Virtual Explorer: a Path Prediction Algorithm for Intelligent Transport Systems

Mobile user tracking is an important issue in wireless Network. Spatial data is used for location based services and to support traffic management. Traffic management is an important problem faced by the local authorities where they try to manage efficiently all the information gathered for traffic control. For that location and movement determination are important. This paper proposes Virtual Explorer system that detects the movement of mobile user, analyses the information collected about him and predicts his destination only by measuring the signal received from his mobile phone. If some interruption is presented in the path to the destination a notification message is sent to him to inform him about that or to propose an alternative path. This paper proposesa-path prediction algorithm that predicts the future location of the mobile user based on the user's history movement. We expect that our system help in reducing congestion on the principal roads and help in reducing the number of cars that reach certain point in the case of accident. In addition, our system can help the police to keep track the pedestrian only by collecting information from his mobile phone. Keywords: traffic management, path prediction, location based detection, received signal strengt

Managing Software Project Risks With The Chi-Square (X2)Technique

[Abstract] Regardless how much effort we put into software projects to make them succeed, many software projects have very high failure rate. The aim of this paper is to present a new technique by which we can study the impact of different control factors and different risk factors to determine software project risks. The new technique uses the chi-square test to control the risks in a software project. Fourteen risk factors and eighteen control factors were used in this paper. A group of manageys was used in this study. Successful project risk management will greatly improve the probability of project success. [Keywords] Software project management; risk management, risk factors, risk controls, ChiSquar

A reliable route repairing scheme for internet of vehicles

Recently, Internet of Vehicles (IoVs) has been recognised as a key solution for vehicular communications. Connected vehicles and infrastructure' roadside units have been shaping the underlying architecture of IoVs technology, where the conventional routing protocols cannot facilitate reliable and efficient communication for dynamic IoVs topologies. Hence, this technology is highly susceptible to frequent network fragmentations, thus exposing communication channels to regular failure problems. This paper, thus, introduces a novel routing repair strategy, referred as Reliable Route Repairing Strategy (RRRS) to tackle routing failure problems. Repairing the operation of channel communications is prioritised according to a stability degree of the connected vehicles. The RRRS features are combined with the traditional AOMDV protocol, and a comparison study has been conducted to compare the AOMDV, the RRRS-AOMDV and the HM-AOMDV protocols. The simulation results demonstrate that the RRRS-AOMDV achieves better performance, about 30% to 45% in terms of packets overhead and latency

Utilizing business intelligence and digital transformation and leadership to enhance employee job satisfaction and business added value in greater Amman municipality

The goal of this study was to find out how business intelligence systems, AI, and digital leadership affect how satisfied employees are with their jobs and how much value they add to companies in the Greater Amman Municipality. After the study samples were taken and looked at, a total of 246 samples were approved to be used in the PLS software-based analysis. The results of this study showed that putting in place business intelligence tools, artificial intelligence, and digital leadership all made employees happier with their jobs and gave businesses more value. The research showed that there are four key parts to digital leadership: commander, communicator, collaborator, and co-creator. The main parts of business intelligence are Data Warehouse, Data Mining, Business Process Management, and Competitive Intelligence. Findings show that digital transformation is made up of three key parts: changing processes, developing business models, and changing domains. The results also show that an employee's level of job satisfaction, which includes things like business success, work commitment, and job thinking, is linked to how much value they add to the company. Intriguingly, the current results go against those of earlier studies, which said that the variables of interest have no effect on how happy employees are with their jobs or how much value companies add for their customers. When the results of this study are looked at as a whole, they say that businesses should start doing things that make employees happier at work and increase the value of the business. The current study is innovative because it focuses on the most important parts of business intelligence, artificial intelligence, and digital leadership in order to improve employee satisfaction at work and the quality of business learning with added value in Greater Amman Municipality

Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

Correction to: Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

The original version of this article unfortunately contained a mistake

Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

Adaptive Task Scheduling Using Low-Level Runtime APIs and Machine Learning

The introduction of task constructs in the OpenMP programming model offers a user a new way to specifying parallelism within applications while making the OpenMP runtime responsible for scheduling tasks for parallel execution. The ability to observe performance for OpenMP tasking programs and scheduling schemes has been a challenge due to the lack of performance interface standards in the runtime layer. In this work, we propose new tasking profiling interfaces compatible with the OMPT (OpenMP Performance Tools) interface. We describe the integration of these interfaces into a profiling tool that we have developed and show how we employ them to analyze various OpenMP task scheduling strategies on exploiting data locality, maintaining load balance, and minimizing overhead costs. We use this analysis to build a portable and adaptive framework (APARF). The framework comprises of proposed low-level tasking runtime interfaces, a profiling tool, and a hybrid machine learning model. We show that APARF can effectively be used to select an optimum task scheduling scheme for any given application with low profiling costs. Our hybrid model predicts the best scheduling strategy for a variety of unseen applications with an average accuracy of 93% while maintaining a 100% training accuracy. Compared to Intel, PGI and GNU compilers, APARF achieved better performance in most cases. When applied to different unseen benchmark applications, an average performance enhancement of 25% was obtained as compared to the default configuration. APARF was evaluated using a real application (Molecular Dynamics), where we achieved up to 31% performance improvement.Computer Science, Department o

A Compiler-Based Tool for Array Analysis in HPC Applications

Array region analysis plays a significant role in various optimizations at compile time. Displaying array access information efficiently in HPC applications has been a vital challenge for scientists and developers for the past few years. Dragon array region analysis tool is a powerful and interactive tool that was built on top of the OpenUH compiler, an open source C/C++/Fortran compiler, that supports OpenMP and CAF programming models. We have extended the linear-based Region analysis method and the high level IR (WHIRL) of OpenUH to visualize the static and interprocedural array region accesses, the frequency of these accesses per access mode, the access mode in which the array is processed, the number of dimensions, the size of each dimension, the total size in bytes allocated to this array statically, and the memory location. We have also defined the access density term which illustrates the frequency of accesses per bytes allocated to these arrays. The information provided enables users to efficiently develop and optimize HPC applications by understanding procedure side effects and finding inefficiencies in defining arrays, which guides to a better memory allocation and cache usage. Moreover, we demonstrate the access density of the portions of arrays that have been accessed, which is crucial to reduce data transfers between host and device when using directive-based GPU programming models