An-Najah National University

About: An-Najah National University is a education organization based out in Nablus, Palestinian Territory. It is known for research contribution in the topics: Population & Adsorption. The organization has 1857 authors who have published 2607 publications receiving 68226 citations. The organization is also known as: An Najah National University.

Indoor guided evacuation: TIN for graph generation and crowd evacuation

Abstract: This paper presents two complementary methods: an approach to compute a network data-set for indoor space of a building by using its two-dimensional (2D) floor plans and limited semantic information, combined with an optimal crowd evacuation method. The approach includes three steps: (1) generate critical points in the space, (2) connect neighbour points to build up the network, and then (3) run the optimal algorithm for optimal crowd evacuation from a room to the exit gates of the building.Triangulated Irregular Network (TIN) is used in the first two steps.The optimal evacuation crowd is not based on the nearest evacuation gate for a person but relies on optimal sorting of the waiting lists at each gate of the room to be evacuated. As an example case, a rectangular room with 52 persons with two gates is evacuated in 102 elementary interval times (one interval corresponds to the time for one step for normal velocity walking), whereas it would have been evacuated in not less than 167 elementary ste...

Bibliometric analysis of literature in AIDS-related stigma and discrimination.

Abstract: Stigma and discrimination are major barriers in the global fight against human immunodeficiency virus (HIV) and acquired immunodeficiency syndrome (AIDS). The aim of this study was to create an analytical inventory of worldwide research output in AIDS-related stigma and discrimination. SciVerse Scopus was used for the study period from 1980 to 2017 to retrieve literature in AIDS-related stigma and discrimination. Results were presented as bibliometric tables and maps. In total, 2,509 documents were retrieved. Approximately 40% (n = 990) of the retrieved documents were published in the last 5 years (2013-2017). Retrieved documents received an average of 19.8 citations per article and had an average of 3.2 authors per article. The Hirsh index of the retrieved documents was 94. Most frequently encountered topics were mental health, adherence, adolescents, women, disclosure, and Africa. The USA contributed to 1,226 (48.9%) documents while the African region contributed to 531 (21.2%) documents. Research collaboration among most active countries was relatively low. Authors and institutions from the USA dominated this field. AIDS Care was the most active journal in publishing documents in this field with 307 (13.4%) documents while documents published in Social Medicine journal received the highest citations. Research in AIDS-related stigma and discrimination had witnessed a noticeable increase in the past decade, but the overall number of publications is considered insignificant relative to the size of the problem and the global number of infected people. There was a relative underpresentation of literature from African region despite the fact that more than two-thirds of HIV-infected people in the world are living in Africa.

Use of a relevance vector machine for groundwater quality monitoring network design under uncertainty

Abstract: This paper presents a methodology for groundwater quality monitoring network design. This design takes into account uncertainties in aquifer properties, pollution transport processes, and climate. The methodology utilizes a statistical learning algorithm called relevance vector machines (RVM), which is a sparse Bayesian framework that can be used for obtaining solutions to regression and classification tasks. Application of the methodology is illustrated using the Eocene Aquifer in the northern part of the West Bank, Palestine. The procedure presented in this paper utilizes a Monte Carlo (MC) simulation process to capture the uncertainties in recharge, hydraulic conductivity, and nitrate reaction processes through the application of a groundwater flow model and a nitrate fate and transport model. This MC modeling approach provides several thousand realizations of nitrate distribution in the aquifer. Subsets of these realizations are then used to design the monitoring network. This is done by building a best-fit model of nitrate concentration distribution everywhere in the aquifer for each Monte Carlo subset using RVM. The outputs from the RVM model are the distribution of nitrate concentration everywhere in the aquifer, the uncertainty in the characterization of those concentrations, and the number and locations of “relevance vectors” (RVs). The RVs form the basis of the optimal characterization of nitrate throughout the aquifer and represent the optimal locations of monitoring wells. In this paper, the number of monitoring wells and their locations where chosen based on the performance of the RVM model runs. The results from 100 model runs show the consistency of the model in selecting the number and locations of RV‘s. After implementing the design, the data collected from the monitoring sites can be used to estimate nitrate concentration distribution throughout the entire aquifer and to quantify the uncertainty in those estimates.