Search results for: experimental performance analysis

Authors: Zhi Hao Chow, Cian Mulligan, Jack Walsh, Antonio Garzon Vico, Dimitar Krastev

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Drug development is resource-intensive, time-consuming, and increasingly expensive with each developmental stage. The success rates of drug development are also relatively low, and the resources committed are wasted with each failed candidate. As such, a reliable method of predicting the success of drug development is in demand. The hypothesis was that some examples of failed drug candidates are pushed through developmental pipelines based on false confidence and may possess common linguistic features identifiable through sentiment analysis. Here, the concept of using text analysis to discover such features in research publications and investor reports as predictors of success was explored. R studios were used to perform text mining and lexicon-based sentiment analysis to identify affective phrases and determine their frequency in each document, then using SPSS to determine the relationship between our defined variables and the accuracy of predicting outcomes. A total of 161 publications were collected and categorised into 4 groups: (i) Cancer treatment, (ii) Neurodegenerative disease treatment, (iii) Vaccines, and (iv) Others (containing all other drugs that do not fit into the 3 categories). Text analysis was then performed on each document using 2 separate datasets (BING and AFINN) in R within the category of drugs to determine the frequency of positive or negative phrases in each document. A relative positivity and negativity value were then calculated by dividing the frequency of phrases with the word count of each document. Regression analysis was then performed with SPSS statistical software on each dataset (values from using BING or AFINN dataset during text analysis) using a random selection of 61 documents to construct a model. The remaining documents were then used to determine the predictive power of the models. Model constructed from BING predicts the outcome of drug performance in clinical trials with an overall percentage of 65.3%. AFINN model had a lower accuracy at predicting outcomes compared to the BING model at 62.5% but was not effective at predicting the failure of drugs in clinical trials. Overall, the study did not show significant efficacy of the model at predicting outcomes of drugs in development. Many improvements may need to be made to later iterations of the model to sufficiently increase the accuracy.

Keywords: data analysis, drug development, sentiment analysis, text-mining

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Authors: Jiexuan Lin, Huiyi Chen

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The development of L2 pronunciation competence remains understudied in the literature and it is not clear what may influence learners’ development of L2 pronunciation. The present study was an attempt to find out which of the two common factors in L2 acquisition, i.e., foreign language anxiety or self-perceived L2 proficiency, can better predict Chinese EFL learners’ pronunciation performance. 78 first-year English majors, who had received a three-month pronunciation training course, were asked to 1) fill out a questionnaire on foreign language classroom anxiety, 2) self-report their L2 proficiency in general, in speaking and in pronunciation, and 3) complete an oral and a written test on their L2 pronunciation (the score of the oral part indicates participants’ pronunciation proficiency in oral production, and the score of the written part indexes participants’ ability in applying pronunciation knowledge in comprehension.) Results showed that the pronunciation scores were negatively correlated with the anxiety scores, and were positively correlated with the self-perceived pronunciation proficiency. But only the written scores in the L2 pronunciation test, not the oral scores, were positively correlated with the L2 self-perceived general proficiency. Neither the oral nor the written scores in the L2 pronunciation test had a significant correlation with the self-perceived speaking proficiency. Given the fairly strong correlations, the anxiety scores and the self-perceived pronunciation proficiency were put in regression models to predict L2 pronunciation performance. The anxiety factor alone accounted for 13.9% of the variance and the self-perceived pronunciation proficiency alone explained 12.1% of the variance. But when both anxiety scores and self-perceived pronunciation proficiency were put in a stepwise regression model, only the anxiety scores had a significant and unique contribution to the L2 pronunciation performance (4.8%). Taken together, the results suggested that the learners’ anxiety level could better predict their L2 pronunciation performance, compared with the self-perceived proficiency levels. The obtained data have the following pedagogical implications. 1) Given the fairly strong correlation between anxiety and L2 pronunciation performance, the instructors who are interested in predicting learners’ L2 pronunciation proficiency may measure their anxiety level, instead of their proficiency, as the predicting variable. 2) The correlation of oral scores (in the pronunciation test) with pronunciation proficiency, rather than with speaking proficiency, indicates that a) learners after receiving some amounts of training are to some extent able to evaluate their own pronunciation ability, implying the feasibility of incorporating self-evaluation and peer comments in course instruction; b) the ‘proficiency’ measure used to predict pronunciation performance should be used with caution. The proficiency of specific skills seemingly highly related to pronunciation (i.e., speaking in this case) may not be taken for granted as an effective predictor for pronunciation performance. 3) The correlation between the written scores with general L2 proficiency is interesting.

Keywords: anxiety, Chinese EFL learners, L2 pronunciation, self-perceived L2 proficiency

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Authors: Chen Bo, Wen Zengping

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Based on the results of previous studies, we focus on the research of real ground motion selection and scaling method for structural performance-based seismic evaluation using nonlinear dynamic analysis. The input of earthquake ground motion should be determined appropriately to make them compatible with the site-specific hazard level considered. Thus, an optimized selection and scaling method are established including the use of not only Monte Carlo simulation method to create the stochastic simulation spectrum considering the multivariate lognormal distribution of target spectrum, but also a spectral shape parameter. Its applications in structural fragility analysis are demonstrated through case studies. Compared to the previous scheme with no consideration of the uncertainty of target spectrum, the method shown here can make sure that the selected records are in good agreement with the median value, standard deviation and spectral correction of the target spectrum, and greatly reveal the uncertainty feature of site-specific hazard level. Meanwhile, it can help improve computational efficiency and matching accuracy. Given the important infection of target spectrum’s uncertainty on structural seismic fragility analysis, this work can provide the reasonable and reliable basis for structural seismic evaluation under scenario earthquake environment.

Keywords: ground motion selection, scaling method, seismic fragility analysis, spectral shape

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Authors: Princess Stephanie P. Llanos, Rinlee Butch M. Cervera

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Lithium iron phosphate (LiFePO4) is a potential cathode material for lithium-ion batteries due to its promising characteristics. In this study, carbon-coated nanograined LiFePO4 is synthesized via wet chemistry method at a low temperature of 400 °C and investigated its performance as a cathode in Lithium battery. The X-ray diffraction pattern of the synthesized samples can be indexed to an orthorhombic LiFePO4 structure. Agglomerated particles that range from 200 nm to 300 nm are observed from scanning electron microscopy images. Transmission electron microscopy images confirm the crystalline structure of LiFePO4 and coating of amorphous carbon layer. Elemental mapping using Energy dispersive spectroscopy analysis revealed the homogeneous dispersion of Fe, P, O, and C elements. On the other hand, the electrochemical performances of the synthesized cathodes were investigated using cyclic voltammetry, galvanostatic charge/discharge tests with different C-rates, and cycling performances. Galvanostatic charge and discharge measurements revealed that the sample sintered at 400 °C for 3 hours with carbon coating demonstrated the highest capacity among the samples which reaches up to 160 mAhg⁻¹ at 0.1C rate.

Keywords: cathode, charge-discharge, electrochemical, lithium batteries

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Authors: T.C. Balachandra, Habibuddin Shaik

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This paper presents experimental results leading towards a better understanding of pre-breakdown and breakdown behavior of vacuum gaps under variable frequency alternating excitations. The frequency variation is in the range of 30 to 300 Hz in steps of 10 Hz for a fixed gap spacing of 0.5 mm. The results indicate that the pre-breakdown currents show an inverse relation with the breakdown voltage in general though erratic behavior was observed over a certain range of frequencies. A breakdown voltage peak was observed at 130 Hz. This was pronounced when the electrode pair was of stainless steel and less pronounced when copper and aluminum electrodes were used. The experimental results are explained based on F-N emission, I-F emission, and also thermal interaction due to quasi-continuous shower of anode micro-particles. Further, it is speculated that the ostensible cause for time delay between voltage and current peaks is due to the presence of neutral molecules in the gap.

Keywords: anode hot-spots, F-N emission, I-F emission, microparticle, neutral molecules, pre-breakdown conduction, vacuum breakdown

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Authors: Siqi Lin, Yangang Zhao

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Concrete-filled steel tube column achieves the excellent performance of high strength, stiffness, and ductility due to the confinement from the steel tube. Well understanding the stress of the steel tube is important to make clear the confinement effect. In this paper, the ultimate stress of the steel tube in circular concrete-filled steel tube columns subjected to axial compression was studied. Experimental tests were conducted to investigate the effects of the parameters, including concrete strength, steel strength, and D/t ratio, on the ultimate stress of the steel tube. The stress of the steel tube was determined by employing the Prandtl-Reuss flow rule associated with isotropic strain hardening. Results indicate that the stress of steel tube was influenced by the parameters. Specimen with higher strength ratio fy/fc and smaller D/t ratio generally leads to a higher utilization efficiency of the steel tube.

Keywords: concrete-filled steel tube, axial compression, ultimate stress, utilization efficiency

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Authors: Vimal O. Kumar, C. K. Muthukumaran, P. Rakesh

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Liquid rocket engine (LRE) combustion chamber is subjected to pressure oscillation during the combustion process. The combustion noise (acoustic noise) is a broad band, small amplitude, high frequency component pressure oscillation. They constitute only a minor fraction ( < 1%) of the entire combustion process. However, this high frequency oscillation is huge concern during the design phase of LRE combustion chamber as it would cause catastrophic failure of the chamber. Depends on the chamber geometry, certain frequencies form standing wave pattern, and they resonate with high amplitude and are known as Eigen modes. These Eigen modes could cause failures unless it is suppressed to be within safe limits. These modes are categorized into radial, tangential, and azimuthal modes, and their structure inside the combustion chamber is of interest to the researchers. In the present proposal, experimental as well as numerical simulation will be performed to obtain the frequency-amplitude characteristics of the model combustion chamber for different baffle configuration. The main objective of this study is to find effect of baffle configuration that would provide better suppression of acoustic modes. The experimental study aims at measuring the frequency amplitude characteristics at certain points in the chamber wall. The experimental measurement will be also used for scheme used in numerical simulation. In addition to experiments, numerical simulation would provide detailed structure of the Eigenmodes exhibited and their level of suppression with the aid of different baffle configurations.

Keywords: baffle, instability, liquid rocket engine, pressure response of chamber

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Authors: Sadeq Al Yaari, Muhammad Alkhunayn, Adham Al Yaari, Ayah Al Yaari, Ayman Al Yaari, Montaha Al Yaari, Sajedah Al Yaari, Fatehi Eissa

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The recent rise of smart educational aids and the move away from traditional listening aids are leading to a fundamental shift in the way in which individuals with attention and listening problems (ALP) manipulate listening inputs and/or act appropriately to the spoken information presented to them. A total sample of twenty-six ALP pupils (m=20 and f=6) between 7-12 years old was selected from different strata based on gender, region and school. In the sample size, thirteen (10 males and 3 females) received the treatment in terms of smart classes provided with smart educational aids in a listening course that lasted for four months, while others did not (they studied the same course by the same instructor but in ordinary class). A pretest was administered to assess participants’ levels, and a posttest was given to evaluate their attention and listening comprehension performance, namely in phonetic and phonological tests with sociolinguistic themes that have been designed for this purpose. Test results were analyzed both psychoneurolinguistically and statistically. Results reveal a remarkable change in pupils’ behavioral listening where scores witnessed a significant difference in the performance of the experimental ALP group in the pretest compared to the posttest (Pupils performed better at the pretest-posttest on phonetics than at the two tests on phonology). It is concluded that smart educational aids designed for listening skills help not only increase the listening command of pupils with ALP to understand what they listen to but also develop their interactive listening capability and, at the same rate, are responsible for increasing concentrated and in-depth listening capacity. Plus, ALP pupils become able to grasp the audio content of text recordings, including educational audio recordings, news, oral stories and tales, views, spiritual/religious text and general knowledge. However, the pupils have not experienced individual smart audio-visual aids that connect listening to other language receptive and productive skills, which could be the future area of research.

Keywords: smart educational aids, listening attention, pupils, problems

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Authors: D. M. Bassuney, W. A. Ibrahim, Medhat A. E. Moustafa

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Appropriate start-up of an anaerobic baffled reactor (ABR) is considered to be the most delicate and important issue in the anaerobic process, and depends on several factors such as wastewater composition, reactor configuration, inoculum and operating conditions. In this work, the start-up performance of an ABR with working volume of 30 liters, fed continuously with synthetic food industrial wastewater along with semi-batch study to measure the methangenic activity by specific methanogenic activity (SMA) test were carried out at various organic loading rates (OLRs) to determine the best OLR used to start up the reactor. The comparison was based on COD removal efficiencies, start-up time, pH stability and methane production. An OLR of 1.8 Kg COD/m3d (5400 gCOD/m3 and 3 days HRT) showed best overall performance with COD removal efficiency of 94.44% after four days from the feeding and methane production of 3802 ml/L with an overall SMA of 0.36 gCH4-COD/gVS.d

Keywords: anaerobic baffled reactor, anaerobic reactor start-up, food industrial wastewater, specific methanogenic activity

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Authors: Bitewulign Mekonnen

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Context: This scientific paper focuses on the use of near-infrared (NIR) spectroscopy to determine glucose concentration in aqueous solutions accurately and rapidly. The study compares six different machine learning methods for predicting glucose concentration and also explores the development of a deep learning model for classifying NIR spectra. The objective is to optimize the detection model and improve the accuracy of glucose prediction. This research is important because it provides a comprehensive analysis of various machine-learning techniques for estimating aqueous glucose concentrations. Research Aim: The aim of this study is to compare and evaluate different machine-learning methods for predicting glucose concentration from NIR spectra. Additionally, the study aims to develop and assess a deep-learning model for classifying NIR spectra. Methodology: The research methodology involves the use of machine learning and deep learning techniques. Six machine learning regression models, including support vector machine regression, partial least squares regression, extra tree regression, random forest regression, extreme gradient boosting, and principal component analysis-neural network, are employed to predict glucose concentration. The NIR spectra data is randomly divided into train and test sets, and the process is repeated ten times to increase generalization ability. In addition, a convolutional neural network is developed for classifying NIR spectra. Findings: The study reveals that the SVMR, ETR, and PCA-NN models exhibit excellent performance in predicting glucose concentration, with correlation coefficients (R) > 0.99 and determination coefficients (R²)> 0.985. The deep learning model achieves high macro-averaging scores for precision, recall, and F1-measure. These findings demonstrate the effectiveness of machine learning and deep learning methods in optimizing the detection model and improving glucose prediction accuracy. Theoretical Importance: This research contributes to the field by providing a comprehensive analysis of various machine-learning techniques for estimating glucose concentrations from NIR spectra. It also explores the use of deep learning for the classification of indistinguishable NIR spectra. The findings highlight the potential of machine learning and deep learning in enhancing the prediction accuracy of glucose-relevant features. Data Collection and Analysis Procedures: The NIR spectra and corresponding references for glucose concentration are measured in increments of 20 mg/dl. The data is randomly divided into train and test sets, and the models are evaluated using regression analysis and classification metrics. The performance of each model is assessed based on correlation coefficients, determination coefficients, precision, recall, and F1-measure. Question Addressed: The study addresses the question of whether machine learning and deep learning methods can optimize the detection model and improve the accuracy of glucose prediction from NIR spectra. Conclusion: The research demonstrates that machine learning and deep learning methods can effectively predict glucose concentration from NIR spectra. The SVMR, ETR, and PCA-NN models exhibit superior performance, while the deep learning model achieves high classification scores. These findings suggest that machine learning and deep learning techniques can be used to improve the prediction accuracy of glucose-relevant features. Further research is needed to explore their clinical utility in analyzing complex matrices, such as blood glucose levels.

Keywords: machine learning, signal processing, near-infrared spectroscopy, support vector machine, neural network

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Authors: Ehsan Yari

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In this paper, a numerical study of sheet cavitation has been performed on DTMB4119 and E779A marine propellers with the boundary element method. In propeller design, various parameters of geometry and fluid are incorporated. So a program is needed to solve the flow taking the whole parameters changing into account. The capability of analyzing the wetted and cavitation flow around propellers in steady, unsteady, uniform, and non-uniform conditions while decreasing computational time compared to numerical finite volume methods with acceptable precision are the characteristic features of the present method. Moreover, modifying the position of the detachment point and its corresponding potential value has been considered. Numerical results have been validated with experimental data, showing a good conformation.

Keywords: cavitation, BEM, DTMB4119, E779A

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Authors: Harishkumar Kamath, Chandrakant R. Kini, N. Yagnesh Sharma

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Gas turbines are highly effective engineered prime movers for converting energy from thermal form (combustion stage) to mechanical form – are widely used for propulsion and power generation systems. One method of increasing both the power output and thermal efficiency is to increase the temperature of the gas entering the turbine. In the advanced gas turbines of today, the turbine inlet temperature can be as high as 1500°C; however, this temperature exceeds the melting temperature of the metal blade. With modern gas turbines operating at extremely high temperatures, it is necessary to implement various cooling methods, so the turbine blades and vanes endure in the path of the hot gases. Merely passing coolant air through the blade does not provide adequate cooling; therefore, it is necessary to implement techniques that will further enhance the heat transfer from the blade walls. It is seen that by incorporating helical grooved passages into the leading edge built on turbulence and higher flow rates through the passages, the blade can be cooled effectively. It seen from the analysis helical grooved passages with diameter 5 mm, helical pitch of 50 mm and 8 starts results in better cooling of turbine blade and gives the best thermal performance.

Keywords: blade cooling, helical grooves, leading edge, numerical analysis

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Authors: Eser Yarar, Fahri Vatansever, A. Tamer Erturk, Sedat Karabay

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In this study, drilling behavior of multi-layer orthotropic polyester composites reinforced with woven polyester fiber and PTFE particle was investigated. Conventional drilling methods have low cost and ease of use. Therefore, it is one of the most preferred machining methods. The increasing range of use of composite materials in many areas has led to the investigation of the machinability performance of these materials. The drilling capability of the synthetic polymer composite material was investigated by measuring the cutting forces using different tool diameters, feed rate and high cutting speed parameters. Cutting forces were measured using a dynamometer in the experiments. In order to evaluate the results of the experiment, the Taguchi experimental design method was used. According to the results, the optimum cutting parameters were obtained for 0.1 mm/rev, 1070 rpm and 2 mm diameter drill bit. Verification tests were performed for the optimum cutting parameters obtained according to the model. Verification experiments showed the success of the established model.

Keywords: cutting force, drilling, polimer composite, Taguchi

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Authors: Ghita Benayad

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Asset allocation, which affects the long-term profitability of portfolios by distributing assets to fulfill a range of investment objectives, is the cornerstone of investment management in the dynamic and complicated world of financial markets. This paper offers a technique for optimizing strategic asset allocation with the goal of improving portfolio performance by addressing the inherent complexity and uncertainty of the market through the use of Principal Component Analysis (PCA) in a multi-objective modeling framework. The study's first section starts with a critical evaluation of conventional asset allocation techniques, highlighting how poorly they are able to capture the intricate relationships between assets and the volatile nature of the market. In order to overcome these challenges, the project suggests a PCA-driven methodology that isolates important characteristics influencing asset returns by decreasing the dimensionality of the investment universe. This decrease provides a stronger basis for asset allocation decisions by facilitating a clearer understanding of market structures and behaviors. Using a multi-objective optimization model, the project builds on this foundation by taking into account a number of performance metrics at once, including risk minimization, return maximization, and the accomplishment of predetermined investment goals like regulatory compliance or sustainability standards. This model provides a more comprehensive understanding of investor preferences and portfolio performance in comparison to conventional single-objective optimization techniques. While applying the PCA-driven multi-objective optimization model to historical market data, aiming to construct portfolios better under different market situations. As compared to portfolios produced from conventional asset allocation methodologies, the results show that portfolios optimized using the proposed method display improved risk-adjusted returns, more resilience to market downturns, and better alignment with specified investment objectives. The study also looks at the implications of this PCA technique for portfolio management, including the prospect that it might give investors a more advanced framework for navigating financial markets. The findings suggest that by combining PCA with multi-objective optimization, investors may obtain a more strategic and informed asset allocation that is responsive to both market conditions and individual investment preferences. In conclusion, this capstone project improves the field of financial engineering by creating a sophisticated asset allocation optimization model that integrates PCA with multi-objective optimization. In addition to raising concerns about the condition of asset allocation today, the proposed method of portfolio management opens up new avenues for research and application in the area of investment techniques.

Keywords: asset allocation, portfolio optimization, principle component analysis, multi-objective modelling, financial market

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Authors: Hamed Hossein Afshari, Shahrzad Jalali, Amir Hossein Ghods, Bijan Raahemi

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This paper introduces an automated clustering solution that applies to WiFi/Bluetooth sensing data and is later used for traffic management applications. The paper initially summarizes a number of clustering approaches and thereafter shows their performance for noise removal. In this context, clustering is used to recognize WiFi and Bluetooth MAC addresses that belong to passengers traveling by a public urban transit bus. The main objective is to build an intelligent system that automatically filters out MAC addresses that belong to persons located outside the bus for different routes in the city of Ottawa. The proposed intelligent system alleviates the need for defining restrictive thresholds that however reduces the accuracy as well as the range of applicability of the solution for different routes. This paper moreover discusses the performance benefits of the presented clustering approaches in terms of the accuracy, time and space complexity, and the ease of use. Note that results of clustering can further be used for the purpose of the origin-destination estimation of individual passengers, predicting the traffic load, and intelligent management of urban bus schedules.

Keywords: WiFi-Bluetooth sensing, cluster analysis, artificial intelligence, traffic management

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Authors: Varsha Hemant Patil, Swati A. Bhavsar, Abolee H. Patil

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Image quality assessment plays an important role in image evaluation. This paper aims to present an investigation of classic techniques in use for image quality assessment, especially for super-resolution imaging. Researchers have contributed a lot towards the development of super-resolution imaging techniques. However, not much attention is paid to the development of metrics for testing the performance of developed techniques. In this paper, the study report of existing image quality measures is given. The paper classifies reviewed approaches according to functionality and suitability for super-resolution imaging. Probable modifications and improvements of these to suit super-resolution imaging are presented. The prime goal of the paper is to provide a comprehensive reference source for researchers working towards super-resolution imaging and suggest a better framework for measuring the performance of super-resolution imaging techniques.

Keywords: interpolation, MSE, PSNR, SSIM, super resolution

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Authors: H. J. Pramod, S. Pethkar

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The evaluation of antiurolithiatic potentials from the extracts of Cucumis sativus fruits at different doses and cystone (standard formulation) at a dose of 750 mg/kg were measured for both preventive and curative regimen in wistar rats by adding 0.75% v/v ethylene glycol (EG) to drinking water for 28 days, except normal rats. After the completion of the experimental period, (28th day) urinary parameters like (urine volume, routine urine analysis, levels of calcium, phosphate, oxalate, magnesium, sodium) serum biomarkers like (creatinine, BUN, uric acid, ALP, ALT, AST) kidney homogenate analysis for (levels of calcium, oxalate and phosphate) were analysed. The treated groups shows increased in the urine output significantly compared to the normal. The extract shows significantly decreased in the urinary excretion of the calcium, phosphate, magnesium, sodium and oxalate. The both preventive and curative treatment of extracts showed decrease in the stone forming constituents in the kidneys of urolithiatic rats further the kidneys of all the groups were excised and sectioned for histopathological examination which further claims to posses antiurolithiatic activity.

Keywords: Cucumis sativus, urolithiasis, ethylene glycol, cystone

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Authors: Hesham Hamdy Abdelmohsen, Ahmed Shawky Abdul Azizb, Mona Fawzy Aldaghma

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Helical piles have earned considerable attention as an effective deep foundation alternative due to their rapid installation process and their dual purpose in compression and tension. These piles find common uses as foundations for structures like solar panels, wind turbines, offshore platforms, and some kinds of retaining walls. These structures usually transfer different combinations of loads to their helical-pile foundations in the form of axial and lateral loads. Extensive research has been conducted to investigate and understand the behavior of these piles under the influence of either axial or lateral loads. However, the impacts of loading patterns that may act on the helical piles as combinations of axial compression and lateral loads still need more efforts of research work. This paper presents the results of an experimental (Lab tests) and numerical (PLAXIS-3D) study performed on vertical helical-pile groups under the action of combined loads as axial compression (bearing loads), acting successively with lateral (horizontal) loads. The study aims to clarify the effects of key factors, like helix location and direction of lateral load, on the lateral capacity of helical-pile groups and, consequently, on group efficiency. Besides the variation of helix location and lateral load direction, three patterns of successive bearing combined loads were considered, in which the axial vertical compression load was either zero, V1 or V2, whereas the lateral horizontal loads were varied under each vertical compression load. The study concluded that the lateral capacity of the helical-pile group is significantly affected by helix location within the length of the pile shaft. The optimal lateral performance is achieved with helices at a depth ratio of H/L = 0.4. Furthermore, groups of rectangular plan distribution exhibit greater lateral capacity if subjected to lateral horizontal load in the direction of its long axis. Additionally, the research emphasizes that the presence of vertical compression loading can enhance the lateral capacity of the group. This enhancement depends on the value of the vertical compression load, lateral load direction, and helix location, which highlights the complex interaction effect of these factors on the efficiency of helical-pile groups.

Keywords: helical piles, experimental, numerical, lateral loading, group efficiency

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Authors: Somya Ranjan Patro, Abhigna Bhatt, Arnab Banerjee

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Inertial amplifier has recently gained increasing attention as a new mechanism for vibration control of structures. Currently, theoretical investigations are undertaken by researchers to reveal its fundamentals and to understand its underline principles in altering the structural response of structures against dynamic loadings. This paper investigates experimental and analytical studies on the dynamic characteristics of hybrid beam inertial amplifier (HBIA). The analytical formulation of the HBIA has been derived by implementing the spectral element method and rigid body dynamics. This formulation gives the relation between dynamic force and the response of the structure in the frequency domain. Further, for validation of the proposed HBIA, the experiments have been performed. The experimental setup consists of a 3D printed HBIA of polylactic acid (PLA) material screwed at the base plate of the shaker system. Two numbers of accelerometers are used to study the response, one at the base plate of the shaker second one placed at the top of the inertial amplifier. A force transducer is also placed in between the base plate and the inertial amplifier to calculate the total amount of load transferred from the base plate to the inertial amplifier. The obtained time domain response from the accelerometers have been converted into the frequency domain using the Fast Fourier Transform (FFT) algorithm. The experimental transmittance values are successfully validated with the analytical results, providing us essential confidence in our proposed methodology.

Keywords: inertial amplifier, fast fourier transform, natural frequencies, polylactic acid, transmittance, vibration absorbers

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Authors: Luana N. Cardozo, Debora A. S. Coutinho, Fabiola Lagher, Bruno J. G. Silva, Ivonilce Venture, Mainara Tesser, Graciela Venera

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Ostrich oil is used as food in Brazil, and it has been the subject of scientific research because it contains essential fatty acids (Omega 3, 6, 7, and 9), which provide benefits to human health. Alkylglycerols are lipid ethers consisted of a saturated or unsaturated hydrocarbon chain joined by ether-type bonding to one of the glycerol hydroxyls. It is known that supplementation with alkylglycerols can act significantly on the functioning of immune system cells, both in pathological situations and in homeostasis. Objective: Analyze the presence of alkylglycerols in ostrich oil. Methods: The ostrich oil was bought from an industry that manufactures the product for sale as food, located in Mirante da Serra, northern Brazil. The samples were sent for analysis to the chemistry department of the Federal University of Paraná, where they were analyzed by the gas chromatography method. Results: The analysis of the ostrich oil presented alkylglycerols in area 514505154. Comparison, it is possible to observe that shark liver oil contains the area 26190196, and the difference between both is highly significant. Conclusion: The importance of alkylglycerol supplementation for the immune system is known. The analysis of the results made it possible to verify the presence of alkylglycerols in the ostrich oil, which is five times higher than in the shark liver oil, that would be the largest source food, but was surpassed by the ostrich oil until the present time. The present study emphasizes that ostrich oil can be considered a food source of alkylglycerols and may play a promising role in the immune system because it contains such substance, but further studies are needed to prove its performance in the body.

Keywords: ostrich oil, nutritional composition, alkylglycerols, food

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Authors: R. Praveen, B. R. Chandan Ravi, M. Harikrishna

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Squeak and rattle noises are the most annoying transient vehicle noises produced due to different terrain conditions. Interpretation and prohibition of squeak and rattle noises are the dominant aspects of a vehicle refinement. This paper describes the computer-aided engineering (CAE) approach to evaluating the full vehicle squeak and rattle performance with the measured road surface profile as enforced excitation at the tire patch points. The E-Line methodology has been used to predict the relative displacement at the interface points and the risk areas were identified. Squeak and rattle performance has been evaluated at different speeds and at different road conditions to understand the vehicle characteristics. The competence of the process in predicting the risk and root cause of the problems showcased us a pleasing conformity between the physical testing and CAE simulation results.

Keywords: e-line, enforced excitation, full vehicle, squeak and rattle, road excitation

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Authors: Sangita Pokhrel, Nalinda Somasiri, Rebecca Jeyavadhanam, Swathi Ganesan

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Tourism is a booming industry with huge future potential for global wealth and employment. There are countless data generated over social media sites every day, creating numerous opportunities to bring more insights to decision-makers. The integration of Big Data Technology into the tourism industry will allow companies to conclude where their customers have been and what they like. This information can then be used by businesses, such as those in charge of managing visitor centers or hotels, etc., and the tourist can get a clear idea of places before visiting. The technical perspective of natural language is processed by analysing the sentiment features of online reviews from tourists, and we then supply an enhanced long short-term memory (LSTM) framework for sentiment feature extraction of travel reviews. We have constructed a web review database using a crawler and web scraping technique for experimental validation to evaluate the effectiveness of our methodology. The text form of sentences was first classified through Vader and Roberta model to get the polarity of the reviews. In this paper, we have conducted study methods for feature extraction, such as Count Vectorization and TFIDF Vectorization, and implemented Convolutional Neural Network (CNN) classifier algorithm for the sentiment analysis to decide the tourist’s attitude towards the destinations is positive, negative, or simply neutral based on the review text that they posted online. The results demonstrated that from the CNN algorithm, after pre-processing and cleaning the dataset, we received an accuracy of 96.12% for the positive and negative sentiment analysis.

Keywords: counter vectorization, convolutional neural network, crawler, data technology, long short-term memory, web scraping, sentiment analysis

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Authors: Harsha B. R., Anil Kumar K. S.

Abstract:

Climate and soils are the two most dynamic entities among the factors affecting growth and grapes productivity. Studying of prevailing climate over the years in a region provides sufficient information related to management practices to be carried out in vineyards. Evaluating the suitability of vineyard soils under different climatic conditions serves as the yardstick to analyse the performance of grapevines. This study was formulated to study the climate and evaluate the site-suitability of soils in vineyards of southern Karnataka, which has registered its superiority in the quality production of wine. Ten soil profiles were excavated for suitability evaluation of soils, and six taluks were studied for climatic analysis. In almost all the regions studied, recharge starts at the end of the May or June months, peaking in either September or October months. Soil Starts drying from mid of December months in the taluks studied. Bangalore North (Rajanukunte) soils were highly suited for grapes cultivation with no or slight limitations. Bangalore North (GKVK Farm) was moderately suited with slight to moderate limitations of slope and available nitrogen content. Moderate suitability was observed in the rest of the profiles studied in Eastern dry zone soils with the slight to moderate limitations of either organic carbon or available nitrogen or both in the Eastern dry zone. Magadi (Southern dry zone) soils were moderately suitable with slight to moderate limitations of graveliness, available nitrogen, organic carbon, and exchangeable sodium percentage. Sustainable performance of vineyards in terms of yield can be achieved in these taluks by managing the constraints existing in soils.

Keywords: climatic analysis, dry zone, water recharge, growing period, suitability, sustainability

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Authors: Anastasia K. Eleftheriadou, Athanasios Sfetsos, Nikolaos Gounaris

Abstract:

The present work examines the suitability of a seasonal forecasting model downscaled with a very high spatial resolution in order to assess the energy performance and requirements of buildings. The application of the developed model is applied on Greece for a period and with a forecast horizon of 5 months in the future. Greece, as a country in the middle of a financial crisis and facing serious societal challenges, is also very sensitive to climate changes. The commonly used method for the correlation of climate change with the buildings energy consumption is the concept of Degree Days (DD). This method can be applied to heating and cooling systems for a better management of environmental, economic and energy crisis, and can be used as medium (3-6 months) planning tools in order to predict the building needs and country’s requirements for residential energy use.

Keywords: downscaled seasonal models, degree days, energy performance

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Authors: Reema Jain

Abstract:

Nanofluids are emergent fluids that exhibit thermal properties superior than that of the conventional fluid. Nanofluids are suspensions of nanoparticles in fluids that show significant enhancement of their properties at modest nanoparticle concentrations. Solar collectors are commonly used in areas such as industries, heating, and cooling for domestic purpose, thermal power plants, solar cooker, automobiles, etc. Performance and efficiency of solar collectors depend upon various factors like collector & receiver material, solar radiation intensity, nature of working fluid, etc. The properties of working fluid which flow through the collectors greatly affects its performance. In this research work, a theoretical effort has been made to enhance the efficiency and improve the performance of solar collector by using Nano fluids instead of conventional fluid like water as working fluid.

Keywords: nanofluids, nanoparticles, heat transfer, solar collector

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Authors: Marcelo Franzkowiak Stahlschmidt

Abstract:

This paper discusses the experiments carried out based on the wire drawing process analysis and later annealing on lead furnace on a galvanizing line. Using Design of Experiments methodology, the aim of this work is to understand the occurrence of lead entrainment originating from the annealed wires in order to decrease this problem. Wire samples were collected from wire drawing machines and galvanizing line and submitted to surface roughness analysis and its implications on lead drag out based on wire speed, wire diameter, lead bath temperature, thermal capacity of the lead kettle, wire surface condition, wire roughness and wire superficial cleanliness. Proposals to decrease lead drag out were made in order to increase wire drawing machines and galvanizing line performance.

Keywords: wire drawing process, galvanizing, heat treatment, lead

Procedia PDF Downloads 634

Authors: A. Benatiallah, A. Hadjadj, D. Benatiallah, F. Abaidi, A. Harrouz

Abstract:

Photovoltaic system is established as a reliable and economical source of electricity in rural and Sahara areas, especially in developing countries where the population is dispersed, has low consumption of energy and the grid power is not extended to these areas due to viability and financial problems. The production of energy by the photovoltaic system is very fluctuates and depend of meteorological conditions. Wind is a very important and often neglected parameter in the behavior of the solar module. The electric performances of a solar module to the silicon are very appreciable to the blows; in the present work we have studies the behavior of multi-crystal solar module according to the density of dust, and the principals electric feature of the solar module. An evaluation permits to affirm that a solar module under the effect of sand will collect a lower flux to the normal conditions.

Keywords: photovoltaic, multi-crystal module, experimental, effect of dust, performances

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Authors: Luís F. da Silva, Ariadne C. Catto, Osmando F. Lopes, Khalifa Aguir, Valmor R. Mastelaro, Caue Ribeiro, Elson Longo

Abstract:

Gas detection is important for controlling industrial, and vehicle emissions, agricultural residues, and environmental control. In last decades, several semiconducting oxides have been used to detect dangerous or toxic gases. The excellent gas-sensing performance of these devices have been observed at high temperatures (~250 °C), which forbids the use for the detection of flammable and explosive gases. In this way, ultraviolet light activated gas sensors have been a simple and promising alternative to achieve room temperature sensitivity. Among the semiconductor oxides which exhibit a good performance as gas sensor, the zinc oxide (ZnO) and tin oxide (SnO2) have been highlighted. Nevertheless, their poor selectivity is the main disadvantage for application as gas sensor devices. Recently, heterostructures combining these two semiconductors (ZnO-SnO2) have been studied as an alternative way to enhance the gas sensor performance (sensitivity, selectivity, and stability). In this work, we investigated the influence of mass ratio Zn:Sn on the properties of ZnO-SnO2 nanocomposites prepared by hydrothermal treatment for 4 hours at 200 °C. The crystalline phase, surface, and morphological features were characterized by X-ray diffraction (XRD), high-resolution transmission electron (HR-TEM), and X-ray photoelectron spectroscopy (XPS) measurements. The gas sensor measurements were carried out at room-temperature under ultraviolet (UV) light irradiation using different ozone levels (0.06 to 0.61 ppm). The XRD measurements indicate the presence of ZnO and SnO2 crystalline phases, without the evidence of solid solution formation. HR-TEM analysis revealed that a good contact between the SnO2 nanoparticles and the ZnO nanorods, which are very important since interface characteristics between nanostructures are considered as challenge to development new and efficient heterostructures. Electrical measurements proved that the best ozone gas-sensing performance is obtained for ZnO:SnO2 (50:50) nanocomposite under UV light irradiation. Its sensitivity was around 6 times higher when compared to SnO2 pure, a traditional ozone gas sensor. These results demonstrate the potential of ZnO-SnO2 heterojunctions for the detection of ozone gas at room-temperature when irradiated with UV light irradiation.

Keywords: hydrothermal, zno-sno2, ozone sensor, uv-activation, room-temperature

Procedia PDF Downloads 279

Authors: Maria Ahmadnezhad, Seyedgharani Ghoreishi ‎

Abstract:

Electrohydraulic servo system have been used in industry in a wide ‎number of applications. Its ‎dynamics are highly nonlinear and also ‎have large extent of model uncertainties and external ‎disturbances. ‎In this thesis, a robust back-stepping control (RBSC) scheme is ‎proposed to overcome ‎the problem of disturbances and system ‎uncertainties effectively and to improve the set-point ‎performance ‎of EHS systems. In order to implement the proposed control ‎scheme, the system ‎uncertainties in EHS systems are considered as ‎total leakage coefficient and effective oil volume. In ‎addition, in ‎order to obtain the virtual controls for stabilizing system, the ‎update rule for the ‎system uncertainty term is induced by the ‎Lyapunov control function (LCF). To verify the ‎performance and ‎robustness of the proposed control system, computer simulation of ‎the ‎proposed control system using Matlab/Simulink Software is ‎executed. From the computer ‎simulation, it was found that the ‎RBSC system produces the desired set-point performance and ‎has ‎robustness to the disturbances and system uncertainties of ‎EHS systems.‎

Keywords: electro hydraulic servo system, back-stepping control, robust back-‎stepping control, Lyapunov redesign‎

Procedia PDF Downloads 992

Authors: Abidoye James Alabi

Abstract:

This study investigated the effect of video-based instructional strategy on junior secondary school academic achievement in social studies. The influence of gender on the academic achievement of student taught with video-based instructional strategy was also examined. The study adopted a pre-test and pro-test control group quasi-experimental design. Simple random sampling technique was used to select 40 students from two schools in Akure town in Ondo State. The researcher developed instructional video package on social studies concept which was used as treatment instrument for the experimental group while the control group was exposed to conventional teaching method. The instruments used in this study are social studies achievement test and instructional video package (IVP). T-test statistic was used to analyse the hypotheses. The findings revealed that experimental group performed better than the control group. It was also shown that gender has no significant effect on students’ academic achievement when exposed to an instructional video package. It was recommended that appropriate training and workshop should be organized by the government for the social studies teachers for effective use of instructional video package in order to enhance teachers productivities and learning among students in secondary schools.

Keywords: instructional video package, conventional teaching method, social studies, junior secondary school

Procedia PDF Downloads 417