The Art of Existence and the Regimes of IS-enabled Customer Service Rationalization: A Study of IT Service Management in the UK Higher Education

This paper adopted a critical perspective to examine IS-enabled IT customer services rationalization project in a UK University context. Informed by Foucaultian framework of rationality/power and ethics the paper seeks to demonstrate how individuals deploy their critical moral reflection to enact ‘the care of the self’ in living with the consequences of IS-enabled services process change. The study draws on two years of field work to argue for the multiplicity of individual’s moral judgment under rationalization regimes of truth. Individuals deploy a self reflective rationality to judge the impact of the project on their work and life experience and act accordingly. This paper contributes to IS research by drawing attention to IT service management as an area for academic research as well as to Foucault’s notion of ‘ethics’ which provides a fresh view for understanding the consequences of the development and implementation of IS solutions

Mobile Cloud Computing and Its Effectiveness in Business Organizations

E-commerce business organizations aim at achieving the goals and the mission effectively and efficiently so as to satisfy the diverse interests of the stakeholders. MCC is an ICT concept that enables the organizations to enhance the performance when serving the important stakeholders, who include customers, staff, managers, shareholders, and industry regulators. MCC involves the integration of the mobile devices to enable the sharing of the cloud infrastructure. The integration is done via a network and between the computer devices that operate remotely. The Internet is the most common network that enables the mobile devices to utilize the data and information stored in a cloud database. E-commerce businesses prefer the cloud infrastructure because it has a large data storage capacity and high processing speeds. Also, the cloud service providers invest substantial financial, human, and technological resources in ensuring the security of the effective management of the data resources. The main benefit of MCC is that it reduces the businesses expenses. For example, it enables the companies to offer products and services in the international market via the e-commerce infrastructure. Amazon.com is an example of a Multinational Corporation that is successful in offering high-quality services and products to customers in different countries using the website and the mobile app applications that are supported by the cloud infrastructure. Keywords: mobile cloud computing, cloud computing, E-commerce. DOI: 10.7176/IKM/9-1-0

The Use of Information Systems to Improve Academic Supervision in Colleges

A supervisory service known as academic advice aims to familiarize the student with the university and its scientific departments, the domains in which graduates work, the facets of care, and the services the university offers to its students. The academic advising service assists students in adjusting to the university environment and taking advantage of the opportunities available to them by equipping them with fundamental knowledge and skills that raise their educational attainment. Academic advising is an important link in guiding students to achieve the best performance during the teaching and learning processes, to obtain the best educational outcomes and the best possible academic achievement. Exam anxiety, academic pressures, low achievement, a lack of study time, weak motivation to learn, low self-concept, social and economic pressures, and other issues are common during the university stage and prevent students from adjusting to the university environment. As a result, it becomes urgently necessary to have an advanced academic advising system to address all of these issues and ensure its capacity to achieve psychological harmony. By considering the factors of the student's academic level and university specialty, this study seeks to shed light on the reality of the Faculty of Management Academic Guidance Unit from the perspectives of students and faculty members. The statistical analysis results from the use of various statistical approaches demonstrate that students are generally satisfied with the many dimensions of the questionnaire on the caliber of academic extension services offered by the institution

Applying the big bang-big crunch metaheuristic to large-sized operational problems

In this study, we present an investigation of comparing the capability of a big bang-big crunch metaheuristic (BBBC) for managing operational problems including combinatorial optimization problems. The BBBC is a product of the evolution theory of the universe in physics and astronomy. Two main phases of BBBC are the big bang and the big crunch. The big bang phase involves the creation of a population of random initial solutions, while in the big crunch phase these solutions are shrunk into one elite solution exhibited by a mass center. This study looks into the BBBC’s effectiveness in assignment and scheduling problems. Where it was enhanced by incorporating an elite pool of diverse and high quality solutions; a simple descent heuristic as a local search method; implicit recombination; Euclidean distance; dynamic population size; and elitism strategies. Those strategies provide a balanced search of diverse and good quality population. The investigation is conducted by comparing the proposed BBBC with similar metaheuristics. The BBBC is tested on three different classes of combinatorial optimization problems; namely, quadratic assignment, bin packing, and job shop scheduling problems. Where the incorporated strategies have a greater impact on the BBBC's performance. Experiments showed that the BBBC maintains a good balance between diversity and quality which produces high-quality solutions, and outperforms other identical metaheuristics (e.g. swarm intelligence and evolutionary algorithms) reported in the literature

Susceptible exposed infectious recovered-machine learning for COVID-19 prediction in Saudi Arabia

Susceptible exposed infectious recovered (SEIR) is among the epidemiological models used in forecasting the spread of disease in large populations. SEIR is a fitting model for coronavirus disease (COVID-19) spread prediction. Somehow, in its original form, SEIR could not measure the impact of lockdowns. So, in the SEIR equations system utilized in this study, a variable was included to evaluate the impact of varying levels of social distance on the transmission of COVID-19. Additionally, we applied artificial intelligence utilizing the deep neural network machine learning (ML) technique. On the initial spread data for Saudi Arabia that were available up to June 25th, 2021, this improved SEIR model was used. The study shows possible infection to around 3.1 million persons without lockdown in Saudi Arabia at the peak of spread, which lasts for about 3 months beginning from the lockdown date (March 21st). On the other hand, the Kingdom's current partial lockdown policy was estimated to cut the estimated number of infections to 0.5 million over nine months. The data shows that stricter lockdowns may successfully flatten the COVID-19 graph curve in Saudi Arabia. We successfully predicted the COVID-19 epidemic's peaks and sizes using our modified deep neural network (DNN) and SEIR model

Robust features extraction for general fish classification

Image recognition process could be plagued by many problems including noise, overlap, distortion, errors in the outcomes of segmentation, and impediment of objects within the image. Based on feature selection and combination theory between major extracted features, this study attempts to establish a system that could recognize fish object within the image utilizing texture, anchor points, and statistical measurements. Then, a generic fish classification is executed with the application of an innovative classification evaluation through a meta-heuristic algorithm known as Memetic Algorithm (Genetic Algorithm with Simulated Annealing) with back-propagation algorithm (MA-B Classifier). Here, images of dangerous and non-dangerous fish are recognized. Images of dangerous fish are further recognized as Predatory or Poison fish family, whereas families of non-dangerous fish are classified into garden and food family.  A total of 24 fish families were used in testing the proposed prototype, whereby each family encompasses different number of species. The process of classification was successfully undertaken by the proposed prototype, whereby 400 distinct fish images were used in the experimental tests. Of these fish images, 250 were used for training phase while 150 were used for testing phase. The back-propagation algorithm and the proposed MA-B Classifier produced a general accuracy recognition rate of 82.25 and 90% respectively

Human actinomycetoma caused by Actinomadura mexicana in Sudan: the first report

Mycetoma is a localized, chronic, granulomatous disease that can be caused by fungi (eumycetoma) or bacteria (actinomycetoma). Of the 70 different causative agents implicated in mycetoma worldwide, Actinomadura madurae is the only one that causes multiple cases on all continents. Recently, new Actinomadura species were described as causative agents of human mycetoma. One of these new causative agents was Actinomadura mexicana, which was identified in Latin America. Here we demonstrate that this causative agent is not confined to Latin America and that it is also a causative agent of actinomycetoma in Sudan. The disease was managed by antibiotic treatment alone and resulted in complete cure after 6 months of treatment, which is quick when compared with actinomycetoma cases caused by other Actinomadura species

Digitalization of learning in Saudi Arabia during the COVID-19 outbreak: A survey

Following the outbreak of the novel coronavirus (COVID-19) in China in late December 2019, more than 217 countries became almost immediately infected in the resulting pandemic. Consequently, many of them decided to close their educational institutions as a way of preventing the spread of this virus. For many of them, though, the closure made them unable to deliver learning materials to students owing to their inability to provide the right technology for the purpose. To assist with the digitalizing of learning during this time, this study reviews the most common technologies used in the delivery of learning materials, with the experience of most infected countries being considered. Major challenges in online learning are discussed in this study as well. Further, Saudi Arabia was considered as a case study for the effectiveness of distance learning during the 2020 spring semester, where 300 undergraduate students were surveyed on their opinions of distance learning. The responses to the survey indicated that distance learning was effective in providing the required knowledge to the students during the outbreak of COVID-19. The findings showed that although the lack of interaction and poor internet connections were factors affecting comfortable and successful learning of physics and mathematics, 63% of students were satisfied with learning management systems, 75% of students found it easy to understand course materials, and 67% of students found it easy to understand assignments and could deal with them comfortably. The study findings can encourage educational institutions to digitalize their learning materials in the future

The educational value of ward rounds as a learning and teaching opportunity for house officers, medical officers, and registrars in Sudanese hospitals: a multi-center cross-sectional study

Abstract Background Ward rounds are a cornerstone in the educational experience of junior doctors and an essential part of teaching patient care. Here, we aimed to assess the doctors’ perception of ward rounds as an educational opportunity and to identify the obstacles faced in conducting a proper ward round in Sudanese hospitals. Method A cross-sectional study was conducted from the 15th to the 30th of January 2022 among house officers, medical officers, and registrars in about 50 teaching and referral hospitals in Sudan. House officers and medical officers were considered the learners, while specialist registrars were considered the teachers. Doctors’ perceptions were assessed using an online questionnaire, with a 5-level Likert scale to answer questions. Results A total of 2,011 doctors participated in this study (882 house officers, 697 medical officers, and 432 registrars). The participants were aged 26.9 ± 3.2 years, and females constituted about 60% of the sample. An average of 3.1 ± 6.8 ward rounds were conducted per week in our hospitals, with 11.1 ± 20.3 h spent on ward rounds per week. Most doctors agreed that ward rounds are suitable for teaching patient management (91.3%) and diagnostic investigations (89.1%). Almost all the doctors agreed that being interested in teaching (95.1%) and communicating appropriately with the patients (94.7%) make a good teacher in ward rounds. Furthermore, nearly all the doctors agreed that being interested in learning (94.3%) and communicating appropriately with the teacher (94.5%) make a good student on ward rounds. About 92.8% of the doctors stated that the quality of ward rounds could be improved. The most frequently reported obstacles faced during ward rounds were the noise (70%) and lack of privacy (77%) in the ward environment. Conclusion Ward rounds have a special value in teaching patient diagnosis and management. Being interested in teaching/learning and having good communication skills were the two major criteria that make a good teacher/learner. Unfortunately, ward rounds are faced with obstacles related to the ward environment. It is mandatory to ensure the quality of both ward rounds' teaching and environment to optimize the educational value and subsequently improve patient care practice