Title: Predicting At-Risk Students in Higher Education Institutions: A Model

Abstract:As the nation evolves into a new era, much emphasis has been channelled towards the field of education, in particular higher education institutions. This is in line with the efforts from the government to prepare university graduates to thrive in various sectors, and thus improve the development of the nation in terms of economic, business and technology. The progressive nature of this emphasis is restricted by the ever-present at-risk students in universities. There is a growing number of literatures related to at-risk students in higher education. However, there is a lack of any viable form of prediction of at-risk student identification. As such, a new model is substantially required to predict at-risk students at the earliest possible stage. This paper, hence, studies the related attributes of at-risk students to be deployed in profiling which is then implied in the development of the model. A validation criterion using machine learning algorithms is also discussed in the paper. The impact of the model is the contribution towards practice, knowledge and society.

Title: Optimization Methodology on Decision-Support under Impact from Reneging Patient of Hospital Outpatient Clinics

Abstract:Outpatient practice constitutes an integral part of medical care in hospital for patients who are not admitted into the hospital, but receive the preliminary care services and are discharged the same day. As hospital managements evaluate potential approaches to improve cost, quality, waiting times and throughput efficiencies in the hospital outpatient clinic (HOC), the deployment of cost-effective outpatient settings emerges to be the dominant issues. The research on the optimal deployment of medical resources appears to be a crucial issue of hospital steady-state management. In terms of patients flow and scarce medical resources, the queue-based methodology can be applied to approach the cost optimization and provide a trade-off study between average waiting times (AWT) and the cost issue for hospital management as well. To model the proposed approach for HOC qualitative profile, a generic outpatient clinic system is mapped into the M/M/R/K queue with reneging for application. On quantitative work, comprehensive mathematic analysis on cost and AWT pattern has been made in detail. Relevant simulations have also been conducted to validate the proposed optimization model. The design illustration is presented to demonstrate the application scenario in HOC platform. Hence the proposed approach indeed provides a feasibly cost-oriented decision support framework to adapt management requirement.

Title: A brief review on Echinococcosis and its public health importance

Abstract:Echinococcosis is a zoonotic parasitic disease caused by the larval stages of taeniid tapeworm of the genus Echinococcus . Four out of six species have been considered as a public health concern: Echinococcus granulosus (which causes cystic echinococcosis), Echinococcus multilocularis (which causes alveolar echinococcosis), and Echinococcus vogeli and Echinococcus oligarchs (which causes polycystic echinococcosis). Two new species have recently been identified: Echinococcus shiquicus in small mammals from the Tibetan plateau and Echinococcus felids in African lions, but their zoonotic transmission potential is equivocal. Several studies have shown that this disease is of increasing public health concern and that it can be regarded as emerging or re-emerging disease. The disease is found in many parts of the world specifically in the agricultural inclined regions in the northern part of Africa, the southern part of South America, Europe, Australia, and the Middle East and Southern West part of Asia (Eckert and Deplazes, 2004). This short review is intended to underscore the general aspect of the disease with particular reference to public health importance.


Abstract:The world pandemic as a global disaster of the early 21st century is bringing unexpected problems that have not been experienced ever before by the individual countries and their economies since the end of the World War II. In essence, there are two possibilities of solving the pandemic situation. The first solution is represented by medicine. The substantial solution, however, seems to have security and social formes. The managerial abilities of the Governments of the individual countries and a good level of health care can contribute to regulating and subsequent stopping the pandemic as well. However, this task can not be fulfilled without the fellowship of population, otherwise it could bring chaos and destroy the social values. Mitigating the consequences of the pandemic and removing them is greatly contributed by crisis management together with rescue units. Such a process necessitates the fellowship of population providing a place for medical and technological solutions supported by the developed ones of the crisis management. This paper is a result of solving an institutional project at the University of Security Management in Ko�ice and characterizes the position of the crisis management and rescue units in solving the pandemic in the Slovak Republic. In addition, this paper also compares starting points of the crisis management and measures taken by the selected countries. Identifies the activities of the position, tasks, activities of rescue services of the integrated rescue system of the Slovak Republic within the crisis management.

Title: Numerical Range of Generalized Aluthge Transformation

Abstract:Let $T=U|T|$ be the polar decomposition of an operator $T$. For $s,t\\geq0$ with $s+t=1$,\nthe $(s,t)$-Aluthge transform is defined by $\\Dst(T)=|T|^sU|T|^t$. In this paper, we shall\ndiscuss the numerical range of $\\Dst(T)$ and show that $w(\\Dst(T))\\leq w(T)$ and if $T$\nis an $n\\times n$ matrix, then $\\overline{W(\\Dst(T))}\\subset \\overline{W(T)}$. Moreover, among other things by applying the generalized Aluthge transform of operators, we establish some inequalities involving the numerical radius. Also, we establish some upper bounds for the numerical radius of $2\\times 2$ operator matrices.

Title: The Role of the Current Health Information System (HIS) Workflow Processes in mitigating Opioids Abuse in Saudi Arabia

Abstract:The incidence of opioid abuse is an alarming issue within the healthcare industry as it could cause death and could increase the healthcare cost. Monitoring of opioid intake is essential and interoperable data is highly required to reach the goal of monitoring opioid intake using the Health Information System (HIS). Therefore, this study aims to explore the current workflow of HIS to curb the incidence of opioid abused in Saudi Arabia and to determine healthcare practitioner�s perception towards the role of the current HIS in mitigating the opioid abuse issues. Methods: A Case Study Research was performed at Emergency Department, King Faisal Specialist Hospital and Research Centre (KFSHRC) and Al-Amal Mental Health Complex (AAMHC) from 1st March to 20th April 2018 whereby an observation on the Health Information System (HIS) workflow process was conducted and 37 healthcare practitioners were recruited to determine their perception on the current HIS through 5 Liker-scale questionnaire. Results: Opioid abuse issue is a prevalent issue in Saudi Arabia. Although the healthcare practitioners perceived the current HIS positively in curbing the opioid abuse or misuse issue but only within their organization, the absence of interoperability in the current HIS could be observed. Hence the ultimate role of HIS to curb the opioid abuse issue might not be reached. Conclusion: In order to use the HIS in curbing the issue of opioid abuse, the current workflow of HIS in Saudi Arabia needs to be improved and the function of real-time health information exchange needs to be developed.

Title: Encrypting Communication Transmission Messages by Utilizing Multi-Layer Perception Neural Network

Abstract:Encryptions can play essential role in securely communication transmissions. It can be used to raise the reliability and security of any communication system such as satellite communication and wireless Local Area Network (LAN). Security should satisfy and reassure the data transmission arrival to a specific destination. In this paper, a well-defined and powerful encryption technique is suggested, it can be exploited for securely communication transmissions. This technique utilizes An artificial neural network (ANN) of Multi-Layer Perceptron (MLP). It is used to efficiently encrypt text information into useful codes. Significant accuracies of 100% are investigated for data encryption and decryption as well.

Title: Spotting Fake and Genuine Reviews with Hybridization of Fuzzy and Neural Networks Techniques

Abstract:Sentiment Analysis/Opinion Mining integrates the discipline of Computer Science as well as Business Management. Sentiment Analysis on Fake and Genuine Reviews spotting is based on public emotional approaches. The main aim of this work is for helping customers to identify fake reviews on social media and websites for better decision on product purchases through online. Also it is helpful for sellers and manufacturers to notify fake and genuine reviews of their products. The most emerging techniques viz Fuzzy Logic, Neural Network, Hybrid of Fuzzy Logic, and Neural Network are used to splotch fake and genuine reviews. These techniques analyze social media comments which are then classified to fake and genuine reviews separately. These proposed technique’s performance are evaluated by evaluation metrics providing 96% of Accuracy Score and F1-Score. The higher percentage of evaluation metrics proves better classification of fake and genuine reviews.

Title: Combining Convolutional Neural Network with Recursive Neural Network for Robotic Financial Guidance

Abstract:In the proposed work is discussed the design and the development of a web app platform supporting the choice of financial announcements. The platform is based on digitized information extracted from a pdf file and on automatic text mining data processing. Models integrating Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM). are applied to implement a Decision Support System (DSS) based on Natural Language Processing (NLP), and to favor the choice of the announcement to follow, by guiding financial perspectives. The proposed DSS automatizes the choice process by enhancing announcement keywords, deadlines and requirements to participate to request for funds. The research is finalized to provide a dashboard suggesting automatically all the possibilities for a funding participation matching with company profiles. The paper introduces also an innovative approach based on a successive application of, CNN, LSTM-CNN, and of the combination of CNN + LSTM-CNN, thus furthermore improving text recognition performances. The combined CNN + LSTM-CNN approach provides the best Accuracy of about 95 %, and the best Loss of 0.006 for the specific case of study. The results are obtained within a framework of an industry project.

Title: Cubic intuitionistic commutative ideals of BCK-algebras

Abstract:The notion of cubic intuitionistic commutative ideals in BCK-algebras is introduced. The relationship between a cubic intuitionistic subalgebra, a cubic intuitionistic ideal and a cubic intuitionistic commutative ideal is discussed. Conditions for a cubic intuitionistic ideal to be a cubic intuitionistic commutative ideal are provided. Characterizations of a cubic intuitionistic commutative ideal are considered. The cubic intuitionistic extension property for a cubic intuitionistic commutative ideal is established. The homomorphic image and inverse image of cubic intuitionistic commutative ideals are studied and a few related properties are investigated. Also, the product of cubic intuitionistic commutative ideals of BCK-algebras are investigated.