Effect of Pricing Methods and Public Paying Fee on Cleaning & Sanitation Service in Zanzibar: A Case of West B Municipality

The main objective of the study was to assess the effect of pricing methods and public paying fee on cleaning and sanitation services in West B Municipality, Zanzibar. The survey questionnaire was distributed to the business owner with sample size of 150 and data were collected and analysed based on both descriptive and inferential statistics through Pearson correlation using SPSS version 23.  The study results through descriptive the study shows that about 98 respondents which made 65.3% replied that there is no  impact brought by pricing methods and public paying fee on cleaning and sanitation services. Although the result from person correlation state that there is no significant positive relationship between pricing methods and public paying fee on Cleaning Service & sanitation services. The study recommends that the municipality should establish a specific model for pricing municipality services including cleaning and sanitation services. Keywords: Pricing Methods, Public Paying Fee and Cleaning and Sanitation Service DOI: 10.7176/EJBM/12-29-04 Publication date:October 31st 202

Predicting student performance using data mining and learning analysis technique in Libyan Higher Education

The Technology has an increasing impact on all areas of life, including the education sector, and requires developing countries to emulate developed countries and integrate technology into their education systems. Recently schools in Libya are facing an issue trying to figure out why students perform poorly in certain subjects and how can they know how they will perform next in the future in coming semesters in perspective subject. There are several methods proposed to predict the student’s performance, using data mining techniques. In this paper, there are plans to create Data Mining Techniques in Education (i.e., DME) prediction model clustering, classification and association rule mining in many universities and schools in order to provide students and teachers with the most advanced platform. Although relatively late, the Libyan government finally responded to this challenge by investing heavily in rebuilding the education system and launching a national plan to presented method in terms of predicting students’ performance based on their grades in Math and English. The results are divided in to three main sections clustering analysis using k-mean algorithm, classification analysis was done using two rounds first using Gain Ratio Evaluations to find out the top attributes that used by J84 algorithm in second round of classification, and rule association analysis using A priori algorithm. Rule association analysis is applied for the clusters generate by clustering analysis to generate the rules associated with each cluster. For each section, a list of inputs is presented with the scale used for the values followed by the results of the algorithm and explanation for the finding

Predictive Ability of Utilitarian Religiosity and Excessive Competition in Machiavellian Personality among Graduate Students at Yarmouk University

The study aimed at revealing Predictive Ability of Utilitarian Religiosity and Excessive Competition in Machiavellian Personality among Graduate Students at Yarmouk University. The sample of the study consisted of (366) male and female graduate students from Yarmouk University who were selected in the available method in the summer semester of the academic year 2020/2021. In order to achieve the objectives of the study three scales have been applied: the utilitarian religiosity scale (Al-Khalidi & Al- Dafaeii, 2017), the measure of excess competition (Ryckman, et al., 1990), and the Machiavellian Personality Scale (Dahling et al., 2009). The results of the study revealed a low level of utilitarian religiosity; the average total score was (1.75), and the results revealed a moderate level of excess competition, and the average total score of the scale was (2.67), and the results also revealed a medium degree of Machiavellian personality, and the average total score of the scale was (2.88). The results of the study indicated that the Machiavellian personality can be predicted through utilitarian religiosity and excessive competition; the utilitarian religiosity variable explained (16.9%) of the variance, while the excessive competition variable explained (6.3%) of the variance

Anticancer property of hexane extract of Suaeda fruticose plant leaves against different cancer cell lines

Purpose: To evaluate the bioactivity of hexane extract of S. fruticosa leaves against the cancer cell lines HepG2, MCF-7, and HCT-116, and to determine the chemical composition-function relationship. Methods: Using the liquid-liquid extraction method, the nonpolarL constituent compounds were isolated from the leaves. The cytotoxicity of the hexane extract was evaluated using an SRB assay. Mechanism of action was verified by observing the appearance of apoptotic bodies using fluorescence microscopy, while anti-proliferative activity was assayed via flow cytometry. Results: The results revealed that secondary metabolites in the hexane extract demonstrated the highest cytotoxicity, and thus anticancer activity, against HCT-116 cells, with an IC50 of 17.15 ± 0.78 mg/mL. The presence of apoptotic bodies indicate an ability to induce apoptosis. Flow cytometry results suggest that the secondary metabolites stalled the cell cycle at the G0/G1 phase. Conclusion: The results indicate that S. fruticosa hexane extract may be considered a potential new source of the anti-cancer compound, momilactone B. Keywords: Anticancer, Apoptosis, Colon Cancer, Liver cancer, Breast cancer, Liquid chromatography–mass spectrometry, Suaeda fruticose, Momilactone

The Effect of System Quality and User Quality of Information Technology on Internal Audit Effectiveness in Jordan, And the Moderating Effect of Management Support

The goal of this study is to ascertain the moderating role that management support has in internal audit effectiveness in Jordan, as well as the impact of system quality and user quality of information technology. There were 172 responders in all, and they were split across Jordanian auditors. In the data analysis process, the quantitative analysis test— which consists of the validity test, reliability test, test of conventional assumptions, and hypothesis test—is applied. Information technology system and user quality are independent variables in this study. The dependent variable in this study is internal audit effectiveness, and the moderating variable is management support. The results of this study show that the effectiveness of internal audits is significantly impacted by the system quality and user quality of information technology. Additionally, with Management support acting as a moderating factor, the link between System quality and Audit effectiveness improves. The findings also indicate that when moderating variables are present, the connection between User quality and Audit effectiveness changes from positive to negative. Future research might look at risk management

Fuzzy logic-based vehicle safety estimation using V2V communications and on-board embedded ROS-based architecture for safe traffic management system in hail city

Estimating the state of surrounding vehicles is crucial to either prevent or avoid collisions with other road users. However, due to insufficient historical data and the unpredictability of future driving tactics, estimating the safety status is a difficult undertaking. To address this problem, an intelligent and autonomous traffic management system based on V2V technology is proposed. The main contribution of this work is to design a new system that uses a real-time control system and a fuzzy logic algorithm to estimate safety. The robot operating system (ROS) is the foundation of the control architechture, which connects all the various system nodes and generates the decision in the form of a speech and graphical message. The safe path is determined by a safety evaluation system that combines sensor data with a fuzzy classifier. Moreover, the suitable information processed by each vehicle unit is shared in the group to avoid unexpected problems related to speed, sudden braking, unplanned deviation, street holes, road bumps, and any kind of street issues. The connection is provided through a network based on the ZigBee protocol. The results of vehicle tests show that the proposed method provides a more reliable estimate of safety as compared to other methods

Implementation of machine learning techniques with big data and IoT to create effective prediction models for health informatics

As a result of the availability of healthcare data in sheer size, big data analytics has to grow regularly in this industry to ensure new andeffective opportunities. This is helpful in providing early prevention, prediction, and detection of disease, thus helping in the enhancement ofthe overall life quality of the individuals. Likewise, in this paper, a machine learning-based big data analytics model is developed for predictingmulti-diseases to provide a better decision support system for various healthcare applications. This developed framework utilizes theMapReduce framework, where the map phase performs feature extraction and the reduce phase performs feature selection for the purpose ofhandling and processing big data. The required healthcare data is collected from external web sources. In the map phase, the statisticalfeatures and the Principal Component Analysis (PCA) features are extracted. In the reduction phase, the optimal features are selected with theaid of the developed Hybrid Flower Pollination Bumblebees Optimization Algorithm (HFPBOA). Then, the Ensemble Learning (EL) model isdeveloped to predict the multi-diseases. Moreover, the parameters present in the EL classifiers are optimized by using the same HFPBOA. Thefinal prediction output is obtained by averaging the weight function between the outputs of the NN, KNN, and fuzzy classifier. Thus, theoffered model attains 40.1%, 28.7%, 23.6%, and 10.5% improved than SSA-EL, DOA-EL, BOA-EL, and FA-EL respectively in terms of best value. Theeffectiveness computed for the developed multi-disease prediction framework is guaranteed by comparing the results among the recentlydeveloped prediction approaches

Operating Room Technician, Nurses, and Paramedic with the Support of Healthcare Administration in Management of Disasters

The literature offers significant insights into the various aspects of disaster preparedness among operating room nurses in the event of earthquake disasters. These findings can be utilized by nursing managers, paramedics, and operating room staff in order to develop effective strategies and provide support in areas such as improving knowledge and educational level, enhancing skills, strengthening plans and managerial structures, enhancing equipment preparedness, and explaining resilience strategies in order to improve the disaster preparedness of operating room nurses and the disaster response teams of medical organizations

Epidemiology of facial fractures: Incidence, prevalence and years lived with disability estimates from the Global Burden of Disease 2017 study

Background: The Global Burden of Disease Study (GBD) has historically produced estimates of causes of injury such as falls but not the resulting types of injuries that occur. The objective of this study was to estimate the global incidence, prevalence and years lived with disability (YLDs) due to facial fractures and to estimate the leading injurious causes of facial fracture. Methods: We obtained results from GBD 2017. First, the study estimated the incidence from each injury cause (eg, falls), and then the proportion of each cause that would result in facial fracture being the most disabling injury. Incidence, prevalence and YLDs of facial fractures are then calculated across causes. Results: Globally, in 2017, there were 7 538 663 (95% uncertainty interval 6 116 489 to 9 4

Global trends of hand and wrist trauma : a systematic analysis of fracture and digit amputation using the Global Burden of Disease 2017 Study

Background As global rates of mortality decrease, rates of non-fatal injury have increased, particularly in low Socio-demographic Index (SDI) nations. We hypothesised this global pattern of non-fatal injury would be demonstrated in regard to bony hand and wrist trauma over the 27-year study period. Methods The Global Burden of Diseases, Injuries, and Risk Factors Study 2017 was used to estimate prevalence, age-standardised incidence and years lived with disability for hand trauma in 195 countries from 1990 to 2017. Individual injuries included hand and wrist fractures, thumb amputations and non-thumb digit amputations. Results The global incidence of hand trauma has only modestly decreased since 1990. In 2017, the age-standardised incidence of hand and wrist fractures was 179 per 100 000 (95% uncertainty interval (UI) 146 to 217), whereas the less common injuries of thumb and non-thumb digit amputation were 24 (95% UI 17 to 34) and 56 (95% UI 43 to 74) per 100 000, respectively. Rates of injury vary greatly by region, and improvements have not been equally distributed. The highest burden of hand trauma is currently reported in high SDI countries. However, low-middle and middle SDI countries have increasing rates of hand trauma by as much at 25%. Conclusions Certain regions are noted to have high rates of hand trauma over the study period. Low-middle and middle SDI countries, however, have demonstrated increasing rates of fracture and amputation over the last 27 years. This trend is concerning as access to quality and subspecialised surgical hand care is often limiting in these resource-limited regions.Peer reviewe