Search results for: care networks

Authors: Saif Obaid Alkaabi, Nabil Ayad

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Governments constantly seek to offer faster, more secure, efficient and effective services for their citizens. Recent changes and developments to communication services and technologies, mainly due the Internet, have led to immense improvements in the way governments of advanced countries carry out their interior operations Therefore, advances in e-government services have been broadly adopted and used in various developed countries, as well as being adapted to developing countries. The implementation of advances depends on the utilization of the most innovative structures of data techniques, mainly in web dependent applications, to enhance the main functions of governments. These functions, in turn, have spread to mobile and wireless techniques, generating a new advanced direction called m-government. This paper discusses a selection of available m-government applications and several business modules and frameworks in various fields. Practically, the m-government models, techniques and methods have become the improved version of e-government. M-government offers the potential for applications which will work better, providing citizens with services utilizing mobile communication and data models incorporating several government entities. Developing countries can benefit greatly from this innovation due to the fact that a large percentage of their population is young and can adapt to new technology and to the fact that mobile computing devices are more affordable. The use of models of mobile transactions encourages effective participation through the use of mobile portals by businesses, various organizations, and individual citizens. Although the application of m-government has great potential, it does have major limitations. The limitations include: the implementation of wireless networks and relative communications, the encouragement of mobile diffusion, the administration of complicated tasks concerning the protection of security (including the ability to offer privacy for information), and the management of the legal issues concerning mobile applications and the utilization of services.

Keywords: e-government, m-government, system dependability, system security, trust

Procedia PDF Downloads 383

Authors: Opara Monica, Suriani Ismail, Ahmad Iqmer Nashriq Mohd Nazan

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The true magnitude of the mortality and morbidity attributable to malaria worldwide is, at best, a scientific guess, although it is not disputable that the greatest burden is in sub-Saharan Africa. Those at highest risk are children younger than 5 years and pregnant women, particularly primigravidae. Nationally, malaria remains the third leading cause of death and is still considered a major public health problem. Therefore, this study is aimed to assess the effectiveness of health education intervention on insecticide-treated net use and its practices among pregnant women attending antenatal clinics. Materials and Methods: This study will be an intervention study with two arms double parallel randomized controlled trial (blinded) to be conducted in 3 stages. The first stage will develop health belief model (HBM) program, while in the second stage, pregnant women will be recruited, assessed (baseline data), randomized into two arms of the study, and follow-up for six months. The third stage will evaluate the impact of the intervention on HBM and disseminate the findings. Data will be collected with the use of a structured questionnaire which will contain validated tools. The main outcome measurement will be the treatment effect using HBM, while data will be analysed using SPSS, version 22. Discussion: The study will contribute to the existing knowledge on hospital-based care programs for pregnant women in developing countries where the literature is scanty. It will generally give insight into the importance of HBM measurement in interventional studies on malaria and other related infectious diseases in this setting.

Keywords: malaria, health education, insecticide-treated nets, sub-Saharan Africa

Procedia PDF Downloads 125

Authors: Muhammad Safi, Abdul Manan

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In recent years, research in aircraft avionics systems (i.e., radars and antennas) has grown revolutionary. Aircraft technology is experiencing an increasing inclination from all mechanical to all electrical aircraft, with the introduction of inhabitant air vehicles and drone taxis over the last few years. This develops an overriding need to summarize the history, latest trends, and future development in aircraft avionics research for a better understanding and development of new technologies in the domain of avionics systems. This paper focuses on the future trends in antennas and phased arrays for avionics systems. Along with the general overview of the future avionics trend, this work describes the review of around 50 high-quality research papers on aircraft communication systems. Electric-powered aircraft have been a hot topic in the modern aircraft world. Electric aircraft have supremacy over their conventional counterparts. Due to increased drone taxi and urban air mobility, fast and reliable communication is very important, so concepts of Broadband Integrated Digital Avionics Information Exchange Networks (B-IDAIENs) and Modular Avionics are being researched for better communication of future aircraft. A Ku-band phased array antenna based on a modular design can be used in a modular avionics system. Furthermore, integrated avionics is also emerging research in future avionics. The main focus of work in future avionics will be using integrated modular avionics and infra-red phased array antennas, which are discussed in detail in this paper. Other work such as reconfigurable antennas and optical communication, are also discussed in this paper. The future of modern aircraft avionics would be based on integrated modulated avionics and small artificial intelligence-based antennas. Optical and infrared communication will also replace microwave frequencies.

Keywords: AI, avionics systems, communication, electric aircrafts, infra-red, integrated avionics, modular avionics, phased array, reconfigurable antenna, UAVs

Procedia PDF Downloads 83

Authors: Dimpy Shah

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The global economy has substantially changed in last three decades. Now almost all markets are transparent and visible for global customers. The corporates are now no more reliant on local markets for trade. The information technology revolution has changed business dynamics and marketing practices of corporate. The markets are divided into two different formats: traditional and virtual. In very short span of time, many e-commerce portals have captured global market. This strategy is well supported by global delivery system of multinational logistic companies. Now the markets are dealing with global supply chain networks, which are more demand driven and customer oriented. The corporate have realized importance of supply chain integration and marketing in this competitive environment. The Indian markets are also significantly affected with all these changes. In terms of population, India is in second place after China. In terms of demography, almost half of the population is of youth. It has been observed that the Indian youth are more inclined towards e-commerce and prefer to buy goods from web portal. Initially, this trend was observed in Indian service sector, textile and electronic goods and now further extended in other product categories. The FMCG companies have also recognized this change and started integration of their supply chain with e-commerce platform. This paper attempts to understand contemporary marketing practices of corporate in e-commerce business in Indian food and beverages segment and also tries to identify innovative marketing practices for proper execution of their strategies. The findings are mainly focused on supply chain re-integration and brand building strategies with proper utilization of social media.

Keywords: FMCG (Fast Moving Consumer Goods), ISCM (Integrated supply chain management), RFID (Radio Frequency Identification), traditional and virtual formats

Procedia PDF Downloads 276

Authors: Bello Aishatu, Saleh Hassan, Maianguwa Abdulrashid Dauda, Hammari Abubakar Muhammad, Shu’aibu Isa

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This study investigates the phytochemical constituents and antibacterial activity of methanolic extracts from Syzygium aromaticum (clove buds) against common oral pathogens. The extraction process was performed using methanol, followed by qualitative phytochemical screening to identify bioactive compounds such as alkaloids, flavonoids, tannins, saponin, glycosides, steroids, and anthraquinones. The antibacterial efficacy was evaluated using the agar well diffusion method against several oral pathogens, including Staphylococcus epidermidis, Staphylococcus aureus, Streptococcus mutans, Streptococcus pneumoniae and Enterococcus faecalis. Results indicated that the methanolic extract exhibited significant antibacterial activity, with inhibition zones correlating with the concentration of the extract. The highest inhibition was observed on S. epidermis (25 mm), E. faecalis (22.5 mm), S. aureus (21.5 mm), S. pneumoniae (19 mm) and S. mutans (17 mm) at the highest concentration (500µg/ml). While the lowest inhibition was observed at the lowest concentration (62.5 µg/ml), on S. mutans (7 mm), S. aureus (13.5 mm), S. pneumoniae (14 mm), E. faecalis (14 mm) and S. epidermis (16 mm). The positive control (Ofloxacin)-used during the experiment-shows lesser activity on some tested oral pathogen (S. epidermis and E. faecalis) as compared to that the extract and thus, the extract may serve as an alternative source of treatment of infections caused by Staphylococcus epidermidis and Enterococcus faecalis. Phytochemical analysis revealed a rich profile, suggesting a potential for clove extracts as natural antimicrobial agents in dental care. These findings support the therapeutic use of Syzygium aromaticum in managing oral infections and highlight its importance in phytomedicine.

Keywords: phytochemical, antibacterial, mentholic, clove buds

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Authors: Oumaima Khlifati, Khadija Baba

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Pavement distress is the main factor responsible for the deterioration of road structure durability, damage vehicles, and driver comfort. Transportation agencies spend a high proportion of their funds on pavement monitoring and maintenance. The auscultation of pavement distress was based on the manual survey, which was extremely time consuming, labor intensive, and required domain expertise. Therefore, the automatic distress detection is needed to reduce the cost of manual inspection and avoid more serious damage by implementing the appropriate remediation actions at the right time. Inspired by recent deep learning applications, this paper proposes an algorithm for automatic road distress detection and classification using on the Deep Convolutional Neural Network (DCNN). In this study, the types of pavement distress are classified as transverse or longitudinal cracking, alligator, pothole, and intact pavement. The dataset used in this work is composed of public asphalt pavement images. In order to learn the structure of the different type of distress, the DCNN models are trained and tested as a multi-label classification task. In addition, to get the highest accuracy for our model, we adjust the structural optimization hyper parameters such as the number of convolutions and max pooling, filers, size of filters, loss functions, activation functions, and optimizer and fine-tuning hyper parameters that conclude batch size and learning rate. The optimization of the model is executed by checking all feasible combinations and selecting the best performing one. The model, after being optimized, performance metrics is calculated, which describe the training and validation accuracies, precision, recall, and F1 score.

Keywords: distress pavement, hyperparameters, automatic classification, deep learning

Procedia PDF Downloads 94

Authors: Artitaya Sabangbal, Darawan Augsornwan, Palakorn Surakunprapha, Lalida Petphai

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Background: Srinagarind Hospital Ward 3C has about 180 cases of patients with head and neck cancer per year. Almost all of these patients suffer with pain, fatigue, low self image, swallowing problem and when the tumor is larger they will have breathing problem. Many of them have complication after operation such as pressure sore, pneumonia, deep vein thrombosis. Nursing activity is very important to prevent the complication especially promoting patients early ambulation. The objective of this study was to develop early ambulation protocol for patients with head and neck cancer undergoing operation. Method: this study is one part of nursing system development in patients undergoing operation in Ward 3C. It is a participation action research divided into 3 phases Phase 1 Situation review: In this phase we review the clinical outcomes, process of care, from document such as nurses note and interview nurses, patients and family about early ambulation. Phase 2 Searching nursing intervention about early ambulation from previous study then establish protocol . This phase we have picture package of early ambulation. Phase 3 implementation and evaluation. Result: Patients with head and neck cancer after operation can follow early ambulation protocol 100%, 85 % of patients can follow protocol within 2 days after operation and 100% can follow protocol within 3 days. No complications occur. Patients satisfaction in very good level is 58% and in good level is 42% Length of hospital stay is 6 days in patients with wide excision and 16 day in patients with flap coverage. Conclusion: The early ambulation protocol is appropriate for patients with head and neck cancer who undergo operation. This can restore physical health, reduce complication and increase patients satisfaction.

Keywords: nursing system, early ambulation, head and neck cancer, operation

Procedia PDF Downloads 229

Authors: Ayesha Iftikhar, Faisal Hafeez, Muhammad Jawad Saleem, Afifa Naeem, Muhammad Sohaib

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To further develop integrated pest management (IPM) tactics against insect pests, demographic toxicology is considered important and efficient to evaluate the long-term effects of pesticides on biological control agents. In this study, lethal and sub-lethal effects of Pyriproxyfen (insect growth regulator) two concentrations of LC10 and LC30 were tested on second instar larvae of convergent lady beetle, Hippodamia convergens (Goeze) in order to evaluate the effect of insecticide on demographic parameters of the predator under laboratory conditions. The life table parameters were analysed statistically by using age-stage, two sex life table procedure. The results of this study show that developmental time for immature was prolonged in treated population (LC30 and LC10) rather than in control. Similarly, male and female longevity was also longer in the control group as compared to the treated population. Adult pre-oviposition period and fecundity were also greater in control as compared to the treated population. In addition, population parameters such as net reproductive rate (R0), intrinsic rate of increase (r) and finite rate of increase (λ) were also greater in control group rather than treated population. However, mean generation time (T) was greater in the treated group. The results revealed that pyriproxyfen, even at low concentrations, has potential to greatly affect the population growth of predatory lady beetle, therefore care should be taken when insect growth regulators are used within an IPM framework.

Keywords: ladybird beetle, IGR, integrated pest management, population inhibition

Procedia PDF Downloads 131

Authors: Hadjer Sadoune, Liza Lamini, Scherazade Krim, Amel Djouadi, Rachida Rihani

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Deep neural networks are highly regarded for their accuracy in predicting intricate fermentation processes. Their ability to learn from a large amount of datasets through artificial intelligence makes them particularly effective models. The primary obstacle in improving the performance of these models is to carefully choose the suitable hyperparameters, including the neural network architecture (number of hidden layers and hidden units), activation function, optimizer, learning rate, and other relevant factors. This study predicts biogas production from real wastewater treatment plant data using a sophisticated approach: hybrid Bayesian optimization with a tree-structured Parzen estimator (BO-TPE) for an optimised deep neural network (DNN) model. The plant utilizes an Upflow Anaerobic Sludge Blanket (UASB) digester that treats industrial wastewater from soft drinks and breweries. The digester has a working volume of 1574 m3 and a total volume of 1914 m3. Its internal diameter and height were 19 and 7.14 m, respectively. The data preprocessing was conducted with meticulous attention to preserving data quality while avoiding data reduction. Three normalization techniques were applied to the pre-processed data (MinMaxScaler, RobustScaler and StandardScaler) and compared with the Non-Normalized data. The RobustScaler approach has strong predictive ability for estimating the volume of biogas produced. The highest predicted biogas volume was 2236.105 Nm³/d, with coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE) values of 0.712, 164.610, and 223.429, respectively.

Keywords: anaerobic digestion, biogas production, deep neural network, hybrid bo-tpe, hyperparameters tuning

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Authors: Angalabiri-Owei E. Bekekeme, Brambaifa Nelson

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In view of the peculiar environment of the Niger Delta, access to modern health care is limited, hence the inhabitants especially those in the swampy areas resorts to sourcing for alternatives cure for their ailments using plants commonly found in this area without scientific evaluation. Rhizophora racemosa, G. F. Meyer (Rhizophoraceae) is the most abundant mangrove plant in the Niger Delta Area of Nigeria. The plant has been observed to be used for relief of a toothache and dysmenorrhoea among some Ijaw communities in the region. This work has revealed the likely potential of the plant in drug discovery and development. The crude methanol extract at doses of 300 mg/kg and 600 mg/kg (intraperitoneal) were tested for analgesic effect using fresh egg albumin induced inflammatory pain and Randall–Sellito method to assess the pain threshold. The anti-inflammatory effect was also evaluated with the extract at doses of 300 mg/kg and 600 mg/kg (intraperitoneal) using acute inflammatory model; fresh egg albumin induced paw oedema and assessed using Plethysmometer in rats. The methanol extracts 300 mg/kg and 600 mg/kg exhibited a significant (P < 0.001) and dose-dependent analgesic activity compared with the negative control and a standard drug diclofenac using ANOVA with Least Significant Difference post hoc test as evidenced by increased pain threshold. Also, the extract significantly (P < 0.001) reduced the rat paw oedema induced by the sub plantar injection of fresh egg albumin when compared with the negative control and a standard diclofenac using above statistical methods. This study revealed that the plant possesses analgesic and anti-inflammatory activities hence provide scientific bases for use as medicine.

Keywords: analgesic, anti-inflammatory, plethysmometer, Rhizophora racemosa

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Authors: Yehjune Heo

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As biometric systems become widely deployed, the security of identification systems can be easily attacked by various spoof materials. This paper contributes to finding a reliable and practical anti-spoofing method using Convolutional Neural Networks (CNNs) based on the types of loss functions and optimizers. The types of CNNs used in this paper include AlexNet, VGGNet, and ResNet. By using various loss functions including Cross-Entropy, Center Loss, Cosine Proximity, and Hinge Loss, and various loss optimizers which include Adam, SGD, RMSProp, Adadelta, Adagrad, and Nadam, we obtained significant performance changes. We realize that choosing the correct loss function for each model is crucial since different loss functions lead to different errors on the same evaluation. By using a subset of the Livdet 2017 database, we validate our approach to compare the generalization power. It is important to note that we use a subset of LiveDet and the database is the same across all training and testing for each model. This way, we can compare the performance, in terms of generalization, for the unseen data across all different models. The best CNN (AlexNet) with the appropriate loss function and optimizers result in more than 3% of performance gain over the other CNN models with the default loss function and optimizer. In addition to the highest generalization performance, this paper also contains the models with high accuracy associated with parameters and mean average error rates to find the model that consumes the least memory and computation time for training and testing. Although AlexNet has less complexity over other CNN models, it is proven to be very efficient. For practical anti-spoofing systems, the deployed version should use a small amount of memory and should run very fast with high anti-spoofing performance. For our deployed version on smartphones, additional processing steps, such as quantization and pruning algorithms, have been applied in our final model.

Keywords: anti-spoofing, CNN, fingerprint recognition, loss function, optimizer

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Authors: Noof Eid Al Shammari

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Background: Living with haemodialysis (HD) can impose several physical and social restrictions on the lives of individuals. Usually, the patient has three dialysis sessions per week that each run for three to four hours. This limits the social life of patients and causes a lower quality of life, in conjunction with the fact that people with chronic kidney disease must follow strict fluid and food regimens and use multiple medications. Given these factors, patients undergoing HD generally need psychological support. Objective: This scoping review study aims to evaluate the effectiveness of physical and breathing exercises on quality of life (QOL) and psychophysical status in patients undergoing HD. Methodology: Searches for relevant studies were performed in four databases (MEDLINE, CINAHL, Google Scholar, and PubMed) for articles published between 2011 and 2021. Out of all the searched literature, ten studies met the inclusion criteria (8 randomised controlled trials, one quasi-experimental study, and one pilot study), with a total of 588 patients. Different types of physical and breathing exercises were used (breathing, cardiopulmonary, and physical exercises). Results: All included studies in this scoping review revealed that most of the aerobic or anaerobic exercises, as well as breathing exercises, had a positive effect and significantly improved patients’ QOL, physical functioning, and psychological status. Conclusions: In this review, most of the articles demonstrated a positive effect of physical and breathing exercises on the QOL and psychophysical status of HD patients. Based on the findings of these studies, physical and breathing exercises were shown to improve muscle strength and other health-related aspects of QOL, including sexual, social, cognitive, and physical functions. However, more studies will need to be conducted with a larger sample to determine the best intervention that could be implemented and standardised in nursing care for patients undergoing HD.

Keywords: physical exercise, breathing exercises, quality of life, depression, hemodialysis

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Authors: Carol Anne Hargreaves

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A key issue in stock investment is how to select representative features for stock selection. The objective of this paper is to firstly determine whether an automated stock investment system, using machine learning techniques, may be used to identify a portfolio of growth stocks that are highly likely to provide returns better than the stock market index. The second objective is to identify the technical features that best characterize whether a stock’s price is likely to go up and to identify the most important factors and their contribution to predicting the likelihood of the stock price going up. Unsupervised machine learning techniques, such as cluster analysis, were applied to the stock data to identify a cluster of stocks that was likely to go up in price – portfolio 1. Next, the principal component analysis technique was used to select stocks that were rated high on component one and component two – portfolio 2. Thirdly, a supervised machine learning technique, the logistic regression method, was used to select stocks with a high probability of their price going up – portfolio 3. The predictive models were validated with metrics such as, sensitivity (recall), specificity and overall accuracy for all models. All accuracy measures were above 70%. All portfolios outperformed the market by more than eight times. The top three stocks were selected for each of the three stock portfolios and traded in the market for one month. After one month the return for each stock portfolio was computed and compared with the stock market index returns. The returns for all three stock portfolios was 23.87% for the principal component analysis stock portfolio, 11.65% for the logistic regression portfolio and 8.88% for the K-means cluster portfolio while the stock market performance was 0.38%. This study confirms that an automated stock investment system using machine learning techniques can identify top performing stock portfolios that outperform the stock market.

Keywords: machine learning, stock market trading, logistic regression, cluster analysis, factor analysis, decision trees, neural networks, automated stock investment system

Procedia PDF Downloads 158

Authors: Orapan Thosingha, Tassana Boontong, Prapa Yuttatri, Vilaivan Thongcharoen, Soparn Potaya, Mattika Chaichan, Chanin Chakkrapopyodhin, Khwanthida Phimphakarn, Taddao Nabnean

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This research aimed to explore symptom experiences among Thai adults with chronic illnesses living in an urban community area of Bangkok. The sample was 670 adults with ages ranging from 20-59 years. The majority of them (65.2%) had more than one disease. Hypertension, dyslipidemia, and diabetes were the first three diseases among them. About 58% were female, and 51.1 % stayed with their couples. The studied sample had relatively low socioeconomic status; 33.7% were wage workers, 15.2% were street vendors, and 10.4% were unemployed. About 54 % had family incomes less than 10,000 baht (300 US Dollars) per month, and 41.6% addressed that their incomes were not adequate for daily living. Although the majority of them (63.7%) did not have to pay for hospital visits, they still had to pay for public transportation and could not earn a wage or any income on the hospital visit day. The first three physical symptoms they experienced were knee pain (60.5%) due to being overweight, headache (47.0%), and insomnia (44.6%). About 45% stated that their incomes decreased after having chronic illnesses and 37.2% expressed that having lower incomes affected their living, 34.5% perceived being a burden, and 34.3% regret about depending on others. It can be concluded that adults with low socioeconomic status who experienced chronic illnesses and resided in an urban community area had complex needs. While caring for them, nurses should pay attention not only to a disease-related domain but also to a social-related domain. Reached-out clinics led by professional nurses who are well-prepared for primary medical care and home visit are strongly recommended. National Health Security Office should adopt this policy and develop an action plan to serve the needs of chronically ill adults with low socioeconomic status.

Keywords: chronic illnesses, urban community, socioeconomic status, symptom experiences, low incomes

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Authors: Nadir Atayev, Mehman Hasanov

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Future spacecraft will require a structural change in the way data is transmitted due to the increase in the volume of data required for space communication. Current radio frequency communication systems are already facing a bottleneck in the volume of data sent to the ground segment due to their technological and regulatory characteristics. To overcome these issues, free space optics communication plays an important role in the integrated terrestrial space network due to its advantages such as significantly improved data rate compared to traditional RF technology, low cost, improved security, and inter-satellite free space communication, as well as uses a laser beam, which is an optical signal carrier to establish satellite-ground & ground-to-satellite links. In this approach, there is a need for high-speed and energy-efficient systems as a base platform for sending high-volume video & audio data. Nano Satellite and its branch CubeSat platforms have more technical functionality than large satellites, wheres cover an important part of the space sector, with their Low-Earth-Orbit application area with low-cost design and technical functionality for building networks using different communication topologies. Along the research theme developed in this regard, the output parameter indicators for the FSO of the optical communication transceiver subsystem on the existing CubeSat platforms, and in the direction of improving the mentioned parameters of this communication methodology, 3D optical switch and laser beam controlled optical transponder with 2U CubeSat structural subsystems and application in the Low Earth Orbit satellite network topology, as well as its functional performance and structural parameters, has been studied accordingly.

Keywords: cubesat, free space optics, nano satellite, optical laser communication.

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Authors: Nannapus Saramad, Rewwadee Petsirasan, Jom Suwanno

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Background: This retrospective study design was to describe average blood pressure, blood pressure level, target blood pressure control rate post-stroke BP control in the year following discharge from Sichon hospital, Sichon District, Nakhon Si Thammarat province. The secondary data analysis was employed from the patient’s health records with patient or caregiver interview. A total of 232 eligible post-acute ischemic strokes in the year following discharge (2017-2018) were recruited. Methods: Data analyses were applied to identify the relationship values of single variables were determined through univariate analyses: The Chi-square test, Fisher exact test, the variables found to have a p-value < 0.2 were analyzed by the binary logistic regression Results: Most of the patients in this study were men 61.6%, an average age of 65.4 ± 14.8 years. Systolic blood pressure levels were in the grade 1-2 hypertension and diastolic pressure at optimal and normal at all times during the initial treatment through the present. The results revealed 25% among the groups under the age of 60 achieved BP control; 36.3% for older than 60 years group; and 27.9% for diabetic group. The multivariate analysis revealed the final relationship of four significant variables: 1) receiving calcium-channel blocker (p =.027); 2) medication adherence of antihypertensive (p = .024) 3) medication adherence of antiplatelet ( p = .020); and 4) medication behavior ( p = . 010) . Conclusion: The medical nurse and health care provider should promote their adherence to behavior to improve their blood pressure control.

Keywords: acute ischemic stroke, target blood pressure control, medication adherence, recurrence stroke

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Authors: Catarina Ramos Pereira, Jorge Rodrigues, Natália Oliveira, Jorge Machado, Maria Begoña Criado, Jorge Machado, Henri J. Greten

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Background: Parkinson's disease is a multi-system neurodegenerative disorder characterized by motor and non-motor symptoms. To slow disorder progression, different treatment options are now available, but in most cases, these therapeutic strategies also involve the presence of important side effects. This has led many patients to pursue complementary therapies, such as acupuncture, to alleviate PD symptoms. Therefore, an update on the efficacy of this treatment for patients of PD is of great value. This work presents a systematic review of the efficacy of acupuncture treatments in relieving PD symptoms. Methods: EMBASE, Medline, Pubmed, Science Direct, The Cochrane Library, Cochrane Central Register of Controlled Trials (Central), and Scielo databases were systematically searched from January 2011 through July 2021. Randomized controlled trials (RCTs) published in English with all types of acupuncture treatment were included. The selection and analysis of the articles were conducted by two blinding authors through the Rayyan application. Results: 720 potentially relevant articles were identified; 52 RCTs met our inclusion criteria. After the exclusion of 35, we found 17 eligible. The included RCTs reported positive effects for acupuncture plus conventional treatment compared with conventional treatment alone in the UPDRS score. Conclusions: Additional evidence should be supported by rigorous methodological strategies. Although firm conclusions cannot be drawn, acupuncture treatment, in the framework of an interdisciplinary care team, appears to have positive effects on PD symptoms.

Keywords: systematic review, Parkinson disease, acupuncture, traditional Chinese medicine

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Authors: Izabel Cristina Zattar, Gilberto Passos Lima, Guilherme Schünemann de Oliveira

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In Brazil, there are several institutions committed to the development of new businesses based on product innovation. Among them are business incubators, universities and science institutes. Business incubators can be defined as nurseries for new companies, which may be in the technology segment, discussed in this article. Business incubators provide services related to infrastructure, such as physical space and meeting rooms. Besides these services, incubators also offer assistance in the form of information and communication, access to finance, relationship networks and business monitoring and mentoring processes. Business incubators support not all technology companies. One of the business incubators tasks is to assess the nature and feasibility of new business proposals. To assist in this goal, this paper proposes a methodology for evaluating new business using the Analytic Hierarchy Process (AHP). This paper presents the concepts used in the assessing methodology application for new business, concepts that have been tested with positive results in practice. This study counts on three main steps: first, a hierarchy was built, based on new business manuals used by the business incubators. These books and manuals relate business selection requirements, such as the innovation status and other technological aspects. Then, a questionnaire was generated, in order to guide incubator experts in the parity comparisons at all hierarchy levels. The weights of each requirement are calculated from information obtained from the questionnaire responses. Finally, the proposed method was applied to evaluate five new business proposals, which were applying to be part of a company incubator. The main result is the classification of these new businesses, which helped the incubator experts to decide what companies were more eligible to work with. This classification may also be helpful to the decision-making process of business incubators in future selection processes.

Keywords: Analytic Hierarchy Process (AHP), Brazilian companies incubators, technology companies, incubator

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Authors: Jaiden Xuan Schraut, Leon Liu, Yiqiao Yin

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Computer vision in medical diagnosis has achieved a high level of success in diagnosing diseases with high accuracy. However, conventional classifiers that produce an image to-label result provides insufficient information for medical professionals to judge and raise concerns over the trust and reliability of a model with results that cannot be explained. In order to gain local insight into cancerous regions, separate tasks such as imaging segmentation need to be implemented to aid the doctors in treating patients, which doubles the training time and costs which renders the diagnosis system inefficient and difficult to be accepted by the public. To tackle this issue and drive AI-first medical solutions further, this paper proposes a multi-output network that follows a U-Net architecture for image segmentation output and features an additional convolutional neural networks (CNN) module for auxiliary classification output. Class activation maps are a method of providing insight into a convolutional neural network’s feature maps that leads to its classification but in the case of lung diseases, the region of interest is enhanced by U-net-assisted Class Activation Map (CAM) visualization. Therefore, our proposed model combines image segmentation models and classifiers to crop out only the lung region of a chest X-ray’s class activation map to provide a visualization that improves the explainability and is able to generate classification results simultaneously which builds trust for AI-led diagnosis systems. The proposed U-Net model achieves 97.61% accuracy and a dice coefficient of 0.97 on testing data from the COVID-QU-Ex Dataset which includes both diseased and healthy lungs.

Keywords: multi-output network model, U-net, class activation map, image classification, medical imaging analysis

Procedia PDF Downloads 205

Authors: Laid Fekih

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Background: Depression affects people in all communities across the world and in all aspects of their lives. Its spread varies from one country to another, can happen at any age and get rid of it is not easy. There is no clear policy in Algeria's higher education institutions to detect and treat these disorders or pay particular attention to those at risk. Identifying the prevalence of depression among Algerian students, its correlation with different variables, and studying gender differences in the light of a range of variables is necessary to develop an appropriate plan to raise the level of hope and love of life among students. Method: Random samples of 1500 University of Tlemcen students (967 girls and 533 boys), aged 19 to 24 years completed a self-administered questionnaire that included Beck's Depression Inventory ®-II (BDI®-II), (School Health Promotion: The Mood part), Other questions included in this survey focused on demographic characteristics including gender, age and year of study, academic performance (Annual Average Score (0-20) AAS), were examined. Results: The rate of depression (moderate, severe and extreme) varied from 03% to 13% among university students in Tlemcen University. There was no difference in the rates of depression in male and female students, which means that male and female students do have similar rates of depression. The rate of depression in the first-year of the study shows a higher score relative to students of other years. Depression has a negative relationship with academic performance, which means that depressed students have many difficulties in academic tasks at university. Conclusion: Depression among university students is an important center of interest in the world, not only because of the ease with which they can be followed, or the difficulties encountered during their studies and their technical courses but for the link between the level of depression and the quality of care of mental health services, especially if many students with mood and emotional problems don't meet the criteria for psychotherapy.

Keywords: depression, epidemiology, university students, academic performance

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Authors: Bryce Benson, Sooin Lee, Ashwin Belle

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Unrecognized or delayed identification of patient deterioration is a key cause of in-hospitals adverse events. Clinicians rely on vital signs monitoring to recognize patient deterioration. However, due to ever increasing nursing workloads and the manual effort required, vital signs tend to be measured and recorded intermittently, and inconsistently causing large gaps during patient monitoring. Additionally, during deterioration, the body’s autonomic nervous system activates compensatory mechanisms causing the vital signs to be lagging indicators of underlying hemodynamic decline. This study analyzes the predictive efficacy of the Analytic for Hemodynamic Instability (AHI) system, an automated tool that was designed to help clinicians in early identification of deteriorating patients. The lead time analysis in this retrospective observational study assesses how far in advance AHI predicted deterioration prior to the start of an episode of hemodynamic instability (HI) becoming evident through vital signs? Results indicate that of the 362 episodes of HI in this study, 308 episodes (85%) were correctly predicted by the AHI system with a median lead time of 57 minutes and an average of 4 hours (240.5 minutes). Of the 54 episodes not predicted, AHI detected 45 of them while the episode of HI was ongoing. Of the 9 undetected, 5 were not detected by AHI due to either missing or noisy input ECG data during the episode of HI. In total, AHI was able to either predict or detect 98.9% of all episodes of HI in this study. These results suggest that AHI could provide an additional ‘pair of eyes’ on patients, continuously filling the monitoring gaps and consequently giving the patient care team the ability to be far more proactive in patient monitoring and adverse event management.

Keywords: clinical deterioration prediction, decision support system, early warning system, hemodynamic status, physiologic monitoring

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Authors: Candela Contero Urgal

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Using realia to teach English for Specific Purposes (ESP) is a must, as it is thought to be designed to meet the students’ real needs in their professional life. Teachers are then expected to offer authentic materials and set students in authentic contexts where their learning outcomes can be highly meaningful. One way of engaging students is using social networks as a way to bridge the gap between their everyday life and their ESP learning outcomes. It is in ESP, particularly in Business English teaching, that our study focuses, as the ongoing process of digitalization is leading firms to use social media to communicate with potential clients. The present paper is aimed at carrying out a case study in which different digital tools are employed as a way to offer a collection of formats businesses are currently using so as to internationalize and advertise their products and services. A secondary objective of our study will then be to progress on the development of multidisciplinary competencies students are to acquire during their degree. A two-phased study will be presented. The first phase will cover the analysis of course tasks accomplished by undergraduate students at the University of Cadiz (Spain) in their third year of the Degree in Business Management and Administration by comparing the results obtained during the years 2019 to 2021. The second part of our study will present a survey conducted to these students in 2021 and 2022 so as to verify their interest in learning new ways to digitalize as well as internationalize their future businesses. Findings will confirm students’ interest in working with updated realia in their Business English lessons, as a consequence of their strong belief in the necessity to have authentic contexts and didactic resources. Despite the limitations social media can have as a means to teach business English, students will still find it highly beneficial since it will foster their familiarisation with the digital tools they will need to use when they get to the labour market.

Keywords: English for specific purposes, business English, internationalization of higher education, foreign language teaching

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Authors: D. López-Mancilla, J. M. Roblero-Villa

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Since 1990, the research on chaotic dynamics has received considerable attention, particularly in light of potential applications of this phenomenon in secure communications. Data encryption using chaotic systems was reported in the 90's as a new approach for signal encoding that differs from the conventional methods that use numerical algorithms as the encryption key. The algorithms for image encryption have received a lot of attention because of the need to find security on image transmission in real time over the internet and wireless networks. Known algorithms for image encryption, like the standard of data encryption (DES), have the drawback of low level of efficiency when the image is large. The encrypting based on chaos proposes a new and efficient way to get a fast and highly secure image encryption. In this work, a user interface for image encryption and a novel and easiest way to encrypt images using chaos are presented. The main idea is to reshape any image into a n-dimensional vector and combine it with vector extracted from a chaotic system, in such a way that the vector image can be hidden within the chaotic vector. Once this is done, an array is formed with the original dimensions of the image and turns again. An analysis of the security of encryption from the images using statistical analysis is made and is used a stage of optimization for image encryption security and, at the same time, the image can be accurately recovered. The user interface uses the algorithms designed for the encryption of images, allowing you to read an image from the hard drive or another external device. The user interface, encrypt the image allowing three modes of encryption. These modes are given by three different chaotic systems that the user can choose. Once encrypted image, is possible to observe the safety analysis and save it on the hard disk. The main results of this study show that this simple method of encryption, using the optimization stage, allows an encryption security, competitive with complicated encryption methods used in other works. In addition, the user interface allows encrypting image with chaos, and to submit it through any public communication channel, including internet.

Keywords: image encryption, chaos, secure communications, user interface

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Authors: Keh-Wen Carin Chuang, Kuan-Chou Chen

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Our society is in a constant state of change. Technology advancements continue to affect our daily lives. How we work, communicate and entertain ourselves has changed dramatically in the past decades. As our society learns to accept and adapt to the many different technological advances that seem to inundate every part of our lives, the education institutions must migrate from traditional methods of instruction to online education in order to take full advantage of the opportunities provided by these technology advancements. There are many benefits that can be gained for university and society from offering online programs by utilizing advanced technologies. But the programs must not be implemented carelessly. The key to providing a quality online program is the issue of perceived quality, which takes into account the viewpoint of all stakeholders involved. To truly ensure the institutional quality, however, a systemic view of all factors contributing to the quality must be analyzed and linked to one another — allowing education administrators to understand how each factor contributes to the perceived quality of online education. The perceived quality of an online program will be positively reinforced only through an organizational-wide effort that focuses on managed administration, augmenting online program branding, skilled faculty, supportive alumni, student satisfaction, and effective delivery systems — each of which is vital to a quality online program. This study focuses on the concept of quality assurance in the start-up, implementation, and sustainability of online education. A case of online MBA program will be analyzed to explore the quality assurance. The difficulties in promoting online education quality is the fact that universities are complex networks of disciplinary, social, economic, and political fiefdoms, both internal and external factors to the institutions. As such, the system analysis, a systems-thinking approach, on the issue of perceived quality is ideal to investigate the factors and how each factor contributes to the perceived quality in the online education domain.

Keywords: systems thinking, quality assurance, online education, MBA program

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Authors: F. Longo, G. Granello, G. Tecchio, F. Da Porto

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Unreinforced masonry (URM) infill walls are widely used throughout the world, also in seismic prone regions, as partitions in reinforced concrete building frames. Even if they do not represent structural elements, they can dramatically affect both strength and stiffness of RC structures by acting as a diagonal strut, modifying shear and displacements distribution along the building height, with uncertain consequences on structural safety. In the last decades, many refined models have been developed to describe infill walls effect on frame structural behaviour, but generally restricted to in-plane actions. Only very recently some new approaches were implemented to consider in-plane/out-of-plane interaction of URM infill walls in progressive collapse simulations. In the present work, a particularly promising macro-model was adopted for the progressive collapse analysis of infilled RC frames. The model allows to consider the bi-directional interaction in terms of displacement and strength capacity for URM infills, and to remove the infill contribution when the URM wall is supposed to fail during the analysis process. The model was calibrated on experimental data regarding two different URM panels thickness, modelling with particular care the post-critic softening branch. A frame specimen set representing the most common Italian structures was built considering two main normative approaches: a traditional design philosophy, corresponding to structures erected between 50’s-80’s basically designed to support vertical loads, and a seismic design philosophy, corresponding to current criteria that take into account horizontal actions. Non-Linear Static analyses were carried out on the specimen set and some preliminary evaluations were drawn in terms of different performance exhibited by the RC frame when the contemporary effect of the out-of-plane damage is considered for the URM infill.

Keywords: infill Panels macromodels, in plane-out of plane interaction, RC frames, URM infills

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Authors: Nigina Toktasynova, Sholpan Sagyndykova, Zhanat Kenzhebayeva, Maksat Kalimoldayev, Mariya Ishimova, Irbulat Utepbergenov

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Any business needs a stable operation and continuous improvement, therefore it is necessary to constantly interact with the environment, to analyze the work of the enterprise in terms of employees, executives and consumers, as well as to correct any inconsistencies of certain types of processes and their aggregate. In the case of heat supply organizations, in addition to suppliers, local legislation must be considered which often is the main regulator of pricing of services. In this case, the process approach used to build a functional organizational structure in these types of businesses in Kazakhstan is a challenge not only in the implementation, but also in ways of analyzing the employee's salary. To solve these problems, we investigated the management system of heating enterprise, including strategic planning based on the balanced scorecard (BSC), quality management in accordance with the standards of the Quality Management System (QMS) ISO 9001 and analysis of the system based on expert judgment using fuzzy inference. To carry out our work we used the theory of fuzzy sets, the QMS in accordance with ISO 9001, BSC according to the method of Kaplan and Norton, method of construction of business processes according to the notation IDEF0, theory of modeling using Matlab software simulation tools and graphical programming LabVIEW. The results of the work are as follows: We determined possibilities of improving the management of heat-supply plant-based on QMS; after the justification and adaptation of software tool it has been used to automate a series of functions for the management and reduction of resources and for the maintenance of the system up to date; an application for the analysis of the QMS based on fuzzy inference has been created with novel organization of communication software with the application enabling the analysis of relevant data of enterprise management system.

Keywords: balanced scorecard, heat supply, quality management system, the theory of fuzzy sets

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Authors: Sabah Yasin, Anum Obaid

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Abstract—Working women in Pakistan should not be neglected, as women make up to half of the population, and are highly educated and diversified in their skills and capabilities. With a shift in global economic and social demands the obligations of a women have altered significantly, impacted by the dual pressures of career and personal life. Despite global efforts to improve economic empowerment and health of women, through Sustainable Development Goals, they suffer from social, economic, psychological and physiological challenges. A sound understanding of working women’s nutrition and health-related stress is a prompt necessity, in areas like Faisalabad, thus leading to a public health issue. The current qualitative study is grounded under the paradigm of in-depth interviews with working women, currently working full time in Faisalabad. Participants collected through snowball sampling were women ages 30-40. This study explores the perceptions and experiences as well as barriers and factors effecting the overall wellbeing of working women, regarding nutrition and health-related stress. Findings of the current study disclosed that the nutritional and health well-being of working women in Faisalabad suffers from the impact of various stressors, like long working hours, excessive workload, low income, poor work place culture, unavailability of healthy food choices at work, lack of time, lack of self-care, unattended nutritional deficiencies and overburdened share of responsibilities. Hence, these findings highlight the need for effective strategies and support systems that will address the unique stressors faced by working women and also by educating them in changing their attitudes and understanding psychosocial barriers that impede their ability to maintain nutrition and overall well-being.

Keywords: health triangle, lifestyle behaviors, nutrition-related, professional life, stress, working women

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Authors: Jie Ji, Jing Xu, Yuehong Zhuang, Xiangqing Kang, Ying Qian, Ping Zhou, Di Xue

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Background: In 2014, there were 28,341 health professionals in Pudong new area of Shanghai and the number per 1000 population was 5.199, 55.55% higher than that in 2006. But it was always less than the average number of health professionals per 1000 population in Shanghai from 2006 to 2014. Therefore, allocation planning for the health professionals in Pudong new area has become a high priority task in order to meet the future demands of health care. In this study, we constructed an objective-based system dynamics model to forecast the number of health professionals in Pudong new area of Shanghai in 2020. Methods: We collected the data from health statistics reports and previous survey of human resources in Pudong new area of Shanghai. Nine experts, who were from health administrative departments, public hospitals and community health service centers, were consulted to estimate the current and future status of nine variables used in the system dynamics model. Based on the objective of the number of health professionals per 1000 population (8.0) in Shanghai for 2020, the system dynamics model for health professionals in Pudong new area of Shanghai was constructed to forecast the number of health professionals needed in Pudong new area in 2020. Results: The system dynamics model for health professionals in Pudong new area of Shanghai was constructed. The model forecasted that there will be 37,330 health professionals (6.433 per 1000 population) in 2020. If the success rate of health professional recruitment changed from 20% to 70%, the number of health professionals per 1000 population would be changed from 5.269 to 6.919. If this rate changed from 20% to 70% and the success rate of building new beds changed from 5% to 30% at the same time, the number of health professionals per 1000 population would be changed from 5.269 to 6.923. Conclusions: The system dynamics model could be used to simulate and forecast the health professionals. But, if there were no significant changes in health policies and management system, the number of health professionals per 1000 population would not reach the objectives in Pudong new area in 2020.

Keywords: allocation planning, forecast, health professional, system dynamics

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Authors: Melvin Ouma

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Language is one of the most crucial tools in medical interaction. Its importance is as great today as it was many decades ago. Difficulty in openly discussing certain diseases and body parts is one of the challenges in language use in medical contexts. Guided by H. P. Grice’s Cooperative Principle, this paper explores the flouting of the cooperative principles in Swahili speaking medical setting. The paper examines how men flout the maxims using the Swahili language when reporting reproductive health problems to the doctor. The data used was gathered from a qualitative study carried out in a reproductive health clinic in a public facility in Nakuru County, Kenya. All the research protocols were observed by acquiring all the research permits. Respondents' ethical considerations of consent, privacy, and confidentiality were observed. The respondents recruited were men who visited the reproductive health clinic and voluntarily agreed to participate in the study without coercion or compensation. Participant observation was the key data collection tool, with the doctor and patient conversation digitally recorded. The researcher was allowed into the clinic in a socially acceptable role. Male patients flouted the maxims of quantity, quality, relation, and manner in order to describe their reproductive health problems without embarrassment using the Swahili language. The flouting was done through the discursive strategies of narration and circumlocution. Flouting of the maxims was acceptable to the doctor and patient due to the fact that sexual intercourse and private body parts are taboo topics and uncomfortable to talk about. The quality of health care received by the patient depended on the doctor’s patience when all the maxims were flouted. In the reproductive health clinic, flouting of maxims hindered communication and, at the same time, enhanced communication between the doctor and patient.

Keywords: cooperative principle, doctor, men, reproductive health

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Authors: Roaa Al Sharif, Salsabil Abo Al-Azayem, Nimah Alsomali, Wjoud Alsaeed, Nawal Alshammari, Abdulaziz Alwatban, Yaseen Alrabae, Razan Orfali, Faisal Alqarni, Ahmad Alrasheedi

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from various countries have revealed that nurses possess only a basic understanding of the GCS. Regarding this matter, limited knowledge is available about the situation in Saudi Arabia. Overall, the available research suggests that there is room for improvement in the knowledge of the GCS among nurses in Saudi Arabia. Further training and education programs may be beneficial in enhancing nurses' understanding and application of the GCS in clinical practice. Objective: To determine the level of knowledge and competence in assessing the GCS among staff nurses and to identify factors that might influence their knowledge at King Fahd Medical City in Riyadh, Saudi Arabia. Methods: A descriptive, cross-sectional survey involving 199 KFMC staff nurses was conducted. Nurses were provided with a structured questionnaire, and data were collected and analyzed using SPSS version 16, employing descriptive statistics and Chi-square tests. Results: The majority, 81.4% of nurses, had an average level of knowledge in assessing the Glasgow Coma Scale (GCS). The mean score for measuring the level of knowledge among staff nurses in GCS assessment was 8.8 ± 1.826. Overall, 13.6% of respondents demonstrated good knowledge of the GCS, scoring between 11 and 15 points, while only 5% of nurses exhibited poor knowledge of the GCS assessment. There was a significant correlation between knowledge and nurses' departments (χ2(2) = 19.184, p < 0.001). χ2(2) = 19.184," representing a Chi-square statistic with 2 degrees of freedom used to test the association between categorical variables in the data analysis. Conclusion: The findings indicate that knowledge of GCS assessment among staff nurses in a single center in Saudi Arabia is moderate. Therefore, there is a need for continuous education programs to enhance their competence in using this assessment.

Keywords: Glasgow Coma Scale, brain injury, nurses’ knowledge assessment, continuous education programs

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