Search results for: one side class algorithm

Authors: Heewon Jeong, Seongpyo Kim, Joon Ha Kim

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Over the last few tens of years, the coastal regions of Korea have experienced red tide algal blooms, which are harmful and toxic to both humans and marine organisms due to their potential threat. It was accelerated owing to eutrophication by human activities, certain oceanic processes, and climate change. Previous studies have tried to monitoring and predicting the algae concentration of the ocean with the bio-optical algorithms applied to color images of the satellite. However, the accurate estimation of algal blooms remains problems to challenges because of the complexity of coastal waters. Therefore, this study suggests a new method to identify the concentration of red tide algal bloom from images of geostationary ocean color imager (GOCI) which are representing the water environment of the sea in Korea. The method employed GOCI images, which took the water leaving radiances centered at 443nm, 490nm and 660nm respectively, as well as observed weather data (i.e., humidity, temperature and atmospheric pressure) for the database to apply optical characteristics of algae and train deep learning algorithm. Convolution neural network (CNN) was used to extract the significant features from the images. And then artificial neural network (ANN) was used to estimate the concentration of algae from the extracted features. For training of the deep learning model, backpropagation learning strategy is developed. The established methods were tested and compared with the performances of GOCI data processing system (GDPS), which is based on standard image processing algorithms and optical algorithms. The model had better performance to estimate algae concentration than the GDPS which is impossible to estimate greater than 5mg/m³. Thus, deep learning model trained successfully to assess algae concentration in spite of the complexity of water environment. Furthermore, the results of this system and methodology can be used to improve the performances of remote sensing. Acknowledgement: This work was supported by the 'Climate Technology Development and Application' research project (#K07731) through a grant provided by GIST in 2017.

Keywords: deep learning, algae concentration, remote sensing, satellite

Procedia PDF Downloads 183

Authors: Tiptunya Duangsri, Panwilai Chomchid, Natchanok Jansawang

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This research study was to investigate of education decisions must be made which a part of it should be passed on to future generations as obligatory for all members of a chemistry class for students who will prepare themselves for a special position. The descriptions of instructional design were provided and the recent criticisms are discussed. This research study to an outline of an integrative framework for the description of information and the instructional design model give structure to negotiate a semblance of conscious understanding. The aims of this study are to describe the instructional design model for comparisons between students’ genders of their effects on STEM educational learning achievement motives to their science attitudes and logical thinking abilities with a sample size of 18 students at the 11th grade level with the cluster random sampling technique in Mahawichanukul School were designed. The chemistry learning environment was administered with the STEM education method. To build up the 5-instrument lesson instructional plan issues were instructed innovations, the 30-item Logical Thinking Test (LTT) on 5 scales, namely; Inference, Recognition of Assumptions, Deduction, Interpretation and Evaluation scales was used. Students’ responses of their perceptions with the Test Of Chemistry-Related Attitude (TOCRA) were assessed of their attitude in science toward chemistry. The validity from Index Objective Congruence value (IOC) checked by five expert specialist educator in two chemistry classroom targets in STEM education, the E1/E2 process were equaled evidence of 84.05/81.42 which results based on criteria are higher than of 80/80 standard level with the IOC from the expert educators. Comparisons between students’ learning achievement motives with STEM educational model on stoichiometry issue in chemistry classes with different genders were differentiated at evidence level of .05, significantly. Associations between students’ learning achievement motives on their posttest outcomes and logical thinking abilities, the predictive efficiency (R2) values indicate that 69% and 70% of the variances in different male and female student groups of their logical thinking abilities. The predictive efficiency (R2) values indicate that 73%; and 74% of the variances in different male and female student groups of their science attitudes toward chemistry were associated. Statistically significant on students’ perceptions of their chemistry learning classroom environment and their science attitude toward chemistry when using the MCI and TOCRA, the predictive efficiency (R2) values indicated that 72% and 74% of the variances in different male and female student groups of their chemistry classroom climate, consequently. Suggestions that supporting chemistry or science teachers from science, technology, engineering and mathematics (STEM) in addressing complex teaching and learning issues related instructional design to develop, teach, and assess traditional are important strategies with a focus on STEM education instructional method.

Keywords: development, the instructional design model, students learning achievement motives, science attitudes with STEM educational model, stoichiometry issue, chemistry classes, genders

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Authors: B. S. Premalatha, Kausalya Sahani

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Background: Glomus jugulare tumors arise within the jugular foramen and are commonly seen in females particularly on the left side. Surgical excision of the tumor may cause lower cranial nerve deficits. Cranial nerve involvement produces hoarseness of voice, slurred speech, and dysphagia along with other physical symptoms, thereby affecting the quality of life of individuals. Though oncological clearance is mainly emphasized on while treating these individuals, little importance is given to their communication, voice and swallowing problems, which play a crucial part in daily functioning. Objective: To examine the functions of voice, speech and swallowing outcomes of the subjects, following excision of glomus jugulare tumor. Methods: Two female subjects aged 56 and 62 years had come with a complaint of change in voice, inability to swallow and reduced clarity of speech following surgery for left glomus jugulare tumor were participants of the study. Their surgical information revealed multiple cranial nerve palsies involving the left facial, left superior and recurrent branches of the vagus nerve, left pharyngeal, left soft palate, left hypoglossal and vestibular nerves. Functional outcomes of voice, speech and swallowing were evaluated by perceptual and objective assessment procedures. Assessment included the examination of oral structures and functions, dysarthria by Frenchey dysarthria assessment, cranial nerve functions and swallowing functions. MDVP and Dr. Speech software were used to evaluate acoustic parameters of voice and quality of voice respectively. Results: The study revealed that both the subjects, subsequent to excision of glomus jugulare tumor, showed a varied picture of affected oral structure and functions, articulation, voice and swallowing functions. The cranial nerve assessment showed impairment of the vagus, hypoglossal, facial and glossopharyngeal nerves. Voice examination indicated vocal cord paralysis associated with breathy quality of voice, weak voluntary cough, reduced pitch and loudness range, and poor respiratory support. Perturbation parameters as jitter, shimmer were affected along with s/z ratio indicative of voice fold pathology. Reduced MPD(Maximum Phonation Duration) of vowels indicated that disturbed coordination between respiratory and laryngeal systems. Hypernasality was found to be a prominent feature which reduced speech intelligibility. Imprecise articulation was seen in both the subjects as the hypoglossal nerve was affected following surgery. Injury to vagus, hypoglossal, gloss pharyngeal and facial nerves disturbed the function of swallowing. All the phases of swallow were affected. Aspiration was observed before and during the swallow, confirming the oropharyngeal dysphagia. All the subsystems were affected as per Frenchey Dysarthria Assessment signifying the diagnosis of flaccid dysarthria. Conclusion: There is an observable communication and swallowing difficulty seen following excision of glomus jugulare tumor. Even with complete resection, extensive rehabilitation may be necessary due to significant lower cranial nerve dysfunction. The finding of the present study stresses the need for involvement of as speech and swallowing therapist for pre-operative counseling and assessment of functional outcomes.

Keywords: functional outcome, glomus jugulare tumor excision, multiple cranial nerve impairment, speech and swallowing

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Authors: Mohanad Al-Behadili, Xiang Song, Djamila Ouelhadj, Alex Fraess-Ehrfeld

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In off-shore wind farms, turbine blade inspection accessibility under various sea states is very challenging and greatly affects the downtime of wind turbines. Maintenance of any offshore system is not an easy task due to the restricted logistics and accessibility. The multirotor unmanned helicopter is of increasing interest in inspection applications due to its manoeuvrability and payload capacity. These advantages increase when many of them are deployed simultaneously in a swarm. Hence this paper proposes a drone swarm framework for inspecting offshore wind turbine blades and nacelles so as to reduce downtime. One of the big challenges of this task is that when operating a drone swarm, an individual drone may not have enough power to fly and communicate during missions and it has no capability of refueling due to its small size. Once the drone power is drained, there are no signals transmitted and the links become intermittent. Vessels equipped with 5G masts and small power units are utilised as platforms for drones to recharge/swap batteries. The research work aims at designing a smart energy management system, which provides automated vessel and drone routing and recharging plans. To achieve this goal, a novel mathematical optimisation model is developed with the main objective of minimising the number of drones and vessels, which carry the charging stations, and the downtime of the wind turbines. There are a number of constraints to be considered, such as each wind turbine must be inspected once and only once by one drone; each drone can inspect at most one wind turbine after recharging, then fly back to the charging station; collision should be avoided during the drone flying; all wind turbines in the wind farm should be inspected within the given time window. We have developed a real-time Ant Colony Optimisation (ACO) algorithm to generate real-time and near-optimal solutions to the drone swarm routing problem. The schedule will generate efficient and real-time solutions to indicate the inspection tasks, time windows, and the optimal routes of the drones to access the turbines. Experiments are conducted to evaluate the quality of the solutions generated by ACO.

Keywords: drone swarm, routing, scheduling, optimisation model, ant colony optimisation

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Authors: Natia Jalagonia, Tinatin Kuchukhidze

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Polymer electrolytes (PE) play an important part in electrochemical devices such as batteries and fuel cells. To achieve optimal performance, the PE must maintain a high ionic conductivity and mechanical stability at both high and low relative humidity. The polymer electrolyte also needs to have excellent chemical stability for long and robustness. According to the prevailing theory, ionic conduction in polymer electrolytes is facilitated by the large-scale segmental motion of the polymer backbone, and primarily occurs in the amorphous regions of the polymer electrolyte. Crystallinity restricts polymer backbone segmental motion and significantly reduces conductivity. Consequently, polymer electrolytes with high conductivity at room temperature have been sought through polymers which have highly flexible backbones and have largely amorphous morphology. The interest in polymer electrolytes was increased also by potential applications of solid polymer electrolytes in high energy density solid state batteries, gas sensors and electrochromic windows. Conductivity of 10-3 S/cm is commonly regarded as a necessary minimum value for practical applications in batteries. At present, polyethylene oxide (PEO)-based systems are most thoroughly investigated, reaching room temperature conductivities of 10-7 S/cm in some cross-linked salt in polymer systems based on amorphous PEO-polypropylene oxide copolymers.. It is widely accepted that amorphous polymers with low glass transition temperatures Tg and a high segmental mobility are important prerequisites for high ionic conductivities. Another necessary condition for high ionic conductivity is a high salt solubility in the polymer, which is most often achieved by donors such as ether oxygen or imide groups on the main chain or on the side groups of the PE. It is well established also that lithium ion coordination takes place predominantly in the amorphous domain, and that the segmental mobility of the polymer is an important factor in determining the ionic mobility. Great attention was pointed to PEO-based amorphous electrolyte obtained by synthesis of comb-like polymers, by attaching short ethylene oxide unit sequences to an existing amorphous polymer backbone. The aim of presented work is to obtain of solid polymer electrolyte membranes using PMHS as a matrix. For this purpose the hydrosilylation reactions of α,ω-bis(trimethylsiloxy)methyl¬hydrosiloxane with allyl triethylene-glycol mo¬nomethyl ether and vinyltriethoxysilane at 1:28:7 ratio of initial com¬pounds in the presence of Karstedt’s catalyst, platinum hydrochloric acid (0.1 M solution in THF) and platinum on the carbon catalyst in 50% solution of anhydrous toluene have been studied. The synthesized olygomers are vitreous liquid products, which are well soluble in organic solvents with specific viscosity ηsp ≈ 0.05 - 0.06. The synthesized olygomers were analysed with FTIR, 1H, 13C, 29Si NMR spectroscopy. Synthesized polysiloxanes were investigated with wide-angle X-ray, gel-permeation chromatography, and DSC analyses. Via sol-gel processes of doped with lithium trifluoromethylsulfonate (triflate) or lithium bis¬(trifluoromethylsulfonyl)¬imide polymer systems solid polymer electrolyte membranes have been obtained. The dependence of ionic conductivity as a function of temperature and salt concentration was investigated and the activation energies of conductivity for all obtained compounds are calculated

Keywords: synthesis, PMHS, membrane, electrolyte

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Authors: Mohammad Al-Refai, Majed Wakid

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Introduction: Soil-transmitted diseases (STD) are caused by intestinal worms that are transmitted via various routes into the human body resulting in various clinical manifestations. The intestinal worms causing these infections are known as soil transmitted helminths (STH), including Hook worms, Ascaris lumbricoides (A. lumbricoides), Trichuris trichiura (T. trichiura), and Strongyloides sterocoralis (S. sterocoralis). Objectives: The aim of this study was to investigate the prevalence of STH among newly arrived expatriate labors in Jeddah city, Saudi Arabia, using three different techniques (direct smears, sedimentation concentration, and real-time PCR). Methods: A total of 188 stool specimens were collected and investigated at the parasitology laboratory in the Special Infectious Agents Unit at King Fahd Medical Research Center, King Abdulaziz University in Jeddah, Saudi Arabia. Microscopic examination of wet mount preparations using normal saline and Lugols Iodine was carried out, followed by the formal ether sedimentation method. In addition, real-time PCR was used as a molecular tool to detect several STH and hookworm speciation. Results: Out of 188 stool specimens analyzed, in addition to STH parasite, several other types were detected. 9 samples (4.79%) were positive for Entamoeba coli, 7 samples (3.72%) for T. trichiura, 6 samples (3.19%) for Necator americanus, 4 samples (2.13%) for S. sterocoralis, 4 samples (2.13%) for A. lumbricoides, 4 samples (2.13%) for E. histolytica, 3 samples (1.60%) for Blastocystis hominis, 2 samples (1.06%) for Ancylostoma duodenale, 2 samples (1.06%) for Giardia lamblia, 1 sample (0.53%) for Iodamoeba buetschlii, 1 sample (0.53%) for Hymenolepis nana, 1 sample (0.53%) for Endolimax nana, and 1 sample (0.53%) for Heterophyes heterophyes. Out of the 35 infected cases, 26 revealed single infection, 8 with double infections, and only one triple infection of different STH species and other intestinal parasites. Higher rates of STH infections were detected among housemaids (11 cases) followed by drivers (7 cases) when compared to other occupations. According to educational level, illiterate participants represent the majority of infected workers (12 cases). The majority of workers' positive cases were from the Philippines. In comparison between laboratory techniques, out of the 188 samples screened for STH, real-time PCR was able to detect the DNA in (19/188) samples followed by Ritchie sedimentation technique (18/188), and direct wet smear (7/188). Conclusion: STH infections are a major public health issue to healthcare systems around the world. Communities must be educated on hygiene practices and the severity of such parasites to human health. As far as drivers and housemaids come to close contact with families, including children and elderlies. This may put family members at risk of developing serious side effects related to STH, especially as the majority of workers were illiterate, lacking the basic hygiene knowledge and practices. We recommend the official authority in Jeddah and around the kingdom of Saudi Arabia to revise the standard screening tests for newly arrived workers and enforce regular follow-up inspections to minimize the chances of the spread of STH from expatriate workers to the public.

Keywords: expatriate labors, Jeddah, prevalence, soil transmitted helminths

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Authors: Sonia Butalia, Huong Luu, Alexis Guigue, Karen J. B. Martins, Khanh Vu, Scott W. Klarenbach

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Obesity-related health conditions impose a substantial economic burden on payers due to increased healthcare use. Estimates of healthcare resource use and costs associated with obesity-related comorbidities are needed to inform policies and interventions targeting these conditions. Methods: Adults living with obesity were identified (a procedure-related body mass index code for class 2/3 obesity between 2012 and 2019 in Alberta, Canada; excluding those with bariatric surgery), and outcomes were compared over 1-year (2019/2020) between those who had and did not have specific obesity-related comorbidities. The probability of using a healthcare service (based on the odds ratio of a zero [OR-zero] cost) was compared; 95% confidence intervals (CI) were reported. Logistic regression and a generalized linear model with log link and gamma distribution were used for total healthcare cost comparisons ($CDN); cost ratios and estimated cost differences (95% CI) were reported. Potential socio-demographic and clinical confounders were adjusted for, and incremental cost differences were representative of a referent case. Results: A total of 220,190 adults living with obesity were included; 44% had hypertension, 25% had osteoarthritis, 24% had type-2 diabetes, 17% had cardiovascular disease, 12% had insulin resistance, 9% had chronic back pain, and 4% of females had polycystic ovarian syndrome (PCOS). The probability of hospitalization, ED visit, and ambulatory care was higher in those with a following obesity-related comorbidity versus those without: chronic back pain (hospitalization: 1.8-times [OR-zero: 0.57 [0.55/0.59]] / ED visit: 1.9-times [OR-zero: 0.54 [0.53/0.56]] / ambulatory care visit: 2.4-times [OR-zero: 0.41 [0.40/0.43]]), cardiovascular disease (2.7-times [OR-zero: 0.37 [0.36/0.38]] / 1.9-times [OR-zero: 0.52 [0.51/0.53]] / 2.8-times [OR-zero: 0.36 [0.35/0.36]]), osteoarthritis (2.0-times [OR-zero: 0.51 [0.50/0.53]] / 1.4-times [OR-zero: 0.74 [0.73/0.76]] / 2.5-times [OR-zero: 0.40 [0.40/0.41]]), type-2 diabetes (1.9-times [OR-zero: 0.54 [0.52/0.55]] / 1.4-times [OR-zero: 0.72 [0.70/0.73]] / 2.1-times [OR-zero: 0.47 [0.46/0.47]]), hypertension (1.8-times [OR-zero: 0.56 [0.54/0.57]] / 1.3-times [OR-zero: 0.79 [0.77/0.80]] / 2.2-times [OR-zero: 0.46 [0.45/0.47]]), PCOS (not significant / 1.2-times [OR-zero: 0.83 [0.79/0.88]] / not significant), and insulin resistance (1.1-times [OR-zero: 0.88 [0.84/0.91]] / 1.1-times [OR-zero: 0.92 [0.89/0.94]] / 1.8-times [OR-zero: 0.56 [0.54/0.57]]). After fully adjusting for potential confounders, the total healthcare cost ratio was higher in those with a following obesity-related comorbidity versus those without: chronic back pain (1.54-times [1.51/1.56]), cardiovascular disease (1.45-times [1.43/1.47]), osteoarthritis (1.36-times [1.35/1.38]), type-2 diabetes (1.30-times [1.28/1.31]), hypertension (1.27-times [1.26/1.28]), PCOS (1.08-times [1.05/1.11]), and insulin resistance (1.03-times [1.01/1.04]). Conclusions: Adults with obesity who have specific disease-related health conditions have a higher probability of healthcare use and incur greater costs than those without specific comorbidities; incremental costs are larger when other obesity-related health conditions are not adjusted for. In a specific referent case, hypertension was costliest (44% had this condition with an additional annual cost of $715 [$678/$753]). If these findings hold for the Canadian population, hypertension in persons with obesity represents an estimated additional annual healthcare cost of $2.5 billion among adults living with obesity (based on an adult obesity rate of 26%). Results of this study can inform decision making on investment in interventions that are effective in treating obesity and its complications.

Keywords: administrative data, healthcare cost, obesity-related comorbidities, real world evidence

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Authors: Dávid Kovács, Bálint Csanády, Dániel Boros, Iván Ivkovic, Lóránt Nagy, Dalma Tóth-Lakits, László Márkus, András Lukács

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The modeling practice of financial instruments has seen significant change over the last decade due to the recognition of time-dependent and stochastically changing correlations among the market prices or the prices and market characteristics. To represent this phenomenon, the Stochastic Correlation Process (SCP) has come to the fore in the joint modeling of prices, offering a more nuanced description of their interdependence. This approach has allowed for the attainment of realistic tail dependencies, highlighting that prices tend to synchronize more during intense or volatile trading periods, resulting in stronger correlations. Evidence in statistical literature suggests that, similarly to the volatility, the SCP of certain stock prices follows rough paths, which can be described using fractional differential equations. However, estimating parameters for these equations often involves complex and computation-intensive algorithms, creating a necessity for alternative solutions. In this regard, the Fractional Ornstein-Uhlenbeck (fOU) process from the family of fractional processes offers a promising path. We can effectively describe the rough SCP by utilizing certain transformations of the fOU. We employed neural networks to understand the behavior of these processes. We had to develop a fast algorithm to generate a valid and suitably large sample from the appropriate process to train the network. With an extensive training set, the neural network can estimate the process parameters accurately and efficiently. Although the initial focus was the fOU, the resulting model displayed broader applicability, thus paving the way for further investigation of other processes in the realm of financial mathematics. The utility of SCP extends beyond its immediate application. It also serves as a springboard for a deeper exploration of fractional processes and for extending existing models that use ordinary Wiener processes to fractional scenarios. In essence, deploying both SCP and fractional processes in financial models provides new, more accurate ways to depict market dynamics.

Keywords: fractional Ornstein-Uhlenbeck process, fractional stochastic processes, Heston model, neural networks, stochastic correlation, stochastic differential equations, stochastic volatility

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Authors: Camille Van Eupen, Dirk Maes, Marc Herremans, Kristijn R. R. Swinnen, Ben Somers, Stijn Luca

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In ecology, species distribution models are commonly implemented to study species-environment relationships. These models increasingly rely on opportunistic citizen science data when high-quality species records collected through standardized recording protocols are unavailable. While these opportunistic data are abundant, uncertainty is usually high, e.g., due to observer effects or a lack of metadata. Data quality filtering is often used to reduce these types of uncertainty in an attempt to increase the value of studies relying on opportunistic data. However, filtering should not be performed blindly. In this study, recommendations are built for data quality filtering of opportunistic species occurrence data that are used as input for species distribution models. Using an extensive database of 5.7 million citizen science records from 255 species in Flanders, the impact on model performance was quantified by applying three data quality filters, and these results were linked to species traits. More specifically, presence records were filtered based on record attributes that provide information on the observation process or post-entry data validation, and changes in the area under the receiver operating characteristic (AUC), sensitivity, and specificity were analyzed using the Maxent algorithm with and without filtering. Controlling for sample size enabled us to study the combined impact of data quality filtering, i.e., the simultaneous impact of an increase in data quality and a decrease in sample size. Further, the variation among species in their response to data quality filtering was explored by clustering species based on four traits often related to data quality: commonness, popularity, difficulty, and body size. Findings show that model performance is affected by i) the quality of the filtered data, ii) the proportional reduction in sample size caused by filtering and the remaining absolute sample size, and iii) a species ‘quality profile’, resulting from a species classification based on the four traits related to data quality. The findings resulted in recommendations on when and how to filter volunteer generated and opportunistically collected data. This study confirms that correctly processed citizen science data can make a valuable contribution to ecological research and species conservation.

Keywords: citizen science, data quality filtering, species distribution models, trait profiles

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Authors: F. DelGaudio, H. Gill

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Resuscitation during cardiopulmonary (CPA) arrest is dynamic, high stress, high acuity situation, which can easily lead to communication breakdown, and errors. The care of these high acuity patients has also been shown to increase physiologic stress and task saturation of providers, which can negatively impact the care being provided. These difficulties are further complicated during a global pandemic and pose a significant safety risk to bedside providers. Nurse-led codes are a relatively new concept that may be a potential solution for alleviating some of these difficulties. An experienced nurse who has completed advanced cardiac life support (ACLS), and additional training, assumed the responsibility of directing the mechanics of the appropriate ACLS algorithm. This was done in conjunction with a physician who also acted as a physician leader. The additional nurse-led code training included a multi-disciplinary in situ simulation of a CPA on a suspected COVID-19 patient. During the CPA, the nurse leader’s responsibilities include: ensuring adequate compression depth and rate, minimizing interruptions in chest compressions, the timing of rhythm/pulse checks, and appropriate medication administration. In addition, the nurse leader also functions as a last line safety check for appropriate personal protective equipment and limiting exposure of staff. The use of nurse-led codes for CPA has shown to decrease the cognitive overload and task saturation for the physician, as well as limiting the number of staff being exposed to a potentially infectious patient. The real-world application has allowed physicians to perform and oversee high-risk procedures such as intubation, line placement, and point of care ultrasound, without sacrificing the integrity of the resuscitation. Nurse-led codes have also given the physician the bandwidth to review pertinent medical history, advanced directives, determine reversible causes, and have the end of life conversations with family. While there is a paucity of research on the effectiveness of nurse-led codes, there are many potentially significant benefits. In addition to its value during a pandemic, it may also be beneficial during complex circumstances such as extracorporeal cardiopulmonary resuscitation.

Keywords: cardiopulmonary arrest, COVID-19, nurse-led code, task saturation

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Authors: Fazıl Gökgöz, Fahrettin Filiz

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Load forecasting has become crucial in recent years and become popular in forecasting area. Many different power forecasting models have been tried out for this purpose. Electricity load forecasting is necessary for energy policies, healthy and reliable grid systems. Effective power forecasting of renewable energy load leads the decision makers to minimize the costs of electric utilities and power plants. Forecasting tools are required that can be used to predict how much renewable energy can be utilized. The purpose of this study is to explore the effectiveness of LSTM-based neural networks for estimating renewable energy loads. In this study, we present models for predicting renewable energy loads based on deep neural networks, especially the Long Term Memory (LSTM) algorithms. Deep learning allows multiple layers of models to learn representation of data. LSTM algorithms are able to store information for long periods of time. Deep learning models have recently been used to forecast the renewable energy sources such as predicting wind and solar energy power. Historical load and weather information represent the most important variables for the inputs within the power forecasting models. The dataset contained power consumption measurements are gathered between January 2016 and December 2017 with one-hour resolution. Models use publicly available data from the Turkish Renewable Energy Resources Support Mechanism. Forecasting studies have been carried out with these data via deep neural networks approach including LSTM technique for Turkish electricity markets. 432 different models are created by changing layers cell count and dropout. The adaptive moment estimation (ADAM) algorithm is used for training as a gradient-based optimizer instead of SGD (stochastic gradient). ADAM performed better than SGD in terms of faster convergence and lower error rates. Models performance is compared according to MAE (Mean Absolute Error) and MSE (Mean Squared Error). Best five MAE results out of 432 tested models are 0.66, 0.74, 0.85 and 1.09. The forecasting performance of the proposed LSTM models gives successful results compared to literature searches.

Keywords: deep learning, long short term memory, energy, renewable energy load forecasting

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Authors: Kumari Sweta, Ajanta Goswami, Abhilasha Dixit

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Landslide is a geomorphic process that plays an essential role in the evolution of the hill-slope and long-term landscape evolution. But its abrupt nature and the associated catastrophic forces of the process can have undesirable socio-economic impacts, like substantial economic losses, fatalities, ecosystem, geomorphologic and infrastructure disturbances. The estimated fatality rate is approximately 1person /100 sq. Km and the average economic loss is more than 550 crores/year in the Himalayan belt due to landslides. This study presents a comparative performance of a statistical bivariate method and a machine learning technique for landslide susceptibility mapping in and around Dharamshala, Himachal Pradesh. The final produced landslide susceptibility maps (LSMs) with better accuracy could be used for land-use planning to prevent future losses. Dharamshala, a part of North-western Himalaya, is one of the fastest-growing tourism hubs with a total population of 30,764 according to the 2011 census and is amongst one of the hundred Indian cities to be developed as a smart city under PM’s Smart Cities Mission. A total of 209 landslide locations were identified in using high-resolution linear imaging self-scanning (LISS IV) data. The thematic maps of parameters influencing landslide occurrence were generated using remote sensing and other ancillary data in the GIS environment. The landslide causative parameters used in the study are slope angle, slope aspect, elevation, curvature, topographic wetness index, relative relief, distance from lineaments, land use land cover, and geology. LSMs were prepared using information value (Info Val), and Fuzzy Expert System (FES) models. Info Val is a statistical bivariate method, in which information values were calculated as the ratio of the landslide pixels per factor class (Si/Ni) to the total landslide pixel per parameter (S/N). Using this information values all parameters were reclassified and then summed in GIS to obtain the landslide susceptibility index (LSI) map. The FES method is a machine learning technique based on ‘mean and neighbour’ strategy for the construction of fuzzifier (input) and defuzzifier (output) membership function (MF) structure, and the FR method is used for formulating if-then rules. Two types of membership structures were utilized for membership function Bell-Gaussian (BG) and Trapezoidal-Triangular (TT). LSI for BG and TT were obtained applying membership function and if-then rules in MATLAB. The final LSMs were spatially and statistically validated. The validation results showed that in terms of accuracy, Info Val (83.4%) is better than BG (83.0%) and TT (82.6%), whereas, in terms of spatial distribution, BG is best. Hence, considering both statistical and spatial accuracy, BG is the most accurate one.

Keywords: bivariate statistical techniques, BG and TT membership structure, fuzzy expert system, information value method, machine learning technique

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Authors: Bakytzhan Bimbetov, Abay Zhangabilov, Saule Aitbaeva, Galymzhan Meirambekov

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Mare’s milk (saumal) contains in total about 40 biological components necessary for the human body. The most significant among them are amino acids, fats, carbohydrates, enzymes (lysozyme, amylase), more minerals and vitamins which are well balanced with each other. In Kazakhstan, Company "Eurasia Invest Ltd.” produces a freeze-dried saumal in form of powder by the use of modern German innovative technology by means of evaporating at low temperature (-35°C) with an appropriate pasteurization. Research of freeze-dried biomilk for the qualitative content showed that main ingredients of freshly drown milk are being preserved. We are currently studying medical and dietary properties of freeze-dried mare's milk for diseases of the digestive system, including for nonalcoholic steatohepatitis (NASH) and liver cirrhosis (LC) viral etiology. The studied group consisted of 14 patients with NASH, and 7 patients with LC viral etiology of Class A severity degree as per Child-Pugh. Patients took freeze-dried saumal, preliminary dissolved in boiled warm water (24 g. powder per 200 ml water) 3-4 times a day for a month in conjunction with basic therapy. The results were compared to a control group (11 patients with NASH and LC) who received only basic therapy without mare’s milk. Results of preliminary research showed an improvement of subjective and objective conditions of all patients, but more significant improvement of clinical symptoms and syndromes were observed in the treatment group compared to the control one. Patients with NASH significantly over time compared to the beginning of therapy decreased asthenic and dyspeptic syndromes (p<0,01). Hepatomegaly, identified on the basis of ultrasound prior to treatment was observed in 92,8±2,4% of patients, and after combination therapy hepatomegaly the rate decreased by 14,3%, amounting to 78,5±2,8%. Patients with LC also noted the improvement of asthenic (p<0,01) and dyspeptic (p<0,05) syndromes and hemorrhagic syndrome (nosebleeds and bleeding gums when brushing your teeth, p<0,05), and jaundice. Laboratory study also showed improvement in the research group, but more significant changes were observed in the experimental group. Group of patients with NASH showed a significant improvement of index in cytolysis in conjunction with a combination therapy (p<0,05). In the control group, these indicators were also improved, but they were not statistically reliable (p>0,05). Markers of liver failure were additionally studied during the study of laboratory parameters in patients with liver cirrhosis, in particular, bilirubin, albumin and prothrombin index (PTI). Combined therapy with the use of basic treatment and mare's milk showed a significant improvement in cytolysis and bilirubin (p<0,05). In our opinion, a very important and interesting fact is that, in conjunction with basic therapy, the use of mare's milk revealed an improvement of liver function in the form of normalized PTI and albumin in patients with liver cirrhosis viral etiology. Results of this work have shown therapeutic efficiency of the use of mare's milk in complex treatment of patients with liver disease and require further in-depth study.

Keywords: liver cirrhosis, non-alcohol steatohepatitis, saumal, mare’s milk

Procedia PDF Downloads 227

Authors: Tesfaye Mengistu

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Power cables play a crucial role in the transmission and distribution of electrical energy. As the electricity generation, transmission, distribution, and storage systems become smarter, there is a growing emphasis on incorporating intelligent approaches to ensure the reliability of power cables. Various types of electrical cables are employed for transmitting and distributing electrical energy, with cross-linked polyethylene (XLPE) cables being widely utilized due to their exceptional electrical and mechanical properties. However, insulation defects can occur in XLPE cables due to subpar manufacturing techniques during production and cable joint installation. To address this issue, experts have proposed different methods for monitoring XLPE cables. Some suggest the use of interdigital capacitive (IDC) technology for online monitoring, while others propose employing continuous wave (CW) terahertz (THz) imaging systems to detect internal defects in XLPE plates used for power cable insulation. In this study, we have developed models that employ a custom dataset collected locally to classify the physical safety status of individual power cables. Our models aim to replace physical inspections with computer vision and image processing techniques to classify defective power cables from non-defective ones. The implementation of our project utilized the Python programming language along with the TensorFlow package and a convolutional neural network (CNN). The CNN-based algorithm was specifically chosen for power cable defect classification. The results of our project demonstrate the effectiveness of CNNs in accurately classifying power cable defects. We recommend the utilization of similar or additional datasets to further enhance and refine our models. Additionally, we believe that our models could be used to develop methodologies for detecting power cable defects from live video feeds. We firmly believe that our work makes a significant contribution to the field of power cable inspection and maintenance. Our models offer a more efficient and cost-effective approach to detecting power cable defects, thereby improving the reliability and safety of power grids.

Keywords: artificial intelligence, computer vision, defect detection, convolutional neural net

Procedia PDF Downloads 112

Authors: Veronica S. Moertini, Vinsensius Kevin, Gede Karya

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Customer reviews have been collected by many kinds of e-commerce websites selling products, services, hotel rooms, tickets and so on. Each website collects its own customer reviews. The reviews can be crawled, collected from those websites and stored as big data. Text analysis techniques can be used to analyze that data to produce summarized information, such as customer opinions. Then, these opinions can be published by independent service provider websites and used to help customers in choosing the most suitable products or services. As the opinions are analyzed from big data of reviews originated from many websites, it is expected that the results are more trusted and accurate. Indonesian customers write reviews in Indonesian language, which comes with its own structures and uniqueness. We found that most of the reviews are expressed with “daily language”, which is informal, do not follow the correct grammar, have many abbreviations and slangs or non-formal words. Hadoop is an emerging platform aimed for storing and analyzing big data in distributed systems. A Hadoop cluster consists of master and slave nodes/computers operated in a network. Hadoop comes with distributed file system (HDFS) and MapReduce framework for supporting parallel computation. However, MapReduce has weakness (i.e. inefficient) for iterative computations, specifically, the cost of reading/writing data (I/O cost) is high. Given this fact, we conclude that MapReduce function is best adapted for “one-pass” computation. In this research, we develop an efficient technique for extracting or mining opinions from big data of Indonesian reviews, which is based on MapReduce with one-pass computation. In designing the algorithm, we avoid iterative computation and instead adopt a “look up table” technique. The stages of the proposed technique are: (1) Crawling the data reviews from websites; (2) cleaning and finding root words from the raw reviews; (3) computing the frequency of the meaningful opinion words; (4) analyzing customers sentiments towards defined objects. The experiments for evaluating the performance of the technique were conducted on a Hadoop cluster with 14 slave nodes. The results show that the proposed technique (stage 2 to 4) discovers useful opinions, is capable of processing big data efficiently and scalable.

Keywords: big data analysis, Hadoop MapReduce, analyzing text data, mining Indonesian reviews

Procedia PDF Downloads 201

Authors: Ning Niu

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The study hinges on consumer taste, food industry (wine production) and cultural consumption (vineyard tourism) which are related to the Chinese market, consumers, and visitors traveling to Australian vineyards. The research topic can be summed up as: the economic importance of the Chinese market on Australian wine production; the economic importance of the Chinese market have an impact on how Australian wine is produced or packaged; the impact of mass Chinese wine tourism on Australian vineyards; the gendered and cultured experience of wine tourism for Chines visitors. This study aims to apply the theories of Pierre Bourdieu into the research in food industry and cultural consumption; investigate Chinese experiences with Australian wine products and vineyard tours; to explore the cultural, gendered and class influences on their experiences. The academic background covers the concepts of habitus, taste, capital proposed by Pierre Bourdieu along with long-lasting concepts within China’s cultural context including mianzi (face, dignity/honor/hierarchy) and guanxi (connections/social network), in order to develop new perspectives to study the tastes of Chinese tourists coming to Australia for wine experiences. The documents cited from Australian government or industries will be interpreted, and the analysis of data will constitute the economic background for this current study. The study applies qualitative research and draws from the fieldwork, choosing ethnographic observation, interviews, personal experiences and discursive analysis of government documents and tourism documents. The expected sample size includes three tourism professionals, two or three local Australian wine producers, and 20 to 30 Chinese wine consumers and visitors travelling to Australian vineyards. An embodied ethnography will be used to observe the Chinese participants’ feelings, thoughts, and experiences of their engagement with Australian wine and vineyards. The researcher will interview with Chinese consumers, tourism professionals, and Australian winemakers to collect primary data. Note-taking, picture-taking, and audio-recording will be adopted with informants’ permissions. Personal or group interview will be last for 30 and 60 minutes respectively. Personal experiences of the researcher have been analyzed to respond to some research questions, and have accumulated part of primary data (e.g., photos and stories) to discover how 'mianzi' and 'guanxi' influence Australian wine and tourism industries to meet the demands’ of Chinese consumers. At current stage, the secondary data from analysis of official and industrial documents has proved the economic importance of Chinese market is influencing Australian wine and tourism industries. And my own experiences related to this study, in some sense, has proved the Chinese cultural concepts (mianzi and guanxi) are influencing the Australian wine production and package along with vineyard tours. Future fieldwork will discover more in this research realm, contribute more to knowledge.

Keywords: habitus, taste, capital, mianzi, guanxi

Procedia PDF Downloads 130

Authors: Douglas N. Simões, Michele Pittol, Vanda F. Ribeiro, Daiane Tomacheski, Ruth M. C. Santana

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The increasing demand of thermoplastic elastomers is related to the wide range of applications, such as automotive, footwear, wire and cable industries, adhesives and medical devices, cell phones, sporting goods, toys and others. These materials are susceptible to microbial attack. Moisture and organic matter present in some areas (such as shower area and sink), provide favorable conditions for microbial proliferation, which contributes to the spread of diseases and reduces the product life cycle. Compounds based on SEBS copolymers, poly(styrene-b-(ethylene-co-butylene)-b-styrene, are a class of thermoplastic elastomers (TPE), fully recyclable and largely used in domestic appliances like bath mats and tooth brushes (soft touch). Zinc oxide and zinc ions loaded in personal and home care products have become common in the last years due to its biocidal effect. In that sense, the aim of this study was to evaluate the effect of zinc as antimicrobial agent in compounds based on SEBS/polypropylene/oil/ calcite for use as refrigerator seals (gaskets), bath mats and sink squeegee. Two zinc oxides from different suppliers (ZnO-Pe and ZnO-WR) and one masterbatch of zinc ions (M-Zn-ion) were used in proportions of 0%, 1%, 3% and 5%. The compounds were prepared using a co-rotating double screw extruder (L/D ratio of 40/1 and 16 mm screw diameter). The extrusion parameters were kept constant for all materials. Tests specimens were prepared using the injection molding machine. A compound with no antimicrobial additive (standard) was also tested. Compounds were characterized by physical (density), mechanical (hardness and tensile properties) and rheological properties (melt flow rate - MFR). The Japan Industrial Standard (JIS) Z 2801:2010 was applied to evaluate antibacterial properties against Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli). The Brazilian Association of Technical Standards (ABNT) NBR 15275:2014 were used to evaluate antifungal properties against Aspergillus niger (A. niger), Aureobasidium pullulans (A. pullulans), Candida albicans (C. albicans), and Penicillium chrysogenum (P. chrysogenum). The microbiological assay showed a reduction over 42% in E. coli and over 49% in S. aureus population. The tests with fungi showed inconclusive results because the sample without zinc also demonstrated an inhibition of fungal development when tested against A. pullulans, C. albicans and P. chrysogenum. In addition, the zinc loaded samples showed worse results than the standard sample when tested against A. niger. The zinc addition did not show significant variation in mechanical properties. However, the density values increased with the rise in ZnO additives concentration, and had a little decrease in M-Zn-ion samples. Also, there were differences in the MFR results in all compounds compared to the standard.

Keywords: antimicrobial, home device, SEBS, zinc

Procedia PDF Downloads 324

Authors: Jessica Peart, Sarim Al Zubaidy

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This paper examines the main dialogic and reformative aspects that have constituted the developing implementation of an English language module in a common pre-sessional program in Oman, the General Foundation Program (GFP), at the new Military Technological College (MTC), in Oman’s capital, muscat. The MTC is the first of its kind in the country to merge military with academic training and has been running programs since September 2013 over five trimesters to date, receiving external validation and accreditation from the University of Portsmouth (UoP), UK. From this starting point, We will provide context on the parameters that necessitated delivery of this common but specially tailored pre-sessional program at the MTC and outline in detail how the English module with integrated key study skills and personal tutoring support was initially conceived before operations commenced and cooperation between all stakeholders took practical shape. This enquiry traces how stakeholders from students to faculty, college boards and collaborative university partners have considered and redefined the in part static and dynamic boundaries of their larger and smaller scale stakes. With regard to the widely held recognition that pre-sessional students require training in transferable study skills in order to succeed at university, we will chart the subsequent and ongoing adjustments made to the generic, pastoral and integrated elements of that program. Driving this concerted effort has been at base the need for a GFP concerned with three criteria for incoming MTC students cadets, namely to develop candidate’s rounded capacity for intellectual, technical and physical skill as both students and cadets, to generate linguistic proficiency and discerning use of appropriate language registers and to allow personal and collective time for adjustment to a multilayered, brand new environment, while also working within a regulated timeline for academic progression to the MTC diploma or degree levels. The English Department teaching staff’s facilitation of the initial program’s methodologies and timeframe for the GFP English module has garnered a keen and diverse sense of the holistic student cadet experience, which a range of alterations to the program demonstrate. These include alterations to the class types and overall program duration as well as greater multiplicity of exposure within learning environments. In surveying the impact of these composite maneuvers and challenges within a proactive and evolving context of teaching and learning, it is finally demonstrated how student cadet levels of productivity and self-reliance on the one hand and retention issues on the other are being gainfully steered towards progression within a framework for inclusive reciprocal dialogue, gathering thereby civilian and military backgrounds toward uniquely united ends.

Keywords: English module transferable skills, faculty dialogue, governance structure, overarching regulatory agencies

Procedia PDF Downloads 276

Authors: Kenji Tanaka, Kazumi Sugita, Yuto Mizushima

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This paper introduces a noteworthy form of English communication training for the officers and operators of the Osaka-Bay Marine Traffic Information Service (Osaka MARTIS) of the Japan Coast Guard working in the congested area at the Akashi Strait in Hyogo Prefecture, Japan. The authors of this paper, Marine Technical College’s (MTC) English language instructors, have been holding about forty lectures and exercises in basic and normal Maritime English (ME) for several groups of MARTIS personnel at Osaka MARTIS annually since they started the training in 2005. Trainees are expected to be qualified Maritime Third-Class Radio Operators who are responsible for providing safety information to a daily average of seven to eight hundred vessels that pass through the Akashi Strait, one of Japan’s narrowest channels. As of 2022, the instructors are conducting 55 remote lessons at MARTIS. One lesson is 90 minutes long. All 26 trainees are given oral and written assessments. The trainees need to pass the examination to become qualified operators every year, requiring them to train and maintain their linguistic levels even during the pandemic of Corona Virus Disease-19 (COVID-19). The vessel traffic information provided by Osaka MARTIS in Maritime English language is essential to the work involving the use of very high frequency (VHF) communication between MARTIS and vessels in the area. ME is the common language mainly used on board merchant, fishing, and recreational vessels, normally at sea. ME was edited and recommended by the International Maritime Organization in the 1970s, was revised in 2002, and has undergone continual revision. The vessel’s circumstances are much more serious at the strait than those at the open sea, so these vessels need ME to receive guidance from the center when passing through the narrow strait. The imminent and challenging situations at the strait necessitate that textbooks’ contents include the basics of the phrase book for seafarers as well as specific and additional navigational information, pronunciation exercises, notes on keywords and phrases, explanations about collocations, sample sentences, and explanations about the differences between synonyms especially those focusing on terminologies necessary for passing through the strait. Additionally, short Japanese-English translation quizzes about these topics, as well as prescribed readings about the maritime sector, are include in the textbook. All of these exercises have been trained in the remote education system since the outbreak of COVID-19. According to the guidelines of ME edited in 2009, the lowest level necessary for seafarers is B1 (lower individual users) of The Common European Framework of Reference for Languages: Learning, Teaching, Assessment (CEFR). Therefore, this vocational ME language training at Osaka MARTIS aims for its trainees to communicate at levels higher than B1. A noteworthy proof of improvement from this training is that most of the trainees have become qualified marine radio communication officers.

Keywords: akashi strait, B1 of CEFR, maritime english communication training, osaka martis

Procedia PDF Downloads 124

Authors: Hao Yan, Xiaobing Zhang

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The working mechanism of miniaturized solid rocket motors (SRMs) is not yet fully understood. It is imperative to explore its unique features. However, there are many disadvantages to using common multi-objective evolutionary algorithms (MOEAs) in predicting the parameters of the miniaturized SRM during its conceptual design phase. Initially, the design variables and objectives are constrained in a lumped parameter model (LPM) of this SRM, which leads to local optima in MOEAs. In addition, MOEAs require a large number of calculations due to their population strategy. Although the calculation time for simulating an LPM just once is usually less than that of a CFD simulation, the number of function evaluations (NFEs) is usually large in MOEAs, which makes the total time cost unacceptably long. Moreover, the accuracy of the LPM is relatively low compared to that of a CFD model due to its assumptions. CFD simulations or experiments are required for comparison and verification of the optimal results obtained by MOEAs with an LPM. The conceptual design phase based on MOEAs is a lengthy process, and its results are not precise enough due to the above shortcomings. An artificial neural network (ANN) based parameter prediction is proposed as a way to reduce time costs and improve prediction accuracy. In this method, an ANN is used to build a surrogate model that is trained with a 3D numerical simulation. In design, the original LPM is replaced by a surrogate model. Each case uses the same MOEAs, in which the calculation time of the two models is compared, and their optimization results are compared with 3D simulation results. Using the surrogate model for the parameter prediction process of the miniaturized SRMs results in a significant increase in computational efficiency and an improvement in prediction accuracy. Thus, the ANN-based surrogate model does provide faster and more accurate parameter prediction for an initial design scheme. Moreover, even when the MOEAs converge to local optima, the time cost of the ANN-based surrogate model is much lower than that of the simplified physical model LPM. This means that designers can save a lot of time during code debugging and parameter tuning in a complex design process. Designers can reduce repeated calculation costs and obtain accurate optimal solutions by combining an ANN-based surrogate model with MOEAs.

Keywords: artificial neural network, solid rocket motor, multi-objective evolutionary algorithm, surrogate model

Procedia PDF Downloads 90

Authors: Saltanat Zhilkibayeva, Muratulla Utenov, Nurzhan Utenov

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The distributed inertia forces of complex nature appear in links of rod mechanisms within the motion process. Such loads raise a number of problems, as the problems of destruction caused by a large force of inertia; elastic deformation of the mechanism can be considerable, that can bring the mechanism out of action. In this work, a new analytical approach for the definition of internal forces in links of robotic systems and mechanisms with statically indeterminate and determinate structures taking into account the distributed inertial and concentrated forces is proposed. The relations between the intensity of distributed inertia forces and link weight with geometrical, physical and kinematic characteristics are determined in this work. The distribution laws of inertia forces and dead weight make it possible at each position of links to deduce the laws of distribution of internal forces along the axis of the link, in which loads are found at any point of the link. The approximation matrixes of forces of an element under the action of distributed inertia loads with the trapezoidal intensity are defined. The obtained approximation matrixes establish the dependence between the force vector in any cross-section of the element and the force vector in calculated cross-sections, as well as allow defining the physical characteristics of the element, i.e., compliance matrix of discrete elements. Hence, the compliance matrixes of an element under the action of distributed inertial loads of trapezoidal shape along the axis of the element are determined. The internal loads of each continual link are unambiguously determined by a set of internal loads in its separate cross-sections and by the approximation matrixes. Therefore, the task is reduced to the calculation of internal forces in a final number of cross-sections of elements. Consequently, it leads to a discrete model of elastic calculation of links of rod mechanisms. The discrete model of the elements of mechanisms and robotic systems and their discrete model as a whole are constructed. The dynamic equilibrium equations for the discrete model of the elements are also received in this work as well as the equilibrium equations of the pin and rigid joints expressed through required parameters of internal forces. Obtained systems of dynamic equilibrium equations are sufficient for the definition of internal forces in links of mechanisms, which structure is statically definable. For determination of internal forces of statically indeterminate mechanisms (in the way of determination of internal forces), it is necessary to build a compliance matrix for the entire discrete model of the rod mechanism, that is reached in this work. As a result by means of developed technique the programs in the MAPLE18 system are made and animations of the motion of the fourth class mechanisms of statically determinate and statically indeterminate structures with construction on links the intensity of cross and axial distributed inertial loads, the bending moments, cross and axial forces, depending on kinematic characteristics of links are obtained.

Keywords: distributed inertial forces, internal forces, statically determinate mechanisms, statically indeterminate mechanisms

Procedia PDF Downloads 217

Authors: Martha E. Aguiar-Barrera, Humberto Gutierrez-Pulido, Veronica Vargas-Alejo

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Identifying and modeling random phenomena is a fundamental cognitive process to understand and transform reality. Recognizing situations governed by chance and giving them a scientific interpretation, without being carried away by beliefs or intuitions, is a basic training for citizens. Hence the importance of generating teaching-learning processes, supported using technology, paying attention to model creation rather than only executing mathematical calculations. In order to develop the student's knowledge about basic probability distributions and decision making; in this work a model eliciting activity (MEA) is reported. The intention was applying the Model and Modeling Perspective to design an activity related to civil engineering that would be understandable for students, while involving them in its solution. Furthermore, the activity should imply a decision-making challenge based on sample data, and the use of the computer should be considered. The activity was designed considering the six design principles for MEA proposed by Lesh and collaborators. These are model construction, reality, self-evaluation, model documentation, shareable and reusable, and prototype. The application and refinement of the activity was carried out during three school cycles in the Probability and Statistics class for Civil Engineering students at the University of Guadalajara. The analysis of the way in which the students sought to solve the activity was made using audio and video recordings, as well as with the individual and team reports of the students. The information obtained was categorized according to the activity phase (individual or team) and the category of analysis (sample, linearity, probability, distributions, mechanization, and decision-making). With the results obtained through the MEA, four obstacles have been identified to understand and apply the binomial distribution: the first one was the resistance of the student to move from the linear to the probabilistic model; the second one, the difficulty of visualizing (infering) the behavior of the population through the sample data; the third one, viewing the sample as an isolated event and not as part of a random process that must be viewed in the context of a probability distribution; and the fourth one, the difficulty of decision-making with the support of probabilistic calculations. These obstacles have also been identified in literature on the teaching of probability and statistics. Recognizing these concepts as obstacles to understanding probability distributions, and that these do not change after an intervention, allows for the modification of these interventions and the MEA. In such a way, the students may identify themselves the erroneous solutions when they carrying out the MEA. The MEA also showed to be democratic since several students who had little participation and low grades in the first units, improved their participation. Regarding the use of the computer, the RStudio software was useful in several tasks, for example in such as plotting the probability distributions and to exploring different sample sizes. In conclusion, with the models created to solve the MEA, the Civil Engineering students improved their probabilistic knowledge and understanding of fundamental concepts such as sample, population, and probability distribution.

Keywords: linear model, models and modeling, probability, randomness, sample

Procedia PDF Downloads 118

Authors: Peter Park, Alfonso Ayala, Douglas Saeks, Jordan Miller, Carmen Flores, Karen Nelson

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Introduction Hip fractures account for more than 300,000 hospital admissions every year. Many present as fragility fractures in geriatric patients with multiple medical comorbidities. Standardized protocols for the multidisciplinary management of this patient population have been shown to improve patient outcomes. A hip fracture protocol was implemented at a Level I Trauma center with a focus on pre-operative medical optimization and early surgical care. This study evaluates the efficacy of that protocol, including the early transition period. Methods A retrospective review was performed of all patients ages 60 and older with isolated hip fractures who were managed surgically between 2020 and 2022. This included patients 1 year prior and 1 year following the implementation of a hip fracture protocol at a Level I Trauma center. Results 530 patients were identified: 249 patients were treated before, and 281 patients were treated after the protocol was instituted. There was no difference in mean age (p=0.35), gender (p=0.3), or Charlson Comorbidity Index (p=0.38) between the cohorts. Following the implementation of the protocol, there were observed increases in time to surgery (27.5h vs. 33.8h, p=0.01), hospital length of stay (6.3d vs. 9.7d, p<0.001), and ED LOS (5.1h vs. 6.2h, p<0.001). There were no differences in in-hospital mortality (2.01% pre vs. 3.20% post, p=0.39) and complication rates (25% pre vs 26% post, p=0.76). A trend towards improved outcomes was seen after the early transition period but failed to yield statistical significance. Conclusion Early medical management and surgical intervention are key determining factors affecting outcomes following fragility hip fractures. The implementation of a hip fracture protocol at this institution has not yet significantly affected these parameters. This could in part be due to the restrictions placed at this institution during the COVID-19 pandemic. Despite this, the time to OR pre-and post-implementation was quicker than figures reported elsewhere in literature. Further longitudinal data will be collected to determine the final influence of this protocol. Significance/Clinical Relevance Given the increasing number of elderly people and the high morbidity and mortality associated with hip fractures in this population finding cost effective ways to improve outcomes in the management of these injuries has the potential to have enormous positive impact for both patients and hospital systems.

Keywords: hip fracture, geriatric, treatment algorithm, preoperative optimization

Procedia PDF Downloads 79

Authors: Nana Katsitadze, Tamar Atanelishvili, Mariam Kutateladze, Alexandre Tushishvili

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In the modern world, tourism has emerged as one of the most powerful economic sectors, and due to its high economic performance, it is attractive to the countries with various levels of economic development. The purpose of the present paper, dedicated to discussing the current problems of tourism development, is to find ways which will contribute to bringing more benefits to the country from the sector. Georgia has been successfully developing leisure tourism for the last ten years, and at the next stage of development business, tourism gains particular importance for Georgia as a means of mitigating the negative socio-economic effects caused by the seasonality of tourism and as a high-cost tourism market. Therefore, the object of the paper is to study the factors that contribute to the development of business tourism. The paper uses the research methods such as system analysis, synthesis, analogy, as well as historical, comparative, economic, and statistical methods of analysis. The information base for the research is made up of the statistics on the functioning of the tourism market of Georgia and foreign countries as well as official data provided by international organizations in the field of tourism. Based on the experience of business tourism around the world and identifying the successful start of business tourism development in Georgia and its causing factors, a business tourism development model for Georgia has been developed. The model might be useful as a methodological material for developing a business tourism development concept for the countries with limited financial resources but rich in tourism resources like Georgia. On the initial stage of development (in absence of conventional centers), the suggested concept of business tourism development involves organizing small and medium-sized meetings both in large cities and in regions by using high-class hotel infrastructure and event management services. Relocation of small meetings to the regions encourages inclusive development of the sector based on increasing the awareness of these regions as tourist sites as well as the increase in employment and sales of other tourism or consumer products. Business tourism increases the number of hotel visitors in the non-seasonal period and improves hotel performance indicators, which enhances the attractiveness of investing in the hotel business. According to the present concept of business tourism development, at the initial stage, development of business tourism is based on the existing markets, including internal market, neighboring markets and the markets of geographically relatively near countries and at the next stage, the concept involves generating tourists from other relatively distant target markets. As a result, by gaining experience in business tourism, enhancing professionalism, increasing awareness and stimulating infrastructure development, the country will prepare the basis to move to a higher stage of tourism development. In addition, the experience showed that for attracting large customers, peculiarities of the field require activation of state policy and active use of marketing mechanisms and tools of the state.

Keywords: hotel industry development, MICE model, MICE strategy, MICE tourism in Georgia

Procedia PDF Downloads 157

Authors: Pedro Felgueiras, Ana Miguel, Nélson Almeida, Raquel Silva

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Objective: Through the study of a clinical case of delusional somatic disorder secondary to phantogeusia, we aim to highlight the importance of considering psychosomatic conditions in differential diagnosis, as well as to emphasize the complexity of its comprehension, treatment, and respective impact on patients’ functioning. Methods: Bearing this in mind, we conducted a critical analysis of a case series based on patient observations, clinical data, and complementary diagnostic methods, as well as a non-systematic review of the literature on the subject. Results: A 61-year-old female patient with no history of psychiatric conditions. Family psychiatric history of mood disorder (depression), with psychotic features found in her mother. Medical history of many comorbidities affecting different organ systems (endocrine, gastrointestinal, genitourinary, ophthalmological). Documented neuroticism traits of personality. The patient’s family described a persistent concern about several physical symptoms across her life, with a continuous effort to obtain explanations about any sensation out of her normal perception. Since being subjected to endoscopy in 2018, she started complaints of persistent phantogeusia (acid taste) and developed excessive thoughts, feelings, and behaviors associated with this somatic symptom. The patient was evaluated by several medical specialties, and an extensive panel of medical exams was carried out, excluding any disease. Besides all the investigation and with no evidence of disease signs, acute anxiety, time, and energy dispended to this symptom culminated in severe psychosocial impairment. The patient was admitted to a psychiatric ward for investigation and treatment of this clinical picture, leading to the diagnosis of the delusional somatic disorder. In order to exclude the acute organic etiology of this psychotic disorder, an analytic panel was carried out with no abnormal results. In the context of a psychotic clinical picture, a CT scan was performed, which revealed a right cortical vascular lesion. Neuropsychological evaluation was made, with the description of cognitive functioning being globally normative. During treatment with an antipsychotic (pimozide), a complete remission of the somatic delusion was associated with the disappearance of gustative perception disturbance. In follow-up, a relapse of gustative sensation was documented, and her thoughts and speech were dominated by concerns about multiple somatic symptoms. Conclusion: In terms of abnormal bodily sensations, the oral cavity is one of the frequent sites of delusional disorder. Patients with these gustatory perception distortions complain about unusual sensations without corresponding abnormal findings in the oral area. Its pathophysiology has not been fully elucidated yet. In terms of its comprehensive psychopathology, this case was hypothesized as a paranoid development of a delusional somatic disorder triggered by a post-invasive procedure phantogeusia (which is described as a possible side effect of an endoscopy) in a patient with an anankastic personality. This case presents interesting psychopathology, reinforcing the complexity of psychosomatic disorders in terms of their etiopathogenesis, clinical treatment, and long-term prognosis.

Keywords: psychosomatics, delusional somatic disorder, phantogeusia, paranoid development

Procedia PDF Downloads 129

Authors: Airy Huang, Fuji Foo, Aries Prasetya Wibowo

Abstract:

In recent years, the focus of Natural Language Processing (NLP) development has been gradually shifting from the semantics-based approach to deep learning one, which performs faster with fewer resources. Although it performs well in many applications, the deep learning approach, due to the lack of semantics understanding, has difficulties in noticing and expressing a novel business case with a pre-defined scope. In order to meet the requirements of specific robotic services, deep learning approach is very labor-intensive and time consuming. It is very difficult to improve the capabilities of conversational AI in a short time, and it is even more difficult to self-learn from experiences to deliver the same service in a better way. In this paper, we present an adaptive conversational AI algorithm that combines both semantic knowledge and deep learning to address this issue by learning new business cases through conversations. After self-learning from experience, the robot adapts to the business cases originally out of scope. The idea is to build new or extended robotic services in a systematic and fast-training manner with self-configured programs and constructed dialog flows. For every cycle in which a chat bot (conversational AI) delivers a given set of business cases, it is trapped to self-measure its performance and rethink every unknown dialog flows to improve the service by retraining with those new business cases. If the training process reaches a bottleneck and incurs some difficulties, human personnel will be informed of further instructions. He or she may retrain the chat bot with newly configured programs, or new dialog flows for new services. One approach employs semantics analysis to learn the dialogues for new business cases and then establish the necessary ontology for the new service. With the newly learned programs, it completes the understanding of the reaction behavior and finally uses dialog flows to connect all the understanding results and programs, achieving the goal of self-learning process. We have developed a chat bot service mounted on a kiosk, with a camera for facial recognition and a directional microphone array for voice capture. The chat bot serves as a concierge with polite conversation for visitors. As a proof of concept. We have demonstrated to complete 90% of reception services with limited self-learning capability.

Keywords: conversational AI, chatbot, dialog management, semantic analysis

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Authors: Nkeiruka Elsie Ezomike, Chinwe L. Onyekonwu, Anthony N. Ikefuna, Bede C. Ibe

Abstract:

Superficial fungal infections (SFIs) are one of the common cutaneous infections that affect children worldwide. They may lead to school absenteeism or school drop-out and hence setback in the education of the child. Community-based studies in any locality are good reflections of the health conditions within that area. There is a dearth of information in the literature about SFI among primary school children in Enugu. This study aimed to determine the clinicomycological pattern of SFIs among primary school children in rural and urban communities in Enugu. This was a comparative descriptive cross-sectional study among primary school children in Awgu (rural) and Enugu North (urban) Local Government Areas (LGAs). Subjects' selection was made over 6 months using a multi-stage sampling method. Information such as age, sex, parental education, and occupation were collected using questionnaires. Socioeconomic classes of the children were determined using the classification proposed by Oyedeji et al. The samples were collected from subjects with SFIs. Potassium hydroxide tests were done on the samples. The samples that tested positive were cultured for SFI by inoculating onto Sabouraud's dextrose chloramphenicol actidione agar. The characteristics of the isolates were identified according to their morphological features using Mycology Online, Atlas 2000, and Mycology Review 2003. Equal numbers of children were recruited from the two LGAs. A total of 1662 pupils were studied. The mean ages of the study subjects were 9.03 ± 2.10years in rural and 10.46 ± 2.33years in urban communities. The male to female ratio was 1.6:1 in rural and 1:1.1 in urban communities. The personal hygiene of the children was significantly related to the presence of SFIs. The overall prevalence of SFIs among the study participants was 45%. In the rural, the prevalence was 29.6%, and in the urban prevalence was 60.4%. The types of SFIs were tinea capitis (the commonest), tinea corporis, pityriasis Versicolor, tinea unguium, and tinea manuum with prevalence rates lower in rural than urban communities. The clinical patterns were gray patch and black dot type of non-inflammatory tinea capitis, kerion, tinea corporis with trunk and limb distributions, and pityriasis Versicolor with face, trunk and limb distributions. Gray patch was the most frequent pattern of SFI seen in rural and urban communities. Black dot type was more frequent in rural than urban communities. SFIs were frequent among children aged 5 to 8years in rural and 9 to 12 years in urban communities. SFIs were commoner in males in the rural, whereas female dominance was observed in the urban. SFIs were more in children from low social class and those with poor hygiene. Trichophyton tonsurans and Trichophyton soudanese were the common mycological isolates in rural and urban communities, respectively. In conclusion, SFIs were less prevalent in rural than in urban communities. Trichophyton species were the most common fungal isolates in the communities. Health education of mothers and their children on SFI and good personal hygiene will reduce the incidence of SFIs.

Keywords: clinicomycological pattern, communities, primary school children, superficial fungal infections

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Authors: Ngoc Thao Linh Dang

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Urban waterfront redevelopment is a global phenomenon, and thousands of schemes are being carried out in large metropoles, medium-sized cities, and even small towns all over the world. This opportunity brings the city back to the river and rediscovers waterfront revitalization as a unique opportunity for cities to reconnect with their unique historical and cultural image. The redevelopment can encourage economic investments, serve as a social platform for public interactions, and allow dwellers to express their rights to the city. Many coastal cities have effectively transformed the perception of their waterfront area through years of redevelopment initiatives, having been neglected for over a century. However, this process has never been easy due to the particular complexity of the space: local culture, history, and market-led development. Moreover, municipal governments work out the balance of diverse stakeholder interests, especially when repurposing high-profile and redundant spaces that form the core of urban economic investment while also accommodating the present and future generations in sustainable environments. Urban critics consistently grapple with the effectiveness of the planning process on the new waterfront, where public spaces are criticized for presenting a lack of opportunities for actual public participation due to privatization and authoritarian governance while no longer doing what they are ‘meant to’: all arise in reaction to the perceived failure of these places to meet expectations. The planning culture and the decision-making context determine the level of public involvement in the planning process; however, in the context of competing market forces and commercial interests dominating cities’ planning agendas, planning for public space in urban waterfronts tends to be for economic gain rather than supporting residents' social needs. These newly pleasing settings satisfied the cluster of middle-class individuals, new communities living along the waterfront, and tourists. A trend of public participatory exclusion is primarily determined by the nature of the planning being undertaken and the decision-making context in which it is embedded. Starting from this context, the research investigates the influence of planning on waterfront regeneration and the role of participation in this process. The research aims to look specifically at the characteristics of the planning process of the waterfront in Da Nang and its impact on the regeneration of the place to regain the city’s historical value and enhance local cultural identity and images. Vietnam runs a top-down planning system where municipal governments have control or power over what happens in their city following the approved planning from the national government. The community has never been excluded from development; however, their participation is still marginalized. In order to ensure social equality, a proposed approach called "bottom-up" should be considered and implemented alongside the traditional "top-down" process and provide a balance of perspectives, as it allows for the voices of the most underprivileged social group involved in a planning project to be heard, rather than ignored. The research provides new insights into the influence of the planning process on the waterfront regeneration in the context of Da Nang.

Keywords: planning process, public participation, top-down planning, waterfront regeneration

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Authors: N. K. Ambujam, V. Sudha

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Reservoirs are being contaminated all around the world with point source and Non-Point Source (NPS) pollution. The most common NPS pollutants are sediments and nutrients. Krishnagiri Reservoir (KR) has been chosen for the present case study, which is located in the tropical semi-arid climatic zone of Tamil Nadu, South India. It is the main source of surface water in Krishnagiri district to meet the freshwater demands. The reservoir has lost about 40% of its water holding capacity due to sedimentation over the period of 50 years. Hence, from the research and management perspective, there is a need for a sound knowledge on the spatial and seasonal variations of KR water quality. The present study encompasses the specific objectives as (i) to investigate the longitudinal heterogeneity and seasonal variations of physicochemical parameters, nutrients and biological characteristics of KR water and (ii) to examine the extent of degradation of water quality in KR. 15 sampling points were identified by uniform stratified method and a systematic monthly sampling strategy was selected due to high dynamic nature in its hydrological characteristics. The physicochemical parameters, major ions, nutrients and Chlorophyll a (Chl a) were analysed. Trophic status of KR was classified by using Carlson's Trophic State Index (TSI). All statistical analyses were performed by using Statistical Package for Social Sciences programme, version-16.0. Spatial maps were prepared for Chl a using Arc GIS. Observations in KR pointed out that electrical conductivity and major ions are highly variable factors as it receives inflow from the catchment with different land use activities. The study of major ions in KR exhibited different trends in their values and it could be concluded that as the monsoon progresses the major ions in the water decreases or water quality stabilizes. The inflow point of KR showed comparatively higher concentration of nutrients including nitrate, soluble reactive phosphorus (SRP), total phosphors (TP), total suspended phosphorus (TSP) and total dissolved phosphorus (TDP) during monsoon seasons. This evidently showed the input of significant amount of nutrients from the catchment side through agricultural runoff. High concentration of TDP and TSP at the lacustrine zone of the reservoir during summer season evidently revealed that there was a significant release of phosphorus from the bottom sediments. Carlson’s TSI of KR ranged between 81 and 92 during northeast monsoon and summer seasons. High and permanent Cyanobacterial bloom in KR could be mainly due to the internal loading of phosphorus from the bottom sediments. According to Carlson’s TSI classification Krishnagiri reservoir was ranked in the hyper-eutrophic category. This study provides necessary basic data on the spatio-temporal variations of water quality in KR and also proves the impact of point and NPS pollution from the catchment area. High TSI warrants a greater threat for the recovery of internal P loading and hyper-eutrophic condition of KR. Several expensive internal measures for the reduction of internal loading of P were introduced by many scientists. However, the outcome of the present research suggests for the innovative algae harvesting technique for the removal of sediment nutrients.

Keywords: NPS pollution, nutrients, hyper-eutrophication, krishnagiri reservoir

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Authors: Supriyo Das, Elbir Jove, Ajay Singh, Sophie Corbet, Noel Carr, Martin Deetz

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Water is a critical commodity in the healthcare and medical field. The utility of medical-grade water spans from washing surgical equipment, drug preparation to the key element of life-saving therapy such as hydrotherapy and hemodialysis for patients. A properly treated medical water reduces the bioburden load and mitigates the risk of infection, ensuring patient safety. However, any compromised condition during the production of medical-grade water can create a favorable environment for microbial growth putting patient safety at high risk. Therefore, proper upstream treatment of the medical water is essential before its application in healthcare, pharma and medical space. Reverse Osmosis (RO) is one of the most preferred treatments within healthcare industries and is recommended by all International Pharmacopeias to achieve the quality level demanded by global regulatory bodies. The RO process can remove up to 99.5% of constituents from feed water sources, eliminating bacteria, proteins and particles sizes of 100 Dalton and above. The combination of RO with other downstream water treatment technologies such as Electrodeionization and Ultrafiltration meet the quality requirements of various pharmacopeia monographs to produce highly purified water or water for injection for medical use. In the reverse osmosis process, the water from a liquid with a high concentration of dissolved solids is forced to flow through an especially engineered semi-permeable membrane to the low concentration side, resulting in high-quality grade water. However, these specially engineered RO membranes need to be sanitized either chemically or at high temperatures at regular intervals to keep the bio-burden at the minimum required level. In this paper, we talk about Dupont´s FilmTec Heat Sanitizable Reverse Osmosis membrane (HSRO) for the production of medical-grade water. An HSRO element must be pre-conditioned prior to initial use by exposure to hot water (80°C-85°C) for its stable performance and to meet the manufacturer’s specifications. Without pre-conditioning, the membrane will show variations in feed pressure operations and salt rejection. The paper will discuss the critical variables of pre-conditioning steps that can affect the overall performance of the HSRO membrane and demonstrate the data to support the need for pre-conditioning of HSRO elements. Our preliminary data suggests that there can be up to 35 % reduction in flow due to initial heat treatment, which also positively affects the increase in salt rejection. The paper will go into detail about the fundamental understanding of the performance change of HSRO after the pre-conditioning step and its effect on the quality of medical water produced. The paper will also discuss another critical point, “regular hot water sanitization” of these HSRO membranes. Regular hot water sanitization (at 80°C-85°C) is necessary to keep the membrane bioburden free; however, it can negatively impact the performance of the membrane over time. We will demonstrate several data points on hot water sanitization using FilmTec HSRO elements and challenge its robustness to produce quality medical water. The last part of this paper will discuss the construction details of the FilmTec HSRO membrane and features that make it suitable to pre-condition and sanitize at high temperatures.

Keywords: heat sanitizable reverse osmosis, HSRO, medical water, hemodialysis water, water for Injection, pre-conditioning, heat sanitization

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