Search results for: score prediction

Authors: Jaydip De

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Urban parks are open places, green fields and riverside gardens usually maintained by public or private authorities, or eventually by both jointly; and utilized for a multidimensional purpose by the citizens. These parks are indeed the lung of urban centers. In urban socio-environmental setup, parks are the nucleus of social integration, community building, and physical development. In contemporary cities, these green places seem to perform as the panacea of congested, complex and stressful urban life. The alarmingly increasing urban population and the resultant congestion of high-rises are making life wearisome in neo-liberal cities. This has made the citizen always quest for open space and fresh air. In such a circumstance, the mere existence of parks is not capable of satisfying the growing aspirations. Therefore in this endeavour, a structured attempt is so made to empirically identify the utility, visitors’ satisfaction, and future needs through the cases of two urban parks of Kolkata Metropolitan Area, India. This study is principally based upon primary information collected through visitors’ perception survey conducted at the Chinsurah ground and Chandernagore strand. The correlation between different utility categories is identified and analyzed systematically. At the same time, indices like Weighted Satisfaction Score (WSS), Facility wise Satisfaction Index (FSI), Urban Park Satisfaction Index (UPSI) and Urban Park Necessity Index (UPNI) are advocated to quantify the visitors’ satisfaction and future necessities. It is explored that the most important utilities are passive in nature. Simultaneously, satisfaction levels of visitors are average, and their requirements are centred on the daily needs of the next generation, i.e., the children. Further, considering the visitors’ opinion planning measures are promulgated for holistic development of urban parks to revitalize sustainability of citified life.

Keywords: citified life, future needs, visitors’ satisfaction, urban parks, utility

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Authors: Lina María Martínez Sánchez, Juliana Molina Valencia, Esteban Vallejo Agudelo, Daniel Gallego González, María Isabel Pérez Palacio, Juan Ricardo Gaviria García, María De Los Ángeles Rodríguez Gázquez, Gloria Inés Martínez Domínguez

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Alternative and complementary therapies constitute a vast and complex combination of interventions, philosophies, approaches, and therapies that acquire a holistic healthcare point of view, becoming an alternative for the treatment of patients with chronic pain. Objective: determine the characteristics of the use of alternative and complementary therapies in patients with chronic pain who consulted in a medical institution. Methodology: cross-sectional and descriptive study, with a population of patients that assisted to the outpatient consultation and met the eligibility criteria. Sampling was not conducted. A form was used for the collection of demographic and clinical variables and the Holistic Complementary and Alternative Medicine Questionnaire (HCAMQ) was validated. The analysis and processing of information was carried out using the SPSS program vr.19. Results: 220 people with chronic pain were included. The average age was 54.7±16.2 years, 78.2% were women, and 75.5% belonged to the socioeconomic strata 1 to 3. Musculoskeletal pain (77.7%), migraine (15%) and neuralgia (9.1%) were the most frequently types of chronic pain. 33.6% of participants have used some kind of alternative and complementary therapy; the most frequent were: homeopathy (14.5%), phytotherapy (12.7%), and acupuncture (11.4%). The total average HCAMQ score for the study group was 30.2±7.0 points, which shows a moderate attitude toward the use of complementary and alternative medicine. The highest scores according to the type of pain were: neuralgia (32.4±5.8), musculoskeletal pain (30.5±6.7), fibromyalgia (29.6±7.3) and migraine (28.5±8.8). The reliability of the HCAMQ was acceptable (Cronbach's α: 0.6). Conclusion: it was noted that the types of chronic pain and the clinical or therapeutic management of patients correspond to the data available in current literature. Despite the moderate attitude toward the use of these alternative and complementary therapies, one of every three patients uses them.

Keywords: chronic pain, complementary therapies, homeopathy, acupuncture analgesia

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Authors: Thewodros K. Geberemariam

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The rapid physical expansion of urbanization coupled with aging infrastructure presents a unique decision and management challenges for many big city municipalities. Cities must therefore upgrade and maintain the existing aging urban drainage infrastructure systems to keep up with the demands. Given the overall contribution of assets to municipal revenue and the importance of infrastructure to the success of a livable city, many municipalities are currently looking for a robust and smart urban drainage infrastructure asset management solution that combines management, financial, engineering and technical practices. This robust decision-making shall rely on sound, complete, current and relevant data that enables asset valuation, impairment testing, lifecycle modeling, and forecasting across the multiple asset portfolios. On this paper, predictive computational intelligence (CI) and multi-class machine learning (ML) coupled with online, offline, and historical record data that are collected from an array of multi-parameter sensors are used for the extraction of different operational and non-conforming patterns hidden in structured and unstructured data to determine and produce actionable insight on the current and future states of the network. This paper aims to improve the strategic decision-making process by identifying all possible alternatives; evaluate the risk of each alternative, and choose the alternative most likely to attain the required goal in a cost-effective manner using historical and near real-time urban drainage infrastructure data for urban drainage infrastructures assets that have previously not benefited from computational intelligence and machine learning advancements.

Keywords: computational intelligence, machine learning, urban drainage infrastructure, machine learning, classification, prediction, asset management space

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Authors: Carlos Gonzales, Zaida Quiroz, Marcos Prates

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Several spatial variables collected at the same location that share a common spatial distribution can be modeled simultaneously through a multivariate geostatistical model that takes into account the correlation between these variables and the spatial autocorrelation. The main goal of this model is to perform spatial prediction of these variables in the region of study. Here we focus on a geostatistical multivariate formulation that relies on sharing common spatial random effect terms. In particular, the first response variable can be modeled by a mean that incorporates a shared random spatial effect, while the other response variables depend on this shared spatial term, in addition to specific random spatial effects. Each spatial random effect is defined through a Gaussian process with a valid covariance function, but in order to improve the computational efficiency when the data are large, each Gaussian process is approximated to a Gaussian random Markov field (GRMF), specifically to the block nearest neighbor Gaussian process (Block-NNGP). This approach involves dividing the spatial domain into several dependent blocks under certain constraints, where the cross blocks allow capturing the spatial dependence on a large scale, while each individual block captures the spatial dependence on a smaller scale. The multivariate geostatistical model belongs to the class of Latent Gaussian Models; thus, to achieve fast Bayesian inference, it is used the integrated nested Laplace approximation (INLA) method. The good performance of the proposed model is shown through simulations and applications for massive data.

Keywords: Block-NNGP, geostatistics, gaussian process, GRMF, INLA, multivariate models.

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Authors: Ghalia Shamlan, M. Denise Robertson, Adam Collins

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Appetite control (i.e. control of energy intake) is important for weight maintenance. Exercise contributes to the most variable component of energy expenditure (EE) but its impact is beyond the energy cost of exercise including physiological, behavioural, and appetite effects. Exercise is known to acutely influence effect appetite but evidence as to the independent effect of intensity is lacking. This study investigated the role of exercise intensity on appetite, energy intake (EI), appetite related hormone, fat utilisation and subjective measures of appetite. One hour after a standardised breakfast, 10 sedentary overweight volunteers. Subjects undertook either 8 repeated 60 second bouts of cycling at 95% VO2max (high intensity) or 30 minutes of continuous cycling, at a fixed cadence, equivalent to 50% of the participant’s VO2max (low intensity) in a randomised crossover design. Glucose, NEFA, glucagon-like peptide-1 (GLP-1) were measured fasted, postprandial, and pre and post-exercise. Satiety was assessed subjectively throughout the study using visual analogue scales (VAS). Ad libitum intake of a pasta meal was measured at the end (3-h post-breakfast). Interestingly, there was not significant difference in EE fat oxidation between HI and LI post-exercise. Also, no significant effect of high intensity (HI) was observed on the ad libitum meal, 24h and 48h EI post-exercise. However the mean 24h EI was 3000 KJ lower following HI than low intensity (LI). Despite, no significant differences in hunger score, glucose, NEFA and GLP-1 between both intensities were observed. However, NEFA and GLP-1 plasma level were higher until 30 min post LI. In conclusion, the similarity of EE and oxidation outcomes could give overweight individuals an option to choose between intensities. However, HI could help to reduce EI. There are mechanisms and consequences of exercise in short and long-term appetite control; however, these mechanisms warrant further explanation. These results support the need for future research in to the role of in regulation energy balance, especially for obese people.

Keywords: appetite, exercise, food intake, energy expenditure

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Authors: M. Reza Roshandel, Tannaz Aghaei Badr, Batoul Khoundabi, Sara C. Lewis, Soroush Rais-Bahrami, John Sfakianos, Reza Mehrazin, Ash K. Tewari

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Introduction: Prostate biopsy is the most reliable diagnostic method for choosing the appropriate management of prostate cancer. However, discrepancies between Gleason grade groups (GG) of different biopsies remain a significant concern. This study aims to assess the association of the radiological factors with GG discrepancies in patients with index Prostate Imaging Reporting and Data System (PI-RADS) 3 lesions, using radical prostatectomy (RP) specimens as the most accurate and informative pathology. Methods: This single-institutional retrospective study was performed on a total of 2289 consecutive prostate cancer patients with combined targeted and systematic prostate biopsy followed by radical prostatectomy (RP). The database was explored for patients with the index PI-RADS 3 lesions version 2 and 2.1. Cancers with PI-RADS 4 or 5 scoring were excluded from the study. Patient characteristics and radiologic features were analyzed by multivariable logistic regression. Number-density of lesions was defined as the number of lesions per prostatic volume. Results: Of the 151 prostate cancer cases with PI-RADS 3 index lesions, 27% and 17% had upgrades and downgrades at RP, respectively. Analysis of grade changes showed no significant associations between discrepancies and the number or the number density of PI-RADS 3 lesions. Moreover, the study showed no significant association of the GG changes with race, age, location of the lesions, or prostate volume. Conclusions: This study demonstrated that in PI-RADS 3 cancerous nodules, the chance of the pathology changes in the final pathology of RP specimens was low. Furthermore, having multiple PI-RADS 3 nodules did not change the conclusion, as the possibility of grade changes in patients with multiple nodules was similar to those with solitary lesions.

Keywords: prostate, adenocarcinoma, multiparametric MRI, Gleason score, robot-assisted surgery

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Authors: Samy A. Khalil, U. Ali Rahoma

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The measurements of solar radiation, satellite data has been routinely utilize to estimate solar energy. However, the temporal coverage of satellite data has some limits. The reanalysis, also known as "retrospective analysis" of the atmosphere's parameters, is produce by fusing the output of NWP (Numerical Weather Prediction) models with observation data from a variety of sources, including ground, and satellite, ship, and aircraft observation. The result is a comprehensive record of the parameters affecting weather and climate. The effectiveness of reanalysis datasets (ERA-5) for North Africa was evaluate against high-quality surfaces measured using statistical analysis. Estimating the distribution of global solar radiation (GSR) over five chosen areas in North Africa through ten-years during the period time from 2011 to 2020. To investigate seasonal change in dataset performance, a seasonal statistical analysis was conduct, which showed a considerable difference in mistakes throughout the year. By altering the temporal resolution of the data used for comparison, the performance of the dataset is alter. Better performance is indicate by the data's monthly mean values, but data accuracy is degraded. Solar resource assessment and power estimation are discuses using the ERA-5 solar radiation data. The average values of mean bias error (MBE), root mean square error (RMSE) and mean absolute error (MAE) of the reanalysis data of solar radiation vary from 0.079 to 0.222, 0.055 to 0.178, and 0.0145 to 0.198 respectively during the period time in the present research. The correlation coefficient (R2) varies from 0.93 to 99% during the period time in the present research. This research's objective is to provide a reliable representation of the world's solar radiation to aid in the use of solar energy in all sectors.

Keywords: solar energy, ERA-5 analysis data, global solar radiation, North Africa

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Authors: Charles U. Eze, Joy Johnbest Egbo

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The study investigated the effect of Context-Based Instructional Strategy (CBIS) on students’ achievement in chemistry. CBIS was used as an experimental group and expository method (EM) as a control group, sources showed that students poor achievement in chemistry is from teaching strategy adopted by the chemistry teachers. Two research questions were answered, and two null hypotheses were formulated and tested. This strategy recognizes the need for student-centered, relevance of tasks and students’ voice; it also helps students develop creative and critical learning skills. A quasi-experimental (non-equivalent, pretest, posttest control group) design was adopted for the study. The population for the study comprised all senior secondary class one (SSI) students who were offering chemistry in co-education schools in Agbani Education zone. The instrument for data collection was a self-developed Basic Chemistry Achievement Test (BCAT). Relevant data were collected from a sample of SSI chemistry students using purposive random sampling techniques from two co-education schools in Agbani Education Zone of Enugu State, Nigeria. A reliability co-efficient was obtained for the instrument using Kuder-Richardson formula 20. Mean and standard deviation scores were used to answer the research questions while two-way analysis of covariance (ANCOVA) was used to test the hypotheses. The findings showed that the experimental group taught with context-based instructional strategy (CBIS) obtained a higher mean achievement score than the control group in the post BCAT; male students had higher mean achievement scores than their female counterparts. The difference was significant. It was recommended, among others, that CBIS should be given more emphasis in the training and re-training program of secondary school chemistry teachers.

Keywords: context-based instructional strategy, expository strategy, student-centered

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Authors: Brindha Senthil Kumar, Payel Chakraborty, Senthil Kumar Nachimuthu, Arindam Maitra, Prem Nath

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Gastric cancer is predominantly caused by demographic and diet factors as compared to other cancer types. The aim of the study is to predict Early Gastric Cancer (ECG) from diet and lifestyle factors using supervised machine learning algorithms. For this study, 160 healthy individual and 80 cases were selected who had been followed for 3 years (2016-2019), at Civil Hospital, Aizawl, Mizoram. A dataset containing 11 features that are core risk factors for the gastric cancer were extracted. Supervised machine algorithms: Logistic Regression, Naive Bayes, Support Vector Machine (SVM), Multilayer perceptron, and Random Forest were used to analyze the dataset using Python Jupyter Notebook Version 3. The obtained classified results had been evaluated using metrics parameters: minimum_false_positives, brier_score, accuracy, precision, recall, F1_score, and Receiver Operating Characteristics (ROC) curve. Data analysis results showed Naive Bayes - 88, 0.11; Random Forest - 83, 0.16; SVM - 77, 0.22; Logistic Regression - 75, 0.25 and Multilayer perceptron - 72, 0.27 with respect to accuracy and brier_score in percent. Naive Bayes algorithm out performs with very low false positive rates as well as brier_score and good accuracy. Naive Bayes algorithm classification results in predicting ECG showed very satisfactory results using only diet cum lifestyle factors which will be very helpful for the physicians to educate the patients and public, thereby mortality of gastric cancer can be reduced/avoided with this knowledge mining work.

Keywords: Early Gastric cancer, Machine Learning, Diet, Lifestyle Characteristics

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Authors: Joonas Pääkkönen

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In sports, individuals and teams are typically interested in final rankings. Final results, such as times or distances, dictate these rankings, also known as places. Places can be further associated with ordered random variables, commonly referred to as order statistics. In this work, we introduce a simple, yet accurate order statistical ordinal regression function that predicts relay race places with changeover-times. We call this function the Fenton-Wilkinson Order Statistics model. This model is built on the following educated assumption: individual leg-times follow log-normal distributions. Moreover, our key idea is to utilize Fenton-Wilkinson approximations of changeover-times alongside an estimator for the total number of teams as in the notorious German tank problem. This original place regression function is sigmoidal and thus correctly predicts the existence of a small number of elite teams that significantly outperform the rest of the teams. Our model also describes how place increases linearly with changeover-time at the inflection point of the log-normal distribution function. With real-world data from Jukola 2019, a massive orienteering relay race, the model is shown to be highly accurate even when the size of the training set is only 5% of the whole data set. Numerical results also show that our model exhibits smaller place prediction root-mean-square-errors than linear regression, mord regression and Gaussian process regression.

Keywords: Fenton-Wilkinson approximation, German tank problem, log-normal distribution, order statistics, ordinal regression, orienteering, sports analytics, sports modeling

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Authors: Takuro Kida, Yuichi Kida

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In this paper, it is shown a base of the new trend of algorithm mathematically that treats a historical reason of continuous discrimination in the world as well as its solution by introducing new concepts of parallel world that includes an invisible set of errors as its companion. With respect to a matrix operator-filter bank that the matrix operator-analysis-filter bank H and the matrix operator-sampling-filter bank S are given, firstly, we introduce the detail algorithm to derive the optimum matrix operator-synthesis-filter bank Z that minimizes all the worst-case measures of the matrix operator-error-signals E(ω) = F(ω) − Y(ω) between the matrix operator-input-signals F(ω) and the matrix operator-output-signals Y(ω) of the matrix operator-filter bank at the same time. Further, feedback is introduced to the above approximation theory, and it is indicated that introducing conversations with feedback do not superior automatically to the accumulation of existing knowledge of signal prediction. Secondly, the concept of category in the field of mathematics is applied to the above optimum signal approximation and is indicated that the category-based approximation theory is applied to the set-theoretic consideration of the recognition of humans. Based on this discussion, it is shown naturally why the narrow perception that tends to create isolation shows an apparent advantage in the short term and, often, why such narrow thinking becomes intimate with discriminatory action in a human group. Throughout these considerations, it is presented that, in order to abolish easy and intimate discriminatory behavior, it is important to create a parallel world of conception where we share the set of invisible error signals, including the words and the consciousness of both worlds.

Keywords: matrix filterbank, optimum signal approximation, category theory, simultaneous minimization

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Authors: Novee Lor C. Leyso, Maylin C. Palatino

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Under-five malnutrition continues to persist in the Philippines, particularly in the island Province of Marinduque, with prevalence of some forms of malnutrition even worsening in recent years. Local spatial cluster detection provides a spatial perspective in understanding this phenomenon as key in analyzing patterns of geographic variation, identification of community-appropriate programs and interventions, and focused targeting on high-risk areas. Using data from a province-wide household-based census conducted in 2014–2016, this study aimed to determine and evaluate spatial clusters of under-five malnutrition, across the province and within each municipality at the individual level using household location. Malnutrition was defined as weight-for-age z-score that fall outside the 2 standard deviations from the median of the WHO reference population. The Kulldorff’s elliptical spatial scan statistic in binomial model was used to locate clusters with high-risk of malnutrition, while adjusting for age and membership to government conditional cash transfer program as proxy for socio-economic status. One large significant cluster of under-five malnutrition was found southwest of the province, in which living in these areas at least doubles the risk of malnutrition. Additionally, at least one significant cluster were identified within each municipality—mostly located along the coastal areas. All these indicate apparent geographical variations across and within municipalities in the province. There were also similarities and disparities in the patterns of risk of malnutrition in each cluster across municipalities, and even within municipality, suggesting underlying causes at work that warrants further investigation. Therefore, community-appropriate programs and interventions should be identified and should be focused on high-risk areas to maximize limited government resources. Further studies are also recommended to determine factors affecting variations in childhood malnutrition considering the evidence of spatial clustering found in this study.

Keywords: Binomial model, Kulldorff’s elliptical spatial scan statistic, Philippines, under-five malnutrition

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Authors: Marlene Rosa, Susana Lopes

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There are few studies that explore the potential of board games as a performance measure, despite it can be an interesting strategy in the context of frailty populations. In fact, board games are immersive strategies than can inhibit the pressure of being evaluated. This study aimed to test the ability of gamed-base strategies to assess executive function in elderly population. Sixteen old participants were included: 10 with affected executive functions (G1 – 85.30±6.00 yrs old; 10 male); 6 with executive functions with non-clinical important modifications (G2 - 76.30±5.19 yrs old; 6 male). Executive tests were assessed using the Frontal Assessment Battery (FAB), which is a quick-applicable cognitive screening test (score<12 means impairment). The board game used in this study was the TATI Hand Game, specifically for training rhythmic coordination of the upper limbs with multiple cognitive stimuli. This game features 1 table grid, 1 set of Single Game cards (to play with one hand); Double Game cards (to play simultaneously with two hands); 1 dice to plan Single Game mode; cards to plan the Double Game mode; 1 bell; 2 cups. Each participant played 3 single game cards, and the following data were collected: (i) variability in time during board game challenges (SD); (ii) number of errors; (iii) execution speed (sec). G1 demonstrated: high variability in execution time during board game challenges (G1 – 13.0s vs G2- 0.5s); a higher number of errors (1.40 vs 0.67); higher execution velocity (607.80s vs 281.83s). These results demonstrated the potential of implementing board games as a functional assessment strategy in geriatric care. Future studies might include larger samples and statistical methodologies to find cut-off values for impairment in executive functions during performance in TATI game.

Keywords: board game, aging, executive function, evaluation

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Authors: Ileen Van den Berg, Reinier J. Daals, Chris E. M. Heuberger, Sven P. Hildering, Bob E. Van Maris, Carla M. Smulders, Rafael Aránguiz

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Chile is located along the subduction zone of the Nazca plate beneath the South American plate, where large earthquakes and tsunamis have taken place throughout history. The last significant earthquake (Mw 8.2) occurred in September 2015 and generated a destructive tsunami, which mainly affected the city of Coquimbo (71.33°W, 29.96°S). The inundation area consisted of a beach, damaged seawall, damaged railway, wetland and old neighborhood; therefore, local authorities started a reconstruction process immediately after the event. Moreover, a seismic gap has been identified in the same area, and another large event could take place in the near future. The present work proposed an integrated tsunami reconstruction plan for the city of Coquimbo that considered several variables such as safety, nature & recreation, neighborhood welfare, visual obstruction, infrastructure, construction process, and durability & maintenance. Possible future tsunami scenarios are simulated by means of the Non-hydrostatic Evolution of Ocean WAVEs (NEOWAVE) model with 5 nested grids and a higher grid resolution of ~10 m. Based on the score from a multi-criteria analysis, the costs of the alternatives and a preference for a multifunctional solution, the alternative that includes an elevated coastal road with floodgates to reduce tsunami overtopping and control the return flow of a tsunami was selected as the best solution. It was also observed that the wetlands are significantly restored to their former configuration; moreover, the dynamic behavior of the wetlands is stimulated. The numerical simulation showed that the new coastal protection decreases damage and the probability of loss of life by delaying tsunami arrival time. In addition, new evacuation routes and a smaller inundation zone in the city increase safety for the area.

Keywords: tsunami, Coquimbo, Chile, reconstruction, numerical simulation

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Authors: A. Pensiri, K. Nantaporn, P. Parichut

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Tourism is very important to the economy of many countries due to the large contribution in the areas of employment and income generation. However, the rapid growth of tourism can also be considered as one of the major uses of water user, and therefore also have a significant and detrimental impact on the environment. Guest behavior in water usage can be used to manage water in hotels for sustainable water resources management. This research presents a study of hotel guest water usage behavior at two hotels, namely Hotel A (located in Kathu district) and Hotel B (located in Muang district) in Phuket Province, Thailand, as case studies. Primary and secondary data were collected from the hotel manager through interview and questionnaires. The water flow rate was measured in-situ from each water supply device in the standard room type at each hotel, including hand washing faucets, bathroom faucets, shower and toilet flush. For the interview, the majority of respondents (n = 204 for Hotel A and n = 244 for Hotel B) were aged between 21 years and 30 years (53% for Hotel A and 65% for Hotel B) and the majority were foreign (78% in Hotel A, and 92% in Hotel B) from American, France and Austria for purposes of tourism (63% in Hotel A, and 55% in Hotel B). The data showed that water consumption ranged from 188 litres to 507 liters, and 383 litres to 415 litres per overnight guest in Hotel A and Hotel B (n = 244), respectively. These figures exceed the water efficiency benchmark set for Tropical regions by the International Tourism Partnership (ITP). It is recommended that guest water saving initiatives should be implemented at hotels. Moreover, the results showed that guests have high satisfaction for the hotels, the front office service reveal the top rates of average score of 4.35 in Hotel A and 4.20 in Hotel B, respectively, while the luxury decoration and room cleanliness exhibited the second satisfaction scored by the guests in Hotel A and B, respectively. On the basis of this information, the findings can be very useful to improve customer service satisfaction and pay attention to this particular aspect for better hotel management.

Keywords: hotel, tourism, Phuket, water usage

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Authors: Matthew Venunye Fianu, Jerry Fiave, Ebenezer Kye-Mensah, Dacosta Aboagye, Felix Osei-Sarpong

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Introduction: Road traffic accidents involving motorbikes are a priority public health concern in Ghana. While there are local initiatives to address this public health challenge, little is known about motor riders’ knowledge and compliance with road safety regulations (RSR) and their association with RTAs. The aim of this study was, therefore, to assess motorbike riders’ knowledge and compliance with RSRs. Methodology: Motorbike riders in Hohoe Municipality were randomly sampled in a cross-sectional study in June 2022. Data were collected from 237 riders using a questionnaire designed in Kobocollect and administered by ten research assistants. A score of 70% or less is considered low for knowledge and compliance. The data were exported into Excel and imported into STATA 17 for analysis. A chi-square test was performed to generate descriptive and inferential statistics to establish the association between independent and dependent variables. Results: All 237 respondents were male, and each of them completed the questionnaire representing a 100% response rate. Participants who had knowledge about speed limit at different segments of the road were 59(24.9%), the use of helmet were 124 (52.3%), and alcohol use were 152 (64.1%). Participants who complied with regulations on speed limits, helmet use, and alcohol use were 108 (45.6%), 179(75.5%), and 168(70.8%), respectively. Riders who had at least junior high school education were 2.43 times more likely to adhere to RSR [cOR =2.43(95%CI= 1.15-6.33) p= 0.023] than those who had less education. Similarly, riders who had high knowledge about RSR were 2.07 times more likely to comply with RSR than those who had less knowledge [AOR= -2.07 (95% CI= 0.34-0.97), p=0.038]. Conclusion: Motor riders in the Hohoe Municipality had low knowledge as well as low compliance with road safety regulations. This could be a contributor to road traffic accidents. It is therefore recommended that road safety regulatory authorities and relevant stakeholders enhance the enforcement of RSR. There should also be country-specific efforts to increase awareness among all motor riders, especially those with less than junior high school education.

Keywords: compliance, motor riders, road safety regulations, road traffic accident

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Authors: Othmane Touri, Sanaa El Filali, El Habib Benlahmar

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Natural Language Processing (NLP) has gained significant attention lately. It has proved its ability to analyze and extract insights from unstructured text data in various languages. It is found that one of the most popular NLP applications is sentiment analysis which aims to identify the sentiment expressed in a piece of text, such as positive, negative, or neutral, in multiple languages. While there are several multilingual NLP models available for sentiment analysis, there is a need to investigate their effectiveness in different contexts and applications. In this study, we aim to investigate the effectiveness of different multilingual NLP models for sentiment analysis on a dataset of online product reviews in multiple languages. The performance of several NLP models, including Google Cloud Natural Language API, Microsoft Azure Cognitive Services, Amazon Comprehend, Stanford CoreNLP, spaCy, and Hugging Face Transformers are being compared. The models based on several metrics, including accuracy, precision, recall, and F1 score, are being evaluated and compared to their performance across different categories of product reviews. In order to run the study, preprocessing of the dataset has been performed by cleaning and tokenizing the text data in multiple languages. Then training and testing each model has been applied using a cross-validation approach where randomly dividing the dataset into training and testing sets and repeating the process multiple times has been used. A grid search approach to optimize the hyperparameters of each model and select the best-performing model for each category of product reviews and language has been applied. The findings of this study provide insights into the effectiveness of different multilingual NLP models for Multilingual Sentiment Analysis and their suitability for different languages and applications. The strengths and limitations of each model were identified, and recommendations for selecting the most performant model based on the specific requirements of a project were provided. This study contributes to the advancement of research methods in multilingual NLP and provides a practical guide for researchers and practitioners in the field.

Keywords: NLP, multilingual, sentiment analysis, texts

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Authors: Bi-Huei Tsai

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This work explores the inter-region investment behaviors of integrated circuit (IC) design industry from Taiwan to China using the amount of foreign direct investment (FDI). According to the mutual dependence among different IC design industrial locations, Lotka-Volterra model is utilized to explore the FDI interactions between South and East China. Effects of inter-regional collaborations on FDI flows into China are considered. Evolutions of FDIs into South China for IC design industry significantly inspire the subsequent FDIs into East China, while FDIs into East China for Taiwan’s IC design industry significantly hinder the subsequent FDIs into South China. The supply chain along IC industry includes IC design, manufacturing, packing and testing enterprises. I C manufacturing, packaging and testing industries depend on IC design industry to gain advanced business benefits. The FDI amount from Taiwan’s IC design industry into East China is the greatest among the four regions: North, East, Mid-West and South China. The FDI amount from Taiwan’s IC design industry into South China is the second largest. If IC design houses buy more equipment and bring more capitals in South China, those in East China will have pressure to undertake more FDIs into East China to maintain the leading position advantages of the supply chain in East China. On the other hand, as the FDIs in East China rise, the FDIs in South China will successively decline since capitals have concentrated in East China. Prediction of Lotka-Volterra model in FDI trends is accurate because the industrial interactions between the two regions are included. Finally, this work confirms that the FDI flows cannot reach a stable equilibrium point, so the FDI inflows into East and South China will expand in the future.

Keywords: Lotka-Volterra model, foreign direct investment, competitive, Equilibrium analysis

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Authors: Theresa Ukamaka Nwagha, Angela Ogechukwu Ugwu, Martins Nweke

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Background and Objectives: Blood transfusion is an effective and proven treatment for some severe complications of sickle cell disease. Recurrent transfusions have put patients with sickle cell disease at risk of developing antibodies against the various antigens they were exposed to. This study aims to investigate the frequency of red blood cell alloimmunization in patients with sickle disease in Africa. Materials and Methods: This is a systematic review of peer-reviewed literature published in English. The review was conducted consistent with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist. Data sources for the review include MEDLINE, PubMed, CINAHL, and Academic Search Complete. Included in this review are articles that reported the frequency/prevalence of red blood cell alloimmunization in sickle cell disease patients in Africa. Eligible studies were subjected to independent full-text screening and data extraction. Risk of bias assessment was conducted with the aid of the mixed method appraisal tool. We employed a random-effects model of meta-analysis to estimate the pooled prevalence. We computed Cochrane’s Q statistics and I2 and prediction interval to quantify heterogeneity in effect size. Results: The prevalence estimates range from 2.6% to 29%. Pooled prevalence was estimated to be 10.4% (CI 7.7.–13.8); PI = 3.0 – 34.0%), with significant heterogeneity (I2 = 84.62; PI = 2.0-32.0%) and publication bias (Egger’s t-test = 1.744, p = 0.0965). Conclusion: The frequency of red cell alloantibody varies considerably in Africa. The alloantibodies appeared frequent in this order: the Rhesus, Kell, Lewis, Duffy, MNS, and Lutheran

Keywords: frequency, red blood cell, alloimmunization, sickle cell disease, Africa

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Authors: Muhammed Ashiq Villanthenkodath, Shreya Pal

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Purpose: This study scrutinizes the impact of economic globalization on ecological footprint while endogenizing economic growth and energy consumption from 1990 to 2018 in India. Design/methodology/approach: The standard unit root test has been employed for time series analysis to unveil the integration order. Then, the cointegration was confirmed using autoregressive distributed lag (ARDL) analysis. Further, the study executed the dynamic ARDL simulation model to estimate long-run and short-run results along with simulation and robotic prediction. Findings: The cointegration analysis confirms the existence of a long-run association among variables. Further, economic globalization reduces the ecological footprint in the long run. Similarly, energy consumption decreases the ecological footprint. In contrast, economic growth spurs the ecological footprint in India. Originality/value: This study contributes to the literature in many ways. First, unlike studies that employ CO2 emissions and globalization nexus, this study employs ecological footprint for measuring environmental quality; since it is the broader measure of environmental quality, it can offer a wide range of climate change mitigation policies for India. Second, the study executes a multivariate framework with updated series from 1990 to 2018 in India to explore the link between EF, economic globalization, energy consumption, and economic growth. Third, the dynamic autoregressive distributed lag (ARDL) model has been used to explore the short and long-run association between the series. Finally, to our limited knowledge, this is the first study that uses economic globalization in the EF function of India amid facing a trade-off between sustainable economic growth and the environment in the era of globalization.

Keywords: economic globalization, ecological footprint, India, dynamic ARDL simulation model

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Authors: E. Karacabey, Ş. G. Özçelik, M. S. Turan, C. Baltacıoğlu, E. Küçüköner

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Main concern about deep-fat-fried food materials is their high final oil contents absorbed during frying process and/or after cooling period, since diet including high content of oil is accepted unhealthy by consumers. Different methods have been evaluated to decrease oil content of fried food stuffs. One promising method is partially drying of food material before frying. In the present study it was aimed to control and decrease the final oil content of zucchini slices by means of partial drying and to optimize process conditions. Conventional oven drying was used to decrease moisture content of zucchini slices at a certain extent. Process performance in terms of oil uptake was evaluated by comparing oil content of predried and then fried zucchini slices with those determined for directly fried ones. For predrying and frying processes, oven temperature and weight loss and frying oil temperature and time pairs were controlled variables, respectively. Zucchini slices were also directly fried for sensory evaluations revealing preferred properties of final product in terms of surface color, moisture content, texture and taste. These properties of directly fried zucchini slices taking the highest score at the end of sensory evaluation were determined and used as targets in optimization procedure. Response surface methodology was used for process optimization. The properties, determined after sensory evaluation, were selected as targets; meanwhile oil content was aimed to be minimized. Results indicated that final oil content of zucchini slices could be reduced from 58% to 46% by controlling conditions of predrying and frying processes. As a result, it was suggested that predrying could be one choose to reduce oil content of fried zucchini slices for health diet. This project (113R015) has been supported by TUBITAK.

Keywords: health process, optimization, response surface methodology, oil uptake, conventional oven

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Authors: Zhongmin Wang, Wudong Fan, Hengshan Zhang, Yimin Zhou

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In data-driven prognostic methods, the prediction accuracy of the estimation for remaining useful life of bearings mainly depends on the performance of health indicators, which are usually fused some statistical features extracted from vibrating signals. However, the existing health indicators have the following two drawbacks: (1) The differnet ranges of the statistical features have the different contributions to construct the health indicators, the expert knowledge is required to extract the features. (2) When convolutional neural networks are utilized to tackle time-frequency features of signals, the time-series of signals are not considered. To overcome these drawbacks, in this study, the method combining convolutional neural network with gated recurrent unit is proposed to extract the time-frequency image features. The extracted features are utilized to construct health indicator and predict remaining useful life of bearings. First, original signals are converted into time-frequency images by using continuous wavelet transform so as to form the original feature sets. Second, with convolutional and pooling layers of convolutional neural networks, the most sensitive features of time-frequency images are selected from the original feature sets. Finally, these selected features are fed into the gated recurrent unit to construct the health indicator. The results state that the proposed method shows the enhance performance than the related studies which have used the same bearing dataset provided by PRONOSTIA.

Keywords: continuous wavelet transform, convolution neural net-work, gated recurrent unit, health indicators, remaining useful life

Procedia PDF Downloads 137

Authors: Sayed Mostafa, Siham Mostafa Mohamed Faheid, Ibrahim Rizk Sayed Ahmed, Yasser Fehry Mohamed Kishk, Gamal Hassan Ragab

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Gluten-free foods are still the only treatment for gluten-allergic patients. Consequently, this study is concerned with improving the quality attributes of gluten-free bread using different concentrations (0, 20, 40, 60 and 80ppm) of all maltogenic α-amylase (MA) and xylanase (XY) compared with wheat flour Balady bread and untreated gluten-free Balady bread (GFBB). Pasting properties, falling number, water activity, alkaline water retention capacity (AWRC) and sensory properties (fresh bread, after 24h, after 48h and after 72h) of gluten-free bread were evaluated. Additionally, the effect of merging different concentrations of maltogenic α-amylase and xylanase on stalling behavior (AWRC) and sensory properties of gluten-free Balady bread was investigated. The addition of MA led to a gradually decreased peak viscosity, breakdown, setback and pasting temperature of GFBB with the increasing level of MA. Maltogenic α-amylase and xylanase addition led to a reduction in the FN values compared to the untreated gluten-free sample, noting that the MA-treated samples showed a significant decrease compared to the XY-treated and untreated samples. Wheat flour Balady bread significantly showed a higher value of AWRC compared to untreated gluten-free Balady bread at different storage periods (zero time, after 24h, after 48h and after 72h). MA-treated samples showed higher water binding capacity and water activity (aw)in comparison with XY-treated samples, with significance during all storage periods. Concerning the overall acceptability during the third day, the highest score (4.6) was observed by the GFBB sample containing 40ppm MA, followed by 4.3, which was investigated by the GFBB sample containing 80ppm XY with no significance between them and with significance compared to the other samples.

Keywords: celiac disease, gluten-free products, anti-stalling agents, maltogenic α-amylase, xylanase

Procedia PDF Downloads 85

Authors: Tugba Bayoglu

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Aerodynamic parameter estimation is very crucial in missile design phase, since accurate high fidelity aerodynamic model is required for designing high performance and robust control system, developing high fidelity flight simulations and verification of computational and wind tunnel test results. However, in literature, there is not enough missile aerodynamic parameter identification study for three main reasons: (1) most air to air missiles cannot fly with constant speed, (2) missile flight test number and flight duration are much less than that of fixed wing aircraft, (3) variation of the missile aerodynamic parameters with respect to Mach number is higher than that of fixed wing aircraft. In addition to these challenges, identification of aerodynamic parameters for high wind angles by using classical estimation techniques brings another difficulty in the estimation process. The reason for this, most of the estimation techniques require employing polynomials or splines to model the behavior of the aerodynamics. However, for the missiles with a large variation of aerodynamic parameters with respect to flight variables, the order of the proposed model increases, which brings computational burden and complexity. Therefore, in this study, it is aimed to solve nonlinear aerodynamic parameter identification problem for a supersonic air to air missile by using Artificial Neural Networks. The method proposed will be tested by using simulated data which will be generated with a six degree of freedom missile model, involving a nonlinear aerodynamic database. The data will be corrupted by adding noise to the measurement model. Then, by using the flight variables and measurements, the parameters will be estimated. Finally, the prediction accuracy will be investigated.

Keywords: air to air missile, artificial neural networks, open loop simulation, parameter identification

Procedia PDF Downloads 281

Authors: Mohammed Saleh Rezk, Reza Kashani

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Auxiliary damping has gained popularity in recent years, especially in structures such as mid- and high-rise buildings. Distributed damping systems (typically viscous and viscoelastic) or reactive damping systems (such as tuned mass dampers) are the two types of damping choices for such structures. Distributed VE dampers are normally configured as braces or damping panels, which are engaged through relatively small movements between the structural members when the structure sways under wind or earthquake loading. In addition to being used as stand-alone dampers in distributed damping applications, VE dampers can also be incorporated into the suspension element of tuned mass dampers (TMDs). In this study, analytical and numerical tools for modeling and design of multilayer viscoelastic damping devices to be used in dampening the vibration of large structures are developed. Considering the limitations of analytical models for the synthesis and analysis of realistic, large, multilayer VE dampers, the emphasis of the study has been on numerical modeling using the finite element method. To verify the finite element models, a two-layer VE damper using ½ inch synthetic viscoelastic urethane polymer was built, tested, and the measured parameters were compared with the numerically predicted ones. The numerical model prediction and experimentally evaluated damping and stiffness of the test VE damper were in very good agreement. The effectiveness of VE dampers in adding auxiliary damping to larger structures is numerically demonstrated by chevron bracing one such damper numerically into the model of a massive frame subject to an abrupt lateral load. A comparison of the responses of the frame to the aforementioned load, without and with the VE damper, clearly shows the efficacy of the damper in lowering the extent of frame vibration.

Keywords: viscoelastic, damper, distributed damping, tuned mass damper

Procedia PDF Downloads 108

Authors: Noha Mohammed Ismael Awad Eladal, Aala Shoukry Emara

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Background: Wound healing after dental implant surgery is critical to the procedure's success. The aim of this study was to explore the effects of rutin+vitamin C supplementation in wound healing following the placement of dental implants. Methodology: There were 20 participants in this randomized controlled clinical trial who needed dental implants to replace missing teeth. Patients were divided into two groups, and group A received dental implants. Group B received dental implants with vitamin C administration. Follow-up appointments were performed on day 3, day 7, and day 14 post-surgery, during which soft tissue healing and pain response scores were evaluated using the visual analog scale. Postoperative digital panoramas were taken immediately after surgery, 3 months and 6 months postoperatively. Changes in bone density along with the bone-implant interface at the mesial, distal and apical sides were assessed using the digora software. Results: An independent t-test was used to compare the means of variables between the two groups. At the same time, repeated measures were employed to compare the means of variables between two groups. ANOVA was used to compare bone density for the same group at different dates. Significant increased differences were observed at the mesial, distal and apical sides Surrounding the implants of both groups per time. However, the rate of increase was significantly higher in group B The mean difference at the mesial side after 6 months was 21.99 ± 5.48 in the group B and 14.21 ± 4.95 in group A, while it read 21.74 ± 3.56 in the group B and 10.78 ± 3.90 in group A at the distal side and was 18.90 ± 5.91 in the group B and 10.39 ± 3.49 group A at the apical side. Significance was recorded at P = 0.004, P = 0.0001, and 0.001 at the mesial, distal and apical sides respectively. The mean pain score and wound healing were significantly higher in group A as compared to group B, respectively. Conclusion: The rutin c + vitamin c group significantly promoted bone healing and speeded up the osseointegration process and improved soft tissue healing.

Keywords: osseointegration, soft tissue, rutin c, dental implant

Procedia PDF Downloads 151

Authors: Manish Madappa, Madhavi Gayathri Raman

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The primary vehicle of human communication is language. A breakdown occurring in any aspect of communication may lead to frustration and isolation among the learners and the teachers. Over seven percent of the population in the world currently experience limitations and those children who exhibit a deviant/deficient language acquisition curve even when being in a language rich environment as their peers may be at risk of having a language disorder or language impairment. The difficulty may be in the word level [vocabulary/word knowledge] and/or the sentence level [syntax/morphology) Children with SLI appear to be developing normally in all aspects except for their receptive and/or expressive language skills. Thus, it is utmost importance to identify children with or at risk of SLI so that an early intervention can foster language and social growth, provide the best possible learning environment with special support for language to be explicitly taught and a step in providing continuous and ongoing support. The present study looks at Kannada English bilingual children and works towards identifying children at risk of “specific language impairment”. The study was conducted through an exploratory study which systematically enquired into the narratives of young Kannada-English bilinguals and to investigate the data for story structure in their narrative formulations. Oral narrative offers a rich source of data about a child’s language use in a relatively natural context. The fundamental objective is to ensure comparability and to be more universal and thus allows for the evaluation narrative text competence. The data was collected from 10 class three students at a primary school in Mysore, Karnataka and analyzed for macrostructure component reflecting the goal directed behavior of a protagonist who is motivated to carry out some kind of action with the intention of attaining a goal. The results show that the children exhibiting a deviation of -1.25 SD are at risk of SLI. Two learners were identified to be at risk of Specific Language Impairment with a standard deviation of more the 1.25 below the mean score.

Keywords: bilingual, oral narratives, SLI, macrostructure

Procedia PDF Downloads 289

Authors: Sara Santos, Cristina Saraiva, Sónia Saraiva

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The objective of this study was to evaluate the welfare of reared broilers using scoring systems at the slaughterhouse. The welfare of broilers from 70 different flocks was assessed in three different slaughterhouses, regarding 373043 animals, although not in equal proportions in each slaughterhouse due to the difference in the amount of flocks slaughtered per day because of different company size. Twenty-one flocks were evaluated in slaughterhouse A (30%), thirty in slaughterhouse B (42,9%) and nineteen in slaughterhouse C (27,1%). The parameters evaluated were feather cleanness, foot pad dermatitis, hock burn, breast burn and causes of carcass condemnation. Feather cleanness was scored into three classes: 0=clean; 1=moderately dirty and 2=dirty feathers. Foot pad dermatitis, hock burn and breast ulcer were graded in three classes: 0=no lesions, 1=moderate lesions and 2=severe lesions. Causes of carcass condemnation were divided into emaciation, ascites, colour alteration and febrile state, arthritis, aerosaculitis, dermatitis, peritonitis, myositis, cellulitis, extensive trauma and technopathies as mechanical trauma, insufficient bleeding and deficient plucking. Broilers evaluated had a body weight ranging between 0,909kg and 2,588kg (median 1,522kg) and age between 25 days and 45 days (median 33 days). Rejection rate of flocks ranged between 0,1% and 10,48% (median 1,4029%) and footpad dermatitis total score between 2 and 197, resulting in 20 flocks presenting moderate lesions and 15 flocks with severe lesions. Moderate hock burn was associated with severe foot pad dermatitis and with breast burn. The associations between these lesions suggest that the development of contact dermatitis is caused by a common cause, the prolonged contact with litter of poor quality. In conclusion, contact dermatitis lesions, mostly foot pad dermatitis, feather hygiene conditions and rejection rate were the main restrictions of good welfare and considered important indicators for the follow-up on the farm conditions.

Keywords: broiler, dermatitis, welfare, slaughterhouse

Procedia PDF Downloads 136

Authors: Milan N. A. Van Der Kuil, Anne M. A. Visser-Meily, Andrea W. M. Evers, Ineke J. M. Van Der Ham

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Navigation ability is essential for autonomy and mobility in daily life. In patients with acquired brain injury, navigation impairment is frequently impaired; however, in this study, we tested the effectiveness of a serious gaming training protocol as a tool for cognitive rehabilitation to reduce navigation impairment. In total, 38 patients with acquired brain injury and subjective navigation complaints completed the experiment, with a partially blind, randomized control trial design. An objective navigation test was used to construct a strengths and weaknesses profile for each patient. Subsequently, patients received personalized compensation training that matched their strengths and weaknesses by addressing an egocentric or allocentric strategy or a strategy aimed at minimizing the use of landmarks. Participants in the experimental condition received psychoeducation and a home-based rehabilitation game with a series of exercises (e.g., map reading, place finding, and turn memorization). The exercises were developed to stimulate the adoption of more beneficial strategies, according to the compensatory approach. Self-reported navigation ability (wayfinding questionnaire), participation level, and objective navigation performance were measured before and after 1 and 4 weeks after completing the six-week training program. Results indicate that the experimental group significantly improved in subjective navigation ability both 1 and 4 weeks after completion of the training, in comparison to the score before training and the scores of the control group. Similarly, goal attainment showed a significant increase after the first and fourth week after training. Objective navigation performance was not affected by the training. This navigation training protocol provides an effective solution to address navigation impairment after acquired brain injury, with clear improvements in subjective performance and goal attainment of the participants. The outcomes of the training should be re-examined after implementation in a clinical setting.

Keywords: spatial navigation, cognitive rehabilitation, serious gaming, acquired brain injury

Procedia PDF Downloads 177

Authors: Adelson G. Guillarte, M. D., Noel J. Belonguel, Jarungchai Anton S. Vatanagul

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Patients with malignant middle cerebral infarction (MCA) (with massive brain swelling and herniation) were reported to have a mortality rate of 80% even with the appropriate conservative medical therapy. European Trials (DECIMAL, DESTINY I, and II, HAMLET) showed significant improvement in mortality and functional outcome with hemicraniectomy. No known published local studies in the region, thus a local study is vital. This is a single center, retrospective, descriptive, cross-sectional, chart review study which includes ≥18 year-old patients with malignant MCA infarction, who underwent hemicraniectomy, and those who were given conservative medical therapy alone, from January 2008 to December 2012 at Perpetual Succour Hospital. Excluded were patients whose charts are with insufficient data, prior MCA stroke, with concomitant intracerebral hemorrhage and with other serious medical conditions or terminal illnesses. Minimum of 32 populations were needed. Data were presented in mean, standard deviation, frequency and percentage distribution. Man n Whitney U test and Chi Square test were used. P-values lesser than 0.05 alpha were considered statistically significant. A total of 672 stroke patients were admitted. 34 patients pass the inclusion criteria. 9 underwent hemicraniectomy and 25 were treated by conservative medical therapy alone. Although not statistically significant (64% vs 33%, p=0.112) there were more patients noted improved in the conservative treatment group. Meanwhile, the Hemicraniectomy group have increased percentage of mortality (67%) (p=0.112). There was a decreasing trend in the average NIHSS score in both groups from admission to post-op 7 days (p=0.198, p=0.78). A bigger multicenter prospective study is recommended to control inherent biases and limitations of a retrospective and smaller study.

Keywords: cerebral infarct, hemicraniectomy, ischemic stroke, malignant middle cerebral artery (MCA) infarct

Procedia PDF Downloads 318