Search results for: adaptive educational digital learning environments

Authors: Yichao Liu, Peter Fransson, Julian Heidecke, Jonas Wallin, Joacim Rockloev

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Dengue, a mosquito-borne viral disease, poses a significant public health challenge in endemic tropical or subtropical countries, including Sri Lanka. To reveal insights into the complexity of the dynamics of this disease and study the drivers, a comprehensive model capable of both robust forecasting and insightful inference of drivers while capturing the co-circulating of several virus strains is essential. However, existing studies mostly focus on only one aspect at a time and do not integrate and carry insights across the siloed approach. While mechanistic models are developed to capture immunity dynamics, they are often oversimplified and lack integration of all the diverse drivers of disease transmission. On the other hand, purely data-driven methods lack constraints imposed by immuno-epidemiological processes, making them prone to overfitting and inference bias. This research presents a hybrid model that combines machine learning techniques with mechanistic modelling to overcome the limitations of existing approaches. Leveraging eight years of newly reported dengue case data, along with socioeconomic factors, such as human mobility, weekly climate data from 2011 to 2018, genetic data detecting the introduction and presence of new strains, and estimates of seropositivity for different districts in Sri Lanka, we derive a data-driven vector (SEI) to human (SEIR) model across 16 regions in Sri Lanka at the weekly time scale. By conducting ablation studies, the lag effects allowing delays up to 12 weeks of time-varying climate factors were determined. The model demonstrates superior predictive performance over a pure machine learning approach when considering lead times of 5 and 10 weeks on data withheld from model fitting. It further reveals several interesting interpretable findings of drivers while adjusting for the dynamics and influences of immunity and introduction of a new strain. The study uncovers strong influences of socioeconomic variables: population density, mobility, household income and rural vs. urban population. The study reveals substantial sensitivity to the diurnal temperature range and precipitation, while mean temperature and humidity appear less important in the study location. Additionally, the model indicated sensitivity to vegetation index, both max and average. Predictions on testing data reveal high model accuracy. Overall, this study advances the knowledge of dengue transmission in Sri Lanka and demonstrates the importance of incorporating hybrid modelling techniques to use biologically informed model structures with flexible data-driven estimates of model parameters. The findings show the potential to both inference of drivers in situations of complex disease dynamics and robust forecasting models.

Keywords: compartmental model, climate, dengue, machine learning, social-economic

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Authors: Naresh Kumar, Radhika Sharma, A. K. Singh

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Acid plutonic rocks from the Khanak and Devsar areas of southwestern Haryana were investigated to understand their geochemical and petrogenetic characteristics and tectonic environments. Three dominant rock types (grey, grayish green and pink granites) are the principal geochemical features of Khanak and Devsar areas which reflect the dependencies of their composition on varied geological environment during the anorogenic magmatism. These rocks are enriched in SiO₂, Na₂O+K₂O, Fe/Mg, Rb, Zr, Y, Th, U, REE (Rare Earth Elements) enriched and depleted in MgO, CaO, Sr, P, Ti, Ni, Cr, V and Eu and exhibit a clear affinity to the within-plate granites that were emplaced in an extensional tectonic environment. Chondrite-normalized REE patterns show enriched LREE (Light Rare Earth Elements), moderate to strong negative Eu anomalies and flat heavy REE and grey and grayish green is different from pink granite which is enriched by Rb, Ga, Nb, Th, U, Y and HREE (Heavy Rare Earth Elements) concentrations. The composition of parental magma of both areas corresponds to mafic source contaminated with crustal materials. Petrogenetic modelling suggest that the acid plutonic rocks might have been generated from a basaltic source by partial melting (15-25%) leaving a residue with 35% plagioclase, 25% alkali feldspar, 25% quartz, 7% orthopyroxene, 5% biotite and 3% hornblende. Granites from both areas might be formed from different sources with different degree of melting for grey, grayish green and pink granites.

Keywords: A-type granite, anorogenic, Malani igneous suite, Khanak and Devsar

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Authors: Asma Ameur, Dhafer Malouche

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Nowadays, user comments on the Internet have an important impact on hotel bookings. This confirms that the e-reputation issue can influence the likelihood of customer loyalty to a hotel. In this way, e-reputation has become a real differentiator between hotels. For this reason, we have a unique opportunity in the opinion mining field to analyze the comments. In fact, this field provides the possibility of extracting information related to the polarity of user reviews. This sentimental study (Opinion Mining) represents a new line of research for analyzing the unstructured textual data. Knowing the score of e-reputation helps the hotelier to better manage his marketing strategy. The score we then obtain is translated into the image of hotels to differentiate between them. Therefore, this present research highlights the importance of hotel satisfaction ‘scoring. To calculate the satisfaction score, the sentimental analysis can be manipulated by several techniques of machine learning. In fact, this study treats the extracted textual data by using the Artificial Neural Networks Approach (ANNs). In this context, we adopt the aforementioned technique to extract information from the comments available in the ‘Trip Advisor’ website. This actual paper details the description and the modeling of the ANNs approach for the scoring of online hotel reviews. In summary, the validation of this used method provides a significant model for hotel sentiment analysis. So, it provides the possibility to determine precisely the polarity of the hotel users reviews. The empirical results show that the ANNs are an accurate approach for sentiment analysis. The obtained results show also that this proposed approach serves to the dimensionality reduction for textual data’ clustering. Thus, this study provides researchers with a useful exploration of this technique. Finally, we outline guidelines for future research in the hotel e-reputation field as comparing the ANNs with other technique.

Keywords: clustering, consumer behavior, data mining, e-reputation, machine learning, neural network, online hotel ‘reviews, opinion mining, scoring

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Authors: Yun-Yao Chi, Chieh-Kai Tsai, Dai-Ling Li

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In this paper, a method of fast 3D topography modeling using the high-resolution camera images is studied based on the characteristics of Unmanned Aerial Vehicle (UAV) system for low altitude aerial photogrammetry and the need of three dimensional (3D) urban landscape modeling. Firstly, the existing high-resolution digital camera with special design of overlap images is designed by reconstructing and analyzing the auto-flying paths of UAVs, which improves the self-calibration function to achieve the high precision imaging by software, and further increased the resolution of the imaging system. Secondly, several-angle images including vertical images and oblique images gotten by the UAV system are used for the detail measure of urban land surfaces and the texture extraction. Finally, the aerial photography and 3D topography construction are both developed in campus of Chang-Jung University and in Guerin district area in Tainan, Taiwan, provide authentication model for construction of 3D topography based on combined UAV-based camera images from system. The results demonstrated that the UAV system for low altitude aerial photogrammetry can be used in the construction of 3D topography production, and the technology solution in this paper offers a new, fast, and technical plan for the 3D expression of the city landscape, fine modeling and visualization.

Keywords: 3D, topography, UAV, images

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Authors: Mahima Shrivastava, Soumya Kar, B. Swetha Malika, Lalu Saheb, M. Muthu Kumar, P. V. Ponambala Moorthi

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Natural hazards and manmade destruction causes both economic and societal losses. Generalized pre-mitigation strategies introduced and adopted for prevention of disaster all over the world are capable of augmenting the resiliency and optimizing the life-cycle cost of facilities. In countries like India where varied topographical feature exists requires location specific mitigation measures and strategies to be followed for better enhancement by event-driven and code-driven approaches. Present state of vindication measures followed and adopted, lags dominance in accomplishing the required development. In addition, serious concern and debate over climate change plays a vital role in enhancing the need and requirement for the development of time bound adaptive mitigation measures. For the development of long-term sustainable policies incorporation of future climatic variation is inevitable. This will further assist in assessing the impact brought about by the climate change on life-cycle cost of facilities. This paper develops more definite region specific and time bound pre-mitigation measures, by reviewing the present state of mitigation measures in India and all over the world for improving life-cycle cost of facilities. For the development of region specific adoptive measures, Indian regions were divided based on multiple-calamity prone regions and geo-referencing tools were used to incorporate the effect of climate changes on life-cycle cost assessment. This study puts forward significant effort in establishing sustainable policies and helps decision makers in planning for pre-mitigation measures for different regions. It will further contribute towards evaluating the life cycle cost of facilities by adopting the developed measures.

Keywords: climate change, geo-referencing tools, life-cycle cost, multiple-calamity prone regions, pre-mitigation strategies, sustainable policies

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Authors: Hamza Shams, Sajid Saleem, Bilal A. Siddiqui

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This paper investigates the coefficient of friction at nano-levels of commercially available superhydrophobic/oleophobic coatings when applied over 316L SS. 316L Stainless Steel or Marine Stainless Steel has been selected for its widespread uses in structures, marine and biomedical applications. The coatings were investigated in harsh sand-storm and sea water environments. The particle size of the sand during the procedure was carefully selected to simulate sand-storm conditions. Sand speed during the procedure was carefully modulated to simulate actual wind speed during a sand-storm. Sample preparation was carried out using prescribed methodology by the coating manufacturer. The coating’s adhesion and thickness was verified before and after the experiment with the use of Scanning Electron Microscopy (SEM). The value for nano-level coefficient of friction has been determined using Lateral Force Microscopy (LFM). The analysis has been used to formulate a value of friction coefficient which in turn is associative of the amount of wear the coating can bear before the exposure of the base substrate to the harsh environment. The analysis aims to validate the coefficient of friction value as marketed by the coating manufacturers and more importantly test the coating in real-life applications to justify its use. It is expected that the coating would resist exposure to the harsh environment for a considerable amount of time. Further, it would prevent the sample from getting corroded in the process.

Keywords: 316L SS, scanning electron microscopy, lateral force microscopy, marine stainless steel, oleophobic coating, superhydrophobic coating

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Authors: Chamaraja Parulli

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Family is an important social institution devoted to the growth of a child, and parents are the important agents of socialization. Mentally challenged children are those who are affected by intellectual disability, which is manifested by limitation in intellectual functioning and adoptive behavior. Intellectual disability affects about 3-4 percentage of the general population. Intellectual disability is caused by genetic condition, problems during pregnancy, problems during childbirth, or illness. Mental retardation is the world’s most complex and challenging issue. The stigmatization of disability results in social and economic marginalization. Parents of the mentally challenged children will have a very high level of parenting stress, which is significantly more than the stress perceived by the parents of the children without disability. The prevalence of severe mental disorder called Schizophrenia is among 1.1 percent of the total population in India. On the other hand, 11 to 12 percent is the overall lifetime occurrence rate of mental disorders. While the government has a separate program for mental health, the segment is marred by lack of adequate doctors and infrastructure. Mentally retarded children have certain limitations in mental functioning and skills, which makes them slow learners in speaking, walking, and taking care of their personal needs such as dressing and eating. Accepting a child with mental handicap becomes difficult for parents and to the whole family, as they have to face many problems, including those of management, finance, deprivation of rest, and leisure. Also, the problems faced by the parents can be seen in different areas like – educational, psychological, social, emotional, financial and family related issues. The study brought out various difficulties and problems faced by the parents as well as family members. The findings revealed that the mental retardation is not only a medico-psychological problem but also a socio-cultural problem. The study results, however, indicate that the quality of life of the family having children with mental retardation can be improved to a greater extent by building up a child-friendly ambience at home. The main aim of the present study is to assess the problems faced by the parents of mentally challenged children, with the help of personal interview data collected from the parents of mentally challenged children, residing in Shimoga District of Karnataka State, India. These individuals were selected using stratified random sampling method. Organizing effective intervention programs for parents, family, society, and educational institutions towards reduction of family stress, augmenting the family’s strengths, increasing child’s competence and enhancing the positive attitudes and values of the society will go a long way for the peaceful existence of the mentally challenged children.

Keywords: mentally challenged children, intellectual disability, special children, social infrastructure, differently abled, psychological stress, marginalization

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Authors: Heba M. Jahin, Ali F. Bakr, Zeyad T. Elsayad

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As smart spaces can be defined as any working environment which integrates embedded computers, information appliances and multi-modal sensors to remain focused on the interaction between the users, their activity, and their behavior in the space; hence, smart space must be aware of their contexts and automatically adapt to their changing context-awareness, by interacting with their physical environment through natural and multimodal interfaces. Also, by serving the information used proactively. This paper suggests a dynamic framework through the architectural design process of the space based on the principles of computational methods and context-awareness principles to help in creating a field of changes and modifications. It generates possibilities, concerns about the physical, structural and user contexts. This framework is concerned with five main processes: gathering and analyzing data to generate smart design scenarios, parameters, and attributes; which will be transformed by coding into four types of models. Furthmore, connecting those models together in the interaction model which will represent the context-awareness system. Then, transforming that model into a virtual and ambient environment which represents the physical and real environments, to act as a linkage phase between the users and their activities taking place in that smart space . Finally, the feedback phase from users of that environment to be sure that the design of that smart space fulfill their needs. Therefore, the generated design process will help in designing smarts spaces that can be adapted and controlled to answer the users’ defined goals, needs, and activity.

Keywords: computational methods, context-awareness, design process, smart spaces

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Authors: Mostafa Gamal, Hoda K. Mohamed, Islam El-Maddah, Ali Hamdi

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In recent years, many digital documents on the web have been created due to the rapid growth of ’social applications’ communities or ’Data-intensive applications’. The evolution of online-based multimedia data poses new challenges in storing and querying large amounts of data for online recommender systems. Graph data models have been shown to be more efficient than relational data models for processing complex data. This paper will explain the key differences between graph and relational databases, their strengths and weaknesses, and why using graph databases is the best technology for building a realtime recommendation system. Also, The paper will discuss several similarity metrics algorithms that can be used to compute a similarity score of pairs of nodes based on their neighbourhoods or their properties. Finally, the paper will discover how NLP strategies offer the premise to improve the accuracy and coverage of realtime recommendations by extracting the information from the stored unstructured knowledge, which makes up the bulk of the world’s data to enrich the graph database with this information. As the size and number of data items are increasing rapidly, the proposed system should meet current and future needs.

Keywords: graph databases, NLP, recommendation systems, similarity metrics

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Authors: Pastraporn Thipayasothorn, Vipawan Tadapratheep, Jintana Nokyoo

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A physical realization of good environmental governance about an environmental principle, educational psychology and architecture in the three King Mongkut's Institutes of Technology, is generated for researching physical environmental factors which related to the good environmental governance, communication between the good environmental governance and a physical environmental, and a physical environmental design policy. Moreover, we collected data by a survey, observation and questionnaire that participants are students of the three King Mongkut's Institutes of Technology, and analyzed a relationship between a building utilization and the good environmental governance awareness. We found that, from the data analysis, a balance and creativity participation which played as the project users and communities of the good governance environmental promotion in the institutes helps the good governance and environmental development in the future.

Keywords: built environment, good governance, environmental governance, physical environmental

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Authors: Piotr A. Kowalski, Kasper Sapala, Wiktor Warchalowski

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PM10 is a suspended dust that primarily has a negative effect on the respiratory system. PM10 is responsible for attacks of coughing and wheezing, asthma or acute, violent bronchitis. Indirectly, PM10 also negatively affects the rest of the body, including increasing the risk of heart attack and stroke. Unfortunately, Poland is a country that cannot boast of good air quality, in particular, due to large PM concentration levels. Therefore, based on the dense network of Airly sensors, it was decided to deal with the problem of prediction of suspended particulate matter concentration. Due to the very complicated nature of this issue, the Machine Learning approach was used. For this purpose, Convolution Neural Network (CNN) neural networks have been adopted, these currently being the leading information processing methods in the field of computational intelligence. The aim of this research is to show the influence of particular CNN network parameters on the quality of the obtained forecast. The forecast itself is made on the basis of parameters measured by Airly sensors and is carried out for the subsequent day, hour after hour. The evaluation of learning process for the investigated models was mostly based upon the mean square error criterion; however, during the model validation, a number of other methods of quantitative evaluation were taken into account. The presented model of pollution prediction has been verified by way of real weather and air pollution data taken from the Airly sensor network. The dense and distributed network of Airly measurement devices enables access to current and archival data on air pollution, temperature, suspended particulate matter PM1.0, PM2.5, and PM10, CAQI levels, as well as atmospheric pressure and air humidity. In this investigation, PM2.5, and PM10, temperature and wind information, as well as external forecasts of temperature and wind for next 24h served as inputted data. Due to the specificity of the CNN type network, this data is transformed into tensors and then processed. This network consists of an input layer, an output layer, and many hidden layers. In the hidden layers, convolutional and pooling operations are performed. The output of this system is a vector containing 24 elements that contain prediction of PM10 concentration for the upcoming 24 hour period. Over 1000 models based on CNN methodology were tested during the study. During the research, several were selected out that give the best results, and then a comparison was made with the other models based on linear regression. The numerical tests carried out fully confirmed the positive properties of the presented method. These were carried out using real ‘big’ data. Models based on the CNN technique allow prediction of PM10 dust concentration with a much smaller mean square error than currently used methods based on linear regression. What's more, the use of neural networks increased Pearson's correlation coefficient (R²) by about 5 percent compared to the linear model. During the simulation, the R² coefficient was 0.92, 0.76, 0.75, 0.73, and 0.73 for 1st, 6th, 12th, 18th, and 24th hour of prediction respectively.

Keywords: air pollution prediction (forecasting), machine learning, regression task, convolution neural networks

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Authors: Gintarė Sauliutė, Gintaras Svecevičius

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Landfill leachates contain a number of persistent pollutants, including heavy metals. They have the ability to spread in ecosystems and accumulate in fish which most of them are classified as top-consumers of trophic chains. Fish are freely swimming organisms; but perhaps, due to their species-specific ecological and behavioral properties, they often prefer the most suitable biotopes and therefore, did not avoid harmful substances or environments. That is why it is necessary to evaluate the persistent pollutant dispersion in hydroecosystem using fish tissue metal concentration. In hydroecosystems of hybrid type (e.g. river-pond-river) the distance from the pollution source could be a perfect indicator of such a kind of metal distribution. The studies were carried out in the Kairiai landfill neighboring hybrid-type ecosystem which is located 5 km east of the Šiauliai City. Fish tissue (gills, liver, and muscle) metal concentration measurements were performed on two types of ecologically-different fishes according to their feeding characteristics: benthophagous (Gibel carp, roach) and predatory (Northern pike, perch). A number of mathematical models (linear, non-linear, using log and other transformations) have been applied in order to identify the most satisfactorily description of the interdependence between fish tissue metal concentration and the distance from the pollution source. However, the only one log-multiple regression model revealed the pattern that the distance from the pollution source is closely and positively correlated with metal concentration in all predatory fish tissues studied (gills, liver, and muscle).

Keywords: bioaccumulation in fish, heavy metals, hydroecosystem, landfill leachate, mathematical model

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Authors: Jessica Bogunovich, Kimberly Greene

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As a grounded theory, Professional Reciprocal Altruism in Education (PRAE) offers an empowering means of understanding how the predominant motivator of those entering the teaching profession, altruism, serves as a shared value to inspire the individual’s personal practice beyond a siloed experience and into one of authentic engagement within the Community of Practice (CoP) of professional educators. The process of aligning one’s personal values, attitudes, and preconceived cultural constructs with those of the CoP, affords the alignment of the authentic and professional self; thus, continuously fostering one’s intrinsic motivation to remain engaged in their individual continuous process of growth and development for their students, community, profession, and themselves.

Keywords: altruism, Community of Practice. cultural constructs, teacher attrition, reciprocal altruism, value congruence

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Authors: Saadet Akbay, Ayşe Nihan Avcı

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The perception of colour is a subjective experience which depends on age, gender, race, cultural and educational backgrounds, etc. of an individual. However, colour perception is also affected by the correlated colour temperature (CCT) of a light source which is considered as one of the most fundamental quantitative lighting characteristics. This study focuses on evaluating colour perception in different CCT of light emitting diodes (LED) lighting. The aim is to compare the inherent colours with the perceived colours under two CCT of ‘warm’ (2700K), and ‘cool’ (4000K) LED lights and to understand how different CTT affect the perception of a colour. Analysis and specifications of colour attributes are made with Natural Colour System (NCS) which is an international colour communication system. The outcome of the study reveals the possible tendencies for perceived colours under different illuminance levels of LED lighting.

Keywords: colour perception, correlated colour temperature, inherent and perceived colour, LED lighting, natural colour system (NCS)

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Authors: Febri Ramadhan, Sigid Hariyadi, Niken Tunjung Murti Pratiwi, Budiman Djoko Said

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The scope about maritime security copes all of the problems emanating from maritime domain. Those problems can give such threats to national security of the state. One of threats taking place nowadays in maritime domain is about pollution. Pollution coming from many sources may increase water-borne disease risk that can cause the instability of national security. Pollution coming from many sources may increase water-borne disease risk. Hence the pollution makes an improper condition of environments for humans and others biota dwelling in the waters. One of the tools that can determine about pollution is by measuring about the water quality of its waters. In this case, what brings the waste and pollutants is there an activity of tidal waves introducing substances or energy into the natural environment. Cengkareng Drain is one of the water channels which is affected by tidal waves. Cengkareng Drain was become an observation area to examine the relation between water quality and tide waves. This research was conducted monthly from July to November 2015. Sampling of water was conducted every ebb and tide in every observation. Pollution index showed that the level of pollution on Cengkareng drain was moderately polluted, with the score about 7.7-8.6. Based on the results of t-test and analysis of similarity, the characteristic of water quality on rising tide does not significantly differ from the characteristic of water quality on ebbing tide. Therefore, we need a proper management as a means to control the pollutants in order to make good maritime security strategy.

Keywords: maritime security, Cengkareng drain, water quality, tidal waves

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Authors: Ali Saeed Alghamdi, Basel Mazen Alsolami, Basel Saeed Alghamdi, Muhanad Saleh Alzahrani Alamri, Salman Anwar Thabet, Abdulhalim J. Kinsara

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Objectives: This study measures the knowledge of the cardiovascular disease among the general population in western regions of Saudi Arabia, and it aimed to increase the level of awareness about cardiovascular diseases among the general population by providing an awareness lecture that included information about the risk factors, major symptoms, and prevention of cardiovascular diseases. The lecture has been attached at the end of the questionnaire. Setting: This study was conducted through an online questionnaire that included our aim and main objectives that targeted the general population in the Western regions of Saudi Arabia (Makkah and Madinah regions). Participants: This study participants were 460 collected through an online questionnaire. Methods: All Saudi citizens and residents who live in the western region of Saudi Arabia aged 18 years and above will be invited to participate voluntarily. A pre-structured questionnaire was designed to collect data on age, gender, marital status, education level, occupation, lifestyle habits, and history of heart diseases, with cardiac symptoms and risk factors sections. Results: The majority of respondents were females (74.8%) and Saudis. The knowledge about cardiovascular disease risk factors was weak. Only (18.5%) scores an excellent response regarding risk factors awareness. Lack of exercise, stress, and obesity were the most known risk factors. Regarding cardiovascular disease symptoms, chest pain scores the highest symptom (87.6%) among other symptoms like dyspnea, syncope, and excessive sweating. Participants revealed a poor awareness regarding cardiovascular disease symptoms also (0.9%). However, preventable factors for cardiovascular diseases were more knowledgeable than others categories in this study (60% fall into excellent knowledge). Smoking cessation, normal cholesterol level, and normal blood pressure score the highest preventable methods (92.2%), (88.6%), and (78.7%) respectively. 83.7% of the participant have attended the awareness lecture, and 99 of the attendees reported that the lecture increased their knowledge about cardiovascular disease. Conclusion: This study discussed the level of community awareness of cardiovascular disease in terms of symptoms, risk factors, and protective factors. We found a huge lack of the participant's level of knowledge about the disease and how to prevent it. Moreover, we measure the prevalence of the comorbidities among our participants (diabetes, hypertension, hypercholesterolemia/ hypertriglyceridemia) and their extent of adherence to their medication. In conclusion, this study not only demonstrates awareness of cardiovascular disease risk factors, symptoms, management, and the association between each domain but also provides educational material. Further educational material and campaigns are required to increase awareness and knowledge about cardiovascular diseases.

Keywords: awareness, cardiovascular diseases, education, prevention, risk factors

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Authors: Forouzan Salehi Fergeni

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Converting the movement intents of a person into commands for action employing brain signals like electroencephalogram signals is a brain-computer interface (BCI) system. When left or right-hand motions are imagined, different patterns of brain activity appear, which can be employed as BCI signals for control. To make better the brain-computer interface (BCI) structures, effective and accurate techniques for increasing the classifying precision of motor imagery (MI) based on electroencephalography (EEG) are greatly needed. Subject dependency and non-stationary are two features of EEG signals. So, EEG signals must be effectively processed before being used in BCI applications. In the present study, after applying an 8 to 30 band-pass filter, a car spatial filter is rendered for the purpose of denoising, and then, a method of analysis of variance is used to select more appropriate and informative channels from a category of a large number of different channels. After ordering channels based on their efficiencies, a sequential forward channel selection is employed to choose just a few reliable ones. Features from two domains of time and wavelet are extracted and shortlisted with the help of a statistical technique, namely the t-test. Finally, the selected features are classified with different machine learning and neural network classifiers being k-nearest neighbor, Probabilistic neural network, support-vector-machine, Extreme learning machine, decision tree, Multi-layer perceptron, and linear discriminant analysis with the purpose of comparing their performance in this application. Utilizing a ten-fold cross-validation approach, tests are performed on a motor imagery dataset found in the BCI competition III. Outcomes demonstrated that the SVM classifier got the greatest classification precision of 97% when compared to the other available approaches. The entire investigative findings confirm that the suggested framework is reliable and computationally effective for the construction of BCI systems and surpasses the existing methods.

Keywords: brain-computer interface, channel selection, motor imagery, support-vector-machine

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Authors: S. Sarumathi, C. Deepadharani, Garimella Archana, S. Dakshayani, D. Logeshwaran, D. Jayakumar, Vijayarangan Natarajan

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The need of the hour for the customers who use a dial-up or a low broadband connection for their internet services is to access HD video data. This can be achieved by developing a new video format using H. 265. This is the latest video codec standard developed by ISO/IEC Moving Picture Experts Group (MPEG) and ITU-T Video Coding Experts Group (VCEG) on April 2013. This new standard for video compression has the potential to deliver higher performance than the earlier standards such as H. 264/AVC. In comparison with H. 264, HEVC offers a clearer, higher quality image at half the original bitrate. At this lower bitrate, it is possible to transmit high definition videos using low bandwidth. It doubles the data compression ratio supporting 8K Ultra HD and resolutions up to 8192×4320. In the proposed model, we design a new video format which supports this H. 265 standard. The major areas of applications in the coming future would lead to enhancements in the performance level of digital television like Tata Sky and Sun Direct, BluRay Discs, Mobile Video, Video Conferencing and Internet and Live Video streaming.

Keywords: access HD video, H. 265 video standard, high performance, high quality image, low bandwidth, new video format, video streaming applications

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Authors: Janani V., Tanika Singh, Bala Subramanian R., Santosh Kumar Sharma

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Higher education across the globe is undergoing a sea change. This has created a varied management of higher education in Indian universities, and therefore, we find no universal law regarding HR policies and practices in these universities. As a result, faculty retention is very low, which is a serious concern for educational leaders such as vice-chancellors or directors working in the higher education sector. We can understand this phenomenon in the light of various management theories, among which theory z proposed by William Ouchi is a prominent one. With this backdrop, the present article strives to contextualize theory z in Indian higher education. For the said purpose, qualitative methodology has been adopted, and accordingly, propositions have been generated. We believe that this article will motivate other researchers to empirically test the generated propositions and thereby contribute in the existing literature.

Keywords: education, managemenet, motivation, Theory X, Theory Y, Theory Z, faculty members, universities, India

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Authors: Chenhao Zhu

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Quantitative mapping is playing a growing role in guiding urban planning, such as using a heat map created by CFX, CFD2000, or Envi-met, to adjust the master plan. However, there is no effective quantitative link between the mappings and planning formation. So, in many cases, the decision-making is still based on the planner's subjective interpretation and understanding of these mappings, which limits the improvement of scientific and accuracy brought by the quantitative mapping. Therefore, in this paper, an effort has been made to give a methodology of building a parametric link between the mapping and planning formation. A parametric planning process based on radiant mapping has been proposed for creating an urban green system. In the first step, a script is written in Grasshopper to build a road network and form the block, while the Ladybug Plug-in is used to conduct a radiant analysis in the form of mapping. Then, the research creatively transforms the radiant mapping from a polygon into a data point matrix, because polygon is hard to engage in the design formation. Next, another script is created to select the main green spaces from the road network based on the criteria of radiant intensity and connect the green spaces' central points to generate a green corridor. After that, a control parameter is introduced to adjust the corridor's form based on the radiant intensity. Finally, a green system containing greenspace and green corridor is generated under the quantitative control of the data matrix. The designer only needs to modify the control parameter according to the relevant research results and actual conditions to realize the optimization of the green system. This method can also be applied to much other mapping-based analysis, such as wind environment analysis, thermal environment analysis, and even environmental sensitivity analysis. The parameterized link between the mapping and planning will bring about a more accurate, objective, and scientific planning.

Keywords: parametric link, mapping, urban green system, radiant intensity, planning strategy, grasshopper

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Authors: M. Ntswane, N. Mbuma, M. Labuschagne, A. Mofokeng, M. Rantso

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Cowpea is an essential legume for the nutrition and health of millions of people in different regions. The production and productivity of the crop are very limited in South Africa due to a lack of adapted and stable genotypes. The improvement of nutritional quality is made possible by manipulating the genes of diverse cowpea genotypes available around the world. Assessing the adaptability and stability of the cowpea mutant genotypes for yield and nutritional quality requires examining them in different environments. The objective of the study was to determine the adaptability and stability of cowpea mutant genotypes under South African conditions and to identify the superior genotypes that combine grain yield components, antioxidants, and nutritional quality. Thirty-one cowpea genotypes were obtained from the Agricultural Research Council grain crops (ARC-GC) and were planted in Glen, Mafikeng, Polokwane, Potchefstroom, Taung, and Vaalharts during the 2021/22 summer cropping season. Significant genotype by location interactions indicated the possibility of genetic improvement of these traits. The genotype plus genotype by environment indicated broad adaptability and stability of mutant genotypes. The principal component analysis identified the association of the genotypes with the traits. Phenotypic correlation analysis showed that Zn and protein content were significant and positively correlated and suggested the possibility of indirect selection of these traits. Results from this study could be used to help plant breeders in making informed decisions and developing nutritionally improved cowpea genotypes with the aim of addressing the challenges of poor nutritional quality.

Keywords: cowpea seeds, adaptability, stability, mineral elements, protein content

Procedia PDF Downloads 104

Authors: E. Oliver, A. Cebolla, A. Dominguez, A. Gonzalez-Segura, E. de la Cruz, S. Albertini, L. Ferrini, K. Kronika, T. Nilsen, R. Baños

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The main objective of MEAL is to develop a pedagogical tool aimed to help teachers and nutritionists (students and professionals) to acquire, train, promote and deliver to children basic nutritional education and healthy eating behaviours competencies. MEAL is focused on eating behaviours and not only in nutritional literacy, and will use new technologies like Information and Communication Technologies (ICTs) and serious games (SG) platforms to consolidate the nutritional competences and habits.

Keywords: nutritional education, pedagogical ICT platform, serious games, training course

Procedia PDF Downloads 521

Authors: Antonio M. Oliveira, Patricia Oliveira-Silva, Jose Matias Alves, Gary McPherson

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The music teaching is oriented towards offering formal music training. Due to its specificities, this vocational program starts at a very young age. Although provided by the State, the offer is limited to 6 schools throughout the country, which means that the vacancies for prospective students are very limited every year. It is therefore crucial that these vacancies be taken by especially motivated children grown within households that offer the ideal setting for success. Some of the instruments used to evaluate musical performance are highly sensitive to specific previous training, what represents a severe validity problem for testing children who have had restricted opportunities for formal training. Moreover, these practices may be unfair because, for instance, they may not reflect the candidates’ music aptitudes. Based on what constitutes a prerequisite for making an excellent music student, researchers in this field have long argued that motivation, task commitment, and parents’ support are as important as ability. Thus, the aim of this study is: (1) to prepare an inventory of admission requirements in Australia, Portugal and Ireland; (2) to examine whether the candidates to music conservatories and parents’ level of motivation, assessed at three evaluation points (i.e., admission, at the end of the first year, and at the end of the second year), correlates positively with the candidates’ progress in learning a musical instrument (i.e., whether motivation at the admission may predict student musicianship); (3) an adaptation of an existing instrument to assess the motivation (i.e., to adapt the items to the music setting, focusing on the motivation for playing a musical instrument). The inclusion criteria are: only children registered in the administrative services to be evaluated for entrance to the conservatory will be accepted for this study. The expected number of participants is fifty (5-6 years old) in all the three frequency schemes: integrated, articulated and supplementary. Revisiting musical admission procedures is of particular importance and relevance to musical education because this debate may bring guidance and assistance about the needed improvement to make the process of admission fairer and more transparent.

Keywords: music learning, music admission requirements, student’s motivation, parent’s motivation

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Authors: Daniel D'Souza, Ping Zou

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The period before, during, and after menopause is a sensitive time for women as they experience intense physical and psychological health changes and symptoms. These changes accompany the hormonal changes that mark the end of a woman’s reproductive age. To help mitigate and cope with these changes, prompt and correct treatment is needed. eHealth has emerged as a branch of telemedicine in the past few decades as an alternate avenue for patients to receive care quickly and conveniently, as it relies on the Internet and computers. Within the past few years, eHealth has also given rise to mHealth, which is the use of personal mobile devices to receive treatment and care. However, there is a lack of study on their use for menopause. This review aimed to review and summarize the literature for eHealth or mHealth and menopause. Several databases related to women’s health and digital health were searched for original studies about eHealth or mHealth and menopause. The search yielded 25 results. The results were generally positive, with these interventions being feasible and having positive effects on physical and psychosocial outcomes. However, several issues were raised regarding their design process that may inadvertently prevent these interventions from addressing the needs of all potential users. Therefore, while eHealth and mHealth certainly represent a future model of healthcare delivery for menopausal women, further research and design modifications are needed before this can happen.

Keywords: eHealth, menopause, mHealth, midlife women

Procedia PDF Downloads 138

Authors: Ricardo Avila, Gabriel Lopes, Vania Vidal, Jose Macedo

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This article offers a approach to the automatic discovery of semantic concepts and links in the domain of Oil Exploration and Production (E&P). Machine learning methods combined with textual pre-processing techniques were used to detect local patterns in texts and, thus, generate new concepts and new semantic links. Even using more specific vocabularies within the oil domain, our approach has achieved satisfactory results, suggesting that the proposal can be applied in other domains and languages, requiring only minor adjustments.

Keywords: semantic links, data mining, linked data, SKOS

Procedia PDF Downloads 174

Authors: Pouya Taraghi, Yong Li, Nader Yoosef-Ghodsi, Muntaseer Kainat, Samer Adeeb

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Buried pipelines play a crucial role in the transportation of energy products such as oil, gas, and various chemical fluids, ensuring their efficient and safe distribution. However, these pipelines are often susceptible to ground movements caused by geohazards like landslides, fault movements, lateral spreading, and more. Such ground movements can lead to strain-induced failures in pipes, resulting in leaks or explosions, leading to fires, financial losses, environmental contamination, and even loss of human life. Therefore, it is essential to study how buried pipelines respond when traversing geohazard-prone areas to assess the potential impact of ground movement on pipeline design. As such, this study introduces an approach called the Physics-Informed Neural Network (PINN) to predict the strain demand in inelastic pipes subjected to permanent ground displacement (PGD). This method uses a deep learning framework that does not require training data and makes it feasible to consider more realistic assumptions regarding existing nonlinearities. It leverages the underlying physics described by differential equations to approximate the solution. The study analyzes various scenarios involving different geohazard types, PGD values, and crossing angles, comparing the predictions with results obtained from finite element methods. The findings demonstrate a good agreement between the results of the proposed method and the finite element method, highlighting its potential as a simulation-free, data-free, and meshless alternative. This study paves the way for further advancements, such as the simulation-free reliability assessment of pipes subjected to PGD, as part of ongoing research that leverages the proposed method.

Keywords: strain demand, inelastic pipe, permanent ground displacement, machine learning, physics-informed neural network

Procedia PDF Downloads 59

Authors: Rajkumar Ghosh

Abstract:

India faces a critical task of water shortage, specifically during dry seasons, which adversely impacts agricultural productivity and food protection. Natural farming, specializing in sustainable practices, demands green water management in smart cities in India. This paper examines how rooftop rainwater harvesting (RRWH) can alleviate water scarcity and support sustainable organic farming practices in India. RRWH emerges as a promising way to increase water availability for the duration of dry intervals and decrease reliance on traditional water sources in smart cities. The look at explores the capacity of RRWH to enhance water use performance, help crop growth, enhance soil health, and promote ecological stability inside the farming ecosystem. The medical paper delves into the advantages, challenges, and implementation techniques of RRWH in organic farming. It addresses demanding situations, including seasonal variability of rainfall, limited rooftop vicinity, and monetary concerns. Moreover, it analyses broader environmental and socio-economic implications of RRWH for sustainable agriculture, emphasizing water conservation, biodiversity protection, and the social properly-being of farming communities. The belief underscores the importance of RRWH as a sustainable solution for reaching the aim of sustainable agriculture in natural farming in India. It emphasizes the want for further studies, policy advocacy, and capacity-building initiatives to promote RRWH adoption and assist the transformation in the direction of sustainable organic farming systems. The paper proposes adaptive strategies to triumph over demanding situations and optimize the advantages of RRWH in organic farming. By way of doing so, India can make vast development in addressing water scarcity issues and making sure a greater resilient and sustainable agricultural future in smart cities.

Keywords: rooftop rainwater harvesting, organic farming, green water management, food protection, ecological stabilty

Procedia PDF Downloads 93

Authors: Sergio Mauricio Pérez López, Luis Rodrigo Valencia Pérez, Juan Manuel Peña Aguilar, Adelina Morita Alexander

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The culture of continuous improvement in organizations is very important as it represents a source of competitive advantage. This article discusses the transfer of knowledge between companies which formed cross-functional teams and used a dynamic model for knowledge creation as a framework. In addition, the article discusses the structure of cognitive assets in companies and the concept of "stickiness" (which is defined as an obstacle to the transfer of knowledge). The purpose of this analysis is to show that an improvement in the attitude of individual members of an organization creates opportunities, and that an exchange of information and knowledge leads to generating continuous improvements in the company as a whole. This article also discusses the importance of creating the proper conditions for sharing tacit knowledge. By narrowing gaps between people, mutual trust can be created and thus contribute to an increase in sharing. The concept of adapting knowledge to new environments will be highlighted, as it is essential for companies to translate and modify information so that such information can fit the context of receiving organizations. Adaptation will ensure that the transfer process is carried out smoothly by preventing "stickiness". When developing the transfer process on cross-functional teams (as opposed to working groups), the team acquires the flexibility and responsiveness necessary to meet objectives. These types of cross-functional teams also generate synergy due to the array of different work backgrounds of their individuals. When synergy is established, a culture of continuous improvement is created.

Keywords: knowledge transfer, continuous improvement, teamwork, cognitive assets

Procedia PDF Downloads 320

Authors: Zafer F. Alshehri

Abstract:

This paper investigated mathematics teachers' knowledge of the effective teaching strategies at the Southern Region of Saudi Arabia. Specifically, it aimed to identify a list of the effective strategies of teaching mathematics; the extent of mathematics teachers' knowledge of these strategies; and the differences (if any) of mathematics teachers' knowledge of these strategies regarding scientific degree, teaching experience, and educational sage. To achieve that, the researcher used the descriptive approach for preparing a list of effective mathematics teaching strategies and developing a questionnaire of a sample of (240) mathematics teachers. As a result, there were differences in teachers' knowledge of the effective teaching strategies, which ranked as a low, and the highest knowledge was in favor of higher degrees. In addition, there were a few recommendations and suggestions for developing mathematics teachers' knowledge of effective teaching strategies, such as involving in workshops of mathematics teaching strategies, integrating technology into mathematics teaching, and using research findings in the instruction process.

Keywords: mathematics teaching knowledge, mathematics teachers, effective mathematics teaching strategies

Procedia PDF Downloads 506

Authors: Yuchen Sharon Sung, Yingjui Tseng

Abstract:

High-rise residential buildings have become the most mainstream housing pattern in the world’s metropolises under the current trend of urbanization. The facades of high-rise buildings are essential elements of the urban landscape. The skins of these facades are important media between the interior and exterior of high- rise buildings. It not only connects between users and environments, but also plays an important functional and aesthetic role. This research involves a study of skins of high-rise residential buildings using the methodology of shape grammar to find out the rules which determine the combinations of the facade patterns and analyze the patterns’ parameters using software Grasshopper. We chose a number of facades of high-rise residential buildings as source to discover the underlying rules and concepts of the generation of facade skins. This research also provides the rules that influence the composition of facade skins. The items of the facade skins, such as windows, balconies, walls, sun visors and metal grilles are treated as elements in the system of facade skins. The compositions of these elements will be categorized and described by logical rules; and the types of high-rise building facade skins will be modelled by Grasshopper. Then a variety of analyzed patterns can also be applied on other facade skins through this parametric mechanism. Using these patterns established in the models, researchers can analyze each single item to do more detail tests and architects can apply each of these items to construct their facades for other buildings through various combinations and permutations. The goal of these models is to develop a mechanism to generate prototypes in order to facilitate generation of various facade skins.

Keywords: facade skin, grasshopper, high-rise residential building, shape grammar

Procedia PDF Downloads 505