Search results for: clinical survey data simulation

Authors: Hakim Merarda, Mounir Aksas, Toufik Arrif, Abd Elfateh Belaid, Amor Gama, Reski Khelifi

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Knowledge of wind loads is important to develop a heliostat with good performance. These loads can be calculated by mathematical equations based on several parameters: the density, wind velocity, the aspect ratio of the mirror (height/width) and the coefficient of the height of the tower. Measurement data of the wind velocity and the density of the air are used in a numerical simulation of wind profile that was performed on heliostats with different pylon heights, with 1m^2 mirror areas and with aspect ratio of mirror equal to 1. These measurement data are taken from the meteorological station installed in Ghardaia, Algeria. The main aim of this work is to find a mathematical correlation between the wind loads and the height of the tower.

Keywords: heliostat, solar tower power, wind loads simulation, South Algeria

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Authors: Leila Rashidian

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Temperature rise on Earth has had harmful effects on the Earth's surface and has led to change in precipitation patterns all around the world. The present research was aimed to study the process of climate change according to the data simulation in future and compare these parameters with current situation in the studied stations in Semnan province including Garmsar, Shahrood and Semnan. In this regard, LARS-WG software, HADCM₃ model and A₂ scenario were used for the 2010-2030 period. In this model, climatic parameters such as maximum and minimum temperature, precipitation and radiation were used daily. The obtained results indicated that there will be a 4.4% increase in precipitation in Semnan province compared with the observed data, and in general, there will be a 1.9% increase in temperature. This temperature rise has significant impact on precipitation patterns. Most of precipitation will be raining (torrential rains in some cases). According to the results, from west to east, the country will experience more temperature rise and will be warmer.

Keywords: climate change, Semnan province, Lars.WG model, climate parameters, HADCM₃ model

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Authors: Souad Romdhane, Lotfi Belkacem

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When referring to actuarial analysis of lifetime, only models accounting for observable risk factors have been developed. Within this context, Cox proportional hazards model (CPH model) is commonly used to assess the effects of observable covariates as gender, age, smoking habits, on the hazard rates. These covariates may fail to fully account for the true lifetime interval. This may be due to the existence of another random variable (frailty) that is still being ignored. The aim of this paper is to examine the shared frailty issue in the Cox proportional hazard model by including two different parametric forms of frailty into the hazard function. Four estimated methods are used to fit them. The performance of the parameter estimates is assessed and compared between the classical Cox model and these frailty models through a real-life data set from the Quebec Pension Plan and then using a more general simulation study. This performance is investigated in terms of the bias of point estimates and their empirical standard errors in both fixed and random effect parts. Both the simulation and the real dataset studies showed differences between classical Cox model and shared frailty model.

Keywords: life insurance-pension plan, survival analysis, risk factors, cox proportional hazards model, multivariate failure-time data, shared frailty, simulations study

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Authors: Sachi Nandan Mohanty, Shreya Sinha, Sweeti Sah, Shweta Sharma

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The advancement of natural language processing has majorly influenced the field of medical transcript classification, providing a robust framework for enhancing the accuracy of clinical data processing. It has enormous potential to transform healthcare and improve people's livelihoods. This research focuses on improving the accuracy of medical transcript categorization using Bidirectional Encoder Representations from Transformers (BERT) and its specialized variants, including BioBERT, ClinicalBERT, SciBERT, and BlueBERT. The experimental work employs Optuna, an optimization framework, for hyperparameter tuning to identify the most effective variant, concluding that BioBERT yields the best performance. Furthermore, various optimizers, including Adam, RMSprop, and Layerwise adaptive large batch optimization (LAMB), were evaluated alongside BERT's default AdamW optimizer. The findings show that the LAMB optimizer achieves a performance that is equally good as AdamW's. Synthetic data generation techniques from Gretel were utilized to augment the dataset, expanding the original dataset from 5,000 to 10,000 rows. Subsequent evaluations demonstrated that the model maintained its performance with synthetic data, with the LAMB optimizer showing marginally better results. The enhanced dataset and optimized model configurations improved classification accuracy, showcasing the efficacy of the BioBERT variant and the LAMB optimizer. It resulted in an accuracy of up to 98.2% and 90.8% for the original and combined datasets.

Keywords: BioBERT, clinical data, healthcare AI, transformer models

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Authors: R. Mahmoodi, A. R. Zolfaghari

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In nuclear power plants, loss of coolant from the primary system is the type of reduced removed capacity that is given most attention; such an accident is referred as Loss of Coolant Accident (LOCA). In the current study, investigation of shell and tube THTL heat exchanger behavior during LOCA is implemented by ANSYS CFX simulation software in both steady state and transient mode of turbulent fluid flow according to experimental conditions. Numerical results obtained from ANSYS CFX simulation show good agreement with experimental data of THTL heat exchanger. The results illustrate that in large break LOCA as short term accident, heat exchanger could not fast response to temperature variables but in the long term, the temperature of shell side of heat exchanger will be increase.

Keywords: shell-and-tube heat exchanger, shell-side, CFD, flow and heat transfer, LOCA

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Authors: Siriporn Sikkaphun

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Food is essential for living, and receiving correct, suitable, and adequate food is advantageous to the body, especially for patients because it can enable good recovery. Feeding through a gastrostomy tube is one useful way that is widely used because it is easy, convenient, and economical.To compare the effectiveness of using the clinical guidelines for feeding through a gastrostomy tube in critically ill surgical patients.This is a pre-post quasi-experimental study on 15 critically ill surgical or accident patients who needed intubation and the gastrostomy tube from August 2011 to November 2012. The data were collected using the guidelines, and an evaluation form for effectiveness of guidelines for feeding through a gastrostomy tube in critically ill surgical patients. After using the guidelines for feeding through a gastrostomy tube in critically ill surgical patients, it was found that The average number of days from the admission date to the day the patients received food through the G-tube significantly reduced at the level .05. The number of personnel who practiced nursing activities correctly and suitably for patients with complications during feeding significantly increased at the level .05.The number of patients receiving energy to the target level significantly increased at the level .05. The results of this study indicated that the use of the guidelines for feeding through a gastrostomy tube in critically ill surgical patients was feasible in practice, and the outcomes were beneficial to the patients.

Keywords: clinical guidelines, feeding, gastrostomy tube, critically ill, surgical patients

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Authors: Neha Intikhab Khan, Alanoud AlBalwi, Farah Alqazlan, Tala Almadoudi

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Background: Grammarly, a widely utilized writing assistant launched in 2009, leverages advanced artificial intelligence and natural language processing to enhance writing quality across various platforms. Methods: To collect data on user perceptions of Grammarly, a structured survey was designed and distributed via Google Forms. The survey included a series of quantitative and qualitative questions aimed at assessing various aspects of Grammarly's performance. The survey comprised multiple-choice questions, Likert scale items (ranging from "strongly disagree" to "strongly agree"), and open-ended questions to capture detailed user feedback. The target population included students, friends, and family members. The collected responses were analyzed using statistical methods to quantify user satisfaction. Participation in the survey was voluntary, and respondents were assured anonymity and confidentiality. Results: The survey of 28 respondents revealed a generally favorable perception of Grammarly's AI capabilities. A significant 39.3% strongly agreed that it effectively improves text tone, with an additional 46.4% agreeing, while 10.7% remained neutral. For clarity suggestions, 28.6% strongly agreed, and 57.1% agreed, totaling 85.7% recognition of its value. Regarding grammatical accuracy across various genres, 46.4% rated it a perfect score of 5, contributing to 78.5% who found it highly effective. Conclusion: The evolution of Grammarly from a basic grammar checker to a robust AI-driven application underscores its adaptability and commitment to helping users develop their writing skills.

Keywords: Grammarly, writing tool, user engagement, AI capabilities, effectiveness

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Authors: M. Sai Veerendra

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Today, money laundering (ML) poses a serious threat not only to financial institutions but also to the nation. This criminal activity is becoming more and more sophisticated and seems to have moved from the cliché of drug trafficking to financing terrorism and surely not forgetting personal gain. Most of the financial institutions internationally have been implementing anti-money laundering solutions (AML) to fight investment fraud activities. However, traditional investigative techniques consume numerous man-hours. Recently, data mining approaches have been developed and are considered as well-suited techniques for detecting ML activities. Within the scope of a collaboration project on developing a new data mining solution for AML Units in an international investment bank in Ireland, we survey recent data mining approaches for AML. In this paper, we present not only these approaches but also give an overview on the important factors in building data mining solutions for AML activities.

Keywords: data mining, clustering, money laundering, anti-money laundering solutions

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Authors: Sujata Chaturvedi, Ishita Pant, Deepak Kumar Jha, Vinod Kumar Singh Gautam, Chandra Bhushan Tripathi

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Objective: To describe clinical, histopathological and immunohistochemical profile of glioblastoma in patients and to correlate these findings with patient survival. Material and methods: 30 cases of histopathologically diagnosed glioblastomas were included in this study. These cases were analysed in detail for certain clinical and histopathological parameters. Immunohistochemical staining for p53, epidermal growth factor receptor (EGFR), vascular endothelial growth factor (VEGF), mouse double minute 2 homolog (MDM2) and Ki67 was done and scores were calculated. Results of these findings were correlated with patient survival. Results: A retrospective analysis of the histopathology records and clinical case files was done in 30 cases of glioblastoma (WHO grade IV). The mean age of presentation was 50.6 years with a male predilection. The most common involved site was the frontal lobe. Amongst the clinical parameters, age of the patient and extent of surgical resection showed a significant correlation with the patient survival. Histopathological parameters showed no significant correlation with the patient survival, while amongst the immunohistochemical parameters expression of MDM2 showed a significant correlation with the patient survival. Conclusion: In this study incorporating clinical, histopathological and basic panel of immunohistochemistry, age of the patient, extent of the surgical resection and expression of MDM2 showed significant correlation with the patient survival.

Keywords: glioblastoma, p53, EGFR, VEGF, MDM2, Ki67

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Authors: Won Kyung Ham, Kang Hoon Cho, Sang C. Park

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Presented in this paper is a framework of a software ‘WEMax’. The WEMax is invented for analysis and simulation for manned assembly lines to sustain and improve performance of manufacturing systems. In a manufacturing system, performance, such as productivity, is a key of competitiveness for output products. However, the manned assembly lines are difficult to forecast performance, because human labors are not expectable factors by computer simulation models or mathematical models. Existing approaches to performance forecasting of the manned assembly lines are limited to matters of the human itself, such as ergonomic and workload design, and non-human-factor-relevant simulation. Consequently, an approach for the forecasting and improvement of manned assembly line performance is needed to research. As a solution of the current problem, this study proposes a framework that is for generation and simulation of virtual manned assembly lines, and the framework has been implemented as a software.

Keywords: performance forecasting, simulation, virtual manned assembly line, WEMax

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Authors: C. Patrascioiu, M. Jamali

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The paper deals with the simulation of the crude distillation process using the Unisim Design simulator. The necessity of simulating this process is argued both by considerations related to the design of the crude distillation column, but also by considerations related to the design of advanced control systems. In order to use the Unisim Design simulator to simulate the crude distillation process, the identification of the simulators used in Romania and an analysis of the PRO/II, HYSYS, and Aspen HYSYS simulators were carried out. Analysis of the simulators for the crude distillation process has allowed the authors to elaborate the conclusions of the success of the crude modelling. A first aspect developed by the authors is the implementation of specific problems of petroleum liquid-vapors equilibrium using Unisim Design simulator. The second major element of the article is the development of the methodology and the elaboration of the simulation program for the crude distillation process, using Unisim Design resources. The obtained results validate the proposed methodology and will allow dynamic simulation of the process.  

Keywords: crude oil, distillation, simulation, Unisim Design, simulators

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Authors: Zina Saheb, Ezz El-Masry

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As CMOS technology scaling down, Silicon oxide thickness (SiO2) become very thin (few Nano meters). When SiO2 is less than 3nm, gate direct tunneling (DT) leakage current becomes a dormant problem that impacts the transistor performance. Floating gate MOSFET (FGMOSFET) has been used in many low-voltage and low-power applications. Most of the available simulation models of FGMOSFET for analog circuit design does not account for gate DT current and there is no accurate analysis for the gate DT. It is a crucial to use an accurate mode in order to get a realistic simulation result that account for that DT impact on FGMOSFET performance effectively.

Keywords: CMOS transistor, direct-tunneling current, floating-gate, gate-leakage current, simulation model

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Authors: Madre Paarlber, Alwiena Blignaut

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Background: Medication administration errors remains a global patient safety problem targeted by the WHO (World Health Organization), yet research on this matter is sparce within the South African context. Objective: The aim was to explore and describe nurses’ (medication administrators) perceptions regarding medication administration safety-related culture, incidence, causes, and reporting in the Gauteng Province of South Africa, and to determine any relationships between perceived variables concerned with medication safety (safety culture, incidences, causes, reporting of incidences, and reasons for non-reporting). Method: A quantitative research design was used through which self-administered online surveys were sent to 768 nurses (medication administrators) (n=217). The response rate was 28.26%. The survey instrument was synthesised from the Agency of Healthcare Research and Quality (AHRQ) Hospital Survey on Patient Safety Culture, the Registered Nurse Forecasting (RN4CAST) survey, a survey list prepared from a systematic review aimed at generating a comprehensive list of medication administration error causes and the Medication Administration Error Reporting Survey from Wakefield. Exploratory and confirmatory factor analyses were used to determine the validity and reliability of the survey. Descriptive and inferential statistical data analysis were used to analyse quantitative data. Relationships and correlations were identified between items, subscales and biographic data by using Spearmans’ Rank correlations, T-Tests and ANOVAs (Analysis of Variance). Nurses reported on their perceptions of medication administration safety-related culture, incidence, causes, and reporting in the Gauteng Province. Results: Units’ teamwork deemed satisfactory, punitive responses to errors accentuated. “Crisis mode” working, concerns regarding mistake recording and long working hours disclosed as impacting patient safety. Overall medication safety graded mostly positively. Work overload, high patient-nurse ratios, and inadequate staffing implicated as error-inducing. Medication administration errors were reported regularly. Fear and administrative response to errors effected non-report. Non-report of errors’ reasons was affected by non-punitive safety culture. Conclusions: Medication administration safety improvement is contingent on fostering a non-punitive safety culture within units. Anonymous medication error reporting systems and auditing nurses’ workload are recommended in the quest of improved medication safety within Gauteng Province private hospitals.

Keywords: incidence, medication administration errors, medication safety, reporting, safety culture

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Authors: Philippe Larvet

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This paper presents the concept of an object-based programming language where tests (if... then... else) and control structures (while, repeat, for...) disappear and are replaced by conditions on data. According to the object paradigm, by using this concept, data are still embedded inside objects, as variable-value couples, but object methods are expressed into the form of logical propositions (‘conditions on data’ or COD).For instance : variable1 = value1 AND variable2 > value2 => variable3 = value3. Implementing this approach, a central inference engine turns and examines objects one after another, collecting all CODs of each object. CODs are considered as rules in a rule-based system: the left part of each proposition (left side of the ‘=>‘ sign) is the premise and the right part is the conclusion. So, premises are evaluated and conclusions are fired. Conclusions modify the variable-value couples of the object and the engine goes to examine the next object. The paper develops the principles of writing CODs instead of complex algorithms. Through samples, the paper also presents several hints for implementing a simple mechanism able to process this ‘COD language’. The proposed approach can be used within the context of simulation, process control, industrial systems validation, etc. By writing simple and rigorous conditions on data, instead of using classical and long-to-learn languages, engineers and specialists can easily simulate and validate the functioning of complex systems.

Keywords: conditions on data, logical proposition, programming without code, object-oriented programming, system simulation, system validation

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Authors: R. Periyasamy, Deepak Joshi, Sneh Anand

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Foot posture assessment is important to evaluate foot type, causing gait and postural defects in all age groups. Although different methods are used for classification of foot arch type in clinical/research examination, there is no clear approach for selecting the most appropriate measurement system. Therefore, the aim of this study was to develop a system for evaluation of foot type as clinical decision-making aids for diagnosis of flat and normal arch based on the Arch Index (AI) and foot pressure distribution parameter - Power Ratio (PR) data. The accuracy of the system was evaluated for 27 subjects with age ranging from 24 to 65 years. Foot area measurements (hind foot, mid foot, and forefoot) were acquired simultaneously from foot pressure intensity image using portable PedoPowerGraph system and analysis of the image in frequency domain to obtain foot pressure distribution parameter - PR data. From our results, we obtain 100% classification accuracy of normal and flat foot by using the linear discriminant analysis method. We observe there is no misclassification of foot types because of incorporating foot pressure distribution data instead of only arch index (AI). We found that the mid-foot pressure distribution ratio data and arch index (AI) value are well correlated to foot arch type based on visual analysis. Therefore, this paper suggests that the proposed system is accurate and easy to determine foot arch type from arch index (AI), as well as incorporating mid-foot pressure distribution ratio data instead of physical area of contact. Hence, such computational tool based system can help the clinicians for assessment of foot structure and cross-check their diagnosis of flat foot from mid-foot pressure distribution.

Keywords: arch index, computational tool, static foot pressure intensity image, foot pressure distribution, linear discriminant analysis

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Authors: James Moir

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The mainstay of Big Data is prediction in that it allows practitioners, researchers, and policy analysts to predict trends based upon the analysis of large and varied sources of data. These can range from changing social and political opinions, patterns in crimes, and consumer behaviour. Big Data has therefore shifted the criterion of success in science from causal explanations to predictive modelling and simulation. The 19th-century science sought to capture phenomena and seek to show the appearance of it through causal mechanisms while 20th-century science attempted to save the appearance and relinquish causal explanations. Now 21st-century science in the form of Big Data is concerned with the prediction of appearances and nothing more. However, this pulls social science back in the direction of a more rule- or law-governed reality model of science and away from a consideration of the internal nature of rules in relation to various practices. In effect Big Data offers us no more than a world of surface appearance and in doing so it makes disappear any context-specific conceptual sensitivity.

Keywords: big data, appearance, disappearance, surface, epistemology

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Authors: Masayuki Mori

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This study investigates the relationship between teachers’ perceptions of the usability of classroom space and various elements, including both physical and non-physical, of classroom environments. With the introduction of the GIGA School funding program in Japan in 2019, understanding its impact on learning in classroom space is crucial. The program enabled local educational authorities (LEA) to make it possible to provide one PC/tablet for each student of both elementary and junior high schools. Moreover, at the same time, the program also supported LEA to purchase other electronic devices for educational purposes such as electronic whiteboards, large displays, and real image projectors. A nationwide survey was conducted using random sampling methodology among 100 junior high schools to collect data on classroom space. Of those, 60 schools responded to the survey. The survey covered approximately fifty items, including classroom space size, class size, and educational electronic devices owned. After the data compilation, statistical analysis was used to identify correlations between the variables and to explore the extent to which classroom environment elements influenced teachers’ perceptions. Furthermore, decision tree analysis was applied to visualize the causal relationships between the variables. The findings indicate a significant negative correlation between class size and teachers’ evaluation of usability. In addition to the class size, the way students stored their belongings also influenced teachers’ perceptions. As for the placement of educational electronic devices, the installation of a projector produced a small negative correlation with teachers’ perceptions. The study suggests that while the GIGA School funding program is not significantly influential, traditional educational conditions such as class size have a greater impact on teachers’ perceptions of the usability of classroom space. These results highlight the need for awareness and strategies to integrate various elements in designing the learning environment of the classroom for teachers and students to improve their learning experience.

Keywords: classroom space, GIGA School, questionnaire survey, teachers’ perceptions

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Authors: Zahra Hamedani, Ebrahim Solgi, Henry Skates, Gillian Isoardi

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Daylighting plays a pivotal role in promoting productivity and user satisfaction in office spaces. There is an ongoing trend in designing office buildings with a high proportion of glazing which relatively increases the risk of high visual discomfort. Providing a more realistic lighting analysis can be of high value at the early stages of building design when necessary changes can be made at a very low cost. This holistic approach can be achieved by incorporating subjective evaluation and user behaviour in computer simulation and provide a comprehensive lighting analysis. In this research, a detailed computer simulation model has been made using Radiance and Daysim. Afterwards, this model was validated by measurements and user feedback. The case study building is the school of science at Griffith University, Gold Coast, Queensland, which features highly glazed office spaces. In this paper, the visual comfort predicted by the model is compared with a preliminary survey of the building users to evaluate how user behaviour such as desk position, orientation selection, and user movement caused by daylight changes and other visual variations can inform perceptions of visual comfort. This work supports preliminary design analysis of visual comfort incorporating the effects of gaze shift patterns and views with the goal of designing effective layout for office spaces.

Keywords: lighting simulation, office buildings, user behaviour, validation, visual comfort

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Authors: Lizbeth Puerta, Enselmina Marín

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The purpose of this research is to present a survey to be applied to professors of public universities, to identify the factors that benefit or hinder the university-industry relation. Hence, this research studies some elements that integrate the variables: Knowledge management, technology management, and technology transfer; to define the existence of a relation between these variables and the industry necessities of innovation. This study is exploratory, descriptive and non-experimental. The research question is: What is the impact of the knowledge management, the technology management, and the technology transfer, made by administrative support areas of the public universities, in the industries innovation? Thus, literature review was made to identify some elements that should be considered to design a survey that allows to obtain valid information to the study variables. After this, the survey was developed, and the Content Validity Analysis was made through the Lawshe Model. The analysis indicated that the Content Validity Index (CVI) was 0.80. Hence, it was determined that this survey presents acceptable psychometric properties to be used as an evaluation tool.

Keywords: innovation, knowledge management, technology management, technology transfer

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Authors: Sandra So, Mohd Roslan Ismail, Safurah Jaafar

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With the rapid proliferation of data in healthcare has provided an opportune platform creation of Artificial Intelligence (AI). AI has brought a paradigm shift for healthcare professionals, promising improvement in delivery and quality. This study aims to determine the perception of healthcare personnel on perceived ease of use, perceived usefulness, and subjective norm toward attitude for artificial intelligence acceptance. A cross-sectional single institutional study of employees’ perception of adopting AI in the hospital was conducted. The survey was conducted using a questionnaire adapted from Technology Acceptance Model and a four-point Likert scale was used. There were 96 or 75.5% of the total population responded. This study has shown the significant relationship and the importance of ease of use, perceived usefulness, and subjective norm to the acceptance of AI. In the study results, it concluded that the determining factor to the strong acceptance of AI in their practices is mostly those respondents with the most interaction with the patients and clinical management.

Keywords: artificial intelligence, machine learning, perceived ease of use, perceived usefulness, subjective norm

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Authors: Salem B. Abdalla

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This study investigated the current Building Information Modelling (BIM) trends and practices in the UAE, particularly to shed light on a recently circulated Dubai BIM mandate. Two sets of surveys were mailed to the AEC industry and the corresponding academic sector within the UAE to collect up-to-date data on BIM awareness and utilization. The surveys showed startling results concerning the academic sector in the UAE where almost 70% of respondents were not aware of the BIM mandate. Among the rest, even when aware, the majority of mechanical and electrical engineering schools felt that BIM is not pertinent to their discipline. Therefore, the response to offering BIM in their curriculum was substantially low (35%). On the other hand, the industrial survey identified a large majority (76.5%) of the AEC industry in the UAE are using BIM. The results clearly indicate that the academia should include BIM in their curriculum to produce qualified graduates to support the market. However, the academia is also faced with several obstacles to implement BIM in their curriculum, where the main pretext is that there is “no room for new courses in existing curriculum”.

Keywords: building information modeling, BIM adoption, UAE BIM industry survey, UAE BIM academia survey, Dubai BIM mandate, UK BIM mandate, BIM education, architecture education, engineering schools, BIM implementation, BIM curriculum

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Authors: Meera Tandan, Mohan Timilsina, Martin Cormican, Akke Vellinga

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Background: In general practice, many infections are treated empirically without microbiological confirmation. Understanding susceptibility of antimicrobials during empirical prescribing can be helpful to reduce inappropriate prescribing. This study aims to apply a prediction model using a decision tree approach to predict the antimicrobial resistance (AMR) of urinary tract infections (UTI) based on non-clinical features of patients over 65 years. Decision tree models are a novel idea to predict the outcome of AMR at an initial stage. Method: Data was extracted from the database of the microbiological laboratory of the University Hospitals Galway on all antimicrobial susceptibility testing (AST) of urine specimens from patients over the age of 65 from January 2011 to December 2014. The primary endpoint was resistance to common antimicrobials (Nitrofurantoin, trimethoprim, ciprofloxacin, co-amoxiclav and amoxicillin) used to treat UTI. A classification and regression tree (CART) model was generated with the outcome ‘resistant infection’. The importance of each predictor (the number of previous samples, age, gender, location (nursing home, hospital, community) and causative agent) on antimicrobial resistance was estimated. Sensitivity, specificity, negative predictive (NPV) and positive predictive (PPV) values were used to evaluate the performance of the model. Seventy-five percent (75%) of the data were used as a training set and validation of the model was performed with the remaining 25% of the dataset. Results: A total of 9805 UTI patients over 65 years had their urine sample submitted for AST at least once over the four years. E.coli, Klebsiella, Proteus species were the most commonly identified pathogens among the UTI patients without catheter whereas Sertia, Staphylococcus aureus; Enterobacter was common with the catheter. The validated CART model shows slight differences in the sensitivity, specificity, PPV and NPV in between the models with and without the causative organisms. The sensitivity, specificity, PPV and NPV for the model with non-clinical predictors was between 74% and 88% depending on the antimicrobial. Conclusion: The CART models developed using non-clinical predictors have good performance when predicting antimicrobial resistance. These models predict which antimicrobial may be the most appropriate based on non-clinical factors. Other CART models, prospective data collection and validation and an increasing number of non-clinical factors will improve model performance. The presented model provides an alternative approach to decision making on antimicrobial prescribing for UTIs in older patients.

Keywords: antimicrobial resistance, urinary tract infection, prediction, decision tree

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Authors: Olga Leontjeva

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In the age of Artificial Intelligence (AI), some organization management approaches need to be adapted or changed. Human Resource Management (HRM) is a part of organization management that is under the managers' focus nowadays, because AI integration into organization activities brings some HRM-connected challenges. The topic became more significant during the crises of many organizations in the world caused by the coronavirus pandemic (COVID-19). The paper presents an approach, which will be used for the study that is going to be focused on the various case analysis. The author of the future study will analyze the cases of the organizations from Latvia and Spain that are grouped by the size, type of activity and area of business. The information for the cases will be collected through structured interviews and online surveys. The main result presented is the questionnaire developed that will be used for the study as well as the definition and description of sampling. The first round of the survey will be based on convenience sampling that is the main limitation of the study. To conclude, the approach developed will help to collect valid data if the organizations participating in the survey are ready to share their cases in depth, so the researchers could draw the right conclusions and generalize compared organizations’ cases. The questionnaire developed for the survey is applicable for both written online data collection as well as for the interviews. The case analysis will help to identify some HRM challenges that are connected to AI integration into organization activities such as management of different generation employees and their training peculiarities.

Keywords: age of artificial intelligence, case analysis, generation Y and Z employees, human resource management

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Authors: Afiq Juazer Rizal, Siti Zaleha Misnan, M. Zairi M. Yusof

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Seismic data is the fundamental tool utilized by exploration companies to determine potential hydrocarbon. However, the importance of seismic trace data will be undermined unless the geo-spatial component of the data is understood. Deriving a proposed well to be drilled from data that has positional ambiguity will jeopardize business decision and millions of dollars’ investment that every oil and gas company would like to avoid. Spatial integrity QC workflow has been introduced in PETRONAS to ensure positional errors within the seismic data are recognized throughout the exploration’s lifecycle from acquisition, processing, and seismic interpretation. This includes, amongst other tests, quantifying that the data is referenced to the appropriate coordinate reference system, survey configuration validation, and geometry loading verification. The direct outcome of the workflow implementation helps improve reliability and integrity of sub-surface geological model produced by geoscientist and provide important input to potential hazard assessment where positional accuracy is crucial. This workflow’s development initiative is part of a bigger geospatial integrity management effort, whereby nearly eighty percent of the oil and gas data are location-dependent.

Keywords: oil and gas exploration, PETRONAS, seismic data, spatial integrity QC workflow

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Authors: Boularas El-Alia, Arbi Raja, Bachir Bouiadjra Sara, Rezk-Kallah Haciba, Rezkkallah Baghdad

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Objectives : To determine the handling practices of cytotoxic drugs and to describe clinical manifestations expressed by hospital personnel of Sidi Bel Abbes during the year 2014. Methods: Sectional descriptive study conducted in 3 center university hospital units (Hematology, Oncology and Urology) and Gynecology of EHS Sidi Bel Abbes. A questionnaire was administered to hospital workers regulary exposed to cytotoxic drugs. A work-place visit was performed to have an overview about working conditions. The Cytotoxic Contact Index (CCI) was calculated for each nurse on a period of 15 working days. Treatment of the results was done using SPSS software. Results: The survey reveals that 22 men and 58 women are exposed to cytotoxic drugs for an average of 7 years. Many symptoms such as ocular irritation (38,75%), throat irritation (56,25%), headache (68,75%), dizziness (43,75%), nausea (37,5%), metallic taste (30%), were reported with high frequency. Are noted in the offspring, 3 congenital anomalies,2 diaphragmatic hernia and a cleft palate. The Cytotoxic Contact Index (CCI) was higher than 3 among Oncology nurses and higher than 1 for most of the nurses of Hematology and Gynecology service. The wearing of personal protective clothing was not respected by all workers: (22/23) wear gloves and (20/23) wear a mask,(5/23) wear a cap, (2/23) wear glasses. Only 3 nurses have benefited from continuous training on handling cytotoxic drugs. Conclusion: This study shows a high occupational exposure risk to cytotoxic drugs among persons handling these drugs and the necessity to apply rigorously all measures related to personal protection awareness and training of personnel to minimize these exposure.

Keywords: cytotoxic drugs, handling, clinical manifestations, hospital staff

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Authors: Shuyi Wu, Chuang Li, Quanshui Zheng, Luping Xu

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Stretching and snipping DNA molecule by microfluidic has important application value in gene analysis by lab on a chip. Movement, deformation and fragmenting of DNA in microfluidic are typical fluid-solid coupling problems. An efficient and common simulation system for researching the movement, deformation and fragmenting of DNA by microfluidic has not been well developed. In our study, Brownian dynamics-finite element method (BD-FEM) is used to simulate the dynamic process of stretching and fragmenting DNA by contraction flow. The shape and parameters of micro-channels are changed to optimize the stretching and fragmenting properties of DNA. Our results indicate that strain rate, resulting from contraction microchannel, is the main control parameter for stretching and fragmenting DNA. There is good consistency between the simulation data and previous experimental result about the single DNA molecule behavior and averaged fragmenting properties in this study. BD-FEM method is an efficient calculating tool to research stretching and fragmenting behavior of single DNA molecule and optimize microfluidic devices for manipulating, stretching and fragmenting DNA.

Keywords: fragmenting, DNA, microfluidic, optimize.

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Authors: Joseph E. Estevez, Mahdi Ghazizadeh, James G. Ryan, Ajit D. Kelkar

Abstract:

Radiation shielding is an obstacle in long duration space exploration. Boron Nitride Nanotubes (BNNTs) have attracted attention as an additive to radiation shielding material due to B10’s large neutron capture cross section. The B10 has an effective neutron capture cross section suitable for low energy neutrons ranging from 10-5 to 104 eV and hydrogen is effective at slowing down high energy neutrons. Hydrogenated BNNTs are potentially an ideal nanofiller for radiation shielding composites. We use Molecular Dynamics (MD) Simulation via Material Studios Accelrys 6.0 to model the Young’s Modulus of Hydrogenated BNNTs. An extrapolation technique was employed to determine the Young’s Modulus due to the deformation of the nanostructure at its theoretical density. A linear regression was used to extrapolate the data to the theoretical density of 2.62g/cm3. Simulation data shows that the hydrogenated BNNTs will experience a 11% decrease in the Young’s Modulus for (6,6) BNNTs and 8.5% decrease for (8,8) BNNTs compared to non-hydrogenated BNNT’s. Hydrogenated BNNTs are a viable option as a nanofiller for radiation shielding nanocomposite materials for long range and long duration space exploration.

Keywords: boron nitride nanotube, radiation shielding, young modulus, atomistic modeling

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Authors: Harish Bisht, Bahadur Singh Kotlia, Kireet Kumar

Abstract:

In order to reconstruct past retreating rates, total area loss, volume change and shift in snout position were measured through multi-temporal satellite data from 1989 to 2016 and kinematic GPS survey from 2015 to 2016. The results obtained from satellite data indicate that in the last 27 years, Chaturangi glacier snout has retreated 1172.57 ± 38.3 m (average 45.07 ± 4.31 m/year) with a total area and volume loss of 0.626 ± 0.001 sq. Km and 0.139 Km³, respectively. The field measurements through differential global positioning system survey revealed that the annual retreating rate was 22.84 ± 0.05 m/year. The large variations in results derived from both the methods are probably because of higher difference in their accuracy. Snout monitoring of the Gangotri glacier during the ablation season (May to September) in the years 2005 and 2015 reveals that the retreating rate has been comparatively more declined than that shown by the earlier studies. The GPS dataset shows that the average recession rate is 10.26 ± 0.05 m/year. In order to determine the possible causes of decreased retreating rate, a relationship between debris thickness and melt rate was also established by using ablation stakes. The present study concludes that remote sensing method is suitable for large area and long term study, while kinematic GPS is more appropriate for the annual monitoring of retreating rate of glacier snout. The present study also emphasizes on mapping of all the tributary glaciers in order to assess the overall changes in the main glacier system and its health.

Keywords: Chaturangi glacier, Gangotri glacier, glacier snout, kinematic global positioning system, retreat rate

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Authors: Mehmet Savsar

Abstract:

This paper presents a practical case application of simulation modeling and analysis in a specific industrial setting. Various maintenance related parameters of the equipment in the system under consideration are determined and a simulation model is developed to study system behavior. System performance is determined based on established parameters and operational policies, which included system operation with and without preventive maintenance implementation. The results show that preventive maintenance practice has significant effects on improving system productivity. The simulation procedures outlined in this paper can be used by operation managers to perform production line analysis under different maintenance policies in various industrial settings.

Keywords: simulation, production line, machine failures, maintenance, industrial bakery

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Authors: Sharma Aseem, Dhurat Rachita, Pawar Varsha, Khalse Manisha

Abstract:

Introduction: Androgenetic alopecia (AGA) is a prevalent condition characterized by progressive hair thinning driven by genetic and androgen-related factors. The current FDA-approved treatments include oral finasteride and topical minoxidil, though many patients seek combination therapies to enhance results. This study aims to evaluate the effectiveness of a combination therapy involving Minoxidil, Finasteride, and Capixyl™ based on feedback from dermatologists. Methodology: A survey, validated by experts, was distributed to 29 leading dermatologists across India (in Tier 1 and 2 cities). The survey examined real-world clinical experiences, focusing on patient outcomes and the overall effectiveness of the mentioned formulation. Results: Among the surveyed dermatologists, 41.4% identified women aged 35-40 as the most frequently diagnosed with female pattern hair loss. The combination therapy with Minoxidil, Finasteride, and Capixyl™ was utilized by 34.5% of dermatologists for over 60 patients per month. The majority highlighted the benefits of this combination therapy, which acts via multiple mechanisms, such as vasodilation and dihydrotestosterone (DHT) receptor blockade, resulting in improved hair regrowth. Additionally, patients demonstrated better clinical outcomes, enhanced compliance, and fewer side effects. Demographically, younger patients, particularly those with AGA for less than 10 years, responded more positively to the treatment. Early intervention led to quicker and more significant results. Overall satisfaction among dermatologists was high, with 86.2% expressing positive feedback on the therapy. In terms of treatment outcomes, 51.7% of dermatologists observed visible results within 4-6 months, while 34.5% noticed a significant reduction in hair fall within 8-12 weeks. Improvements in scalp health were reported by 48.3%, and 51.7% saw an increased hair density within 3-4 months. Despite mild side effects such as scalp irritation, dryness, flaking, and occasional issues like folliculitis, headaches, itching, and redness, patient satisfaction remained high. Dermatologists reported that 93.1% of patients experienced faster and better hair regrowth with Capixyl™ compared to Minoxidil alone. Suggestions for improving the formulation included incorporating peptides like Saw Palmetto and enhancing product packaging to better meet patient needs. Discussion: The combination of Minoxidil, Finasteride, and Capixyl™ yielded positive clinical outcomes, especially in improving hair density, scalp health, and overall patient satisfaction. Dermatologists found that Capixyl™ peptides enhanced the therapeutic effect, promoting hair regrowth and improving compliance. While side effects were generally mild, there were suggestions to further improve the formulation by adding additional peptides like Saw Palmetto. Conclusion: The combination of Minoxidil and Finasteride fortified with Capixyl™ presents a promising therapeutic option for managing AGA. Dermatologists reported significant improvements in hair density, scalp health, and patient satisfaction. With its favorable efficacy and manageable side effects, this formulation proves to be a valuable addition to the treatment landscape for AGA.

Keywords: androgenetic alopecia, combination therapy, minoxidil, finasteride, capixyl

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