This paper proposes a novel hybrid intelligence time series model to forecast oil production from two different oil fields in China and Yemen. This model is a modified ANFIS (Adaptive Neuro-Fuzzy Inference System), which is developed by applying a new optimization algorithm called the Aquila Optimizer (AO). The AO is a recently proposed optimization algorithm that was inspired by the behavior of Aquila in nature. The developed model, called AO-ANFIS, was evaluated using real-world datasets provided by local partners. In addition, extensive comparisons to the traditional ANFIS model and several modified ANFIS models using different optimization algorithms. Numeric results and statistics have confirmed the superiority of the AO-ANFIS over traditional ANFIS and several modified models. Additionally, the results reveal that AO is significantly improved ANFIS prediction accuracy. Thus, AO-ANFIS can be considered as an efficient time series tool

Evaluating the Applications of Dendritic Neuron Model with Metaheuristic Optimization Algorithms for Crude-Oil-Production Forecasting

The forecasting and prediction of crude oil are necessary in enabling governments to compile their economic plans. Artificial neural networks (ANN) have been widely used in different forecasting and prediction applications, including in the oil industry. The dendritic neural regression (DNR) model is an ANNs that has showed promising performance in time-series prediction. The DNR has the capability to deal with the nonlinear characteristics of historical data for time-series forecasting applications. However, it faces certain limitations in training and configuring its parameters. To this end, we utilized the power of metaheuristic optimization algorithms to boost the training process and optimize its parameters. A comprehensive evaluation is presented in this study with six MH optimization algorithms used for this purpose: whale optimization algorithm (WOA), particle swarm optimization algorithm (PSO), genetic algorithm (GA), sine–cosine algorithm (SCA), differential evolution (DE), and harmony search algorithm (HS). We used oil-production datasets for historical records of crude oil production from seven real-world oilfields (from Tahe oilfields, in China), provided by a local partner. Extensive evaluation experiments were carried out using several performance measures to study the validity of the DNR with MH optimization methods in time-series applications. The findings of this study have confirmed the applicability of MH with DNR. The applications of MH methods improved the performance of the original DNR. We also concluded that the PSO and WOA achieved the best performance compared with other methods

PATTERN OF LIVER DISEASE ADMISSIONS AT A TERTIARY GOVERNMENT HOSPITAL IN SANA’A, YEMEN

Back ground and objectives:  Liver disease causes major public health problems international, especially in poor countries, and it is associated with poor long-term clinical outcomes and results in the deaths of millions worldwide annually. The aim of this study is to ascertain the virtual frequencies of liver disease and to assess etiological factors among patients admitted to Al-Thawra tertiary Hospital in Sana'a City, Yemen. Methods:  This was a descriptive retrospective analysis study of gastrointestinal patients admitted from January 1, 2021 to December 31, 2021 to the medical wards of Al-Thawra Hospital. This is a tertiary hospital located in the Yemeni capital, Sana'a City. Data were extracted from patient case folders for the period of under review. Data validated with Microsoft Excel version 13 and exported to SPSS version 23.0 for windows; for statistical analysis. Data were evaluated for demographic and other clinical characteristics as definite variables. Results: Of the 516 gastroenterology patients admitted to the gastroenterology service in medical wards during a one-year period, liver disease accounted for 30% of all gastroenterology in the same period. There were 155 patients diagnosed with liver disease. There were 86 (55.5%) males and 69 (44.5%) females, with a male to female ratio of 1.2:1. The mean overall age of patients and the age range were 46.14±16.5 and 8-85 years, respectively. The peak incidence of age occurred during the fifth and sixth decades of life at 38.1%. The most common liver disease was; autoimmune hepatitis 43 (27.7%), followed by nonalcoholic fatty liver disease 35 (22.6%), viral hepatitis 32 (20.6%) and schistosomiasis 10 (6.5%). Conclusion:  Current findings show that autoimmune hepatitis was the most common cause among gastrointestinal diseases in Sana'a city, Yemen; the male to female ratio was roughly the same. In light of this, health education and public awareness about hepatitis virus screening tests and schistosomiasis screening and treatment is the primary preventive strategy to be considered.                        Peer Review History: Received: 4 July 2022; Revised: 12 August; Accepted: 7 September, Available online: 15 September 2022 Academic Editor: Dr. Gehan Fawzy Abdel Raoof Kandeel, Pharmacognosy Department, National Research Centre, Dokki, 12622,  Giza, Egypt, [email protected]  Received file:                             Reviewer's Comments: Average Peer review marks at initial stage: 6.0/10 Average Peer review marks at publication stage: 7.5/10 Reviewers: Dr. Bilge Ahsen KARA, Ankara Gazi Mustafa Kemal Hospital, Turkey, [email protected] Dr. Tamer Elhabibi, Suez Canal University, Egypt, [email protected] Dr. Rima Benatoui,Laboratory of Applied Neuroendocrinology, Department of Biology, Faculty of Science, Badji Mokhtar University Annaba, Algeria.  [email protected] Dr. A.A. Mgbahurike, University of Port Harcourt, Nigeria, [email protected] Similar Articles:   PREVALENCE OF HEPATITIS G VIRUS AMONG PATIENTS WITH CHRONIC LIVER DISEASE AND HEALTHY INDIVIDUALS, SANA'A CITY-YEME