Search results for: prediction interval

Authors: Abdullah Al Mamoon, Ataur Rahman

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Due to climate change, future rainfall will change at many locations on earth; however, the spatial and temporal patterns of this change are not easy to predict. One approach of predicting such future changes is to examine the trends in the historical rainfall data at a given region and use the identified trends to make future prediction. For this, a statistical trend test is commonly applied to the historical data. This paper examines the trends of daily extreme rainfall events from 30 rain gauges located in the State of Qatar. Rainfall data covering from 1962 to 2011 were used in the analysis. A combination of four non-parametric and parametric tests was applied to identify trends at 10%, 5%, and 1% significance levels. These tests are Mann-Kendall (MK), Spearman’s Rho (SR), Linear Regression (LR) and CUSUM tests. These tests showed both positive and negative trends throughout the country. Only eight stations showed positive (upward) trend, which were however not statistically significant. In contrast, significant negative (downward) trends were found at the 5% and 10% levels of significance in six stations. The MK, SR and LR tests exhibited very similar results. This finding has important implications in the derivation/upgrade of design rainfall for Qatar, which will affect design and operation of future urban drainage infrastructure in Qatar.

Keywords: trends, extreme rainfall, daily rainfall, Mann-Kendall test, climate change, Qatar

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Authors: John Davidson, Matteo Castelletti, Ismael Torres, Victor Terente, Jamie Irvine, Sylvie Raymackers

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The current industry approach to pile driving predictions consists of developing a model of the hammer-pile-soil system which simulates the relationship between soil resistance to driving (SRD) and blow counts (or pile penetration per blow). The SRD methods traditionally used are broadly based on static pile capacity calculations. The SRD is used in combination with the one-dimensional wave equation model to indicate the anticipated blowcounts with depth for specific hammer energy settings. This approach has predominantly been calibrated on relatively long slender piles used in the oil and gas industry but is now being extended to allow calculations to be undertaken for relatively short rigid large diameter monopile foundations. This paper evaluates the accuracy of current industry practice when applied to a site where large diameter monopiles were installed in predominantly stiff fissured clay. Actual geotechnical and pile installation data, including pile driving records and signal matching analysis (based upon pile driving monitoring techniques), were used for the assessment on the case study site.

Keywords: driven piles, fissured clay, London clay, monopiles, offshore foundations

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Authors: D. P. N. De Silva, N. P. P. Liyanage

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Zebrafish (Danio rerio) in the family Cyprinidae, is a tropical freshwater fish widely used as a model organism in scientific research. Use of effective and economical anaesthetic is very important when handling fish. Clove oil (active ingredient: eugenol) was identified as a natural product which is safer and economical compared to synthetic chemicals like methanesulfonate (MS-222). Therefore, the aim of this study was to identify the most effective dosage of clove oil solution as an anaesthetic on mature Zebrafish. Clove oil solution was prepared by mixing pure clove oil with 94% ethanol at a ratio of 1:9 respectively. From that solution, different volumes were selected as (0.4 ml, 0.6 ml and 0.8 ml) and dissolved in one liter of conditioned water (dosages : 0.4 ml/L, 0.6 ml/L and 0.8 ml/L). Water quality parameters (pH, temperature and conductivity) were measured before and after adding clove oil solution. Mature Zebrafish with similar standard length (2.76 ± 0.1 cm) and weight (0.524 ± 0.1 g) were selected for this experiment. Time taken for loss of equilibrium (initiation phase) and complete loss of movements including opercular movement (anaesthetic phase) were measured. To detect the efficacy on anaesthetic recovery, time taken to begin opercular movements (initiation of recovery phase) until swimming (post anaesthetic phase) were observed. The results obtained were analyzed according to the analysis of variance (ANOVA) and Tukeys’ method using SPSS version 17.0 at 95% confidence interval (p<0.5). According to the results, there was no significant difference at the initiation phase of anaesthesia in all three doses though the time taken was varied from 0.14 to 0.41 minutes. Mean value of the time taken to complete the anaesthetic phase at 0.4 ml/L dosage was significantly different with 0.6 ml/L and 0.8 ml/L dosages independently (p=0.01). There was no significant difference among recovery times at all dosages but 0.8 ml/L dosage took longer time compared to 0.6 ml/L dosage. The water quality parameters (pH and temperature) were stable throughout the experiment except conductivity, which increased with the higher dosage. In conclusion, the best dosage need to anaesthetize Zebrafish using clove oil solution was 0.6 ml/L due to its fast initiation of anaesthesia and quick recovery compared to the other two dosages. Therefore clove oil can be used as a good substitute for synthetic anaesthetics because of its efficacy at a lower dosage with higher safety at a low cost.

Keywords: anaesthetics, clove oil, zebrafish, Cyprinidae

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Authors: Eman Ahmed Ahmed, Ghada Abdelmoneim Mohamed, Hamada Ahmed Hamada, Nagui Sobhi Nassif

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Impaired skeletal muscle endurance may be an important causal factor in the development of patellofemoral pain syndrome (PFPS). However, there is lack of information regarding the effect of hip versus knee muscle fatigue on isokinetic parameters, and myoelectric activity of hip and knee muscles in these patients. Purpose: The study was conducted to investigate the effect of hip abductors versus knee extensors fatigue protocol on knee proprioception, hip and knee muscle strength and their myoelectric activity in patients with PFPS. Methods: Fifteen female patients with PFPS participated in the study. They were tested randomly under two fatiguing conditions; hip abductors and knee extensors fatigue protocols. Isolated muscle fatigue of two muscles was induced isokinetically on the affected side in a two separate sessions with a rest interval of at least three days. After determining peak torque, patients performed continuous maximal concentric-eccentric contraction of the selected muscle until the torque output dropped below 50% of peak torque value for 3 consecutive repetitions. Knee proprioception, eccentric hip abductors' peak torque, eccentric knee extensors' peak torque, EMG ratio of vastus medialis obliquus (VMO) / vastus lateralis (VL), and EMG activity of gluteus medius (GM) muscle, were recorded before and immediately after each fatigue protocol using the Biodex Isokinetic system and EMG Myosystem. Results: Two-way within subject MANOVA revealed that eccentric knee extensors’ peak torque decreased significantly after hip abductors fatigue protocol compared to pre fatigue condition (p<0.05). On the other hand, there was no statistically significant difference in the eccentric hip abductors’ peak torque after admitting knee extensors fatigue protocol (p > 0.05). Moreover, no significant difference was found in knee proprioception, EMG ratio of VMO/VL, and EMG activity of GM muscle, after either hip or knee fatigue protocol (p>0.05). Conclusion: A hip focused rehabilitation program may be beneficial in improving knee function through correcting faulty kinematics and hence decrease knee loading in patients with PFPS.

Keywords: electromyography, knee proprioception, mechanical responses, muscle fatigue, patellofemoral pain syndrome

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Authors: Rida Kanwal, Wang Yuhui, Song Weiguo

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Wildfires are one of the most prominent threats to ecosystems, human health, and economic activities, with wind acting as a critical driving factor. This study combines machine learning (ML) and remote sensing (RS) to assess the effects of wind on wildfires in Chongqing Province from August 16-23, 2022. Landsat 8 satellite images were used to estimate the difference normalized burn ratio (dNBR), representing prefire and postfire vegetation conditions. Wind data was analyzed through geographic information system (GIS) mapping. Correlation analysis between wind speed and fire radiative power (FRP) revealed a significant relationship. An autoregressive integrated moving average (ARIMA) model was developed for wind forecasting, and linear regression was applied to determine the effect of wind speed on FRP. The results identified high wind speed as a key factor contributing to the surge in FRP. Wind-rose plots showed winds blowing to the northwest (NW), aligning with the wildfire spread. This model was further validated with data from other provinces across China. This study integrated ML, RS, and GIS to analyze wildfire behavior, providing effective strategies for prediction and management.

Keywords: wildfires, machine learning, remote sensing, wind speed, GIS, wildfire behavior

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Authors: Ahmed Sami Hammami, Mohamed Jellazi

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Background: The aim of the study is to evaluate the magnitude of different psychological outcomes among Tunisian health care professionals (HCP) during the COVID-19 pandemic and to identify the associated factors. Methods: HCP completed a cross-sectional questionnaire from April 4th to April, 28th 2020. The survey collected demographic information, factors that may interfere with the psychological outcomes, behavior changes and mental health measurements. The latter was assessed through 3 scales; the 7-item questions Insomnia Severity Index, the 2-item Patient Health Questionnaire and the 2-item Generalized Anxiety Disorder. Multivariable logistic regression was conducted to identify factors associated with psychological outcomes. Results: A total of 503 HCP successfully completed the survey; among those, n=493 consented to enroll in the study, 411 [83.4%] were physicians, 323 [64.2%] were women and 271 [55%] had a second-line working position. A significant proportion of HCP had anxiety 35.7%, depression 35.1% and insomnia 23.7%. Females, those with psychiatric history and those using public transport exhibited the highest proportions for overall symptoms compared to other groups e.g., depression among females vs. males: 44,9% vs. 18,2%, P=0.00. Those with a previous medical history and nurses, had more anxiety and insomnia compared to other groups e.g. anxiety among nurses vs. interns/residents vs. attending 45,1% vs 36,1% vs 27,5%; p=0.04. Multivariable logistic regression showed that female gender was a risk factor for all psychological outcomes e.g. female sex increased the odds of anxiety by 2.86; 95% confidence interval [CI], 1, 78-4, 60; P=0.00, whereas having a psychiatric history was a risk factor for both anxiety and insomnia. (e.g. for insomnia OR=2,86; 95% [CI], 1,78-4,60; P=0.00), Having protective equipment was associated with lower risk for depression (OR=0,41; 95% CI, 0,27-0,62; P=0.00) and anxiety. Physical activity was also protective against depression and anxiety (OR=0,41, 95% CI, 0,25-0,67, P=0.00). Conclusion: Psychological symptoms are usually undervalued among HCP, though the COVID-19 pandemic played a major role in exacerbating this burden. Prompt psychological support should be endorsed and simple measures such as physical activity and ensuring the necessary protection are paramount to improve mental health outcomes and the quality of care provided to patients.

Keywords: COVID-19 pandemic, health care professionals, mental health, protective factors, psychological symptoms, risk factors

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Authors: Zahra Hamedani

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Many wonderful technological developments in recent years has opened up the possibility of using intelligent buildings for a number of important applications, ranging from minimizing resource usage as well as increasing building efficiency to maximizing comfort, adaption to inhabitants and responsiveness to environmental changes. The concept of an intelligent building refers to the highly embedded, interactive environment within which by exploiting the use of artificial intelligence provides the ability to know its configuration, anticipate the optimum dynamic response to prevailing environmental stimuli, and actuate the appropriate physical reaction to provide comfort and efficiency. This paper contains a general identification of the intelligence paradigm and its impacts on the architecture arena, that with examining the performance of artificial intelligence, a mechanism to analyze and finally for decision-making to control the environment will be described. This mechanism would be a hierarchy of the rational agents which includes decision-making, information, communication and physical layers. This multi-agent system relies upon machine learning techniques for automated discovery, prediction and decision-making. Then, the application of this mechanism regarding adaptation and responsiveness of intelligent building will be provided in two scales of environmental and user. Finally, we review the identifications of sustainability and evaluate the potentials of intelligent building systems in the creation of sustainable architecture and environment.

Keywords: artificial intelligence, intelligent building, responsiveness, adaption, sustainability

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Authors: Jayanta Pokharel, Gokarna Aryal, Netra Kanaal, Chris Tsokos

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Investment in stocks and shares aims to seek potential gains while weighing the risk of future needs, such as retirement, children's education etc. Analysis of the behavior of the stock market returns and making prediction is important for investors to mitigate risk on investment. Historically, the normal variance models have been used to describe the behavior of stock market returns. However, the returns of the financial assets are actually skewed with higher kurtosis, heavier tails, and a higher center than the normal distribution. The Laplace distribution and its family are natural candidates for modeling stock returns. The Variance-Gamma (VG) distribution is the most sought-after distributions for modeling asset returns and has been extensively discussed in financial literatures. In this paper, it explore the other Laplace family, such as Asymmetric Laplace, Skewed Laplace, Kumaraswamy Laplace (KS) together with Variance-Gamma to model the weekly returns of the S&P 500 Index and it's eleven business sector indices. The method of maximum likelihood is employed to estimate the parameters of the distributions and our empirical inquiry shows that the Kumaraswamy Laplace distribution performs much better for stock returns modeling among the choice of distributions used in this study and in practice, KS can be used as a strong alternative to VG distribution.

Keywords: stock returns, variance-gamma, kumaraswamy laplace, maximum likelihood

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Authors: Amit Kumar, Amanpreet Chander, Ashish Sahani

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This paper presents our recent work on real-time human activity detection based on the media pipe pipeline and machine learning algorithms. The proposed system can detect human activities, including running, jumping, squatting, bending to the left or right, and standing still. This is a robust solution for developing a yoga, dance, metaverse, and fitness application that checks for the correction of the pose without having any additional monitor like a personal trainer. MediaPipe solution offers an open-source cross-platform which utilizes a two-step detector-tracker ML pipeline for live detection of key landmarks on our body which can be used for motion data collection. The prediction of real-time poses uses a variety of machine learning techniques and different types of analysis. Without primarily relying on powerful desktop environments for inference, our method achieves real-time performance on the majority of contemporary mobile phones, desktops/laptops, Python, or even the web. Experimental results show that our method outperforms the existing method in terms of accuracy and real-time capability, achieving an accuracy of 99.92% on testing datasets.

Keywords: human activity detection, media pipe, machine learning, metaverse applications

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Authors: Farhad Alizadeh, Alireza Faregh Gharamaleki, Mojtaba Jalilzadeh, Houshang Gholami, Ali Akhoundzadeh

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This study presented hybrid pre-processing approach along with a conceptual model to enhance the accuracy of river discharge prediction. In order to achieve this goal, Ensemble Empirical Mode Decomposition algorithm (EEMD), Discrete Wavelet Transform (DWT) and Mutual Information (MI) were employed as a hybrid pre-processing approach conjugated to Least Square Support Vector Machine (LSSVM). A conceptual strategy namely multi-station model was developed to forecast the Souris River discharge more accurately. The strategy used herein was capable of covering uncertainties and complexities of river discharge modeling. DWT and EEMD was coupled, and the feature selection was performed for decomposed sub-series using MI to be employed in multi-station model. In the proposed feature selection method, some useless sub-series were omitted to achieve better performance. Results approved efficiency of the proposed DWT-EEMD-MI approach to improve accuracy of multi-station modeling strategies.

Keywords: river stage-discharge process, LSSVM, discrete wavelet transform, Ensemble Empirical Decomposition Mode, multi-station modeling

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Authors: Novutry Siregar, Afdal, Emilzon Taslim

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Hyaline Membrane Disease (HMD) is the main cause of respiratory failure in preterm neonates caused by surfactant deficiency. Nasal Continuous Positive Airway Pressure (NCPAP) is the therapy for HMD. The success of therapy is determined by gestational age, birth weight, HMD grade, time of NCAP administration, and time of breathing frequency recovery. The aim of this research is to identify the predictive factor of NCPAP therapy success in preterm neonates with HMD. This study used a cross-sectional design by using medical records of patients who were treated in the Perinatology of the Pediatric Department of Dr. M. Djamil Padang Central Hospital from January 2015 to December 2017. The samples were eighty-two neonates that were selected by using the total sampling technique. Data analysis was done by using the Chi-Square Test and the Multiple Logistic Regression Prediction Model. The results showed the success rate of NCPAP therapy reached 53.7%. Birth weight (p = 0.048, OR = 3.34 95% CI 1.01-11.07), HMD grade I (p = 0.018, OR = 4.95 CI 95% 1.31-18.68), HMD grade II (p = 0.044, OR = 5.52 95% CI 1.04-29.15), and time of breathing frequency recovery (p = 0,000, OR = 13.50 95% CI 3.58-50, 83) are the predictive factors of NCPAP therapy success in preterm neonates with HMD. The most significant predictive factor is the time of breathing frequency recovery.

Keywords: predictive factors, the success of therapy, NCPAP, preterm neonates, HMD

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Authors: Hamidreza Saberkari, Mousa Shamsi, Hossein Ahmadi, Saeed Vaali, , MohammadHossein Sedaaghi

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In the recent years, using signal processing tools for accurate identification of the protein coding regions has become a challenge in bioinformatics. Most of the genomic signal processing methods is based on the period-3 characteristics of the nucleoids in DNA strands and consequently, spectral analysis is applied to the numerical sequences of DNA to find the location of periodical components. In this paper, a novel ensemble algorithm for gene selection in DNA sequences has been presented which is based on the combination of Goertzel algorithm and anti-notch filter (ANF). The proposed algorithm has many advantages when compared to other conventional methods. Firstly, it leads to identify the coding protein regions more accurate due to using the Goertzel algorithm which is tuned at the desired frequency. Secondly, faster detection time is achieved. The proposed algorithm is applied on several genes, including genes available in databases BG570 and HMR195 and their results are compared to other methods based on the nucleotide level evaluation criteria. Implementation results show the excellent performance of the proposed algorithm in identifying protein coding regions, specifically in identification of small-scale gene areas.

Keywords: protein coding regions, period-3, anti-notch filter, Goertzel algorithm

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Authors: Anna M. N. Shifotoka, Richard Walker, Katie Haighton, Richard McNally

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An analysis of trends in Case Notification Rates (CNR) can be used to monitor the impact of Tuberculosis (TB) control interventions over time in order to inform the implementation of current and future TB interventions. A retrospective analysis of trends in TB CNR for two urban regions in Namibia, namely Khomas and Erongo regions, was conducted. TB case notification data were obtained from annual TB reports of the national TB programme, Ministry of Health and Social Services, covering the period from 1997 to 2015. Joinpoint regression was used to analyse trends in CNR for different types of TB groups. A trend was considered to be statistically significant when a p-value was less than 0.05. During the period under review, the crude CNR for all forms of TB declined from 808 to 400 per 100 000 population in Khomas, and from 1051 to 611 per 100 000 population in Erongo. In both regions, significant change points in trends were observed for all types of TB groups examined. In Khomas region, the trend for new smear positive pulmonary TB increased significantly by an annual rate of 4.1% (95% Confidence Interval (CI): 0.3% to 8.2%) during the period 1997 to 2004, and thereafter declined significantly by -6.2% (95%CI: -7.7% to -4.3%) per year until 2015. Similarly, the trend for smear negative pulmonary TB increased significantly by 23.7% (95%CI: 9.7 to 39.5) per year from 1997 to 2004 and thereafter declined significantly by an annual change of -26.4% (95%CI: -33.1% to -19.8%). The trend for all forms of TB CNR in Khomas region increased significantly by 8.1% (95%CI: 3.7 to 12.7) per year from 1997 to 2004 and thereafter declined significantly a rate of -8.7% (95%CI: -10.6 to -6.8). In Erongo region, the trend for smear positive pulmonary TB increased at a rate of 1.2% (95%CI: -1.2% to 3.6%) annually during the earlier years (1997 to 2008), and thereafter declined significantly by -9.3% (95%CI: -13.3% to -5.0%) per year from 2008 to 2015. Also in Erongo, the trend for all forms of TB CNR increased significantly by an annual rate of 4.0% (95%CI: 1.4% to 6.6%) during the years between 1997 to 2006 and thereafter declined significantly by -10.4% (95%CI: -12.7% to -8.0%) per year during 2006 to 2015. The trend for extra-pulmonary TB CNR declined but did not reach statistical significance in both regions. In conclusion, CNRs declined for all types of TB examined in both regions. Further research is needed to study trends for other TB dimensions such as treatment outcomes and notification of drug resistant TB cases.

Keywords: epidemiology, Namibia, temporal trends, tuberculosis

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Authors: Ali Ahmadi, Maryam Abbasi, Mohammad Mehdi Parsaei

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Background: Stress in the workplace today is one of the most important public health concerns and a serious threat to the health of the workforce worldwide. Occupational stress can cause occupational events and reduce quality of life. As a result, it has a very undesirable impact on the performance of organizations, companies, and their human resources. This study aimed to evaluate the relationship between job stress dimensions and occupational accidents in industrial factories in Southwest Iran. Materials and Methods: This cross-sectional study was conducted among 200 workers in the summer of 2023 in the Southwest of Iran. To select participants, we used a convenience sampling method. The research tools in this study were the Health and Safety Executive (HSE) stress questionnaire with 35 questions and 7 dimensions and demographic information. A high score on this questionnaire indicates that there is low job stress and pressure. All workers completed the informed consent form. Univariate analysis was performed using chi-square and T-test. Multiple regression analysis was used to estimate the odds ratios (OR) and 95% confidence interval (CI) for the association of stress-related factors with job accidents in participants. Stata 14.0 software was used for analysis. Results: The mean age of the participants was 39.81(6.36) years. The prevalence of job accidents was 28.0% (95%CI: 21.0, 34.0). Based on the results of the multiple logistic regression with the adjustment of the effect of the confounding variables, one increase in the score of the demand dimension had a protective impact on the risk of job accidents(aOR=0.91,95%CI:0.85-0.95). Additionally, an increase in one of the scores of the managerial support (aOR=0.89, 95% CI: 0.83-0.95) and peer support (aOR=0.76, 95%CI: 0.67-87) dimensions was associated with a lower number of job accidents. Among dimensions, an increase in the score of relationship (aOR=0.89, 95%CI: 0.80-0.98) and change (aOR=0.86, 95%CI: 0.74-0.96) reduced the odds of the accident's occurrence among the workers by 11% and 16%, respectively. However, there was no significant association between role and control dimensions and the job accident (p>0.05). Conclusions: The results show that the prevalence of job accidents was alarmingly high. Our results suggested that an increase in scores of dimensions HSE questioners is significantly associated with a decrease the accident occurrence in the workplace. Therefore, planning to address stressful factors in the workplace seems necessary to prevent occupational accidents.

Keywords: HSE, Iran, job stress occupational accident, safety, occupational health

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Authors: Yung-Jin Weng, Chia-Chi Chang, Chun-Yu Tsai

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This paper is focused on the research of imprinting and replica molding of quasi-grey scale soft mold curved surface microstructure mold. In this paper, a magnetic photocuring forming system is first developed and built independently, then the magnetic curved surface microstructure soft mode is created; moreover, the magnetic performance of the magnetic curved surface at different heights is tested and recorded, and through experimentation and simulation, the magnetic curved surface microstructure soft mold is used in the research of quasi-grey scale soft mold curved surface microstructure imprinting and replica molding. The experimental results show that, under different surface curvatures and voltage control conditions, different quasi-grey scale array microstructures take shape. In addition, this paper conducts research on the imprinting and replica molding of photoresist composite magnetic powder in order to discuss the forming performance of magnetic photoresist, and finally, the experimental result is compared with the simulation to obtain more accurate prediction and results. This research is predicted to provide microstructure component preparation technology with heterogeneity and controllability, and is a kind of valid shaping quasi-grey scale microstructure manufacturing technology method.

Keywords: soft mold, magnetic, microstructure, curved surface

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Authors: Pompa Marcello, Mauro Capocelli, Vincenzo Piemonte

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This work focuses on a mathematical model able to describe the gastro-intestinal physiology and providing a rational tool for the design of an artificial gastro-intestinal system. This latter is mainly devoted to analyse the absorption and bioavailability of drugs and nutrients through in vitro tests in order to overcome (or, at least, to partially replace) in vivo trials. The provided model realizes a conjunction ring (with extended prediction capability) between in vivo tests and mechanical-laboratory models emulating the human body. On this basis, no empirical equations controlling the gastric emptying are implemented in this model as frequent in the cited literature and all the sub-unit and the related system of equations are physiologically based. More in detail, the model structure consists of six compartments (stomach, duodenum, jejunum, ileum, colon and blood) interconnected through pipes and valves. Paracetamol, Ketoprofen, Irbesartan and Ketoconazole are considered and analysed in this work as reference drugs. The mathematical model has been validated against in vivo literature data. Results obtained show a very good model reliability and highlight the possibility to realize tailored simulations for different couples patient-drug, including food adsorption dynamics.

Keywords: gastro-intestinal model, drugs bioavailability, paracetamol, ketoprofen

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Authors: Zhenyu Yang, Qiunan Chen, Xiaocheng Huang

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Reliable prediction of tunnel collapse remains a prominent challenge in the field of civil engineering. In this study, leveraging the nonlinear Hoek-Brown failure criterion and the upper-bound theorem, an analytical solution for the collapse surface of shallowly buried circular tunnels was derived, taking into account the coupled effects of surface loads and pore water pressures. Initially, surface loads and pore water pressures were introduced as external force factors, equating the energy dissipation rate to the external force, yielding our objective function. Subsequently, the variational method was employed for optimization, and the outcomes were juxtaposed with previous research findings. Furthermore, we utilized the deduced equation set to systematically analyze the influence of various rock mass parameters on collapse shape and extent. To validate our analytical solutions, a comparison with prior studies was executed. The corroboration underscored the efficacy of our proposed methodology, offering invaluable insights for collapse risk assessment in practical engineering applications.

Keywords: tunnel roof stability, analytical solution, hoek–brown failure criterion, limit analysis

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Authors: Ismael Zamora, Elisabeth Ortega, Tatiana Radchenko, Guillem Plasencia

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The structure elucidation based on Mass Spectra (MS) data of unknown substances is an unresolved problem that affects many different fields of application. The recent overview of software available for structure elucidation of small molecules has shown the demand for efficient computational tool that will be able to perform structure elucidation of unknown small molecules and peptides. We developed an algorithm for De-Novo fragment analysis based on MS data that proposes a set of scored and ranked structures that are compatible with the MS and MSMS spectra. Several different algorithms were developed depending on the initial set of fragments and the structure building processes. Also, in all cases, several scores for the final molecule ranking were computed. They were validated with small and middle databases (DB) with the eleven test set compounds. Similar results were obtained from any of the databases that contained the fragments of the expected compound. We presented an algorithm. Or De-Novo fragment analysis based on only mass spectrometry (MS) data only that proposed a set of scored/ranked structures that was validated on different types of databases and showed good results as proof of concept. Moreover, the solutions proposed by Mass Spectrometry were submitted to the prediction of NMR spectra in order to elucidate which of the proposed structures was compatible with the NMR spectra collected.

Keywords: De Novo, structure elucidation, mass spectrometry, NMR

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Authors: E. Ghasemi Ardi, K. J. Dong, A. B. Yu, R. Y. Yang

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In current work, a numerical model based on the discrete element method (DEM) was developed which provided information about particle dynamic and impact event condition inside a laboratory scale impact mill (Fritsch). It showed that each particle mostly experiences three impacts inside the mill. While the first impact frequently happens at front surface of the rotor’s rib, the frequent location of the second impact is side surfaces of the rotor’s rib. It was also showed that while the first impact happens at small impact angle mostly varying around 35º, the second impact happens at around 70º which is close to normal impact condition. Also analyzing impact energy revealed that varying mill speed from 6000 to 14000 rpm, the ratio of first impact’s average impact energy and minimum required energy to break particle (Wₘᵢₙ) increased from 0.30 to 0.85. Moreover, it was seen that second impact poses intense impact energy on particle which can be considered as the main cause of particle splitting. Finally, obtained information from DEM simulation along with obtained data from conducted experiments was implemented in semi-empirical equations in order to find selection and breakage functions. Then, using a back-calculation approach, those parameters were used to predict the PSDs of ground particles under different impact energies. Results were compared with experiment results and showed reasonable accuracy and prediction ability.

Keywords: single particle breakage, particle dynamic, population balance model, particle size distribution, discrete element method

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Authors: Ashenafi Ayele, Shewit Haftu, Tesfalem Araya

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Background: “Post-psychotic depression”, “post schizophrenic depression”, and “secondary depression” have been used to describe the occurrence of depressive symptoms during the chronic phase of schizophrenia. Post-psychotic depression is the most common cause of death due to suicide in schizophrenia patients. Overall lifetime risk for patients with schizophrenia is 50% for suicide attempts and 9-13% lifetime risk for completed suicide and also it is associated with poor prognosis and poor quality of life. Objective: To assess determinant of post psychotic depression in schizophrenia patients ACSH and Mekelle General Hospital, Tigray Ethiopia 2019. Methods: An institutional based unmatched case control study was conducted among 69 cases and 138 controls with the ratio of case to control 1 ratio 2. The sample is calculated using epi-info 3.1 to assess the determinant factors of post-psychotic depression in schizophrenia patients. The cases were schizophrenia patients who have been diagnosed at least for more than one-year stable for two months, and the controls are any patients who are diagnosed as schizophrenia patients. Study subjects were selected using a consecutive sampling technique. The Calgary depression scale for schizophrenia self-administered questionnaire was used. Before the interview, it was assessed the client’s capacity to give intended information using a scale called the University of California, San Diego Brief Assessment of Capacity to Consent (UBACC). Bivariant and multiple Logistic regression analysis was performed to determine between the independent and dependent variables. The significant independent predictor was declared at 95% confidence interval and P-value of less than 0.05. Result: Females were affected by post psychotic depression with the (AOR=2.01, 95%CI: 1.003- 4.012, P= 0.49).Patients who have mild form of positive symptom of schizophrenia affected by post psychotic depression with (AOR =4.05, 95%CI: 1.888- 8.7.8, P=0001).Patients who have minimal form of negative symptom of schizophrenia are affected by post psychotic depression with (AOR =4.23, 95%CI: 1.081-17.092, P=.038). Conclusion: In this study, sex (female) and presence of positive and negative symptoms of schizophrenia were significantly associated. It is recommended that the post psychotic depression should be assessed in every schizophrenia patient to decrease the severity of illness, and to improve patient’s quality of life.

Keywords: determinants, post-psychotic depression, Mekelle city

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Authors: K. Doi, T. Nishimura, H. Fujimoto, T. Tanaka

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It has been known that visually impaired persons have some problems in getting visual information. Therefore, information accessibility for the visually impaired persons is very important in a current information society. Some application software with read-aloud function for using personal computer and smartphone are getting more and more popular among visually impaired persons in the world. On the other hand, it is also very important for being able to learn how to read and write characters such as Braille and Visual character. Braille typewriter has been widely used in learning Braille. And also raised-line drawing kits as writing material has been used for decades for especially acquired visually impaired persons. However, there are some drawbacks such as the drawn line cannot be erased. Moreover, visibility of drawing lines is not so good for visually impaired with low vision. We had significant number of requests for developing new writing material for especially acquired visually impaired persons instead of raised-line drawing kits. For conducting development research of novel writing material, we could receive a research grant from ministry of health, labor and welfare in Japanese government. In this research, we developed writing material typed pens and pencils with Beeswax-discharge instead of conventional raised-line drawing kits. This writing material was equipped with cartridge heater for melting beeswax and its heat controller. When this pen users held down the pen tip on the regular paper such as fine paper and so on, the melted beeswax could be discharged from pen tip with valve structure. The beeswax was discharged at 100 gf of holding down force based on results of our previous trial study. The shape of pen tip was semispherical for becoming low friction between pen tip and surface of paper. We conducted one basic experiment to evaluate influence of the curvature of pen tip on ease to write. Concretely, the conditions of curvature was 0.15, 0.35, 0.50, 1.00 mm. The following four interval scales were used as indexes of subjective assessment during writing such as feeling of smooth motion of pen, feeling of comfortable writing, sense of security and feeling of writing fatigue. Ten subjects were asked to participate in this experiment. The results reveal that subjects could draw easily when the radius of the pen tip was 1.00 mm, and lines drawn with beeswax-discharge writing material were easy to perceive.

Keywords: beeswax-discharge writing material, raised-line drawing kits, visually impaired persons, pen tip

Procedia PDF Downloads 311

Authors: Mohammed S. Bhader, Abdullah A. Ghaddaf, Anas Alamoudi, Amal Abualola, Renad Kalantan, Noura Alkhulaifi, Ibrahim Halawani, Mohammed Alhindi

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Background: Noninvasive neurally adjusted ventilatory assist (NAVA) is a relatively new mode of noninvasive ventilation with promising clinical and patient-ventilator outcomes for preterm infants. The aim of this systematic review was to compare NAVA to nasal continuous or positive airway pressure (NCPAP) or intermittent positive airway pressure (NIPP) for preterm infants. Methods: We searched the online databases Medline, Embase, and CENTRAL. We included randomized controlled trials (RCTs) that compared NAVA to NCPAP or NIPP for preterm infants < 37 weeks gestational age. We sought to evaluate the following outcomes: noninvasive intubation failure rate, desaturation rate, the fraction of inspired oxygen (FiO2), and length of stay in the neonatal intensive care unit (NICU). We used the mean difference (MD) to represent continuous outcomes, while the odds ratio (OR) was used to represent dichotomous outcomes. Results: A total of 11 RCTs that enrolled 429 preterm infants were deemed eligible. NAVA showed similar clinical outcomes to NCPAP or NIPP with respect to noninvasive intubation failure (RR for NAVA versus NCPAP: 0.82, 95% confidence interval (CI): 0.49 to 1.37), desaturation rate (RR for NAVA versus NCPAP: 0.69, 95%CI: 0.36 to 1.29; RR for NAVA versus NIPP: 0.58, 95%CI: 0.08 to 4.25), FiO2 (MD for NAVA versus NCPAP: –0.01, 95%CI: –0.04 to 0.02; MD for NAVA versus NIPP: –7.16, 95%CI: –22.63 to 8.31), and length of stay in the NICU (MD for NAVA versus NCPAP: 1.34, 95%CI: –4.17 to 6.85). Conclusion: NAVA showed similar clinical and ventilator-related outcomes compared to the usual care noninvasive respiratory support measures NCPAP or NIPP for preterm infants.

Keywords: preterm infants, noninvasive neurally adjusted ventilatory assist, NIV-NAVA, non-invasive ventilation, nasal continuous or positive airway pressure, NCPAP, intermittent positive airway pressure ventilation, NIPP, respiratory distress syndrome, RDS

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Authors: Florian Tille, Heide Weishaar, Bernhard Gibis, Susanne Schnitzer

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Introduction: The quality of patient-doctor communication and of written health information is central to organizational health literacy (HL). Whether patients understand their doctors’ explanations and textual material on health, however, is understudied. This study identifies the overall levels of patient understanding of health information and its associations with patients’ social characteristics in outpatient health care in Germany. Materials & Methods: This analysis draws on data collected via a 2017 national health survey with a sample of 6,105 adults. Quality of communication was measured for consultations with general practitioners (GPs) and specialists (SPs) via the Ask Me 3 program questions, and through a question on written health material. Correlations with social characteristics were explored employing bivariate and multivariate logistic regression analyses. Results: Over 90% of all respondents reported that they had understood their doctors’ explanations during the last consultation. Failed understanding was strongly correlated with patients’ very poor health (Odds Ratio [OR]: 5.19; 95% confidence interval [CI]: 2.23–12.10; ref. excellent/very good health), current health problem (OR: 6.54, CI: 1.70–25.12; ref. preventive examination) and age 65 years and above (OR: 2.97, CI: 1.10–8.00; ref. 18 to 34 years). Fewer patients answered they understood written material well (86.7% for las visit at GP, 89.7% at SP). Understanding written material poorly was highly associated with basic education (OR: 4.20, CI: 2.76–6.39; ref. higher education) and 65 years old and above (OR: 2.66, CI: 1.43–4.96). Discussion: Overall ratings of oral patient-doctor communication and written communication of health information are high. Yet, a considerable share of patients reports not-understanding their doctors and poor understanding of the written health-related material. Interventions that can contribute to improving organizational HL in outpatient care in Germany include HL training for doctors, reducing system barriers to easily-accessible health information for patients and combining oral and written health communication means. Conclusion: This work adds to the study of organizational HL in Germany. To increase patient understanding of health-relevant information and thereby possibly reduce health disparities, meeting the communication needs especially of persons in different age groups, with basic education and in very poor health is suggested.

Keywords: health survey, organizational health literacy, patient-doctor communication, social characteristics, outpatient care, Ask Me 3

Procedia PDF Downloads 167

Authors: L. Adjlout, N.Benharrat, O. Ladjdel, F. Djemil, A. Adjlout, T. Yahiaoui

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The present investigation is an experimental and numerical studies of the turbulence level influence on the flow in a smooth staggered tube bundle. The experiments were carried out in a closed circuit wind tunnel of subsonic type (TE44). Three turbulence levels at the inlet namely 1%, 4.6% and 6.3% and two Reynolds numbers Re = 9300 and Re = 13950 were performed. The obtained results for the central tube show that there are two minimum values for the angles 70° and 280° corresponding to the separation points. The pressure coefficient distributions seem to have constant values between 120° and 240° resulting in Von Karman street configuration in the wake. These remarks were valid for the tests carried out. The numerical study was performed by the ANSYS FLUENT code which solves the averaged Navier-Stokes equations (RANS). Two turbulence models (k-ε RNG and k-ε realizable), two types of grids and two levels of turbulence at the entrance of 4.6% and 6.3% for Reynolds numbers of 9300 and 13950 were considered. The obtained results for the central tube were compared with the present experimental results. It is concluded that the K-ε realizable is more suitable for the pressure distribution prediction than the K-ε RNG model compared to the present experimental results for this studied case.

Keywords: tube bundle, staggered configuration, turbulence level, numerical, experimental

Procedia PDF Downloads 129

Authors: Sospeter P. Maganga, Alphonce Wikedzi, Mussa D. Budeba, Samwel V. Manyele

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This study characterizes complex gold ores (elemental and mineralogical composition, gold distribution, ore grindability, and mineral liberation) for preliminary process selection. About 200 kg of ore samples were collected from each location using systematic sampling by mass interval. Ores were dried, crushed, milled, and split into representative sub-samples (about 1 kg) for elemental and mineralogical composition analyses using X-ray fluorescence (XRF), fire assay finished with Atomic Absorption Spectrometer (AAS), and X-ray Diffraction (XRD) methods, respectively. The gold distribution was studied on size-by-size fractions, while ore grindability was determined using the standard Bond test. The mineral liberation analysis was conducted using ThermoFisher Scientific Mineral Liberation Analyzer (MLA) 650, where unsieved polished grain mounts (80% passing 700 µm) were used as MLA feed. Two MLA measurement modes, X-ray modal analysis (XMOD) and sparse phase liberation-grain X-ray mapping analysis (SPL-GXMAP), were employed. At least two cyanide consumers (Cu, Fe, Pb, and Zn) and kinetics impeders (Mn, S, As, and Bi) were present in all locations investigated. Copper content at Kapanda (0.77% Cu) and Ibindi (7.48% Cu) exceeded the recommended threshold of 0.5% Cu for direct cyanidation. The gold ore at Ibindi indicated a higher rate of grinding compared to other locations. This could be explained by the highest grindability (2.119 g/rev.) and lowest Bond work index (10.213 kWh/t) values. The pyrite-marcasite, chalcopyrite, galena, and siderite were identified as major gold, copper, lead, and iron-bearing minerals, respectively, with potential for economic extraction. However, only gold and copper can be recovered under conventional milling because of grain size issues (galena is exposed by 10%) and process complexity (difficult to concentrate and smelt iron from siderite). Therefore, the preliminary process selection is copper flotation followed by gold cyanidation for Kapanda and Ibindi ores, whereas gold cyanidation with additives such as glycine or ammonia is selected for Mawemeru and Itumbi ores because of low concentrations of Cu, Pb, Fe, and Zn minerals.

Keywords: complex gold ores, mineral liberation, ore characterization, ore grindability

Procedia PDF Downloads 73

Authors: Ali Reza Tahavvor, Saeed Hosseini, Nazli Jowkar, Afshin Karimzadeh Fard

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Experimental & numeral study of temperature distribution during milling process, is important in milling quality and tools life aspects. In the present study the milling cross-section temperature is determined by using Artificial Neural Networks (ANN) according to the temperature of certain points of the work piece and the points specifications and the milling rotational speed of the blade. In the present work, at first three-dimensional model of the work piece is provided and then by using the Computational Heat Transfer (CHT) simulations, temperature in different nods of the work piece are specified in steady-state conditions. Results obtained from CHT are used for training and testing the ANN approach. Using reverse engineering and setting the desired x, y, z and the milling rotational speed of the blade as input data to the network, the milling surface temperature determined by neural network is presented as output data. The desired points temperature for different milling blade rotational speed are obtained experimentally and by extrapolation method for the milling surface temperature is obtained and a comparison is performed among the soft programming ANN, CHT results and experimental data and it is observed that ANN soft programming code can be used more efficiently to determine the temperature in a milling process.

Keywords: artificial neural networks, milling process, rotational speed, temperature

Procedia PDF Downloads 407

Authors: B. S. Fatoyinbo, D. Stretch, O. T. Amoo, D. Allopi

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This study extends the use of the Drainage Area Regionalization (DAR) method in generating synthetic data and calibrating PyTOPKAPI stream yield for an ungauged basin at a daily time scale. The generation of runoff in determining a river yield has been subjected to various topographic and spatial meteorological variables, which integers form the Catchment Characteristics Model (CCM). Many of the conventional CCM models adapted in Africa have been challenged with a paucity of adequate, relevance and accurate data to parameterize and validate the potential. The purpose of generating synthetic flow is to test a hydrological model, which will not suffer from the impact of very low flows or very high flows, thus allowing to check whether the model is structurally sound enough or not. The employed physically-based, watershed-scale hydrologic model (PyTOPKAPI) was parameterized with GIS-pre-processing parameters and remote sensing hydro-meteorological variables. The validation with mean annual runoff ratio proposes a decent graphical understanding between observed and the simulated discharge. The Nash-Sutcliffe efficiency and coefficient of determination (R²) values of 0.704 and 0.739 proves strong model efficiency. Given the current climate variability impact, water planner can now assert a tool for flow quantification and sustainable planning purposes.

Keywords: catchment characteristics model, GIS, synthetic data, ungauged basin

Procedia PDF Downloads 327

Authors: Issam Aouari, Abdelmalek Abdelhamid

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For seismologists, the characterization of seismic demand should include the amplitude and duration of strong shaking in the system. The duration of ground shaking is one of the key parameters in earthquake resistant design of structures. This paper proposes a nonlinear statistical model to estimate earthquake ground motion duration in soft soils using multiple seismicity indicators. Three definitions of ground motion duration proposed by literature have been applied. With a comparative study, we select the most significant definition to use for predict the duration. A stochastic model is presented for the McCann and Shah Method using nonlinear regression analysis based on a data set for moment magnitude, source to site distance and site conditions. The data set applied is taken from PEER strong motion databank and contains shallow earthquakes from different regions in the world; America, Turkey, London, China, Italy, Chili, Mexico...etc. Main emphasis is placed on soft site condition. The predictive relationship has been developed based on 600 records and three input indicators. Results have been compared with others published models. It has been found that the proposed model can predict earthquake ground motion duration in soft soils for different regions and sites conditions.

Keywords: duration, earthquake, prediction, regression, soft soil

Procedia PDF Downloads 153

Authors: Raza Abdulla Saeed

Abstract:

In this study, the three-dimensional cavitating turbulent flow in a complete Francis turbine is simulated using mixture model for cavity/liquid two-phase flows. Numerical analysis is carried out using ANSYS CFX software release 12, and standard k-ε turbulence model is adopted for this analysis. The computational fluid domain consist of spiral casing, stay vanes, guide vanes, runner and draft tube. The computational domain is discretized with a three-dimensional mesh system of unstructured tetrahedron mesh. The finite volume method (FVM) is used to solve the governing equations of the mixture model. Results of cavitation on the runner’s blades under three different boundary conditions are presented and discussed. From the numerical results it has been found that the numerical method was successfully applied to simulate the cavitating two-phase turbulent flow through a Francis turbine, and also cavitation is clearly predicted in the form of water vapor formation inside the turbine. By comparison the numerical prediction results with a real runner; it’s shown that the region of higher volume fraction obtained by simulation is consistent with the region of runner cavitation damage.

Keywords: computational fluid dynamics, hydraulic francis turbine, numerical simulation, two-phase mixture cavitation model

Procedia PDF Downloads 562

Authors: Lizhou Chen, Abdelhamid Belgaid, Assem Elsayed, Xiaoming Yang

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Compression index is essential in foundation settlement calculation. The traditional method for determining compression index is consolidation test which is expensive and time consuming. Many researchers have used regression methods to develop empirical equations for predicting compression index from soil properties. Based on a large number of compression index data collected from consolidation tests, the accuracy of some popularly empirical equations were assessed. It was found that primary compression index is significantly overestimated in some equations while it is underestimated in others. The sensitivity analyses of soil parameters including water content, liquid limit and void ratio were performed. The results indicate that the compression index obtained from void ratio is most accurate. The ANOVA (analysis of variance) demonstrates that the equations with multiple soil parameters cannot provide better predictions than the equations with single soil parameter. In other words, it is not necessary to develop the relationships between compression index and multiple soil parameters. Meanwhile, it was noted that secondary compression index is approximately 0.7-5.0% of primary compression index with an average of 2.0%. In the end, the proposed prediction equations using power regression technique were provided that can provide more accurate predictions than those from existing equations.

Keywords: compression index, clay, settlement, consolidation, secondary compression index, soil parameter

Procedia PDF Downloads 163