Search results for: learning assessment

Authors: Fouzia Qamar, Shahida Hasnain

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The objective of the present study was to evaluate the possible role of Agrobacterium tumefaciens as a possible insect biocontrol agent. Pests selected for the present challenge were adult males of Periplaneta americana and last instar larvae of Pieris brassicae and Spodoptera litura. Different ranges of bacterial doses were selected and tested to score the mortalities of the insects after 24 hours, for the lethal dose estimation studies. Mode of application for the inoculation of the bacteria, was the microinjection technique. The evaluation of the possible entomopathogenic carrying attribute of bacterial Ti plasmid, led to the conclusion that the loss of plasmid was associated with the loss of virulence against target insects.

Keywords: agrobacterium tumefaciens, toxicity assessment, biopesticidal attribute, entomopathogenic agent

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Authors: Pranee Suecharoen, Ratchadaporn Soontornpas, Jaturat Kanpittaya

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Background: Contrast media has an important role for disease diagnosis through detection of pathologies. Contrast media can, however, cause adverse reactions after administration of its agents. Although non-ionic contrast media are commonly used, the incidence of adverse events is relatively low. The most common reactions found (10.5%) were mild and manageable and/or preventable. Pharmacists can play an important role in evaluating adverse reactions, including awareness of the specific preparation and the type of adverse reaction. As most common types of adverse reactions are idiosyncratic or pseudo-allergic reactions, common standards need to be established to prevent and control adverse reactions promptly and effectively. Objective: To measure the effect of using tools for symptom evaluation in order to reduce the severity, or prevent the occurrence, of adverse reactions from contrast media. Methods: Retrospective review descriptive research with data collected on adverse reactions assessment and Naranjo’s algorithm between June 2015 and May 2016. Results: 158 patients (10.53%) had adverse reactions. Of the 1,500 participants with an adverse event evaluation, 137 (9.13%) had a mild adverse reaction, including hives, nausea, vomiting, dizziness, and headache. These types of symptoms can be treated (i.e., with antihistamines, anti-emetics) and the patient recovers completely within one day. The group with moderate adverse reactions, numbering 18 cases (1.2%), had hypertension or hypotension, and shortness of breath. Severe adverse reactions numbered 3 cases (0.2%) and included swelling of the larynx, cardiac arrest, and loss of consciousness, requiring immediate treatment. No other complications under close medical supervision were recorded (i.e., corticosteroids use, epinephrine, dopamine, atropine, or life-saving devices). Using the guideline, therapies are divided into general and specific and are performed according to the severity, risk factors and ingestion of contrast media agents. Patients who have high-risk factors were screened and treated (i.e., prophylactic premedication) for prevention of severe adverse reactions, especially those with renal failure. Thus, awareness for the need for prescreening of different risk factors is necessary for early recognition and prompt treatment. Conclusion: Studying adverse reactions can be used to develop a model for reducing the level of severity and setting a guideline for a standardized, multidisciplinary approach to adverse reactions.

Keywords: role of pharmacist, management of adverse reactions, guideline for contrast media, non-ionic contrast media

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Authors: Gyoomi Kim, Jiyoung Bae

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In the field of language education research, there are not many tries to empirically examine learners’ acceptance behavior and related factors of mobile-assisted language learning (MALL). This study is one of the few attempts to propose an integrated theoretical framework that explains MALL users’ acceptance behavior and potential factors. Constructs from technology acceptance model (TAM) and MALL research are tested in the integrated framework. Based on previous studies, a hypothetical model was developed. Four external variables related to the MALL user’s acceptance behavior were selected: subjective norm, content reliability, interactivity, self-regulation. The model was also composed of four other constructs: two latent variables, perceived ease of use and perceived usefulness, were considered as cognitive constructs; attitude toward MALL as an affective construct; behavioral intention to use MALL as a behavioral construct. The participants were 438 undergraduate students who enrolled in an intensive English program at one university in Korea. This particular program was held in January 2018 using the vacation period. The students were given eight hours of English classes each day from Monday to Friday for four weeks and asked to complete MALL courses for practice outside the classroom. Therefore, all participants experienced blended MALL environment. The instrument was a self-response questionnaire, and each construct was measured by five questions. Once the questionnaire was developed, it was distributed to the participants at the final ceremony of the intensive program in order to collect the data from a large number of the participants at a time. The data showed significant evidence to support the hypothetical model. The results confirmed through structural equation modeling analysis are as follows: First, four external variables such as subjective norm, content reliability, interactivity, and self-regulation significantly affected perceived ease of use. Second, subjective norm, content reliability, self-regulation, perceived ease of use significantly affected perceived usefulness. Third, perceived usefulness and perceived ease of use significantly affected attitude toward MALL. Fourth, attitude toward MALL and perceived usefulness significantly affected behavioral intention to use MALL. These results implied that the integrated framework from TAM and MALL could be useful when adopting MALL environment to university students or adult English learners. Key constructs except interactivity showed significant relationships with one another and had direct and indirect impacts on MALL user’s acceptance behavior. Therefore, the constructs and validated metrics is valuable for language researchers and educators who are interested in MALL.

Keywords: blended MALL, learner factors/variables, mobile-assisted language learning, MALL, technology acceptance model, TAM, theoretical framework

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Authors: Yujiang Wu

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As electrical machine (e-machine) power density re-querulents become more stringent in vehicle electrification, mounting a temperature sensor for e-machine stator windings becomes increasingly difficult. This can lead to higher manufacturing costs, complicated harnesses, and reduced reliability. In this paper, we propose a deep-learning method for predicting electric machine winding temperature, which can either replace the sensor entirely or serve as a backup to the existing sensor. We compare the performance of our method, the stateful long short-term memory networks (LSTM) with truncated backpropagation through time (TBTT), with that of linear regression, as well as stateless LSTM with/without residual connection. Our results demonstrate the strength of combining stateful LSTM and TBTT in tackling nonlinear time series prediction problems with long sequence lengths. Additionally, in industrial applications, high-temperature region prediction accuracy is more important because winding temperature sensing is typically used for derating machine power when the temperature is high. To evaluate the performance of our algorithm, we developed a temperature-stratified MSE. We propose a simple but effective data preprocessing trick to improve the high-temperature region prediction accuracy. Our experimental results demonstrate the effectiveness of our proposed method in accurately predicting winding temperature, particularly in high-temperature regions, while also reducing manufacturing costs and improving reliability.

Keywords: deep learning, electrical machine, functional safety, long short-term memory networks (LSTM), thermal management, time series prediction

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Authors: Anthony Halog

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In the coming decades the world that we know today will be drastically transformed. Population and economic growth, particularly in developing countries, are radically changing the demand for food and natural resources. Due to the transformations caused by these megatrends, especially economic growth which is rapidly expanding the middle class and changing consumption patterns worldwide, it is expected that this will result to an increase of approximately 40 percent in the demand for food, water, energy and other resources in the next decades. To fulfill this demand in a sustainable and efficient manner while avoiding food and water scarcity as well as environmental catastrophes in the near future, some industries, particularly the ones involved in food and energy production, have to drastically change its current production systems towards circular and green economy. In Australia, the agri-food industry has played a very important role in the scenario described above. It is one of the major food exporters in the world, supplying fast growing international markets in Asia and the Middle East. Though the Australian food supply chains are economically and technologically developed, it has been facing enduring challenges about its international competitiveness and environmental burdens caused by its production processes. An integrated framework for sustainability assessment is needed to precisely identify inefficiencies and environmental impacts created during food production processes. This research proposes a combination of industrial ecology and systems science based methods and tools intending to develop a novel and useful methodological framework for life cycle sustainability analysis of the agri-food industry. The presentation highlights circular economy paradigm aiming to implement sustainable industrial processes to transform the current industrial model of agri-food supply chains. The results are expected to support government policy makers, business decision makers and other stakeholders involved in agri-food-energy production system in pursuit of green and circular economy. The framework will assist future life cycle and integrated sustainability analysis and eco-redesign of food and other industrial systems.

Keywords: circular economy, eco-efficiency, agri-food systems, green economy, life cycle sustainability assessment

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Authors: Ruiyuan Wang, Jing Han, Bruno Di Biase, Mark Antoniou

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The purpose of this study is to explore the relationship between working memory (WM) capacity and Chinese-English consecutive interpreting (CI) performance in interpreting learners with different study abroad experience (SAE). Such relationship is not well understood. This study also examines whether Chinese interpreting learners with SAE in English-speaking countries, demonstrate a better performance in inflectional morphology and agreement, notoriously unstable in Chinese speakers of English L2, in their interpreting output than learners without SAE. Fifty Chinese university students, majoring in Chinese-English Interpreting, were recruited in Australia (n=25) and China (n=25). The two groups matched in age, language proficiency, and interpreting training period. Study abroad (SA) group has been studying in an English-speaking country (Australia) for over 12 months, and none of the students recruited in China (the no study abroad = NSA group) had ever studied or lived in an English-speaking country. Data on language proficiency and training background were collected via a questionnaire. Lexical retrieval performance and working memory (WM) capacity data were collected experimentally, and finally, interpreting data was elicited via a direct CI task. Main results of the study show that WM significantly correlated with participants' CI performance independently of learning context. Moreover, SA outperformed NSA learners in terms of subject-verb number agreement. Apart from that, WM capacity was also found to correlate significantly with their morphosyntactic accuracy. This paper sheds some light on the relationship between study abroad, WM capacity, and CI performance. Exploring the effect of study abroad on interpreting trainees and how various important factors correlate may help interpreting educators bring forward more targeted teaching paradigms for participants with different learning experiences.

Keywords: study abroad experience, consecutive interpreting, working memory, inflectional agreement

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Authors: Hasibul Kabir, Samin Shahriar Tokey, Md. Tofazzal Hossain

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One of the most necessary things in the present time is raising social awareness about global warming and climate change among the people. Though many types of mediums and techniques have been used to teach people about this global phenomenon, there are still more effective ways to reach people with useful information about global warming. As many traditional methods to teach people about global warming and climate change did not work well, video games were overdue. To learn how effective a video game can be in this regard, we developed a Video game, "Historia's Nightmare," that teaches people about Global warming and climate change. The game was designed to entertain people and give them an idea about the reasons and consequences of global warming and climate change while not being like traditional educational games. The game threw a mini quiz consisting of two MCQs based on the information shown in the game, where a gamer had to pass the quiz to reach the next level. We published the game on different platforms to let all types of people play and complete our experiment effectively. The game continuously communicated with our server to send data about gamers' performance. We observed the data, including the participants' performance, time spent, quiz score, and the in-game feedback on a regular basis, and finally came to a verdict. In our experiment, we have found that most participants positively accepted the game and learned something new. The participants who spent more on our game performed better in both quiz and the game. Our experiment's result demonstrates that video games can be a great way to teach people something, particularly to raise social awareness about global warming and climate change. It also demonstrates that the game can be a significant element in education and learning improvement.

Keywords: video game, global warming, social awareness, climate change, education, feedback

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Authors: Takatoshi Ishii, Koji Kimita, Keiichi Muramatsu, Yoshiki Shimomura

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To increase the quality of learning, teacher and learner need mutual effort for realization of educational value. For this purpose, we need to manage the co-creational education among teacher and learners. In this research, we try to find a feature of co-creational education. To be more precise, we analyzed learners’ reports by natural language processing, and extract some features that describe the state of the co-creational education.

Keywords: co-creational education, e-portfolios, ICT integration, latent dirichlet allocation

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Authors: Francis C. Emejeamara, Alison S. Tomlin, James Gooding

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Due to the highly turbulent nature of urban air flows, and by virtue of the fact that turbines are likely to be located within the roughness sublayer of the urban boundary layer, proposed urban wind installations are faced with major challenges compared to rural installations. The challenge of operating within turbulent winds can however, be counteracted by the development of suitable gust tracking solutions. In order to assess the cost effectiveness of such controls, a detailed understanding of the urban wind resource, including its turbulent characteristics, is required. Estimating the ambient turbulence and total kinetic energy available at different control response times is essential in evaluating the potential performance of wind systems within the urban environment should effective control solutions be employed. However, high resolution wind measurements within the urban roughness sub-layer are uncommon, and detailed CFD modelling approaches are too computationally expensive to apply routinely on a city wide scale. This paper therefore presents an alternative semi-empirical methodology for estimating the excess energy content (EEC) present in the complex and gusty urban wind. An analytical methodology for predicting the total wind energy available at a potential turbine site is proposed by assessing the relationship between turbulence intensities and EEC, for different control response times. The semi-empirical model is then incorporated with an analytical methodology that was initially developed to predict mean wind speeds at various heights within the built environment based on detailed mapping of its aerodynamic characteristics. Based on the current methodology, additional estimates of turbulence intensities and EEC allow a more complete assessment of the available wind resource. The methodology is applied to 4 UK cities with results showing the potential of mapping turbulence intensities and the total wind energy available at different heights within each city. Considering the effect of ambient turbulence and choice of wind system, the wind resource over neighbourhood regions (of 250 m uniform resolution) and building rooftops within the 4 cities were assessed with results highlighting the promise of mapping potential turbine sites within each city.

Keywords: excess energy content, small-scale wind, turbulence intensity, urban wind energy, wind resource assessment

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Authors: Sherry Junette Tagle

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Extensive research continues to prove the positive effects of home and school collaborations in education. Although parent involvement programs in Benguet, Philippines are in place, the impact has yet to affect the current aggregate performance of elementary pupils. This study describes the involvement of public elementary teachers and parents along Epstein’s types of involvement using the sequential explanatory design. Survey and interview results show that teachers place greater value on activities that cater to communicating, volunteering, learning at home and decision making. On the other hand, parents are actively involved in all six types and value the importance of their involvement in school to their child’s schooling. Parents of grades 1-4 pupils significantly give importance to communicating activities to offset difficulties encountered by young pupils while parents of grades 5-6 pupils, have declining interest in volunteering and learning at home activities citing older children as being more independent to do teacher-assigned tasks. Teachers, compared to the other respondent groups, significantly place higher value on the importance of parent leaders as their partners in implementing school activities. In general, involvement of parents and teachers in home-school activities is intensive in the lower grade levels and decreases as their child progresses through school. A recommended program for future collaborations of the Philippine’s Department of Education has been formulated to diversify existing activities and elicit greater participation among the school’s stakeholders to achieve holistic development of the pupils and ultimately improve pupils’ school aggregate performance.

Keywords: Epstein's types of involvement, community collaborations, home and school partnerships, parent involvement

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Authors: Abdul Khalique Baloch, Ali Okatan

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The quality analysis of food and vegetable from image is hot topic now a day, where researchers make them better then pervious findings through different technique and methods. In this research we have review the literature, and find gape from them, and suggest better proposed approach, design the algorithm, developed a software to measure the quality from images, where accuracy of image show better results, and compare the results with Perouse work done so for. The Application we uses an open-source dataset and python language with tensor flow lite framework. In this research we focus to sort food and vegetable from image, in the images, the application can sorts and make them grading after process the images, it could create less errors them human base sorting errors by manual grading. Digital pictures datasets were created. The collected images arranged by classes. The classification accuracy of the system was about 94%. As fruits and vegetables play main role in day-to-day life, the quality of fruits and vegetables is necessary in evaluating agricultural produce, the customer always buy good quality fruits and vegetables. This document is about quality detection of fruit and vegetables using images. Most of customers suffering due to unhealthy foods and vegetables by suppliers, so there is no proper quality measurement level followed by hotel managements. it have developed software to measure the quality of the fruits and vegetables by using images, it will tell you how is your fruits and vegetables are fresh or rotten. Some algorithms reviewed in this thesis including digital images, ResNet, VGG16, CNN and Transfer Learning grading feature extraction. This application used an open source dataset of images and language used python, and designs a framework of system.

Keywords: deep learning, computer vision, image processing, rotten fruit detection, fruits quality criteria, vegetables quality criteria

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Authors: Getalem E. Haylia

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The Ribb dam is one of the irrigation projects in the Upper Blue Nile basin, Ethiopia, to irrigate the Fogera plain. Reservoir sedimentation is a major problem because it reduces the useful reservoir capacity by the accumulation of sediments coming from the watersheds. Estimates of sediment yield are needed for studies of reservoir sedimentation and planning of soil and water conservation measures. The objective of this study was to simulate the Ribb dam catchment sediment yield using SWAT model and to estimate Ribb reservoir effective life according to trap efficiency methods. The Ribb dam catchment is found in North Western part of Ethiopia highlands, and it belongs to the upper Blue Nile and Lake Tana basins. Soil and Water Assessment Tool (SWAT) was selected to simulate flow and sediment yield in the Ribb dam catchment. The model sensitivity, calibration, and validation analysis at Ambo Bahir site were performed with Sequential Uncertainty Fitting (SUFI-2). The flow data at this site was obtained by transforming the Lower Ribb gauge station (2002-2013) flow data using Area Ratio Method. The sediment load was derived based on the sediment concentration yield curve of Ambo site. Stream flow results showed that the Nash-Sutcliffe efficiency coefficient (NSE) was 0.81 and the coefficient of determination (R²) was 0.86 in calibration period (2004-2010) and, 0.74 and 0.77 in validation period (2011-2013), respectively. Using the same periods, the NS and R² for the sediment load calibration were 0.85 and 0.79 and, for the validation, it became 0.83 and 0.78, respectively. The simulated average daily flow rate and sediment yield generated from Ribb dam watershed were 3.38 m³/s and 1772.96 tons/km²/yr, respectively. The effective life of Ribb reservoir was estimated using the developed empirical methods of the Brune (1953), Churchill (1948) and Brown (1958) methods and found to be 30, 38 and 29 years respectively. To conclude, massive sediment comes from the steep slope agricultural areas, and approximately 98-100% of this incoming annual sediment loads have been trapped by the Ribb reservoir. In Ribb catchment, as well as reservoir systematic and thorough consideration of technical, social, environmental, and catchment managements and practices should be made to lengthen the useful life of Ribb reservoir.

Keywords: catchment, reservoir effective life, reservoir sedimentation, Ribb, sediment yield, SWAT model

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Authors: A. O. Abulibdeh

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The aim of this study is to investigate and compare the changes in the Land Surface Temperature (LST) as a function of urbanization, particularly land use/land cover changes, in three cities in the UAE, mainly Abu Dhabi, Dubai, and Al Ain. The scale of this assessment will be at the macro- and micro-levels. At the macro-level, a comparative assessment will take place to compare between the four cities in the UAE. At the micro-level, the study will compare between the effects of different land use/land cover on the LST. This will provide a clear and quantitative city-specific information related to the relationship between urbanization and local spatial intra-urban LST variation in three cities in the UAE. The main objectives of this study are 1) to investigate the development of LST on the macro- and micro-level between and in three cities in the UAE over two decades time period, 2) to examine the impact of different types of land use/land cover on the spatial distribution of LST. Because these three cities are facing harsh arid climate, it is hypothesized that (1) urbanization is affecting and connected to the spatial changes in LST; (2) different land use/land cover have different impact on the LST; and (3) changes in spatial configuration of land use and vegetation concentration over time would control urban microclimate on a city scale and control macroclimate on the country scale. This study will be carried out over a 20-year period (1996-2016) and throughout the whole year. The study will compare between two distinct periods with different thermal characteristics which are the cool/cold period from November to March and warm/hot period between April and October. The best practice research method for this topic is to use remote sensing data to target different aspects of natural and anthropogenic systems impacts. The project will follow classical remote sensing and mapping techniques to investigate the impact of urbanization, mainly changes in land use/land cover, on LST. The investigation in this study will be performed in two stages. Stage one remote sensing data will be used to investigate the impact of urbanization on LST on a macroclimate level where the LST and Urban Heat Island (UHI) will be compared in the three cities using data from the past two decades. Stage two will investigate the impact on microclimate scale by investigating the LST and UHI using a particular land use/land cover type. In both stages, an LST and urban land cover maps will be generated over the study area. The outcome of this study should represent an important contribution to recent urban climate studies, particularly in the UAE. Based on the aim and objectives of this study, the expected outcomes are as follow: i) to determine the increase or decrease of LST as a result of urbanization in these four cities, ii) to determine the effect of different land uses/land covers on increasing or decreasing the LST.

Keywords: land use/land cover, global warming, land surface temperature, remote sensing

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Authors: Castillo-Acevedo J, Mena-Rivero R, Silva-Poot H

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In Mexico, as largely of the developing countries, the rural housing is a study object, since the diversity of constructive idiosyncrasies for locality, involves various factors that make it vulnerable; an important aspect of study is the progressive deterioration that is seen in the rural housing. Various social programs, contribute financial resources in the field of housing to provide support for families living in rural areas, however, they do not provide a coordination with the self-construction that is usually the way in which is built in these areas. The present study, exposes the physical situation and an economic assessment that presents the rural self-constructed housing in three rural communities in the south of the state of Quintana Roo, Mexico, which were built with funding from federal social programs. The information compilation was carried out in a period of seven months in which there was used the intentional sampling of typical cases, where the object study was the housing constructed with supports of the program “Rural Housing” between the year 2009 and 2014. Instruments were used as the interview, ballot papers of observation, ballot papers of technical verification and various measuring equipment laboratory for the classification of pathologies; for the determination of some pathologies constructive Mexican standards were applied how NMX-C-192-ONNCCE, NMX-C-111-ONNCCE, NMX-C-404-ONNCCE and finally used the software of Opus CMS ® with the help of tables of the National Consumer Price Index (CPI) for update of costs and wages according to the line of being applied in Mexico, were used for an economic valuation. The results show 11 different constructive pathologies and exposes greater presence with the 22.50% to the segregation of the concrete; the economic assessment shows that 80% of self-constructed housing, exceed the cost of construction it would have compared to a similar dwelling built by a construction company; It is also exposed to the 46.10% of the universe of study represent economic losses in materials to the social activities by houses not built. The system of self-construction used by the social programs, affect to some extent the program objectives applied in underserved areas, as implicit and additional costs affect the economic capacity of beneficiaries who invest time and effort in an activity that are not specialists, which this research provides foundations for sustainable alternatives or possibly eliminate the practice of self-construction of implemented social programs in marginalized rural communities in the south of state of Quintana Roo, Mexico.

Keywords: economic valuation, pathologies constructive, rural housing, social programs

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Authors: Yasmin Hussein Embaby

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Introduction: Athletic Training has its essentials, rules, and methods that help individual in reaching the maximum possible athletic level during the exercised physical activity, therefore; it is important for those working in athletic field to recognize and understand what is going on inside our bodies. This will show the close relationship between physiology and athletic training as the science that explains the various changes that happen to respond to the practice of physical activities. Swimming is one of the water sports that play a major role in influencing the full compatibility of body parts and its systems during the practice of different swimming methods, which uses aqueous to move. It is the initial nucleus in swimming learning and through which the beginner gain a sense of security, safety and the ability to move in aqueous by learning basic skills. Research Methodology: The researcher used the experimental methodology by using pre and post measurement on two equal groups (experimental – control) because it is appropriate for the research. Conclusions: Through the results and information found by the researcher, and in light of the related studies, theoretical readings and the statistical treatments of data; the researcher reached the following conclusions: 1. Muscle relaxation exercises have a positive effect on performance level in crawl swimming and on endorphin hormone as it helps in increasing its normal rater in body, the improvement percentage for experimental group in the relaxation ability, level of endorphin hormone exceeds those of control group. 2. The validity of muscle relaxation exercises proposed for the application, which achieved its objectives, namely increasing the level of endorphin hormone in the body; where research results showed a statistically significant difference in the level of endorphin hormone in favor of the experimental sample.

Keywords: beginners, endorphin hormone, relaxing exercises, swimming

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Authors: Areej Isam Barham

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Developing students’ number sense is an essential element in the learning of mathematics. Number sense is one of the foundational ideas in mathematics where students need to understand numbers, representing them in different ways, and realize the relationships among numbers. Number sense also reflects students’ understanding of the meaning of operations, how they related to one another, how to compute fluently and make reasonable estimates. Developing students’ number sense in the mathematics classroom requires good preparation for mathematics teachers, those who will direct their students towards the real understanding of numbers and its implementation in the learning of mathematics. This study describes the development of elementary prospective mathematics teachers’ number sense through a mathematics teaching methods course at Qatar University. The study examined the effect of using the Lesh model in enhancing mathematics prospective teachers’ number sense. Thirty-nine elementary prospective mathematics teachers involved in the current study. The study followed an experimental research approach, and quantitative research methods were used to answer the research questions. Pre-post number sense test was constructed and implemented before and after teaching by using the Lesh model. Data were analyzed using Statistical Packages for Social Sciences (SPSS). Descriptive data analysis and t-test were used to examine the impact of using the Lesh model in enhancing prospective teachers’ number sense. Finding of the study indicated poor number sense and limited numeracy skills before implementing the use of the Lesh model, which highly demonstrate the importance of the study. The results of the study also revealed a positive impact on the use of the Lesh model in enhancing prospective teachers’ number sense with statistically significant differences. The discussion of the study addresses different features and issues related to the participants’ number sense. In light of the study, the research presents recommendations and suggestions for the future development of mathematics prospective teachers’ number sense.

Keywords: number sense, Lesh model, prospective mathematics teachers, development of number sense

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Authors: Andrew Hall, Paul Clarkson

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Climate change is predicted to increase the number of extreme weather events intensifying the strain on Railway Earthworks. This paper describes the use of Distributed Rayleigh Sensing to monitor low frequency activity on a vulnerable earthworks sectionprone to landslides alongside a railway line in Northern Spain. The vulnerable slope is instrumented with conventional slope stability sensors allowing an assessment to be conducted of the application of Distributed Rayleigh Sensing as an earthwork condition monitoring tool to enhance the resilience of railway networks.

Keywords: condition monitoring, railway earthworks, distributed rayleigh sensing, climate change

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Authors: Marcelo Pereira Introini

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The global value chains (GVC) approach contributes to a better understanding of the international production organization amid globalization’s second unbundling from the 1970s on. Mainly due to the tools that help to understand the importance of critical competences, technological capabilities, and functions performed by each player, GVC research flourished in recent years, rooted in discussing the possibilities of integration and repositioning along regional and global value chains. Regarding this context, part of the literature endorsed a more optimistic view that engaging in fragmented production networks could represent learning opportunities for developing countries’ firms, since the relationship with transnational corporations could allow them build skills and competences. Increasing recognition that GVCs are based on asymmetric power relations provided another sight about benefits, costs, and development possibilities though. Once leading companies tend to restrict the replication of their technologies and capabilities by their suppliers, alternative strategies beyond the functional specialization, seen as a way to integrate value chains, began to be broadly highlighted. This paper organizes a coherent narrative about the shortcomings of the GVC analytical framework, while recognizing its multidimensional contributions and recent developments. We adopt two different and complementary perspectives to explore the idea of integration in the international production. On one hand, we emphasize obstacles beyond production components, analyzing the role played by intangible assets and intellectual property regimes. On the other hand, we consider the importance of domestic production and innovation systems for technological development. In order to provide a deeper understanding of the restrictions on technological learning of developing countries’ firms, we firstly build from the notion of intellectual monopoly to analyze how flagship companies can prevent subordinated firms from improving their positions in fragmented production networks. Based on intellectual property protection regimes we discuss the increasing asymmetries between these players and the decreasing access of part of them to strategic intangible assets. Second, we debate the role of productive-technological ecosystems and of interactive and systemic technological development processes, as concepts of the Innovation Systems approach. Supporting the idea that not only endogenous advantages are important for international competition of developing countries’ firms, but also that the building of these advantages itself can be a source of technological learning, we focus on local efforts as a crucial element, which is not replaceable for technology imported from abroad. Finally, the paper contributes to the discussion about technological development as a two-dimensional dynamic. If GVC analysis tends to underline a company-based perspective, stressing the learning opportunities associated to GVC integration, historical involvement of national States brings up the debate about technology as a central aspect of interstate disputes. In this sense, technology is seen as part of military modernization before being also used in civil contexts, what presupposes its role for national security and productive autonomy strategies. From this outlook, it is important to consider it as an asset that, incorporated in sophisticated machinery, can be the target of state policies besides the protection provided by intellectual property regimes, such as in export controls and inward-investment restrictions.

Keywords: global value chains, innovation systems, intellectual monopoly, technological development

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Authors: A.Halim Sahelan, Mohd Halid Abu, Jamaluddin Hashim, Zulisman Maksom, Mohd Afif Md Nasir

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This study aims to assess the students' needs for the tour planning e-guide. The study is developing on the contribution and importance of the Educational Tour Planning Guide (ETP) is a multimedia courseware as one of the effective methods in teaching and learning of environmental science among the students in primary schools of the Ministry of Education, Malaysia. It is to provide the student with knowledge and experience about tourism, environmental science activities and process. E-guide to ETP also hopes to strengthen the student understanding toward the subject learns in the tourism environmental science. In order to assess the student's needs on the e-Guide to Educational Tour Planning in Environmental Science, the study has produced a similar e-Guide to ETP in the form as a courseware to be tested during the study. The study has involved several steps in order to be completed. It is such as the formulation of the problem, the review of the literature, the formulation of the study methodology, the production of the e-Guide to ETP, field survey and finally the analyses and discussion made on the data gathered during the study. The survey has involved 100 respondents among the students in standard six primary schools in Kluang Johor. Through the findings, the study indicates that the currently tested product is acceptable among the students in learning environmental science as a guide to plan for the tour. The findings also show a slight difference between the respondents who are using the e-Guide to ETP, and those who are not on the basis of the e-Guide to ETP results. Due the important for the study, the researcher hopes to be having a fair discussion and excellence, recommendation for the development of the product of the current study. This report is written also important to provide a written reference for the future related study.

Keywords: the tour planning e-guide, the Educational Tour Planning Guide, environmental science, multimedia course ware

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Authors: E. N. Jansen van Vuuren

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When visiting Foundation Phase (FP) students during their Teaching Practice at schools in rural Mpumalanga, the lack of music education is evident through the absence of musical sounds, with the exception of a limited repertoire of songs that are sung by all classes everywhere you go. The absence of music teaching resources such as posters and music instruments add to the perception that generalist teachers in the FP are not teaching music. Pre-service students also acknowledge that they have never seen a music class being taught during their teaching practice visits at schools. This lack of music mentoring impacts the quality of teachers who are about to enter the workforce and ultimately results in the perpetuation of no music education in many rural schools. The situation in more affluent schools present a contrasting picture with music education being given a high priority and generalist teachers often being supported by music specialists, paid for by the parents. When student teachers start their music course, they have limited knowledge to use as a foundation for their studies. The aim of the study was to ascertain the music knowledge that students gained throughout their school careers so that the curriculum could be adapted to suit their needs. By knowing exactly what pre-service teachers know about music, the limited tuition time at tertiary level can be used in the most suitable manner and concentrate on filling the knowledge gaps. Many scholars write about the decline of music education in South African schools and mention reasons, but the exact music knowledge void amongst students does not feature in the studies. Knowing the parameters of students’ music knowledge will empower lecturers to restructure their curricula to meet the needs of pre-service students. The research question asks, “what is the extent of the music void amongst rural pre-service teachers in a B.Ed. FP course at an African university?” This action research was done using a pragmatic paradigm and mixed methodology. First year students in the cohort studying for a B.Ed. in FP were requested to complete an online baseline assessment to determine the status quo. This assessment was compiled using the CAPS music content for Grade R to 9. The data was sorted using the elements of music as a framework. Findings indicate that students do not have a suitable foundation in music education despite supposedly having had music tuition from grade R to grade 9. Knowing the content required to fill the lack of knowledge provides academics with valuable information to amend their curricula and to ensure that future teachers will be able to provide rural learners with the same foundations in music as those received by learners in more affluent schools. It is only then that the rich music culture of the African continent will thrive.

Keywords: generalist educators, music education, music curriculum, pre-service teachers

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Authors: Kali Prasad Sarma

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Indiscriminate disposal of municipal solid waste (MSW) in open dumping site is a common scenario in developing countries like India which poses a risk to the environment as well as human health. The objective of the present investigation was to find out the concentration of heavy metals (Pb, Cr, Ni, Mn, Zn, Cu, and Cd) and other physicochemical parameters of leachate and soil collected from an open dumping site of Tezpur town, Assam, India and its associated potential ecological risk. Tezpur is an urban agglomeration coming under the category of Class I UAs/Towns with a population of 105,377 as per data released by Government of India for Census 2011. Impact of the leachate on the groundwater was also addressed in our study. The concentrations of heavy metals were determined using ICP-OES. Energy dispersive X-Ray (SEM-EDS) microanalysis was also conducted to see the presence of the studied metals in the soil. X-Ray diffraction analysis (XRD) and Fourier Transform Infrared (FTIR) spectroscopy were also used to identify dominant minerals present in the soil samples. The trend of measured heavy metals in the soil samples was found in the following order: Mn > Pb > Cu > Zn > Cr > Ni > Cd. The assessment of heavy metal contamination in the soil was carried out by calculating enrichment factor (EF), geo-accumulation index (Igeo), contamination factor (Cfi), degree of contamination (Cd), pollution load index (PLI) and ecological risk factor (Eri). The study showed that the concentrations of Pb, Cu, and Cd were much higher than their respective average shale value and the EF of the soil samples depicted very severe enrichment for Pb, Cu, and Cd; moderate enrichment for Cr and Zn. Calculated Igeo values indicated that the soil is moderate to strongly contaminated with Pb and uncontaminated to moderately contaminated with Cd and Cu. The Cfi value for Pb indicates a very strong contamination level of the metal in the soil. The Cfi values for Cu and Cd were 2.37 and 1.65 respectively indicating moderate contamination level. To apportion the possible sources of heavy metal contamination in soil, principal components analysis (PCA) has been adopted. From the leachate, heavy metals are accumulated at the dumping site soil which could easily percolate through the soil and reach the groundwater. The possible relation of groundwater contamination due to leachate percolation was examined by analyzing the heavy metal concentrations in groundwater with respect to distance from the dumping site. The concentrations of Cd and Pb in groundwater (at a distance of 20m from dumping site) exceeded the permissible limit for drinking water as set by WHO. Occurrence of elevated concentration of potentially toxic heavy metals such as Pb and Cd in groundwater and soil are much environmental concern as it is detrimental to human health and ecosystem.

Keywords: groundwater, heavy metal contamination, leachate, open dumping site

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Authors: Biljana Marković

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Social networks are an integral part of our everyday lives, becoming an indispensable medium for communication in personal and business environments. New forms and ways of communication change the general mindset and significantly affect the quality of life of individuals. Quality of life is perceived as an abstract term, but often people are not aware that they directly affect the quality of their own lives, making minor but significant everyday choices and decisions. Quality of life can be defined broadly, but in the widest sense, it involves a subjective sense of satisfaction with one's life. Scientific knowledge about the impact of social networks on self-assessment of the quality of life of individuals is only just beginning to be researched. Available research indicates potential benefits as well as a number of disadvantages. In the context of the previous claims, the focus of the study conducted by the authors of this paper focuses on analyzing the impact of social networks on individual’s self-assessment of quality of life and the correlation between time spent on social networks, and the choice of content that individuals choose to share to present themselves. Moreover, it is aimed to explain how much and in what ways they critically judge the lives of others online. The research aspires to show the positive as well as negative aspects that social networks, primarily Facebook and Instagram, have on creating a picture of individuals and how they compare themselves with others. The topic of this paper is based on quantitative research conducted on a representative sample. An analysis of the results of the survey conducted online has elaborated a hypothesis which claims that content shared by individuals on social networks influences the image they create about themselves. A comparative analysis of the results obtained with the results of similar research has led to the conclusion about the synergistic influence of social networks on the feeling of the quality of life of respondents. The originality of this work is reflected in the approach of conducting research by examining attitudes about an individual's life satisfaction, the way he or she creates a picture of himself/herself through social networks, the extent to which he/she compares herself/himself with others, and what social media applications he/she uses. At the cognitive level, scientific contributions were made through the development of information concepts on quality of life, and at the methodological level through the development of an original methodology for qualitative alignment of respondents' attitudes using statistical analysis. Furthermore, at the practical level through the application of concepts in assessing the creation of self-image and the image of others through social networks.

Keywords: quality of life, social media, self image, influence of social media

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Authors: Shreyas Kumar, Mili Shangari

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Integrating artificial intelligence (AI) in the cyber insurance sector represents a significant advancement, offering the potential to revolutionize risk assessment, fraud detection, and claims processing. However, this integration introduces a range of regulatory and economic challenges that must be addressed to ensure responsible and effective deployment of AI technologies. This paper examines the multifaceted regulatory landscape governing AI in cyber insurance and explores the economic implications of compliance, innovation, and market dynamics. AI's capabilities in processing vast amounts of data and identifying patterns make it an invaluable tool for insurers in managing cyber risks. Yet, the application of AI in this domain is subject to stringent regulatory scrutiny aimed at safeguarding data privacy, ensuring algorithmic transparency, and preventing biases. Regulatory bodies, such as the European Union with its General Data Protection Regulation (GDPR), mandate strict compliance requirements that can significantly impact the deployment of AI systems. These regulations necessitate robust data protection measures, ethical AI practices, and clear accountability frameworks, all of which entail substantial compliance costs for insurers. The economic implications of these regulatory requirements are profound. Insurers must invest heavily in upgrading their IT infrastructure, implementing robust data governance frameworks, and training personnel to handle AI systems ethically and effectively. These investments, while essential for regulatory compliance, can strain financial resources, particularly for smaller insurers, potentially leading to market consolidation. Furthermore, the cost of regulatory compliance can translate into higher premiums for policyholders, affecting the overall affordability and accessibility of cyber insurance. Despite these challenges, the potential economic benefits of AI integration in cyber insurance are significant. AI-enhanced risk assessment models can provide more accurate pricing, reduce the incidence of fraudulent claims, and expedite claims processing, leading to overall cost savings and increased efficiency. These efficiencies can improve the competitiveness of insurers and drive innovation in product offerings. However, balancing these benefits with regulatory compliance is crucial to avoid legal penalties and reputational damage. The paper also explores the potential risks associated with AI integration, such as algorithmic biases that could lead to unfair discrimination in policy underwriting and claims adjudication. Regulatory frameworks need to evolve to address these issues, promoting fairness and transparency in AI applications. Policymakers play a critical role in creating a balanced regulatory environment that fosters innovation while protecting consumer rights and ensuring market stability. In conclusion, the integration of AI in cyber insurance presents both regulatory and economic challenges that require a coordinated approach involving regulators, insurers, and other stakeholders. By navigating these challenges effectively, the industry can harness the transformative potential of AI, driving advancements in risk management and enhancing the resilience of the cyber insurance market. This paper provides insights and recommendations for policymakers and industry leaders to achieve a balanced and sustainable integration of AI technologies in cyber insurance.

Keywords: artificial intelligence (AI), cyber insurance, regulatory compliance, economic impact, risk assessment, fraud detection, cyber liability insurance, risk management, ransomware

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Authors: Melis Inalpulat, Levent Genc

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Land Use Land Cover (LULC) changes due to human activities and natural causes have become a major environmental concern. Assessment of temporal remote sensing data provides information about LULC impacts on environment. Land Surface Temperature (LST) is one of the important components for modeling environmental changes in climatological, hydrological, and agricultural studies. In this study, LULC changes (September 7, 1984 and July 8, 2014) especially in agricultural lands together with population changes (1985-2014) and LST status were investigated using remotely sensed and census data in South Marmara Watershed, Turkey. LULC changes were determined using Landsat TM and Landsat OLI data acquired in 1984 and 2014 summers. Six-band TM and OLI images were classified using supervised classification method to prepare LULC map including five classes including Forest (F), Grazing Land (G), Agricultural Land (A), Water Surface (W), and Residential Area-Bare Soil (R-B) classes. The LST image was also derived from thermal bands of the same dates. LULC classification results showed that forest areas, agricultural lands, water surfaces and residential area-bare soils were increased as 65751 ha, 20163 ha, 1924 ha and 20462 ha respectively. In comparison, a dramatic decrement occurred in grazing land (107985 ha) within three decades. The population increased % 29 between years 1984-2014 in whole study area. Along with the natural causes, migration also caused this increase since the study area has an important employment potential. LULC was transformed among the classes due to the expansion in residential, commercial and industrial areas as well as political decisions. In the study, results showed that agricultural lands around the settlement areas transformed to residential areas in 30 years. The LST images showed that mean temperatures were ranged between 26-32 °C in 1984 and 27-33 °C in 2014. Minimum temperature of agricultural lands was increased 3 °C and reached to 23 °C. In contrast, maximum temperature of A class decreased to 41 °C from 44 °C. Considering temperatures of the 2014 R-B class and 1984 status of same areas, it was seen that mean, min and max temperatures increased by 2 °C. As a result, the dynamism of population, LULC and LST resulted in increasing mean and maximum surface temperatures, living spaces/industrial areas and agricultural lands.

Keywords: census data, landsat, land surface temperature (LST), land use land cover (LULC)

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

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

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

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Authors: A. Shaygani, R. Saifi, M. S. Saidi, M. Sani

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Particle size distribution, the most important characteristics of aerosols, is obtained through electrical characterization techniques. The dynamics of charged nano-particles under the influence of electric field in electrical mobility spectrometer (EMS) reveals the size distribution of these particles. The accuracy of this measurement is influenced by flow conditions, geometry, electric field and particle charging process, therefore by the transfer function (transfer matrix) of the instrument. In this work, a wire-cylinder corona charger was designed and the combined field-diffusion charging process of injected poly-disperse aerosol particles was numerically simulated as a prerequisite for the study of a multi-channel EMS. The result, a cloud of particles with non-uniform charge distribution, was introduced to the EMS. The flow pattern and electric field in the EMS were simulated using computational fluid dynamics (CFD) to obtain particle trajectories in the device and therefore to calculate the reported signal by each electrometer. According to the output signals (resulted from bombardment of particles and transferring their charges as currents), we proposed a modification to the size of detecting rings (which are connected to electrometers) in order to evaluate particle size distributions more accurately. Based on the capability of the system to transfer information contents about size distribution of the injected particles, we proposed a benchmark for the assessment of optimality of the design. This method applies the concept of Von Neumann entropy and borrows the definition of entropy from information theory (Shannon entropy) to measure optimality. Entropy, according to the Shannon entropy, is the ''average amount of information contained in an event, sample or character extracted from a data stream''. Evaluating the responses (signals) which were obtained via various configurations of detecting rings, the best configuration which gave the best predictions about the size distributions of injected particles, was the modified configuration. It was also the one that had the maximum amount of entropy. A reasonable consistency was also observed between the accuracy of the predictions and the entropy content of each configuration. In this method, entropy is extracted from the transfer matrix of the instrument for each configuration. Ultimately, various clouds of particles were introduced to the simulations and predicted size distributions were compared to the exact size distributions.

Keywords: aerosol nano-particle, CFD, electrical mobility spectrometer, von neumann entropy

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Authors: Yusuf Berkay Metinal, Gulden Gumusburun Ayalp

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Architectural education is characterized by its distinctive amalgamation of studio-based pedagogy and theoretical instruction. It offers students a comprehensive learning experience that blends practical skill development with critical inquiry and conceptual exploration. Design studios are central to this educational paradigm, which serve as dynamic hubs of creativity and innovation, providing students with immersive environments for experimentation and collaborative engagement. The physical presence and interactive dynamics inherent in studio-based learning underscore the indispensability of face-to-face instruction and interpersonal interaction in nurturing the next generation of architects. However, architectural education underwent a seismic transformation in response to the global COVID-19 pandemic, precipitating an abrupt transition from traditional, in-person instruction to online education modalities. While this shift introduced newfound flexibility in terms of temporal and spatial constraints, it also brought many challenges to the fore. Chief among these challenges was maintaining effective communication and fostering meaningful collaboration among students in virtual learning environments. Besides these challenges, lack of peer learning emerged as a vital issue of the educational experience, particularly crucial for novice students navigating the intricacies of architectural practice. Nevertheless, the pivot to online education also laid bare a discernible decline in educational efficacy, prompting inquiries regarding the enduring viability of online education in architectural pedagogy. Moreover, as educational institutions grappled with the exigencies of remote instruction, discernible disparities between different institutional contexts emerged. While state universities often contended with fiscal constraints that shaped their operational capacities, private institutions encountered challenges from a lack of institutional fortification and entrenched educational traditions. Acknowledging the multifaceted nature of these challenges, this study endeavored to undertake a comprehensive inquiry into the dynamics of online education within architectural pedagogy by interrogating variables such as class level and type of university; the research aimed to elucidate demographic critical success factors that underpin the effectiveness of online education initiatives. To this end, a meticulously constructed questionnaire was administered to architecture students from diverse academic institutions across Turkey, informed by an exhaustive review of extant literature and scholarly discourse. The resulting dataset, comprising responses from 232 participants, underwent rigorous statistical analysis, including independent samples t-test and one-way ANOVA, to discern patterns and correlations indicative of overarching trends and salient insights. In sum, the findings of this study serve as a scholarly compass for educators, policymakers, and stakeholders navigating the evolving landscapes of architectural education. By elucidating the intricate interplay of demographical factors that shape the efficacy of online education in architectural pedagogy, this research offers a scholarly foundation upon which to anchor informed decisions and strategic interventions to elevate the educational experience for future cohorts of aspiring architects.

Keywords: architectural education, COVID-19, distance education, online education

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Authors: Jesus D. Cortes Gil, Fernanda Ewerling, Leonardo Ferreira, Aluisio J. D. Barros

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Background: The sustainable development goals call for inclusive, equitable, and quality learning opportunities for all. This is especially important for children, to ensure they all develop to their full potential. We studied the prevalence and inequalities of suspected delay in child development in 63 low- and middle-income countries. Methods and Findings: We used the early child development module from national health surveys, which covers four developmental domains (physical, social-emotional, learning, literacy-numeracy) and provides a combined indicator (early child development index, ECDI) of whether children are on track. We calculated the age-adjusted prevalence of suspected delay at the country level and stratifying by wealth, urban/rural residence, sex of the child, and maternal education. We also calculated measures of absolute and relative inequality. We studied 330.613 children from 63 countries. The prevalence of suspected delay for the ECDI ranged from 3% in Barbados to 67% in Chad. For all countries together, 25% of the children were suspected of developmental delay. At regional level, the prevalence of delay ranged from 10% in Europe and Central Asia to 42% in West and Central Africa. The literacy-numeracy domain was by far the most challenging, with the highest proportions of delay. We observed very large inequalities, and most markedly for the literacy-numeracy domain. Conclusions: To date, our study presents the most comprehensive analysis of child development using an instrument especially developed for national health surveys. With a quarter of the children globally suspected of developmental delay, we face an immense challenge. The multifactorial aspect of early child development and the large gaps we found only add to the challenge of not leaving these children behind.

Keywords: child development, inequalities, global health, equity

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Authors: Precious Ehiomogue, Ifechukwude Israel Ahuchaogu, Isiguzo Edwin Ahaneku

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Vermicompost is the product of the decomposition process using various species of worms, to create a mixture of decomposing vegetable or food waste, bedding materials, and vemicast. This process is called vermicomposting, while the rearing of worms for this purpose is called vermiculture. Several works have verified the adsorption of toxic metals using vermicompost but the application is still scarce for the retention of organic compounds. This research brings to knowledge the effectiveness of earthworm waste (vermicompost) for the remediation of crude oil contaminated soils. The remediation methods adopted in this study were two soil washing methods namely, batch and column process which represent laboratory and in-situ remediation. Characterization of the vermicompost and crude oil contaminated soil were performed before and after the soil washing using Fourier transform infrared (FTIR), scanning electron microscopy (SEM), X-ray fluorescence (XRF), X-ray diffraction (XRD) and Atomic adsorption spectrometry (AAS). The optimization of washing parameters, using response surface methodology (RSM) based on Box-Behnken Design was performed on the response from the laboratory experimental results. This study also investigated the application of machine learning models [Artificial neural network (ANN), Adaptive neuro fuzzy inference system (ANFIS). ANN and ANFIS were evaluated using the coefficient of determination (R²) and mean square error (MSE)]. Removal efficiency obtained from the Box-Behnken design experiment ranged from 29% to 98.9% for batch process remediation. Optimization of the experimental factors carried out using numerical optimization techniques by applying desirability function method of the response surface methodology (RSM) produce the highest removal efficiency of 98.9% at absorbent dosage of 34.53 grams, adsorbate concentration of 69.11 (g/ml), contact time of 25.96 (min), and pH value of 7.71, respectively. Removal efficiency obtained from the multilevel general factorial design experiment ranged from 56% to 92% for column process remediation. The coefficient of determination (R²) for ANN was (0.9974) and (0.9852) for batch and column process, respectively, showing the agreement between experimental and predicted results. For batch and column precess, respectively, the coefficient of determination (R²) for RSM was (0.9712) and (0.9614), which also demonstrates agreement between experimental and projected findings. For the batch and column processes, the ANFIS coefficient of determination was (0.7115) and (0.9978), respectively. It can be concluded that machine learning models can predict the removal of crude oil from polluted soil using vermicompost. Therefore, it is recommended to use machines learning models to predict the removal of crude oil from contaminated soil using vermicompost.

Keywords: ANFIS, ANN, crude-oil, contaminated soil, remediation and vermicompost

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Authors: Roberto Feltrero, Sara Osuna-Acedo

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Responsible Research and Innovation have to accomplish one fundamental aim: everybody has to participate in the benefits of innovation, but also innovation has to be democratic; that is to say, everybody may have the possibility to participate in the decisions in the innovation process. Particularly, a democratic and inclusive model of social participation and innovation includes persons with disabilities and people at risk of discrimination. Innovations on Artificial Intelligence for social development have to accomplish the same dual goal: improving equality for accessing fields of public interest like education, training and public services, as well as improving civic and democratic participation in the process of developing such innovations for all. This research aims to develop innovations, policies and policy recommendations to apply and disseminate such artificial intelligence and social model for making educational and administrative processes more accessible. First, designing a citizen participation process to engage citizens in the designing and use of artificial intelligence tools for public services. This will result in improving trust in democratic institutions contributing to enhancing the transparency, effectiveness, accountability and legitimacy of public policy-making and allowing people to participate in the development of ethical standards for the use of such technologies. Second, improving educational tools for lifelong learning with AI models to improve accountability and educational data management. Dissemination, education and social participation will be integrated, measured and evaluated in innovative educational processes to make accessible all the educational technologies and content developed on AI about responsible and social innovation. A particular case will be presented regarding access for all to educational tools and public services. This accessibility requires cognitive adaptability because, many times, legal or administrative language is very complex. Not only for people with cognitive disabilities but also for old people or citizens at risk of educational or social discrimination. Artificial Intelligence natural language processing technologies can provide tools to translate legal, administrative, or educational texts to a more simple language that can be accessible to everybody. Despite technological advances in language processing and machine learning, this becomes a huge project if we really want to respect ethical and legal consequences because that kinds of consequences can only be achieved with civil and democratic engagement in two realms: 1) to democratically select texts that need and can be translated and 2) to involved citizens, experts and nonexperts, to produce and validate real examples of legal texts with cognitive adaptations to feed artificial intelligence algorithms for learning how to translate those texts to a more simple and accessible language, adapted to any kind of population.

Keywords: responsible research and innovation, AI social innovations, cognitive accessibility, public participation

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