Search results for: statistical machine translation

Authors: Hounyèmè Romuald, Maxime Logez, Mama Daouda, Argillier Christine

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In view of the very strong degradation of aquatic ecosystems, it is urgent to set up monitoring systems that are best able to report on the effects of the stresses they undergo. This is particularly true in developing countries, where specific and relevant quality standards and funding for monitoring programs are lacking. The objective of this study was to make a relevant and objective choice of physicochemical parameters informative of the main stressors occurring on African lakes and to identify their alteration thresholds. Based on statistical analyses of the relationship between several driving forces and the physicochemical parameters of the Nokoué lagoon, relevant Physico-chemical parameters were selected for its monitoring. An innovative method based on Bayesian statistical modeling was used. Eleven Physico-chemical parameters were selected for their response to at least one stressor and their threshold quality standards were also established: Total Phosphorus (<4.5mg/L), Orthophosphates (<0.2mg/L), Nitrates (<0.5 mg/L), TKN (<1.85 mg/L), Dry Organic Matter (<5 mg/L), Dissolved Oxygen (>4 mg/L), BOD (<11.6 mg/L), Salinity (7.6 .), Water Temperature (<28.7 °C), pH (>6.2), and Transparency (>0.9 m). According to the System for the Evaluation of Coastal Water Quality, these thresholds correspond to” good to medium” suitability classes, except for total phosphorus. One of the original features of this study is the use of the bounds of the credibility interval of the fixed-effect coefficients as local weathering standards for the characterization of the Physico-chemical status of this anthropized African ecosystem.

Keywords: driving forces, alteration thresholds, acadjas, monitoring, modeling, human activities

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Authors: Rohit Gupta, Ravinder Agarwal

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Surface electromyographic (sEMG) signal has the potential to identify the human activities and intention. This potential is further exploited to control the artificial limbs using the sEMG signal from residual limbs of amputees. The paper deals with the development of multichannel cost efficient sEMG signal interface for research application, along with evaluation of proposed class dependent statistical approach of the feature selection method. The sEMG signal acquisition interface was developed using ADS1298 of Texas Instruments, which is a front-end interface integrated circuit for ECG application. Further, the sEMG signal is recorded from two lower limb muscles for three locomotions namely: Plane Walk (PW), Stair Ascending (SA), Stair Descending (SD). A class dependent statistical approach is proposed for feature selection and also its performance is compared with 12 preexisting feature vectors. To make the study more extensive, performance of five different types of classifiers are compared. The outcome of the current piece of work proves the suitability of the proposed feature selection algorithm for locomotion recognition, as compared to other existing feature vectors. The SVM Classifier is found as the outperformed classifier among compared classifiers with an average recognition accuracy of 97.40%. Feature vector selection emerges as the most dominant factor affecting the classification performance as it holds 51.51% of the total variance in classification accuracy. The results demonstrate the potentials of the developed sEMG signal acquisition interface along with the proposed feature selection algorithm.

Keywords: classifiers, feature selection, locomotion, sEMG

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Authors: Nazih Ramadan, Manal Mohy-Eldine, Amani Hanoon, Alaa Shehab

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Background and Aims: The study of fingerprints is widely used in providing a clue regarding identity. Age and gender identification from fingerprints is an important step in forensic anthropology in order to minimize the list of suspects search. The aim of this study was to determine finger ridge density and patterns among Egyptians, and to estimate age and gender using ridge densities. Materials and Methods: This study was conducted on 177 randomly-selected healthy Egyptian subjects (90 males and 87 females). They were divided into three age groups; Group (a): from 6-< 12 years, group (b) from 12-< 18 years and group (c) ≥ 18 years. Bilateral digital prints, from every subject, were obtained by the inking procedure. Ridge count per 25 mm² was determined together with assessment of ridge pattern type. Statistical analysis was done with references to different age and sex groups. Results: There was a statistical significant difference in ridge density between the different age groups; where younger ages had significantly higher ridge density than older ages. Females proved to have significantly higher ridge density than males. Also, there was a statistically significant negative correlation between age and ridge density. Ulnar loops were the most frequent pattern among Egyptians then whorls then arches then radial loops. Finally, different regression models were constructed to estimate age and gender from fingerprints ridge density. Conclusion: fingerprint ridge density can be used to identify both age and sex of subjects. Further studies are recommended on different populations, larger samples or using different methods of fingerprint recording and finger ridge counting.

Keywords: age, sex identification, Egyptian population, fingerprints, ridge density

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Authors: Ezayra Dubria, Leonora Yambao

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Mother Tongue–Based Multilingual Education (MTB-MLE) is a salient part of the recent reform in the country’s Education system which is the implementation of the K to 12 Basic Education Program. Its importance is highlighted by the passing of Republic Act 10523, otherwise known as the ‘Enhanced Basic Education Act of 2013’. However, teachers, especially new teachers encounter problems in using mother tongue as medium of instruction. Fortunately, teachers are able to create strategies which address these problems. Specifically, this paper gathered the viewpoints of teachers in using mother tongue and analyzed the different problems and strategies used. The problems encountered by teachers are lack of instructional materials written in mother tongue, especially books, lack of vocabulary, lack of teacher training, and influences of social media to learners. The strategies which address these problems are translation of literary pieces and other instructional materials, vocabulary enrichment through the use of word-of-the-day and picture-word association, remedial class, storytelling, differentiated instruction, explicit teaching, individual and group activities, and utilization of multilingual teaching.

Keywords: mother tongue-based instruction, multilingualism, problems, strategies

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Authors: Mohammad H. Taheri, David J. Brown, Nasser Sherkat

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Engagement is one of the most important factors in determining successful outcomes and deep learning in students. Existing approaches to detect student engagement involve periodic human observations that are subject to inter-rater reliability. Our solution uses real-time multimodal multisensor data labeled by objective performance outcomes to infer the engagement of students. The study involves four students with a combined diagnosis of cerebral palsy and a learning disability who took part in a 3-month trial over 59 sessions. Multimodal multisensor data were collected while they participated in a continuous performance test. Eye gaze, electroencephalogram, body pose, and interaction data were used to create a model of student engagement through objective labeling from the continuous performance test outcomes. In order to achieve this, a type of continuous performance test is introduced, the Seek-X type. Nine features were extracted including high-level handpicked compound features. Using leave-one-out cross-validation, a series of different machine learning approaches were evaluated. Overall, the random forest classification approach achieved the best classification results. Using random forest, 93.3% classification for engagement and 42.9% accuracy for disengagement were achieved. We compared these results to outcomes from different models: AdaBoost, decision tree, k-Nearest Neighbor, naïve Bayes, neural network, and support vector machine. We showed that using a multisensor approach achieved higher accuracy than using features from any reduced set of sensors. We found that using high-level handpicked features can improve the classification accuracy in every sensor mode. Our approach is robust to both sensor fallout and occlusions. The single most important sensor feature to the classification of engagement and distraction was shown to be eye gaze. It has been shown that we can accurately predict the level of engagement of students with learning disabilities in a real-time approach that is not subject to inter-rater reliability, human observation or reliant on a single mode of sensor input. This will help teachers design interventions for a heterogeneous group of students, where teachers cannot possibly attend to each of their individual needs. Our approach can be used to identify those with the greatest learning challenges so that all students are supported to reach their full potential.

Keywords: affective computing in education, affect detection, continuous performance test, engagement, flow, HCI, interaction, learning disabilities, machine learning, multimodal, multisensor, physiological sensors, student engagement

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Authors: Orkide Donma, Mustafa M. Donma

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Obesity may lead to growing serious health problems throughout the world. Vitamin D appears to play a role in cardiovascular and metabolic health. Vitamin D deficiency may add to derangements in human metabolic systems, particularly those of children. Childhood obesity is associated with an increased risk of chronic and sophisticated diseases. The aim of this study is to investigate associations as well as possible differences related to parameters affected by obesity and their relations with vitamin D status in obese (OB) and morbid obese (MO) children. This study included a total of 78 children. Of them, 41 and 37 were OB and MO, respectively. WHO BMI-for age percentiles were used for the classification of obesity. The values above 99 percentile were defined as MO. Those between 95 and 99 percentiles were included into OB group. Anthropometric measurements were recorded. Basal metabolic rates (BMRs) were measured. Vitamin D status is determined by the measurement of 25-hydroxy cholecalciferol [25- hydroxyvitamin D3, 25(OH)D] using high-performance liquid chromatography. Vitamin D status was evaluated as deficient, insufficient and sufficient. Values < 20.0 ng/ml, values between 20-30 ng/ml and values > 30.0 ng/ml were defined as vitamin D deficient, insufficient and sufficient, respectively. Optimal 25(OH)D level was defined as ≥ 30 ng/ml. SPSSx statistical package program was used for the evaluation of the data. The statistical significance degree was accepted as p < 0.05. Mean ages did not differ between the groups. Significantly increased body mass index (BMI), waist circumference (C) and neck C as well as significantly decreased fasting blood glucose (FBG) and vitamin D values were observed in MO group (p < 0.05). In OB group, 37.5% of the children were vitamin D deficient, and in MO group the corresponding value was 53.6%. No difference between the groups in terms of lipid profile, systolic blood pressure (SBP), diastolic blood pressure (DBP) and insulin values was noted. There was a severe statistical significance between FBG values of the groups (p < 0.001). Important correlations between BMI, waist C, hip C, neck C and both SBP as well as DBP were found in OB group. In MO group, correlations only with SBP were obtained. In a similar manner, in OB group, correlations were detected between SBP-BMR and DBP-BMR. However, in MO children, BMR correlated only with SBP. The associations of vitamin D with anthropometric indices as well as some lipid parameters were defined. In OB group BMI, waist C, hip C and triglycerides (TRG) were negatively correlated with vitamin D concentrations whereas none of them were detected in MO group. Vitamin D deficiency may contribute to the complications associated with childhood obesity. Loss of correlations between obesity indices-DBP, vitamin D-TRG, as well as relatively lower FBG values, observed in MO group point out that the emergence of MetS components starts during obesity state just before the transition to morbid obesity. Aside from its deficiency state, associations of vitamin D with anthropometric measurements, blood pressures and TRG should also be evaluated before the development of morbid obesity.

Keywords: children, morbid obesity, obesity, vitamin D

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Authors: Lemoussi Somia, Ouali Mohammed, Zemirline Adel

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In precision engineering, including precision positioning, micro-manipulation, robotic systems... a majority of these applications actuated by piezo stack used the compliant amplifier mechanism to amplifying motion and guiding it as needed utilize the flexibility of their components, in this paper, we present a novel approach introducing a symmetric structure comprising three stages, featuring rectangular flexure hinges with a compact size of 77mm×42mm×10mm. This design provides the capability for rotation, translation or a combination of both movements in both directions. The system allows for a displacement of 2107.5 μm when the input displacement of PZT is 50 μm while considering the material constraints of the aluminum alloy (7075 T6) which has a maximum admissible stress of 500 MPa However, our proposed design imposes additional constraints to ensure the stress remains below 361 MPa for optimal performance. These findings were obtained through finite element simulations conducted using ANSYS Workbench. Furthermore, our module facilitates precise control of various components within robotic systems, allowing for adjustable speeds based on specific requirements or desired outcomes.

Keywords: robotic, piezoelectric, compliant mechanism, flexure hinge

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Authors: Uraib Sharaha, Ahmad Salman, Eladio Rodriguez-Diaz, Elad Shufan, Klaris Riesenberg, Irving J. Bigio, Mahmoud Huleihel

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Antimicrobial drugs have an important role in controlling illness associated with infectious diseases in animals and humans. However, the increasing resistance of bacteria to a broad spectrum of commonly used antibiotics has become a global health-care problem. Rapid determination of antimicrobial susceptibility of a clinical isolate is often crucial for the optimal antimicrobial therapy of infected patients and in many cases can save lives. The conventional methods for susceptibility testing like disk diffusion are time-consuming and other method including E-test, genotyping are relatively expensive. Fourier transform infrared (FTIR) microscopy is rapid, safe, and low cost method that was widely and successfully used in different studies for the identification of various biological samples including bacteria. The new modern infrared (IR) spectrometers with high spectral resolution enable measuring unprecedented biochemical information from cells at the molecular level. Moreover, the development of new bioinformatics analyses combined with IR spectroscopy becomes a powerful technique, which enables the detection of structural changes associated with resistivity. The main goal of this study is to evaluate the potential of the FTIR microscopy in tandem with machine learning algorithms for rapid and reliable identification of bacterial susceptibility to antibiotics in time span of few minutes. The bacterial samples, which were identified at the species level by MALDI-TOF and examined for their susceptibility by the routine assay (micro-diffusion discs), are obtained from the bacteriology laboratories in Soroka University Medical Center (SUMC). These samples were examined by FTIR microscopy and analyzed by advanced statistical methods. Our results, based on 550 E.coli samples, were promising and showed that by using infrared spectroscopic technique together with multivariate analysis, it is possible to classify the tested bacteria into sensitive and resistant with success rate higher than 85% for eight different antibiotics. Based on these preliminary results, it is worthwhile to continue developing the FTIR microscopy technique as a rapid and reliable method for identification antibiotic susceptibility.

Keywords: antibiotics, E. coli, FTIR, multivariate analysis, susceptibility

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Authors: Mohamed Mamdouh Al-Banna, Warda Youssef Mohamed Morsy, Hanaa Ali El-Feky, Ashraf Hussein Abdelmohsen

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Background: The mechanically ventilated patients need a special nursing care with continuous closed observation. The patients’ body mass index may affect their prognosis or outcomes. Aim of the study: to investigate the relationship between BMI and selected outcomes of critically ill mechanically ventilated patients. Research Design: A descriptive correlational research design was utilized Research questions: a) what is the BMI profile of mechanically ventilated patients admitted to critical care units over a period of six months? b) What is the relationship between body mass index and frequency of organ dysfunction, length of ICU stay, weaning from mechanical ventilation, and the mortality rate among adult critically ill mechanically ventilated patients? Setting: different intensive care units of Cairo University Hospitals. Sample: A convenience sample of 30 mechanically ventilated patients for at least 72 hours. Tools of data collection: Three tools were utilized to collect data pertinent to the current study: tool 1: patients’ sociodemographic and medical data sheet, tool 2: BURNS Wean Assessment Program (BWAP) checklist, tool 3: Sequential organ failure assessment (SOFA score) sheet. Results: The majority of the studied sample (77%) was males, and (26.7 %) of the studied sample were in the age group of 18-28 years old, and (26.7 %) were in the age group of 40-50 years old. Moreover, two thirds (66.7%) of the studied sample were within normal BMI. No significant statistical relationship between BMI category and ICU length of stay or the mortality rate among the studied sample, (X² = 11.31, P value = 0.79), (X² = 0.15, P value = 0.928) respectively. No significant statistical relationship between BMI category and the weaning trials from mechanical ventilation among the studied sample, (X² = 0.15, P value = 0.928). No significant statistical relationship was found between BMI category and the occurrence of organ dysfunction among the studied sample, (X² = 2.54, P value = 0.637). Conclusion: No relationship between the BMI categories and the selected patients’ outcomes (weaning from MV, length of ICU stay, occurrence of organ dysfunction, mortality rate). Recommendations: Replication of this study on a larger sample from different geographical locations in Arab Republic of Egypt, conducting farther studies to assess the effect of the quality of nursing care on the mechanically ventilated patients’ outcomes.

Keywords: mechanical ventilation, body mass index, outcomes of mechanically ventilated patient, organ failure

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Authors: Sonakshi Saxena, Moosath Harishankar Vasudevan

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The current study seeks to investigate the differences in the psychological impact of movies in their original and translated versions. International cinema is exemplar of the success of globalization. The multitude of languages in the global village does not seem to impede the common cinematic goal of filmmakers across linguistic boundaries. To understand, hence, whether the psychological impact of movies, intentional or otherwise, is preserved when the original is translated into a different language, an experimental design was adopted. Multilingual participants in the age group 18-25 years were recruited for the same. A control group and an experimental group were randomly assigned and the psychological impacts of movies were studied under two conditions- a) watching the movie in its original language, and b) watching the movie in its original language as well as translated version. For the second condition, the experimental group was further divided into two groups randomly to balance order effects. The major aspects of psychological impact assessed were emotional impact and attitude towards the movie. The scores were compared for the two groups. It is further discussed whether the experience is salient across language or do languages inherently possess the ability to alter experiences of the audience.

Keywords: experimental design, movies, psychological impact, translation

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Authors: Ewa Rusak, Sebastian Seget, Aleksandra Mroskowiak, Mirosław Partyka, Ewa Samulska, Julia Strózik, Anna Wilk, Przemysława Jarosz-Chobot

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Introduction: Various infections can affect children suffering from Type 1 Diabetes (T1D) because of dysfunctions of the immune system. The urinary tract and urethra of these children can be easily infected areas because of glycosuria. Aim: The microflora assessment of the urethra area of children with newly diagnosed T1D. Methods: The materials of the study were swabs taken prospectively from the urethral area of 63 children at the time of diagnosis of T1D (37 boys), then the results were correlated to the clinical parameters. In the statistical analysis, there were T student, Chi square, and U Mann-Whitney tests used. Results: The mean age was 9.4 years (6 months-17.4 years). The mean HbA1c value was 12.1% (5,6% - 20.1%). The mean value of glycosuria was 4463.2 mg/dl (0 - 9770 mg/dl). Ketoacidosis was diagnosed in 29 children (49%). The following microbial species were isolated in the collected materials: Staphylococcus epidermidis in 18 children (28.6%), Enterococcus faecalis in 17 children (27%), Candida albicans in 15 children (23.8%), coagulase-negative staphylococciin 11 children (17.5%), group B Streptococcus beta-hemolysis in 10 children (15.9%), S. aureus, E. coli, S. anginosus, C. glucuronolyticum, and A. urinae in 7 children each (11.1%), group B Streptococcus beta-hemolysis and S. hominis in 6 children each (9.5%), L. gasseri in 5 children (7.5%), C. dubliniensis in 4 children (6.3) and other, isolated cases. 2 of diagnosed patients were cultured negatively (3.2%). There were statistical correlations between the type of colonisation and patients’ sex and HbA1C value. Conclusions: It is extremely important to examine the urethral area at the time of diagnosis of T1D in order to detect inflammation and to undertake the appropriate and effective intervention.

Keywords: diabetology, skin disorders, microbiology, microflora

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Authors: Kewei Fan, Sihong Liu, Yi Pik Cheng

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This paper aims to analyse the failure behaviour of the retaining wall constructed with soil bags that are formed by filling river sand into woven bags (geosynthetics). Model tests were conducted to obtain the failure mode of the wall, and shear tests on two-layers and five-layers of soil bags were designed to investigate the mechanical characteristics of the interface of soil bags. The test results show that the slip surface in the soil bags-constructed retaining wall is ladder-like due to the inter-layer insertion of soil bags, and the wall above the ladder-like surface undergoes a rigid body translation. The insertion strengthens the shear strength of two-layer staggered-stacked soil bags. Meanwhile, it affects the shape of the slip surface of the five-layer staggered-stacked soil bags. Finally, the interlayer resisting friction of soil bags is found to be related to the shape of the slip surface.

Keywords: geosynthetics, retaining wall, soil bag, failure mode, interface, shear strength

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Authors: Junichiro Kawaguchi

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Space debris problems have emerged and threatened the use of low earth orbit around the Earth owing to a large number of spacecraft. In debris removal, a number of research and patents have been proposed and published so far. They assume servicing spacecraft, robots to be built for accessing the target debris objects. The robots should be sophisticated enough automatically to access the debris articulating the attitude and the translation motion with respect to the debris. This paper presents the idea of using the torpedo-like third unsophisticated and disposable body, in addition to the first body of the servicing robot and the second body of the target debris. The third body is launched from the first body from a distance farer than the size of the second body. This paper presents the method and the system, so that the third body is launched from the first body. The third body carries both a net and an inflatable or extendible drag deceleration device and is built small and light. This method enables even a micro to nano satellite to perform contactless and multiple debris removal even via a single flight.

Keywords: ballute, debris removal, echo satellite, gossamer, gun-net, inflatable space structure, small satellite, un-cooperated target

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Authors: Minghui Zhang, Sirine Fkaier, Sabri Fernana, Svetlana Kiseleva, Denis Kiselev

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The real-time identification of bacteria and fungi is difficult because they emit much weaker signals than pollen. In 2020, Plair developed Rapid-E+, which extends abilities of Rapid-E to detect smaller bioaerosols such as bacteria and fungal spores with diameters down to 0.3 µm, while keeping the similar or even better capability for measurements of large bioaerosols like pollen. Rapid-E+ enables simultaneous measurements of (1) time-resolved, polarization and angle dependent Mie scattering patterns, (2) fluorescence spectra resolved in 16 channels, and (3) fluorescence lifetime of individual particles. Moreover, (4) it provides 2D Mie scattering images which give the full information on particle morphology. The parameters of every single bioaerosol aspired into the instrument are subsequently analysed by machine learning. Firstly, pure species of microbes, e.g., Bacillus subtilis (a species of bacteria), and Penicillium chrysogenum (a species of fungal spores), were aerosolized in a bioaerosol chamber for Rapid-E+ training. Afterwards, we tested microbes under different concentrations. We used several steps of data analysis to classify and identify microbes. All single particles were analysed by the parameters of light scattering and fluorescence in the following steps. (1) They were treated with a smart filter block to get rid of non-microbes. (2) By classification algorithm, we verified the filtered particles were microbes based on the calibration data. (3) The probability threshold (defined by the user) step provides the probability of being microbes ranging from 0 to 100%. We demonstrate how Rapid-E+ identified simultaneously microbes based on the results of Bacillus subtilis (bacteria) and Penicillium chrysogenum (fungal spores). By using machine learning, Rapid-E+ achieved identification precision of 99% against the background. The further classification suggests the precision of 87% and 89% for Bacillus subtilis and Penicillium chrysogenum, respectively. The developed algorithm was subsequently used to evaluate the performance of microbe classification and quantification in real-time. The bacteria and fungi were aerosolized again in the chamber with different concentrations. Rapid-E+ can classify different types of microbes and then quantify them in real-time. Rapid-E+ enables classifying different types of microbes and quantifying them in real-time. Rapid-E+ can identify pollen down to species with similar or even better performance than the previous version (Rapid-E). Therefore, Rapid-E+ is an all-in-one instrument which classifies and quantifies not only pollen, but also bacteria and fungi. Based on the machine learning platform, the user can further develop proprietary algorithms for specific microbes (e.g., virus aerosols) and other aerosols (e.g., combustion-related particles that contain polycyclic aromatic hydrocarbons).

Keywords: bioaerosols, laser-induced fluorescence, Mie-scattering, microorganisms

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Authors: S. Boria

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In the last years, the crashworthiness of an automotive body structure can be improved, since the beginning of the design stage, thanks to the development of specific optimization tools. It is well known how the finite element codes can help the designer to investigate the crashing performance of structures under dynamic impact. Therefore, by coupling nonlinear mathematical programming procedure and statistical techniques with FE simulations, it is possible to optimize the design with reduced number of analytical evaluations. In engineering applications, many optimization methods which are based on statistical techniques and utilize estimated models, called meta-models, are quickly spreading. A meta-model is an approximation of a detailed simulation model based on a dataset of input, identified by the design of experiments (DOE); the number of simulations needed to build it depends on the number of variables. Among the various types of meta-modeling techniques, Kriging method seems to be excellent in accuracy, robustness and efficiency compared to other ones when applied to crashworthiness optimization. Therefore the application of such meta-model was used in this work, in order to improve the structural optimization of a bumper for a racing car in composite material subjected to frontal impact. The specific energy absorption represents the objective function to maximize and the geometrical parameters subjected to some design constraints are the design variables. LS-DYNA codes were interfaced with LS-OPT tool in order to find the optimized solution, through the use of a domain reduction strategy. With the use of the Kriging meta-model the crashworthiness characteristic of the composite bumper was improved.

Keywords: composite material, crashworthiness, finite element analysis, optimization

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Authors: Mehdi Nasr Esfahani, Abdal-Rasool Gholamalian, Abdelfattah A. Dababat

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Wheat, Triticum aestivum L. is one of the most important and strategic crops in the human diet. Several diseases threaten this particular crop. Common root rot disease of wheat by a fungal agent, Bipolaris sorokiniana is one of the important diseases, causing considerable losses worldwide. Resistant sources are the only feasible and effective method of control for managing diseases. In this study, the response of 33 domestic and exotic wheat genotypes, including cultivars and promising lines were screened to B. sorokiniana at greenhouse and field conditions, based on five scoring scale indexes of 0 to 100 severity percentage. The screening was continued on resistant wheat genotypes and repeated several times to confirm the greenhouse and field results. Statistical and cluster analysis of data was performed using SAS and SPSS software, respectively. The results showed that, the response of wheat genotypes to the disease in the greenhouse and field conditions was highly significant. The highest rate of common root rot disease infection, B. sorokiniana in the greenhouse and field, was of CVS. Karkheh and Beck Cross-Roshan with 60.83% and 59.16% disease severity respectively, and the lowest one were in cv. Alvand with 18.33%, followed by cv. Baharan with 19.16% disease severity, with a highly significant difference respectively. The remaining wheat genotypes were located in between these two highest and lowest infected groups to B. sorokiniana significantly. There was a high correlation coefficient between the related statistical groups and cluster analysis.

Keywords: wheat, rot, root, crown, fungus, genotype, resistance

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Authors: Faiza Belbachir, Thibault Schienhinski

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The massive development of online social networks allows users to post and share their opinions on various topics. With this huge volume of opinion, it is interesting to extract and interpret these information for different domains, e.g., product and service benchmarking, politic, system of recommendation. This is why opinion detection is one of the most important research tasks. It consists on differentiating between opinion data and factual data. The difficulty of this task is to determine an approach which returns opinionated document. Generally, there are two approaches used for opinion detection i.e. Lexical based approaches and Machine Learning based approaches. In Lexical based approaches, a dictionary of sentimental words is used, words are associated with weights. The opinion score of document is derived by the occurrence of words from this dictionary. In Machine learning approaches, usually a classifier is trained using a set of annotated document containing sentiment, and features such as n-grams of words, part-of-speech tags, and logical forms. Majority of these works are based on documents text to determine opinion score but dont take into account if these texts are really correct. Thus, it is interesting to exploit other information to improve opinion detection. In our work, we will develop a new way to consider the opinion score. We introduce the notion of trust score. We determine opinionated documents but also if these opinions are really trustable information in relation with topics. For that we use lexical SentiWordNet to calculate opinion and trust scores, we compute different features about users like (numbers of their comments, numbers of their useful comments, Average useful review). After that, we combine opinion score and trust score to obtain a final score. We applied our method to detect trust opinions in TRIPADVISOR collection. Our experimental results report that the combination between opinion score and trust score improves opinion detection.

Keywords: Tripadvisor, opinion detection, SentiWordNet, trust score

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Authors: Nico Rosamilia

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The study evaluates the importance of non-financial disclosure practices for regulators, investors, businesses, and markets. It aims to create a sector-specific set of indicators for environmental, social, and governance (ESG) performances alternative to the ratings of the agencies. The existing literature extensively studies the implementation of ESG rating systems. Conversely, this study has a twofold outcome. Firstly, it should generalize incentive systems and governance policies for ESG and sustainable principles. Therefore, it should contribute to the EU Sustainable Finance Disclosure Regulation. Secondly, it concerns the market and the investors by highlighting successful sustainable investing. Indeed, the study contemplates the effect of ESG adoption practices on corporate value. The research explores the asset pricing angle in order to shed light on the fragmented argument on the finance of ESG. Investors may be misguided about the positive or negative effects of ESG on performances. The paper proposes a different method to evaluate ESG performances. By comparing the results of a traditional econometric approach (Lasso) with a machine learning algorithm (Random Forest), the study establishes a set of indicators for ESG performance. Therefore, the research also empirically contributes to the theoretical strands of literature regarding model selection and variable importance in a finance framework. The algorithms will spit out sector-specific indicators. This set of indicators defines an alternative to the compounded scores of ESG rating agencies and avoids the possible offsetting effect of scores. With this approach, the paper defines a sector-specific set of indicators to standardize ESG disclosure. Additionally, it tries to shed light on the absence of a clear understanding of the direction of the ESG effect on corporate value (the problem of endogeneity).

Keywords: ESG ratings, non-financial information, value of firms, sustainable finance

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Authors: Hyunsun Lee, Yi Zhu

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Wireless ad-hoc network is a decentralized type of temporary machine-to-machine connection that is spontaneous or impromptu so that it does not rely on any fixed infrastructure and centralized administration. As unmanned aerial vehicles (UAVs), also called drones, have recently become more accessible and widely utilized in military and civilian domains such as surveillance, search and detection missions, traffic monitoring, remote filming, product delivery, to name a few. The communication between these UAVs become possible and materialized through Flying Ad-hoc Networks (FANETs). However, due to the high mobility of UAVs that may cause different types of transmission interference, it is vital to design robust routing protocols for FANETs. In this talk, the multicast routing method based on a modified stochastic branching process is proposed. The stochastic branching process is often used to describe an early stage of an infectious disease outbreak, and the reproductive number in the process is used to classify the outbreak into a major or minor outbreak. The reproductive number to regulate the local transmission rate is adapted and modified for flying ad-hoc network communication. The performance of the proposed routing method is compared with other well-known methods such as flooding method and gossip method based on three measures; average reachability, average node usage and average branching factor. The proposed routing method achieves average reachability very closer to flooding method, average node usage closer to gossip method, and outstanding average branching factor among methods. It can be concluded that the proposed multicast routing scheme is more efficient than well-known routing schemes such as flooding and gossip while it maintains high performance.

Keywords: Flying Ad-hoc Networks, Multicast Routing, Stochastic Branching Process, Unmanned Aerial Vehicles

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Authors: Oum Elkhir Mahmoudi, Nebiha Ben Haj Ali

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Micropaleontological, sedimentological and statistical studies were carried out on the late Paleoceneearly Eocene succession of Sra Ouertaine and Dyr El Kef in Northern open phosphatic Basin of Tunisia. Based on the abundance and stratigraphic distribution of planktic foraminiferal species, five planktic zones have been recognized from the base to the top of the phosphatic layers. The El Acarinina sibaiyaensis Zone, the E2 Pseudohastigerina wilcoxensis Zone, the E3 Morozovella marginodentata Zone, the E4 Morozovella formosa Zones and the E5 Morozovella subbotinae Zone. The placement of Paleocene-Eocene boundary (PETM) is just below the base of the phosphatic interval. The ETM-2 event may be detectable in the analyzed biotic record of Sra Ouertaine. Based on benthic assemblages, abundances, cluster and multivariate statistical analyses, two biofacies were recognized for each section. The recognized ecozones are typical of warm and shallow water inner neritic setting (dominance of epifaunal fauna Anomalinoides, Dentalina and Cibicidoides associated with Frondicularia phosphatica, Trochamminoides globigeriniformis and Eponides elevatus). The paleoenvironment is eutrophic (presence of several bolivinitids and verneuilinids). For the Dyr El Kef section and P5 and E2 of Sra Ouertaine section, our records indicate that paleoenvironment is influenced by coastal upwelling without oxygen-deficiency, the paleodepth is estimated to be around 50 m. The paleoecosystem is diversified and balanced with a general tendency to stressed condition. While the upper part of Sra Ouertaine section is more eutrophic, influenced by coastal upwelling with oxygen-deficiency, the paleodepth is estimated to be less than 50 m and the ecosystem is unsettled.

Keywords: Tunisia, early Eocene, foraminifera, chronostratigraphy

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Authors: Ondrej Slach, Jan Machacek, Jan Zenka, Lucie Hyllova, Petr Rumpel

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The aim of the paper is to identify and asses different trajectories of two fashionable urban policies –creative and smart cities– in specific post-socialistic context. Drawing on the case of Czechia, we employ the concept of policy mobility research. More specifically, we employ a discourse analysis in order to identify the so-called 'infrastructure' of both policies (such as principal actors, journals, conferences, events), with the special focus on 'agents of transfer' in a multiscale perspective. The preliminary results indicate faster and more aggressive spatial penetration of smart cities policy compared to creative cities policy in Czechia. Further, it seems that existed translation and implementation of smart cities policy into the national and urban context resulted in deliberated fragmented policy of smart cities in Czechia (pure technocratic view), which might be a threat for the future development of social sustainability, especially in cities that are facing increasing social polarisation. Last but not least, due to the fast spatial penetration of the concept and policies of smart cities, it seems that creative cities policy has almost been crowded out of the Czech urban agenda.

Keywords: policy mobility, smart cities, creative cities, Czechia

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Authors: Reza Johari Fard, Najmeh Cheraghi, Parvin Ehtesham Zadeh, Parviz Asgari

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The aim of this study was to investigate and comparison of the effectiveness of schema mode therapy and emotionally focused couples therapy in attachment styles (secure, avoidant, and anxious) in couples with marital conflict in a quasiexperimental method in a pretest, posttest, and follow up design with a control group. The statistical population of the study included all the couples with marital conflict who visited the Mehrana counseling center in 2019 in Ahvaz, Iran 45 couples were selected by voluntary sampling method and randomly divided into two experimental groups and one control group (15 pairs in each group). The participants completed the Adult Attachment Scale (Hazan and Shaver). The experimental groups underwent schema mode therapy and emotionally focused couples therapy for 12 sessions, but the control group did not receive any intervention. The data were analyzed by the statistical analysis of repeated measures in SPSS-19 software. The results showed that both schema mode therapy and emotionally focused couples therapy are effective in increasing the secure attachment style and reducing avoidant and ambivalent attachment styles in couples with marital conflict. There was no significant difference between the schema mode therapy group and the emotionally focused couple's therapy group in attachment styles. Therefore, it is recommended that therapists and family counselors use these therapies along with other therapeutic interventions to increase secure attachment styles and reduce marital conflicts.

Keywords: schema mode therapy, emotional focused couple therapy, attachment styles, marital conflict

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Authors: Muhammad Cheema, Tahir Shah, Subhash Anand

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The cost of making apparel fabrics for garment manufacturing is very high because of their conventional manufacturing processes and new methods/processes are being constantly developed for making fabrics by unconventional methods. With the advancements in technology and the availability of the innovative fibres, durable nonwoven fabrics by using the hydroentanglement process that can compete with the woven fabrics in terms of their aesthetic and tensile properties are being developed. In the work reported here, the hydroentangled nonwoven fabrics were developed through a hybrid nonwoven manufacturing processes by using fibrillated Tencel® and bi-component (sheath/core) polyethylene/polyester (PE/PET) fibres, in which the initial nonwoven fabrics were prepared by the needle-punching method followed by hydroentanglement process carried out at optimal pressures of 50 to 250bars. The prepared fabrics were characterized according to the British Standards (BS 3356:1990, BS 9237:1995, BS 13934-1:1999) and the attained results were compared with those for a standard plain-weave cotton, polyester woven fabric and commercially available nonwoven fabric (Evolon®). The developed hydroentangled fabrics showed better drape properties owing to their flexural rigidity of 252 mg.cm in the machine direction, while the corresponding commercial hydroentangled fabric displayed a value of 1340 mg.cm in the machine direction. The tensile strength of the developed hydroentangled fabrics showed an approximately 200% increase than the commercial hydroentangled fabrics. Similarly, the developed hydroentangled fabrics showed higher properties in term of air permeability, such as the developed hydroentangled fabric exhibited 448 mm/sec and Evolon fabric exhibited 69 mm/sec at 100 Pa pressure. Thus for apparel fabrics, the work combining the existing methods of nonwoven production, provides additional benefits in terms of cost, time and also helps in reducing the carbon footprint for the apparel fabric manufacture.

Keywords: hydroentanglement, nonwoven apparel, durable nonwoven, wearable nonwoven

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Authors: Aliaa M. El-Borai, Ehab A. Beltagy, Eman E. Gadallah, Samy A. ElAssar

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Bioremediation technology is now used for treatment instead of traditional metal removal methods. A strain was isolated from Marsa Alam, Red sea, Egypt showed high resistance to high lead concentration and was identified by the 16S rRNA gene sequencing technique as Halomonas sp. ES015. Medium optimization was carried out using Plackett-Burman design, and the most significant factors were yeast extract, casamino acid and inoculums size. The optimized media obtained by the statistical design raised the removal efficiency from 84% to 99% from initial concentration 250 ppm of lead. Moreover, Box-Behnken experimental design was applied to study the relationship between yeast extract concentration, casamino acid concentration and inoculums size. The optimized medium increased removal efficiency to 97% from initial concentration 500 ppm of lead. Immobilized Halomonas sp. ES015 cells on sponge cubes, using optimized medium in loop bioremediation column, showed relatively constant lead removal efficiency when reused six successive cycles over the range of time interval. Also metal removal efficiency was not affected by flow rate changes. Finally, the results of this research refer to the possibility of lead bioremediation by free or immobilized cells of Halomonas sp. ES015. Also, bioremediation can be done in batch cultures and semicontinuous cultures using column technology.

Keywords: bioremediation, lead, Box–Behnken, Halomonas sp. ES015, loop bioremediation, Plackett-Burman

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Authors: Bhuyain Mobarok Hossain

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Image classification and localization research is currently an important strategy in the field of computer vision. The evolution and advancement of deep learning and convolutional neural networks (CNN) have greatly improved the capabilities of object detection and image-based classification. Target detection is important to research in the field of computer vision, especially in video surveillance systems. To solve this problem, we will be applying a convolutional neural network of multiple scales at multiple locations in the image in one sliding window. Most translation networks move away from the bounding box around the area of interest. In contrast to this architecture, we consider the problem to be a classification problem where each pixel of the image is a separate section. Image classification is the method of predicting an individual category or specifying by a shoal of data points. Image classification is a part of the classification problem, including any labels throughout the image. The image can be classified as a day or night shot. Or, likewise, images of cars and motorbikes will be automatically placed in their collection. The deep learning of image classification generally includes convolutional layers; the invention of it is referred to as a convolutional neural network (CNN).

Keywords: image classification, object detection, localization, particle filter

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Authors: Ndidi F. Amulu, Patrick E. Amulu, Gordian O. Mbah, Callistus N. Ude

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Comparative analysis of the properties of melon seed, coconut fruit and their oil yield were evaluated in this work using standard analytical technique AOAC. The results of the analysis carried out revealed that the moisture contents of the samples studied are 11.15% (melon) and 7.59% (coconut). The crude lipid content are 46.10% (melon) and 55.15% (coconut).The treatment combinations used (leaching time, leaching temperature and solute: solvent ratio) showed significant difference (p < 0.05) in yield between the samples, with melon oil seed flour having a higher percentage range of oil yield (41.30 – 52.90%) and coconut (36.25 – 49.83%). The physical characterization of the extracted oil was also carried out. The values gotten for refractive index are 1.487 (melon seed oil) and 1.361 (coconut oil) and viscosities are 0.008 (melon seed oil) and 0.002 (coconut oil). The chemical analysis of the extracted oils shows acid value of 1.00mg NaOH/g oil (melon oil), 10.050mg NaOH/g oil (coconut oil) and saponification value of 187.00mg/KOH (melon oil) and 183.26mg/KOH (coconut oil). The iodine value of the melon oil gave 75.00mg I2/g and 81.00mg I2/g for coconut oil. A standard statistical package Minitab version 16.0 was used in the regression analysis and analysis of variance (ANOVA). The statistical software mentioned above was also used to optimize the leaching process. Both samples gave high oil yield at the same optimal conditions. The optimal conditions to obtain highest oil yield ≥ 52% (melon seed) and ≥ 48% (coconut seed) are solute - solvent ratio of 40g/ml, leaching time of 2hours and leaching temperature of 50oC. The two samples studied have potential of yielding oil with melon seed giving the higher yield.

Keywords: Coconut, Melon, Optimization, Processing

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Authors: Mustafa Metin Donma

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Metabolic syndrome (MetS) components are noteworthy among children with obesity and morbid obesity because they point out the cases with MetS, which have the great tendency to severe health problems such as cardiovascular diseases both in childhood and adulthood. In clinical practice, considerable efforts are being observed to bring into the open the striking differences between morbid obese cases and those with MetS findings. The most privileged aspect is concerning cardiometabolic features. The aim of this study was to derive an index which behaves different in children with and without MetS from the cardiac point of view. For the purpose, aspartate transaminase (AST), a cardiac enzyme still being used independently to predict cardiac-related problems, was used. One hundred and twenty four children were recruited from the outpatient clinic of Department of Pediatrics in Tekirdag Namik Kemal University, Faculty of Medicine. Forty-three children with normal body mass index, forty-one and forty morbid obese (MO) children with MetS and without the characteristic features of MetS, respectively, were included in the study. Weight, height, waist circumference (WC), hip C (HC), head C (HdC), neck C (NC), systolic and diastolic blood pressure values were measured and recorded. Body mass index and anthropometric ratios were calculated. Fasting blood glucose (FBG), insulin (INS), triglycerides (TRG), high density lipoprotein cholesterol (HDL-C) analyses were performed. The values for AST, alanin transaminase (ALT) and AST/ALT were obtained. Advanced Donma cardiac index (ADCI) values were calculated. The formula for the index was [(TRG/HDL-C) * (INS/FBG)] * [(WC+HC)/Height] * [(HdC+NC)/Height]. Statistical evaluations including correlation analysis were done by a statistical package program. The statistical significance degree was accepted as p<0.05. The index, ADCI, was developed from both anthropometric and biochemical parameters. All anthropometric measurements except weight were included in the equation. Besides all biochemical parameters concerning MetS components were also added. This index was tested in each of three groups. Its performance was compared with the performance of cardiometabolic index (CMI). It was also checked whether it was compatible with AST activity. The performance of ADCI was better than that of CMI. Instead of double increase, the increase of three times was observed in children with MetS compared to MO children. The index was correlated with AST in MO group and with AST/ALT in MetS group. In conclusion, this index was superior in discovering cardiac problems in MO and in diagnosing MetS in MetS groups. It was also arbiter to point out cardiovascular and MetS aspects among the groups.

Keywords: aspartate transaminase, cardiac, children, index, obesity

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Authors: Sung Yong Kim, Byung Joo Song

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Background: Circulating 25-hydroxyvitamin D (25(OH)D) levels has been considered to be inversely related to breast cancer development, recurrence risk, and mortality. Mean vitamin D levels in Korean population is lower than western countries due to higher incidence of lactose intolerance and lower exposure to sunlight. The purpose of this study was to assess incidence of 25(OH)D deficiency at diagnosis and after adjuvant chemotherapy and to investigate the correlation serum 25(OH)D levels with clinicopathologic features. Methods: From December 2011 to October 2012, 280 breast cancer patients seen at a single tertiary cancer center were enrolled. Serum 25(OH)D was measured at the time of surgery and after completion of adjuvant chemotherapy. Statistical analyses used chi-square test, Fisher's exact test, t-test, and ANOVA. Results: Mean serum 25(OH)D was 18.5 ng/ml. The 25(OH)D levels were deficient (<20 ng/ml) in 190 patients (67.9%), insufficient (20-29 ng/ml) in 51 patients(18.2%), and sufficient (30-150 ng/ml) in 39 patients(13.9%). A notable decrease in 25(OH)D concentration was observed(p<0.001) after chemotherapy but was not related to chemotherapy regimens. It was found significant lower 25(OH)D levels at winter season(from October to March, p=0.030). Subjects with invasive carcinoma (IDC or ILC) had significantly lower circulating levels of 25(OH)D than those with ductal carcinoma in situ(DCIS) (p=0.010). Patients with larger tumor size tends to have lower serum 25(OH)D but there were no statistical significance. Conclusions: Most of the breast cancer patients showed deficient or insufficient serum 25(OH)D concentration. Incidence of vitamin D deficiency was higher in invasive carcinoma than DCIS. Serum 25(OH)D levels were decreased after chemotherapy. Consideration should be given to the supplement of vitamin D to those patients.

Keywords: breast neoplasms, vitamin D, Korean population, breast cancer

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Authors: Milan Joshi, Harsh Agrawal, Pallaw Mishra, Sanand Sule

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Predicting electricity usage is a crucial aspect of organizing and controlling sustainable energy systems. The task of forecasting electricity load is intricate and requires a lot of effort due to the combined impact of social, economic, technical, environmental, and cultural factors on power consumption in communities. As a result, it is important to create strong models that can handle the significant non-linear and complex nature of the task. The objective of this study is to create and compare three machine learning techniques for predicting electricity load for both the day ahead and intraday, taking into account various factors such as meteorological data and social events including holidays and festivals. The proposed methods include a LightGBM, FBProphet, combination of FBProphet and LightGBM for day ahead and Motifs( Stumpy) based on Mueens algorithm for similarity search for intraday. We utilize these techniques to predict electricity usage during normal days and social events in the Himachal Region. We then assess their performance by measuring the MSE, RMSE, and MAPE values. The outcomes demonstrate that the combination of FBProphet and LightGBM method is the most accurate for day ahead and Motifs for intraday forecasting of electricity usage, surpassing other models in terms of MAPE, RMSE, and MSE. Moreover, the FBProphet - LightGBM approach proves to be highly effective in forecasting electricity load during social events, exhibiting precise day ahead predictions. In summary, our proposed electricity forecasting techniques display excellent performance in predicting electricity usage during normal days and special events in the Himachal Region.

Keywords: feature engineering, FBProphet, LightGBM, MASS, Motifs, MAPE

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Authors: Cristina Diaz, Lucia Perez-Gandarillas, Gonzalo Garcia-Fuentes, Simone Visigalli, Roberto Canziani, Giuseppe Di Florio, Paolo Gronchi

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During their lifetime, industrial machines are often subjected to chemical, mechanical and thermal extreme conditions. In some cases, the loss of efficiency comes from the degradation of the surface as a result of its exposition to abrasive environments that can cause wear. This is a common problem to be solved in industries of diverse nature such as food, paper or concrete industries, among others. For this reason, a good selection of the material is of high importance. In the machine design context, stainless steels such as AISI 304 and 316 are widely used. However, the severity of the external conditions can require additional protection for the steel and sometimes coating solutions are demanded in order to extend the lifespan of these materials. Therefore, the development of effective coatings with high wear resistance is of utmost technological relevance. In this research, bilayer coatings made of Titanium-Tantalum, Titanium-Niobium, Titanium-Hafnium, and Titanium-Zirconium have been developed using magnetron sputtering configuration by PVD (Physical Vapor Deposition) technology. Their tribological behavior has been measured and evaluated under different environmental conditions. Two kinds of steels were used as substrates: AISI 304, AISI 316. For the comparison with these materials, titanium alloy substrate was also employed. Regarding the characterization, wear rate and friction coefficient were evaluated by a tribo-tester, using a pin-on-ball configuration with different lubricants such as tomato sauce, wine, olive oil, wet compost, a mix of sand and concrete with water and NaCl to approximate the results to real extreme conditions. In addition, topographical images of the wear tracks were obtained in order to get more insight of the wear behavior and scanning electron microscope (SEM) images were taken to evaluate the adhesion and quality of the coating. The characterization was completed with the measurement of nanoindentation hardness and elastic modulus. Concerning the results, thicknesses of the samples varied from 100 nm (Ti-Zr layer) to 1.4 µm (Ti-Hf layer) and SEM images confirmed that the addition of the Ti layer improved the adhesion of the coatings. Moreover, results have pointed out that these coatings have increased the wear resistance in comparison with the original substrates under environments of different severity. Furthermore, nanoindentation hardness results showed an improvement of the elastic strain to failure and a high modulus of elasticity (approximately 200 GPa). As a conclusion, Ti-Ta, Ti-Zr, Ti-Nb, and Ti-Hf are very promising and effective coatings in terms of tribological behavior, improving considerably the wear resistance and friction coefficient of typically used machine materials.

Keywords: coating, stainless steel, tribology, wear

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