Search results for: film scores

Authors: Jay Ananth

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The drug discovery process currently requires numerous years of clinical testing as well as money just for a single drug to earn FDA approval. For drugs that even make it this far in the process, there is a very slim chance of receiving FDA approval, resulting in detrimental hurdles to drug accessibility. To minimize these inefficiencies, numerous studies have implemented computational methods, although few computational investigations have focused on a crucial feature of drugs: lipophilicity. Lipophilicity is a physical attribute of a compound that measures its solubility in lipids and is a determinant of drug efficacy. This project leverages Artificial Intelligence to predict the impact of a drug’s lipophilicity on its performance by accounting for factors such as binding affinity and toxicity. The model predicted lipophilicity and binding affinity in the validation set with very high R² scores of 0.921 and 0.788, respectively, while also being applicable to a variety of target receptors. The results expressed a strong positive correlation between lipophilicity and both binding affinity and toxicity. The model helps in both drug development and discovery, providing every pharmaceutical company with recommended lipophilicity levels for drug candidates as well as a rapid assessment of early-stage drugs prior to any testing, eliminating significant amounts of time and resources currently restricting drug accessibility.

Keywords: drug discovery, lipophilicity, ligand-receptor interactions, machine learning, drug development

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Authors: Ashkan Forootan, Reza Rashedi

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Polyethylene has wide usage areas such as blow molding, pipe, film, cable insulation. However, regardless to its growing applications, it has some constraints such as the limited 70C operating temperature. Polyethylene thermo setting procedure whose molecules are knotted and 3D-molecular-network formed , is developed to conquer the above problem and to raise the applicable temperature of the polymer. This paper reports the cross-linking for two different molecular weight grades of LLDPE by adding 0.5, 1, and 2% of DCP (Dicumyl Peroxide). DCP was chosen for its prevalence among various cross-linking agents. Structural parameters such as molecular weight, melt flow index, comonomer, number of branches,etc. were obtained through the use of relative tests as Gel Permeation Chromatography and Fourier Transform Infra Red spectrometer. After calculating the percentage of gel content, properties of the pure and cross-linked samples were compared by thermal and mechanical analysis with DMTA and FTIR and the effects of cross-linking like viscous and elastic modulus were discussed by using various structural paprameters such as MFI, molecular weight, short chain branches, etc. Studies showed that cross-linked polymer, unlike the pure one, had a solid state with thermal mechanical properties in the range of 110 to 120C and this helped overcome the problem of using polyethylene in temperatures near the melting point.

Keywords: LLDPE, cross-link, structural parameters, DCP, DMTA, GPC

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Authors: Yu-Chen Luo, Wan-Tzu Yen, I-Ping Liu, Po-Hsuan Yeh, Yuh-Lang Lee

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The use of a Pt electrode leads to high catalytic efficiency in the ethanol electro-oxidation. However, the carbon monoxide (CO) released in the reaction will poison the Pt surfaces, lowering the electrocatalytic activity. In this study, composite electrodes are prepared to overcome the poisoning issue, and the related electro-oxidation behaviors are studied by surface-enhanced infrared absorption spectroscopy (SEIRAS) and cyclic voltammetry (CV). An electroless plating method is utilized to deposit Pt catalytic layers on the Pd film-coated FTO substrates. According to the SEIRAS spectra, the carbon dioxide signal of the Pt/Pd composite electrode is larger than that of the Pt one, whereas the CO signal of the composite electrode is relatively smaller. This result suggests that the studied Pt/Pd electrode has a better ability against CO poisoning. The CV analyses are conducted in alkaline environments, and current densities related to the ethanol oxidation in the forward scan (If) and to the CO poisoning in the backward scan (Ib) are measured. A higher ratio of If to Ib (If/Ib) usually represents a better ability against the poisoning effect. The If/Ib values are 2.53 and 2.07 for the Pt and Pt/Pd electrodes, respectively, which is possibly attributed to the increasing ability of CO adsorption of Pt electrode. Despite the lower If/Ib, the Pt/Pd composite electrode shows a higher ethanol oxidation performance in the alkaline system than the Pt does. Furthermore, its stability is also superior.

Keywords: cyclic voltammogram, electroless deposition, ethanol electro-oxidation, surface-enhanced infrared absorption spectroscopy

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Authors: Jiyaul Haque, Vandana Srivastava, M. A. Quraishi

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The amino acids based corrosion inhibitors 2-(3-(carboxymethyl)-1H-imidazol-3-ium-1-yl) acetate (Z-1),2-(3-(1-carboxyethyl)-1H-imidazol-3-ium-1-yl) propanoate (Z-2) and 2-(3-(1-carboxy-2-phenylethyl)-1H-imidazol-3-ium-1-yl)-3- phenylpropanoate (Z-3) were synthesized by the reaction of amino acids, glyoxal and formaldehyde, and characterized by the FTIR and NMR spectroscopy. The corrosion inhibition performance of synthesized inhibitors was studied by electrochemical (EIS and PDP), surface and DFT methods. The results show, the studied Z-1, Z-2 and Z-3 are effective inhibitors, showed the maximum inhibition efficiency of 88.52 %, 89.48 and 96.08% at concentration 200ppm, respectively. The results of potentiodynamic polarization (PDP) study showed that Z-1 act as a cathodic inhibitor, while Z-2 and Z-3 act as mixed type inhibitors. The results of electrochemical impedance spectroscopy (EIS) studies showed that zwitterions inhibit the corrosion through adsorption mechanism. The adsorption of synthesized zwitterions on the mild steel surface was followed the Langmuir adsorption isotherm. The formation of zwitterions film on mild steel surface was confirmed by the scanning electron microscope (SEM) and energy-dispersive X-ray spectroscopy (EDX). The quantum chemical parameters were used to study the reactivity of inhibitors and supported the experimental results. An inhibitor adsorption model is proposed.

Keywords: electrochemical impedance spectroscopy, green corrosion inhibitors, mild steel, SEM, quantum chemical calculation, zwitterions

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Authors: Aye Pa Pa Myo

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Writing in English is accounted as a complex process for English as a foreign language learners. Besides, committing errors in writing can be found as an inevitable part of language learners’ writing. Generally, academic writing is quite difficult for most of the students to manage for getting better scores. Students can commit common errors in their writings when they try to write academic writing. Error analysis deals with identifying and detecting the errors and also explains the reason for the occurrence of these errors. In this paper, the researcher has an attempt to examine the common errors of undergraduate students in their academic writings at Pathein University. The purpose of doing this research is to investigate the errors which students usually commit in academic writing and to find out the better ways for correcting these errors in EFL classrooms. In this research, fifty-third-year non-English specialization students attending Pathein University were selected as participants. This research took one month. It was conducted with a mixed methodology method. Two mini-tests were used as research tools. Data were collected with a quantitative research method. Findings from this research pointed that most of the students noticed their common errors after getting the necessary input, and they became more decreased committing these errors after taking mini-test; hence, all findings will be supportive for further researches related to error analysis in academic writing.

Keywords: academic writing, error analysis, EFL learners, mini-tests, mixed methodology

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Authors: Fatimah Al-Hayazi, Ehteram. A. Noor, Aisha H. Moubaraki

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The inhibitive effect of Securigera securidaca seed extract (SSE) on mild steel corrosion in 1 M HCl solution has been studied by weight loss and electrochemical techniques at four different temperatures. All techniques studied provided data that the studied extract does well at all temperatures, and its inhibitory action increases with increasing its concentration. SEM images indicate thin-film formation on mild steel when corroded in solutions containing 1 g L-1 of inhibitor either at low or high temperatures. The polarization studies showed that SSE acts as an anodic inhibitor. Both polarization and impedance techniques show an acceleration behaviour for SSE at concentrations ≤ 0.1 g L-1 at all temperatures. At concentrations ≥ 0.1 g L-1, the efficiency of SSE is dramatically increased with increasing concentration, and its value does not change appreciably with increasing temperature. It was found that all adsorption data obeyed Temkin adsorption isotherm. Kinetic activation and thermodynamic adsorption parameters are evaluated and discussed. The results revealed an endothermic corrosion process with an associative activation mechanism, while a comprehensive adsorption mechanism for SSE on mild steel surfaces is suggested, in which both physical and chemical adsorption are involved in the adsorption process. A good correlation between inhibitor constituents and their inhibitory action was obtained.

Keywords: corrosion, inhibition of steel, hydrochloric acid, thermodynamic study

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Authors: Tianyu Chen

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The No Child Left Behind Act (NCLB) of 2001 was a major federal education policy that aimed to improve academic outcomes for all students in the United States. This study examines whether NCLB improved college readiness, measured by access to higher education, for different demographic groups. Using data from the Integrated Public Use Microdata Series (IPUMS) from 2003-2008, regression analyses explore the relationship between gender, race, family income, and region with occupational education score. The results indicate that NCLB implementation had a positive effect on college access for women and Asian students compared to other groups. Higher family income was also associated with an increased likelihood of pursuing higher education, especially for families in the South. While NCLB intended to close achievement gaps, disparities in college readiness remained five years after implementation. Further research could examine longer-term trends and additional factors influencing the policy's effectiveness across student subgroups. This study provides evidence that simply holding schools accountable for test scores may not sufficiently improve equitable educational outcomes. More targeted support of disadvantaged groups may be needed to fulfill the goal of "no child left behind."

Keywords: no child left behind act, college readiness, achievement gaps, educational equity

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Authors: B. Pavan Kumar Reddy, P. Michael Preetam Raj, Souri Banerjee, Souvik Kundu

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In this work, the fabrication and characterization of copper-doped zinc oxide (Cu:ZnO) based memristor devices with aluminum (Al) and indium tin oxide (ITO) metal electrodes are reported. The thin films of Cu:ZnO was synthesized using low-cost and low-temperature chemical process. The Cu:ZnO was then deposited onto ITO bottom electrodes using spin-coater technique, whereas the top electrode Al was deposited utilizing physical vapor evaporation technique. Ellipsometer was employed in order to measure the Cu:ZnO thickness and it was found to be 50 nm. Several surface and materials characterization techniques were used to study the thin-film properties of Cu:ZnO. To ascertain the efficacy of Cu:ZnO for memristor applications, electrical characterizations such as current-voltage (I-V), data retention and endurance were obtained, all being the critical parameters for next-generation memory. The I-V characteristic exhibits switching behavior with asymmetrical hysteresis loops. This work imputes the resistance switching to the positional drift of oxygen vacancies associated with respect to the Al/Cu:ZnO junction. Further, a non-linear curve fitting regression techniques were utilized to determine the equivalent circuit for the fabricated Cu:ZnO memristors. Efforts were also devoted in order to establish its potentiality for different electronic applications.

Keywords: copper doped, metal-oxides, oxygen vacancies, resistive switching

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Authors: Woei-Shyan Lee, Yu-Liang Chuang

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The nano-mechanical properties of as-deposited Cu/Si thin films indented to a depth of 2000 nm are investigated using a nanoindentation technique. The nanoindented specimens are annealed at a temperature of either 160 °C or 210°C, respectively. The microstructures of the as-deposited and annealed samples are then examined via transmission electron microscopy (TEM). The results show that both the loading and the unloading regions of the load-displacement curve are smooth and continuous, which suggests that no debonding or cracking occurs during nanoindentation. In addition, the hardness and Young’s modulus of the Cu/Si thin films are found to vary with the nanoindentation depth, and have maximum values of 2.8 GPa and 143 GPa, respectively, at the maximum indentation depth of 2000 nm. The TEM observations show that the region of the Cu/Si film beneath the indenter undergoes a phase transformation during the indentation process. In the case of the as-deposited specimens, the indentation pressure induces a completely amorphous phase within the indentation zone. For the specimens annealed at a temperature of 160°C, the amorphous nature of the microstructure within the indented zone is maintained. However, for the specimens annealed at a higher temperature of 210°C, the indentation affected zone consists of a mixture of amorphous phase and nanocrystalline phase. Copper silicide (η-Cu3Si) precipitates are observed in all of the annealed specimens. The density of the η-Cu3Si precipitates is found to increase with an increasing annealing temperature.

Keywords: nanoindentation, Cu/Si thin films, microstructural evolution, annealing temperature

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Authors: Pandega Gama Mahardika, Muhammad Rifki Al Iksan, Datuk Fachrul Razy

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Oil And Gas Tanker Driver is a high-risk jobdesc. drivers drive with sleep circadian rhythm disturbances. Therefore, FAMOUS (Fatigue Management Online Ultimate System) conducted a diagnostic test on the effectiveness and accuracy of the Psychomotor vigilance test (PVT) in the field to capture the fatigue level of Oil And Gas Tanker Driver. Fatigue examination with the PVP method for 3 minutes using the Pertamina FAMOUS system (Fatigue Management Online Ultimate System). The research sample was Oil And Gas Tanker Driver Elnusa petrofin drivers as many as 2205 people. PVT is categorical data that states a driver has a low or high fatigue level. The quality of sleep at home was recorded by filling in a score of 1 = not well, 2 = not well, 3 = well, per person. A total of 1852 (84%) driver had a low fatigue level, while 353 (16%) driver had a high fatigue level. Poor sleep quality was experienced by 68 (79%) driver who had a high fatigue level. Oil And Gas Tanker Driver who slept soundly at home as many as 1804 (87%) had a low fatigue level. The correlation coefficient of sleep quality home and fatigue level is significant because it shows a probability value of 0.00 (p <5%). Fatigue level can be diagnosed through examining sleep quality, using FAMOUS Program for occupational medicine, particularly in the oil and gas sector.

Keywords: psychomotor vigilance test, fatigue, sleep, oil and gas tanker driver drivers, pertamina FAMOUS

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Authors: Asefa Kenefergib, Dawit Amogne, Yinager Teklesellassie

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A study investigated the effects of text modifications on reading comprehension and motivation among Ethiopian secondary school students. A total of 120 students participated, initially taking a reading comprehension pretest and completing a reading motivation questionnaire. Afterward, they were divided into three groups: control, simplified, and elaborated. Each group then took part in a reading comprehension posttest and another reading motivation questionnaire following an eight-week instructional intervention. Despite initial differences, both the simplified and elaborated text groups showed comparable levels of reading motivation and comprehension. The data were analyzed using SPSS version 25, with a one-way ANOVA used to assess the effectiveness of the modified texts in enhancing reading comprehension. The results indicated that the experimental groups performed significantly better on the posttest compared to the control group, suggesting that text modifications can positively influence students' comprehension skills. Furthermore, the impact of text modifications on student reading motivation was assessed using a one-way ANOVA. The findings revealed that both the elaborated and simplified text groups scored higher than the control group in various dimensions of reading motivation, including reading efficacy, curiosity, challenge, compliance, and reading work avoidance. However, the control and simplified groups had nearly similar mean scores in the dimension of reading competition. These results clearly demonstrate that modifying texts can enhance EFL learners' reading motivation and comprehension.

Keywords: simplification, elaboration, reading motivation, reading comprehension

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Authors: Jasmine H. Gagnon

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The present study examined how grandiose narcissists make adaptive trade-offs between mating investment, parenting investment, and somatic investment relative to individuals without narcissistic personalities. A sample of 509 males and females between the ages of 24 and 35 years old (49.31% female) completed a personality inventory assessing Honesty-Humility, Emotionality, Extraversion, Agreeableness, Conscientiousness, and Openness to Experience. In a Latent Profile Analysis (LPA), personality inventory scores were used to classify participants into latent groups. The model of best fit identified one grandiose narcissist group and three groups with non-narcissistic personalities. Covariate analyses revealed that individuals with narcissistic traits made significantly more significant somatic investments in comparison to two of the three non-narcissistic latent groups. No other significant differences between the narcissistic and non-pathological groups were found. Thus, grandiose narcissists trade off parenting and mating investments to make more significant somatic investments. That is, they expend a larger portion of their energetic resources on maintaining their physical health and careers and similar quantities of energetic resources on maintaining relationships with their offspring and potential romantic partners as individuals without narcissistic personalities.

Keywords: narcissism, grandiose narcissism, HEXACO, trade-offs, mating, parenting, somatic, dark triad

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Authors: Peter Adekunle, Clinton Aigbavboa, Matthew Ikuabe, Opeoluwa Akinradewo

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The future of machine learning (ML) in building may seem like a distant idea that will take decades to materialize, but it is actually far closer than previously believed. In reality, the built environment has been progressively increasing interest in machine learning. Although it could appear to be a very technical, impersonal approach, it can really make things more personable. Instead of eliminating humans out of the equation, machine learning allows people do their real work more efficiently. It is therefore vital to evaluate the factors influencing the implementation and challenges of implementing machine learning techniques in the South African built environment. The study's design was one of a survey. In South Africa, construction workers and professionals were given a total of one hundred fifty (150) questionnaires, of which one hundred and twenty-four (124) were returned and deemed eligible for study. Utilizing percentage, mean item scores, standard deviation, and Kruskal-Wallis, the collected data was analyzed. The results demonstrate that the top factors influencing the adoption of machine learning are knowledge level and a lack of understanding of its potential benefits. While lack of collaboration among stakeholders and lack of tools and services are the key hurdles to the deployment of machine learning within the South African built environment. The study came to the conclusion that ML adoption should be promoted in order to increase safety, productivity, and service quality within the built environment.

Keywords: machine learning, implementation, built environment, construction stakeholders

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Authors: Liberata Borralho, Saúl N. de Jesus, Adelinda Candeias, Victória Fernández-Puig

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In the last decades, we have witnessed a deterioration in the health of teachers worldwide, reflecting the constant social, political and economic changes. The quality of teaching and the success of students depends on the health status of the teachers, which justifies the importance of periodically evaluating their health. With this purpose, the Teacher’s Health Questionnaire was applied to 15.394 teachers teaching in Portugal and Spain (6.208 Spanish and 9.186 Portuguese) of primary and secondary education (3.482 men, 11.911 women). This questionnaire is specific and includes both the main risks of the teaching profession and the manifestations of teacher well-being, according to the definition recommended by the World Health Organization. A descriptive analysis of the results was carried out, including a study of the dimensions and the differences according to some sociodemographic and professional variables, from an analysis of variance ANOVA, applying the Bonferroni correction. Cluster analysis (K-means) allowed us to obtain cutoff scores to assess health status. The results allow concluding that Portuguese teachers perceive a poor well-being in the performance of their professional activity and that more than half present manifestations in the various dimensions of health deterioration, highlighting the exhaustion and cognitive disorders. In turn, Spanish teachers demonstrate a high level of well-being, being the musculoskeletal dimensions and cognitive disorders the main manifestations of deterioration of health.

Keywords: job prevention, occupational health, teacher’s health, teachers work risks, teacher’s well-being

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Authors: P. Mambanga, Goon, L. O. Amusa

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The purpose of the study was to investigate the socio-cultural factors hindering sport participation among female students in the Centre for Biokinetics, Recreation and Sport Science, University of Venda. A descriptive survey of 100 female student selected by simple random sampling was used and utilises the close ended questionnaire designed in a likert format was use for data collection. Face and content validity was employed in which the supervisor went through the instrument and correct and accept it thus checking the validity of the instrument. The test-retest approach was used to test the reliability of the instrument. Ethical considerations were ensured and confidentiality respected. Data was collected and presented in tables and results interpreted. Chi square which is a measure of non-parametric investigation was employed in order to analyse the observed and expected scores, with the probability value was set at 0.05 levels of significance on a two-tailed test of the hypotheses formulated for the study. Findings of the study established significant socio-cultural factors that hinder female sport participation among female students in the Centre for Biokinetics, Recreation and Sport Science. The study concluded that the low level participation of female students at the University of Venda might be as a result of socio-cultural factors.

Keywords: female students, sport participation, University of Venda, biokinetic

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Authors: T. Hojageldiyev, Y. Bolmammedov

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Increasing evidence suggests late chronotype individuals are at increased risk of developing psychopathological conditions. Our previously conducted study aimed to know the distribution of chronotypes according to age revealed that evening-types reaching a peak at age 14. While there is growing number of studies evaluating associations between chronotype and affective symptoms, to our best knowledge there are no studies addressing the issue of prevalence of anhedonia according to age groups of people. The sample included 545 healthy students between 13-21 years old from secondary schools and universities of Turkmenistan. Self-report 14 item Snaith-Hamilton Pleasure Scale (SHAPS) was used to assess hedonic tone of students. SHAPS score of 3 or higher indicates the criteria for the anhedonia. According to similarity of hedonic capacity participants divided into three age groups. Group I (age 13-14-15) includes 206 students (92 female), group II (age 16-17) includes 256 students (111 female) and group III (age 18-19-20-21) includes 83 (37 female). Statistical analysis was performed using Microsoft Excel 2013 and GraphPad Prism 7.0 programs. According to results average SHAPS scores of group I is 1.93 ± 1.94, group II 1.08 ± 1.43 and group III 1.29 ± 1.62. Students with anhedonia in group I consisted 30.5%, in group II 13,2% and in group III 12.04%. There are no gender differences. According to questionnaire results, higher prevalence of anhedonia is at the age between 13-15 than other age groups, and hedonic capacity increases as the age of students increases (p < 0.05). As a result, distribution of evening-types according to age correlates with hedonic capacity which is evening-types tends to have lower hedonic capacity.

Keywords: anhedonia, age, chronotype, hedonic capacity

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Authors: Henry R. Troy

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Corpora are becoming more prevalent in the language classroom, especially in the development of dictionaries and course materials. Nevertheless, corpora are still perceived by many educators as difficult to use directly in the classroom, a process which is also known as “data-driven learning” (DDL). Action research has been identified as a method by which DDL’s efficiency can be increased, but it is also an approach few studies on DDL have employed. Studies into the effectiveness of DDL in language education in Japan are also rare, and investigations focused more on student and teacher reactions rather than pre and post-test scores are rarer still. This study investigates the student and teacher reactions to the use of SkELL, a free online corpus designed to be user-friendly, for vocabulary learning at a university in Japan. Action research is utilized to refine the teaching methodology, with changes to the method based on student and teacher feedback received via surveys submitted after each of the four implementations of DDL. After some training, the students used tablets to study the target vocabulary autonomously in pairs and groups, with the teacher acting as facilitator. The results show that the students enjoyed using SkELL and felt it was effective for vocabulary learning, while the teaching methodology grew in efficiency throughout the course. These findings suggest that action research can be a successful method for increasing the efficacy of DDL in the language classroom, especially with teachers and students who are new to the practice.

Keywords: action research, corpus linguistics, data-driven learning, vocabulary learning

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Authors: Adzongo Philomena Ibuh, Aloga O. Austin

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The purpose of the study was to examine lifelong education for teachers as a tool for achieving effective teaching and learning. Lifelong education enhances social inclusion, personal development, citizenship, employability, teaching and learning, community and the nation, and the challenges of lifelong education were also discussed. Descriptive survey design was adopted for the study. A simple random sampling technique was used to select 80 teachers as sample from a population of 105 senior secondary school teachers in Makurdi local government area of Benue state. A 20-item self designed questionnaire subjected to expert validation and reliability was used to collect data. The reliability Alpha coefficient of 0.87 was established using Crombach Alpha technique, mean scores and standard deviation were used to answer the 2 research questions while chi-square was used to analyze data for the 2 hypotheses. The findings of the study revealed that, lifelong education for teachers can be used to achieve as a tool for achieving effective teaching and learning, and the study recommended among others that government, organizations and individuals should in collaboration put lifelong education programmes for teachers on the priority list. The paper concluded that the strategic position of lifelong education for teachers towards enhanced teaching and learning makes it imperative for all hands to be on deck to support the programme financially and otherwise.

Keywords: effective teaching and learning, lifelong education, teachers, tool

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Authors: Ramona Zharfpeykan, Paul Rouse

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Organizational sustainability is important to both organizations themselves and their stakeholders. Despite its increasing popularity and increasing numbers of organizations reporting sustainability, research on evaluating and comparing the sustainability performance of companies is limited. The aim of this study was to develop models to measure sustainability performance for both cross-sectional and longitudinal comparisons across companies in the same or different industries. A secondary aim was to see if sustainability reports can be used to evaluate sustainability performance. The study used both a content analysis of Australian sustainability reports in mining and metals and financial services for 2011-2014 and a survey of Australian and New Zealand organizations. Two methods ranging from a composite index using uniform weights to data envelopment analysis (DEA) were employed to analyze the data and develop the models. The results show strong statistically significant relationships between the developed models, which suggests that each model provides a consistent, systematic and reasonably robust analysis. The results of the models show that for both industries, companies that had sustainability scores above or below the industry average stayed almost the same during the study period. These indices and models can be used by companies to evaluate their sustainability performance and compare it with previous years, or with other companies in the same or different industries. These methods can also be used by various stakeholders and sustainability ranking companies such as the Global Reporting Initiative (GRI).

Keywords: data envelopment analysis, sustainability, sustainability performance measurement system, sustainability performance index, global reporting initiative

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Authors: C. -L. Huang, J. -H. Ho

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Social media has become more and more important in our life. Many enterprises promote their services and products to fans via the social media. The positive or negative sentiment of feedbacks from fans is very important for enterprises to improve their products, services, and promotion activities. The purpose of this paper is to understand the sentiment of the fan’s responses by analyzing the responses posted by fans on Facebook. The entity and aspect of fan’s responses were analyzed based on a predefined ontology. The ontology for cell phone sentiment analysis consists of aspect categories on the top level as follows: overall, shape, hardware, brand, price, and service. Each category consists of several sub-categories. All aspects for a fan’s response were found based on the ontology, and their corresponding sentimental terms were found using lexicon-based approach. The sentimental scores for aspects of fan responses were obtained by summarizing the sentimental terms in responses. The frequency of 'like' was also weighted in the sentimental score calculation. Three famous cell phone fan pages on Facebook were selected as demonstration cases to evaluate performances of the proposed methodology. Human judgment by several domain experts was also built for performance comparison. The performances of proposed approach were as good as those of human judgment on precision, recall and F1-measure.

Keywords: opinion mining, ontology, sentiment analysis, text mining

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Authors: Aqsa Ali, Aleem Mushtaq, Attaullah Memon, Monna

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In this paper, we present a low cost design for a smart glove that can perform sign language recognition to assist the speech impaired people. Specifically, we have designed and developed an Assistive Hand Gesture Interpreter that recognizes hand movements relevant to the American Sign Language (ASL) and translates them into text for display on a Thin-Film-Transistor Liquid Crystal Display (TFT LCD) screen as well as synthetic speech. Linear Bayes Classifiers and Multilayer Neural Networks have been used to classify 11 feature vectors obtained from the sensors on the glove into one of the 27 ASL alphabets and a predefined gesture for space. Three types of features are used; bending using six bend sensors, orientation in three dimensions using accelerometers and contacts at vital points using contact sensors. To gauge the performance of the presented design, the training database was prepared using five volunteers. The accuracy of the current version on the prepared dataset was found to be up to 99.3% for target user. The solution combines electronics, e-textile technology, sensor technology, embedded system and machine learning techniques to build a low cost wearable glove that is scrupulous, elegant and portable.

Keywords: American sign language, assistive hand gesture interpreter, human-machine interface, machine learning, sensing glove

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Authors: Ibrahim Khalil Ibrahim, Enas Mohamed Shahine, Abeer Shawky El Hadedy, Emmanuel Kamal Aziz Saba, Ghada Salah Attia Hussein

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Osteoarthritis (OA) is a multifactorial disease characterized by a progressive degradation of articular cartilage and is the leading cause of disability in elderly persons. IL-18 contributes to the destruction of cartilage and bone in the disease process of arthritis. The aim of the study was to investigate the role of IL-18 in primary knee OA patients. Serum level of IL-18 was assessed by enzyme-linked immunosorbent assay in 30 primary knee OA patients and compared to 20 age and gender-matched healthy volunteers as a control group. Radiographic severity of OA was assessed by Kellgren and Lawrence (KL) global scale. Pain, stiffness and functional assessment were done using Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). OA patients had significantly higher serum IL-18 level than in control group (420.93 ± 345.4 versus 151.03 ± 144.16 pg/ml, P=0.001). Serum level of IL-18 was positively correlated with KL global scale (P=0.001). There were no statistically significant correlations between serum level of IL-18 and pain, stiffness, function subscales and total WOMAC index scores among the studied patients. In conclusions, IL-18 has a role in the pathogenesis of OA and it is positively correlated with the radiographic damage of OA.

Keywords: Interlukin-18, knee osteoarthritis, primary osteoarthritis, WOMAC scale

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Authors: Vita Strazdina, Aleksandrs Jemeljanovs, Vita Sterna

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Not all proteins have the same nutritional value, since protein quality strongly depends on its amino acid composition and digestibility. The meat of game animals could be a high protein source because of its well-balanced essential amino acids composition. Investigations about biochemical composition of game meat such as wild boar (Sus scrofa scrofa), roe deer (Capreolus capreolus) and beaver (Castor fiber) are not very much. Therefore, the aim of the investigation was evaluate protein composition of game meat hunted in Latvia. The biochemical analysis, evaluation of connective tissue and essential amino acids in meat samples were done, the amino acids score were calculate. Results of analysis showed that protein content 20.88-22.05% of all types of meat samples is not different statistically. The content of connective tissue from 1.3% in roe deer till 1.5% in beaver meat allowed classified game animal as high quality meat. The sum of essential amino acids in game meat samples were determined 7.05–8.26g100g-1. Roe deer meat has highest protein content and lowest content of connective tissues among game meat hunted in Latvia. Concluded that amino acid score for limiting amino acids phenylalanine and tyrosine is high and shows high biological value of game meat.

Keywords: dietic product, game meat, amino acids, scores

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Authors: Hatice Karakoyun, Mustafa Akdag

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This study has been made to examine the attitudes of pre-school teachers towards values education. The study has been made as a general scanning model. The study’s working group contains 108 pre-school teachers who worked in Diyarbakır, Turkey. In this study Values Education Attitude Scale (VEAS), which developed by Yaşaroğlu (2014), was used. In order to analyze the data for sociodemographic structure, percentage and frequency values were examined. The Kolmogorov-Smirnov method was used in determination of the normal distribution of data. During analyzing the data, KolmogorovSimirnov test and the normal curved histograms were examined to determine which statistical analyzes would be applied on the scale and it was found that the distribution was not normal. Thus, the Mann Whitney U analysis technique which is one of the nonparametric statistical analysis techniques were used to test the difference of the scores obtained from the scale in terms of independent variables. According to the analyses, it seems that pre-school teachers’ attitudes toward values education are positive. According to the scale with the highest average, it points out that pre-school teachers think that values education is very important for students’ and children’s future. The variables included in the scale (gender, seniority, age group, education, school type, school place) seem to have no effect on the pre-school teachers’ attitude grades which joined to the study.

Keywords: attitude scale, pedagogy, pre-school teacher, values education

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Authors: Izharul Haq

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Every one of us seek to aspire to gain quality education. The biggest stake holders are students who labor through years acquiring knowledge and skill to help them prepare for their career. Parents spend a fortune on their children’s education. Companies spend billions of dollars to enhance standards by developing new education products and services. Quality education is the golden key to a long lasting prosperity for the individual and the nation. But unfortunately, education standards are continuously deteriorating and it has become a global phenomenon. Unfortunately, teaching is often described as a ‘popularity contest’ and those teachers who are usually popular with students are often those who compromise teaching to appease students. Such teachers also ‘teach-to-the-test’ ensuring high test scores. Such teachers, hence, receive good student rating. Teachers who are conscientious, rigorous and thorough are often the victims of good appraisal. Government and private organizations are spending billions of dollars trying to capture the characteristics of a good teacher. But the results are still vague and inconclusive. At present there is no objective way to measure teaching effectiveness. In this paper we present an innovative method to objectively measure teaching effectiveness using a new teaching tool (TSquare). The TSquare tool used in the study is practical, easy to use, cost effective and requires no special equipment to implement. Hence it has a global appeal for poor and the rich countries alike.

Keywords: measuring teaching effectiveness, quality in education, student learning, teaching styles

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

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

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

Procedia PDF Downloads 131

Authors: Hamood Al Kiyumi, Salim Al Huseini, Khalid Al Risi, Hassan Mirza, Amira Al Hosni, Sanjay Jaju, Asaad Al Habsi

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Objectives: The aim of this study was to assess the proportion of depressive symptoms along with demographic data in children diagnosed with epilepsy in a tertiary care institution in Oman. Methods: This cross-sectional study was conducted between June 2016 and August 2018. We have included 75 children with age group from five to 12 years old, attending epilepsy clinic at Sultan Qaboos University Hospital who were diagnosed with epilepsy and already on treatment. Patients were excluded if they have mental retardation. Validated Depression Scale for Children (CES-DC) questionnaire was utilized to assess the level of depressive symptoms among children. In addition, we have looked at associated factors including seizure status in the last three months, compliance with antiepileptic medications, type of epilepsy, and number of antiepileptic medications. Results: In this study, we found that depressive symptoms were present in 39 (52%) of patients. We also found that 96% of the patients were compliant to medications. In addition, seizure was present in the last three months in 48% of the sample studies. There was no statistically significant association between any of the studied variables and depression. Conclusions: Although depression is highly prevalent in children with epilepsy, this study did not find any significant association between the CES-DC scores and the studied factors.

Keywords: depression, children, epilepsy, Oman

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

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

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

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Authors: Nipin Kohli, Ravi Chand Singh

Abstract:

Diabetes mellitus is a serious illness and can be life-threatening if left untreated. Acetone present in the exhaled breath of a diabetic person is a biomarker of patients suffering from diabetes mellitus and is higher than its usual concentration present in the breath of healthy people. In the present work, a portable gas sensor system based on chromium oxide (Cr₂O₃) nanoparticles has been developed that can analyze diabetic patient’s breath. Undoped and indium (In) doped Cr₂O₃ nanoparticles were synthesized by a chemical route and characterized by X-ray diffraction, scanning electron microscopy, Raman spectroscopy, UV-visible spectroscopy, and photoluminescence spectroscopy for their structural, morphological and optical properties. Thick film gas sensors were fabricated out of synthesized samples. To diagnose diabetes, the sensors’ response to low concentrations of acetone was measured, and it was found that the addition of indium dramatically enhances the acetone gas sensing response. Moreover, the fabricated sensors were highly stable, reproducible and resistant to humidity. Enhancement of sensor response of doped sensors towards acetone can be ascribed to increase in defects due to addition of a dopant, and it was found that in-doped Cr₂O₃ sensors are more useful for analysis of breath of diabetic patients.

Keywords: Diabetes mellitus, nanoparticles, raman spectroscopy, sensor

Procedia PDF Downloads 142

Authors: Mitra Savabi-Esfahani, Fariba Taleghani, Mahnaz Noroozi, Maryam Tabatabaeian, Elsebeth Lynge

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Breast cancer is a health concern in worldwide. All women have not adequate information about breast cancer, resulting in undetected some tumors until advanced stages. Therefore awareness of people was recommended as a strategy to control that. The aim of this study was to assess the effect of an educational intervention on women's knowledge and attitude about breast cancer and screening. This study was conducted in 2016 on 191 women. All women living in one of big cities were invited to enroll in training classes. Inclusion criteria consisted women who were 20 - 69 years and not participated in any educational intervention. The lecture with group discussion was used as educational methods. Data collection tool was a structured questionnaire which filled out before and after intervention. The reliability of the questionnaire was determined by Cronbach's alpha. The data were analyzed using SPSS software. The average age was 44/4 ± 11.5 and 42.6% of the women had obtained high school. Of the 191 women, 70(36.6%) and 76(39.8%) had low and medium level of knowledge respectively and half of them, 95(50%) had medium level of attitude in before intervention. There was significant difference between mean scores of knowledge and attitude before and after the intervention by Paired T test (p < 0/001). It seems applying effective educational interventions can increase knowledge and attitude women about breast cancer particularly in community that they have insufficient levels. Moreover, the lecture method along with group discussion can be proposed as effective and conventional methods for this purpose.

Keywords: attitude, breast cancer, educational intervention, knowledge

Procedia PDF Downloads 307