743 research outputs found
Root-cause analysis of RSAF Maintenance-related Flight Safety Mishaps
Poor maintenance is a major factor in many aviation mishaps. This is due to the fact that some maintenance activities are carried out improperly or overlooked as a result of human error. It is important to acknowledge that maintenance mistakes are a visible sign of deeper organizational issues. Therefore, adequate solutions to maintenance issues must consider organizational influences. Despite efforts to reduce the accident rate within the Royal Saudi Air Force (RSAF), the RSAF suffers from an increasing trend in mishaps attributed to maintenance. Therefore, safety data was analyzed to examine trends. Additionally, the Human Factors Analysis and Classification System (HFACS) was used to investigate accident reports in an attempt to discover the root causes of the accidents. HFACS was applied to 16 maintenance-related accidents to capture the nature of and connections among latent conditions and active failures, as well as uncover the underlying causes to the accidents. Twelve-hour shifts, fatigue, shift handover documentation & record-keeping, and management response to maintenance issues were among the underlying causes discovered in this research
Towards semantic-aware and ontology-based e-Government service integration - an applicative case study of Saudi Arabia's King Abdullah Scholarship program
By improving the quality of e-government services by enabling access to services across different government agencies through one portal, services integration plays a key role in e-government development. This paper proposes a conceptual framework of ontology based e-government service integration, using Saudi Arabia's King Abdullah Scholarship Program (SAKASP) as a case study. SAKASP is a multi-domain program in which students must collect information from various Ministries to complete applications and the administering authority must verify the information supplied by the Ministries. The current implementation of SAKASP is clumsy because it is a mixture of online submission and manual collection and verification of information; its time-consuming and tedious procedures are inconvenient for the applicants and inefficient for the administrators. The proposed framework provides an integrated service by employing semantic web service (SWS) and ontology, improving the current implementation of SAKASP by automatically collecting and processing the related information for a given application. The article includes a typical scenario that demonstrates the workflow of the framework. This framework is applicable to other multi-domain e-government services. © Springer-Verlag Berlin Heidelberg 2010
Knowledge-based life event model for e-government service integration with illustrative examples
The advancement of information and communications technology and web services offers an opportunity for e-government service integration, which can help improve the availability and quality of services offered. However, few of the potential service integration applications have been adopted by governments to increase the accessibility of and satisfaction with government services and information for citizens. Recently, the 'life event' concept was introduced as the core element of integrating complexity of service delivery to improve the efficiency and reusability of e-government services, web-based information management systems. In addition, a semantic web-based ontology is considered to be the most powerful conceptual approach for dealing with challenges associated with developing seamless systems in distributed environments. Among these challenges are interoperability, which can be loosely defined as the technical capability for interoperation. Despite the conceptual emergence of semantic web-based ontology for life events, the question remains of what methodology to use when designing a semantic web-based ontology for life events. This paper proposes a semantic web-based ontology model for life events for e-government service integration created using a methodology that implements the model using the ontology modelling tool Protégé and evaluates the model using Pellet Reasoner and the SPARQL query language. In addition, this model is illustrated by two examples, the Saudi Arabia King Abdullah Scholarship and Hafiz, to show the advantages of integrated systems compared with standalone systems. These examples show that the new model can effectively support the integration of standalone e-government services automatically so that citizens do not need to manually execute individual services. This can significantly improve the accessibility of e-government services and citizen's satisfaction. © 2014-IOS Press
Highly sensitive alkane odour sensors based on functionalised gold nanoparticles
We deposit dense, ordered, thin films of Au-dodecanethiol core/shell nanoparticles by the Langmuir-Schafer (LS) printing method, and find that their resistance at ambient temperature responds selectively and sensitively to alkane odours. Response is a rapid resistance increase due to swelling, and is strongest for alkane odours where the alkane chain is similar in length to the dodecane shell. For decane odours, we find a response to concentrations as low as 15 ppm, about 600 times below the lower explosive limit. Response is weaker, but still significant, to aromatic odours (e.g. Toluene, Xylene), while potential interferants such as polar and/or hydrogen-bonding odours (e.g. alcohols, ketones, water vapour) are somewhat rejected. Resistance is weakly dependent on temperature, and recovers rapidly and completely to its original value within the error margin of measurement. (C) 2011 Elsevier B.V. All rights reserved
Oral health status and treatment needs of children with sickle cell disease in Abha and Khamis Mushait cities of southern Saudi Arabia
Background: This study aimed to assess the oral health status and dental treatment needs of children with Sickle Cell disease (SCD) in Abha and Khamis Mushait cities of southern Saudi Arabia.Methods: A total of 82 children were included in the study, 41 children with SCD and 41 control group. A total of 82 children having age group of 2 to 13 years from Abha and Khamis Mushait cities of southern Saudi Arabia were examined. The clinical examinations were performed by experienced clinicians in those children who fulfilled the required inclusion criteria. Intraoral examination was done using Decayed-Missing-Filled Teeth Index (DMFT Index) and other dental conditions were examined. Statistical analysis was done with Chi square test and level of significance was set at p<0.05.Results: Prevalence of dental caries was shown between the 2 groups of children i.e., SCD and control. When SCD was compared with control group, the Mean ±Standard deviation for decayed missing filled tooth was found to be DMFT= 6.95±4.79, 8.02±4.33 respectively. Statistically no significant difference was found (P=0.290). 17.1% of children with SCD group has gingivitis compared to control group which is 7.3%. Statistically no significant difference was found (P=0.177). Dental trauma, deleterious oral habits and tooth brushing amount SCD children were shown no statistically significant compared to control group.Conclusions: In the present study no significant difference was evident in dental diseases and treatment needs among SCD and Control group
Characterisation of M2 muscarinic acetylcholine receptor signalling in dental pulp stem cells
Cholinergic signalling is hypothesised to occur in stem cells, and there is evidence that mesenchymal stem cells (MSCs) express a functional cholinergic system. Expression of functional acetylcholine receptors (AChRs) have been reported in several types of MSC, which suggests that MSCs have non-neuronal cholinoceptive properties that may play a role in their regenerative potential. However, this remains relatively unexplored, particularly, in Dental pulp stem cells (DPSCs). This project commenced by reviewing AChRs in MSCs, highlighting DPSCs characteristics, and then investigated the presence of functional AChRs and their role in modulating DPSCs regenerative potential.
This study commenced by identifying gene expression of both classes of AChRs, the muscarinic (mAChRs) and the nicotinic (nAChRs), in DPSCs. Protein expression of detected AChRs was assessed via western blotting and immunofluorescence. Functionality of expressed AChRs was assessed using an array of AChRs agonists and antagonists and DPSCs viable count was measured via MTT assay. Subtype selective agonist was used to study the role of the targeted AChR and its influence on DPSCs regenerative potential. Proliferation of DPSCs in response to that stimulation was assessed via measuring viable cell count using MTT assay, Cell Counting Kit-8 (CCK-8), and cell cycle analysis. Survival of DPSCs was assessed via detecting proliferation recovery, measuring Lactate dehydrogenase (LDH) levels, and detecting Annexin V/Propidium iodide staining. Stemness potential of DPSCs was assessed via detecting gene expression of MSCs stemness markers and pluripotency markers. Migration of DPSCs was investigated using a wound healing assays. Osteogenic differentiation of DPSCs was assessed via phenotypic mineralisation stains. Gene expression of cell cycle markers, stemness markers, osteogenic markers were assessed via Real-time polymerase chain reaction (q-PCR). Whole RNA sequencing (RNA-seq) was undertaking to measure transcriptome changes and enriched signalling pathways. Follow-up analysis was undertaking via measuring the phosphorylation and transcripts levels of ERK1 and ERK2 of the Mitogen-activated protein kinase (MAPK) pathway.
The results showed transcripts expression for the M2, M3 and M5 mAChRs, and expression of subunits that support the formation of α7 and α4β2-nAChRs. Subtype selective agonists/antagonists results suggest DPSCs to express functional M2 mAChR, α7 nAChRs, and α4β2-nAChRs. This was based on the ability of the agonists to influence DPSCs viable count and the subtype selective antagonist to cancel that effect. The project then focussed on mAChRs and protein expression of M2, M3 and M5 mAChRs were detected. The subsequent work focused on investigating the role of the M2 mAChRs in modulating the function of DPSCs via activating this receptor through its selective agonist Arecaidine propargyl ester (APE). Activation of the M2 mAChR inhibited DPSCs proliferation, in a reversable manner, without affecting DPSCs viability or survival. Further evidence showed that the M2 mAChR inhibits DPSCs proliferation by arresting cell cycle progression. This was further corroborated via expression analysis of key genes involved in the regulating cell cycle. The results also showed that M2 mAChR activation inhibited DPSCs migration and differentiation potential but did not interfere with DPSCs stemness. This was further corroborated via expression analysis of key genes involved in stemness and osteogenesis. The data obtained suggests that M2 mAChR activation induce DPSCs to go into a quiescent state.
The RNA-seq results showed that DPSCs responded differently to M2 mAChR activation 4 and 24 hours post activation, with different sets of differentially expressed genes (DEGs). The analysis of the enriched pathways suggested that M2 mAChR activation regulates cellular processes involved in metabolism, growth, adhesion, and response to stimuli. These processes function in proliferation, migration, and cell cycle through several metabolic pathways associated with response to cellular and oxidative stress. Follow up analysis showed upregulation of ERK1 and ERK2 phosphorylation and transcripts, which are downstream effectors of the MAPK pathway. The data obtained suggests that the transcriptomic data support the observed inhibitory effect of the M2 mAChR on DPSCs functions and highlights the many downstream effectors involved in the M2 mAChR downstream signalling.
In conclusion, this thesis presents evidence for the expression of a functional M2 mAChR in DPSCs, indicating the involvement of ACh signalling in modulating DPSCs behaviour. It also provides a promising route ultimately to pharmacologically control the regenerative output of DPSCs
Cloud intrusion detection systems: fuzzy logic and classifications
Cloud Computing (CC), as defned by national Institute of Standards and Technology (NIST), is a new technology model for enabling convenient, on-demand network access to a shared pool of configurable computing resources such as networks, servers, storage, applications, and services that can be rapidly provisioned and released with minimal management effort or service-provider interaction. CC is a fast growing field; yet, there are major concerns regarding the detection of security threats, which in turn have urged experts to explore solutions to improve its security performance through conventional approaches, such as, Intrusion Detection System (IDS). In the literature, there are two most successful current IDS tools that are used worldwide: Snort and Suricata; however, these tools are not flexible to the uncertainty of intrusions. The aim of this study is to explore novel approaches to uplift the CC security performance using Type-1 fuzzy logic (T1FL) technique with IDS when compared to IDS alone. All experiments in this thesis were performed within a virtual cloud that was built within an experimental environment. By combining fuzzy logic technique (FL System) with IDSs, namely SnortIDS and SuricataIDS, SnortIDS and SuricataIDS for detection systems were used twice (with and without FL) to create four detection systems (FL-SnortIDS, FL-SuricataIDS, SnortIDS, and SuricataIDS) using Intrusion Detection Evaluation Dataset (namely ISCX). ISCX comprised two types of traffic (normal and threats); the latter was classified into four classes including Denial of Service, User-to-Root, Root-to-Local, and Probing. Sensitivity, specificity, accuracy, false alarms and detection rate were compared among the four detection systems. Then, Fuzzy Intrusion Detection System model was designed (namely FIDSCC) in CC based on the results of the aforementioned four detection systems. The FIDSCC model comprised of two individual systems pre-and-post threat detecting systems (pre-TDS and post-TDS). The pre-TDS was designed based on the number of threats in the aforementioned classes to assess the detection rate (DR). Based on the output of this DR and false positives of the four detection systems, the post-TDS was designed in order to assess CC security performance. To assure the validity of the results, classifier algorithms (CAs) were introduced to each of the four detection systems and four threat classes for further comparison. The classifier algorithms were OneR, Naive Bayes, Decision Tree (DT), and K-nearest neighbour. The comparison was made based on specific measures including accuracy, incorrect classified instances, mean absolute error, false positive rate, precision, recall, and ROC area. The empirical results showed that FL-SnortIDS was superior to FL-SuricataIDS, SnortIDS, and SuricataIDS in terms of sensitivity. However, insignificant difference was found in specificity, false alarms and accuracy among the four detection systems. Furthermore, among the four CAs, the combination of FL-SnortIDS and DT was shown to be the best detection method. The results of these studies showed that FIDSCC model can provide a better alternative to detecting threats and reducing the false positive rates more than the other conventional approaches
The Effectiveness of Using E-learning and Distance Learning Applications in Jordanian Universities in the light of the Coronavirus Pandemic from the Students Point of View
This study aims to determine the effectiveness of the use of e-learning and distance learning (DL) tools in Jordanian universities according to the students perception of the coronavirus. The study followed a descriptive research method using descriptive questionnaires. A sample of (372) male and female undergraduate and graduate students from different Jordanian universities. The results showed that (73.7%) of the respondents used online distance learning every day during the coronavirus pandemic. Most of the students believe that the coronavirus epidemic has changed the use of online education more and more and the use of electronic devices to increase communication with others (teachers, colleagues). There is no significant difference in the level (α≥ 0.05) of the effectiveness of using E-Learning and Distance Learning applications according to gender and residence. Although a significant difference occurred between the variable age and the degree of university. The results of the study can be used to advise the teacher to focus more on activities that show a high level of enjoyment, especially website optimization and instruction. Colleges are now seen as important places of learning in the classroom. Websites and tutorials must be updated regularly
A Systematic Approach to Offshore Fields Development Using an Integrated Workflow
I present a systematic method to primary develop existing black oil fields. This
method uses integrated reservoir development workflow (IRDW) that relies on
integrated asset model (IAM). Developing any existing field means providing a plan that
generally serves the development goal(s) specified by management. However, serving
the development goal(s) by itself does not guarantee an optimal development plan. Plans
that do not rely on an IAM are less accurate. Some plans do not include economics in
their evaluation. Such plans are technically accepted but usually impractical or
unprofitable. Plans that only evaluate the field based on current, or short-term,
conditions are potential candidates for bottlenecks, thus costly reevaluations. In addition,
plans that do not consider all suitable options are misleading and have no room for
optimization. Finally, some plans are based on “rules of thumb,” ease of operations, or
operators’ preference, not on technical evaluation. These plans mostly lower long-term
profitability and cause further production problems. To overcome these problems,
project management must form a multidisciplinary team that uses the IRDW. The IRDW
guides the team through its phases, stages, and steps to selecting the optimal development plan. The IAM consists of geological, reservoir, wellbore, facility, and
economic models. The IRDW dictates building an IAM for the base (do nothing) case
and for each development plan. The team must evaluate each scenario over the lifetime
of the field, or over the timeframe the management specifies. Net present value (NPV)
and Present value ratio (PVR) for all options are compared to the base case and against
each other. The optimum development plan is the one that have the highest NPV and
highest PVR. The results of the research showed that forming a multidisciplinary team
and using a LDFC saves time and it guarantees selecting the optimal development plan if
all applicable development options are considered
- …