Search results for: regression training

Authors: Dongkwon Han, Sangho Kim, Sunil Kwon

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Unconventional gas resources have dramatically changed the future energy landscape. Unlike conventional gas resources, the key challenges in unconventional gas have been the requirement that applies to advanced approaches for production forecasting due to uncertainty and complexity of fluid flow. In this study, artificial neural network (ANN) model which integrates machine learning and data-driven approach was developed to predict productivity in shale gas. The database of 129 wells of Eagle Ford shale basin used for testing and training of the ANN model. The Input data related to hydraulic fracturing, well completion and productivity of shale gas were selected and the output data is a cumulative production. The performance of the ANN using all data sets, clustering and variables importance (VI) models were compared in the mean absolute percentage error (MAPE). ANN model using all data sets, clustering, and VI were obtained as 44.22%, 10.08% (cluster 1), 5.26% (cluster 2), 6.35%(cluster 3), and 32.23% (ANN VI), 23.19% (SVM VI), respectively. The results showed that the pre-trained ANN model provides more accurate results than the ANN model using all data sets.

Keywords: unconventional gas, artificial neural network, machine learning, clustering, variables importance

Procedia PDF Downloads 191

Authors: Yixiu Liu, Yunzhou Zhang, Jianning Chi, Hao Chu, Rui Zheng, Libo Sun, Guanghao Chen, Fangtong Zhou

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In the last few years, large-scale person re-identification has attracted a lot of attention from video surveillance since it has a potential application prospect in public safety management. However, it is still a challenging job considering the variation in human pose, the changing illumination conditions and the lack of paired samples. Although the accuracy has been significantly improved, the data dependence of the sample training is serious. To tackle this problem, a new strategy is proposed based on bag of visual words (BoVW) model of designing the feature representation which has been widely used in the field of image retrieval. The local features are extracted, and more discriminative feature representation is obtained by cross-view dictionary learning (CDL), then the assignment map is obtained through k-means clustering. Finally, the BoVW histograms are formed which encodes the images with the statistics of the feature classes in the assignment map. Experiments conducted on the CUHK03, Market1501 and MARS datasets show that the proposed method performs favorably against existing approaches.

Keywords: bag of visual words, cross-view dictionary learning, person re-identification, reranking

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

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

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

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Authors: Samira Rabiei, Faezeh Askari, Reza Rastmanesh

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Objective: To evaluate the effects of nutrition education and adherence to a healthy diet on glycemic and lipidemic control in patients with T2DM. Material and Methods: A randomized controlled trial was conducted on 494 patients with T2DM, aged 14-87 years from both sexes who were selected by convenience sampling from referees to Aliebneabitaleb hospital in Ghom. The participants were divided into two 247 person groups by stratified randomization. Both groups received a diet adjusted based on ideal body weight, and the intervention group was additionally educated about healthy food choices regarding diabetes. Information on medications, psychological factors, diet and physical activity was obtained from questionnaires. Blood samples were collected to measure FBS, 2 hPG, HbA1c, cholesterol, and triglyceride. After 2 months, weight and biochemical parameters were measured again. Independent T-test, Mann-Whitney, Chi-square, and Wilcoxon were used as appropriate. Logistic regression was used to determine the odds ratio of abnormal glycemic and lipidemic control according to the intervention. Results: The mean weight, FBS, 2 hPG, cholesterol and triglyceride after intervention were significantly lower than before that (p < 0.05). Discussion: Nutrition education plus a weigh reducer diet is more effective on glycemic and lipidemic control than a weight reducer diet, alone.

Keywords: type 2 diabetes mellitus, nutrition education, glycemic control, lipid profile

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Authors: Suleiman Musa, Shuaibu Sidi Safiyanu

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This study examined the digital preservation in Nigeria university libraries. A comparison between the university of Nigeria Nsukka (UNN) and Ahmadu Bello University Zaria (ABU, Zaria). The study utilized primary source of data obtained from two selected institution librarians. Finding revealed varying results in terms of skills acquired by librarians before and after digitization of the two institutions. The study reports that journals publication, text book, CD-ROMS, conference papers and proceedings, theses, dissertations and seminar papers are among the information resources available for digitization. The study further documents that copyright issue, power failure, and unavailability of needed materials are among the challenges facing the digitization of library of the institution. On the basis of the finding, the study concluded that digitization of library enhances efficiency in organization and retrieval of information services. The study therefore recommended that software should be upgraded with backup, training of the librarians on digital process, installation of antivirus and enhancement of technical collaboration between the library and MIS.

Keywords: digitalization, preservation, libraries, comparison

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Authors: Jayprakash Yadav, Nivedita Patra

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Polyhydroxybutyrate (PHB) is an interesting material in the field of medical science, pharmaceutical industries, and tissue engineering because of its properties such as biodegradability, biocompatibility, hydrophobicity, and elasticity. PHB is naturally accumulated by several microbes in their cytoplasm during the metabolic process as energy reserve material. PHB can be extracted from cell biomass using halogenated hydrocarbons, chemicals, and enzymes. In this study, a cheaper and non-toxic solvent, acetone, was used for the extraction process. The different parameters like acetone percentage, and solvent pH, process temperature, and incubation periods were optimized using the Response Surface Methodology (RSM). RSM was performed and the determination coefficient (R2) value was found to be 0.8833 from the quadratic regression model with no significant lack of fit. The designed RSM model results indicated that the fitness of the response variable was significant (P-value < 0.0006) and satisfactory to denote the relationship between the responses in terms of PHB recovery and purity with respect to the values of independent variables. Optimum conditions for the maximum PHB recovery and purity were found to be solvent pH 7, extraction temperature - 43 °C, incubation time - 70 minutes, and percentage acetone – 30 % from this study. The maximum predicted PHB recovery was found to be 0.845 g/g biomass dry cell weight and the purity was found to be 97.23 % using the optimized conditions.

Keywords: acetone, PHB, RSM, halogenated hydrocarbons, extraction, bacillus subtilis.

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Authors: Bayu Anggara, Arita Dewi Nugrahini, Didik Purwadi

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Dry sorting workstation needs labor to produce green tea in Gambung Tea Factory. Observation results show that there is labor who are not working at the moment and doing overtime jobs to meet production targets. The measurement of the level of labor effectiveness has never been done before. The purpose of this study is to determine the level of labor effectiveness and provide recommendations for improvement based on the results of the Pareto diagram and Ishikawa diagram. The method used to measure the level of labor effectiveness is Overall Labor Effectiveness (OLE). OLE had three indicators which are availability, performance, and quality. Recommendations are made based on the results of the Pareto diagram and Ishikawa diagram for indicators that do not meet world standards. Based on the results of the study, the OLE value was 68.19%. Recommendations given to improve labor performance are adding mechanics, rescheduling rest periods, providing special training for labor, and giving rewards to labor. Furthermore, the recommendations for improving the quality of labor are procuring water content measuring devices, create material standard policies, and rescheduling rest periods.

Keywords: Ishikawa diagram, labor effectiveness, OLE, Pareto diagram

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Authors: J. K. Adedeji, M. O. Oyekanmi

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This paper has critically examined the use of Machine Learning procedures in curbing unauthorized access into valuable areas of an organization. The use of passwords, pin codes, user’s identification in recent times has been partially successful in curbing crimes involving identities, hence the need for the design of a system which incorporates biometric characteristics such as DNA and pattern recognition of variations in facial expressions. The facial model used is the OpenCV library which is based on the use of certain physiological features, the Raspberry Pi 3 module is used to compile the OpenCV library, which extracts and stores the detected faces into the datasets directory through the use of camera. The model is trained with 50 epoch run in the database and recognized by the Local Binary Pattern Histogram (LBPH) recognizer contained in the OpenCV. The training algorithm used by the neural network is back propagation coded using python algorithmic language with 200 epoch runs to identify specific resemblance in the exclusive OR (XOR) output neurons. The research however confirmed that physiological parameters are better effective measures to curb crimes relating to identities.

Keywords: biometric characters, facial recognition, neural network, OpenCV

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Authors: Pelin Kinay, Andy P. Morse, Elmer V. Villanueva, Karyn Morrissey, Philip L Staddon, Shanzheng Zhang, Jingjing Liu

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The present study aims to evaluate the climate change and health related knowledge, attitudes and practices (KAP) of the elderly population (60 years plus) in Hefei and Suzhou cities of China (n=300). This cross-sectional study includes 150 participants in each city. Data regarding demographic characteristics, KAP, and climate change perceptions were collected using a semi-structured questionnaire. When asked about the potential impacts of climate change over 79% of participants stated that climate change affected their lifestyle. Participants were most concerned about storms (51.7%), food shortage (33.3%) and drought (26%). The main health risks cited included water contamination (32%), air pollution related diseases (38.3%) and lung disease (43%). Finally, a majority (68.3%) did not report receiving government assistance on climate change issues. Logistic regression models were used to analyse the data in order to understand the links between socio-demographical factors and KAP of the participants. These findings provide insights for potential adaptation strategies targeting the elderly. It is recommended that government should take responsibility in creating awareness strategies to improve the coping capacity of elderly in China to climate change and its health impacts and develop climate change adaptation strategies.

Keywords: China, climate change, elderly, KAP

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Authors: G. Infante Dennis, S. Balinas Elvira, C. Valencia Yolanda, Cunanan

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This paper examined the feed-backs, concerns, and insights of the teachers, supervisors, and teacher-trainers on the nature and qualities of the K-12 grade 8 design, content, approaches, and materials. Specifically, it sought to achieve the following objectives: 1) to describe the critical nature and qualities of the design, content, teaching-learning-and-evaluation approaches, and the materials to be utilized in the implementation of the grade 8 curriculum; 2) to extract the possible challenges relevant to the implementation of the design, content, teaching-learning-and-evaluation approaches, and the materials of the grade 8 curriculum in terms of the linguistic and technical competence of the teachers, readiness to implement, willingness to implement, and capability to make relevant adaptations; 3) to present essential demands on the successful and meaningful implementation of the grade 8 curriculum in terms of teacher-related factors, school-related factors, and student-related concerns.

Keywords: curriculum reforms, K-12, teacher-training, language teaching, learning

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Authors: Amanda Burrell, Tonia Gary, David Wright, Kumara Ward

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This paper explores the concept of academic identity as it relates to the lecture, in particular, the digitized lecture delivered to a camera, in the absence of a student audience. Many academics have the performance aspect of the role thrust upon them with little or no training. For the purpose of this study, we look at the performance of the academic identity and examine tailored film presence coaching for its contributions toward academic identity, specifically in relation to feelings of self-confidence and diminishment of discomfort or stage fright. The case is articulated through the lens of scholar-practitioners, using expert facilitated participatory action research. It demonstrates in our sample of experienced academics, all reported some feelings of uncertainty about presenting lectures to camera prior to coaching. We share how power poses and reframing fear, produced improvements in the ease and competency of all participants. We share exactly how this insight could be adapted for self-coaching by any academic when called to present to a camera and consider the relationship between this and academic identity.

Keywords: academic identity, digitized lecture, embodied learning, performance coaching

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Authors: Samuel Ato Dadzie

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The objective of this study is to examine the influence of eclectic paradigm on motivational strategy of foreign subsidiaries in Ghana. This study uses binary regression model, and the analysis was based on 75 manufacturing investments made by MNEs from different countries in 1994–2008. The results indicated that perceived market size increases the probability of foreign firms undertaking a market seeking (MS) in Ghana, while perceived cultural distance between Ghana and foreign firm’s home countries decreased the probability of foreign firms undertaking an market seeking (MS) foreign direct investment (FDI) in Ghana. Furthermore, extensive international experience decreases the probability of foreign firms undertaking a market seeking (MS) foreign direct investment (FDI) in Ghana. Most of the studies done by earlier researchers were based on the advanced and emerging countries and offered support for the theory, which was used in generalizing the result that multinational corporations (MNCs) normally used the theory regarding investment strategy outside their home country. In using the same theory in the context of Ghana, the result does not offer strong support for the theory. This means that MNCs that come to Sub-Sahara Africa cannot rely much on eclectic paradigm for their motivational strategies because prevailing economic conditions in Ghana are different from that of the advanced and emerging economies where the institutional structures work.

Keywords: foreign subsidiary, motives, Ghana, foreign direct investment

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Authors: Uduak Umoh, Imo Eyoh, Emmauel Nyoho

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This paper compares fuzzy-machine learning algorithms such as Support Vector Machine (SVM), and K-Nearest Neighbor (KNN) for the predicting cases of fire outbreak. The paper uses the fire outbreak dataset with three features (Temperature, Smoke, and Flame). The data is pre-processed using Interval Type-2 Fuzzy Logic (IT2FL) algorithm. Min-Max Normalization and Principal Component Analysis (PCA) are used to predict feature labels in the dataset, normalize the dataset, and select relevant features respectively. The output of the pre-processing is a dataset with two principal components (PC1 and PC2). The pre-processed dataset is then used in the training of the aforementioned machine learning models. K-fold (with K=10) cross-validation method is used to evaluate the performance of the models using the matrices – ROC (Receiver Operating Curve), Specificity, and Sensitivity. The model is also tested with 20% of the dataset. The validation result shows KNN is the better model for fire outbreak detection with an ROC value of 0.99878, followed by SVM with an ROC value of 0.99753.

Keywords: Machine Learning Algorithms , Interval Type-2 Fuzzy Logic, Fire Outbreak, Support Vector Machine, K-Nearest Neighbour, Principal Component Analysis

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Authors: Nevine Henry Wasef

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The research discusses how Egyptian citizens perceive the performance of public sector officials, particularly the ethical values manifested in their behavior. It aims at answering the question of how Egyptian citizens’ perception of public officials affects citizens' trust in the government at large and the process of public service delivery specifically. The hypothesis is that public opinion about civil servants’ ethical values would be proportional to citizens’ trust in the government, which means that the more citizens regard administrators with high ethical standards, the higher trust in the government they would have and vice versa. The research would focus on the independent variable of trust in the government and the dependent variable of public perception of administrators’ ethical performance. The data would be collected through surveys designed to measure the public evaluation of public officials they are interacting with and the quality of services delivered to them. The study concludes that implementing ethical values in public administration has a crucial role in improving citizens’ trust in the government based on various case studies of governments that successfully adopted ethical training programs for their civil servants.

Keywords: trust, distrust, ethics, performance, integrity, values, public service

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Authors: Firas M. Tuaimah, Huda M. Abdul Abbas

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Accurate Short Term Load Forecasting (STLF) is essential for a variety of decision making processes. However, forecasting accuracy can drop due to the presence of uncertainty in the operation of energy systems or unexpected behavior of exogenous variables. Interval Type 2 Fuzzy Logic System (IT2 FLS), with additional degrees of freedom, gives an excellent tool for handling uncertainties and it improved the prediction accuracy. The training data used in this study covers the period from January 1, 2012 to February 1, 2012 for winter season and the period from July 1, 2012 to August 1, 2012 for summer season. The actual load forecasting period starts from January 22, till 28, 2012 for winter model and from July 22 till 28, 2012 for summer model. The real data for Iraqi power system which belongs to the Ministry of Electricity.

Keywords: short term load forecasting, prediction interval, type 2 fuzzy logic systems, electric, computer systems engineering

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Authors: Adeola Adejumo, Oluwole David Adebayo, Muraina Kamilu Olanrewaju

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The purpose of this study was to investigate the influence of some psychological factors (i.e, school climate, parental involvement and classroom interaction) on the learning gains of university undergraduates in Mathematics in Ibadan, Nigeria. Three hundred undergraduates who are on open distance learning education programme in the University of Ibadan and thirty mathematics lecturers constituted the study’s sample. Both the independent and dependent variables were measured with relevant standardized instruments and the data obtained was analyzed using multiple regression statistical method. The instruments used were school climate scale, parental involvement scale and classroom interaction scale. Three research questions were answered in the study. The result showed that there was significant relationship between the three independent variables (school climate, parental involvement and classroom interaction) on the students’ learning gain in mathematics and that the independent variables both jointly and relatively contributed significantly to the prediction of students’ learning gain in mathematics. On the strength of these findings, the need to enhance the school climate, improve the parents’ involvement in the student’s education and encourage students’ classroom interaction were stressed and advocated.

Keywords: school climate, parental involvement, ODL, learning gains, mathematics

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Authors: Rida Kanwal, Wang Yuhui, Song Weiguo

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Wildfires are one of the most prominent threats to ecosystems, human health, and economic activities. Wind is a driving factor of wildfires. This paper combines machine learning (ML) and remote sensing (RS) to assess the effects of wind on wildfires in Chongqing Province from August 16-23, 2022. In this research, Landsat 8 satellite images are used for the estimation of the difference normalized burn ratio (dNBR), which represents the prefire and postfire vegetation conditions. Wind data were sourced from the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis version 5 (ERA5) dataset and analyzed with geographic information system (GIS) mapping. Correlation analysis between the wind speed and FRP revealed a significant relationship. An autoregressive integrated moving average (ARIMA) model was developed for wind forecasting, and linear regression was used to determine the effect of wind speed on FRP. The results depicted high wind speed as one of the prominent factors behind the surge in FRP. Winds blowing to the northwest (NW), where wildfires spread, were discovered in the wind-rose plots. Furthermore, this model was validated with data from different provinces of China. This study integrated ML, RS, and GIS to analyze wildfire behavior for effective prediction and management strategies.

Keywords: wildfires, machine learning, wind, wind speed

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Authors: Salem Abdalla

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Objective: Dipyrone is a widely used, well tolerated analgesic drug which, however, is compromised by agranulocytosis as an adverse effect. Subsequent to no enzymatic hydrolysis, the primary metabolic step is N-demethylation of 4-methylaminoantipyrine (4-MAA) to 4-aminoantipyrine (4-AA). The aim of the present study was to identify the cytochrome P-450 enzyme (CYP) mediating this reaction. Methods: We identified the relevant CYP using virus expressed isolated rat liver microsomes with chemical inhibition studies. The substrate of 4-methylaminantipyrine was employed at six different concentrations (25, 50, 100, 400, 800, and 1200 µmol/l) with varying concentrations of selective inhibitors of CYP1A2 (furafylline, fluvoxamine), CYP3A4 (ketoconazole), CYP2A6 (coumarin), CYP2D6 (quinidine), CYP2C19 (omeprazole, fluvoxamine, tranylcypromine), CYP2C9 (sulfaphenazole), and CYP1A1 (alpha-naphthoflavone). 4-MAA and 4-AA were analyzed by HPLC, and enzyme kinetic parameters (Km and Vmax) were determined by regression (Sigma plot 9.0). Results: The N-demethylation of 4-MAA by microsomes prepared from baculovirus-expressing human CYP was pronounced with CYP2C19. Intrinsic clearances of the most active enzymes were 0.092, 0.027, and 0.026 for the CYP enzymes 2C19, 2D6, and 1A2, respectively. Metabolism by rat liver microsomes was strongly inhibited by omeprazole (IC50 of 0.05). Conclusion: The enzyme CYP2C19 apparently has an important role in N-demethylation of 4-methylaminoantipyrine which should be further analyzed in clinical studies and which may also be interesting concerning the agranulocytosis.

Keywords: dipyrone, 4-methylaminoantipyrine (4-MAA), 4- aminoantipyrine (4-AA), metabolism, human CYP2C19

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Authors: S. Sharan Sundar, Nithish B. Moudhgalya, Nidhi Bhandari, Vineeth Vijayaraghavan

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Automatic Short Answer Grading is one of the prime applications of artificial intelligence in education. Several approaches involving the utilization of selective handcrafted features, graphical matching techniques, concept identification and mapping, complex deep frameworks, sentence embeddings, etc. have been explored over the years. However, keeping in mind the real-world application of the task, these solutions present a slight overhead in terms of computations and resources in achieving high performances. In this work, a simple and effective solution making use of elemental features based on statistical, linguistic properties, and word-based similarity measures in conjunction with tree-based classifiers and regressors is proposed. The results for classification tasks show improvements ranging from 1%-30%, while the regression task shows a stark improvement of 35%. The authors attribute these improvements to the addition of multiple similarity scores to provide ensemble of scoring criteria to the models. The authors also believe the work could reinstate that classical natural language processing techniques and simple machine learning models can be used to achieve high results for short answer grading.

Keywords: artificial intelligence, intelligent systems, natural language processing, text mining

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Authors: Ali H. Muhammad

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This paper investigates both instrumental and emotional family support on employee job satisfaction and perception of work-family conflict. Instrumental family support is manifested in family behavior that contributes to the reduction of employee’s family responsibilities and keeping the physical home environment in a proper shape. Emotional family support includes the encouragement and praise that the employee receives from his family and families for the employee’s work problem and their role in assisting the employees in dealing with these problems. The paper suggests that instrumental and emotional family support increases employee’s job satisfaction. Furthermore, the study proposes that family support decreases employee’s perception of work-family conflict. In addition, this study examines the reliability and validity of the family support index developed by Lynda King and her colleagues in 1995. Confirmatory factor analysis is used to test the validity of the instrument in an Arab business setting. A paper-pencil questionnaire was used to collect data from a random sample of 70 Kuwaiti employees working in the oil sector. Data were analyzed using factor analysis, reliability tests, and regression analysis. Results confirmed the research hypothesis. Family support had a positive effect on job satisfaction. Furthermore, family support significantly contributed to the reduction of employee perception of work-family conflict.

Keywords: family support, job satisfaction, work-family conflict, Kuwait oil sector

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Authors: Vesna Karapetkovska Hristova, M. Ayaz Ahmad, Julijana Tomovska, Biljana Bogdanova Popov, Blagojce Najdovski

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The average total concentrations of heavy metals; (cadmium [Cd], copper [Cu], nickel [Ni], lead [Pb], and zinc [Zn]) were analyzed in soil and vegetables samples collected from the different region of Macedonia during the years 2010-2012. Basic soil properties such as pH, organic matter and clay content were also included in the study. The average concentrations of Cd, Cu, Ni, Pb, Zn in the A horizon (0-30 cm) of agricultural soils were as follows, respectively: 0.25, 5.3, 6.9, 15.2, 26.3 mg kg-1 of soil. We have found that neural networking model can be considered as a tool for prediction and spatial analysis of the processes controlling the metal transfer within the soil-and vegetables. The predictive ability of such models is well over 80% as compared to 20% for typical regression models. A radial basic function network reflects good predicting accuracy and correlation coefficients between soil properties and metal content in vegetables much better than the back-propagation method. Neural Networking / soft computing can support the decision-making processes at different levels, including agro ecology, to improve crop management based on monitoring data and risk assessment of metal transfer from soils to vegetables.

Keywords: soft computing approach, total concentrations, heavy metals, agricultural soils

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Authors: Vivienne Langhorne, Helen Sharpe

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Body dissatisfaction begins developing in middle childhood, with wide-ranging implications for mental health and well-being. Previous research on parent behavior has focused on the role of explicit parent behaviors in adolescent and young adult body dissatisfaction, leaving a gap in understanding how implicit parent behaviors relate to body dissatisfaction in childhood. The current study investigated how implicit parent behavior (such as modeling own body dissatisfaction and dieting) relates to parent and child body dissatisfaction. It was hypothesized that implicit behavior would be directly related to parent and child body dissatisfaction and mediate the relationship between the two. Furthermore, this study aimed to examine child gender as a potential moderator in this mediation, as research shows that boys and girls experience body dissatisfaction differently. This study analyzed survey responses on parent body dissatisfaction, implicit behavior, and child body dissatisfaction measures from a sample of 166 parent-child dyads with children between the ages of 6 to 9 years old. Regression analyses revealed that parent body dissatisfaction is related to both parent-implicit behavior and child body dissatisfaction. However, implicit behavior did not mediate the relationship between the two body dissatisfaction variables. Additionally, the results of moderated mediation indicated there were no child gender differences in the strength of the association between parental implicit behaviors and child body dissatisfaction. These findings highlight the need for further research into the mechanisms behind parent and child body dissatisfaction to better understand the process through which intergenerational transmission occurs.

Keywords: body dissatisfaction, implicit behaviour, middle childhood, parenting

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Authors: Freda E. Asem, R. D. Osei, D. B. Sarpong, J. K. Kuwornu

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While market access remains important, Ghana’s major handicap is her inability to sustain export growth on the open market. The causes of these could be attributed to inefficiency, lack of competitiveness and supply-side constraints. This study examined the challenges faced by smallholder horticultural farmers and how it relates to their technical efficiency. The study employed mixed methods to address the problem. Using the Millennium Development Account (MiDA) Farmer Based Organization survey data on farm households in 23 districts in Ghana, the study assessed the technical efficiency of smallholder horticultural farmers (taking into account production risks). Focus group discussions (FGDs) and in-depth interviews were also conducted on smallholder mango, pineapple, and chilli pepper farmers selected districts in Ghana. Results revealed the constraints faced by smallholder horticultural farmers to be marketing, training, funding, accessibility, and affordability of inputs, land, access to credit, and the disconnect between themselves and policy makers and implementers.

Keywords: productivity, gender, policy, efficiency, constraints

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Authors: Chandra Prayaga, Aaron Wade, Lakshmi Prayaga, Gopi Shankar Mallu

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This paper presents the use of machine learning algorithms to predict the success of students in an introductory physics course. Data having 140 rows pertaining to the performance of two batches of students was used. The lack of sufficient data to train robust machine learning models was compensated for by generating synthetic data similar to the real data. CTGAN and CTGAN with Gaussian Copula (Gaussian) were used to generate synthetic data, with the real data as input. To check the similarity between the real data and each synthetic dataset, pair plots were made. The synthetic data was used to train machine learning models using the PyCaret package. For the CTGAN data, the Ada Boost Classifier (ADA) was found to be the ML model with the best fit, whereas the CTGAN with Gaussian Copula yielded Logistic Regression (LR) as the best model. Both models were then tested for accuracy with the real data. ROC-AUC analysis was performed for all the ten classes of the target variable (Grades A, A-, B+, B, B-, C+, C, C-, D, F). The ADA model with CTGAN data showed a mean AUC score of 0.4377, but the LR model with the Gaussian data showed a mean AUC score of 0.6149. ROC-AUC plots were obtained for each Grade value separately. The LR model with Gaussian data showed consistently better AUC scores compared to the ADA model with CTGAN data, except in two cases of the Grade value, C- and A-.

Keywords: machine learning, student success, physics course, grades, synthetic data, CTGAN, gaussian copula CTGAN

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Authors: Atuhurra Jesse, N'guessan Yves-Roland Douha, Pabitra Lenka

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The detection of diseases within plants has attracted a lot of attention from computer vision enthusiasts. Despite the progress made to detect diseases in many plants, there remains a research gap to train image classifiers to detect the cacao swollen shoot virus disease or CSSVD for short, pertinent to cacao plants. This gap has mainly been due to the unavailability of high quality labeled training data. Moreover, institutions have been hesitant to share their data related to CSSVD. To fill these gaps, image classifiers to detect CSSVD-infected cacao plants are presented in this study. The classifiers are based on VGG16, ResNet50 and Vision Transformer (ViT). The image classifiers are evaluated on a recently released and publicly accessible KaraAgroAI Cocoa dataset. The best performing image classifier, based on ResNet50, achieves 95.39\% precision, 93.75\% recall, 94.34\% F1-score and 94\% accuracy on only 20 epochs. There is a +9.75\% improvement in recall when compared to previous works. These results indicate that the image classifiers learn to identify cacao plants infected with CSSVD.

Keywords: CSSVD, image classification, ResNet50, vision transformer, KaraAgroAI cocoa dataset

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Authors: Ningombam Linthoingambi Devi, Amrendra Kumar

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The long term sampling at one of the most populated city in Indo-Gangetic region shows higher mass concentration of atmospheric aerosol (PM₂.₅) during spring season (144.70µg/m³), summer season (91.96 µg/m³), the autumn season (266.48µg/m³) and winter season (367.09 µg/m³) respectively. The concentration of PM₂.₅ in Patna across the year shows much higher than the limit fixed by the national ambient air quality level fixed by central pollution control board India (CPCB, India) and World Health Organization (WHO). Different water-soluble cation (Na⁺, K⁺, Ca²⁺, NH₄⁺ , and Mg²⁺) and anion (Cl⁻, NO₃⁻ , and SO₄²⁻) species were detected in PM₂.₅. Results show the significantly higher loaded of water-soluble ions during winter and spring seasons. The acidity of the atmosphere was revealed and calculated using selected major cations (K⁺, Ca²⁺ , and NH₄⁺) and anions (SO₄²⁻, and NO₃⁻). A regression correlation was analyzed to check the significant linkage between the acidity and alkalinity ions. During the winter season (r² = 0.79) and spring season (r² = 0.64) shows good significant correlation between the cations and anions. The ratio of NO₃⁻/SO₄²⁻ indicates the sources of secondary pollutants were mainly influenced by industrial and vehicular emission however SO₄²⁻ mostly emitted from industries during the winter season.

Keywords: aerosols, inorganic species, source apportionment, Indo-Gangetic region

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Authors: Ali Kassem, Esam Nada, Amro Abdelhamed, Shigeo Horie

Abstract:

Objective: Diabetes mellitus (DM) is associated with macrovascular complications, including coronary artery disease (CAD), and microvascular complications that contribute to the pathogenesis of erectile dysfunction (ED). On the other hand, silent myocardial ischemia (SMI) is more common in diabetic patients and is a strong predictor of cardiac events and mortality in diabetic and non-diabetic patients. Recently, Multidetector computed tomographic coronary angiography (MDCT-CA) has become a reliable non-invasive imaging modality for screening diabetic patients for SMI. We aim to evaluate the presence of SMI using (MDCT-CA) in patients with type 2DM having ED. Methods: This study evaluated 20 patients (mean age 61.45 ± 10.7 years), with DM and ED without any history of angina or angina equivalent. ED was tested with the Sexual Health Inventory for Men score, erection hardness score (EHS), and maximal penile circumferential change by an erect meter. Results: Of twenty studied patients, coronary artery stenosis was detected in 13 (65%) patients in the form of one-vessel disease (n = 6, 30%), two-vessel disease (n = 2, 10%), and three-vessel disease (n = 5, 25%). Maximum coronary artery stenosis was positively correlated with age (P < 0.016,) and negatively correlated with EHS (P <04). Multivariate regression analysis using age and EHS showed that age was the only independent predictor of SMI (P <04). Conclusion: MDCT-CA is a useful tool to identify SMI in patients with diabetes mellitus and ED. One should consider the possibility of SMI especially in elderly patients with DM who have ED.

Keywords: diabetes mellitus, erectile dysfunction, microvascular, silent ischemia

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Authors: Temitope Adewale, Oladapo Raji

Abstract:

The study was designed to investigate the assessment of women's involvement in fishing. In order to give the study a direction, five research questions, as well as two hypotheses, were postulated, and a total of fifty (50) respondents each were selected from two local government areas for the study. This brings a total of one hundred (100) respondents selected from these local government areas in Lagos state. The outcome of the finding indicates that the percentage of the respondents’ age, 49% was between 31 and 35 years, 56% has a working experience of 6-10 years, 61% were married, 69% had secondary education as their educational level. However, findings show that socio-economic characteristics (x2 =15.504, df=6, p < 0.05) and income (r=0.83, p < 0.05) have a significant relationship on the fishing. It was established that the Women in Fish production/processing were faced with a lot of constraints such as high cost of inputs, inadequate electricity supply, lack of adequate capital, non-availability of the improved oven, non-availability of extension agents, inadequate fish landing, lack of transportation facilities, lack of training on financial management and loan acquisition which affected the level of output of women in Fish processing adversely.

Keywords: women, fishing, agriculture, Lagos

Procedia PDF Downloads 139

Authors: Olga Castiblanco, Diego Vizcaíno

Abstract:

Changing the traditional way of using experimentation in science teaching is quite a challenge. This research results talk about the characterization of physics experiments, not because of the topic it deals with, nor depending on the material used in the assemblies, but related to the possibilities it offers to enrich interaction in the classroom and thereby contribute to the development of scientific thinking skills. It is an action-research of type intervention in the classroom, with four courses of Physics Teaching undergraduate students from a public university in Bogotá. This process allows characterizing typologies such as discrepant, homemade, illustrative, research, recreational, crucial, mental, and virtual experiments. Students' production and researchers' reports on each class were the most relevant data. Content analysis techniques let to categorize the information and obtain results on the richness that each typology of experiment offers when interacting in the classroom. Results show changes in the comprehension of new teachers' role, far from being the possessor and transmitter of the truth. Besides, they understand strategies to engage students effectively since the class advances extending ideas, reflections, debates, and questions, either towards themselves, their classmates, or the teacher.

Keywords: physics teacher training, non-traditional experimentation, contextualized education, didactics of physics

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Authors: Sanja Podunavac-Kuzmanović, Denis Kučević, Strahinja Kovačević, Milica Karadžić, Lidija Jevrić

Abstract:

The present study describes the application of chemometric methods in analysis of milk samples which were collected in a conventional dairy farm and an organic dairy farm in AP Vojvodina, Republic of Serbia. The chemometric analysis included the application of univariate regression modeling and Analysis of Variance (ANOVA) method. The ANOVA was used in order to determine the differences in fatty acids content in the milk samples from conventional and organic farm. The results of the ANOVA testing indicate that there is a highly statistically significant difference between the content of fatty acid (saturated fatty acid vs. unsaturated fatty acids) in different dairy farming. Besides, the linear univariate models have been obtained as a result of modeling the linear relationships between the milk fat content and saturated fatty acids content, and the linear relationships between the milk fat content and unsaturated fatty acids content. The models obtained on the basis of the milk samples which originate from the organic farming are statistically better than the models based on the milk samples from conventional farming.

Keywords: hemometrics, milk, organic farming, quality control

Procedia PDF Downloads 233