The Effective Utilization of Knowledge Management in E-Government: A Case Study of E-Government in Jordan

The study is aimed at investigating the effective utilization of knowledge management in the Jordanian e-government system. The study proposes the knowledge management model for the implementation of egovernment in Jordan. The sample consisted of 132 employees derived from a population that had a sufficient knowledge of knowledge management in the Jordanian e-government team. The data collection tool used was a selfadministrated questionnaire. The study revealed the existence of a strong correlation between knowledge management and the utilization of knowledge. Furthermore, the study sample agreed that knowledge management is a widespread organizational practice. The study concluded that the utilization of knowledge is related to proper planning and follow-up of the applications for the knowledge management in Jordan e-government entities. In addition, the study recommended the spread of the culture of knowledge management which was supported by the senior management at the Jordanian entities

Arabic Text Categorization Using Support vector machine, Naïve Bayes and Neural Network

Text classification is a very important area ininformation retrieval. Text classificationtechniques used to classify documents into a setof predefined categories. There are severaltechniques and methods used to classify data andin fact there are many researches talks aboutEnglish text classification. Unfortunately, fewresearches talks about Arabic text classification.This paper talks about three well-knowntechniques used to classify data. These threewell-known techniques are applied on Arabicdata set. A comparative study is made betweenthese three techniques. Also this study used fixednumber of documents for all categories ofdocuments in training and testing phase. Theresult shows that the Support Vector machinegives the best results

Using Remote Sensing Data to Evaluate Habitat Loss in the Mobile, Galveston, and Tampa Bay Watersheds

The Gulf of Mexico has experienced dramatic wetland habitat area losses over the last two centuries. These losses not only damage species diversity, but contribute to water quality, flood control, and aspects of the Gulf coast economy. Overall wetland losses since the 1950s were examined using land cover/land use (LCLU) change analysis in three Gulf coast watershed regions: Mobile Bay, Galveston Bay, and Tampa Bay. Two primary causes of this loss, LCLU change and climate change, were then assessed using LCLU maps, U.S. census population data, and available current and historical climate data from NOAA. Sea level rise, precipitation, and temperature effects were addressed, with emphasis on analysis of the effects of sea level rise on salt marsh degradation. Ecological impacts of wetland loss, including fishery depletion, eutrophication, and hypoxia were addressed using existing literature and data available from NOAA. These ecological consequences in turn have had an affect on the Gulf coast economy, which was analyzed using fishery data and addressing public health impacts of changes in the environment caused by wetland habitat loss. While recent federal and state efforts to reduce wetland habitat loss have been relatively successful, this study implies a need for more aggressive action in the Gulf coast area, as the effects of wetland loss reach far beyond individual wetland systems themselves to the Gulf of Mexico as a whole

Improving the admission process in a higher education institute using Lean Six Sigma: A case study

Purpose The purpose of this study is to implement lean six sigma (LSS) methodology to improve the admission process in a higher education institute (HEI). Design/methodology/approach In this study, case study research methodology is adopted and implemented through an LSS define-measure-analyze-improve-control (DMAIC) framework. Findings The preliminary investigation showed that the completion of the whole admission process of a new student takes an average of 88 min, which is equivalent to a sigma level of about 0.71 based on the targeted admission cycle time of 60 min. The implementation of the proposed LSS approach increased the sigma level from 0.71 to 2.57, which indicates a reduction in the mean admission cycle time by around 55%. This substantial improvement is expected not only to provide an efficient admission process but also to enhance the satisfaction of students and employees and increase the reputation of the HEI to a significant level. Research limitations/implications In this study, the sample size used in the analysis is considered small. In addition, the effectiveness of the proposed approach is investigated using a discrete event simulation with a single-case study, which may limit generalization of the results. However, this study can provide useful guidance for further research for the generalization of the results to wider scopes in terms of different sectors of HEIs and geographical locations. Practical implications This study uses several statistical process control tools and techniques through a LSS DMAIC framework to identify and element the root causes of the long admission cycle time at a HEI. The approach followed, and the lessons learned, as documented in the study, can be of a great benefit in improving different sectors of HEIs. Originality/value This study is one of the few attempts to implement LSS in HEIs to improve the administrative process so that better-quality services can be provided to customers, such as students and guardians. The project is implemented by a group of undergraduate students as a part of their senior design project, which paves the way for involving students in future LSS projects in HEIs. This study is expected to help to improve understanding of how LSS methodology can be implemented in solving quality-related problems in HEIs and to offer valuable insights for both academics and practitioners.©2023 Emerald Publishing Limited. This manuscript version is made available under the Creative Commons Attribution–NonCommercial 4.0 International (CC BY–NC 4.0) license, https://creativecommons.org/licenses/by-nc/4.0/fi=vertaisarvioitu|en=peerReviewed

Fine particulate matter pollution and risk of community-acquired sepsis

While air pollution has been associated with health complications, its effect on sepsis risk is unknown. We examined the association between fine particulate matter (PM2.5) air pollution and risk of sepsis hospitalization. We analyzed data from the 30,239 community-dwelling adults in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) cohort linked with satellite-derived measures of PM2.5 data. We defined sepsis as a hospital admission for a serious infection with ≥2 systemic inflammatory response (SIRS) criteria. We performed incidence density sampling to match sepsis cases with 4 controls by age (±5 years), sex, and race. For each matched group we calculated mean daily PM2.5 exposures for short-term (30-day) and long-term (one-year) periods preceding the sepsis event. We used conditional logistic regression to evaluate the association between PM2.5 exposure and sepsis, adjusting for education, income, region, temperature, urbanicity, tobacco and alcohol use, and medical conditions. We matched 1386 sepsis cases with 5544 non-sepsis controls. Mean 30-day PM2.5 exposure levels (Cases 12.44 vs. Controls 12.34 µg/m3; p = 0.28) and mean one-year PM2.5 exposure levels (Cases 12.53 vs. Controls 12.50 µg/m3; p = 0.66) were similar between cases and controls. In adjusted models, there were no associations between 30-day PM2.5 exposure levels and sepsis (4th vs. 1st quartiles OR: 1.06, 95% CI: 0.85–1.32). Similarly, there were no associations between one-year PM2.5 exposure levels and sepsis risk (4th vs. 1st quartiles OR: 0.96, 95% CI: 0.78–1.18). In the REGARDS cohort, PM2.5 air pollution exposure was not associated with risk of sepsis

Enhancing the Productivity of a Roof-Type Solar Still Utilizing Alumina Nanoparticles and Vacuum Pump

Unlike conventional fresh water producing systems, from saline or brackish water, the innovative solar water producing systems are efficient and effective. Experiments were conducted on two identical roof-type solar stills and simultaneously tested under the same weather conditions. One of these stills was modified by integrating a vacuum pump to lower the pressure inside while the other still was used as a reference unit. Different concentrations of Al2O3 nanoparticles were chosen, 0.2%, 0.4%, and 0.6%, and used with water inside the modified still. It was verified that the modified still, without nanoparticles, yields 34.84% more production than the conventional still. In addition, the modified still with a 0.4% of Al2O3 nanoparticles produced the highest percentage of distilled water, 44.42% in comparison to the one without the use of Al2O3 nanoparticles, followed by 37.94% and 24.07% for 0.6% and 0.2% of Al2O3 nanoparticles, respectively

Global Urban Observation (I): International Collaboration Opportunities: NASA GEO Subtask SB-04

No abstract availabl

Dynamic congestion management system for cloud service broker

This is an open access article licenced under a CC-BY-SA license, https://creativecommons.org/licenses/by-sa/4.0/The cloud computing model offers a shared pool of resources and services with diverse models presented to the clients through the internet by an on-demand scalable and dynamic pay-per-use model. The developers have identified the need for an automated system (cloud service broker (CSB)) that can contribute to exploiting the cloud capability, enhancing its functionality, and improving its performance. This research presents a dynamic congestion management (DCM) system which can manage the massive amount of cloud requests while considering the required quality for the clients’ requirements as regulated by the service-level policy. In addition, this research introduces a forwarding policy that can be utilized to choose high-priority calls coming from the cloud service requesters and passes them by the broker to the suitable cloud resources. The policy has made use of one of the mechanisms that are used by Cisco to assist the administration of the congestion that might take place at the broker side. Furthermore, the DCM system is used to help in provisioning and monitoring the works of the cloud providers through the job operation. The proposed DCM system was implemented and evaluated by using the CloudSim tool.Peer reviewe