Search results for: time series data mining

Authors: Adekunle Kolawole Ojo, Idowu Peter Adebayo, Egwuche Sylvester O.

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Chronic Kidney Disease (CKD) is a significant cause of morbidity and mortality across developed and developing nations and is associated with increased risk. There are no existing electronic means of capturing and monitoring CKD in Nigeria. The work is aimed at developing a spatial data model that can be used to implement renal registries required for tracking and monitoring the spatial distribution of renal diseases by public health officers and patients. In this study, we have developed a spatial data model for a functional renal registry.

Keywords: renal registry, health informatics, chronic kidney disease, interface

Procedia PDF Downloads 179

Authors: I. Ben Kaddour, S. Larbaoui

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Since their first synthesis in 1984, silicoaluminophosphates have proven their effectiveness as a good adsorbent and catalyst in several environmental and energy applications. In this work, the photocatalytic reaction of the photo-degradation of a pharmaceutical product in water was carried out in the presence of a series of materials based on titanium oxide, anatase phase, supported on the microporous framework of the SAPO4-5 at different levels, under ultraviolet light. These photo-catalysts were characterized by different physicochemical analysis methods in order to determine their structural, textural, and morphological properties, such as X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), microscopy scanning electronics (SEM), nitrogen adsorption measurements, UV-visible diffuse reflectance spectroscopy (UV-Vis-DRS). In this study, liquid chromatography coupled with spectroscopy of mass (LC-MS) was used to determine the nature of the intermediate products formed during the photocatalytic degradation of DCF.

Keywords: photocatalysis, titanium dioxide, SAPO-5, diclofenac

Procedia PDF Downloads 54

Authors: Mehmet Demir Kaya, Onur İleri, Süleyman Avcı

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This study was conducted to determine a suitable time and temperature combination for the electrical conductivity test to be used in sorghum seeds. Fifty seeds known initial seed moisture content and weight of fresh and dead seeds (105°C for 6h) of seven sorghum cultivars were used as material. The electrical conductivities of soak water were measured using EC meter at 20, 25 and 30°C for 4, 8, 12 and 24 h using 50 mL deionized water. The experimental design was three factors factorial (7 × 3 × 4) arranged in a completely randomized design; with four replications and 50 seeds per replicate. The results showed that increased time and temperature caused a remarkable increase in EC values of all of the cultivars. Temperature significantly affected the electrical conductivity values and the best results were obtained at 25°C. The cultivars having the lowest germination percentage gave the highest electrical conductivity value. Dead seeds always gave higher electrical conductivity at 25°C for all periods. It was concluded that the temperature of 25°C and higher period than 12 h was the optimum combination for the electrical conductivity test in sorghum.

Keywords: Sorghum bicolor, seed vigor, cultivar, temperature

Procedia PDF Downloads 297

Authors: E. Keramaris, V. Kanakoudis

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In this study the water flow in an open channel over a sharp-crested weir is investigated experimentally. For this reason a series of laboratory experiments were performed in an open channel with a sharp-crested weir. The maximum head expected over the weir, the total upstream water height and the downstream water height of the impact in the constant bed of the open channel were measured. The discharge was measured using a tank put right after the open channel. In addition, the discharge and the upstream velocity were also calculated using already known equations. The main finding is that the relative error percentage for the majority of the experimental measurements is ± 4%, meaning that the calculation of the discharge with a sharp-crested weir gives very good results compared to the numerical results from known equations.

Keywords: sharp-crested weir, weir height, flow measurement, open channel flow

Procedia PDF Downloads 128

Authors: Thomas Giansetto, Olivier Broux, Géraldine Bolen, Stéphanie Claeys

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Objective: To describe a modified preputial urethrostomy in four dogs. Study design: Short case series. Animals: Four male dogs were treated by the modified preputial urethrostomy, three because of urethral stenosis, and one because of severe complications following perineal urethrostomy. Methods: Four dogs were presented for dysuria and urinary obstruction. secondary to urethral stenosis or tear. Obstruction was treated with a modified preputial urethrostomy. Results: Four dogs had resolution of dysuria with a modified preputial urethrostomy without penile amputation. None of the dogs presented signs of dysuria, urinary tract infection, or dermatitis postoperatively. Two dogs showed signs of urinary incontinence 15 days and one month postoperatively. Conclusion: The modified preputial urethrostomy resulted in a favorable prognosis and may be an alternative to prepubic urethrostomy in male dogs.

Keywords: urethrostomy, preputial, technique, urogenital

Procedia PDF Downloads 147

Authors: H. Aksas, S. Boughrara, K. Louhab

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The goal of this study was the use of life cycle assessment (LCA) methodology to assess the environmental impact of pharmaceutical product (four kinds of syrup form and tree kinds of pomade form), which are produced in one leader manufactory in Algeria town that is SAIDAL Company. The impacts generated have evaluated using SimpaPro7.1 with CML92 Method for syrup form and EPD 2007 for pomade form. All impacts evaluated have compared between them, with determination of the compound contributing to each impacts in each case. Data needed to conduct Life Cycle Inventory (LCI) came from this factory, by the collection of theoretical data near the responsible technicians and engineers of the company, the practical data are resulting from the assay of pharmaceutical liquid, obtained at the laboratories of the university. This data represent different raw material imported from European and Asian country necessarily to formulate the drug. Energy used is coming from Algerian resource for the input. Outputs are the result of effluent analysis of this factory with different form (liquid, solid and gas form). All this data (input and output) represent the ecobalance.

Keywords: pharmaceutical product, drug residues, LCA methodology, environmental impacts

Procedia PDF Downloads 237

Authors: M. Zayoud, S. Oueida, S. Ionescu, P. AbiChar

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Background: Wireless sensor network is encompassed of diversified tools of information technology, which is widely applied in a range of domains, including military surveillance, weather forecasting, and earthquake forecasting. Strengthened grounds are always developed for wireless sensor networks, which usually emerges security issues during professional application. Thus, essential technological tools are necessary to be assessed for secure aggregation of data. Moreover, such practices have to be incorporated in the healthcare practices that shall be serving in the best of the mutual interest Objective: Aggregation of encrypted data has been assessed through homomorphic stream cipher to assure its effectiveness along with providing the optimum solutions to the field of healthcare. Methods: An experimental design has been incorporated, which utilized newly developed cipher along with CPU-constrained devices. Modular additions have also been employed to evaluate the nature of aggregated data. The processes of homomorphic stream cipher have been highlighted through different sensors and modular additions. Results: Homomorphic stream cipher has been recognized as simple and secure process, which has allowed efficient aggregation of encrypted data. In addition, the application has led its way to the improvisation of the healthcare practices. Statistical values can be easily computed through the aggregation on the basis of selected cipher. Sensed data in accordance with variance, mean, and standard deviation has also been computed through the selected tool. Conclusion: It can be concluded that homomorphic stream cipher can be an ideal tool for appropriate aggregation of data. Alongside, it shall also provide the best solutions to the healthcare sector.

Keywords: aggregation, cipher, homomorphic stream, encryption

Procedia PDF Downloads 244

Authors: Omar Al Ali

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The current study was aimed to explore the relationships between emotional intelligence, cognitive ability, and leader's performance. Data were collected from 260 senior managers from UAE. The results showed that there are significant relationships between emotional intelligence and leadership performance as measured by the annual internal evaluations of each participant (r = .42, p < .01). Data from regression analysis revealed that both variables namely emotional intelligence (beta = .31, p < .01), and cognitive ability (beta = .29, p < .01), predicted leadership competencies, and together explained 26% of its variance. Data suggests that EI and cognitive ability are significantly correlated with leadership performance. In depth implications of the present findings for human resource development theory and practice are discussed.

Keywords: emotional intelligence, cognitive ability, leadership, performance

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Authors: Tisciane Perpetuo e Oliveira, Dante Inga Narvaez, Marcelo Gradella Villalva

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Installations of solar photovoltaic systems have increased considerably in the last decade. Therefore, it has been noticed that monitoring of meteorological data (solar irradiance, air temperature, wind velocity, etc.) is important to predict the potential of a given geographical area in solar energy production. In this sense, the present work compares two computational tools that are capable of estimating the energy generation of a photovoltaic system through correlation analyzes of solar radiation data: PVsyst software and an algorithm based on the PVlib package implemented in MATLAB. In order to achieve the objective, it was necessary to obtain solar radiation data (measured and from a solarimetric database), analyze the decomposition of global solar irradiance in direct normal and horizontal diffuse components, as well as analyze the modeling of the devices of a photovoltaic system (solar modules and inverters) for energy production calculations. Simulated results were compared with experimental data in order to evaluate the performance of the studied methods. Errors in estimation of energy production were less than 30% for the MATLAB algorithm and less than 20% for the PVsyst software.

Keywords: energy production, meteorological data, irradiance decomposition, solar photovoltaic system

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Authors: Mona Hejazi, Ali Motie Nasrabadi

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Epilepsy is a persistent neurological disorder that affects more than 50 million people worldwide. Hence, there is a necessity to introduce an efficient prediction model for making a correct diagnosis of the epileptic seizure and accurate prediction of its type. In this study we consider how the Effective Connectivity (EC) patterns obtained from intracranial Electroencephalographic (EEG) recordings reveal information about the dynamics of the epileptic brain and can be used to predict imminent seizures, as this will enable the patients (and caregivers) to take appropriate precautions. We use this definition because we believe that effective connectivity near seizures begin to change, so we can predict seizures according to this feature. Results are reported on the standard Freiburg EEG dataset which contains data from 21 patients suffering from medically intractable focal epilepsy. Six channels of EEG from each patients are considered and effective connectivity using Directed Transfer Function (DTF) and Granger Causality (GC) methods is estimated. We concentrate on effective connectivity standard deviation over time and feature changes in five brain frequency sub-bands (Alpha, Beta, Theta, Delta, and Gamma) are compared. The performance obtained for the proposed scheme in predicting seizures is: average prediction time is 50 minutes before seizure onset, the maximum sensitivity is approximate ~80% and the false positive rate is 0.33 FP/h. DTF method is more acceptable to predict epileptic seizures and generally we can observe that the greater results are in gamma and beta sub-bands. The research of this paper is significantly helpful for clinical applications, especially for the exploitation of online portable devices.

Keywords: effective connectivity, Granger causality, directed transfer function, epilepsy seizure prediction, EEG

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Authors: O. A. Lawal, O. A Ojesanmi

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The demand for wireless cellular services continues to increase while the radio resources remain limited. Thus, network operators have to continuously manage the scarce radio resources in order to have an improved quality of service for mobile users. This paper proposes how to handle the problem of congestion in the mobile network by prioritizing handoff call, using the guard channel allocation scheme. The research uses specific threshold value for the time of allocation of the channel in the algorithm. The scheme would be simulated by generating various data for different traffics in the network as it would be in the real life. The result would be used to determine the probability of handoff call dropping and the probability of the new call blocking as a way of measuring the network performance.

Keywords: call block, channel, handoff, mobile cellular network

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Authors: Virgino Stephano Moniaga

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Thermal comfort inside a building can affect students in their learning process. The learning process of students can be improved if the condition of the classrooms is comfortable. This study will be conducted in SMA Negeri 1 Amurang which is a senior high school building located in South Minahasa Regency. Based on preliminary survey, generally, students were not satisfied with the existing level of comfort, which subsequently affected the teaching and learning process in the classroom. The purpose of this study is to analyze the comfort level of classrooms occupants and recommend building design solutions that can improve the thermal comfort of classrooms. In this study, three classrooms will be selected for thermal comfort measurements. The thermal comfort measurements will be taken in naturally ventilated classrooms. The measured data comprise of personal data (clothing and students activity), air humidity, air temperature, mean radiant temperature and air flow velocity. Simultaneously, the students will be asked to fill out a questionnaire that asked about the level of comfort that was felt at the time. The results of field measurements and questionnaires will be analyzed based on the PMV and PPD indices. The results of the analysis will decide whether the classrooms are comfortable or not. This study can be continued to obtain a more optimal design solution to improve the thermal comfort of the classrooms. The expected results from this study can improve the quality of teaching and learning process between teachers and students which can further assist the government efforts to improve the quality of national education.

Keywords: classrooms, PMV, PPD, thermal comfort

Procedia PDF Downloads 297

Authors: Leal Leonardo, Pires Carlos Augusto de Moraes, Casiraghi Magela

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In this work were realized the modeling and simulation of the catalytic reformer process, of ample form, considering all the equipment that influence the operation performance. Considered it a semi-regenerative reformer, with four reactors in series intercalated with four furnaces, two heat exchanges, one product separator and one recycle compressor. A simplified reactional system was considered, involving only ten chemical compounds related through five reactions. The considered process was the applied to aromatics production (benzene, toluene, and xylene). The models developed to diverse equipment were interconnecting in a simulator that consists of a computer program elaborate in FORTRAN 77. The simulation of the global model representative of reformer unity achieved results that are compatibles with the literature ones. It was then possible to study the effects of operational variables in the products concentration and in the performance of the unity equipment.

Keywords: catalytic reforming, modeling, simulation, petrochemical engineering

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Authors: Talat Ghomashchi, Zahra Akbari, Shirin Malekpour, Marjan Alimirzaee

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Mixing the waste water of industries with natural water has caused environmental pollution. So researcher try to obtain methods and optimum conditions for waste water treatment. One of important stage in waste water treatment is dissolved air flotation. DAF is used for the removal of suspended solids and oils from waste water. In this paper, the effect of several parameters on flotation efficiency with Cationic polyacrylamide as flocculant, was examined, namely, (a) concentration of cationic flocculants, (b) pH (c) fast mixing time, (d) fast mixing speed,(e) slow mixing time,(f) retention time and temperature. After design of experiment, in each trial turbidity of waste water was measured by spectrophotometer. Results show that contribution of pH and concentration of flocculant on flotation efficiency are 75% and 9% respectively. Cationic polyacrylamide led to a significant increase in the settling speed and effect of temperature is negligible. In the optimum condition, the outcome of the DAF unit is increased and amount of suspended solid and oil in waste water is decreased effectively.

Keywords: dissolved air flotation, oil industry, waste water, treatment

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Authors: Leila Karshenas, Hamid Reza Khodaei, Behnaz Mahdavi

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We know that nitric oxide (NO) plays an important role in all sexual activities of animals. It is made in body from NO synthase enzyme and L-arginin molecule. NO can bound with sulfur-iron complexes and because production of steroid sexual hormones is related to enzymes which have this complex, NO can change the activity of these enzymes. NO affects many cells including endothelial cells of veins, macrophages and mast cells. These cells are found in testis leydig cells and therefore are important source of NO in testis tissue. Minimizing damages to sperm at the time of sperm freezing and thawing is really important. The goal of this study was to determine the function of NO before freezing and its effects on quality and viability of sperms after thawing and incubation. 4 Holstein bulls were selected from the age of 4, and artificial insemination was done for 3 weeks (2 times a week). Treatments were 0, 10, 50 and 100 nm of sodium nitroprusside (SNP). Data analysis was performed by SAS98 program. Also, mean comparison was done using Duncan's multiple ranges test (P<0.05). Concentrations used was found to increase motility and viability of spermatozoa at 1, 2 and 3 hours after thawing significantly (P<0.05), but there was no significant difference at zero time. SNP levels reduced the amount of lipid peroxidation in sperm membrane, increased acrosome health and improved sample membranes especially in 50 and 100 nm treatments. According to results, adding SNP to semen diluents increases motility and viability of spermatozoa. Also, it reduces lipid peroxidation in sperm membrane and improves sperm function.

Keywords: sperm motility, nitric oxide, lipid peroxidation, spermatozoa

Procedia PDF Downloads 342

Authors: Shaan Khosla, Jon Krohn

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In a recruiting context, machine learning models are valuable for recommendations: to predict the best candidates for a vacancy, to match the best vacancies for a candidate, and compile a set of similar candidates for any given candidate. While useful to create these models, validating their accuracy in a recommendation context is difficult due to a sparsity of data. In this report, we use network graph data to generate useful representations for candidates and vacancies. We use candidates and vacancies as network nodes and designate a bi-directional link between them based on the candidate interviewing for the vacancy. After using node2vec, the embeddings are used to construct a validation dataset with a ranked order, which will help validate new recommender systems.

Keywords: AI, machine learning, NLP, recruiting

Procedia PDF Downloads 75

Authors: Αlexios Kotsakis, Stefanos Katsavounis, Dimitra Alexiou

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Networks can be utilized to represent project planning problems, using nodes for activities and arcs to indicate precedence relationship between them. For fixed activity duration, a simple algorithm calculates the amount of time required to complete a project, followed by the activities that comprise the critical path. Program Evaluation and Review Technique (PERT) generalizes the above model by incorporating uncertainty, allowing activity durations to be random variables, producing nevertheless a relatively crude solution in planning problems. In this paper, based on the findings of the relevant literature, which strongly suggests that a Beta distribution can be employed to model earthmoving activities, we utilize Monte Carlo simulation, to estimate the project completion time distribution and measure the influence of skewness, an element inherent in activities of modern technical projects. We also extract the activity criticality index, with an ultimate goal to produce more accurate planning estimations.

Keywords: beta distribution, PERT, Monte Carlo simulation, skewness, project completion time distribution

Procedia PDF Downloads 133

Authors: Oktavian Prasetia Wardana, Martono Tri Utomo, Risa Etika, Kartika Darma Handayani, Dina Angelika, Wurry Ayuningtyas

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Background: Critically ill neonates are newborn babies with high-risk factors that potentially cause disability and/or death. Scoring systems for determining the severity of the disease have been widely developed as well as some designs for use in neonates. The SNAPPE-II method, which has been used as a mortality predictor scoring system in several referral centers, was found to be slow in assessing the outcome of critically ill neonates in the Neonatal Intensive Care Unit (NICU). Objective: To analyze the predictive value of MSNS on the outcome of critically ill neonates at the time of arrival up to 24 hours after being admitted to the NICU. Methods: A longitudinal observational analytic study based on medical record data was conducted from January to August 2022. Each sample was recorded from medical record data, including data on gestational age, mode of delivery, APGAR score at birth, resuscitation measures at birth, duration of resuscitation, post-resuscitation ventilation, physical examination at birth (including vital signs and any congenital abnormalities), the results of routine laboratory examinations, as well as the neonatal outcomes. Results: This study involved 105 critically ill neonates who were admitted to the NICU. The outcome of critically ill neonates was 50 (47.6%) neonates died, and 55 (52.4%) neonates lived. There were more males than females (61% vs. 39%). The mean gestational age of the subjects in this study was 33.8 ± 4.28 weeks, with the mean birth weight of the subjects being 1820.31 ± 33.18 g. The mean MSNS score of neonates with a deadly outcome was lower than that of the lived outcome. ROC curve with a cut point MSNS score <10.5 obtained an AUC of 93.5% (95% CI: 88.3-98.6) with a sensitivity value of 84% (95% CI: 80.5-94.9), specificity 80 % (CI 95%: 88.3-98.6), Positive Predictive Value (PPV) 79.2%, Negative Predictive Value (NPV) 84.6%, Risk Ratio (RR) 5.14 with Hosmer & Lemeshow test results p>0.05. Conclusion: The MSNS score has a good predictive value and good calibration of the outcomes of critically ill neonates admitted to the NICU.

Keywords: critically ill neonate, outcome, MSNS, NICU, predictive value

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Authors: Yi-Ling Lin, Lu-Ming Tseng

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Customer sexual harassment is recognized as a serious problem in the personal selling industry. At a personal level, customer sexual harassment could have very negative impacts on the salespeople's physical and mental health. At the organizational level, customer sexual harassment is destructive in terms of organizational reputation. Therefore, this research takes Taiwan's life insurance salesperson as the research sample and explores the impacts of customer power and perceived behavioral control on the life insurance salespeople's whistleblowing intentions to report quid pro quo and hostile work environment types of customer sexual harassment. This study then investigates how personal factors (such as gender difference) may relate to the intentions. Questionnaires are often used as a data collection instrument in studies on workplace sexual harassment. This study collects data through questionnaire surveys, and the research sample of this research is the full-time life insurance salespeople in Taiwan. The hypotheses are examined by using PLS regression approach. The main results show that the types of customer sexual harassment, customer power, and gender are related to the whistleblowing intentions. To our best knowledge, this is the first empirical study to test the relationships among customer reward power, customer coercive power, perceived behavioral control, and the salespeople's whistleblowing intentions toward customer sexual harassment. The findings may provide some implications for the researchers and official authorities.

Keywords: customer sexual harassment, life insurance salespeople, perceived behavioral control, PLS regression

Procedia PDF Downloads 117

Authors: Zülfiye Bıkmaz, Aytolan Yıldırım

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This study was planned as a descriptive regressive study in order to determine the relationship between the competency levels of working nurses, the levels of competency expected by nursing students, the critical thinking disposition of nurses, their perceived autonomy levels, and certain socio demographic characteristics. It is also a methodological study with regard to the intercultural adaptation of the Nursing Competence Scale (NCS) in both working and student samples. The sample of the study group of nurses at a university hospital for at least 6 months working properly and consists of 443 people filled out questionnaires. The student group, consisting of 543 individuals from the 4 public university nursing 3rd and 4th grade students. Data collection tools consisted of a questionnaire prepared in order to define the socio demographic, economic, and personal characteristics of the participants, the ‘Nursing Competency Scale’, the ‘Autonomy Subscale of the Sociotropy – Autonomy Scale’, and the ‘California Critical Thinking Disposition Inventory’. In data evaluation, descriptive statistics, nonparametric tests, Rasch analysis and correlation and regression tests were used. The language validity of the ‘NCS’ was performed by translation and back translation, and the context validity of the scale was performed with expert views. The scale, which was formed into its final structure, was applied in a pilot application from a group consisting of graduate and student nurses. The time constancy of the test was obtained by analysis testing retesting method. In order to reduce the time problems with the two half reliability method was used. The Cronbach Alfa coefficient of the scale was found to be 0.980 for the nurse group and 0.986 for the student group. Statistically meaningful relationships between competence and critical thinking and variables such as age, gender, marital status, family structure, having had critical thinking training, education level, class of the students, service worked in, employment style and position, and employment duration were found. Statistically meaningful relationships between autonomy and certain variables of the student group such as year, employment status, decision making style regarding self, total duration of employment, employment style, and education status were found. As a result, it was determined that the NCS which was adapted interculturally was a valid and reliable measurement tool and was found to be associated with autonomy and critical thinking.

Keywords: nurse, nursing student, competence, autonomy, critical thinking, Rasch analysis

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Authors: Bing Lu, Shuang Li, Hongyuan Zhou

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The steel–concrete hybrid structure has been extensively employed in high–rise buildings and super high–rise buildings. The light gauge steel–concrete hybrid structure, including light gauge steel structure and concrete hybrid structure, is a new–type steel–concrete hybrid structure, which possesses some advantages of light gauge steel structure and concrete hybrid structure. The seismic behavior and loss assessment of three high–rise buildings with three different concrete hybrid structures were investigated through finite element software, respectively. The three concrete hybrid structures are reinforced concrete column–steel beam (RC‒S) hybrid structure, concrete–filled steel tube column–steel beam (CFST‒S) hybrid structure, and tubed concrete column–steel beam (TC‒S) hybrid structure. The nonlinear time-history analysis of three high–rise buildings under 80 earthquakes was carried out. After simulation, it indicated that the seismic performances of three high–rise buildings were superior. Under extremely rare earthquakes, the maximum inter–storey drifts of three high–rise buildings are significantly lower than 1/50. The inter–storey drift and floor acceleration of high–rise building with CFST‒S hybrid structure were bigger than those of high–rise buildings with RC‒S hybrid structure, and smaller than those of high–rise building with TC‒S hybrid structure. Then, based on the time–history analysis results, the post-earthquake repair cost ratio and repair time of three high–rise buildings were predicted through an economic performance analysis method proposed in FEMA‒P58 report. Under frequent earthquakes, basic earthquakes and rare earthquakes, the repair cost ratio and repair time of three high-rise buildings were less than 5% and 15 days, respectively. Under extremely rare earthquakes, the repair cost ratio and repair time of high-rise buildings with TC‒S hybrid structure were the most among three high rise buildings. Due to the advantages of CFST-S hybrid structure, it could be extensively employed in high-rise buildings subjected to earthquake excitations.

Keywords: seismic behavior, loss assessment, light gauge steel–concrete hybrid structure, high–rise building, time–history analysis

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Authors: Zahid Ullah, Atlas Khan

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In today's data-driven world, the role of mathematics in bridging the gap between theory and applications is becoming increasingly vital. This abstract highlights the significance of mathematics as a powerful tool for analyzing, interpreting, and extracting meaningful insights from vast amounts of data. By integrating mathematical principles with real-world applications, researchers can unlock the full potential of data-driven decision-making processes. This abstract delves into the various ways mathematics acts as a bridge connecting theoretical frameworks to practical applications. It explores the utilization of mathematical models, algorithms, and statistical techniques to uncover hidden patterns, trends, and correlations within complex datasets. Furthermore, it investigates the role of mathematics in enhancing predictive modeling, optimization, and risk assessment methodologies for improved decision-making in diverse fields such as finance, healthcare, engineering, and social sciences. The abstract also emphasizes the need for interdisciplinary collaboration between mathematicians, statisticians, computer scientists, and domain experts to tackle the challenges posed by the data-driven landscape. By fostering synergies between these disciplines, novel approaches can be developed to address complex problems and make data-driven insights accessible and actionable. Moreover, this abstract underscores the importance of robust mathematical foundations for ensuring the reliability and validity of data analysis. Rigorous mathematical frameworks not only provide a solid basis for understanding and interpreting results but also contribute to the development of innovative methodologies and techniques. In summary, this abstract advocates for the pivotal role of mathematics in bridging theory and applications in a data-driven world. By harnessing mathematical principles, researchers can unlock the transformative potential of data analysis, paving the way for evidence-based decision-making, optimized processes, and innovative solutions to the challenges of our rapidly evolving society.

Keywords: mathematics, bridging theory and applications, data-driven world, mathematical models

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Authors: Hossam N. Alhawatmeh, Areen I. Albustanji

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Hemodialysis negatively affects physical and psychological health. Pain, poor sleep quality, and low self-esteem are highly prevalent among patients with end-stage renal disease (ESRD) who receive hemodialysis, significantly increasing mortality and morbidity of those patients. Mind-body interventions (MBI), such as mindfulness meditation, have been recently gaining popularity that improved pain, sleep quality, and self-esteem in different populations. However, to our best knowledge, its effects on these health problems in patients receiving hemodialysis have not been studied in Jordan. Thus, the purpose of the study was to examine the effect of mindfulness meditation on pain, sleep quality, and self-esteem in patients with ESR receiving hemodialysis in Jordan. An experimental repeated-measures, randomized, parallel control design was conducted on (n =60) end-stage renal disease patients undergoing hemodialysis between March and June 2023 in the dialysis center at a public hospital in Jordan. Participants were randomly assigned to the experimental (n =30) and control groups (n =30) using a simple random assignment method. The experimental group practiced mindfulness meditation for 30 minutes three times per week for five weeks during their hemodialysis treatments. The control group's patients continued to receive hemodialysis treatment as usual for five weeks during hemodialysis sessions. The study variables for both groups were measured at baseline (Time 0), two weeks after intervention (Time 1), and at the end of intervention (Time 3). The numerical rating scale (NRS), the Rosenberg Self-Esteem Scale (RSES-M), and the Pittsburgh Sleep Quality Index (PSQI) were used to measure pain, self-esteem, and sleep quality, respectively. SPSS version 25 was used to analyze the study data. The sample was described by frequency, mean, and standard deviation as an appropriate. The repeated measures analysis of variance (ANOVA) tests were run to test the study hypotheses. The results of repeated measures ANOVA (within-subject) revealed that mindfulness meditation significantly decrease pain by the end of the intervention in the experimental group. Additionally, mindfulness meditation improved sleep quality and self-esteem in the experimental group, and these improvements occurred significantly after two weeks of the intervention and at the end of the intervention. The results of repeated measures ANOVA (within and between-subject) revealed that the experimental group, compared to the control group, experienced lower levels of pain and higher levels of sleep quality and self-esteem over time. In conclusion, the results provided substantial evidence supporting the positive impacts of mindfulness meditation on pain, sleep quality, and self-esteem in patients with ESRD undergoing hemodialysis. These results highlight the potential of mindfulness meditation as an adjunctive therapy in the comprehensive care of this patient population. Incorporating mindfulness meditation into the treatment plan for patients receiving hemodialysis may contribute to improved well-being and overall quality of life.

Keywords: hemodialysis, pain, sleep quality, self-esteem, mindfulness

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Authors: C. Mayr, J. Periya, A. Kariminezhad

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In this paper, we developed a learning framework for the classification of vulnerable road users (VRU) by their range-Doppler signatures. The frequency-modulated continuous-wave (FMCW) radar raw data is first pre-processed to obtain robust object range-Doppler maps per coherent time interval. The complex-valued range-Doppler maps captured from our outdoor measurements are further fed into a convolutional neural network (CNN) to learn the classification. This CNN has gone through a hyperparameter optimization process for improved learning. By learning VRU range-Doppler signatures, the three classes 'pedestrian', 'dog', and 'noise' are classified with an average accuracy of almost 95%. Interestingly, this classification accuracy holds for a combined longitudinal and lateral object trajectories.

Keywords: machine learning, radar, signal processing, autonomous driving

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Authors: Babak H. Mamaqani, Alimohammad Entezarmahdi

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There are many researches on parameters affecting seismic behavior of steel moment frames. Great deal of these researches considers cover plate connections with or without haunch and direct beam to column connection for exterior columns. Also there are experimental results for interior connections with equal beam depth on both sides but not much research has been performed on the seismic behavior of joints with unequal beam depth. Based on previous experimental results, a series of companion analyses have been set up considering different beam height and connection detailing configuration to investigate the seismic behavior of the connections. Results of this study indicate that when the differences between beams height on both side increases, use of haunch connection system leads to significant improvement in the seismic response whereas other configurations did not provide satisfying results.

Keywords: analytical modeling, Haunch connection, seismic design, unequal beam depth

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Authors: M. Grifoni, G. Petruzzelli, M. Barbafieri, I. Rosellini, B. Pezzarossa, F. Pedron

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Evapotranspiration (ET) covers are an alternative cover system that utilizes water balance approach to maximize the ET process to reduce the contaminants leaching through the soil profile. Microcosm tests allow to identify in a short time the most suitable plant species to be used as alternative covers, their survival capacity, and simultaneously the transpiration and evaporation rate of the cover in a specific contaminated soil. This work shows the soil characterization and ET results of microcosm tests carried out on two contaminated soils by using Triticum durum and Helianthus annuus species. The data indicated that transpiration was higher than evaporation, supporting the use of plants as alternative cover at this contaminated site.

Keywords: contaminated sites, evapotranspiration cover, evapotranspiration, microcosm experiments

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Authors: R. Gautam, P. Sastha Kanagasabai, G. N. Rathna

Abstract:

The proposed healthcare system enables quadriplegic patients, people with severe motor disabilities to send commands to electronic devices and monitor their vitals. The growth of Brain-Computer-Interface (BCI) has led to rapid development in 'assistive systems' for the disabled called 'assistive domotics'. Brain-Computer-Interface is capable of reading the brainwaves of an individual and analyse it to obtain some meaningful data. This processed data can be used to assist people having speech disorders and sometimes people with limited locomotion to communicate. In this Project, Emotiv EPOC Headset is used to obtain the electroencephalogram (EEG). The obtained data is processed to communicate pre-defined commands over the internet to the desired mobile phone user. Other Vital Information like the heartbeat, blood pressure, ECG and body temperature are monitored and uploaded to the server. Data analytics enables physicians to scan databases for a specific illness. The Data is processed in Intel Edison, system on chip (SoC). Patient metrics are displayed via Intel IoT Analytics cloud service.

Keywords: brain computer interface, Intel Edison, Emotiv EPOC, IoT analytics, electroencephalogram

Procedia PDF Downloads 174

Authors: Ramona Zharfpeykan

Abstract:

This study analyses the trend and nature of sustainability key performance indicators (KPIs) reporting in firms globally. It presents both trend and panel data of sustainability reports of 798 firms in the Global Reporting Initiative (GRI) database from 2010 to 2014. The results show some fluctuations in the frequency of sustainability KPI reporting globally across the time while the major focus of reports in firms stayed almost the same. It made us further analyse this trend and found that there are some indicators, such as 'environmental protect expenses' and 'number of grievances', that was barely reported over this period along with some highly popular ones such as 'direct economic value' and 'employment rate'. We could not find any statistical correlation between the KPI reporting percentage and the firms’ industries generally and neither if they belong to environmentally sensitive industries.

Keywords: global reporting initiatives, sustainability reporting, sustainability KPI, trends of sustainability reporting

Procedia PDF Downloads 127

Authors: Ren Junn Hwang, Chung-Chien Lu, Jain-Shing Wu

Abstract:

Cloud outsource storage is one of important services in cloud computing. Cloud users upload data to cloud servers to reduce the cost of managing data and maintaining hardware and software. To ensure data confidentiality, users can encrypt their files before uploading them to a cloud system. However, retrieving the target file from the encrypted files exactly is difficult for cloud server. This study proposes a protocol for performing multikeyword searches for encrypted cloud data by applying k-nearest neighbor technology. The protocol ranks the relevance scores of encrypted files and keywords, and prevents cloud servers from learning search keywords submitted by a cloud user. To reduce the costs of file transfer communication, the cloud server returns encrypted files in order of relevance. Moreover, when a cloud user inputs an incorrect keyword and the number of wrong alphabet does not exceed a given threshold; the user still can retrieve the target files from cloud server. In addition, the proposed scheme satisfies security requirements for outsourced data storage.

Keywords: fault-tolerance search, multi-keywords search, outsource storage, ranked search, searchable encryption

Procedia PDF Downloads 363

Authors: Fatemah A. Alqallaf, Debasis Kundu

Abstract:

The aim of this paper is to introduce a bivariate inverse generalized exponential distribution which has a singular component. The proposed bivariate distribution can be used when the marginals have heavy-tailed distributions, and they have non-monotone hazard functions. Due to the presence of the singular component, it can be used quite effectively when there are ties in the data. Since it has four parameters, it is a very flexible bivariate distribution, and it can be used quite effectively for analyzing various bivariate data sets. Several dependency properties and dependency measures have been obtained. The maximum likelihood estimators cannot be obtained in closed form, and it involves solving a four-dimensional optimization problem. To avoid that, we have proposed to use an EM algorithm, and it involves solving only one non-linear equation at each `E'-step. Hence, the implementation of the proposed EM algorithm is very straight forward in practice. Extensive simulation experiments and the analysis of one data set have been performed. We have observed that the proposed bivariate inverse generalized exponential distribution can be used for modeling dependent competing risks data. One data set has been analyzed to show the effectiveness of the proposed model.

Keywords: Block and Basu bivariate distributions, competing risks, EM algorithm, Marshall-Olkin bivariate exponential distribution, maximum likelihood estimators

Procedia PDF Downloads 122