Search results for: learning delivery modes

Authors: Fang Gong

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Distance measures are an indispensable part of many instance-based learning (IBL) and machine learning (ML) algorithms. The value difference metrics (VDM) and inverted specific-class distance measure (ISCDM) are among the top-performing distance measures that address nominal attributes. VDM performs well in some domains owing to its simplicity and poorly in others that exist missing value and non-class attribute noise. ISCDM, however, typically works better than VDM on such domains. To maximize their advantages and avoid disadvantages, in this paper, a selection approach: a discriminative model for nominal attributes-based distance measures is proposed. More concretely, VDM and ISCDM are built independently on a training dataset at the training stage, and the most credible one is recorded for each training instance. At the test stage, its nearest neighbor for each test instance is primarily found by any of VDM and ISCDM and then chooses the most reliable model of its nearest neighbor to predict its class label. It is simply denoted as a discriminative distance measure (DDM). Experiments are conducted on the 34 University of California at Irvine (UCI) machine learning repository datasets, and it shows DDM retains the interpretability and simplicity of VDM and ISCDM but significantly outperforms the original VDM and ISCDM and other state-of-the-art competitors in terms of accuracy.

Keywords: distance measure, discriminative model, nominal attributes, nearest neighbor

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Authors: Lorena Alemán de la Garza, Marcela Georgina Gómez-Zermeño

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This paper presents the SolarSPELL case study that aims to generate information on the use of indicators that help evaluate the pedagogical quality of a digital library resources. SolarSPELL is a solar-powered digital library with WiFi connectivity. It offers a variety of open educational resources selected for their potential for the digital transformation of educational practices and the achievement of the 2030 Agenda for Sustainable Development, adopted by all United Nations Member States. The case study employed a quantitative methodology and the research instrument was applied to 55 teachers, directors and librarians. The results indicate that it is possible to strengthen the pedagogical quality of open educational resources, through actions focused on improving temporal and technological parameters. They also reveal that users believe that SolarSPELL improves the teaching-learning processes and motivates the teacher to improve his or her development. This study provides valuable information on a tool that supports teaching-learning processes and facilitates connectivity with renewable energies that improves the teacher training in active methodologies for ecosystem learning.

Keywords: educational innovation, digital library, pedagogical quality, solar energy, teacher training, sustainable development

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Authors: Naima Bouslah, Leila Bounabi, Farid Ouazib, Nabila Haddadine

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Conventional release dosage forms are known to provide an immediate release of the drug. Controlling the rate of drug release from polymeric matrices is very important for a number of applications, particularly in the pharmaceutical area. Hydrogels are polymers in three-dimensional network arrangement, which can absorb and retain large amounts of water without dissolution. They have been frequently used to develop controlled released formulations for oral administration because they can extend the duration of drug release and thus reduce dose to be administrated improving patient compliance. Tramadol is an opioid pain medication used to treat moderate to moderately severe pain. When taken as an immediate-release oral formulation, the onset of pain relief usually occurs within about an hour. In the present work, we synthesized pH-responsive hydrogels of (hydroxyl ethyl methacrylate-co-acrylic acid), (HEMA-AA) for control drug delivery of tramadol in the gastro-intestinal tractus. The hydrogels with different acrylic acid content, were synthesized by free radical polymerization and characterized by FTIR spectroscopy, X ray diffraction analysis (XRD), differential scanning calorimetry (DSC) and thermo gravimetric analysis (TGA). FTIR spectroscopy has shown specific hydrogen bonding interactions between the carbonyl groups of the hydrogels and hydroxyl groups of tramadol. Both the XRD and DSC studies revealed that the introduction of tramadol in the hydrogel network induced the amorphization of the drug. The swelling behaviour, absorptive kinetics and the release kinetics of tramadol in simulated gastric fluid (pH 1.2) and in simulated intestinal fluid (pH 7.4) were also investigated. The hydrogels exhibited pH-responsive behavior in the swelling study. The (HEMA-AA) hydrogel swelling was much higher in pH =7.4 medium. The tramadol release was significantly increased when pH of the medium was changed from simulated gastric fluid (pH 1.2) to simulated intestinal fluid (pH 7.4). Using suitable mathematical models, the apparent diffusional coefficients and the corresponding kinetic parameters have been calculated.

Keywords: biopolymres, drug delivery, hydrogels, tramadol

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Authors: Carly Madge, Melanie Zurba, Ryan Bullock

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The Boreal Forest has experienced some of the most drastic climate change-induced temperature rises in Canada, with average winter temperatures increasing by 3°C since 1948. One of the main concerns of the province of Saskatchewan, and particularly wildfire managers, is the increased risk of wildfires due to climate change. With these concerns in mind Sakaw Askiy Management Inc., a forestry corporation located in Prince Albert, Saskatchewan with operations in the Boreal Forest biome, is developing wildfire risk reduction strategies that are supported by the shareholders of the corporation as well as the stakeholders of the Prince Albert Forest Management Area (which includes citizens, hunters, trappers, cottage owners, and outfitters). In the past, wildfire management strategies implemented through harvesting have been received with skepticism by some community members of Prince Albert. Engagement of the stakeholders of the Prince Albert Management Area through the development of the wildfire risk reduction strategies aims to reduce this skepticism and rebuild some of the trust that has been lost between industry and community. This research project works with the framework of social learning, which is defined as the learning that occurs when individuals come together to form a group with the purpose of understanding environmental challenges and determining appropriate responses to them. The project evaluates the social learning processes that occur through the development of the risk reduction strategies and how the learning has allowed Sakaw to work towards implementing the strategies into their forest harvesting plans. The incorporation of wildfire risk reduction strategies works to increase the adaptive capacity of Sakaw, which in this case refers to the ability to adjust to climate change, moderate potential damages, take advantage of opportunities, and cope with consequences. Using semi-structured interviews and wildfire workshop meetings shareholders and stakeholders shared their knowledge of wildfire, their main wildfire concerns, and changes they would like to see made in the Prince Albert Forest Management Area. Interviews and topics discussed in the workshops were inductively coded for themes related to learning, adaptive capacity, areas of concern, and preferred methods of wildfire risk reduction strategies. Analysis determined that some of the learning that has occurred has resulted through social interactions and the development of networks oriented towards wildfire and wildfire risk reduction strategies. Participants have learned new knowledge and skills regarding wildfire risk reduction. The formation of wildfire networks increases access to information on wildfire and the social capital (trust and strengthened relations) of wildfire personnel. Both factors can be attributed to increases in adaptive capacity. Interview results were shared with the General Manager of Sakaw, where the areas of concern and preferred strategies of wildfire risk reduction will be considered and accounted for in the implementation of new harvesting plans. This research also augments the growing conceptual and empirical evidence of the important role of learning and networks in regional wildfire risk management efforts.

Keywords: adaptive capacity, community-engagement, social learning, wildfire risk reduction

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Authors: Jamie Sundvall, Lisa Jennings

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Site based field internship learning (SBL) is an educational approach within a Master’s of Social Work (MSW) university field placement department that promotes a more streamlined approach to the integration of theory and evidence based practices for social work students. The SBL model is founded on research in the field, consideration of current work force needs, United States national trends of MSW graduate skill and knowledge deficits, educational trends in students pursing a master’s degree in social work, and current social problems that require unique problem solving skills. This study explores the use of site-based learning in a hybrid social work program. In this setting, site based learning pairs online education courses and social work field education to create training opportunities for social work students within their own community and cultural context. Students engage in coursework in an online setting with both synchronous and asynchronous features that facilitate development of core competencies for MSW students. Through the SBL model, students are then partnered with faculty in a virtual course room and a university vetted site within their community. The study explores how this model of learning creates community partnerships, through which students engage in a learning loop to develop social work skills, while preparing students to address current community, social, and global issues with the engagement of technology. The goal of SBL is to more effectively equip social work students for practice according to current workforce demands, provide access to education and care to populations who have limited access, and create self-sustainable partnerships. Further, the model helps students learn integration of evidence based practices and helps instructors more effectively teach integration of ethics into practice. The study found that the SBL model increases the influence and professional relevance of the social work profession, and ultimately facilitates stronger approaches to integrating theory into practice. Current implementation of the practice in the United States will be presented in the study. dditionally, future research conceptualization of SBL models will be presented, in order to collaborate on advancing best approaches of translating theory into practice, according to the current needs of the profession and needs of social work students.

Keywords: collaboration, fieldwork, research, site-based learning, technology

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Authors: Ogbeta I. Joseph, Habiba B. A. Awwalu, Otokiti Jimoh

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This paper entitled science education in Nigeria issues and challenges highlighted the role of science education to the development of science and technology in Nigeria. Science embraces every attempt of human to explore and manage the natural world, the contribution of science education to the technological development of the nation, the role of science education in ICT development, the importance of mathematics in the development of science education, the paper also analyzed the challenges facing the development of science education to include corruption, insecurity, and political instability, the paper concluded by encouraging the government and other stakeholders in educational sector to pay more attention to the teaching and learning of science in our schools. Therefore recommended the development that emphasizes should be on the teaching and learning of science base subjects in the school.

Keywords: education, science, technology and national development, challenges

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Authors: Kornelia Kordiak

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The research is based on a biographical approach and serves as a foundation for understanding individual human destinies through the analysis of the context of life experiences. It focuses on the significance of childhood in shaping family micro-worlds from the perspective of biographical learning. In this case, the family micro-world is interpreted as a complex of beliefs and judgments about elements of the ‘total universe’ based on the individual's experiences. The main aim of the research is to understand the importance of childhood in shaping family micro-worlds from the perspective of reflection on biographical learning. Additionally, it contributes to a deeper understanding of the familial experiences of the studied individuals who form these family micro-worlds and the course of the biographical learning process in the subjects. Biographical research aligns with an interpretative paradigm, where individuals are treated as active interpreters of the world, giving meaning to their experiences and actions based on their own values and beliefs. The research methods used in the project—narrative interview method and analysis of personal documents—enable obtaining a multidimensional perspective on the phenomenon under study. Narrative interviews serve as the main data collection method, allowing researchers to delve into various life contexts of individuals. Analysis of these narratives identifies key moments and life patterns, as well as discovers the significance of childhood in shaping family micro-worlds. Moreover, analysis of personal documents such as diaries or photographs enriches the understanding of the studied phenomena by providing additional contexts and perspectives. The research will be conducted in three phases: preparatory, main, and final. The anticipated schedule includes preparation of research tools, selection of research sample, conducting narrative interviews and analysis of personal documents, as well as analysis and interpretation of collected research material. The narrative interview method and document analysis will be utilized to capture various contexts and interpretations of childhood experiences and family relations. The research will contribute to a better understanding of family dynamics and individual developmental processes. It will allow for the identification and understanding of mechanisms of biographical learning and their significance in shaping identity and family relations. Analysis of adult narratives will enable the identification of factors determining patterns of behavior and attitudes in adult life, which may have significant implications for pedagogical practice.

Keywords: childhood, adulthood, biographical learning, narrative interview, analysis of personal documents, family micro-worlds

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Authors: Surajit Chakrabarty, Piyush Chauhan, Subhasis Panda, Sujoy Bhattacharya

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A large proportion of roads in India are not well maintained as per the laid down public safety guidelines leading to loss of direction control and fatal accidents. We propose a technique to detect speed breakers and potholes using mobile sensor data captured from multiple vehicles and provide a profile of the road. This would, in turn, help in monitoring roads and revolutionize digital maps. Incorporating randomness in the model formulation for detection of speed breakers and potholes is crucial due to substantial heterogeneity observed in data obtained using a mobile application from multiple vehicles driven by different drivers. This is accomplished with Hidden Markov Models, whose hidden state sequence is found for each time step given the observables sequence, and are then fed as input to LSTM network with peephole connections. A precision score of 0.96 and 0.63 is obtained for classifying bumps and potholes, respectively, a significant improvement from the machine learning based models. Further visualization of bumps/potholes is done by converting time series to images using Markov Transition Fields where a significant demarcation among bump/potholes is observed.

Keywords: deep learning, hidden Markov model, pothole, speed breaker

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Authors: Julie Mariam Abraham, G. J. Melendez-Torres

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Background. Maternal mortality is disproportionately higher in low- and middle- income countries (LMICs) compared to other parts of the world. At the current pace of progress, the Sustainable Development Goals for maternal mortality rate will not be achieved by 2030. A variety of factors influence the increased risk of maternal complications in LMICs. These are exacerbated by socio-economic and political factors, including poverty, illiteracy, and gender inequality. This paper aims to use realist synthesis to identify the contexts, mechanisms, and outcomes (CMOs) of maternal health interventions conducted in LMICs to inform evidence-based practice for future maternal health interventions. Methods. In May 2022, we searched four electronic databases for systematic reviews of maternal health interventions in LMICs published in the last five years. We used open and axial coding of CMOs to develop an explanatory framework for intervention effectiveness. Results. After eligibility screening and full-text analysis, 44 papers were included. The intervention strategies and measured outcomes varied within reviews. Healthcare system level contextual factors were the most frequently reported, and infrastructural capacity was the most reported context. The most prevalent mechanism was increased knowledge and awareness. Discussion. Health system infrastructure must be considered in interventions to ensure effective implementation and sustainability. Healthcare-seeking behaviours are embedded within social and cultural norms, environmental conditions, family influences, and provider attitudes. Therefore, effective engagement with communities and families is important to create new norms surrounding pregnancy and delivery. Future research should explore community mobilisation and involvement to enable tailored interventions with optimal contextual fit.

Keywords: maternal mortality, service delivery and organisation, realist synthesis, sustainable development goals, overview of reviews

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Authors: Vijaya Dixit Aasheesh Dixit

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Shipbuilding industry operates in Engineer Procure Construct (EPC) context. Product mix of a shipyard comprises of various types of ships like bulk carriers, tankers, barges, coast guard vessels, sub-marines etc. Each order is unique based on the type of ship and customized requirements, which are engineered into the product right from design stage. Thus, to execute every new project, a shipyard needs to upgrade its production expertise. As a result, over the long run, holistic learning occurs across different types of projects which contributes to the knowledge base of the shipyard. Simultaneously, in the short term, during execution of a project comprising of multiple sister ships, repetition of similar tasks leads to learning at activity level. This research aims to capture above learnings of a shipyard and incorporate learning curve effect in project scheduling and materials procurement to improve project performance. Extant literature provides support for the existence of such learnings in an organization. In shipbuilding, there are sequences of similar activities which are expected to exhibit learning curve behavior. For example, the nearly identical structural sub-blocks which are successively fabricated, erected, and outfitted with piping and electrical systems. Learning curve representation can model not only a decrease in mean completion time of an activity, but also a decrease in uncertainty of activity duration. Sister ships have similar material requirements. The same supplier base supplies materials for all the sister ships within a project. On one hand, this provides an opportunity to reduce transportation cost by batching the order quantities of multiple ships. On the other hand, it increases the inventory holding cost at shipyard and the risk of obsolescence. Further, due to learning curve effect the production scheduled of each consequent ship gets compressed. Thus, the material requirement schedule of every next ship differs from its previous ship. As more and more ships get constructed, compressed production schedules increase the possibility of batching the orders of sister ships. This work aims at integrating materials management with project scheduling of long duration projects for manufacturing of multiple sister ships. It incorporates the learning curve effect on progressively compressing material requirement schedules and addresses the above trade-off of transportation cost and inventory holding and shortage costs while satisfying budget constraints of various stages of the project. The activity durations and lead time of items are not crisp and are available in the form of probabilistic distribution. A Stochastic Mixed Integer Programming (SMIP) model is formulated which is solved using evolutionary algorithm. Its output provides ordering dates of items and degree of order batching for all types of items. Sensitivity analysis determines the threshold number of sister ships required in a project to leverage the advantage of learning curve effect in materials management decisions. This analysis will help materials managers to gain insights about the scenarios: when and to what degree is it beneficial to treat a multiple ship project as an integrated one by batching the order quantities and when and to what degree to practice distinctive procurement for individual ship.

Keywords: learning curve, materials management, shipbuilding, sister ships

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Authors: Sibonakaliso Shadrack Nhlabathi

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In South Africa local governments which are charged with the provision of services and amenities, frequently, face challenges of public protests against what the public perceives to be poor services. Public protests are common, even though the Integrated Development Plan, a central public participation document, which informs local government planning and resources management, ought to be a reflection of the voices of the beneficiary communities. The Integrated Development Plan concept –which evolved from the international discourse on governance, planning, and urban management of the 1990s, and, which bears similarities to the UK’s approaches to urban management and planning– is a significant concept in the planning practice in South Africa. Against this backdrop of the spread of public protests and the supposedly public participation in IDP formulation, this study investigated the extent to which residents of the city of uMhlathuze municipality, South Africa, could use Geographical Information Systems (GIS) Story Maps to enhance public participation in the provision of services and amenities. To this effect, this study collected and analysed data obtained through interactive web maps or hard copy maps; this map data was accompanied by research participants’ attributes data. Research participants identified positive or negative service delivery areas. Positive places were the places which the residents represented as good infrastructural, and amenities areas and weak places were marked as poor amenities. Participants then located each of their identified strong or weak places as points on the GIS Story Maps or on hard copy maps of the city. The information which participants provided was subsequently analysed to produce maps of patterns of service provision. In this way, the study succeeded to identify places that needed attention regarding delivery of services and amenities. Thus, this study advanced service provision through GIS Story Maps.

Keywords: GIS, IPD, South Africa, story maps

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Authors: Proud Arunrangsiwed

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Crisis management strategies could be found in various curriculums, not only in schools of business, but also schools of communication. Young students, such as freshmen and sophomores of undergraduate schools, may not care about learning crisis management strategies. Moreover, crisis management strategies are not a topic art students are familiar with. The current paper discusses a way to adapt entertainment media into a crisis management lesson, and the importance of learning crisis management strategies in the school of animation. Students could learn crisis management strategies by watching movies with content about a crisis and responding to crisis responding. The students should then participate in follow up discussions related to the strategies that were used to address the crisis, as well as their success in solving the crisis.

Keywords: situational crisis communication theory, crisis response strategies, media effect, unintentional effect

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Authors: Beverley Gallimore

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The Individuals with Disabilities Education Act of 2004 (IDEA) has helped to improve outcomes for students with special education needs. Through IDEA, students with Special Education Needs (SEN) have opportunities for more equitable education within the General Education classroom. However, students with disabilities lack access to instructions that can help them to maximize their fullest learning potential. Recently, educational stakeholders have emphasized Integrated Co-teaching as a tool to increase engagement and learning outcomes for students with disabilities in general education classrooms. As a result of this new approach, general and special education teachers are working collaboratively to teach students with disabilities. However, co-teaching models are not properly designed and structured to effectively benefit students with disabilities. Teachers must be oriented correctly in the co-teaching models if it is to be beneficial for students.

Keywords: CO-teaching, differentiation, equitable, collaborative

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Authors: Wieke Ellen Bouwes

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This study aims to unravel which factors enhance accessibility of video consultations (VCs) for patients with low digital literacy. Thirteen in-depth interviews with patients, hospital employees, eHealth experts, and digital support organizations were held. Patients with low digital literacy received in-home support during real-time video consultations and are observed during the set-up of these consultations. Key findings highlight the importance of patient acceptance, emphasizing video consultations benefits and avoiding standardized courses. The lack of a uniform video consultation system across healthcare providers poses a barrier. Familiarity with support organizations – to support patients in usage of digital tools - among healthcare practitioners enhances accessibility. Moreover, considerations regarding the Dutch General Data Protection Regulation (GDPR) law influence support patients receive. Also, provider readiness to use video consultations influences patient access. Further, alignment between learning styles and support methods seems to determine abilities to learn how to use video consultations. Future research could delve into tailored learning styles and technological solutions for remote access to further explore effectiveness of learning methods.

Keywords: video consultations, digital literacy skills, effectiveness of support, intra- and inter-organizational relationships, patient acceptance of video consultations

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Authors: Bahram Besharti, Hossein Navid, Hadi Karimi, Hossein Behfar, Iraj Eskandari

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Multiple or miss sowing by seed drills is a common problem on the farm. This problem causes overuse of seeds, wasting energy, rising crop treatment cost and reducing crop yield in harvesting. To be informed of mentioned faults and monitoring the performance of seed drills during sowing, developing a seed sensor for detecting seed mass flow rate and monitoring in a delivery tube is essential. In this research, an infrared seed sensor was developed to estimate seed mass flow rate in seed drills. The developed sensor comprised of a pair of spaced apart circuits one acting as an IR transmitter and the other acting as an IR receiver. Optical coverage in the sensing section was obtained by setting IR LEDs and photo-diodes directly on opposite sides. Passing seeds made interruption in radiation beams to the photo-diode which caused output voltages to change. The voltage difference of sensing units summed by a microcontroller and were converted to an analog value by DAC chip. The sensor was tested by using a roller seed metering device with three types of seeds consist of chickpea, wheat, and alfalfa (representing large, medium and fine seed, respectively). The results revealed a good fitting between voltage received from seed sensor and mass flow of seeds in the delivery tube. A linear trend line was set for three seeds collected data as a model of the mass flow of seeds. A final mass flow model was developed for various size seeds based on receiving voltages from the seed sensor, thousand seed weight and equivalent diameter of seeds. The developed infrared seed sensor, besides monitoring mass flow of seeds in field operations, can be used for the assessment of mechanical planter seed metering unit performance in the laboratory and provide an easy calibrating method for seed drills before planting in the field.

Keywords: seed flow, infrared, seed sensor, seed drills

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Authors: Claus N. Holm, Oliver F. Grooss, Robert A. Alphinas

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This research strives to predict the remaining product life cycle of a song on radio after it has been played for one or two months. The best results were achieved using a k-d tree to calculate the most similar songs to the test songs and use a Random Forest model to forecast radio plays. An 82.78% and 83.44% accuracy is achieved for the two time periods, respectively. This explorative research leads to over 4500 test metrics to find the best combination of models and pre-processing techniques. Other algorithms tested are KNN, MLP and CNN. The features only consist of daily radio plays and use no musical features.

Keywords: hit song science, product life cycle, machine learning, radio

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Authors: David Lynch, Jake Madden

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There exists a body of literature that reports on the many benefits of partnerships between universities and schools, especially in terms of teaching improvement and school reform. This is because such partnerships can build significant teaching capital, by deepening and expanding the skillsets and mindsets needed to create the connections that support ongoing and embedded teacher professional development and career goals. At the same time, this literature is critical of such initiatives when the partnership outcomes are short- term or one-sided, misaligned to fundamental problems, and not expressly focused on building the desired teaching capabilities. In response to this situation, research conducted by Professor David Lynch and his TeachLab research team, has begun to shed light on the strengths and limitations of school/university partnerships, via the identification of key conceptual elements that appear to act as critical partnership success factors. These elements are theorised as an inter-play between professional knowledge acquisition, readiness, talent management and organisational structure. However, knowledge of how these elements are established, and how they manifest within the school and its teaching workforce as an overall system, remains incomplete. Therefore, research designed to more clearly delineate these elements in relation to their impact on school/university partnerships is thus required. It is within this context that this paper reports on the development and testing of a Professional Learning (PL) model for schools and their teachers that incorporates school-university research partnering within a systematic, whole-of-school PL strategy that is underpinned and structured by a micro-credentialing (MC) regime. MC involves learning a narrow-focused certificate (a micro-credential) in a specific topic area (e.g., 'How to Differentiate Instruction for English as a second language Students') and embedded in the teacher’s day-to-day teaching work. The use of MC is viewed as important to the efficacy and sustainability of teacher PL because it (1) provides an evidence-based framework for teacher learning, (2) has the ability to promote teacher social capital and (3) engender lifelong learning in keeping professional skills current in an embedded and seamless to work manner. The associated research is centred on a primary school in Australia (P-6) that acted as an arena to co-develop, test/investigate and report on outcomes for teacher PL that uses MC to support a whole-of-school partnership with a university.

Keywords: teaching improvement, teacher professional learning, talent management, education partnerships, school-university research

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Authors: Tomotaka Aoki, Isao Tomita

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We examined the on-off ratio and frequency components of output signals from an electron-interference device made of GaAs/AlₓGa₁₋ₓAs by solving the time-dependent Schrödinger's equation on conducting electrons in the channel waveguide of the device. For electron-wave modulation, a periodic voltage of frequency f was applied to the channel. Furthermore, we examined the voltage-amplitude dependence of the signals in time and frequency domains and found that large applied voltage deformed the output-signal waveform and created additional side modes (frequencies) near the modulation frequency f and that there was a trade-off between on-off ratio and side-mode creation.

Keywords: electrical conduction, electron interference, frequency spectrum, on-off ratio

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Authors: Mohammad H. Taheri, David J. Brown, Nasser Sherkat

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Engagement is one of the most important factors in determining successful outcomes and deep learning in students. Existing approaches to detect student engagement involve periodic human observations that are subject to inter-rater reliability. Our solution uses real-time multimodal multisensor data labeled by objective performance outcomes to infer the engagement of students. The study involves four students with a combined diagnosis of cerebral palsy and a learning disability who took part in a 3-month trial over 59 sessions. Multimodal multisensor data were collected while they participated in a continuous performance test. Eye gaze, electroencephalogram, body pose, and interaction data were used to create a model of student engagement through objective labeling from the continuous performance test outcomes. In order to achieve this, a type of continuous performance test is introduced, the Seek-X type. Nine features were extracted including high-level handpicked compound features. Using leave-one-out cross-validation, a series of different machine learning approaches were evaluated. Overall, the random forest classification approach achieved the best classification results. Using random forest, 93.3% classification for engagement and 42.9% accuracy for disengagement were achieved. We compared these results to outcomes from different models: AdaBoost, decision tree, k-Nearest Neighbor, naïve Bayes, neural network, and support vector machine. We showed that using a multisensor approach achieved higher accuracy than using features from any reduced set of sensors. We found that using high-level handpicked features can improve the classification accuracy in every sensor mode. Our approach is robust to both sensor fallout and occlusions. The single most important sensor feature to the classification of engagement and distraction was shown to be eye gaze. It has been shown that we can accurately predict the level of engagement of students with learning disabilities in a real-time approach that is not subject to inter-rater reliability, human observation or reliant on a single mode of sensor input. This will help teachers design interventions for a heterogeneous group of students, where teachers cannot possibly attend to each of their individual needs. Our approach can be used to identify those with the greatest learning challenges so that all students are supported to reach their full potential.

Keywords: affective computing in education, affect detection, continuous performance test, engagement, flow, HCI, interaction, learning disabilities, machine learning, multimodal, multisensor, physiological sensors, student engagement

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Authors: Parisa Shirzadeh

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Drug delivery systems in which drugs are traditionally used, multi-stage and at specified intervals by patients, do not meet the needs of the world's up-to-date drug delivery. In today's world, we are dealing with a huge number of recombinant peptide and protean drugs and analogues of hormones in the body, most of which are made with genetic engineering techniques. Most of these drugs are used to treat critical diseases such as cancer. Due to the limitations of the traditional method, researchers sought to find ways to solve the problems of the traditional method to a large extent. Following these efforts, controlled drug release systems were introduced, which have many advantages. Using controlled release of the drug in the body, the concentration of the drug is kept at a certain level, and in a short time, it is done at a higher rate. Graphene is a natural material that is biodegradable, non-toxic, and natural compared to carbon nanotubes; its price is lower than carbon nanotubes and is cost-effective for industrialization. On the other hand, the presence of highly effective surfaces and wide surfaces of graphene plates makes it more effective to modify graphene than carbon nanotubes. Graphene oxide is often synthesized using concentrated oxidizers such as sulfuric acid, nitric acid, and potassium permanganate based on Hummer 1 method. In comparison with the initial graphene, the resulting graphene oxide is heavier and has carboxyl, hydroxyl, and epoxy groups. Therefore, graphene oxide is very hydrophilic and easily dissolves in water and creates a stable solution. On the other hand, because the hydroxyl, carboxyl, and epoxy groups created on the surface are highly reactive, they have the ability to work with other functional groups such as amines, esters, polymers, etc. Connect and bring new features to the surface of graphene. In fact, it can be concluded that the creation of hydroxyl groups, Carboxyl, and epoxy and in fact graphene oxidation is the first step and step in creating other functional groups on the surface of graphene. Chitosan is a natural polymer and does not cause toxicity in the body. Due to its chemical structure and having OH and NH groups, it is suitable for binding to graphene oxide and increasing its solubility in aqueous solutions. Graphene oxide (GO) has been modified by chitosan (CS) covalently, developed for control release of doxorubicin (DOX). In this study, GO is produced by the hummer method under acidic conditions. Then, it is chlorinated by oxalyl chloride to increase its reactivity against amine. After that, in the presence of chitosan, the amino reaction was performed to form amide transplantation, and the doxorubicin was connected to the carrier surface by π-π interaction in buffer phosphate. GO, GO-CS, and GO-CS-DOX characterized by FT-IR, RAMAN, TGA, and SEM. The ability to load and release is determined by UV-Visible spectroscopy. The loading result showed a high capacity of DOX absorption (99%) and pH dependence identified as a result of DOX release from GO-CS nanosheet at pH 5.3 and 7.4, which show a fast release rate in acidic conditions.

Keywords: graphene oxide, chitosan, nanosheet, controlled drug release, doxorubicin

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Authors: Azadeh Afrasyabi, Ali Khaleghi, Aliakbar Alijarahi

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Training at an early age is so important, because of tremendous changes in adolescence, including the formation of character, physical changes and other factors. One of the most sensitive sectors in this field is the children with a disability and are somehow special children who have trouble in communicating with their environment. One of the emerging technologies in the field of education that can be effectively profitable called augmented reality, where the combination of real world and virtual images in real time produces new concepts that can facilitate learning. The purpose of this paper is to propose an effective training method for special and disabled children based on augmented reality. Of course, in particular, the efficiency of augmented reality in teaching children with autism will consider, also examine the various aspect of this disease and different learning methods in this area.

Keywords: technology in education, augmented reality, special education, teaching methods

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Authors: Natascha C. D'Amico, Enzo Grossi, Giovanni Valbusa, Ala Malasevschi, Gianpiero Cardone, Sergio Papa

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Purpose: To characterize, through a radiomic approach, the nature of areas classified PI-RADS (Prostate Imaging Reporting and Data System) 3/5, recognized in multiparametric prostate magnetic resonance with T2-weighted (T2w), diffusion and perfusion sequences with paramagnetic contrast. Methods and Materials: 24 cases undergoing multiparametric prostate MR and biopsy were admitted to this pilot study. Clinical outcome of the PI-RADS 3/5 was found through biopsy, finding 8 malignant tumours. The analysed images were acquired with a Philips achieva 1.5T machine with a CE- T2-weighted sequence in the axial plane. Semi-automatic tumour segmentation was carried out on MR images using 3DSlicer image analysis software. 45 shape-based, intensity-based and texture-based features were extracted and represented the input for preprocessing. An evolutionary algorithm (a TWIST system based on KNN algorithm) was used to subdivide the dataset into training and testing set and select features yielding the maximal amount of information. After this pre-processing 20 input variables were selected and different machine learning systems were used to develop a predictive model based on a training testing crossover procedure. Results: The best machine learning system (three-layers feed-forward neural network) obtained a global accuracy of 90% ( 80 % sensitivity and 100% specificity ) with a ROC of 0.82. Conclusion: Machine learning systems coupled with radiomics show a promising potential in distinguishing benign from malign tumours in PI-RADS 3/5 areas.

Keywords: machine learning, MR prostate, PI-Rads 3, radiomics

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Authors: Frida C. Jaime Franco, C. Paulina Navarro Núñez, R. Jacob Sánchez Nájera

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The importance of developing multi-language abilities in our global society is noteworthy. However, the necessity, interest, and consciousness of the significance that the development of another language represents, apart from the mother tongue, is not always the same in all contexts as it is in multicultural communities, especially in rural higher education institutions immersed in small communities. Leading opportunities for digital interaction among learners from Mexico and abroad partners represents scaffolding towards, not only language skills development but also intercultural communicative competences (ICC). This study leads us to consider what should be the best approach to work while applying a program of ICC integrated into the practice of EFL. While analyzing the roots of the language, it is possible to obtain the main objective of learning another language, to communicate with a functional purpose, as well as attaching social practices to the learning process, giving a result of functionality and significance to the target language. Hence, the collateral impact that collaborative learning leads to, aims to contribute to a better global understanding as well as a means of self and other cultural awareness through intercultural communication. While communicating through the target language by online collaboration among students in platforms of long-distance communication, language is used as a tool of interaction to broaden students’ perspectives reaching a substantial improvement with the help of their differences. This process should consider the application of the target language in the inquiry of sociocultural information, expecting the learners to integrate communicative skills to handle cultural differentiation at the same time they apply the knowledge of their target language in a real scenario of communication, despite being through virtual resources.

Keywords: collaborative learning, communicative approach, culture, interaction, interculturalism, target language, virtual partnership

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Authors: Thohidul Islam, Md. Hamidul Haque, Robin Kumar Biswas

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Floods are one of the deadliest natural disasters which are very complex to model; however, machine learning is opening the door for more reliable and accurate flood prediction. In this research, a multilayer perceptron neural network (MLP) is developed to model the rainfall-water level relation, in a subtropical monsoon climatic region of the Bangladesh-India border. Our experiments show promising empirical results to forecast the water level for 1 day lead time. Our best performing MLP model achieves 98.7% coefficient of determination with lower model complexity which surpasses previously reported results on similar forecasting problems.

Keywords: flood forecasting, machine learning, multilayer perceptron network, regression

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Authors: Gracia V. Navarro, Maria V. Gonzalez, Carlos G. Reed

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The eudaimonic perspective in philosophy and psychology suggests that a good life is closely related to developing oneself in order to contribute to the well-being and happiness of other people and of the world as a whole. Educational psychology can help to achieve this through the design and validation of educative models. Since 2004, the University of Concepcion and other Chilean universities apply an educative model to train socially responsible professionals, people that in the exercise of their profession contribute to generate equity for the development and assess the impacts of their decisions, opting for those that serve the common good. The main aim is to identify if a relationship exists between achieved learning, attitudes toward social responsibility, self-attribution of socially responsible behavior, value type, professional behavior observed and, participation in a specific model to train socially responsible (SR) professionals. The Achieved Learning and Attitudes Toward Social Responsibility Questionnaire, interview with employers and Values Questionnaire and Self-attribution of SR Behavior Questionnaire is applied to 394 students and graduates, divided into experimental and control groups (trained and not trained under the educative model), in order to identify the professional behavior of the graduates. The results show that students and graduates perceive cognitive, affective and behavioral learning, with significant differences in attitudes toward social responsibility and self-attribution of SR behavior, between experimental and control. There are also differences in employers' perceptions about the professional practice of those who were trained under the model and those who were not. It is concluded that the educative model has an impact on the learning of social responsibility and educates for a full life. It is also concluded that it is necessary to identify mediating variables of the model effect.

Keywords: educative model, good life, professional social responsibility, values

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Authors: Zabeehullah, Fahim Arif, Yawar Abbas

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Software Defined Network (SDN) is a next genera-tion networking model which simplifies the traditional network complexities and improve the utilization of constrained resources. Currently, most of the SDN based Internet of Things(IoT) environments use traditional network routing strategies which work on the basis of max or min metric value. However, IoT network heterogeneity, dynamic traffic flow and complexity demands intelligent and self-adaptive routing algorithms because traditional routing algorithms lack the self-adaptions, intelligence and efficient utilization of resources. To some extent, SDN, due its flexibility, and centralized control has managed the IoT complexity and heterogeneity but still Software Defined IoT (SDIoT) lacks intelligence. To address this challenge, we proposed a model called Deep Routing Strategy (DRS) which uses Deep Learning algorithm to perform routing in SDIoT intelligently and efficiently. Our model uses real-time traffic for training and learning. Results demonstrate that proposed model has achieved high accuracy and low packet loss rate during path selection. Proposed model has also outperformed benchmark routing algorithm (OSPF). Moreover, proposed model provided encouraging results during high dynamic traffic flow.

Keywords: SDN, IoT, DL, ML, DRS

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Authors: Flavio Campos

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This paper describes an implementation of a STEM curriculum program using robotics as a technological resource at a private school in Brazil. Emphasized the pedagogic and didactic aspects and brings a discussion about STEM curriculum and the perspective of using robotics and the relation between curriculum, science and technologies into the learning process. The results indicate that STEM curriculum integration with robotics as a technological resource in K-12 students learning process has complex aspects, such as relation between time/space, the development of educators and the relation between robotics and other subjects. Therefore, the comprehension of these aspects could indicate some steps that we should consider when integrating STEM basis and robotics into curriculum, which can improve education for science and technology significantly.

Keywords: STEM curriculum, educational robotics, constructionist approach, education and technology

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Authors: Hashini E. Mohottala

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We report the combine use of Wikispaces (WikiS) and Group Problem Solving (GPS) sessions conducted in the introductory level physics classes. As a part of this new teaching tool, some essay type problems were posted on the WikiS in weekly basis and students were encouraged to participate in problem solving without providing numerical final answers but the steps. Wikispace is used as a platform for students to meet online and create discussions. Each week students were further evaluated on problem solving skills opening up more opportunity for peer interaction through GPS. Each group was given a different problem to solve and the answers were graded. Students developed a set of skills in decision-making, problem solving, communication, negotiation, critical and independent thinking and teamwork through the combination of WikiS and GPS.

Keywords: group problem solving (GPS), wikispace (WikiS), physics education, learning

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Authors: Sungmin Park, Gyungmok Nam, Seungpyo Woo, Young Choi, Sangheon Park, Sang-Hee Yoon

Abstract:

Puncturing human skin with microneedles is critically important for microneedle-mediate drug delivery. Despite of extensive efforts in the past decades, the scale-up fabrication of sharp-tipped and high-aspect-ratio microneedles, especially made of biodegradable polymers, is still a long way off. Here, we present a UV dose insensitive and cost-effective microfabrication method for the biodegradable polymer microneedles with sharp tips and long lengths which can pierce human skin with low insertion force. The biodegradable polymer microneedles are fabricated with the polymer solution casting where a poly(lactic-co-glycolic acid) (PLGA, 50:50) solution is coated onto a SU-8 mold prepared with a reverse, ramped, and rotational (R3) UV exposure. The R3 UV exposure is modified from the multidirectional UV exposure both to suppress UV reflection from the bottom surface without anti-reflection layers and to optimize solvent concentration in the SU-8 photoresist, therefore achieving robust (i.e., highly insensitive to UV dose) and cost-effective fabrication of biodegradable polymer microneedles. An optical model for describing the spatial distribution of UV irradiation dose of the R3 UV exposure is also developed to theoretically predict the microneedle geometry fabricated with the R3 UV exposure and also to demonstrate the insensitiveness of microneedle geometry to UV dose. In the experimental characterization, the microneedles fabricated with the R3 UV exposure are compared with those fabricated with a conventional method (i.e., multidirectional UV exposure). The R3 UV exposure-based microfabrication reduces the end-tip radius by a factor of 5.8 and the deviation from ideal aspect ratio by 74.8%, compared with conventional method-based microfabrication. The PLGA microneedles fabricated with the R3 UV exposure pierce full-thickness porcine skins successfully and are demonstrated to completely dissolve in PBS (phosphate-buffered saline). The findings of this study will lead to an explosive growth of the microneedle-mediated drug delivery market.

Keywords: R³ UV exposure, optical model, UV dose, reflection, solvent concentration, biodegradable polymer microneedle

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Authors: Huai-Feng Wang, Meng-Lin Lou, Ru-Lin Zhang

Abstract:

One good analysis method in seismic response analysis is direct time integration, which widely adopts Rayleigh damping. An approach is presented for selection of Rayleigh damping coefficients to be used in seismic analyses to produce a response that is consistent with Modal damping response. In the presented approach, the expression of the error of peak response, acquired through complete quadratic combination method, and Rayleigh damping coefficients was set up and then the coefficients were produced by minimizing the error. Two finite element modes of soil layers, excited by 28 seismic waves, were used to demonstrate the feasibility and validity.

Keywords: Rayleigh damping, modal damping, damping coefficients, seismic response analysis

Procedia PDF Downloads 433