Search results for: digital learning environment

Authors: Sabitha Rahim

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In the context of teaching vocabulary of English as Foreign Language (EFL), the confluence of memory and retention is one of the most significant factors in students' language acquisition. The progress of students engaged in foreign language acquisition is often stymied by vocabulary attrition, which leads to learners' lack of confidence and motivation. However, among other factors, little research has investigated the importance of neuroplasticity in Foreign Language acquisition and how underused neural pathways lead to the loss of plasticity, thereby affecting the learners’ vocabulary retention and motivation. This research explored the effect of enhancing vocabulary acquisition of EFL students in the Foundation Year at King Abdulaziz University through various methods and neuroplasticity exercises that reinforced their attention, motivation, and engagement. It analyzed the results to determine if stimulating the brain of EFL learners by various physical and mental activities led to the improvement in short and long term memory in vocabulary retention. The main data collection methods were student surveys, assessment records of teachers, student achievement test results, and students' follow-up interviews. A key implication of this research is for the institutions to consider having multiple varieties of student activities promoting brain plasticity within the classrooms as an effective tool for foreign language acquisition. Building awareness among the faculty and adapting the curriculum to include activities that promote brain plasticity ensures an enhanced learning environment and effective language acquisition in EFL classrooms.

Keywords: language acquisition, neural paths, neuroplasticity, vocabulary attrition

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Authors: Angela Mathias Kavishe

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Sexual harassment directed at women is reported in many societies, including in Tanzania. The advent of ICT technology, especially in universities, seems to aggravate the situation by extending harassment to cyberspace in various forms, including cyberstalking. Evidence shows that online violence is more dangerous than physical one due to the ability to access multiple private information, attack many victims, mask the perpetrator's identity, suspend the threat for a long time and spread over time and space. The study aimed to measure the magnitude of cyber harassment in Tanzanian higher learning institutions and to assess institutional sensitivity to ICT-mediated gender-based violence. It was carried out in 4 higher learning institutions in Tanzania: Mwalimu Nyerere Memorial Academy and Institute of Finance Management in Dar es Salaam and SAUT, and the University of Dodoma, where a survey questionnaire was distributed to 400 students and 40 key informants were interviewed. It was found that in each institution, the majority of female students experienced online harassment on social media perpetrated by ex-partners, male students, and university male teaching staff. The perpetrators compelled the female students to post nude pictures, have sexual relations with them, or utilize the posted private photographs to force female students to practice online or offline sexual relations. These threats seem to emanate from social-cultural beliefs about the subordinate position of women in society and that women's bodies are perceived as sex objects. It is therefore concluded that cyberspace provides an alternative space for perpetrators to exercise violence towards women.

Keywords: cyberstalking, embodiment, gender-based violence, internet

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Authors: Mansur Hamma-Adama, Tahar Kouider

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Construction Industry has been evolving since the development of Building Information Modelling (BIM). This technological process is unstoppable; it is out to the market with remarkable case studies of solving the long industry’s history of fragmentation. This industry has been changing over time; United States has recorded the most significant development in construction digitalization, Australia, United Kingdom and some other developed nations are also amongst promoters of BIM process and its development. Recently, a developing country like China and Malaysia are keying into the industry’s digital shift, while very little move is seen in South Africa whose development is considered higher and perhaps leader in the digital transition amongst the African countries. To authors’ best knowledge, Nigerian construction industry has never engaged in BIM discussions hence has no attention at national level. Consequently, Nigeria has no “Noteworthy BIM publications.” Decision makers and key stakeholders need to be informed on the current trend of the industry’s development (BIM in specific) and the opportunities of adopting this digitalization trend in relation to the identified challenges. BIM concept can be traced mostly in Architectural practices than engineering practices in Nigeria. A superficial BIM practice is found to be at organisational level only and operating a model based - “BIM stage 1.” Research to adopting this innovation has received very little attention. This piece of work is literature review based, aimed at exploring BIM in Nigeria and its prospects. The exploration reveals limitations in the literature availability as to extensive research in the development of BIM in the country. Numerous challenges were noticed including building collapse, inefficiencies, cost overrun and late project delivery. BIM has potentials to overcome the above challenges and even beyond. Low level of BIM adoption with reasonable level of awareness is noticed. However, lack of policy and guideline as well as serious lack of experts in the field are amongst the major barriers to BIM adoption. The industry needs to embrace BIM to possibly compete with its global counterpart.

Keywords: adoption, BIM, CAD, construction industry, Nigeria, opportunities

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Authors: Mairo H. Ipadeola, Catherine James Atteng

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The term social inclusion refers to a process by which those disadvantaged in society can have access to fully participate in education like others. Student with special needs are expected to learn along with their peers within the some educational institutions which provide adequate access for all. There for, the study sort to understand the typical ways in which students with disabilities (SWD) were denied from fully participating as students in Kaduna Polytechnic. In doing this, two (2) objectives and research questions were raised. Firstly, to explore the attitudes of others towards students with disabilities in the institutions and secondly, to ascertain the extent of social participation and physical accessibility for students with disabilities (SWD) while in the institutions. Based on the objectives the paper postulated the research questions: what are the attitudes of management, teachers, and students towards students with special need in Kaduna Polytechnic and to what extent did the students with disabilities experience social participation and physical accessibility within Kaduna Polytechnic school environment? The study area was Kaduna Polytechnic. The study engaged the interview for the data collected which were transcribed and analyzed by thematic coding. The findings were categorized under themes, sub-themes, and codes. The findings revealed that the perception, behavior, and association experiences of students with disabilities within Kaduna Polytechnic were not encouraging. Their experiences were characterized by negative attitudes, feelings of rejection, neglect, and bullying. Data generated on social participation indicated that 71% of the respondents believed that learning, school activities, recreations, and student politics between SWD and the other student were in the direction of low / very low. All the respondents, particularly students with blindness and physical challenges faced difficulty with environmental and physical access above all within the school environment, classroom, walkways and ramps, Also, directions were none existent in most departments with physical access to classrooms, toilets, cafeterias, and school shops absent or very low (71% and 29% of the respondents). The conclusion was that the physical barriers limited the possibilities of social participation of SWD.The paper made some recommendations such as mass public enlightenment on radio and television to change the perception of society about people with disability. Also, the federal, state, and local governments enact building acts for fresh builders and adopted measures and time frames for existing public buildings to be made accessible for people with disabilities. All stakeholders should ensure that the five (5) percent budget set aside by State Universal Basic Education Board (SUBEB) and/or Tertiary Education Trust Fund (TETFUND) for the provision of specialized equipment and facilities for the student with special needs should be used prudently spent and monitored by the board.cm.

Keywords: social inclusion, students with disability, social participation, environmental/physical access

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Authors: A. Nachour, L. Ouzizi, Y. Aoura

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Recent developments on multi-agent system have brought a new research field on image processing. Several algorithms are used simultaneously and improved in deferent applications while new methods are investigated. This paper presents a new automatic method for edge detection using several agents and many different actions. The proposed multi-agent system is based on parallel agents that locally perceive their environment, that is to say, pixels and additional environmental information. This environment is built using Vector Field Convolution that attract free agent to the edges. Problems of partial, hidden or edges linking are solved with the cooperation between agents. The presented method was implemented and evaluated using several examples on different synthetic and medical images. The obtained experimental results suggest that this approach confirm the efficiency and accuracy of detected edge.

Keywords: edge detection, medical MRImages, multi-agent systems, vector field convolution

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Authors: Rida Akzar, Risti Permani, Wahida , Wendy Umberger

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Adoption of farm innovations may increase farm productivity, and therefore improve market access and farm incomes. However, most studies that look at the level and drivers of innovation adoption only focus on a specific type of innovation. Farmers may consider multiple innovation options, and constraints such as budget, environment, scarcity of labour supply, and the cost of learning. There have been some studies proposing different methods to combine a broad variety of innovations into a single measurable index. However, little has been done to compare these methods and assess whether they provide similar information about farmer segmentation by their ‘innovativeness’. Using data from a recent survey of 220 dairy farm households in West Java, Indonesia, this study compares and considers different methods of deriving an innovation index, including expert-weighted innovation index; an index derived from the total number of adopted technologies; and an index of the extent of adoption of innovation taking into account both adoption and disadoption of multiple innovations. Second, it examines the distribution of different farming systems taking into account their innovativeness and farm characteristics. Results from this study will inform policy makers and stakeholders in the dairy industry on how to better design, target and deliver programs to improve and encourage farm innovation, and therefore improve farm productivity and the performance of the dairy industry in Indonesia.

Keywords: adoption, dairy, household survey, innovation index, Indonesia, multiple innovations dairy, West Java

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Authors: Kavyadevi N., Kaviya G., Gowsalya P., Janani M., Mohanraj S.

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Hevea brasiliensis, also known as the rubber tree, is one of the foremost assets of crops in the world. One of the most significant advantages of the Rubber Plant in terms of air oxygenation is its capacity to reduce the likelihood of an individual developing respiratory allergies like asthma. To construct such a system that can properly identify crop diseases and pests and then create a database of insecticides for each pest and disease, we must first give treatment for the illness that has been detected. We shall primarily examine three major leaf diseases since they are economically deficient in this article, which is Bird's eye spot, algal spot and powdery mildew. And the recommended work focuses on disease identification on rubber tree leaves. It will be accomplished by employing one of the superior algorithms. Input, Preprocessing, Image Segmentation, Extraction Feature, and Classification will be followed by the processing technique. We will use time-consuming procedures that they use to detect the sickness. As a consequence, the main ailments, underlying causes, and signs and symptoms of diseases that harm the rubber tree are covered in this study.

Keywords: image processing, python, convolution neural network (CNN), machine learning

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Authors: Lv Shizeng, Han Xiao, Zhang Yi, Ding Wenjing

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The lunar sample storage device is mainly used for the preparation of the lunar samples, observation, physical analysis and other work. The lunar samples and operating equipment are placed directly inside the storage device. The inside of the storage device is a high purity nitrogen environment to ensure that the sample is not contaminated by the Earth's environment. In order to ensure that the water and oxygen indicators in the storage device meet the sample requirements, a dynamic gas cycle is required between the storage device and the external purification equipment. However, the internal gas disturbance in the storage device can affect the operation of the sample. In this paper, the storage device model is established, and the tetrahedral mesh is established by Tetra/Mixed method. The influence of different inlet position and gas flow on the internal flow field disturbance is calculated, and the disturbed flow area should be avoided during the sampling operation.

Keywords: lunar samples, gas disturbance, storage device, characteristic analysis

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Authors: Hediye Saglam

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This research has been carried out to bring in the 6 acquisitions in the 2014 Preschool Teaching Programme of the Turkish Ministry of Education through the method of analogy. This research is practiced based on the experimental pattern with pre-test and final test controlling groups. The working group of the study covers the group between 5-6 ages. The study takes 5 weeks including the 2 weeks spent for pre-test and the final test. It is conducted with the preschool teacher who gives the lesson along with the researcher in the in-class and out-of-class rainbow experiments of the students for 5 weeks. 'One Sample T Test' is used for the evaluation of the pre-test and final test. SPSS 17 programme is applied for the analysis of the data. Results: As an outcome of the study it is observed that analogy method affects children’s learning of the rainbow. For this very reason teachers should receive inservice training for different methods and techniques like analogy. This method should be included in preschool education programme and should be applied by teachers more often.

Keywords: acquisitions of preschool education programme, analogy method, pre-test/final test, rainbow experiments

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Authors: Nadia Theuma

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Climate change is a reality that has started to leave an impact on the physical environment as well as on the built environment, in particular built heritage. This paper explores the argument that climate change is also a trigger which can lead to identifying a number of creative solutions that can transform built heritage into sustainable buildings. Using the Maltese Islands, and in particular the city of Valletta which is also a World Heritage Site, this paper illustrates some of the innovative solutions that are being developed to make heritage buildings more sustainable and in doing so, mitigating the negative impacts of climate change. The paper looks in detail at the most notable initiatives being developed, their implementation and application, which at times is not easy considering the restrictions within protected built heritage areas and the positive impacts that they will have on visitor experience and overall sustainability of the Maltese tourism product. The paper will conclude by outlining how these solutions can be adapted to buildings with similar climatic conditions.

Keywords: built heritage, creative solutions, climate change, Maltese Islands

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Authors: Fharia Tilat Loba

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Studies show that there is a certain group of students who are more vulnerable to bullying due to their physical appearance, disability, sexual preference, race, and lack of social and behavioral skills. Students with autism spectrum disorders (ASD) are one of the most vulnerable groups among these at-risk groups. Researchers suggest that focusing on vulnerable groups of students who can be the target of bullying helps to understand the causes and patterns of aggression, which ultimately helps in structuring intervention programs to reduce bullying. Since Australia ratified the United Nations Convention on the Rights of Persons with Disabilities in 2006, it has been committed to providing an inclusive, safe, and effective learning environment for all children. In addition, the 2005 Disability Standards for Education seeks to ensure that students with disabilities can access and participate in education on the same basis as other students, covering all aspects of education, including harassment and victimization. However, bullying hinders students’ ability to fully participate in schooling. The proposed study aims to synthesize the notions of traditional bullying and cyberbullying and attempts to understand the experiences of students with ASD who are experiencing bullying in their schools. The proposed study will primarily focus on identifying the gaps between policy and practice related to bullying, and it will also attempt to understand the experiences of parents of students with ASD and professionals who have experience dealing with bullying at the school level in Australia. This study is expected to contribute to the theoretical knowledge of the bullying phenomenon and provide a reference for advocacy at the school, organization, and government levels.

Keywords: education policy, bullying, Australia, neurodiversity

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Authors: Mohamed Bualhamam

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Due to the complex nature of tourism resources of the Northern part of the United Arab Emirates (UAE), the potential of Geographical Information Systems (GIS) and Remote Sensing (RS) in resolving these issues was used. The study was an attempt to use existing GIS data layers to identify sensitive natural environment and archaeological heritage resources that may be threatened by increased urban growth and give some specific recommendations to protect the area. By identifying sensitive natural environment and archaeological heritage resources, public agencies and citizens are in a better position to successfully protect important natural lands and direct growth away from environmentally sensitive areas. The paper concludes that applications of GIS and RS in study of urban growth impact in tourism resources are a strong and effective tool that can aid in tourism planning and decision-making. The study area is one of the fastest growing regions in the country. The increase in population along the region, as well as rapid growth of towns, has increased the threat to natural resources and archeological sites. Satellite remote sensing data have been proven useful in assessing the natural resources and in monitoring the changes. The study used GIS and RS to identify sensitive natural environment and archaeological heritage resources that may be threatened by increased urban growth. The result of GIS analyses shows that the Northern part of the UAE has variety for tourism resources, which can use for future tourism development. Rapid urban development in the form of small towns and different economic activities are showing in different places in the study area. The urban development extended out of old towns and have negative affected of sensitive tourism resources in some areas. Tourism resources for the Northern part of the UAE is a highly complex resources, and thus requires tools that aid in effective decision making to come to terms with the competing economic, social, and environmental demands of sustainable development. The UAE government should prepare a tourism databases and a GIS system, so that planners can be accessed for archaeological heritage information as part of development planning processes. Applications of GIS in urban planning, tourism and recreation planning illustrate that GIS is a strong and effective tool that can aid in tourism planning and decision- making. The power of GIS lies not only in the ability to visualize spatial relationships, but also beyond the space to a holistic view of the world with its many interconnected components and complex relationships. The worst of the damage could have been avoided by recognizing suitable limits and adhering to some simple environmental guidelines and standards will successfully develop tourism in sustainable manner. By identifying sensitive natural environment and archaeological heritage resources of the Northern part of the UAE, public agencies and private citizens are in a better position to successfully protect important natural lands and direct growth away from environmentally sensitive areas.

Keywords: GIS, natural environment, UAE, urban growth

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Authors: Ioanna Taouki, Marie Lallier, David Soto

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Metacognition refers to the capacity to reflect upon our own cognitive processes. Although there is an ongoing discussion in the literature on the role of metacognition in learning and academic achievement, little is known about its neurodevelopmental trajectories in early childhood, when children begin to receive formal education in reading. Here, we evaluate the metacognitive ability, estimated under a recently developed Signal Detection Theory model, of a cohort of children aged between 6 and 7 (N=60), who performed three two-alternative-forced-choice tasks (two linguistic: lexical decision task, visual attention span task, and one non-linguistic: emotion recognition task) including trial-by-trial confidence judgements. Our study has three aims. First, we investigated how metacognitive ability (i.e., how confidence ratings track accuracy in the task) relates to performance in general standardized tasks related to students' reading and general cognitive abilities using Spearman's and Bayesian correlation analysis. Second, we assessed whether or not young children recruit common mechanisms supporting metacognition across the different task domains or whether there is evidence for domain-specific metacognition at this early stage of development. This was done by examining correlations in metacognitive measures across different task domains and evaluating cross-task covariance by applying a hierarchical Bayesian model. Third, using robust linear regression and Bayesian regression models, we assessed whether metacognitive ability in this early stage is related to the longitudinal learning of children in a linguistic and a non-linguistic task. Notably, we did not observe any association between students’ reading skills and metacognitive processing in this early stage of reading acquisition. Some evidence consistent with domain-general metacognition was found, with significant positive correlations between metacognitive efficiency between lexical and emotion recognition tasks and substantial covariance indicated by the Bayesian model. However, no reliable correlations were found between metacognitive performance in the visual attention span and the remaining tasks. Remarkably, metacognitive ability significantly predicted children's learning in linguistic and non-linguistic domains a year later. These results suggest that metacognitive skill may be dissociated to some extent from general (i.e., language and attention) abilities and further stress the importance of creating educational programs that foster students’ metacognitive ability as a tool for long term learning. More research is crucial to understand whether these programs can enhance metacognitive ability as a transferable skill across distinct domains or whether unique domains should be targeted separately.

Keywords: confidence ratings, development, metacognitive efficiency, reading acquisition

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Authors: W. Nootcharin, S. Sujittra, K. Mayuso, K. Kornphimol, M. Rawiwan

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Silver has distinct antibacterial properties and has been used as a component of commercial products with many applications. An increasing number of commercial products cause risks of silver effects for human and environment such as the symptoms of Argyria and the release of silver to the environment. Therefore, the detection of silver in the aquatic environment is important. The colorimetric chemosensor is designed by the basic of ligand interactions with a metal ion, leading to the change of signals for the naked-eyes which are very useful method to this application. Dithizone ligand is considered as one of the effective chelating reagents for metal ions due to its high selectivity and sensitivity of a photochromic reaction for silver as well as the linear backbone of dithizone affords the rotation of various isomeric forms. The present study is focused on the conformation and interaction of silver ion and silver nanoparticles (AgNPs) with dithizone using density functional theory (DFT). The interaction parameters were determined in term of binding energy of complexes and the geometry optimization, frequency of the structures and calculation of binding energies using density functional approaches B3LYP and the 6-31G(d,p) basis set. Moreover, the interaction of silver–dithizone complexes was supported by UV–Vis spectroscopy, FT-IR spectrum that was simulated by using B3LYP/6-31G(d,p) and 1H NMR spectra calculation using B3LYP/6-311+G(2d,p) method compared with the experimental data. The results showed the ion exchange interaction between hydrogen of dithizone and silver atom, with minimized binding energies of silver–dithizone interaction. However, the result of AgNPs in the form of complexes with dithizone. Moreover, the AgNPs-dithizone complexes were confirmed by using transmission electron microscope (TEM). Therefore, the results can be the useful information for determination of complex interaction using the analysis of computer simulations.

Keywords: silver nanoparticles, dithizone, DFT, NMR

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Authors: Hazim Abdulsada

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The inspection of underneath vehicle system has been given significant attention by governments after the threat of terrorism become more prevalent. New technologies such as mobile robots and computer vision are led to have more secure environment. This paper proposed that a mobile robot like Aria robot can be used to search and inspect the bombs under parking a lot vehicle. This robot is using fuzzy logic and subsumption algorithms to control the robot that movies underneath the vehicle. An OpenCV library and laser Hokuyo are added to Aria robot to complete the experiment for under vehicle inspection. This experiment was conducted at the indoor environment to demonstrate the efficiency of our methods to search objects and control the robot movements under vehicle. We got excellent results not only by controlling the robot movement but also inspecting object by the robot camera at same time. This success allowed us to know the requirement to construct a new cost effective robot with more functionality.

Keywords: fuzzy logic, mobile robots, Opencv, subsumption, under vehicle inspection

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Authors: Karen Armstrong

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Recent concerns about the value of teaching cursive handwriting in the classroom are based on the belief that cursive handwriting or penmanship is an outdated and unnecessary skill in today’s online world. The discussion of this issue begins with a description of current initiatives to eliminate handwriting instruction in schools. This is followed by a brief history of cursive writing through the ages. Next considered is a description of its benefits as a preliminary process for younger children as compared with immediate instruction in keyboarding, particularly in the areas of vision, cognition, motor skills and automatic fluency. Also considered, is cursive’s companion, paper itself, and the impact of a paperless, “screen and keyboard” environment. The discussion concludes with a consideration of the unique contributions of cursive and keyboarding as written forms of communication, along with their respective surfaces, paper and screen. Finally, an assessment of the practical utility of each skill is followed by an informal assessment of what is lost and what remains as we move from a predominantly paper and pen world of handwriting to texting and keyboarding in an environment of screens.

Keywords: asemic writing, cursive, handwriting, keyboarding, paper

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Authors: Mina Shokry Hanna Saleh Tadros

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The centrality of the Petroleum Industry in the world energy is undoubted. The world economy almost runs and depends on petroleum. Petroleum industry is a multi-trillion industry; it turns otherwise poor and underdeveloped countries into wealthy nations and thrusts them at the center of international diplomacy. Although these developing nations lack the necessary technology to explore and exploit petroleum resources they are not without help as developed nations, represented by their multinational corporations are ready and willing to provide both the technical and managerial expertise necessary for the development of this natural resource. However, the exploration of these petroleum resources comes with, sometimes, grave, concomitant consequences. These consequences are especially pronounced with respect to the environment. From the British Petroleum Oil rig explosion and the resultant oil spillage and pollution in New Mexico, United States to the Mobil Oil spillage along Egyptian coast, the story and consequence is virtually the same. Egypt’s delta Region produces Nigeria’s petroleum which accounts for more than ninety-five percent of Nigeria’s foreign exchange earnings. Between 1999 and 2007, Egypt earned more than $400 billion from petroleum exports. Nevertheless, petroleum exploration and exploitation has devastated the Delta environment. From oil spillage which pollutes the rivers, farms and wetlands to gas flaring by the multi-national corporations; the consequences is similar-a region that has been devastated by petroleum exploitation. This paper thus seeks to examine the consequences and impact of petroleum pollution in the Egypt Delta with particular reference on the right of the people of Niger Delta to a healthy environment. The paper further seeks to examine the relevant international, regional instrument and Nigeria’s municipal laws that are meant to protect the result of the people of the Egypt Delta and their enforcement by the Nigerian State. It is quite worrisome that the Egypt Delta Region and its people have suffered and are still suffering grave violations of their right to a healthy environment as a result of petroleum exploitation in their region. The Egypt effort at best is half-hearted in its protection of the people’s right.

Keywords: crude oil, fire, floating roof tank, lightning protection systemenvironment, exploration, petroleum, pollutionDuvernay petroleum system, oil generation, oil-source correlation, Re-Os

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Authors: Babanyara Y. Y., Ibrahim D. B., Garba T., Bogoro A. G., Abubakar, M. Y.

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Medical care is vital for our life, health, and well-being. However, the waste generated from medical activities can be hazardous, toxic, and even lethal because of their high potential for diseases transmission. The hazardous and toxic parts of waste from healthcare establishments comprising infectious, medical, and radioactive material as well as sharps constitute a grave risks to mankind and the environment, if these are not properly treated/disposed or are allowed to be mixed with other municipal waste. In Nigeria, practical information on this aspect is inadequate and research on the public health implications of poor management of medical wastes is few and limited in scope. Findings drawn from Literature particularly in the third world countries highlights financial problems, lack of awareness of risks involved in MWM, lack of appropriate legislation and lack of specialized MWM staff. The paper recommends how MWM practices can be improved in medical facilities.

Keywords: environmental pollution, infectious, management, medical waste, public health

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Authors: Zakaria Kharbouch, Mustapha Bouchaara, F. Elkouihen, A. Habbal, A. Ratnani, A. Faik

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Solid-state lithium-ion batteries have garnered increasing interest in modern energy research due to their potential for safer, more efficient, and sustainable energy storage systems. Among the critical components of these batteries, the electrolyte plays a pivotal role, with LLZO garnet-based electrolytes showing significant promise. Garnet materials offer intrinsic advantages such as high Li-ion conductivity, wide electrochemical stability, and excellent compatibility with lithium metal anodes. However, optimizing ionic conductivity in garnet structures poses a complex challenge, primarily due to the multitude of potential dopants that can be incorporated into the LLZO crystal lattice. The complexity of material design, influenced by numerous dopant options, requires a systematic method to find the most effective combinations. This study highlights the utility of machine learning (ML) techniques in the materials discovery process to navigate the complex range of factors in garnet-based electrolytes. Collaborators from the materials science and ML fields worked with a comprehensive dataset previously employed in a similar study and collected from various literature sources. This dataset served as the foundation for an extensive data refinement phase, where meticulous error identification, correction, outlier removal, and garnet-specific feature engineering were conducted. This rigorous process substantially improved the dataset's quality, ensuring it accurately captured the underlying physical and chemical principles governing garnet ionic conductivity. The data refinement effort resulted in a significant improvement in the predictive performance of the machine learning model. Originally starting at an accuracy of 0.32, the model underwent substantial refinement, ultimately achieving an accuracy of 0.88. This enhancement highlights the effectiveness of the interdisciplinary approach and underscores the substantial potential of machine learning techniques in materials science research.

Keywords: lithium batteries, all-solid-state batteries, machine learning, solid state electrolytes

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Authors: Houmame Benbouali

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The risks, in general, exist in any project; one can hardly carry out a project without taking risks. The hydraulic works are rather complex projects in their design, realization and exploitation, and are often subjected at the multiple risks being able to influence with their good performance, and can have an negative impact on their environment. The present study was carried out to quote the impacts caused by purification plant STEP Chlef on the environment, it aims has studies the environmental impacts during construction and when designing this STEP, it is divided into two parts: The first part results from a research task bibliographer which contain three chapters (-cleansing of water worn-general information on water worn-proceed of purification of waste water). The second part is an experimental part which is divided into four chapters (detailed state initial-description of the station of purification-evaluation of the impacts of the project analyzes measurements and recommendations).

Keywords: treatment plant, waste water, waste water treatment, environmental impact

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Authors: Chinedu F. Anochie

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The deterioration of materials as a result of their interaction with the environment has been a huge challenge to engineering. Many steps have been taking to tackle corrosion and its effects on harmful effects on engineering materials and structures. Corrosion inhibition, coating, passivation, materials selection, and cathodic protection are some of the methods utilized to curtail the rate at which materials corrode. The use of sacrificial anodes (magnesium, aluminum, or zinc) to protect the metal of interest is a widespread technique used to prevent corrosion in underground structures, ship hauls, and other structures susceptible to corrosion attack. However, certain factors, like resistivity, affect the performance of sacrificial anodes. To establish the effect of soil resistivity on the effectiveness of a cathodic protection system, a mild steel specimen was cathodically protected around Workshop 2 area, Federal University of Technology, Owerri, Nigeria. Design calculations showed that one zinc anode was sufficient to protect the pipe. The specimen (mild steel pipe) was coated with white and black polykene tapes and was subsequently buried in a high resistivity soil. The pipe-to-soil potential measurements were obtained using a digital fluke multimeter. The protection potential obtained on installation was higher than the minimum protection criteria. However, the potential results obtained over a fourteen-day intervals continually decreased to a value significantly lower than the minimum protection criteria. This showed that the sacrificial anode (zinc) was rendered ineffective by the high resistivity of the area of installation. It has been shown that the resistivity of the soil has a marked effect on the feasibility of cathodic protection systems. This work justified that zinc anode cannot be used for cathodic protection around Workshop 2 area, Federal University of Technology, Owerri, Nigeria, because of the high resistivity of the area. An experimental data which explains the effectiveness of galvanic anode cathodic protection system on corrosion control of a small steel structure, exposed to a soil of high resistivity has been established.

Keywords: cathodic protection, corrosion, pipe, sacrificial anode

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Authors: Salisu Gidado Dalibi, Sadiq Gumi Abubakar, JingChun Feng

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Nigeria’s population is about 190 million and is on the increase annually making it the seventh most populated nation in the world and first in Africa. This population growth comes with its prospects, needs, and challenges especially on the existing and future infrastructure. Infrastructure refers to structures, systems, and facilities serving the economy of a country, city, town, businesses, industries, etc. These include roads, railways lines, bridges, tunnels, ports, stadiums, dams and water projects, power generation plants and distribution grids, information, and communication technology (ICT), etc. The Nigerian government embarked on several infrastructural development projects (IDPs) to address the deficit as the present infrastructure cannot cater to the needs nor sustain the country. However, delivering such IDPs have not been smooth; comes with challenges from within and outside the project; frequent delays and abandonment. Thus, affecting all the stakeholders involved. Hence, the aim of this paper is to identify and assess the factors that are hindering the effective delivery of IDPs in Nigeria’s built environment with the view to offer more insight into such factors, and ways to address them. The methodology adopted in this study involves the use of secondary sources of data from several materials (official publications, journals, newspapers, internet, etc.) were reviewed within the IDPs field by laying more emphasis on Nigeria’s cases. The hindrance factors in this regard were identified which forms the backbone of the questionnaire. A pilot survey was used to test its suitability; after which it was randomly administered to various project professionals in Nigeria’s construction industry using a 5-point Likert scale format to ascertain the impact of these hindrances. Cronbach’s Alpha reliability test, mean item score computations, relative importance indices, T-test, Chi-Square statistics were used for data analyses. The results outline the impact of various internal, external and project related factors that are hindering IDPs within Nigeria’s built environment.

Keywords: built environment, development, factors, hindrances, infrastructure, Nigeria, project

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Authors: C. Zimmermann, E. Lackner, M. Ebner

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Massive Open Online Courses (MOOCs) are increasingly popular learning hubs that are boasting considerable participant numbers, innovative technical features, and a multitude of instructional resources. Still, there is a high level of evidence showing that almost all MOOCs suffer from a declining frequency of participant activity and fairly low completion rates. In this paper, we would like to share the lessons learned in implementing several design patterns that have been suggested in order to foster participant activity. Our conclusions are based on experiences with the ‘Dr. Internet’ MOOC, which was created as an xMOOC to raise awareness for a more critical approach to online health information: participants had to diagnose medical case studies. There is a growing body of recommendations (based on Learning Analytics results from earlier xMOOCs) as to how the decline in participant activity can be alleviated. One promising focus in this regard is instructional design patterns, since they have a tremendous influence on the learner’s motivation, which in turn is a crucial trigger of learning processes. Since Medieval Age storytelling, micro-learning units and specific comprehensible, narrative structures were chosen to animate the audience to follow narration. Hence, MOOC participants are not likely to abandon a course or information channel when their curiosity is kept at a continuously high level. Critical aspects that warrant consideration in this regard include shorter course duration, a narrative structure with suspense peaks (according to the ‘storytelling’ approach), and a course schedule that is diversified and stimulating, yet easy to follow. All of these criteria have been observed within the design of the Dr. Internet MOOC: 1) the standard eight week course duration was shortened down to six weeks, 2) all six case studies had a special quiz format and a corresponding resolution video which was made available in the subsequent week, 3) two out of six case studies were split up in serial video sequences to be presented over the span of two weeks, and 4) the videos were generally scheduled in a less predictable sequence. However, the statistical results from the first run of the MOOC do not indicate any strong influences on the retention rate, so we conclude with some suggestions as to why this might be and what aspects need further consideration.

Keywords: case study, Dr. internet, experience, MOOCs, design patterns

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Authors: Fernanda M. Assef, Maria Teresinha A. Steiner

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The aim of this paper is to compare and discuss better classifier algorithm options for credit risk assessment by applying different Machine Learning techniques. Using records from a Brazilian financial institution, this study uses a database of 5,432 companies that are clients of the bank, where 2,600 clients are classified as non-defaulters, 1,551 are classified as defaulters and 1,281 are temporarily defaulters, meaning that the clients are overdue on their payments for up 180 days. For each case, a total of 15 attributes was considered for a one-against-all assessment using four different techniques: Artificial Neural Networks Multilayer Perceptron (ANN-MLP), Artificial Neural Networks Radial Basis Functions (ANN-RBF), Logistic Regression (LR) and finally Support Vector Machines (SVM). For each method, different parameters were analyzed in order to obtain different results when the best of each technique was compared. Initially the data were coded in thermometer code (numerical attributes) or dummy coding (for nominal attributes). The methods were then evaluated for each parameter and the best result of each technique was compared in terms of accuracy, false positives, false negatives, true positives and true negatives. This comparison showed that the best method, in terms of accuracy, was ANN-RBF (79.20% for non-defaulter classification, 97.74% for defaulters and 75.37% for the temporarily defaulter classification). However, the best accuracy does not always represent the best technique. For instance, on the classification of temporarily defaulters, this technique, in terms of false positives, was surpassed by SVM, which had the lowest rate (0.07%) of false positive classifications. All these intrinsic details are discussed considering the results found, and an overview of what was presented is shown in the conclusion of this study.

Keywords: artificial neural networks (ANNs), classifier algorithms, credit risk assessment, logistic regression, machine Learning, support vector machines

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Authors: Claudia Martínez-Araneda, Mariella Gutiérrez, Pedro Gómez, Diego Maldonado, Alejandra Segura, Christian Vidal-Castro

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The purpose of this document is to showcase the preliminary work in developing an EduChatbot-type tool and measuring the effects of its use aimed at providing effective feedback to students in programming courses. This bot, hereinafter referred to as tutorBot+, was constructed based on chatGPT and is tasked with assisting and delivering timely positive feedback to students in the field of computer science at the Universidad Católica de Concepción. The proposed working method consists of four stages: (1) Immersion in the domain of Large Language Models (LLMs), (2) Development of the tutorBot+ prototype and integration, (3) Experiment design, and (4) Intervention. The first stage involves a literature review on the use of artificial intelligence in education and the evaluation of intelligent tutors, as well as research on types of feedback for learning and the domain of chatGPT. The second stage encompasses the development of tutorBot+, and the final stage involves a quasi-experimental study with students from the Programming and Database labs, where the learning outcome involves the development of computational thinking skills, enabling the use and measurement of the tool's effects. The preliminary results of this work are promising, as a functional chatBot prototype has been developed in both conversational and non-conversational versions integrated into an open-source online judge and programming contest platform system. There is also an exploration of the possibility of generating a custom model based on a pre-trained one tailored to the domain of programming. This includes the integration of the created tool and the design of the experiment to measure its utility.

Keywords: assessment, chatGPT, learning strategies, LLMs, timely feedback

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Authors: I. Stathopoulos, V. Syrgiamiotis, E. Karavasilis, A. Ploussi, I. Nikas, C. Hatzigiorgi, K. Platoni, E. P. Efstathopoulos

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Introduction: Brain and central nervous system (CNS) tumors form the second most common group of cancer in children, accounting for 30% of all childhood cancers. MRI is the key imaging technique used for the visualization and management of pediatric brain tumors. Initial characterization of tumors from MRI scans is usually performed via a radiologist’s visual assessment. However, different brain tumor types do not always demonstrate clear differences in visual appearance. Using only conventional MRI to provide a definite diagnosis could potentially lead to inaccurate results, and so histopathological examination of biopsy samples is currently considered to be the gold standard for obtaining definite diagnoses. Machine learning is defined as the study of computational algorithms that can use, complex or not, mathematical relationships and patterns from empirical and scientific data to make reliable decisions. Concerning the above, machine learning techniques could provide effective and accurate ways to automate and speed up the analysis and diagnosis for medical images. Machine learning applications in radiology are or could potentially be useful in practice for medical image segmentation and registration, computer-aided detection and diagnosis systems for CT, MR or radiography images and functional MR (fMRI) images for brain activity analysis and neurological disease diagnosis. Purpose: The objective of this study is to provide an automated tool, which may assist in the imaging evaluation and classification of brain neoplasms in pediatric patients by determining the glioma type, grade and differentiating between different brain tissue types. Moreover, a future purpose is to present an alternative way of quick and accurate diagnosis in order to save time and resources in the daily medical workflow. Materials and Methods: A cohort, of 80 pediatric patients with a diagnosis of posterior fossa tumor, was used: 20 ependymomas, 20 astrocytomas, 20 medulloblastomas and 20 healthy children. The MR sequences used, for every single patient, were the following: axial T1-weighted (T1), axial T2-weighted (T2), FluidAttenuated Inversion Recovery (FLAIR), axial diffusion weighted images (DWI), axial contrast-enhanced T1-weighted (T1ce). From every sequence only a principal slice was used that manually traced by two expert radiologists. Image acquisition was carried out on a GE HDxt 1.5-T scanner. The images were preprocessed following a number of steps including noise reduction, bias-field correction, thresholding, coregistration of all sequences (T1, T2, T1ce, FLAIR, DWI), skull stripping, and histogram matching. A large number of features for investigation were chosen, which included age, tumor shape characteristics, image intensity characteristics and texture features. After selecting the features for achieving the highest accuracy using the least number of variables, four machine learning classification algorithms were used: k-Nearest Neighbour, Support-Vector Machines, C4.5 Decision Tree and Convolutional Neural Network. The machine learning schemes and the image analysis are implemented in the WEKA platform and MatLab platform respectively. Results-Conclusions: The results and the accuracy of images classification for each type of glioma by the four different algorithms are still on process.

Keywords: image classification, machine learning algorithms, pediatric MRI, pediatric oncology

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Authors: Nathaniel Evans, Jessica Boersma, Kenneth Kass

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With technology and STEM fields growing every day, there is a significant projected shortfall in qualified cybersecurity workers. As such, it is essential to develop a cybersecurity curriculum that builds skills and cultivates interest in cybersecurity early on. With new jobs being created every day and an already significant gap in the job market, it is vital that educators are pro-active in introducing a cybersecurity curriculum where students are able to learn new skills and engage in an age-appropriate cyber curriculum. Within this growing world of cybersecurity, students should engage in age-appropriate technology and cybersecurity curriculum, starting with elementary school (k-5), extending through high school, and ultimately into college. Such practice will provide students with the confidence, skills, and, ultimately, the opportunity to work in the burgeoning information security field. This paper examines educational methods, pedagogical practices, current cybersecurity curricula, and other educational resources and conducts analysis for false assumptions and developmental appropriateness. It also examines and identifies common mistakes with current cyber curriculum and lessons and discuss strategies for improvement. Throughout the lessons that were reviewed, many common mistakes continued to pop up. These mistakes included age appropriateness, technology resources that were available, and consistency of student’s skill levels. Many of these lessons were written for the wrong grade levels. The ones written for the elementary level all had activities that assumed that every student in the class could read at grade level and also had background knowledge of the cyber activity at hand, which is not always the case. Another major mistake was that these lessons assumed that all schools had any kind of technology resource available to them. Some schools are 1:1, and others are only allotted three computers in their classroom where the students have to share. While coming up with a cyber-curriculum, it has to be kept in mind that not all schools are the same, not every classroom is the same. There are many students who are not reading at their grade level or have not had exposure to the digital world. We need to start slow and ease children into the cyber world. Once they have a better understanding, it will be easier to move forward with these lessons and get the students engaged. With a better understanding of common mistakes that are being made, a more robust curriculum and lessons can be created that no only spark a student’s interest in this much-needed career field but encourage learning while keeping our students safe from cyber-attacks.

Keywords: assumptions, cybersecurity, k-12, teacher

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Authors: Noor-ul-Amin, Lubna Nawab, Sabiha Sultana

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Geopolymer with different silica to alumina ratio with iron have been synthesized using sodium silicate, aluminum, and iron salts as a source of silica, alumina and iron source, and sodium/potassium hydroxide as an alkaline medium. The iron source will be taken from iron (III) salts and laterite clay samples. Laterite has been used as a natural source of iron in modified geopolymer. The synthesized iron modified geopolymer was submitted to the different aggressive environment, including chloride and sulphate solutions in different concentration. Different experimental techniques, including XRF, XRD, and FTIR, were used to study the bonding nature and effect of aggressive environment on geopolymer. The major phases formed during geopolymerization are sodalite (Na₄Al₃Si₃O₁₂Cl), albite (NaAlSi₃O₈), hematite (Fe₂O₃), and chabazite as confirmed from the XRD results. The resulting geopolymer showed greater resistance to sulphate and chloride as compared to the normal geopolymer.

Keywords: modified geopolymer, laterite, chloride, sulphate

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Authors: Nicola Colaninno, Eugenio Morello

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The urban environment affects local-to-global climate and, in turn, suffers global warming phenomena, with worrying impacts on human well-being, health, social and economic activities. Physic-morphological features of the built-up space affect urban air temperature, locally, causing the urban environment to be warmer compared to surrounding rural. This occurrence, typically known as the Urban Heat Island (UHI), is normally assessed by means of air temperature from fixed weather stations and/or traverse observations or based on remotely sensed Land Surface Temperatures (LST). The information provided by ground weather stations is key for assessing local air temperature. However, the spatial coverage is normally limited due to low density and uneven distribution of the stations. Although different interpolation techniques such as Inverse Distance Weighting (IDW), Ordinary Kriging (OK), or Multiple Linear Regression (MLR) are used to estimate air temperature from observed points, such an approach may not effectively reflect the real climatic conditions of an interpolated point. Quantifying local UHI for extensive areas based on weather stations’ observations only is not practicable. Alternatively, the use of thermal remote sensing has been widely investigated based on LST. Data from Landsat, ASTER, or MODIS have been extensively used. Indeed, LST has an indirect but significant influence on air temperatures. However, high-resolution near-surface air temperature (NSAT) is currently difficult to retrieve. Here we have experimented Geographically Weighted Regression (GWR) as an effective approach to enable NSAT estimation by accounting for spatial non-stationarity of the phenomenon. The model combines on-site measurements of air temperature, from fixed weather stations and satellite-derived LST. The approach is structured upon two main steps. First, a GWR model has been set to estimate NSAT at low resolution, by combining air temperature from discrete observations retrieved by weather stations (dependent variable) and the LST from satellite observations (predictor). At this step, MODIS data, from Terra satellite, at 1 kilometer of spatial resolution have been employed. Two time periods are considered according to satellite revisit period, i.e. 10:30 am and 9:30 pm. Afterward, the results have been downscaled at 30 meters of spatial resolution by setting a GWR model between the previously retrieved near-surface air temperature (dependent variable), the multispectral information as provided by the Landsat mission, in particular the albedo, and Digital Elevation Model (DEM) from the Shuttle Radar Topography Mission (SRTM), both at 30 meters. Albedo and DEM are now the predictors. The area under investigation is the Metropolitan City of Milan, which covers an area of approximately 1,575 km2 and encompasses a population of over 3 million inhabitants. Both models, low- (1 km) and high-resolution (30 meters), have been validated according to a cross-validation that relies on indicators such as R2, Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). All the employed indicators give evidence of highly efficient models. In addition, an alternative network of weather stations, available for the City of Milano only, has been employed for testing the accuracy of the predicted temperatures, giving and RMSE of 0.6 and 0.7 for daytime and night-time, respectively.

Keywords: urban climate, urban heat island, geographically weighted regression, remote sensing

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Authors: Yaxin Bi

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Accurate prediction and understanding of the evolution mechanisms of earthquakes remain challenging in the fields of geology, geophysics, and seismology. This study leverages Long Short-Term Memory (LSTM) networks and Generative Adversarial Networks (GANs), a generative model tailored to time-series data, for generating synthetic time series data based on Swarm satellite data, which will be used for detecting seismic anomalies. LSTMs demonstrated commendable predictive performance in generating synthetic data across multiple countries. In contrast, the GAN models struggled to generate synthetic data, often producing non-informative values, although they were able to capture the data distribution of the time series. These findings highlight both the promise and challenges associated with applying deep learning techniques to generate synthetic data, underscoring the potential of deep learning in generating synthetic electromagnetic satellite data.

Keywords: LSTM, GAN, earthquake, synthetic data, generative AI, seismic precursors

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