GPS/INS SYSTEM INTEGRATION BASED ON NEURO-WAVELET TECHNIQUES

ABSTRACT Global Positioning System (GPS) and Strapdown Inertial Navigation System (SDINS) can be integrated together to provide a reliable navigation system. This paper offers a new method for error estimation in a GPS/INS augmented system based on Artificial Neural Network (ANN) and Wavelet Transform (WT). An ANN was adopted in this paper to model the GPS/INS position and velocity errors in real time to predict the error in the integrated system and provide accurate navigation information for a moving vehicle. It was found that the proposed technique reduces the standard deviation error in the position by about 91% for X, Y, and Z axes, while in velocity it was reduced by about 94% for North, East, and Down directions. K KE EY YW WO OR RD D: : vehicular navigation, inertial navigation, GPS, wavelet multi-resolution analysis, neural networks

Implementation of an intelligent SINS navigator based on ANFIS

In this work an intelligent navigator developed to overcome the limitations of existing Strapdown Inertial Navigation Systems (SINS) algorithm. This system is based on Adaptive Neuro-Fuzzy Inference System (ANFIS). As in previous work, which is based on Artificial Neural Network, the window based weight updating strategy was used, and the intelligent navigator evaluated using several SINS hypothetical field tests data. And the results show that the intelligent navigator based on ANFIS more powerful compared with other (traditional and intelligent navigator based on ANN)

Impact of Landfills on Soil Contamination by Some Heavy Metals at Kani-qrzhala in Erbil City- Iraqi Kurdistan Region

The present study was carried out in November 2019 to investigate the impact of Kani-qrzhala landfill on soil pollution of the surrounding area caused by the disposed of refuses from houses, factories, and hospitals. Soil samples were collected from 6 sites in Kani-qrzhala landfill on Erbil-Mosul Road ((Latitude 36˚13̍ N, Longitude 43˚.58̍̍ E). Soil samples were taken randomly selected at different depths (0-10), (10-20), (20-30) cm, were collected randomly at the dumpsite field in the study area with a control sample. The different parameters of soil samples were analyzed of contaminated metals such as Iron (Fe), Manganese (Mn), Nickel (Ni), Lead (Pb), and Zinc (Zn) were determined in the study soil samples by using portable x-ray fluorescence (XRF). Additionally, specialization index Geoaccumulation (I geo) was calculated and used for evaluating the soil pollution status: In the depth (0-10) cm, the heavy metals concentration was recorded as follow: Fe > Pb > Zn > Ni > Mn. Also in the depth (10-20) cm Fe > Pb > Zn > Mn > Ni. In the depth (20-30) cm depth Fe > Pb > Mn > Zn > Ni (0 mg kg-1). Measuring Geoaccumulation index (I geo): The results show that most the most location of the study area of soil surrounding the dumpsite were polluted by heavy metals followed by series: Ni, Pb > Zn > Fe >Mn

Impact of Crude Oil discharge from Oil Refineries near Gwer Road of Erbil City on Soil Physico-chemical Properties and Metal Emancipations

The study was carried out in October 2021 nearby oil refineries which are located near Gwer road and 15 km far away from Erbil city (36° 8'32.31"N, 43°46'32.61"E), to investigate the impact of residual crude oil discharged from surrounding oil refineries on soil Physico-chemical properties and heavy metals contamination. A total of 108 soil samples were collected from (8) different locations, (4) distances, and (3) depths alongside the residual crude oil stream. By using (XRF) technique to determine total heavy metals concentration from collected soil samples. The range of soil pH is between (7.23- 8.7) and an increase in crude oil quantity causes increases in soil pH. (Fe) has the highest concentration among the studied metals ranging between (11925.09 - 22394.37 mgkg-1) followed by (Mn) which ranged between (127.89 - 528.12 mgkg-1) and (Zn) ranged between (41.68 - 107.58 mgkg-1). According to Pearson’s correlation, there is a significant positive correlation between (Fe and Mn) at (p ≤ 0.01, r=.753**) which indicates both metals are derived from the same source. Moreover, there are a significant positive correlation between (Zn and Mn) at (p ≤ 0.05, r=.338*) However, the correlation is less strong compared to (Fe and Mn) this mean (Zn) derived from multiple sources other than crude oil like automobile and truck tire which is one of the major sources for (Zn), since the study area was located next to the busy road

MULTISPECTRAL IMAGE FUSION USING SLANTLET-BASED RIDGELET TRANSFORM

This paper introduces a new method in the multispectral image fusion based on ridgelet transform which represents edges better than wavelets. Since edges play a fundamental rule in image understanding, one good way to enhance spatial resolution is to enhance the edges. Ridgelet based image fusion method provides richer information in the spatial and spectral domains simultaneously. Also another method introduced based on new Hybrid transform which is improvement from the Ridgelet transform. Here we used our method to merge the panchromatic image of IKONOS sensor (1m resolution) with its multispectral image (4m resolution). The software used in this paper is (Matlab V 7.0.4 )

Repurposing of Antibiotics for Clinical Management of COVID-19: A Narrative Review

Background: Drug repurposing otherwise known as drug repositioning or drug re-profling is a time-tested approach in drug discovery through which new medical uses are being established for already known drugs. Antibi‑ otics are among the pharmacological agents being investigated for potential anti-SARS-COV-2 activities. The antibiot‑ ics are used either to resolve bacterial infections co-existing with COVID-19 infections or exploitation of their potential antiviral activities. Herein, we aimed to review the various antibiotics that have been repositioned for the manage‑ ment of COVID-19. Methods: This literature review was conducted from a methodical search on PubMed and Web of Science regarding antibiotics used in patients with COVID-19 up to July 5, 2020. Results: Macrolide and specifcally azithromycin is the most common antibiotic used in the clinical management of COVID-19. The other antibiotics used in COVID-19 includes teicoplanin, clarithromycin, doxycycline, tetracyclines, levo‑ foxacin, moxifoxacin, ciprofoxacin, and cefuroxime. In patients with COVID-19, antibiotics are used for their immunemodulating, anti-infammatory, and antiviral properties. The precise antiviral mechanism of most of these antibiotics has not been determined. Moreover, the use of some of these antibiotics against SARS-CoV-2 infection remains highly controversial and not widely accepted. Conclusion: The heavy use of antibiotics during the COVID-19 pandemic would likely worsen antibiotic resistance crisis. Consequently, antibiotic stewardship should be strengthened in order to prevent the impacts of COVID-19 on the antibiotic resistance crisi

Outcome and Management of Sepsis at RozhHalat Emergency Hospital in Erbil –Kurdistan region of Iraq

Sepsis is a very common condition in emergency hospitals and presentation is variable, it is under diagnosed with very high mortality rate. All patients with infection are at risk of developing sepsis. Sepsis is a complex condition characterized by activation of inflammatory process and coagulation system in response to microbial insult. An observational prospective study was carried out at RozhHalat emergency hospital in Erbil-Kurdistan region of Iraq between February 2017 to January 2018.The study was approved by the scientific and ethical committee of Kurdistan board of medical specialties. 50 patients aged between (10 - 80) years old presented to this hospital with sign and symptoms of infection were recruited to this study. 50 patients with signs and symptoms of sepsis were recorded in this study. The mean age was 47 with male to female ration of 2:3 (42% male and 58% female). The overall mortality rate was high at 68% with higher rate among female and older age group. The blood culture was positive in 74% of cases of which 52% were gram positive and 22% were gram-negative microorganisms. A Positive blood culture associated with higher mortality rate of 81% compared with 21% if the blood culture was negative. In majority of cases the site of infection was from multiple source (34%) followed by respiratory infection (26%).Skin and soft tissue infection was associated with the lowest mortality of 2.9%. High number of cases (82%) developed complications and 52% of cases developed more than 2 organ failures. All patients received empirical antibiotic therapy however 46% of cases received the wrong antimicrobials. The survival rate was higher   (44%) among patients given the right antibiotics. Similarly patients had better chance of survival if appropriate fluid resuscitation therapy was give. The overall mortality among vasopressor treated patients were 72% compared with 78% chance of mortality if they were not treated with any vasopressor therapy, among those who received inotropic support Noradrenaline associated with higher survival rate(72%). A qSOFA score of more than 2 associated with 86.4 % of mortality compared with 75.5% mortality with similar SIRS criteria. Factors associated with high mortality were: female gender, older age group, positive blood culture, wrong antibiotics therapy, less fluid resuscitation, multisource of infection, multi-organ failure, high lactic acid level and high qSOFA score. This study shows that sepsis is associated with high overall mortality rate of 68% in the RozhHalat emergency hospital and higher rate of death among female and older age group. Negative blood culture, appropriate use of antibiotics and fluid therapy associated with better chance of survival. Vasopressor therapy did not result in better survival outcome except for Noradrenaline. The qSOFA score is as good as SIRS criteria in predicting mortality. High lactate, multi-organ failure and multisource of infection associated with the worst outcome

The Influence of Age and Cardiorespiratory Fitness on Cardiac Autonomic Modulation. A Pilot Study.

Maximal rate of oxygen consumption (VO2max) is traditionally viewed as the gold standard of determining cardiorespiratory fitness (CF) in healthy and diseased populations. CF has a significant influence on the improvement of cardiac autonomic modulation (CAM) and the risk of morbidity and mortality rates. Heart rate variability (HRV) is a non-invasive way to assess CAM. Age is another factor that influences CAM and CF in healthy and diseased populations. However, what is not fully elucidated, is if CF is maintained at a high level throughout adulthood, will CAM remain relatively unchanged. PURPOSE: To determine if age and CF are significantly correlated to variables of HRV to determine CAM in healthy fit individuals. METHODS: Twenty-two healthy individuals (n = 14 male; n = 8 female, Age 33.2 ± 11.8 years, %BF 18.3 ± 6.0, VO2max 42.0 ± 6.2 ml/ /kg/min) completed a single health assessment to quantify CF and HRV. HRV was measured for 5 mins in the supine position and during a standard VO2max test using an elastic belt and Bluetooth monitor (Polar H7). CardioMood software was used to process HRV variables high frequency (HF), low frequency (LF), total power (TP) were assessed for frequency domain, and standard deviation of all NN intervals (SDNN) and the square root of the mean of the squares of successive R-R interval differences (RMSSD) for the time domain. Pearson correlation was used to check associations between age and CF, and CAM. Multiple regression was implemented to determine if there were any differences in HRV variables in relation to age and VO2max. A paired sample t-test was used to determine changes in HRV variables from rest to VO2max. All analyses were performed using SAS (v.9.3). RESULTS: HRV variables were significantly altered from rest to VO2max (p \u3c 0.05). HRV time and frequency domain variables were not significantly correlated to age and CF level (p \u3e 0.05). The multiple regression analysis indicated that the only significance was max heart rate is 0.642 bpm lower during exercise for each 1-year increase in age (p = 0.035). CONCLUSION: The analysis of pilot data focused on determining the impact of CF and age on CAM appears not to be significantly correlated when utilizing HRV. However, due to the project\u27s continuation and further data collection, significant outcomes may still be observed

Integration of global positioning system and inertial navigation system with different sampling rate using adaptive neuro fuzzy inference system

Integration of the Global Positioning System (GPS) and Inertial Navigation System (INS) has become increasingly common in the last two decades, because the characteristics of GPS and INS are complementary and the integration between both systems will maximize their advantages and minimize their weakness. Over time, inertial navigators drift from their preset alignments. Or, the initial alignment may have been corrupted by vehicle motion, with imperfect transfer of alignment and velocities to the navigator. Also, there may not have been enough time to perfect alignment. In such case, navigators can be benefit from aiding such as GPS. The integration between the GPS and INS leads to accurate navigation solution by overcoming each of their respective shortcomings. And to make this integration possible the difference between the GPS and INS systems in sampling rate must be solved before any integration can be work properly. In this paper, the GPS low rate problem is solved by predicting or extrapolating the mislaid reading data of the GPS to be attuned with those of INS data using Adaptive Neuro Fuzzy Inference System (ANFIS). Hence, the gap between the two systems reading data is solved to provide synchronization between the INS and GPS systems. So, it is possible to compare the reading data of both systems. Three strategies have been proposed and the results shows superior performance in predicting missed GPS data with lowest mean error

The Ability of implementing Cloud Computing in Higher Education - KRG

Cloud computing is a new technology. CC is an online service can store and retrieve information, without the requirement for physical access to the files on hard drives. The information is available on a system, server where it can be accessed by clients when it’s needed. Lack of the ICT infrastructure of universities of the Kurdistan Regional Government (KRG) can use  this new technology, because of economical advantages, enhanced data managements, better maintenance, high performance, improve availability and accessibility therefore achieving an easy maintenance  of organizational  institutes. The aim of this research is to find the ability and possibility to implement the cloud computing in higher education of the KRG. This research will help the universities to start establishing a cloud computing in their services. A survey has been conducted to evaluate the CC services that have been applied to KRG universities have by using cloud computing services. The results showed that the most of KRG universities are using SaaS. MHE-KRG universities and institutions are confronting many challenges and concerns in term of security, user privacy, lack of integration with current systems, and data and documents ownership