Search results for: learning difficulty

Authors: Ka C. Lam, Oluwafunmibi S. Idowu

Abstract:

Uncertainty in cost is a major factor affecting performance of construction projects. To our knowledge, several conceptual cost models have been developed with varying degrees of accuracy. Incorporating conceptual quantities into conceptual cost models could improve the accuracy of early predesign cost estimates. Hence, the development of quantity models for estimating conceptual quantities of framed reinforced concrete structures using supervised machine learning is the aim of the current research. Using measured quantities of structural elements and design variables such as live loads and soil bearing pressures, response and predictor variables were defined and used for constructing conceptual quantities models. Twenty-four models were developed for comparison using a combination of non-parametric support vector regression, linear regression, and bootstrap resampling techniques. R programming language was used for data analysis and model implementation. Gross soil bearing pressure and gross floor loading were discovered to have a major influence on the quantities of concrete and reinforcement used for foundations. Building footprint and gross floor loading had a similar influence on beams and slabs. Future research could explore the modelling of other conceptual quantities for walls, finishes, and services using machine learning techniques. Estimation of conceptual quantities would assist construction planners in early resource planning and enable detailed performance evaluation of early cost predictions.

Keywords: bootstrapping, conceptual quantities, modelling, reinforced concrete, support vector regression

Procedia PDF Downloads 213

Authors: Nasser Mansour, Ziad Said, Abdullah Abu-Tineh

Abstract:

STEM teachers face the challenge of possessing expertise not only in their subject disciplines but also in the pedagogical knowledge required for integrated STEM lessons. However, research reveals a lack of pedagogical competencies related to project-based learning (PBL) in the STEM context. To bridge this gap, the study examines teachers' competencies and self-efficacy in TPACK (Technological Pedagogical Content Knowledge) and its specific integration with PBL and STEM content. Data from 245 specialized science and math teachers were collected using a questionnaire. The study emphasizes the importance of addressing gender disparities, supporting formal teacher education, and recognizing the expertise and experiences of STEM teachers in effective technology integration. The findings indicate that gender plays a role in self-efficacy beliefs, with females exhibiting higher confidence in pedagogical knowledge and males demonstrating higher confidence in technological knowledge. Teaching experience and workload factors have a limited impact on teachers' Technological Pedagogical Content Knowledge (TPACK). These findings enhance our understanding of contextual factors impacting science and math teachers' self-efficacy in utilizing TPACK for STEM and PBL. They inform the development of targeted interventions, professional development programs, and support systems to enhance teachers' competencies and self-efficacy in TPACK for teaching science and Mathematics through STEM and PBL.

Keywords: technological pedagogical content knowledge, TPACK, STEM, project-based learning, PBL, self-efficacy, mathematics, science

Procedia PDF Downloads 66

Authors: Tamar Bikashvili, Tamar Lordkipanidze, Ilia Lazrishvili

Abstract:

Heavy metals remain one of serious environmental problems due to their toxic effects. The effect of arsenic and manganese compounds on rat behavior and neuromorphology was studied. Wistar rats were assigned to four groups: rats in control group were given regular water, while rats in other groups drank water with final manganese concentration of 10 mg/L (group A), 20 mg/L (group B) and final arsenic concentration 68 mg/L (group C), respectively, for a month. To study exploratory and anxiety behavior and also to evaluate aggressive performance in “home cage” rats were tested in “Open Field” and to estimate learning and memory status multi-branched maze was used. Statistically significant increase of motor and oriental-searching activity in experimental groups was revealed by an open field test, which was expressed in increase of number of lines crossed, rearing and hole reflexes. Obtained results indicated the suppression of fear in rats exposed to manganese. Specifically, this was estimated by the frequency of getting to the central part of the open field. Experiments revealed that 30-day exposure to 10 mg/ml manganese did not stimulate aggressive behavior in rats, while exposure to the higher dose (20 mg/ml), 37% of initially non-aggressive animals manifested aggressive behavior. Furthermore, 25% of rats were extremely aggressive. Obtained data support the hypothesis that excess manganese in the body is one of the immediate causes of enhancement of interspecific predatory aggressive and violent behavior in rats. It was also discovered that manganese intoxication produces non-reversible severe learning disability and insignificant, reversible memory disturbances. Studies of rodents exposed to arsenic also revealed changes in the learning process. As it is known, the distribution of metal ions differs in various brain regions. The principle manganese accumulation was observed in the hippocampus and in the neocortex, while arsenic was predominantly accumulated in nucleus accumbens, striatum, and cortex. These brain regions play an important role in the regulation of emotional state and motor activity. Histopathological analyzes of brain sections illustrated two morphologically distinct altered phenotypes of neurons: (1) shrunk cells with indications of apoptosis - nucleus and cytoplasm were very difficult to be distinguished, the integrity of neuronal cytoplasm was not disturbed; and (2) swollen cells - with indications of necrosis. Pyknotic nucleus, plasma membrane disruption and cytoplasmic vacuoles were observed in swollen neurons and they were surrounded by activated gliocytes. It’s worth to mention that in the cortex the majority of damaged neurons were apoptotic while in subcortical nuclei –neurons were mainly necrotic. Ultrastructural analyses demonstrated that all cell types in the cortex and the nucleus caudatus represent destructed mitochondria, widened neurons’ vacuolar system profiles, increased number of lysosomes and degeneration of axonal endings.

Keywords: arsenic, manganese, behavior, learning, neuron

Procedia PDF Downloads 362

Authors: Jamerson Felipe Pereira Lima, Jeane Cecília Bezerra de Melo

Abstract:

The difficulty and cost related to obtaining of protein tertiary structure information through experimental methods, such as X-ray crystallography or NMR spectroscopy, helped raising the development of computational methods to do so. An approach used in these last is prediction of tridimensional structure based in the residue chain, however, this has been proved an NP-hard problem, due to the complexity of this process, explained by the Levinthal paradox. An alternative solution is the prediction of intermediary structures, such as the secondary structure of the protein. Artificial Intelligence methods, such as Bayesian statistics, artificial neural networks (ANN), support vector machines (SVM), among others, were used to predict protein secondary structure. Due to its good results, artificial neural networks have been used as a standard method to predict protein secondary structure. Recent published methods that use this technique, in general, achieved a Q3 accuracy between 75% and 83%, whereas the theoretical accuracy limit for protein prediction is 88%. Alternatively, to achieve better results, support vector machines prediction methods have been developed. The statistical evaluation of methods that use different AI techniques, such as ANNs and SVMs, for example, is not a trivial problem, since different training sets, validation techniques, as well as other variables can influence the behavior of a prediction method. In this study, we propose a prediction method based on artificial neural networks, which is then compared with a selected SVM method. The chosen SVM protein secondary structure prediction method is the one proposed by Huang in his work Extracting Physico chemical Features to Predict Protein Secondary Structure (2013). The developed ANN method has the same training and testing process that was used by Huang to validate his method, which comprises the use of the CB513 protein data set and three-fold cross-validation, so that the comparative analysis of the results can be made comparing directly the statistical results of each method.

Keywords: artificial neural networks, protein secondary structure, protein structure prediction, support vector machines

Procedia PDF Downloads 624

Authors: Supat Chaiyakul, Direk Sukkasem, Patnachapa Natthapanpaisith

Abstract:

Sinlek rice flour beverage or instant product is a dietary supplement for dysphagia, or difficulty swallowing. It is also consumed by individuals who need to consume supplements to maintain their calorific needs. This product provides protein, fat, iron, and a high concentration of carbohydrate from rice flour. However, the application of native flour is limited due to its high viscosity. Starch modification by controlling starch retrogradation was used in this study. The research studies the effects of rice flour concentration and retrogradation treatment on the physical properties of instant Sinlek brown rice. The native rice flour, gelatinized rice flour, and flour gels retrograded under 4 °C for 3 and 7 days were investigated. From the statistical results, significant differences between native and retrograded flour were observed. The concentration of rice flour was the main factor influencing the swelling power, solubility, and pasting properties. With the increase in rice flour content from 10 to 15%, swelling power, peak viscosity, trough, and final viscosity decreased; but, solubility, pasting temperature, peak time, breakdown, and setback increased. The peak time, pasting temperature, peak viscosity, trough, and final viscosity decreased as the storage period increased from 3 to 7 days. The retrograded rice flour powders had lower pasting temperature, peak viscosity, breakdown, and final viscosity than the gelatinized and native flour powders. Reduction of starch viscosity by gelatinization and controlling starch retrogradation could allow for increased quantities of rice flour in instant rice beverages. Also, the treatment could increase the energy and nutrient densities of rice beverages without affecting the viscosity of this product.

Keywords: instant rice, pasting properties, pregelatinization, retrogradation

Procedia PDF Downloads 246

Authors: Nawras Kurzom, Avi Mendelsohn

Abstract:

The effects of background music on learning and memory are inconsistent, partly due to the intrinsic complexity and variety of music and partly to individual differences in music perception and preference. A prominent musical feature that is known to elicit strong emotional responses is musical tension. Musical tension can be brought about by building anticipation of rhythm, harmony, melody, and dynamics. Delaying the resolution of dominant-to-tonic chord progressions, as well as using dissonant harmonics, can elicit feelings of tension, which can, in turn, affect memory formation of concomitant information. The aim of the presented studies was to explore how forming declarative memory is influenced by musical tension, brought about within continuous music as well as in the form of isolated chords with varying degrees of dissonance/consonance. The effects of musical tension on long-term memory of declarative information were studied in two ways: 1) by evoking tension within continuous music pieces by delaying the release of harmonic progressions from dominant to tonic chords, and 2) by using isolated single complex chords with various degrees of dissonance/roughness. Musical tension was validated through subjective reports of tension, as well as physiological measurements of skin conductance response (SCR) and pupil dilation responses to the chords. In addition, music information retrieval (MIR) was used to quantify musical properties associated with tension and its release. Each experiment included an encoding phase, wherein individuals studied stimuli (words or images) with different musical conditions. Memory for the studied stimuli was tested 24 hours later via recognition tasks. In three separate experiments, we found positive relationships between tension perception and physiological measurements of SCR and pupil dilation. As for memory performance, we found that background music, in general, led to superior memory performance as compared to silence. We detected a trade-off effect between tension perception and memory, such that individuals who perceived musical tension as such displayed reduced memory performance for images encoded during musical tension, whereas tense music benefited memory for those who were less sensitive to the perception of musical tension. Musical tension exerts complex interactions with perception, emotional responses, and cognitive performance on individuals with and without musical training. Delineating the conditions and mechanisms that underlie the interactions between musical tension and memory can benefit our understanding of musical perception at large and the diverse effects that music has on ongoing processing of declarative information.

Keywords: musical tension, declarative memory, learning and memory, musical perception

Procedia PDF Downloads 102

Authors: Dujrudee Chinwong, Chanida Prompantakorn, Ubonphan Chaichana, Surarong Chinwong

Abstract:

Objective: Understanding the university students’ perceptions on smoking caused lung cancer based on the Health Belief Model should help health care providers in assisting them to quit smoking. Thus, this study aimed to investigate the University students’ health belief in smoking behaviors caused lung cancer, which based on the Health Belief Model. Methods: Data were collected from voluntary participants using a self-administered questionnaire. Participants were students studying at a University in northern Thailand who were current smokers; they were selected using snowball sampling. Results: Of 361 students, 84% were males; 78% smoked not more than 10 cigarettes a day; 68% intended to quit smoking. Our findings, based on the health belief model, showed that 1) perceived susceptibility: participants strongly believed that if they did not stop smoking, they were at high risk of lung cancer (88%); 2) perceived severity: they strongly believed that they had a high chance of death from lung cancer if they continued smoking (84%); 3) perceived benefits: they strongly believed that quitting smoking could reduce the chance of developing lung cancer; 4) perceived barriers of quitting smoking: they strongly believed in the difficulty of quitting smoking because it needed a high effort and strong intention (69%); 5) perceived self-efficacy: however, they strongly believed that they can quit smoking right away if they had a strong intention to quit smoking (70%); 6) cues to action: they strongly believed in the support of parents (85%) and lovers (78%) in helping them to quit smoking. Further, they believed that limitation on smoking area in the University and smoking cessation services provided by the University can assist them to quit smoking. Conclusion: The Health Belief Model helps us to understand students’ smoking behaviors caused lung cancer. This could lead to designing a smoking cessation program to assist students to quit smoking.

Keywords: health belief model, lung cancer, smoking, Thailand

Procedia PDF Downloads 303

Authors: Murat Emre, Zeynep Tufekcioglu

Abstract:

Objective: We describe a patient with late onset phenylketonuria which presented with rapidly progressive dementia and parkinsonism that were reversible after management. Background: Phenylketonuria is an autosomal recessive disorder due to mutations in the phenylalanine hydroxlase gene. It normally presents in childhood, in rare cases, however, it may have its onset in adulthood and may mimic other neurological disorders. Case description: A previously normal functioning, 59 year old man was admitted for blurred vision, cognitive impairment and gait difficulty which emerged over the past eight months. In neurological examination he had brisk reflexes, slow gait and left-dominant parkinsonism. Mini-mental state examination score was 25/30, neuropsychological testing revealed a dysexecutive syndrome with constructional apraxia and simultanagnosia. In cranial MRI there were bilateral diffuse hyper-intense lesions in parietal and occipital white matter with no significant atrophy. Electroencephalography showed diffuse slowing with predominance of teta waves. In cerebrospinal fluid examination protein level was slightly elevated (61mg/dL), oligoclonal bands were negative. Electromyography was normal. Routine laboratory examinations for rapidly progressive dementia and parkinsonism were also normal. Serum amino acid levels were determined to explore metabolic leukodystrophies and phenylalanine level was found to be highly elevated (1075 µmol/L) with normal tyrosine (61,20 µmol/L). His cognitive impairment and parkinsonian symptoms improved following three months of phenylalanine restricted diet. Conclusions: Late onset phenylketonuria is a rare, potentially reversible cause of rapidly progressive parkinsonism with dementia. It should be considered in the differential diagnosis of patients with suspicious features.

Keywords: dementia, neurology, Phenylketonuria, rapidly progressive parkinsonism

Procedia PDF Downloads 274

Authors: M. Pushparani, A. Sagaya

Abstract:

Embedded systems have emerged as important elements in various domains with extensive applications in automotive, commercial, consumer, healthcare and transportation markets, as there is emphasis on intelligent devices. On the other hand, Business Intelligence (BI) has also been extensively used in a range of applications, especially in the agriculture domain which is the area of this research. The aim of this research is to create a framework for Embedded Weight Comparison Algorithm with Business Intelligence (EWCA-BI). The weight comparison algorithm will be embedded within the plantation management system and the weighbridge system. This algorithm will be used to estimate the weight at the site and will be compared with the actual weight at the plantation. The algorithm will be used to build the necessary alerts when there is a discrepancy in the weight, thus enabling better decision making. In the current practice, data are collected from various locations in various forms. It is a challenge to consolidate data to obtain timely and accurate information for effective decision making. Adding to this, the unstable network connection leads to difficulty in getting timely accurate information. To overcome the challenges embedding is done on a portable device that will have the embedded weight comparison algorithm to also assist in data capture and synchronize data at various locations overcoming the network short comings at collection points. The EWCA-BI will provide real-time information at any given point of time, thus enabling non-latent BI reports that will provide crucial information to enable efficient operational decision making. This research has a high potential in bringing embedded system into the agriculture industry. EWCA-BI will provide BI reports with accurate information with uncompromised data using an embedded system and provide alerts, therefore, enabling effective operation management decision-making at the site.

Keywords: embedded business intelligence, weight comparison algorithm, oil palm plantation, embedded systems

Procedia PDF Downloads 291

Authors: Ramuel Spirituel Mattathiah A. San Juan, Neil Ambasing

Abstract:

Background: Reversal of vision metamorphopsia is a transient form of metamorphopsia described as an upside-down alteration of the visual field in the coronal plane. Patients would describe objects, such as cups, upside down, but the tea would not spill, and people would walk on their heads. It is extremely rare as a stable finding, lasting days or weeks. We report a case wherein this type of metamorphopsia occurred only in written words and lasted for six months. Objective: To the best of our knowledge, we report the first rare occurrence of reversal of vision metamorphopsia described as inverted words as the sole initial presentation of an underlying stroke. Case Presentation: We report a 59-year-old male with poorly controlled hypertension and diabetes mellitus who presented with a 3-day history of difficulty reading, described as the words were turned upside down as if the words were inverted horizontally then with the progression of deficits such as right homonymous hemianopia and achromatopsia, prosopagnosia. Cranial magnetic resonance imaging (MRI) revealed an acute infarct on the left posterior cerebral artery territory. Follow-up after six months revealed improvement of the visual field cut but with the persistence of the higher cortical function deficits. Conclusion: We report the first rare occurrence of metamorphopsia described as purely inverted words as the sole initial presentation of an underlying stroke. The differential diagnoses of a patient presenting with text reversal metamorphopsia should include stroke in the occipitotemporal areas. It further expands the landscape of metamorphopsias due to its exclusivity to written words and prolonged duration. Knowing these clinical features will help identify the lesion locus and improve subsequent stroke care, especially in time-bound management like intravenous thrombolysis.

Keywords: rare presentation, text reversal metamorphopsia, ischemic stroke, stroke

Procedia PDF Downloads 67

Authors: Ohud Adnan Saffar

Abstract:

This study aims to know the effect of using universal design for learning (UDL) to improve the quality of vocational programme with intellectual disabilities (SID) and the challenges facing this method from the teachers' point of view. The significance of the study: There are comparatively few published studies on UDL in emerging nations. Therefore, this study will encourage the researchers to consider a new approaches teaching. Development of this study will contribute significant information on the cognitively disabled community on a universal scope. In order to collect and evaluate the data and for the verification of the results, this study has been used the mixed research method, by using two groups comparison method. To answer the study questions, we were used the questionnaire, lists of observations, open questions, and pre and post-test. Thus, the study explored the advantages and drawbacks, and know about the impact of using the UDL method on integrating SID with students non-special education needs in the same classroom. Those aims were realized by developing a workshop to explain the three principles of the UDL and train (16) teachers in how to apply this method to teach (12) students non-special education needs and the (12) SID in the same classroom, then take their opinion by using the questionnaire and questions. Finally, this research will explore the effects of the UDL on the teaching of professional photography skills for the SID in Saudi Arabia. To achieve this goal, the research method was a comparison of the performance of the SID using the UDL method with that of female students with the same challenges applying other strategies by teachers in control and experiment groups, we used the observation lists, pre and post-test. Initial results: It is clear from the previous response to the participants that most of the answers confirmed that the use of UDL achieves the principle of inclusion between the SID and students non-special education needs by 93.8%. In addition, the results show that the majority of the sampled people see that the most important advantages of using UDL in teaching are creating an interactive environment with using new and various teaching methods, with a percentage of 56.2%. Following this result, the UDL is useful for integrating students with general education, with a percentage of 31.2%. Moreover, the finding indicates to improve understanding through using the new technology and exchanging the primitive ways of teaching with the new ones, with a percentage of 25%. The result shows the percentages of the sampled people's opinions about the financial obstacles, and it concluded that the majority see that the cost is high and there is no computer maintenance available, with 50%. There are no smart devices in schools to help in implementing and applying for the program, with a percentage of 43.8%.

Keywords: universal design for learning, intellectual disabilities, vocational programme, the challenges facing this method

Procedia PDF Downloads 131

Authors: Nicole A. Alford

Abstract:

The study of online graduate education started just 30 years ago, with the first online graduate program in the 1990s. Institutions are looking for ways to increase retention and support the needs of students with the rapid expansion of online higher education due to the global pandemic. Online education provides access and opportunities to those who otherwise would be unable to pursue an advanced degree for logistical reasons. Thus, the objective of the critical literature review is to survey current research of student experiences given the expanding role of online doctoral programs. The guiding research questions are: What are the personal, professional, and student life practices of graduate students who enrolled in a fully online university doctoral program or course? and How do graduate students who enrolled in a fully online doctoral program or course describe the factors that contributed to their continued study? The systematic literature review was conducted employing a variety of databases to locate articles using key Boolean terms and synonyms within three categories of the e-learning, doctoral education, and student perspectives. Inclusion criteria for the literature review consisted of empirical peer-reviewed studies with original data sources that focused on doctoral programs and courses within a fully online environment and centered around student experiences. A total of 16 articles were selected based on the inclusion criteria and systemically analyzed through coding using the Boote and Beile criteria. Major findings suggest that doctoral students face stressors related to social and emotional wellbeing in the online environment. A lack of social connection, isolation, and burnout were the main challenges experienced by students. Students found support from their colleagues, advisors, and faculty to persist. Communities and cohorts of online doctoral students were found to guard against these challenges. Moreover, in the methods section of the articles, there was a lack of specificity related to student demographics, general student information, and insufficient detail about the online doctoral program. Additionally, descriptions regarding the experiences of cohorts and communities in the online environment were vague and not easily replicable with the given details. This literature review reveals that doctoral students face social and emotional challenges related to isolation and the rigor of the academic process and lean on others for support to continue in their studies. Given the lack of current knowledge about online doctoral students, it proves to be a challenge to identify effective practices and create high-retention doctoral programs in online environments. The paucity of information combined with the dramatic transition to e-learning due to the global pandemic can provide a perfect storm for attrition in these programs. Several higher education institutions have transitioned graduate studies online, thus providing an opportunity for further exploration. Given the new necessity of online learning, this work provides insight into examining current practices in online doctoral programs that have moved to this modality during the pandemic. The significance of the literature review provides a springboard for research into online doctoral programs as the solution to continue advanced education amongst a global pandemic.

Keywords: e-learning, experiences, higher education, literature review

Procedia PDF Downloads 117

Authors: Abdullahi Mannir Rawayau

Abstract:

This paper identifies the problems that have aided the decoy to adequate basic infrastructural amenities, sub-standard housing, over-crowding, poor ventilation in homes and work places, sanitation, and non-compliance with building bye-laws and regulation. The paper also asserts the efficient disposal of solid and liquid waste is one of the challenges in the informal areas due to threats on the environment and public health. Sanitation services in the informal settlements have been found to be much lower compared to the average for unban. Bearing in mind a factor which prevents sustainable sanitation in informal areas which include low incomes, insecure tenure, low education levels, difficulty topography and transitory populations, and this study aim to identify effective strategies for achieving sustainable sanitation with specific reference to the informal settlement. Using the Shanghai Low-Cost as a case study. The primary data collected was through observation and interview method. Similarly, the secondary data used for the study was collected through literature reviews from extent studies with specific reference to informal settlement. A number of strategies towards achieving sustainable sanitation in the study were identified here in classified into three (3):- Advocacy and capacity building, infrastructural provision and institutionalization of systems and processes. The paper concludes with the premise on the need to build alliances between the government and stakeholders concerned with sanitation provision through the creation of sanitation and employ adaptable technology. Provision of sanitation facilities in public areas and to establish a statutory body for timely response to sanitation waste management in Katsina. It is imperative to check and prevent further decay for harmonious living and sustainable development.

Keywords: built environment, sanitation, facilities, settlement

Procedia PDF Downloads 230

Authors: Randall E. Osborne

Abstract:

In a course on International Psychology, 8 theoretical perspectives (Critical Psychology, Liberation Psychology, Post-Modernism, Social Constructivism, Social Identity Theory, Social Reduction Theory, Symbolic Interactionism, and Vygotsky’s Sociocultural Theory) are used as a framework for getting students to understand the concept of and need for Globalization. One of critical psychology's main criticisms of conventional psychology is that it fails to consider or deliberately ignores the way power differences between social classes and groups can impact the mental and physical well-being of individuals or groups of people. Liberation psychology, also known as liberation social psychology or psicología social de la liberación, is an approach to psychological science that aims to understand the psychology of oppressed and impoverished communities by addressing the oppressive sociopolitical structure in which they exist. Postmodernism is largely a reaction to the assumed certainty of scientific, or objective, efforts to explain reality. It stems from a recognition that reality is not simply mirrored in human understanding of it, but rather, is constructed as the mind tries to understand its own particular and personal reality. Lev Vygotsky argued that all cognitive functions originate in, and must therefore be explained as products of social interactions and that learning was not simply the assimilation and accommodation of new knowledge by learners. Social Identity Theory discusses the implications of social identity for human interactions with and assumptions about other people. Social Identification Theory suggests people: (1) categorize—people find it helpful (humans might be perceived as having a need) to place people and objects into categories, (2) identify—people align themselves with groups and gain identity and self-esteem from it, and (3) compare—people compare self to others. Social reductionism argues that all behavior and experiences can be explained simply by the affect of groups on the individual. Symbolic interaction theory focuses attention on the way that people interact through symbols: words, gestures, rules, and roles. Meaning evolves from human their interactions in their environment and with people. Vygotsky’s sociocultural theory of human learning describes learning as a social process and the origination of human intelligence in society or culture. The major theme of Vygotsky’s theoretical framework is that social interaction plays a fundamental role in the development of cognition. This presentation will discuss how these theoretical perspectives are incorporated into a course on International Psychology, a course on the Politics of Hate, and a course on the Psychology of Prejudice, Discrimination and Hate to promote student thinking in a more ‘global’ manner.

Keywords: globalization, international psychology, society and culture, teaching interculturally

Procedia PDF Downloads 257

Authors: Deniz Peksen

Abstract:

This thesis aims to predict trend movement of closing price of stock and to maximize portfolio by utilizing the predictions. In this context, the study aims to define a stock portfolio strategy from models created by using Logistic Regression, Gradient Boosting and Random Forest. Recently, predicting the trend of stock price has gained a significance role in making buy and sell decisions and generating returns with investment strategies formed by machine learning basis decisions. There are plenty of studies in the literature on the prediction of stock prices in capital markets using machine learning methods but most of them focus on closing prices instead of the direction of price trend. Our study differs from literature in terms of target definition. Ours is a classification problem which is focusing on the market trend in next 20 trading days. To predict trend direction, fourteen years of data were used for training. Following three years were used for validation. Finally, last three years were used for testing. Training data are between 2002-06-18 and 2016-12-30 Validation data are between 2017-01-02 and 2019-12-31 Testing data are between 2020-01-02 and 2022-03-17 We determine Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate as benchmarks which we should outperform. We compared our machine learning basis portfolio return on test data with return of Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate. We assessed our model performance with the help of roc-auc score and lift charts. We use logistic regression, Gradient Boosting and Random Forest with grid search approach to fine-tune hyper-parameters. As a result of the empirical study, the existence of uptrend and downtrend of five stocks could not be predicted by the models. When we use these predictions to define buy and sell decisions in order to generate model-based-portfolio, model-based-portfolio fails in test dataset. It was found that Model-based buy and sell decisions generated a stock portfolio strategy whose returns can not outperform non-model portfolio strategies on test dataset. We found that any effort for predicting the trend which is formulated on stock price is a challenge. We found same results as Random Walk Theory claims which says that stock price or price changes are unpredictable. Our model iterations failed on test dataset. Although, we built up several good models on validation dataset, we failed on test dataset. We implemented Random Forest, Gradient Boosting and Logistic Regression. We discovered that complex models did not provide advantage or additional performance while comparing them with Logistic Regression. More complexity did not lead us to reach better performance. Using a complex model is not an answer to figure out the stock-related prediction problem. Our approach was to predict the trend instead of the price. This approach converted our problem into classification. However, this label approach does not lead us to solve the stock prediction problem and deny or refute the accuracy of the Random Walk Theory for the stock price.

Keywords: stock prediction, portfolio optimization, data science, machine learning

Procedia PDF Downloads 86

Authors: Rishabh Ambavanekar

Abstract:

Expressive Aphasia (EA) is an oral disability, common among stroke victims, in which the Broca’s area of the brain is damaged, interfering with verbal communication abilities. EA currently has no technological solutions and its only current viable solutions are inefficient or only available to the affluent. This prompts the need for an affordable, innovative solution to facilitate recovery and assist in speech generation. This project proposes a novel concept: using a wearable low-cost electroencephalography (EEG) device-based brain-computer interface (BCI) to translate a user’s inner dialogue into words. A low-cost EEG device was developed and found to be 10 to 100 times less expensive than any current EEG device on the market. As part of the BCI, a machine learning (ML) model was developed and trained using the EEG data. Two stages of testing were conducted to analyze the effectiveness of the device: a proof-of-concept and a final solution test. The proof-of-concept test demonstrated an average accuracy of above 90% and the final solution test demonstrated an average accuracy of above 75%. These two successful tests were used as a basis to demonstrate the viability of BCI research in developing lower-cost verbal communication devices. Additionally, the device proved to not only enable users to verbally communicate but has the potential to also assist in accelerated recovery from the disorder.

Keywords: neurotechnology, brain-computer interface, neuroscience, human-machine interface, BCI, HMI, aphasia, verbal disability, stroke, low-cost, machine learning, ML, image recognition, EEG, signal analysis

Procedia PDF Downloads 122

Authors: Soumya Sajjan

Abstract:

Liver cancer is the most common cancer disease worldwide in men and women, and is one of the few cancers still on the rise. Liver disease is the 4th leading cause of death. According to new NHS (National Health Service) figures, deaths from liver diseases have reached record levels, rising by 25% in less than a decade; heavy drinking, obesity, and hepatitis are believed to be behind the rise. In this study, we focus on Development of Diagnostic Classifier for Ultrasound liver lesion. Ultrasound (US) Sonography is an easy-to-use and widely popular imaging modality because of its ability to visualize many human soft tissues/organs without any harmful effect. This paper will provide an overview of underlying concepts, along with algorithms for processing of liver ultrasound images Naturaly, Ultrasound liver lesion images are having more spackle noise. Developing classifier for ultrasound liver lesion image is a challenging task. We approach fully automatic machine learning system for developing this classifier. First, we segment the liver image by calculating the textural features from co-occurrence matrix and run length method. For classification, Support Vector Machine is used based on the risk bounds of statistical learning theory. The textural features for different features methods are given as input to the SVM individually. Performance analysis train and test datasets carried out separately using SVM Model. Whenever an ultrasonic liver lesion image is given to the SVM classifier system, the features are calculated, classified, as normal and diseased liver lesion. We hope the result will be helpful to the physician to identify the liver cancer in non-invasive method.

Keywords: segmentation, Support Vector Machine, ultrasound liver lesion, co-occurance Matrix

Procedia PDF Downloads 415

Authors: Boon Yih Mah

Abstract:

Web-based Cognitive Writing Instruction (WeCWI)’s contribution towards language development can be divided into linguistic and non-linguistic perspectives. In linguistic perspective, WeCWI focuses on the literacy and language discoveries, while the cognitive and psychological discoveries are the hubs in non-linguistic perspective. In linguistic perspective, WeCWI draws attention to free reading and enterprises, which are supported by the language acquisition theories. Besides, the adoption of process genre approach as a hybrid guided writing approach fosters literacy development. Literacy and language developments are interconnected in the communication process; hence, WeCWI encourages meaningful discussion based on the interactionist theory that involves input, negotiation, output, and interactional feedback. Rooted in the e-learning interaction-based model, WeCWI promotes online discussion via synchronous and asynchronous communications, which allows interactions happened among the learners, instructor, and digital content. In non-linguistic perspective, WeCWI highlights on the contribution of reading, discussion, and writing towards cognitive development. Based on the inquiry models, learners’ critical thinking is fostered during information exploration process through interaction and questioning. Lastly, to lower writing anxiety, WeCWI develops the instructional tool with supportive features to facilitate the writing process. To bring a positive user experience to the learner, WeCWI aims to create the instructional tool with different interface designs based on two different types of perceptual learning style.

Keywords: WeCWI, literacy discovery, language discovery, cognitive discovery, psychological discovery

Procedia PDF Downloads 565

Authors: Jisoo Song

Abstract:

Today’s mobile applications are communicating with servers more and more in order to access external services or information. Also, server-side code changes are more frequent than client-side code changes in a mobile application. The frequent changes lead to an increase in testing cost increase. To reduce costs, UI based test automation can be one of the solutions. It is a common automation technique in system-level testing. However, it can be unsuitable for mobile applications. When you automate tests based on UI elements for mobile applications, there are some limitations such as the overhead of script maintenance or the difficulty of finding invisible defects that UI elements cannot represent. To overcome these limitations, we present a new automation technique based on Rest API. You can automate system-level tests through test scripts that you write. These scripts call a series of Rest API in a user’s action sequence. This technique does not require testers to know the internal implementation details, only input and expected output of Rest API. You can easily modify test cases by modifying Rest API input values and also find problems that might not be evident from the UI level by validating output values. For example, when an application receives price information from a payment server and user cannot see it at UI level, Rest API based scripts can check whether price information is correct or not. More than 10 mobile applications at our company are being tested automatically based on Rest API scripts whenever application source code, mostly server source code, is built. We are finding defects right away by setting a script as a build job in CI server. The build job starts when application code builds are completed. This presentation will also include field cases from our company.

Keywords: case studies at SK Planet, introduction of rest API based test automation, limitations of UI based test automation

Procedia PDF Downloads 450

Authors: Anita De Melo

Abstract:

Today we live in a crucial time of ecological crisis, of environmental catastrophes worldwide, and this scenario is, arrogantly, overlooked by powerful economic forces and their politics. Thus, a critical pedagogy that leads to action and that fosters ecoliteracy, environment education, is now inevitable, and it must become an integral part of the school curriculum across the disciplines, including the social sciences and the humanities. One of the most important contemporary and emerging movement of today is ecopedagogy, a movement that blends theory and ethics towards a curriculum that focus on an environmental education that will promote ecological justice, respect, and care by educating students to become planetary citizens. This paper aims, first, to emphasize the need for discussions and investigations regarding ecoliteracy within our field of teaching foreign languages, which will consider, among others, the of role language in stimulating sustainability, and the role of second language proficiency in fostering positive transnational dialogues conducive to fighting our current planetary crisis. Second, this paper suggests and discusses some critical ecopedagogical practices -- in the form of project-based learning, service-learning and environmental-oriented study abroad programs – apropos to ecoliteracy. These interdisciplinary projects can and should bring students in contact with communities speaking the target language, and such encounter would facilitate cultural exchanges and promote positive language proficiency whilst it would also give students the opportunity to work with finding ideas/projects to fight our current ecological catastrophe.

Keywords: critical pedagogy, ecoliteracy, ecopedagogy, planetary crisis

Procedia PDF Downloads 252

Authors: Hichem Sassi

Abstract:

Pneumonia, being a respiratory infection, has garnered global attention due to its rapid transmission and relatively high mortality rates. Timely detection and treatment play a crucial role in significantly reducing mortality associated with pneumonia. Presently, X-ray diagnosis stands out as a reasonably effective method. However, the manual scrutiny of a patient's X-ray chest radiograph by a proficient practitioner usually requires 5 to 15 minutes. In situations where cases are concentrated, this places immense pressure on clinicians for timely diagnosis. Relying solely on the visual acumen of imaging doctors proves to be inefficient, particularly given the low speed of manual analysis. Therefore, the integration of artificial intelligence into the clinical image diagnosis of pneumonia becomes imperative. Additionally, AI recognition is notably rapid, with convolutional neural networks (CNNs) demonstrating superior performance compared to human counterparts in image identification tasks. To conduct our study, we utilized a dataset comprising chest X-ray images obtained from Kaggle, encompassing a total of 5216 training images and 624 test images, categorized into two classes: normal and pneumonia. Employing five mainstream network algorithms, we undertook a comprehensive analysis to classify these diseases within the dataset, subsequently comparing the results. The integration of artificial intelligence, particularly through improved network architectures, stands as a transformative step towards more efficient and accurate clinical diagnoses across various medical domains.

Keywords: deep learning, computer vision, pneumonia, models, comparative study

Procedia PDF Downloads 68

Authors: Musbah Abdussayed

Abstract:

The washback effect refers to the influence of assessment on teaching and learning, and this washback effect can either be positive or negative. This study implemented, sequentially, self-assessment (SA) and peer assessment (PA) and examined the washback effect of self and peer assessment (SPA) activities on the writing growth during the revision phase in the writing process. Twenty advanced Arabic as a second language learners from a private school in the USA participated in the study. The participants composed and then revised a short Arabic story as a part of a midterm grade. Qualitative data was collected, analyzed, and synthesized from ten interviews with the learners and from the twenty learners’ post-reflective journals. The findings indicate positive washback effects on the learners’ writing growth. The PA activity enhanced descriptions and meaning, promoted creativity, and improved textual coherence, whereas the SA activity led to detecting editing issues. Furthermore, both SPA activities had washback effects in common, including helping the learners meet the writing genre conventions and developing metacognitive awareness. However, the findings also demonstrate negative washback effects on the learners’ attitudes during the revision phase in the writing process, including bias toward self-evaluation during the SA activity and reluctance to rate peers’ writing performance during the PA activity. The findings suggest that self-and peer assessment activities are essential teaching and learning tools that can be utilized sequentially to help learners tackle multiple writing areas during the revision phase in the writing process.

Keywords: self assessment, peer assessment, washback effect, second language writing, writing process

Procedia PDF Downloads 75

Authors: B. Padmaja, V. V. Rama Prasad, K. V. N. Sunitha, E. Krishna Rao Patro

Abstract:

Stress is a psychological condition that reduces the quality of sleep and affects every facet of life. Constant exposure to stress is detrimental not only for mind but also body. Nevertheless, to cope with stress, one should first identify it. This paper provides an effective method for the cognitive stress level detection by using data provided from a physical activity tracker device Fitbit. This device gathers people’s daily activities of food, weight, sleep, heart rate, and physical activities. In this paper, four major stressors like physical activities, sleep patterns, working hours and change in heart rate are used to assess the stress levels of individuals. The main motive of this system is to use machine learning approach in stress detection with the help of Smartphone sensor technology. Individually, the effect of each stressor is evaluated using logistic regression and then combined model is built and assessed using variants of ordinal logistic regression models like logit, probit and complementary log-log. Then the quality of each model is evaluated using Akaike Information Criterion (AIC) and probit is assessed as the more suitable model for our dataset. This system is experimented and evaluated in a real time environment by taking data from adults working in IT and other sectors in India. The novelty of this work lies in the fact that stress detection system should be less invasive as possible for the users.

Keywords: physical activity tracker, sleep pattern, working hours, heart rate, smartphone sensor

Procedia PDF Downloads 259

Authors: Jian Li

Abstract:

The uncertainty quantification and inversion problems of subsurface oil-water phase flow usually require extensive repeated forward calculations for new runs with changed conditions. To reduce the computational time, various forms of surrogate models have been built. Related research shows that deep learning has emerged as an effective surrogate model, while most surrogate models with deep learning are purely data-driven, which always leads to poor robustness and abnormal results. To guarantee the model more consistent with the physical laws, a coupled theory-guided convolutional neural network (TgCNN) based surrogate model is built to facilitate computation efficiency under the premise of satisfactory accuracy. The model is a convolutional neural network based on multi-well reservoir simulation. The core notion of this proposed method is to bridge two separate blocks on top of an overall network. They underlie the TgCNN model in a coupled form, which reflects the coupling nature of pressure and water saturation in the two-phase flow equation. The model is driven by not only labeled data but also scientific theories, including governing equations, stochastic parameterization, boundary, and initial conditions, well conditions, and expert knowledge. The results show that the TgCNN-based surrogate model exhibits satisfactory accuracy and efficiency in subsurface oil-water phase flow under multi-well conditions.

Keywords: coupled theory-guided convolutional neural network, multi-well conditions, surrogate model, subsurface oil-water phase

Procedia PDF Downloads 89

Authors: Asima Ranjan Parhi

Abstract:

English language teaching-learning in higher education departments in Indian and Asian contexts needs to be one of innovation and experimentation rather than rigid prescription. The communicative language teaching has been proposing the context to be of primary importance in this process. Today, English print and electronic media have flooded the market with plenty of material suitable to the classroom context. The entries are poetic, catchy and contain a deliberate method in them which could be utilized to teach not only English language but literature, literary terms and the theory of literature. The Bollywood movies, especially through their songs have been propagating a package which may be useful to teach language and even theory in the sub-continent. While investigating, one may be fascinated to see how such material in the body of media (print and electronic), movies and popular songs generate a data for our classroom in our context, thereby developing a mass language with huge pedagogical implications. Harping on the four skills of teaching and learning of a language in general and English language in particular appears stale and mechanical in a decontextualised, matter of fact classroom. So this discussion visualizes a model beyond these skills as well as the conventional theory, literature, language classroom practices in order to build up a systematic pattern stressing the factors responsible in the particular context, that of specific language, society and culture in tune with language-literature teaching. This study intends to examine certain catchy use of the language entries in mass media which could be in the direction of inviting more such investigations in the Asian context in order to develop a common platform of decolonized pedagogy.

Keywords: pedagogy, electronic media, Bollywood, decolonized, mass media

Procedia PDF Downloads 278

Authors: Shakila N. Senarath, Dinesh Asanka, Janaka Wijayanayake

Abstract:

The necessity of cosmetic products is arising to fulfill consumer needs of personality appearance and hygiene. A cosmetic product consists of various chemical ingredients which may help to keep the skin healthy or may lead to damages. Every chemical ingredient in a cosmetic product does not perform on every human. The most appropriate way to select a healthy cosmetic product is to identify the texture of the body first and select the most suitable product with safe ingredients. Therefore, the selection process of cosmetic products is complicated. Consumer surveys have shown most of the time, the selection process of cosmetic products is done in an improper way by consumers. From this study, a content-based system is suggested that recommends cosmetic products for the human factors. To such an extent, the skin type, gender and price range will be considered as human factors. The proposed system will be implemented by using Machine Learning. Consumer skin type, gender and price range will be taken as inputs to the system. The skin type of consumer will be derived by using the Baumann Skin Type Questionnaire, which is a value-based approach that includes several numbers of questions to derive the user’s skin type to one of the 16 skin types according to the Bauman Skin Type indicator (BSTI). Two datasets are collected for further research proceedings. The user data set was collected using a questionnaire given to the public. Those are the user dataset and the cosmetic dataset. Product details are included in the cosmetic dataset, which belongs to 5 different kinds of product categories (Moisturizer, Cleanser, Sun protector, Face Mask, Eye Cream). An alternate approach of TF-IDF (Term Frequency – Inverse Document Frequency) is applied to vectorize cosmetic ingredients in the generic cosmetic products dataset and user-preferred dataset. Using the IF-IPF vectors, each user-preferred products dataset and generic cosmetic products dataset can be represented as sparse vectors. The similarity between each user-preferred product and generic cosmetic product will be calculated using the cosine similarity method. For the recommendation process, a similarity matrix can be used. Higher the similarity, higher the match for consumer. Sorting a user column from similarity matrix in a descending order, the recommended products can be retrieved in ascending order. Even though results return a list of similar products, and since the user information has been gathered, such as gender and the price ranges for product purchasing, further optimization can be done by considering and giving weights for those parameters once after a set of recommended products for a user has been retrieved.

Keywords: content-based filtering, cosmetics, machine learning, recommendation system

Procedia PDF Downloads 138

Authors: Feiying Wu

Abstract:

Chatbots are computer programs that attempt to engage a human in a dialogue, which originated in the 1960s with MIT's Eliza. However, they have become widespread more recently as advances in language technology have produced chatbots with increasing linguistic quality and sophistication, leading to their potential to serve as a tool for Computer-Assisted Language Learning(CALL). The aim of this article is to assess the feasibility of using two chatbots, Mitsuku and CleverBot, as pedagogical tools for learning English as a second language by stimulating L2 learners with distinct English proficiencies. Speaking of the input of stimulated learners, they are measured by AntWordProfiler to match the user's expected vocabulary proficiency. Totally, there are four chat sessions as each chatbot will converse with both beginners and advanced learners. For evaluation, it focuses on chatbots' responses from a linguistic standpoint, encompassing vocabulary and sentence levels. The vocabulary level is determined by the vocabulary range and the reaction to misspelled words. Grammatical accuracy and responsiveness to poorly formed sentences are assessed for the sentence level. In addition, the assessment of this essay sets 25% lexical and grammatical incorrect input to determine chatbots' corrective ability towards different linguistic forms. Based on statistical evidence and illustration of examples, despite the small sample size, neither Mitsuku nor CleverBot is ideal as educational tools based on their performance through word range, grammatical accuracy, topic range, and corrective feedback for incorrect words and sentences, but rather as a conversational tool for beginners of L2 English.

Keywords: chatbots, CALL, L2, corrective feedback

Procedia PDF Downloads 82

Authors: Surichai Butcha, Dararat Khampusaen

Abstract:

As the Internet is recognized as a high potential and powerful educational tool to access sources of knowledge, plagiarism is an increasing unethical issue found in students’ writing. This paper is deriving from the 1st phase of an on-going study investigating the effects of the supplementary on citing sources on undergraduate students’ writing. The 40 participants were divided into 1 experimental group and 1 control group. Both groups were administered with a questionnaire on knowledge and an interview on attitude related to using sources in writing. Only the experimental group undertook the 4 lessons focusing on using outside sources and citing the original work (quoting, synthesizing, summarizing and paraphrasing) were delivered to them via e-learning tools throughout a semester. Participants were required to produce 4 writing tasks after each lesson. The results were concerned with types and factors on using outside sources in writing of Thai undergraduate EFL students from the survey. The interview results supported and clarified the survey result. In addition, the writing rubrics confirmed the types of plagiarism frequently occurred in students’ writing. The results revealed the types and factors on plagiarism including their perceptions on using the outside sources in their writing from the interview. The discussion shed the lights on cultural dimensions of plagiarism in student writing, roles of teachers, library, and university policy on the rate of plagiarism. Also, the findings promoted the awareness on ethics in writing and prevented the rate of potential unintentional plagiarism. Additionally, the results of this phase of study could lead to the appropriate contents to be considered for inclusion in the supplementary on using sources for writing for future research.

Keywords: citing source, EFL writing, e-learning, Internet, plagiarism

Procedia PDF Downloads 152

Authors: Nathaniel Carpenter

Abstract:

Web-enabled systems for supporting youth mental health management in Australia are pioneering in their field; however, with their success, these systems are experiencing exponential growth in demand which is straining an already stretched service. Supporting youth mental is critical as the lack of support is associated with significant and lasting negative consequences. To meet this growing demand, and provide critical support, investigations are needed on evaluating and improving existing online support services. Improvements should focus on developing frameworks capable of augmenting and scaling service provisions. There are few investigations informing best-practice frameworks when implementing e-mental health support systems for youth mental health; there are fewer which implement machine learning or artificially intelligent systems to facilitate the delivering of services. This investigation will use a case study methodology to highlight the design features which are important for systems to enable young people to self-manage their mental health. The investigation will also highlight the current information system challenges, to include challenges associated with service quality, provisioning, and scaling. This work will propose methods of meeting these challenges through improved design, service augmentation and automation, service quality, and through artificially intelligent inspired solutions. The results of this study will inform a framework for supporting youth mental health with intelligent and scalable web-enabled technologies to support an ever-growing user base.

Keywords: artificial intelligence, information systems, machine learning, youth mental health

Procedia PDF Downloads 119

Authors: Molly Gerrish

Abstract:

This work explores the physical, emotional, social, and cognitive risks and benefits related to nature-based teaching and highlights the importance of promoting a sustainable workforce within early childhood programs. Assessing and managing risks can help programs reimagine their approach to teaching, learning, recruitment, family connectivity, and staff motivation. The importance of staff sustainability and motivation/engagement related to social justice and the environment will be discussed. We will explore ways to manage fears and limitations faced by early childhood programs regarding nature experiences and risky play in a variety of locations using a lens of place-based learning. We will also examine the alignment of sustainability and social-emotional development, mental health supports, social awareness, and risk assessment. The work will discuss the varied perceptions of risk in diverse areas and the impact on the early childhood workforce. Motivational theory and compassion resiliency are hallmarks of both recruiting and retaining high-quality early childhood educators; the work will discuss how to balance programmatic constraints and healthy motivation for students and teachers while empowering individuals to advocate for their mental health and well-being. Finally, the work will highlight the positive impact of nature-based teaching practices and the overall benefit to young children and their educators.

Keywords: child’s rights, inclusion, nature-based education, risk assessment

Procedia PDF Downloads 66