Search results for: deep learning.

Authors: Gabriele Iannotta

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This paper investigates credit cycles by means of an experiment based on a Kiyotaki & Moore (1997) model with heterogeneous expectations. The aim is to examine how a credit squeeze caused by high lender-level risk perceptions affects the real prices of a collateralised asset, with a special focus on the macroeconomic implications of rising price volatility in terms of total welfare and the number of bankruptcies that occur. To do that, a learning-to-forecast experiment (LtFE) has been run where participants are asked to predict the future price of land and then rewarded based on the accuracy of their forecasts. The setting includes one lender and five borrowers in each of the twelve sessions split between six control groups (G1) and six treatment groups (G2). The only difference is that while in G1 the lender always satisfies borrowers’ loan demand (bankruptcies permitting), in G2 he/she closes the entire credit market in case three or more bankruptcies occur in the previous round. Experimental results show that negative risk-driven supply shocks amplify the volatility of collateral prices. This uncertainty worsens the agents’ ability to predict the future value of land and, as a consequence, the number of defaults increases and the total welfare deteriorates.

Keywords: Behavioural Macroeconomics, Credit Cycle, Experimental Economics, Heterogeneous Expectations, Learning-to-Forecast Experiment

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Authors: Sara Mosteller, Larissa K. Samuelson, Sobanawartiny Wijeakumar, John P. Spencer

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This study was designed to examine how humans are able to teach and learn semantic information as well as cooperate in order to jointly achieve sophisticated goals. Specifically, we are measuring individual differences in how these abilities develop from foundational building blocks in early childhood. The current study adopts a paradigm for novel noun learning developed by Samuelson, Smith, Perry, and Spencer (2011) to a hyperscanning paradigm [Cui, Bryant and Reiss, 2012]. This project measures coordinated brain activity between a parent and child using simultaneous functional near infrared spectroscopy (fNIRS) in pairs of 2.5, 3.5 and 4.5-year-old children and their parents. We are also separately testing pairs of adult friends. Children and parents, or adult friends, are seated across from one another at a table. The parent (in the developmental study) then teaches their child the names of novel toys. An experimenter then tests the child by presenting the objects in pairs and asking the child to retrieve one object by name. Children are asked to choose from both pairs of familiar objects and pairs of novel objects. In order to explore individual differences in cooperation with the same participants, each dyad plays a cooperative game of Jenga, in which their joint score is based on how many blocks they can remove from the tower as a team. A preliminary analysis of the noun-learning task showed that, when presented with 6 word-object mappings, children learned an average of 3 new words (50%) and that the number of objects learned by each child ranged from 2-4. Adults initially learned all of the new words but were variable in their later retention of the mappings, which ranged from 50-100%. We are currently examining differences in cooperative behavior during the Jenga playing game, including time spent discussing each move before it is made. Ongoing analyses are examining the social dynamics that might underlie the differences between words that were successfully learned and unlearned words for each dyad, as well as the developmental differences observed in the study. Additionally, the Jenga game is being used to better understand individual and developmental differences in social coordination during a cooperative task. At a behavioral level, the analysis maps periods of joint visual attention between participants during the word learning and the Jenga game, using head-mounted eye trackers to assess each participant’s first-person viewpoint during the session. We are also analyzing the coherence in brain activity between participants during novel word-learning and Jenga playing. The first hypothesis is that visual joint attention during the session will be positively correlated with both the number of words learned and with the number of blocks moved during Jenga before the tower falls. The next hypothesis is that successful communication of new words and success in the game will each be positively correlated with synchronized brain activity between the parent and child/the adult friends in cortical regions underlying social cognition, semantic processing, and visual processing. This study probes both the neural and behavioral mechanisms of learning and cooperation in a naturalistic, interactive and developmental context.

Keywords: communication, cooperation, development, interaction, neuroscience

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Authors: Chungkuk Jin, Moohyun Kim, Woo Chul Chung

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This paper presents global performance and dynamic behaviors of a discrete-pontoon-type floating bridge with mooring lines in time domain under wind and wave excitations. The structure is designed for long-distance and deep-water crossing and consists of the girder, columns, pontoons, and mooring lines. Their functionality and behaviors are investigated by using elastic-floater/mooring fully-coupled dynamic simulation computer program. Dynamic wind, first- and second-order wave forces, and current loads are considered as environmental loads. Girder’s dynamic responses and mooring tensions are analyzed under different analysis methods and environmental conditions. Girder’s lateral responses are highly influenced by the second-order wave and wind loads while the first-order wave load mainly influences its vertical responses.

Keywords: floating bridge, mooring line, pontoon, wave excitation

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Authors: Chastiti Mediafira Wulolo

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Our Eyes is a cooperation pact in the field of intelligence information exchanges initiated by the Indonesian Ministry of Defense, which has been signed by Indonesia, Philippines, Malaysia, Brunei Darussalam, Thailand, and Singapore. This cooperation mostly engages the military acts as a central role, but this pact still requires the involvement of various parties such as police and other linear institution. This paper will use a qualitative content analysis method by doing some deep analyzing the pattern of cooperation itself. As the implementation of translantic counter-terrorism cooperation, this research will address how the role of Our Eyes can be optimized as a form of government’s response towards the contemporary threat in the Dynamics of Strategic Environmental Security in the Asia Pacific Region. Optimizing the role of this cooperation will also acquire from the previous counter-terrorism cooperation in ASEAN region, so it expects that Our Eyes collaboration can be the most effective cooperation in overcoming terrorism issues in ASEAN, eventually in Asia Pacific.

Keywords: our eyes, Defense Ministry of Indonesia, ASEAN, counter-terrorism

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Authors: David Tena-Gago, Jose M. Alcaraz Calero, Qi Wang

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The evolution and integration of automated vehicles have become more and more tangible in recent years. State-of-the-art technological advances in the field of camera-based Artificial Intelligence (AI) and computer vision greatly favor the performance and reliability of the Advanced Driver Assistance System (ADAS), leading to a greater knowledge of vehicular operation and resembling human behavior. However, the exclusive use of this technology still seems insufficient to control vehicular operation at 100%. To reveal the degree of accuracy of the current camera-based automated driving AI modules, this paper studies the structure and behavior of one of the main solutions in a controlled testing environment. The results obtained clearly outline the lack of reliability when using exclusively the AI model in the perception stage, thereby entailing using additional complementary sensors to improve its safety and performance.

Keywords: accuracy assessment, AI-driven mobility, artificial intelligence, automated vehicles

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Authors: Nour El Houda Arabi, Aicha Iratni, Talaighil Razika, Bruno Capoen, Mohamed Bouazaoui

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In this paper, we report the effect of the calcination temperature and SiO2 addition on structural, optical and hydrophilicity of TiO2 films deposited by deep-coating sol-gel process. XRD investigation of the structural TiO2 films with increasing the temperature calcination, reveals that rutile phase will appear for the high temperature (>1000°C). However, the addition of SiO2 relate the densification of TiO2 films. Ellipsometric and UV-visible measure show that the refractive index grow with increasing temperature, against the film thickness decreases. On the other hand, the addition of SiO2 decreases the refractive index and increases the TiO2 film thickness. Finally, the hydrophilicity is assisted by contact angle measurement. It is found that addition of 50% of SiO2 to TiO2 is most effective for reducing the contact angle of water.

Keywords: physical properties, sol, gel, TiO2/SiO2 composite films

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Authors: Yining Yu, Bingjie Li, Miaolei Jia, Lei Wang

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Ambient color temperature is one of the most ubiquitous factors in retailing. However, there is limited research regarding the effect of cold versus warm ambient color on consumers’ food consumption. This research investigates an unexplored lay belief named the “cold ambient color = healthy” intuition and its impact on food choice. We demonstrate that consumers have built the “cold ambient color = healthy” intuition, such that they infer that a restaurant with a cold-colored ambiance is more likely to sell healthy food than a warm-colored restaurant. This deep-seated intuition also guides consumers’ food choices. We find that using a cold (vs. warm) ambient color increases the choice of healthy food, which offers insights into healthy diet promotion for retailers and policymakers. Theoretically, our work contributes to the literature on color psychology, sensory marketing, and food consumption.

Keywords: ambient color temperature, cold ambient color, food choice, consumer wellbeing

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Authors: Regina Chua

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To reduce the costs of re-fielding a large survey, a Random Forest classifier was applied to measure the accuracy of classifying individuals into their assigned segments with the fewest possible questions. Given a long survey, one needed to determine the most predictive ten or fewer questions that would accurately assign new individuals to custom segments. Furthermore, the solution needed to be quick in its classification and usable in non-Python environments. In this paper, a supervised Random Forest classifier was modeled on a dataset with 7,000 individuals, 60 questions, and 254 features. The Random Forest consisted of an iterative collection of individual decision trees that result in a predicted segment with robust precision and recall scores compared to a single tree. A random 70-30 stratified sampling for training the algorithm was used, and accuracy trade-offs at different depths for each segment were identified. Ultimately, the Random Forest classifier performed at 87% accuracy at a depth of 10 with 20 instead of 254 features and 10 instead of 60 questions. With an acceptable accuracy in prioritizing feature selection, new tools were developed for non-Python environments: a worksheet with a formulaic version of the algorithm and an embedded function to predict the segment of an individual in real-time. Random Forest was determined to be an optimal classification model by its feature selection, performance, processing speed, and flexible application in other environments.

Keywords: machine learning, supervised learning, data science, random forest, classification, prediction, predictive modeling

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Authors: Pieter De Vries, Renate Klaassen, Maria Ioannides

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This paper is about an explorative research into the use of emerging technologies for teaching and learning in higher engineering education. The assumption is that these technologies and applications, which are not yet widely adopted, will help to improve education and as such actively work on the ability to better deal with the mismatch of skills bothering our industries. Technologies such as 3D printing, the Internet of Things, Virtual Reality, and others, are in a dynamic state of development which makes it difficult to grasp the value for education. Also, the instruments in current educational research seem not appropriate to assess the value of such technologies. This explorative research aims to foster an approach to better deal with this new complexity. The need to find out is urgent, because these technologies will be dominantly present in the near future in all aspects of life, including education. The methodology used in this research comprised an inventory of emerging technologies and tools that potentially give way to innovation and are used or about to be used in technical universities. The inventory was based on both a literature review and a review of reports and web resources like blogs and others and included a series of interviews with stakeholders in engineering education and at representative industries. In addition, a number of small experiments were executed with the aim to analyze the requirements for the use of in this case Virtual Reality and the Internet of Things to better understanding the opportunities and limitations in the day-today learning environment. The major findings indicate that it is rather difficult to decide about the value of these technologies for education due to the dynamic state of change and therefor unpredictability and the lack of a coherent policy at the institutions. Most decisions are being made by teachers on an individual basis, who in their micro-environment are not equipped to select, test and ultimately decide about the use of these technologies. Most experiences are being made in the industry knowing that the skills to handle these technologies are in high demand. The industry though is worried about the inclination and the capability of education to help bridge the skills gap related to the emergence of new technologies. Due to the complexity, the diversity, the speed of development and the decay, education is challenged to develop an approach that can make these technologies work in an integrated fashion. For education to fully profit from the opportunities, these technologies offer it is eminent to develop a pro-active strategy and a sustainable approach to frame the emerging technologies development.

Keywords: emerging technologies, internet of things, pro-active strategy, virtual reality

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Authors: Dina Salem

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A variety of definitions and interpretations for sustainable development has been offered since the widely known definition of the World Commission on Environment and Development in 1987, the perspectives have ranged from deep ecology to better life quality for people. Sustainable landscape is widely understood as a key contributor to urban sustainability for the fact that all landscapes has a social, economic, cultural and ecological function for the community’s well-being and urban development, that was evident even before the emergence of sustainability concept. In this paper, the concepts of landscape planning and sustainable development are briefly reviewed; visions for landscape sustainability are demonstrated and classified. Challenges facing sustainable landscape planning are discussed. Finally, the paper investigates how our future urban open space could be sustainable and how does this contribute to urban sustainability, by creating urban landscapes that takes into account the social and cultural values of users of urban open space besides the ecological balance of urban open spaces as an integrated network.

Keywords: urban landscape, urban sustainability, resilience, open spaces

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Authors: Alfia Sari

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The implementation of the Content Language Integrated Learning (CLIL) approach in Indonesia has shown positive impacts in several educational institutions. Several studies have proven the benefits of implementing the CLIL approach, including the development of students’ language and content subject knowledge. Interestingly, one primary school in Surabaya, Indonesia, has been successfully implementing the CLIL approach. The students achieved high content and language subject scores, and the school was accredited A. A study on how the CLIL approach was practiced is important to investigate how teachers implemented it and how students benefited from it. Therefore, this present study attempted to investigate the implementation of the CLIL approach in this school to characterize good practices that can be implemented in other schools. A case study was conducted to observe its implementation in the third-grade classes (English, Science, and Math) by using the Protocol for Language Arts Teaching Observation (PLATO). The findings indicated that the CLIL teaching in this school accommodated the content and language well (scores 3-4). The content and language were clearly integrated, and the teachers successfully carried out the subjects in English. Teachers offered students opportunities to listen, speak, read, and write using the target language. This study described some characteristics of CLIL teaching in primary school that can be used as examples for future CLIL teachers to integrate the content and language in their teaching practices.

Keywords: CLIL, ELT, young learners, case study

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Authors: Obokhai Kess Asikhia

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This work explores design concept generation by understanding user needs through observation and interview. The aim is to examine several principles and guidelines in obtaining evidence from observing how users interact with the targeted product and interviewing them to acquire deep insights of their needs. With the help of Quality Function Deployment (QFD), the identified needs of the users while interacting with the product were ranked using the normalised weighting approach. Furthermore, a low fidelity prototype of the alarm clock is developed with a view of addressing the identified needs of the users. Finally, the low fidelity prototype design was evaluated with two design prototypes already existing in the market through a study involving 30 participants. Preliminary results reveal higher performance ratings by the majority of the participants of the new prototype compared to the other existing alarm clocks in the market used in the study.

Keywords: design concept, low fidelity prototype, normalised weighting approach, quality function deployment, user needs

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Authors: Olufemi Sunday Onabajo

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Radio according to communication scholars is a veritable instrument of mass education. However, its full potentials in boosting higher education have not been realized because of the commercial nature of radio stations in Nigeria. The licensing of campus radio for disseminating information on university curricular is aimed at reinforcing information shared during face to face teaching. This study anchored on Agenda Setting and Technology determinism theories seeks to find out the extent to which university students in Lead City University and University of Ibadan, Nigeria have keyed-in to the philosophy of their campus radio – Lead City FM and Diamond FM in making information dissemination in their domiciled universities less cumbersome. The study employs both qualitative and quantitative methods though the use of depth interview for ten (10) academic staff and five (5) radio personnel of both radio stations; and a questionnaire addressed to 200 students of both institutions using the systematic random sampling technique. The data collected was analyzed using simple percentage and chi-square one tail test, and it was discovered that students of both universities and their radio personnel are yet to realize the potentials of campus radio as a resource alternative to effective learning, and recommends the coming together of all stakeholders to articulate the way forward.

Keywords: disseminating information, effective learning, resource alternative, utilizing radio

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Authors: Linda Fellag, Arlene Caney

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E-learning has earned an essential place in academia because it promotes learner autonomy, student engagement, and technological aptitude, and allows for flexible learning. However, despite advantages, educators have been slower to embrace e-learning for ESL and other non-traditional students for fear that such students will not succeed without the direct faculty contact and academic support of face-to-face classrooms. This study aims to determine if a non-traditional student-friendly online course can produce student retention and performance rates that compare favorably with those of students in standard online sections of the same course aimed at traditional college-level students. One Music faculty member is currently collaborating with an English instructor to redesign an online college-level Music Appreciation course for non-traditional college students. At Community College of Philadelphia, Introduction to Music Appreciation was recently designated as one of the few college-level courses that advanced ESL, and developmental English students can take while completing their language studies. Beginning in Fall 2017, the course will be critical for international students who must maintain full-time student status under visa requirements. In its current online format, however, Music Appreciation is designed for traditional college students, and faculty who teach these sections have been reluctant to revise the course to address the needs of non-traditional students. Interestingly, presenters maintain that the online platform is the ideal place to develop language and college readiness skills in at-risk students while maintaining the course's curricular integrity. The two faculty presenters describe how curriculum rather than technology drives the redesign of the digitized music course, and self-study materials, guided assignments, and periodic assessments promote independent learning and comprehension of material. The 'scaffolded' modules allow ESL and developmental English students to build on prior knowledge, preview key vocabulary, discuss content, and complete graded tasks that demonstrate comprehension. Activities and assignments, in turn, enhance college success by allowing students to practice academic reading strategies, writing, speaking, and student-faculty and peer-peer communication and collaboration. The course components facilitate a comparison of student performance and retention in sections of the redesigned and existing online sections of Music Appreciation as well as in previous sections with at-risk students. Indirect, qualitative measures include student attitudinal surveys and evaluations. Direct, quantitative measures include withdrawal rates, tests of disciplinary knowledge, and final grades. The study will compare the outcomes of three cohorts in the two versions of the online course: ESL students, at-risk developmental students, and college-level students. These data will also be compared with retention and student outcomes data of the three cohorts in f2f Music Appreciation, which permitted non-traditional student enrollment from 1998-2005. During this eight-year period, the presenter addressed the problems of at-risk students by adding language and college success support, which resulted in strong retention and outcomes. The presenters contend that the redesigned course will produce favorable outcomes among all three cohorts because it contains components which proved successful with at-risk learners in f2f sections of the course. Results of their study will be published in 2019 after the redesigned online course has met for two semesters.

Keywords: college readiness, e-learning, music appreciation, online courses

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Authors: Paul Dankers, Juliet Stoltenkamp, Carolynne Kies

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In May 2005, the University of the Western Cape (UWC) established an eLearning Division (ED) that, over the past 18 years, accelerated into the institutionalization of an efficient eLearning Centre. The initial objective of the ED was to incessantly align itself with emerging technologies caused by digital transformation, which progressively impacted Higher Education Institutions (HEIs) globally. In this paper, we present how the UWC eLearning Division (ED) first evolved into the eLearning Development and Support Unit (EDUS), currently called the ‘Centre for Innovative Education and Communication Technologies (CIECT). CIECT was strategically separated from the Department of Information and Communication Services (ICS) in 2009 and repositioned as an independent structure at UWC. Using a comparative research method, we highlight the transformative eLearning landscape at UWC by doing a detailed account of the shift in practices. Our research method will determine the initial vision and outcomes of institutionalizing an eLearning division. The study aims to compare across space or time the eLearning division’s rate of growth. By comparing the progressive growth of the UWCs eLearning division over the years, we will be able to document the successes and achievements of the eLearning division precisely. This study’s outcomes will act as a reference for novel research subjects on formalising eLearning. More research that delves into the effectiveness of having an eLearning division at HEIs in support of students’ teaching and learning is needed.

Keywords: eLearning, institutionalization, teaching and learning, transformation

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Authors: Ai Chin Wong, Wan Ahmad Jaafar Wan Yahaya, Balakrishnan Muniandy

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This study aims to explore the impact of Virtual Reality (VR) using visual signaling principles in learning about the science laboratory safety guide; this study involves students with different spatial ability. There are two types of science laboratory safety lessons, which are Virtual Reality with Signaling (VRS) and Virtual Reality Non Signaling (VRNS). This research has adopted a 2 x 2 quasi-experimental factorial design. There are two types of variables involved in this research. The two modes of courseware form the independent variables with the spatial ability as the moderator variable. The dependent variable is the students’ performance. This study sample consisted of 141 students. Descriptive and inferential statistics were conducted to analyze the collected data. The major effects and the interaction effects of the independent variables on the independent variable were explored using the Analyses of Covariance (ANCOVA). Based on the findings of this research, the results exhibited low spatial ability students in VRS outperformed their counterparts in VRNS. However, there was no significant difference in students with high spatial ability using VRS and VRNS. Effective learning in students with different spatial ability can be boosted by implementing the Virtual Reality with Signaling (VRS) in the design as well as the development of Virtual Science Laboratory (ViSLab).

Keywords: spatial ability, science laboratory safety, visual signaling principles, virtual reality

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Authors: Pooja Khanal, Huaming Zhang

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Labeling of issues/bugs, also known as bug classification, plays a vital role in software engineering. Some known labels/classes of bugs are 'User Interface', 'Security', and 'API'. Most of the time, when a reporter reports a bug, they try to assign some predefined label to it. Those issues are reported for a project, and each project is a repository in GitHub/GitLab, which contains multiple issues. There are many software project repositories -ranging from individual projects to commercial projects. The labels assigned for different repositories may be dependent on various factors like human instinct, generalization of labels, label assignment policy followed by the reporter, etc. While the reporter of the issue may instinctively give that issue a label, another person reporting the same issue may label it differently. This way, it is not known mathematically if a label in one repository is similar or different to the label in another repository. Hence, the primary goal of this research is to find the semantic differences between bug labeling of different repositories via machine learning. Independent optimal classifiers for individual repositories are built first using the text features from the reported issues. The optimal classifiers may include a combination of multiple classifiers stacked together. Then, those classifiers are used to cross-test other repositories which leads the result to be deduced mathematically. The produce of this ongoing research includes a formalized open-source GitHub issues database that is used to deduce the similarity of the labels pertaining to the different repositories.

Keywords: bug classification, bug labels, GitHub issues, semantic differences

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Authors: Suphitcha Charoen-Amornkitt, Chokeanand Bussracumpakorn

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The tendency of the Karen backstrap weaving succession has gradually decreased due to the difficulty of weaving techniques and the relocation of the young generation. The Yang Nam Klat Nuea community, Nong Ya Plong District, Phetchaburi, is a Pwo Karen community that is seriously confronted with a lack of cultural heritage. Thus, a group of weavers was formed to revive the knowledge of weaving. However, they have been gradually confronted with culture assimilation to mainstream culture from the desire for marketing acceptance and imperative and forced the extinction of culture due to the disappearance of weaving details and techniques. Although there are practical solutions, i.e., product development, community improvement, knowledge improvement, and knowledge transfer, to inherit the Karen weaving culture, people in the community cannot fulfill their deep intention about the weaving inheritance as most solutions have focused on developing the commercial products and making the income instead of inheriting their knowledge. This research employed qualitative user research with an in-depth user interview to study communal knowledge transfer succession based on the internal involved parties, i.e., four expert weavers, three young weavers, and three 4th generation villagers. The purpose is to explore the correlation and mindset of villagers towards the culture with specific issues, including the psychology of culture, core knowledge and learning methods, cultural inheritance, and cultural engagement. As a result, the existing models of knowledge management mostly focused on tangible strategies, which can notice progress in short terms, such as direct teaching and consistent practicing. At the same time, the motivation and passion of inheritors were abolished while the research found that the young generation who profoundly connected with the textile culture will have a more significant intention to continue the culture. Therefore, this research suggests both internal and external solutions to treat the community. Regarding the internal solutions, family, weaving group, and school have an important role to participate with young villagers by encouraging activities to support the cultivating of Karen’s history, understanding their identities, and adapting the culture as a part of daily life. At the same time, collecting all of the knowledge in the archives, e.g., recorded video, instruction, and books, can crucially prevent the culture from extinction. Regarding the external solutions, this study suggests that working with social media will enhance the intimacy of textile culture, while the community should relieve the roles in marketing competition and start to drive cultural experiences to create a new market position. In conclusion, this research intends to explore the causes and motivation to support the transfer of the culture to the 4th generation villagers and to raise awareness of the diversity of culture in society. With these suggestions and the desire to improve pride and confidence in culture, the community agrees that strengthening the relationships between the young villagers and the weaving culture can bring attention and interest back to the weaving culture.

Keywords: Pwo Karen textile culture, backstrap weaving succession, cultural inheritance, knowledge transfer, knowledge management

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Authors: José María Renteria, Vania Salas

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This study explores the impact of inclusive education on the educational outcomes of students without Special Educational Needs (non-SEN) in Peru, utilizing official Ministry of Education data and implementing cross-sectional regression analyses. Inclusive education is a complex issue that, without appropriate adaptations and comprehensive understanding, can present substantial challenges to the educational community. While prior research from developed nations offers diverse perspectives on the effects of inclusive education on non-SEN students, limited evidence exists regarding its impact in developing countries. Our study addresses this gap by examining inclusive education in Peru and its effects on non-SEN students, thereby contributing to the existing literature. the findings reveal that, on average, the presence of SEN students in regular classrooms does not significantly affect their non-SEN counterparts. However, we uncover heterogeneous effects contingent on the specific type of SEN and students’ academic placement. These results emphasize the importance of targeted resources, specialized teachers, and parental involvement in facilitating successful inclusive education, particularly for specific SEN types and students positioned at the lower end of the academic achievement spectrum. In summary, this study underscores the need for tailored strategies and additional resources to foster the success of inclusive education and calls for further research in this field to expand our understanding and enhance educational policy.

Keywords: inclusive education, special educational needs, learning achievement, Peru, Basic education

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Authors: Marcia Figueira

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Context: Positivist transformations in agriculture were responsible for top-down – often coercive – mechanisms of uniformed modernization that weathered local diversities and agency. New development pathways need to now shift according to comprehensive integrations of knowledge - scientific, indigenous, and local, and to be sustained on political interventions, bottom-up change, and social learning if climate goals are to be met – both in mitigation and adaptation. Objectives The objectives of this research are to understand how social-ecological and socio-technical systems characterisation can be nested to bridge scientific research/knowledge into a local context and knowledge system; and, with it, stem sustainable innovation. Methods To do so, we conducted a scoping review to explore theoretical and empirical works linked to Ostrom’s Social-Ecological Systems framework and Geels’ multi-level perspective of socio-technical systems transformations in the context of agriculture. Results As a result, we were able to identify key variables and connections to 1- understand the rules in use and the community attributes influencing resource management; and 2- how they are and have been shaped and shaping systems innovations. Conclusion Based on these results, we discuss how to leverage action research for mutual learning toward a replicable but highly place-based agriculture transformation frame.

Keywords: agriculture systems innovations, social-ecological systems, socio-technical systems, action research

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Authors: Shan Zhang, Peter Suechting

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Predicting trade patterns is critical to decision-making in public and private domains, especially in the current context of trade disputes among major economies. In the past, U.S. recycling has relied heavily on strong demand for recyclable materials overseas. However, starting in 2017, a series of new recycling policies (bans and higher inspection standards) was enacted by multiple countries that were the primary importers of recyclables from the U.S. prior to that point. As the global trade flow of recycling shifts, some new importers, mostly developing countries in South and Southeast Asia, have been overwhelmed by the sheer quantities of scrap materials they have received. As the leading exporter of recyclable materials, the U.S. now has a pressing need to build its recycling industry domestically. With respect to the global trade in scrap materials used for recycling, the interest in this paper is (1) predicting how the export of recyclable materials from the U.S. might vary over time, and (2) predicting how international trade flows for recyclables might change in the future. Focusing on three major recyclable materials with a history of trade, this study uses data-driven and machine learning (ML) algorithms---supervised (shrinkage and tree methods) and unsupervised (neural network method)---to decipher the international trade pattern of recycling. Forecasting the potential trade values of recyclables in the future could help importing countries, to which those materials will shift next, to prepare related trade policies. Such policies can assist policymakers in minimizing negative environmental externalities and in finding the optimal amount of recyclables needed by each country. Such forecasts can also help exporting countries, like the U.S understand the importance of healthy domestic recycling industry. The preliminary result suggests that gravity models---in addition to particular selection macroeconomic predictor variables--are appropriate predictors of the total export value of recyclables. With the inclusion of variables measuring aspects of the political conditions (trade tariffs and bans), predictions show that recyclable materials are shifting from more policy-restricted countries to less policy-restricted countries in international recycling trade. Those countries also tend to have high manufacturing activities as a percentage of their GDP.

Keywords: environmental economics, machine learning, recycling, international trade

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Authors: Hanan Begali, Shahi Dost, Annett Ziegler, Markus Cornberg, Maria-Esther Vidal, Anke R. M. Kraft

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Chronic hepatitis B virus (HBV) infection can be treated with nucleot(s)ide analog (NA), for example, which inhibits HBV replication. However, they have hardly any influence on the functional cure of HBV, which is defined by hepatitis B surface antigen (HBsAg) loss. NA needs to be taken life-long, which is not available for all patients worldwide. Additionally, NA-treated patients are still at risk of developing cirrhosis, liver failure, or hepatocellular carcinoma (HCC). Although each patient has the same components of the immune system, immune responses vary between patients. Therefore, a deeper understanding of the immune response against HBV in different patients is necessary to understand the parameters leading to HBV cure and to use this knowledge to optimize HBV therapies. This requires seamless integration of an enormous amount of diverse and fine-grained data from viral markers, e.g., hepatitis B core-related antigen (HBcrAg) and hepatitis B surface antigen (HBsAg). The data integration system relies on the assumption that profiling human immune systems requires the analysis of various variables (e.g., demographic data, treatments, pre-existing conditions, immune cell response, or HLA-typing) rather than only one. However, the values of these variables are collected independently. They are presented in a myriad of formats, e.g., excel files, textual descriptions, lab book notes, and images of flow cytometry dot plots. Additionally, patients can be identified differently in these analyses. This heterogeneity complicates the integration of variables, as data management techniques are needed to create a unified view in which individual formats and identifiers are transparent when profiling the human immune systems. The proposed study (HBsRE) aims at integrating heterogeneous data sets of 87 chronically HBV-infected patients, e.g., clinical data, immune cell response, and HLA-typing, with knowledge encoded in biomedical ontologies and open-source databases into a knowledge-driven framework. This new technique enables us to harmonize and standardize heterogeneous datasets in the defined modeling of the data integration system, which will be evaluated in the knowledge graph (KG). KGs are data structures that represent the knowledge and data as factual statements using a graph data model. Finally, the analytic data model will be applied on top of KG in order to develop a deeper understanding of the immune profiles among various patients and to evaluate factors playing a role in a holistic profile of patients with HBsAg level loss. Additionally, our objective is to utilize this unified approach to stratify patients for new effective treatments. This study is developed in the context of the project “Transforming big data into knowledge: for deep immune profiling in vaccination, infectious diseases, and transplantation (ImProVIT)”, which is a multidisciplinary team composed of computer scientists, infection biologists, and immunologists.

Keywords: chronic hepatitis B infection, immune response, knowledge graphs, ontology

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Authors: Sergey Ermolin, Olga Ermolin

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A Deep Convolution Neural Network with Triplet Loss is used to identify duplicate images in real-estate advertisements in the presence of image artifacts such as watermarking, cropping, hue/brightness adjustment, and others. The effects of batch normalization, spatial dropout, and various convergence methodologies on the resulting detection accuracy are discussed. For comparative Return-on-Investment study (per industry request), end-2-end performance is benchmarked on both Nvidia Titan GPUs and Intel’s Xeon CPUs. A new real-estate dataset from San Francisco Bay Area is used for this work. Sufficient duplicate detection accuracy is achieved to supplement other database-grounded methods of duplicate removal. The implemented method is used in a Proof-of-Concept project in the real-estate industry.

Keywords: visual recognition, convolutional neural networks, triplet loss, spatial batch normalization with dropout, duplicate removal, advertisement technologies, performance benchmarking

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Authors: Felicia Titilayo Olanrewaju

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Folktales are a subclass of folklores which are verbally told and passed down from one generation to another, from the elderly ones to their children, usually at moonlight. These tales are heavily laden with moral lessons of what should be done and what not within the society. Though these are oftentimes heavily embellished yet are related to guide, guard, train, and dishing out moral attributes and mores worthwhile for ethical progression of the young minds within our traditional settings. With the rapid advancement of technological know-how, the existence of most of these moral-inclined stories becomes questionable; hence this study appraised the influences of these traditional storytellings have in the upgrading of moral learning of ethical behavioral traits acceptable among the Yoruba people. Oral interviews couples with recording gadgets were used to collate both sample parents' and children’s responses within a particular community in Owo (ute) local government area of Owo Ondo State, Nigeria. Findings reveal that diverse tales told at moonlight periods have an untold impact on the speedy growth of the children intellectually than the modern happenings around them. These telltale stories become powerful aids in learning goodly traits and eschewing bad manners. It is recommended that folk stories be told within the household among the family after hard labour in the evenings as this would help develop human relationships and brings about a strong sense of community bindings.

Keywords: folktales, folklores, impact, advancement, ethical progression

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Authors: David Barney, Francis Pleban, Muna Muday

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The purpose of this study was to explore gender differences of former physical education students related to reflective experiences of competition in physical education learning environment. In the school environment, students are positioned in competitive situations, including in the physical education context. Therefore it is important to prepare future physical educators to address the role of competition in physical education. Participants for this study were 304 college-aged students and young adults (M = 1.53, SD = .500), from a private university and local community located in the western United States. When comparing gender, significant differences (p < .05) were reported for four (questions 5, 7, 12, and 14) of the nine scaling questions. Follow-up quantitative findings reported that males (41%) more than females (27%) witnessed fights in physical education environment during competitive games. Qualitative findings reported fighting were along the lines of verbal confrontation. Female participants tended to experience being excluded from games, when compared to male participants. Both male and female participants (total population; 95%, males; 98%; and females 92%) were in favor of including competition in physical education for students. Findings suggest that physical education teachers and physical education teacher education programs have a responsibility to develop gender neutral learning experiences that help students better appreciate the role competition plays, both in and out of the physical education classroom.

Keywords: competition, physical education, physical education teacher education, gender

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Authors: Arnab Banerjee, Deep Sagar Verma

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Tier 3 cities of India is home to one of the fastest growing socio-economic powers in the world and hence is the focus of a lot of business activity as it is almost a blue ocean giving the first mover a huge strategic advantage. Among the various sectors, the retailing is perhaps one of the most promising sectors. The study caries out 129 successfully structured mall-intercept interviews in the town of Shillong, Meghalaya in an attempt to understand the SBO and MBO shoppers. Demographic variables itself does not show any store format preference although discounts do attract the lower income group more while clear difference is observed among genders when it comes to importance of ambience, and it is more pronounced for SBO patrons. SBO patrons are more focused while MBO patrons are more into leisure shopping. Price is the most important predictor of satisfaction especially for MBO shoppers. The market shows three basic segments i.e experiential, relationship and value shoppers.

Keywords: demographic variables, degree of importance, degree of satisfaction, SBO and MBO

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Authors: Christopher Thornton, Niina Kolehmainen, Kianoush Nazarpour

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Background: Accelerometers are widely used to measure physical activity behavior, including in children. The traditional method for processing acceleration data uses cut points, relying on calibration studies that relate the quantity of acceleration to energy expenditure. As these relationships do not generalise across diverse populations, they must be parametrised for each subpopulation, including different age groups, which is costly and makes studies across diverse populations difficult. A data-driven approach that allows physical activity intensity states to emerge from the data under study without relying on parameters derived from external populations offers a new perspective on this problem and potentially improved results. We evaluated the data-driven approach in a diverse population with a range of rapidly evolving physical and mental capabilities, namely very young children (9-38 months old), where this new approach may be particularly appropriate. Methods: We applied an unsupervised machine learning approach (a hidden semi-Markov model - HSMM) to segment and cluster the accelerometer data recorded from 275 children with a diverse range of physical and cognitive abilities. The HSMM was configured to identify a maximum of six physical activity intensity states and the output of the model was the time spent by each child in each of the states. For comparison, we also processed the accelerometer data using published cut points with available thresholds for the population. This provided us with time estimates for each child’s sedentary (SED), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA). Data on the children’s physical and cognitive abilities were collected using the Paediatric Evaluation of Disability Inventory (PEDI-CAT). Results: The HSMM identified two inactive states (INS, comparable to SED), two lightly active long duration states (LAS, comparable to LPA), and two short-duration high-intensity states (HIS, comparable to MVPA). Overall, the children spent on average 237/392 minutes per day in INS/SED, 211/129 minutes per day in LAS/LPA, and 178/168 minutes in HIS/MVPA. We found that INS overlapped with 53% of SED, LAS overlapped with 37% of LPA and HIS overlapped with 60% of MVPA. We also looked at the correlation between the time spent by a child in either HIS or MVPA and their physical and cognitive abilities. We found that HIS was more strongly correlated with physical mobility (R²HIS =0.5, R²MVPA= 0.28), cognitive ability (R²HIS =0.31, R²MVPA= 0.15), and age (R²HIS =0.15, R²MVPA= 0.09), indicating increased sensitivity to key attributes associated with a child’s mobility. Conclusion: An unsupervised machine learning technique can segment and cluster accelerometer data according to the intensity of movement at a given time. It provides a potentially more sensitive, appropriate, and cost-effective approach to analysing physical activity behavior in diverse populations, compared to the current cut points approach. This, in turn, supports research that is more inclusive across diverse populations.

Keywords: physical activity, machine learning, under 5s, disability, accelerometer

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Authors: Jutharat Sunprasert, Ekapong Hirunsirisawat, Narongrit Waraporn, Somporn Peansukmanee

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Metal Ship and Robotic Car is one of the hands-on activities in the course, the Fundamental of Engineering that can be divided into three parts. The first part, the metal ships, was made by using engineering drawings, physics and mathematics knowledge. The second part is where the students learned how to construct a robotic car and control it using computer programming. In the last part, the students had to combine the workings of these two objects in the final testing. This aim of study was to investigate the effectiveness of hands-on activity by integrating Science, Technology, Engineering and Mathematics (STEM) concepts to develop scientific and engineering skills. The results showed that the majority of students felt this hands-on activity lead to an increased confidence level in the integration of STEM. Moreover, 48% of all students engaged well with the STEM concepts. Students could obtain the knowledge of STEM through hands-on activities with the topics science and mathematics, engineering drawing, engineering workshop and computer programming; most students agree and strongly agree with this learning process. This indicated that the hands-on activity: “Metal Ship and Robotic Car” is a useful tool to integrate each aspect of STEM. Furthermore, hands-on activities positively influence a student’s interest which leads to increased learning achievement and also in developing scientific and engineering skills.

Keywords: hands-on activity, STEM education, computer programming, metal work

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Authors: Tahmina Huq

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This paper presents the findings of an action research study that aimed to investigate the efficacy of a visual dialogue strategy in assisting autistic students with intellectual disabilities in managing their immediate emotions and improving their academic achievements. The research sought to explore the effectiveness of teaching self-regulation techniques as an alternative to traditional approaches involving segregation. The study identified visual dialogue as a valuable tool for promoting self-regulation in this specific student population. Action research was chosen as the methodology due to its suitability for immediate implementation of the findings in the classroom. Autistic students with intellectual disabilities often face challenges in controlling their emotions, which can disrupt their learning and academic progress. Conventional methods of intervention, such as isolation and psychologist-assisted approaches, may result in missed classes and hindered academic development. This study introduces the utilization of visual dialogue between students and teachers as an effective self-regulation strategy, addressing the limitations of traditional approaches. Action research was employed as the methodology for this study, allowing for the direct application of the findings in the classroom. The study observed two 15-year-old autistic students with intellectual disabilities who exhibited difficulties in emotional regulation and displayed aggressive behaviors. The research question focused on the effectiveness of visual dialogue in managing the emotions of these students and its impact on their learning outcomes. Data collection methods included personal observations, log sheets, personal reflections, and visual documentation. The study revealed that the implementation of visual dialogue as a self-regulation strategy enabled the students to regulate their emotions within a short timeframe (10 to 30 minutes). Through visual dialogue, they were able to express their feelings and needs in socially appropriate ways. This finding underscores the significance of visual dialogue as a tool for promoting emotional regulation and facilitating active participation in classroom activities. As a result, the students' learning outcomes and social interactions were positively impacted. The findings of this study hold significant implications for educators working with autistic students with intellectual disabilities. The use of visual dialogue as a self-regulation strategy can enhance emotional regulation skills and improve overall academic progress. The action research approach outlined in this paper provides practical guidance for educators in effectively implementing self-regulation strategies within classroom settings. In conclusion, the study demonstrates that visual dialogue is an effective strategy for enhancing emotional regulation in autistic students with intellectual disabilities. By employing visual communication, students can successfully regulate their emotions and actively engage in classroom activities, leading to improved learning outcomes and social interactions. This paper underscores the importance of implementing self-regulation strategies in educational settings to cater to the unique needs of autistic students.

Keywords: action research, self-regulation, autism, visual communication

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Authors: Yash Bingi, Yiqiao Yin

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Reduction of child mortality is an ongoing struggle and a commonly used factor in determining progress in the medical field. The under-5 mortality number is around 5 million around the world, with many of the deaths being preventable. In light of this issue, Cardiotocograms (CTGs) have emerged as a leading tool to determine fetal health. By using ultrasound pulses and reading the responses, CTGs help healthcare professionals assess the overall health of the fetus to determine the risk of child mortality. However, interpreting the results of the CTGs is time-consuming and inefficient, especially in underdeveloped areas where an expert obstetrician is hard to come by. Using a support vector machine (SVM) and oversampling, this paper proposed a model that classifies fetal health with an accuracy of 99.59%. To further explain the CTG measurements, an algorithm based on Randomized Input Sampling for Explanation ((RISE) of Black-box Models was created, called Feature Alteration for explanation of Black Box Models (FAB), and compared the findings to Shapley Additive Explanations (SHAP) and Local Interpretable Model Agnostic Explanations (LIME). This allows doctors and medical professionals to classify fetal health with high accuracy and determine which features were most influential in the process.

Keywords: machine learning, fetal health, gradient boosting, support vector machine, Shapley values, local interpretable model agnostic explanations

Procedia PDF Downloads 142