Search results for: regression coefficient

Authors: Kelly F. Delgado-De Agrela, Sonia E. Ruiz, Marco A. Santos-Santiago

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An approach is proposed for the design of regular buildings equipped with non-linear viscous dissipating devices. The approach is based on a direct-displacement seismic design method which satisfies seismic performance objectives. The global system involved is formed by structural regular moment frames capable of supporting gravity and lateral loads with elastic response behavior plus a set of non-linear viscous dissipating devices which reduce the structural seismic response. The dampers are characterized by two design parameters: (1) a positive real exponent α which represents the non-linearity of the damper, and (2) the damping coefficient C of the device, whose constitutive force-velocity law is given by F=Cvᵃ, where v is the velocity between the ends of the damper. The procedure is carried out using a substitute structure. Two limits states are verified: serviceability and near collapse. The reduction of the spectral ordinates by the additional damping assumed in the design process and introduced to the structure by the viscous non-linear dampers is performed according to a damping reduction factor. For the design of the non-linear damper system, the real velocity is considered instead of the pseudo-velocity. The proposed design methodology is applied to an 8-story steel moment frame building equipped with non-linear viscous dampers, located in intermediate soil zone of Mexico City, with a dominant period Tₛ = 1s. In order to validate the approach, nonlinear static analyses and nonlinear time history analyses are performed.

Keywords: based design, direct-displacement based design, non-linear viscous dampers, performance design

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Authors: Helida T. G. Soares, Antonio J. P. da Silva

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As the society develops, the accumulation of solid waste in landfills, in the environment, and the depletion of the raw material increases. In this way, there is relevance in researching the interaction between the environmental management and civil construction; therefore, this project has for scope the analysis and the effects of the rubber microparticles use as a small aggregate added to the sand, producing an ecological mortar for the pavement constitution, from the mixture of a paste, composed of Portland cement and water, and its application in sports courts. It was used the detailed reutilization of micro rubber in its most primordial, micro form, highlighting the powder pattern as the additional balancing of the mortar, analyzing the evolution of the mechanical properties. Percentages of 5, 10 and 15% rubber were used based on the total mass of the trace, where there is no removal of aggregates or cement, only increment of the rubber. The results obtained through the mechanical test of simple compression showed that the rubber, added to the mortar, presents low mechanical resistance compared to the reference trait, the study of this subject is vast of possibilities to be explored. In this sense, we seek sustainability and innovation from the use of an ecological material, thus adding value and reducing the impact of this material on the environment. The manufacturing process takes place from the direct mixing of cement paste and rubber, whether manually, mechanically or industrially. It results in the production of a low-cost mortar, through the use of recycled rubber, with high efficiency in general properties, such as compressive strength and friction coefficient, allowing its use for the construction of floors for sports courts with high durability. Thus, it is possible to reuse this micro rubber residue in other applications in simple concrete artifacts.

Keywords: civil construction, ecological mortar, high efficiency, rubber

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Authors: Jing Chen, Jun-E Liu, Peng Yue

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Objective: The objective of this study was to develop a psychological adjustment and adaptation status scale for breast cancer survivors, and to examine the reliability and validity of the scale. Method: 37 breast cancer survivors were recruited in qualitative research; a five-subject theoretical framework and an item pool of 150 items of the scale were derived from the interview data. In order to evaluate and select items and reach a preliminary validity and reliability for the original scale, the suggestions of study group members, experts and breast cancer survivors were taken, and statistical methods were used step by step in a sample of 457 breast cancer survivors. Results: An original 24-item scale was developed. The five dimensions “domestic affections”, “interpersonal relationship”, “attitude of life”, “health awareness”, “self-control/self-efficacy” explained 58.053% of the total variance. The content validity was assessed by experts, the CVI was 0.92. The construct validity was examined in a sample of 264 breast cancer survivors. The fitting indexes of confirmatory factor analysis (CFA) showed good fitting of the five dimensions model. The criterion-related validity of the total scale with PTGI was satisfactory (r=0.564, p<0.001). The internal consistency reliability and test-retest reliability were tested. Cronbach’s alpha value (0.911) showed a good internal consistency reliability, and the intraclass correlation coefficient (ICC=0.925, p<0.001) showed a satisfactory test-retest reliability. Conclusions: The scale was brief and easy to understand, was suitable for breast cancer patients whose physical strength and energy were limited.

Keywords: breast cancer survivors, rehabilitation, psychological adaption and adjustment, development of scale

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Authors: Izani Uzair Zubair, Mohd Ismail Ibrahim, Mohd Nazri Shafei, Hassan Merican Omar Naina Merican, Mohamad Sabri Othman, Mohd Izmi Ahmad Ibrahim, Rasilah Ramli, Rajpal Singh Karam Singh

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Nurses experience a higher prevalence of low back pain (LBP) and musculoskeletal complaints as compared to other hospital workers. Due to no proper policy related to LBP, the job has exposed them to the problem. Thus, the current study aims to look at the intensity of the problem and factors associated with development of LBP. Method and Tools: A cross sectional study was carried out among 1292 nurses from six public hospitals in Penang. They were randomly selected and those who were pregnant and have been diagnosed to have LBP were excluded. A Malay validated BACK Questionnaire was used. The associated factors were determined by using multiple logistic regression from SPSS version 20.0. Result: Most of the respondents were at mean age 30 years old and had mean working experience 86 months. The prevalence of LBP was identified as 76% (95% CI 74, 82). Factors that were associated with LBP among nurses include lifting a heavy object (OR2.626 (95% CI 1.978, 3.486) p =0.001 and the estimation weight of the lifted object (OR1.443 (95% CI 1.056, 1.970) p =0.021. Conclusion: Nurses who practice lifting heavy object and weight of the object lifted give a significant contribution to the development of LBP. The prevalence of the problem is significantly high. Thus, a proper no weight lifting policy should be considered.

Keywords: low back pain, nurses, Penang public hospital, Penang

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Authors: K. N. Kiran, S. Anish

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It is well known that secondary flow loses account about one third of the total loss in any axial turbine. Modern gas turbine height is smaller and have longer chord length, which might lead to increase in secondary flow. In order to improve the efficiency of the turbine, it is important to understand the behavior of secondary flow and device mechanisms to curtail these losses. The objective of the present work is to understand the effect of a stream wise end-wall fence on the aerodynamics of a linear turbine cascade. The study is carried out computationally by using commercial software ANSYS CFX. The effect of end-wall on the flow field are calculated based on RANS simulation by using SST transition turbulence model. Durham cascade which is similar to high-pressure axial flow turbine for simulation is used. The aim of fencing in blade passage is to get the maximum benefit from flow deviation and destroying the passage vortex in terms of loss reduction. It is observed that, for the present analysis, fence in the blade passage helps reducing the strength of horseshoe vortex and is capable of restraining the flow along the blade passage. Fence in the blade passage helps in reducing the under turning by 7⁰ in comparison with base case. Fence on end-wall is effective in preventing the movement of pressure side leg of horseshoe vortex and helps in breaking the passage vortex. Computations are carried for different fence height whose curvature is different from the blade camber. The optimum fence geometry and location reduces the loss coefficient by 15.6% in comparison with base case.

Keywords: boundary layer fence, horseshoe vortex, linear cascade, passage vortex, secondary flow

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Authors: Fatima Alsalem

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Objectives: This study aims to explore the perceived credibility of social media influencers and their effect on purchase intention. In addition, the study aims to investigate the relationship between satisfaction with content promoted via social media and its relation to purchasing intention. Methodology: This study uses an exploratory and quantitative methodology. It was implemented through a cross-sectional survey that asked respondents to identify the time they spend using social media, satisfaction with influencers’ content, types of influencers they prefer, motivations to use social media, purchase intention of products promoted by influencers, as well as three credibility dimensions. Sample: the sample included 1184 Kuwaiti nationals, of which 50.4% (N=593) were males and 49.6% (N=584) were females. Results: The analysis of the data indicated that comedy and entertainment influencers are the most preferred type of influencers, while fashion influencers “fashionistas” are the least preferred. Based on the results of the regression analysis, the perceived credibility of influencers and satisfaction with their content is positively related to higher purchase intention. While all dimensions of credibility are positively related to higher purchase intention, attractiveness is the strongest predictor. Conclusion: The significant value of this study is the examination of the perceived credibility of influencers and the type of influencer social media users prefer to follow. The current research proves that the attractiveness of influencers is the highest dimension of their perceived credibility, which was prevalent in the findings.

Keywords: influencers, social media, mass media, credibility

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Authors: Julita D. L. Nainggolan, Cindy Novita Ongkowijoyo, Veli Sungono, Dyana Safitri Velies, Ernestine Vivie Sadeli, Jimmy

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Introduction: Normal menstrual cycle in women ranges from 21-34 days. Menopause is defined as the time when there have been no menstrual periods for 12 consecutive months and no other biological or physiological cause can be identified. Caffeine might increase the estradiol in the early of follicular phase and possibly increase the progesterone and shorten menstruation cycle. Women with shorter menstrual cycle, (below 26 days) would likely get to menopause 1.4 years earlier than those who are normal, and 2.2 years earlier than women with longer menstrual cycle. Purpose: To study the association of caffeine consumption in coffee, tea, and soft drinks with the age of menopause. Design Study: A cross-sectional study using purposive sampling of 132 menopause women from elderly nursing, hospitals and students’ relatives from August 2015-December 2015. The mean difference of age of menopause among the caffeine intake was analyzed by using the unpaired t-test and logistic regression. Results: Mean current age of the respondents are 61.4 years ± SD 9.8; and age of menopause was 47.7 years ± SD 4.2. There are 49.6% who drink coffee, 62.6% of tea and 7.6% of soft drinks. The analysis of t-test showed no significant mean difference in age of menopause among women who drink coffee, tea and soft drinks, mean age of 47.63 ± 4.3 in coffee with p=0.392, mean age of 47.8 ± 4 in tea with p=0.373; and mean age of 46 ± 5.5 with p=0.083 after adjustment of smoking history. Conclusion: Consumption of caffeine among women who drink coffee, tea, and soft drinks did not show significant mean difference in age of menopause.

Keywords: caffeine, menopause, coffee, tea, soda, soft drinks

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Authors: Saci Abdelhakim Ferkous, Khedoudja Soudani, Smail Haddadi

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This paper presents the results of a laboratory experimental study that explores the skid resistance of asphalt concrete mixtures made of local low-performance aggregates by partially replacing sand with olive mill waste (OMW). OMW was mixed with aggregates using a dry process by replacing sand with contents of 5%, 7%, 10% and 15%. The mechanical performances of the mixtures were evaluated using the Marshall and Duriez tests. A modified accelerated polishing machine was used as polishing equipment, and a British pendulum tester (BPT) was used to test the skid resistance of the samples. Finally, texture parameter analysis was performed using scanning electron microscopy (SEM) and Mountains Map software to assess the effect of OMW on the friction coefficient evolution. Using a distinct road wheel for a modified version of an accelerated polishing machine, which is normally used to determine the polished stone value of aggregates, the results showed that the addition of OMW up to 10% conferred a better skid resistance in comparison to normal asphalt concrete. The presence of olive mill waste in the mixture until 15% guarantees a gain of 22%-29% in skid resistance after polishing compared with the reference mix. Indeed, from texture parameter analysis, it was observed that there was differential wear of the lightweight aggregates (OMW) compared to the other aggregates during the polishing process, which created a new surface microtexture that had new peaks and led to a good level of friction compared to the mixtures without OMW. In general, it was found that OMW is a promising modifier for asphalt mixtures with both engineering and economic merits.

Keywords: skid resistance, olive mill waste, polishing resistance, accelerated polishing machine, local materials, sustainable development.

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Authors: Kate Ebere Maduforo

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Examining the constraints faced by female entrepreneurs is an important subject which most literature on female entrepreneurship is centered on. However, the majority of the existing literature has focused on studying female entrepreneurs in developed societies. Recently, a sense of urgency that has emerged in trying to understand the challenges and motivations of female entrepreneurs in developing countries. The arousal of such interest has been attributed to women entrepreneurs in developing countries being identified as catalysts of economic development at a national level and champions of poverty eradication at the domestic level. This paper, therefore, examines the peculiar constraints faced by women-owned businesses in the mist of political chaos and instability. In this case, the issues experienced by female entrepreneurs in Egypt during the aftermath of the Arab Spring is the focus. Using the logit and probit regression models, data from the World Bank Middle East North Africa Enterprise Survey (MENA ES) are analyzed. The results identified that female entrepreneurs still lack business funding through financial institutions, but get significant funding assistance from family, friends, and money lenders. In addition, women-owned businesses promote and hire mostly women. Female entrepreneurs showed a preference for an impartial judicial system as a contributor to business growth.

Keywords: female entrepreneurship, development, Middle East, developing countries

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Authors: Nnadi Ezekiel Ejiofor

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The construction industry plays a decisive role in the healthy development of any nation. Not only large but even small construction projects contribute to a country’s economic growth. There is a need for good management to ensure successful delivery and sustainability because of the plethora of risks that have resulted in low-profit margins for contractors, cost and schedule overruns, poor quality delivery, and abandoned projects. This research reviewed Capitalization on Sustainable Risk Management. Questionnaires and oral interviews conducted were utilized as means of data collection. One hundred and ninety-eight (198) large construction firms in Nigeria form the population of this study. 15 (fifteen) companies that emanated from merger and acquisition were used for the study. The instruments used for data collection were a researcher-developed structured questionnaire based on a five-point rating scale, interviews, focus group discussion, and secondary sources (bill of quantities and stock and exchange commission). The instrument was validated by two experts in the field. The reliability of the instrument was established by applying the split-half method. Kendall’s coefficient of concordance was used to test the data, and a degree of agreement was obtained. Data were subjected to descriptive statistics and analyzed using analysis of variance, t-test, and SPSS. The identified impacts of capitalization were an increase in turnover (24.5%), improvement in the image (24.5%), risk reduction (20%), business expansion (17.3%), and geographical spread (13.6%). The study strongly advocates the inclusion of risk management evaluation as part of the construction procurement process.

Keywords: capitalization, project delivery, risks, risk management, sustainability

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Authors: O. B. Enemuo, A. A. Onubuogu

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This work evaluated the influence of interior of decoration on customer perception of hotels in Uyo Akwa Ibom State. Specifically the study identified the various interior decoration used in hotels in the study area, determined the interior decoration used in hotels that appeal to the customer more, ascertained the influence of interior decoration on the level of patronage in the hotel in the study area and suggested ways of improving the interior decoration of hotels in the study area for sustainability. The study was guided by four research questions and two hypotheses. It adopted survey research design; structured questionnaire was used for data collection. The samples for the study were four hundred (400) staff and managers from the various hotels in the study area. Data generated were analyzed using mean and standard deviation analyses of variance (ANOVA) derived from regression analyses to test the hypotheses. The result of the finding showed that satisfactory interior decoration has a positive influence on the sustainability of the hospitality establishments in Uyo. The hypothesis showed that there was a significant relationship between the gender perception on the influence of interior decoration in the hotel and significant relationship between the gender perceptions on the influence of interior decoration in the hotels. From the finding, it was recommended that the hotels should design interior decorative service delivery system which has an impact on customer satisfaction in the hospitality industry and practiced healthy decorative environment and increased customer satisfaction.

Keywords: influence, interior decoration, customer’s perception, hotels

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Authors: Kudzanayi Chiteka, Wellington Makondo

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The whole world is on the drive to go green owing to the negative effects of burning fossil fuels. Therefore, there is immediate need to identify and utilise alternative renewable energy sources. Among these energy sources solar energy is one of the most dominant in Zimbabwe. Solar power plants used to generate electricity are entirely dependent on solar radiation. For planning purposes, solar radiation values should be known in advance to make necessary arrangements to minimise the negative effects of the absence of solar radiation due to cloud cover and other naturally occurring phenomena. This research focused on the prediction of Global Horizontal Irradiation values for the sixth day given values for the past five days. Artificial intelligence techniques were used in this research. Three models were developed based on Support Vector Machines, Radial Basis Function, and Feed Forward Back-Propagation Artificial neural network. Results revealed that Support Vector Machines gives the best results compared to the other two with a mean absolute percentage error (MAPE) of 2%, Mean Absolute Error (MAE) of 0.05kWh/m²/day root mean square (RMS) error of 0.15kWh/m²/day and a coefficient of determination of 0.990. The other predictive models had prediction accuracies of MAPEs of 4.5% and 6% respectively for Radial Basis Function and Feed Forward Back-propagation Artificial neural network. These two models also had coefficients of determination of 0.975 and 0.970 respectively. It was found that prediction of GHI values for the future days is possible using artificial intelligence-based predictive models.

Keywords: solar energy, global horizontal irradiation, artificial intelligence, predictive models

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Authors: Julie Ann L. Gadin, Andrearose C. Igano, Carl Joseph S. Ignacio, Christopher C. Bacungan

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Corn production has become an important and pervasive industry in the Visayas for many years. Its role as a substitute commodity to rice heightens demand for health-particular consumers. Unfortunately, the corn industry is confronted with several challenges, such as weak institutions. Considering these issues, the paper examined the factors that influence corn production in the three administrative regions in the Visayas, namely, Western Visayas, Central Visayas, and Eastern Visayas. The data used was retrieved from a variety of publicly available data sources such as the Philippine Statistics Authority, the Department of Agriculture, the Philippine Crop Insurance Corporation, and the International Disaster Database. Utilizing a dataset from 2002 to 2019, the indicators were tested using three multiple linear regression (MLR) models. Results showed that the land area harvested (p=0.02), and the value of corn production (p=0.00) are statistically significant variables that influence corn production in the Visayas. Given these findings, it is suggested that the policy of forest conversion and sustainable land management should be effective in enabling farmworkers to obtain land to grow corn crops, especially in rural regions. Furthermore, the Biofuels Act of 2006, the Livestock Industry Restructuring and Rationalization Act, and supported policy, Senate Bill No. 225, or an Act Establishing the Philippine Corn Research Institute and Appropriating Funds, should be enforced inclusively in order to improve the demand for the corn-allied industries which may lead to an increase in the value and volume of corn production in the Visayas.

Keywords: corn, industry, production, MLR, Visayas

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Authors: Lucretia Ramnath

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Fishmeal is extensively used for fish farming but is an expensive fish feed ingredient. A cheaper alternate to fishmeal is single cell protein (SCP) which can be cultivated on fermentable sugars recovered from organic waste streams such as pulp and paper mill sludge (PPMS). PPMS has a high cellulose content, thus is suitable for glucose recovery through enzymatic hydrolysis but is hampered by lignin and ash. To render PPMS amenable for enzymatic hydrolysis, the PPMS waspre-treated to produce a glucose-rich hydrolysate which served as a feed stock for the production of fungal SCP. The PPMS used in this study had the following composition: 72.77% carbohydrates, 8.6% lignin, and 18.63% ash. The pre-treatments had no significant effect on lignin composition but had a substantial effect on carbohydrate and ash content. Enzymatic hydrolysis of screened PPMS was previously optimized through response surface methodology (RSM) and 2-factorial design. The optimized protocol resulted in a hydrolysate containing 46.1 g/L of glucose, of which 86% was recovered after downstream processing by passing through a 100-mesh sieve (38 µm pore size). Vogel’s medium supplemented with 10 g/L hydrolysate successfully supported the growth of Fusarium venenatum, conducted using standard growth conditions; pH 6, 200 rpm, 2.88 g/L ammonium phosphate, 25°C. A maximum F. venenatum biomass of 45 g/L was produced with a yield coefficient of 4.67. Pulp and paper mill sludge hydrolysate contained approximately five times more glucose than what was needed for SCP production and served as a suitable carbon source. We have shown that PPMS can be successfully beneficiated for SCP production.

Keywords: pulp and paper waste, fungi, single cell protein, hydrolysate

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Authors: Muhammad Afzal Malik

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Traditional Learning & Distance based learning are the two systems prevailing in Pakistan. These systems affect the level of education standard. The purpose of this study was to compare the traditional classroom learning and distance learning in Pakistan: (a) To explore the effectiveness of the traditional to Distance learning in Pakistan; (b) To identify the factors that affect traditional and distance learning. This review found that, on average, students in traditional classroom conditions performed better than those receiving education in and distance learning. The difference between student outcomes for traditional Classroom and distance learning classes —measured as the difference between treatment and control means, divided by the pooled standard deviation— was larger in those studies contrasting conditions that blended elements of online and face-to-face instruction with conditions taught entirely face-to-face. This research was conducted to highlight the impact of distance learning education system on education standard. The education standards were institutional support, course development, learning process, student support, faculty support, evaluation and assessment. A well developed questionnaire was administered and distributed among 26 faculty members of GCET, H-9 and Virtual University of Pakistan from each. Data was analyzed through correlation and regression analysis. Results confirmed that there is a significant relationship and impact of DLE system on education standards. This will also provide baseline for future research. It will add value to the existing body of knowledge.

Keywords: distance learning education, higher education, education standards, student performance

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Authors: Namwinwelbere Dabire, Eugene C. Ezin, Adandedji M. Firmin

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The prediction of hydrological flows (rainfall-depth or rainfall-discharge) is becoming increasingly important in the management of hydrological risks such as floods. In this study, the Long Short-Term Memory (LSTM) network, a state-of-the-art algorithm dedicated to time series, is applied to predict the daily water level of Nokoue Lake in Benin. This paper aims to provide an effective and reliable method enable of reproducing the future daily water level of Nokoue Lake, which is influenced by a combination of two phenomena: rainfall and river flow (runoff from the Ouémé River, the Sô River, the Porto-Novo lagoon, and the Atlantic Ocean). Performance analysis based on the forecasting horizon indicates that LSTM can predict the water level of Nokoué Lake up to a forecast horizon of t+10 days. Performance metrics such as Root Mean Square Error (RMSE), coefficient of correlation (R²), Nash-Sutcliffe Efficiency (NSE), and Mean Absolute Error (MAE) agree on a forecast horizon of up to t+3 days. The values of these metrics remain stable for forecast horizons of t+1 days, t+2 days, and t+3 days. The values of R² and NSE are greater than 0.97 during the training and testing phases in the Nokoué Lake basin. Based on the evaluation indices used to assess the model's performance for the appropriate forecast horizon of water level in the Nokoué Lake basin, the forecast horizon of t+3 days is chosen for predicting future daily water levels.

Keywords: forecasting, long short-term memory cell, recurrent artificial neural network, Nokoué lake

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Authors: Haibin Zhou, Pingping Yao, Kunyang Fan

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Copper-based sintered friction materials are widely used in the brake system of different applications such as engineering machinery or high-speed train, due to the excellent mechanical, thermal and tribological performance. Considering the diversity of the working conditions of brake system, it is necessary to identify well and understand the tribological performance and wear mechanisms of friction materials for different conditions. Fe has been a preferred reinforcement for copper-based friction materials, due to its ability to improve the wear resistance and mechanical properties of material. Wear map is well accepted as a useful research method for evaluation of wear performances and wear mechanisms over a wider range of working conditions. Therefore, it is significantly important to construct a wear map which can give out the effects of work condition and Fe reinforcement on tribological performance of Cu-based friction materials. In this study, the copper-based sintered friction materials with the different addition of Fe reinforcement (0-20 vol. %) were studied. The tribological tests were performed against stainless steel in a ring-on-ring braking tester with varying braking energy density (0-5000 J/cm2). The linear wear and friction coefficient were measured. The worn surface, cross section and debris were analyzed to determine the dominant wear mechanisms for different testing conditions. On the basis of experimental results, the wear map and wear mechanism map were established, in terms of braking energy density and the addition of Fe. It was found that with low contents of Fe and low braking energy density, adhesive wear was the dominant wear mechanism of friction materials. Oxidative wear and abrasive wear mainly occurred under moderate braking energy density. In the condition of high braking energy density, with both high and low addition of Fe, delamination appeared as the main wear mechanism.

Keywords: Cu-based friction materials, Fe reinforcement, wear map, wear mechanism

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Authors: Mehdi Modabberifar, Milad Roodi, Ehsan Souri

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In recent years, honeycomb fiber reinforced plastic (FRP) sandwich panels have been increasingly used in various industries. Low weight, low price, and high mechanical strength are the benefits of these structures. However, their mechanical properties and behavior have not been fully explored. The objective of this study is to conduct a combined numerical-statistical investigation of honeycomb FRP sandwich beams subject to torsion load. In this paper, the effect of geometric parameters of the sandwich panel on the maximum shear strain in both face and core and angle of torsion in a honeycomb FRP sandwich structures in torsion is investigated. The effect of Parameters including core thickness, face skin thickness, cell shape, cell size, and cell thickness on mechanical behavior of the structure were numerically investigated. Main effects of factors were considered in this paper and regression equations were derived. Taguchi method was employed as experimental design and an optimum parameter combination for the maximum structure stiffness has been obtained. The results showed that cell size and face skin thickness have the most significant impacts on torsion angle, maximum shear strain in face and core.

Keywords: finite element, honeycomb FRP sandwich panel, torsion, civil engineering

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Authors: Seongcheol Kwon, Jeongmin Kim, Kwang Ryel Ryu

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We assume an IoT-based smart-home environment where the on-off status of each of the electrical appliances including the room lights can be recognized in a real time by monitoring and analyzing the smart meter data. At any moment in such an environment, we can recognize what the household or the user is doing by referring to the status data of the appliances. In this paper, we focus on a smart-home service that is to activate a robot vacuum cleaner at right time by recognizing the user situation, which requires a situation-aware model that can distinguish the situations that allow vacuum cleaning (Yes) from those that do not (No). We learn as our candidate models a few classifiers such as naïve Bayes, decision tree, and logistic regression that can map the appliance-status data into Yes and No situations. Our training and test data are obtained from simulations of user behaviors, in which a sequence of user situations such as cooking, eating, dish washing, and so on is generated with the status of the relevant appliances changed in accordance with the situation changes. During the simulation, both the situation transition and the resulting appliance status are determined stochastically. To compare the performances of the aforementioned classifiers we obtain their learning curves for different types of users through simulations. The result of our empirical study reveals that naïve Bayes achieves a slightly better classification accuracy than the other compared classifiers.

Keywords: situation-awareness, smart home, IoT, machine learning, classifier

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Authors: Min Chen, Rubi Gupta

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Understanding and predicting stock market movements is a challenging problem. It is believed stock markets are partially driven by public sentiments, which leads to numerous research efforts to predict stock market trend using public sentiments expressed on social media such as Twitter but with limited success. Recently a microblogging website StockTwits is becoming increasingly popular for users to share their discussions and sentiments about stocks and financial market. In this project, we analyze the text content of StockTwits tweets and extract financial sentiment using text featurization and machine learning algorithms. StockTwits tweets are first pre-processed using techniques including stopword removal, special character removal, and case normalization to remove noise. Features are extracted from these preprocessed tweets through text featurization process using bags of words, N-gram models, TF-IDF (term frequency-inverse document frequency), and latent semantic analysis. Machine learning models are then trained to classify the tweets' sentiment as positive (bullish) or negative (bearish). The correlation between the aggregated daily sentiment and daily stock price movement is then investigated using Pearson’s correlation coefficient. Finally, the sentiment information is applied together with time series stock data to predict stock price movement. The experiments on five companies (Apple, Amazon, General Electric, Microsoft, and Target) in a duration of nine months demonstrate the effectiveness of our study in improving the prediction accuracy.

Keywords: machine learning, sentiment analysis, stock price prediction, tweet processing

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Authors: Yosra Makni Fourati, Sana Masmoudi Mardassi

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This paper investigates the effect of Book-tax conformity on audit quality regarding the proxies of audit fees, auditors’ industry specialization and audit report lag. Using a sample of Canadian firms listed on the Toronto Stock Exchange spanning the years 2006- 2016, we applied an Ordinary Least Squares (OLS) regression to test hypotheses of this research. The authors find that higher Book-tax conformity leads to lower audit fees. They also provide evidence that there is a negative association between Book-tax conformity and auditors’ industry specialization, whereas there is a positive association between Book-tax conformity and audit report lag. Overall, the findings are prominent to better understanding the effect of Book-tax conformity on audit quality and are relevant for academic researchers, practitioners, and regulators. As the paper investigates the relationship of Book-tax conformity and audit quality using a sample of Canadian firms, it brings original insights regarding the importance of audit fees and Book-tax conformity. In addition, it considers the role of auditor’s industry specialization in the relation between audit quality and Book-tax conformity by considering a sample listed on the Toronto Stock Exchange. This paper contributes to the existing literature by highlighting the Canadian setting, to our best knowledge. In addition, our results are prominent to the auditing literature as they introduce a different determinant of auditors’ industry specialization and audit report lag.

Keywords: audit fees, auditors' industry specialization, audit report lag, book-tax conformity

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Authors: Fatiha Mohammed Arab, Benoit Augier, Francois Deniset, Pascal Casari, Jacques Andre Astolfi

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For the top high performance foiling yachts, cavitation is often a limiting factor for take-off and top speed. This work investigates solutions to delay the onset of cavitation thanks to structural morphing. The structural morphing is based on compliant leading and trailing edge, with effect similar to flaps. It is shown here that the commonly accepted effect of flaps regarding the control of lift and drag forces can also be used to postpone the inception of cavitation. A numerical and experimental study is conducted in order to assess the effect of the geometric parameters of hydrofoil on their hydrodynamic performances and in cavitation inception. The effect of a 70% trailing edge and a 30% leading edge of NACA 0012 is investigated using Xfoil software at a constant Reynolds number 106. The simulations carried out for a range flaps deflections and various angles of attack. So, the result showed that the lift coefficient increase with the increase of flap deflection, but also with the increase of angle of attack and enlarged the bucket cavitation. To evaluate the efficiency of the Xfoil software, a 2D analysis flow over a NACA 0012 with leading and trailing edge flap was studied using Fluent software. The results of the two methods are in a good agreement. To validate the numerical approach, a passive adaptive composite model is built and tested in the hydrodynamic tunnel at the Research Institute of French Naval Academy. The model shows the ability to simulate the effect of flap by a LE and TE structural morphing due to hydrodynamic loading.

Keywords: cavitation, flaps, hydrofoil, panel method, xfoil

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Authors: Hakeem Ade Omokayode Idowu

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The extent of the role played by human capabilities developments as well as knowledge management on employees’ performance in the nuclear energy sector of Nigeria remains unclear. This is in view of the important role which human resource capabilities could play in the desire to generate energy using nuclear resources. This study appraised the extent of human resource capabilities available in the nuclear energy sector of Nigeria. It further examined the relationship between knowledge management and employees’ performance in the nuclear energy sector. The study adopted a descriptive research design with a population that comprised all the 1736 members of staff of the selected centres, institutes, and the headquarters of the Nigeria Atomic Energy Commission (NAEC), Nigerian Nuclear Regulatory Authority (NNRA), and Energy Commission of Nigeria (ECN) and a sample size of 332 employees was selected using purposive and convenience sampling techniques. Data collected were subjected to analysis using frequency counts and simple regression. The results showed that majority of the employees perceived that they have to a high extent of availability of knowledge (118, 35.5%), credibility (134, 40.4%), alignment (130, 39.2%), performance (126, 38%) and innovation (138, 41.6%) The result of the hypothesis tested indicated that knowledge management has a positive and significant effect on employees’ performance (Beta weight = 0.336, R2 =0.113, F-value = 41.959, p-value = 0.000< 0.05). The study concluded that human resource capabilities and knowledge management could enhance employee performance within the nuclear energy sector of Nigeria.

Keywords: human resource capabilities, knowledge management, employees productivity, national development

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Authors: Ranjitkumar Patil

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Age estimation has its importance in forensic dentistry. Dental age estimation has emerged as an alternative to skeletal age determination. The methods based on stages of tooth formation, as appreciated on radiographs, seems to be more appropriate in the assessment of age than those based on skeletal development. The study was done to evaluate dental age in north Indian population using Cameriere’s method. Aims/Objectives: The study was conducted to assess the dental age of North Indian children using Cameriere’smethodand to compare the chronological age and dental age for validation of the Cameriere’smethod in the north Indian population. A comparative study of 02 year duration on the OPG (using PLANMECA Promax 3D) data of 497 individuals with age ranging from 5 to 15 years was done based on simple random technique ethical approval obtained from the institutional ethical committee. The data was obtained based on inclusion and exclusion criteria was analyzed by a software for dental age estimation. Statistical analysis: Student’s t test was used to compare the morphological variables of males with those of females and to compare observed age with estimated age. Regression formula was also calculated. Results: Present study was a comparative study of 497 subjects with a distribution between male and female, with their dental age assessed by using Panoramic radiograph, following the method described by Cameriere, which is widely accepted. Statistical analysis in our study indicated that gender does not have a significant influence on age estimation. (R2= 0.787). Conclusion: This infers that cameriere’s method can be effectively applied in north Indianpopulation.

Keywords: Forensic, Chronological Age, Dental Age, Skeletal Age

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Authors: Wajid Mumtaz, Aamir Saeed Malik, Syed Saad Azhar Ali, Mohd Azhar Mohd Yasin

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In this paper, a technique based on electroencephalogram (EEG) analysis is presented, aiming for diagnosing major depressive disorder (MDD) among a potential population of MDD patients and healthy controls. EEG is recognized as a clinical modality during applications such as seizure diagnosis, index for anesthesia, detection of brain death or stroke. However, its usability for psychiatric illnesses such as MDD is less studied. Therefore, in this study, for the sake of diagnosis, 2 groups of study participants were recruited, 1) MDD patients, 2) healthy people as controls. EEG data acquired from both groups were analyzed involving inter-hemispheric asymmetry and composite permutation entropy index (CPEI). To automate the process, derived quantities from EEG were utilized as inputs to classifier such as logistic regression (LR) and support vector machine (SVM). The learning of these classification models was tested with a test dataset. Their learning efficiency is provided as accuracy of classifying MDD patients from controls, their sensitivities and specificities were reported, accordingly (LR =81.7 % and SVM =81.5 %). Based on the results, it is concluded that the derived measures are indicators for diagnosing MDD from a potential population of normal controls. In addition, the results motivate further exploring other measures for the same purpose.

Keywords: major depressive disorder, diagnosis based on EEG, EEG derived features, CPEI, inter-hemispheric asymmetry

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Authors: Antoine Vikkey Hinson, Ranty Jolianelle Dassi, Menonli Adjobimey, Rose Mikponhoue, Paul Ayelo

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Introduction: The psychological hardship of the teaching profession maintains a chronic stress that inevitably evolves into burnout (BO) in the absence of adequate preventive measures. The objective of this study is to study the prevalence and factors associated with burnout among secondary school teachers in the city of Cotonou in 2022. Methods: This was a descriptive cross-sectional study with an analytical aim and prospective data collection that took place over a period of 2 months, from July 19 to August 19 and from October 1 to October 31, 2022. Sampling was done using a three-stage probability sampling technique. Data analysis was performed using R 4.1.1 software. Bivariate logistic regression was used to identify associated factors. The significance level chosen was 5% (p < 0.05). Results: A total of 270 teachers were included in the study, of whom 208 (77.00%) were men. The mean age of the workers was 38.03 ± 8.30 years. According to the Maslach Burnout Inventory, 58.51% of the teachers had burnout, with 41.10% of teachers in emotional exhaustion, 27.40% in depersonalization and 21.90% in loss of personal accomplishment. The severity of the syndrome was low to moderate in almost all teachers. The occurrence of BO was associated with), not practicing sports (ORa= 2,38 [1,32; 4,28]), jobs training (ORa= 1,86 [1,04; 3,34]) and an imbalance of effort/reward (ORa= 5,98 [2,24;15,98]). Conclusion: The prevalence of BO is high among secondary school teachers in the city of Cotonou. A larger scale study, including research on its consequences on the teacher and the learner, is necessary in order to act quickly to implement a prevention program.

Keywords: burnout, teachers, Maslach burnout inventory, associated factors, Benin

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Authors: Jerickson Abbie Flores, Jana Fragante, Jan Paolo Dipasupil, Jan Jorge Francisco

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Malnutrition is one of the rapidly growing health problems affecting the world at present. Children affected are not only at risk for significant health problems, but are also faced with psychological and social consequences, including low self-esteem. School-age children are specifically vulnerable to develop poor self-esteem especially when their peers find them physically unattractive. Thus, malnutrition, whether obesity or undernourishment, contributes a significant role to a developing child’s health and behavior. This research aims to determine if there is a significant difference on the level of self-esteem among Filipino children ages 9-12 years old with abnormal body mass index (BMI) and those children with desirable BMI. Using a cross-sectional study design, the correlation between body mass index (BMI) and self-esteem was observed among children ages 9-12 years old. Participants took the Hare self esteem questionnaire, which is specifically designed to measure self-esteem in school age children. The lowest possible score is 15 and the highest possible score is 45. A total of 1140 students with ages 9-12 years old from Cembo Elementary School (public school) participated in the study. Among the participants, 239 out of the 1140 have desirable body mass index, 878 are underweight, and 23 are overweight. Using the test questionnaire, the computed mean scores were 36.599, 36.045 and 36.583 for normal, underweight and overweight categories respectively. Using Pearson’s Correlation Test and Spearman’s Correlation Coefficient Test, the study showed positive correlation (p value of 0.047 and 0.004 respectively) between BMI and Self-esteem scores which indicates that the higher the BMI, the higher the self-esteem of the participants.

Keywords: body mass index, malnutrition, school-age children, self-esteem

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Authors: Aref Aasi, Sahar Ebrahimi Bajgani, Erfan Aasi

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Breast cancer (BC) continues to be the most frequent cancer in females and causes the highest number of cancer-related deaths in women worldwide. Inspired by recent advances in studying the relationship between different patient attributes and features and the disease, in this paper, we have tried to investigate the different classification methods for better diagnosis of BC in the early stages. In this regard, datasets from the University Hospital Centre of Coimbra were chosen, and different machine learning (ML)-based and neural network (NN) classifiers have been studied. For this purpose, we have selected favorable features among the nine provided attributes from the clinical dataset by using a random forest algorithm. This dataset consists of both healthy controls and BC patients, and it was noted that glucose, BMI, resistin, and age have the most importance, respectively. Moreover, we have analyzed these features with various ML-based classifier methods, including Decision Tree (DT), K-Nearest Neighbors (KNN), eXtreme Gradient Boosting (XGBoost), Logistic Regression (LR), Naive Bayes (NB), and Support Vector Machine (SVM) along with NN-based Multi-Layer Perceptron (MLP) classifier. The results revealed that among different techniques, the SVM and MLP classifiers have the most accuracy, with amounts of 96% and 92%, respectively. These results divulged that the adopted procedure could be used effectively for the classification of cancer cells, and also it encourages further experimental investigations with more collected data for other types of cancers.

Keywords: breast cancer, diagnosis, machine learning, biomarker classification, neural network

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Authors: Fidel O. Okopi, Aminu Kazeem Ibrahim

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The study investigated psychosocial determinants ‘attitudes and self-esteem’ of school violent behaviors and the efficacy of covert sensitization therapy in combination with systematic approach therapy among male students in Lagos metropolis. Ex-post facto experimental research design was adopted for the study. The samples consisted of 39 school violent behavior students identified through the School Disciplinary Record Books and another 39 non-school violent behavior students identified through randomization. The two groups were from four randomly selected Public Senior Secondary Schools. School Violent Behavior Attitudes Scale (SVBAS) and School Violent Behavior Self-Esteem Scale (SVBSES) were used to collect data for the study. Face and Content validity with the Reliability coefficient of 0.772 for SVBAS and 0.813 for SVBSES were obtained. The results showed that the attitude of school violent behavior students do not significantly differ from that of school non-violent behavior students; the self-esteem of school violent behavior students differs significantly from that of school non-violent behavior students and that Covert Sensitization therapy in combination with Systematic Approach therapy were effective in modifying the self-esteem and attitude of school violent behavior students as surf iced in the pre-test and post-test analysis of school violent behavior students’ responses. The School counselors can modify male school violent behaviors that are traced to attitude and self-esteem with Covert Sensitization therapy in combination with Systematic Approach therapy in metropolitan areas.

Keywords: psychosocial determinants, violent behavior, covert sensitization therapy, systematic approach therapy

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Authors: Oscar Covarrubias, Diane Ghanem, Christopher Murdock, Babar Shafiq

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Introduction: ChatGPT is an advanced language AI tool designed to understand and generate human-like text. The aim of this study is to assess the ability of ChatGPT-4 to re-write orthopaedic trauma patient education materials at the recommended 6th-grade level. Methods: Two independent reviewers accessed ChatGPT-4 (chat.openai.com) and gave identical instructions to simplify the readability of provided text to a 6th-grade level. All trauma-related articles by the Orthopaedic Trauma Association (OTA) and American Academy of Orthopaedic Surgeons (AAOS) were sequentially provided. The academic grade level was determined using the Flesh-Kincaid Grade Level (FKGL) and Flesch Reading Ease (FRE). Paired t-tests and Wilcox-rank sum tests were used to compare the FKGL and FRE between the ChatGPT-4 revised and original text. Inter-rater correlation coefficient (ICC) was used to assess variability in ChatGPT-4 generated text between the two reviewers. Results: ChatGPT-4 significantly reduced FKGL and increased FRE scores in the OTA (FKGL: 5.7±0.5 compared to the original 8.2±1.1, FRE: 76.4±5.7 compared to the original 65.5±6.6, p < 0.001) and AAOS articles (FKGL: 5.8±0.8 compared to the original 8.9±0.8, FRE: 76±5.5 compared to the original 56.7±5.9, p < 0.001). On average, 14.6% of OTA and 28.6% of AAOS articles required at least two revisions by ChatGPT-4 to achieve a 6th-grade reading level. ICC demonstrated poor reliability for FKGL (OTA 0.24, AAOS 0.45) and moderate reliability for FRE (OTA 0.61, AAOS 0.73). Conclusion: This study provides a novel, simple and efficient method using language AI to optimize the readability of patient education content which may only require the surgeon’s final proofreading. This method would likely be as effective for other medical specialties.

Keywords: artificial intelligence, AI, chatGPT, patient education, readability, trauma education

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