Search results for: computer- supported collaborative learning

Authors: Agnes J. Otjen, Sarah Keller

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A Montana university has used applied consumer research in experiential learning with non-profit clients for over a decade. Through trial and error, a successful protocol has been established from problem statement through formative research to integrated marketing campaign execution. In this paper, we describe the protocol and its applications. Analysis was completed to determine the effectiveness of the campaigns and the results of how pre- and post-consumer research mark societal change because of media.

Keywords: consumer, research, marketing, communications

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Authors: M. Shaheed Hartley

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Science and mathematics are regarded as gateway subjects in South Africa as they are the perceived route to careers in science, engineering, technology and mathematics (STEM). One of the biggest challenges that the country faces is the poor achievement of learners in these two learning areas in the external high school exit examination. To compound the problem many national and international benchmark tests paint a bleak picture of the state of science and mathematics in the country. In an attempt to address this challenge, the education department of the Eastern Cape Province invited the Science Learning Centre of the University of the Western Cape to provide training to their science teachers in the form of a structured course conducted on a part-time basis in 2010 and 2011. The course was directed at improving teachers’ content knowledge, pedagogical strategies and practical and experimental skills. A total of 41 of the original 50 science teachers completed the course and received their certificates in 2012. As part of their continuous professional development, 31 science teachers enrolled for BEd Hons in science education in 2013 and 28 of them completed the course in 2014. These students graduated in 2015. Of the 28 BEd Hons students who completed the course 23 registered in 2015 for Masters in Science Education and were joined by an additional 3 students. This paper provides a reflection by science educators on the training, supervision and mentorship provided to them as students of science education. The growth and development of students through their own reflection and understanding as well as through the eyes of the lecturers and supervisors that took part in the training provide the evaluation of the professional development process over the past few years. This study attempts to identify the merits, challenges and limitations of this project and the lessons to be learnt on such projects. It also documents some of the useful performance indicators with a view to developing a framework for good practice for such programmes.

Keywords: reflection, science education, professional development, rural schools

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Authors: B. Kodedova, E. Filova, M. Kralovic, E. Amler

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Vitiligo is the most common depigmentation disorder of the skin characterized by loss of melanocyte in the epidermis that leads to white lesions. One of the possible treatments is autologous transplantation of melanocytes. Biodegradable electrospun polymeric nanofibers provide good mechanical properties and could serve as suitable scaffold for epithelial cells cultivation and follow up transplantation. Moreover the microarchitecture of nanofibers mimics the structure of extracellular matrix and its porosity allows nutrients and waste exchange. The aim of this work was to develop biocompatible and biodegradable polymeric scaffolds suitable for autologous melanocytes transplantation. Electrospun polyvinyl alcohol (PVA) nanofibers were modified by cold methane plasma to lower their hydrofility and to achieve better adhesion, proliferation and viability of the murine melanocyte (Melan-a). Cells were seeded on the modified scaffolds and their adhesion, metabolic activity, proliferation and melanin synthesis was evaluated and compared to non-modified scaffolds. Results clearly indicate that cold methane plasma modified PVA nanofibers are suitable for melanocyte cultivation and may be future candidate for vitiligo treatment. Furthermore, the nanofibers can be functionalized with various bioactive substances, for enhancement of the melanocyte proliferation, melanogenesis or healing and regenerative processes. The project was supported by the Ministry of Education, Youth and Sports NPU I: LO1309 and by Grant Agency of Charles University (grant No. 1228214).

Keywords: melanocyte, nanofibers, polyvinyl alcohol, plasma modification

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Authors: Jongsung Kim, Daegun Han, Myungjin Lee, Soojun Kim, Hung Soo Kim

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Recently, the frequency and magnitude of natural disasters are gradually increasing due to climate change. Especially in Korea, large-scale damage caused by heavy rainfall frequently occurs due to rapid urbanization. Therefore, this study proposed a Heavy rain Damage Risk Index (HDRI) using PSR (Pressure – State - Response) structure for heavy rain risk assessment. We constructed pressure index, state index, and response index for the risk assessment of each local government in Gyeonggi-do province, and the evaluation indices were determined by principal component analysis. The indices were standardized using the Z-score method then HDRIs were obtained for 31 local governments in the province. The HDRI is categorized into three classes, say, the safest class is 1st class. As the results, the local governments of the 1st class were 15, 2nd class 7, and 3rd class 9. From the study, we were able to identify the risk class due to the heavy rainfall for each local government. It will be useful to develop the heavy rainfall prediction function by risk class, and this was performed in this issue. Also, this risk class could be used for the decision making for efficient disaster management. Acknowledgements: This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2017R1A2B3005695).

Keywords: natural disaster, heavy rain risk assessment, HDRI, PSR

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Authors: Irina A. Gudkova, Yousra Demigha

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Scientific research is moving more and more towards the study of complex systems in several areas of economics, biology physics, and computer science. In this paper, we will work on complex systems in communication networks, Wireless Sensor Networks (WSN) that are considered as stochastic systems composed of interacting entities. The current advancements of the sensing in computing and communication systems is an investment ground for research in several tracks. A detailed presentation was made for the WSN, their use, modeling, different problems that can occur in their application and some solutions. The main goal of this work reintroduces the idea of mean field method since it is a powerful technique to solve this type of models especially systems that evolve according to a Continuous Time Markov Chain (CTMC). Modeling of a CTMC has been focused; we obtained a large system of interacting Continuous Time Markov Chain with population entities. The main idea was to work on one entity and replace the others with an average or effective interaction. In this context to make the solution easier, we consider a wireless sensor network as a multi-body problem and we reduce it to one body problem. The method was applied to a system of WSN modeled as a Markovian queue showing the results of the used technique.

Keywords: Continuous-Time Markov Chain, Hidden Markov Chain, mean field method, Wireless sensor networks

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Authors: Ivana Cestar, Ivica Stančerić, Saša Ahac, Vesna Dragčević, Tamara Džambas

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On special paved areas, such as road intersections, vehicles are usually moving through horizontal curves with smaller radii and occupy considerably greater area compared to open road segments. Planning procedure of these areas is mainly an iterative process that consists of designing project elements, assembling those elements to a design project, and analyzing swept paths for the design vehicle. If applied elements do not fulfill the swept path requirements for the design vehicle, the process must be carried out again. Application of specialized computer software for swept path analysis significantly facilitates planning procedure of special paved areas. There are various software of this kind available on the global market, and each of them has different specifications. In this paper, comparison of two software commonly used in Croatia (Auto TURN and Vehicle Tracking) is presented, their advantages and disadvantages are described, and their applicability on a particular paved area is discussed. In order to reveal which one of the analyszed software is more favorable in terms of swept paths widths, which one includes input parameters that are more relevant for this kind of analysis, and which one is more suitable for the application on a certain special paved area, the analysis shown in this paper was conducted on a number of different intersection types.

Keywords: software comparison, special paved areas, swept path analysis, swept path input parameters

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Authors: L. M. Ombaka, R. S. Oosthuizen, P. G. Ndungu, V. O. Nyamori

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Understanding the role of nitrogen species on the catalytic properties of nitrogen-doped carbon nanotubes (N-CNTs) as catalysts supports is critical as nitrogen species influence the support’s properties. To evaluate the influence of pyrrolic nitrogen on the physicochemical properties and catalytic activity of N-CNTs supported Pd (Pd/N-CNTs); N-CNTs containing varying pyrrolic contents were synthesized. The catalysts were characterised by the use of transmission electron microscope (TEM), scanning electron microscope, X-ray photoelectron spectroscopy (XPS), X-ray diffraction, Fourier transform infrared spectroscopy, and temperature programmed reduction. TEM analysis showed that the Pd nanoparticles were mainly located along the defect sites on N-CNTs. XPS analysis revealed that the abundance of Pd0 decreased while that of Pd2+ increased as the quantity of pyrrolic nitrogen increased. The increase of Pd2+ species was accredited to the formation of stable Pd-N coordination complexes which prevented further reduction of Pd2+ to Pd0 during synthesis. The formed Pd-N complexes increased the stability and dispersion of Pd2+ nanoparticles. The selective hydrogenation of nitrobenzophenone to aminobenzophenone over Pd/N-CNTs was compared to that of Pd on carbon nanotubes (Pd/CNTs). Pd/N-CNTs showed a higher catalytic activity and selectivity compared with Pd/CNTs. Pyrrolic nitrogen functional groups significantly promoted the selectivity towards aminobenzophenone formation.

Keywords: pyrrolic N-CNTs, hydrogenation reactions, chemical vapour deposition technique

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Authors: Onesmus Nyaude

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The aim of the study was to investigate participants’ views on how corruption can be combated to enhance learner academic achievement. The study was undertaken on three select public secondary institutions in Zimbabwe. This study also focuses on exploring the various views of educators; parents and the learners on the role played by corruption in perpetuating the seemingly existing learner academic achievement disparities in various educational institutions. The study further interrogates and examines the nexus between the prevalence of corruption in schools and the subsequent influence on the academic achievement of learners. Corruption is considered a form of social injustice; hence in Zimbabwe, the general consensus is that it is perceived rife to the extent that it is overtaking the traditional factors that contributed to the poor academic achievement of learners. Coupled to this, have been the issue of gross abuse of power and some malpractices emanating from concealment of essential and official transactions in the conduct of business. Through proposing robust anti-corruption mechanisms, teaching and learning resources poured in schools would be put into good use. This would prevent the unlawful diversion and misappropriation of the resources in question which has always been the culture. This study is of paramount significance to curriculum planners, teachers, parents, and learners. The study was informed by the interpretive paradigm; thus qualitative research approaches were used. Both probability and non-probability sampling techniques were adopted in ‘site and participants’ selection. A representative sample of (150) participants was used. The study found that the majority of the participants perceived corruption as a social problem and a human right threat affecting the quality of teaching and learning processes in the education sector. It was established that corruption prevalence within institutions is as a result of the perpetual weakening of ethical values and other variables linked to upholding of ‘Ubuntu’ among general citizenry. It was further established that greediness and weak systems are major causes of rampant corruption within institutions of higher learning and are manifesting through abuse of power, bribery, misappropriation and embezzlement of material and financial resources. Therefore, there is great need to collectively address the problem of corruption in educational institutions and society at large. The study additionally concludes that successful combating of corruption will promote successful moral development of students as well as safeguarding their human rights entitlements. The study recommends the adoption of principles of good corporate governance within educational institutions in order to successfully curb corruption. The study further recommends the intensification of interventionist strategies and strengthening of systems in educational institutions as well as regular audits to overcome the problem associated with rampant corruption cases.

Keywords: academic achievement, combating, corruption, good corporate governance, qualitative study

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Authors: Nihan Akdemir

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This research aims to investigate the role of fashion in the context of the deconstruction of gender stereotypes. Expectation of society and culture related to the biological structure of the individual corresponds to the gender. At this point there are some unseen rules which are given to person even from his/her childhoods according to the sex and gender, are called stereotypes. With basic example, girls should wear pink, and the boys should wear blue. Or boys do not wear skirt and the woman must behave like a woman. There are also many many stereotypes like them. But the clothing style the individual uses to express his or her gender identity may not match the expectations of the community and society. In the context of big role of the clothing, these stereotypes could be deconstructed because clothes are the visible expression of gender identity of the person. And fashion is a big part of this structure because fashion is a pioneer of what people wear in other words fashion tells to people what should they wear this season. Nowadays fashion has also meant about expressing identity independent of whether you were born male or female. Many fashion brands prepare their collections in the concept of ‘gender fluid’ by deconstructions. It means that fashion is opening the roads for being more free about the gender identity. The representations of gender fluidity through fashion help bring a sense of normality to people who are trying to find the self-confidence to express who they want to be. Maybe the voice of the streets carries this point to the catwalks firstly, and then it becomes a trend. All these items have been explained with visual images and supported by the literature investigations. And the results are showed that the numbers of collections about it are increasing and fashion sector takes this issue into consideration. And this new approach reached to the streets.

Keywords: fashion, gender identity, gender stereotypes, trend

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Authors: Ali Karrech, Alberto Puccini, Ben Galvin, Davide Galli

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This paper summarises the laboratory tests, numerical models and statistical approach developed to investigate the behaviour of concrete blocks loaded in shear through metallic anchors. This research is proposed to bridge a gap in the state of the art and practice related to anchors loaded against partially confined concrete surfaces. Eight concrete blocks (420 mm x 500 mm x 1000 mm) with 150 and/or 250 deep anchors were tested. The stainless-steel anchors of diameter 16 mm were bonded with HIT-RE 500 V4 injection epoxy resin and were subjected to shear loading against partially supported edges. In addition, finite element models were constructed to validate the laboratory tests and explore the influence of key parameters such as anchor depth, anchor distance from the edge, and compressive strength on the stability of the block. Upon their validation experimentally, the numerical results were used to populate, develop and interpret a systematic parametric study based on the Design of Experiment approach through the Box-Behnken design and Response Surface Methodology. An empirical model has been derived based on this approach, which predicts the load capacity with the desirable intervals of confidence.

Keywords: finite element modelling, design of experiment, response surface methodology, Box-Behnken design, empirical model, interval of confidence, load capacity

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Authors: Neha Narayanan

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The paper tries to explore the role of language in determining spaces occupied by women in everyday lives. It is inspired from an ongoing action research work which employs ‘immersion’- arriving at a research problematic through community research, as a methodology in a Kondh adivasi village, Kirkalpadu located in Rayagada district of the Indian state of Odisha. In the dominant development discourse, language is associated with either preservation or conservation of endangered language or empowerment through language. Beyond these, is the discourse of language as a structure, with the hegemonic quality to organise lifeworld in a specific manner. This rigid structure leads to an experience of constriction of space for women. In Kirkalpadu, the action research work is with young and unmarried women of the age 15-25. During daytime, these women are either in the agricultural field or in the bari -the backyard of the house whose rooms are linearly arranged one after the other ending with the kitchen followed by an open space called bari (in Odia) which is an intimate and gendered space- where they are not easily visible. They justify the experience of restriction in mobility and fear of moving out of the village alone by the argument that the place and the men are nihi-aaeh (not good). These women, who have dropped out of school early to contribute to the (surplus) labour requirement in the household, want to learn English to be able to read signboards when they are on the road, to be able to fill forms at a bank and use mobile phones to communicate with their romantic partner(s). But the incapacity to have within one’s grasp the province of language and the incapacity to take the mobile phone to the kind of requirements marked by the above mentioned impossible transactions with space restricts them to the bari of the house. The paper concludes by seeking to explore the possibilities of learning and rethinking languages which takes into cognizance the gendered experience of women and the desire of women to cross the borders and occupy spaces restricted to them.

Keywords: action research, gendered experience, language, space

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Authors: Jawaher A. Alsultan, Allen Feldman

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With the rapid switch to remote learning due to the COVID-19 pandemic, science teachers were suddenly required to teach their classes online. This breakneck shift to eLearning raised the question of how teacher educators could support science teachers who wanted to use reform-based methods of instruction while using virtual technologies. In this retrospective self-study, we, two science teacher educators, examined our practice as we worked with science teachers to implement inquiry, discussion, and argumentation [IDA] through eLearning. Ten high school science teachers from a large school district in the southeastern US participated virtually in the COVID-19 Community of Practice [COVID-19 CoP]. The CoP met six times from the end of April through May 2020 via Zoom. Its structure was based on a model of action research called enhanced normal practice [ENP], which includes exchanging stories, trying out ideas, and systematic inquiry. Data sources included teacher educators' meeting notes and reflective conversations, audio recordings of the CoP meetings, teachers' products, and post-interviews of the teachers. Findings included a new understanding of the role of existing relationships, shared goals, and similarities in the participants' situations, which helped build trust in the CoP, and the effects of our paying attention to the science teachers’ needs led to a well-functioning CoP. In addition, we became aware of the gaps in our knowledge of how the teachers already used apps in their practice, which they then shared with all of us about how they could be used for online teaching using IDA. We also identified the need to pay attention to feelings about tensions between the teachers and us around the expectations for final products and the project's primary goals. We found that if we are to establish relationships between us as facilitators and teachers that are honest, fair, and kind, we must express those feelings within the collective, dialogical processes that can lead to learning by all members of the CoP, whether virtual or face-to-face.

Keywords: community of practice, facilitators, self-study, action research

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Authors: Keden Montgomery, Kathie Ardzejewska, Alison Casey, Rosemarie Hogan

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Research was undertaken to explore the question “what is known about the experiences of regional, rural and remote Australian women undertaking a Bachelor of Nursing program delivered online?”. The findings will support future research aimed at improving the retention and completion rates of women studying nursing in regional, rural and remote areas.  There is a critical shortage of nurses working in regional, rural and remote (RRR) Australia. It is well supported that this shortage of nurses is most likely to be addressed by nursing students who are completing their studies in RRR areas. Despite this, students from RRR Australia remain an equity group and experience poorer outcomes than their metropolitan counterparts. Completion rates for RRR students who enrol in tertiary education courses are much less than students from metropolitan areas. In addition to this, RRR students are less likely than students from metropolitan areas to gain a tertiary level qualification at all, and even less likely to gain a Bachelor level degree which is required for Registered Nurses. Supporting students to remain in regional, rural and remote areas while they study reduces the need for students to relocate to metropolitan areas and to continue living and working in RRR areas after graduation. This research holds implications for workforce shortages internationally.

Keywords: nurse education, online education, regional, rural, remote, workforce

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Authors: Sean W. T. Bayly, Daniel Glover, Don Horrell, Simon Horrocks, Barnes Callum, Stuart Gibson, Mac Misuira

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We assess suitability of recent, ∼7B parameter, instruction-tuned Language Models for Generative Named Entity Recognition (GNER). Alongside Retrieval Augmented Generation (RAG), and supported by task-specific prompting, our proposed Multi-Level Information Retrieval method achieves notable improvements over finetuned entity-level and sentence-level methods. We conclude that language models directed toward this task are highly capable when distinguishing between positive classes (precision). However, smaller models seem to struggle to find all entities (recall). Poorly defined classes such as ”Miscellaneous” exhibit substantial declines in performance, likely due to the ambiguity it introduces to the prompt. This is partially resolved through a self-verification method using engineered prompts containing knowledge of the stricter class definitions, particularly in areas where their boundaries are in danger of overlapping, such as the conflation between the location ”Britain” and the nationality ”British”. Finally, we explore correlations between model performance on the GNER task with performance on relevant academic benchmarks.

Keywords: generative named entity recognition, information retrieval, lightweight artificial intelligence, prompt engineering, personal information identification, retrieval augmented generation, self verification

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Authors: Hanan M. Alghamdi, Kholud E. Alsalami, Manal I. Alshaikhi, Nouf M. Alsalami, Sara A. Awad, Ruqaya A. Alrabei

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Tourism in Saudi Arabia is one of the emerging sectors with rapid growth. The Kingdom of Saudi Arabia is characterized by its wonderful and historical areas, which constitute important cultural and tourist landmarks. These landmarks attract the attention of the government of Saudi Arabia; hence the improvement of the tourism sector becomes one of the important axes of Saudi Arabia's vision 2030. There is a need to enhance the tourist experience by facilitating the tourism process for visitors to the Kingdom of Saudi Arabia. This project aims to design an application to serve domestic tourists and visitors from outside the Kingdom of Saudi Arabia. This application will contain an automated tourist generate plan service by sentiment analysis of comments in Google Map using Lexicon for method Rule-based approach. There are thirteen regions in the kingdom of Saudi Arabia. The regions supported in this application will be Makkah and Asir regions. According to the output of the sentiment analysis, the application will recommend restaurants and cafes, activities (parks, museums) and shopping (shopping centers) in the generated plan. After that, the system will show the user a drop-down list of “Mega-events in Saudi Arabia” containing a link to the site of events in the Kingdom of Saudi Arabia. and “important information for you” public decency regulations.

Keywords: tourist automated plan, sentiment analysis, comments in google map, tourism in Saudi Arabia

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Authors: Qiang Wang, Hongyang Yu

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Multi-human 3D pose estimation is a challenging task in computer vision, which aims to recover the 3D joint locations of multiple people from multi-view images. In contrast to traditional methods, which typically only use color (RGB) images as input, our approach utilizes both color and depth (D) information contained in RGB-D images. We also employ a transformer-based model as the backbone of our approach, which is able to capture long-range dependencies and has been shown to perform well on various sequence modeling tasks. Our method is trained and tested on the Carnegie Mellon University (CMU) Panoptic dataset, which contains a diverse set of indoor and outdoor scenes with multiple people in varying poses and clothing. We evaluate the performance of our model on the standard 3D pose estimation metrics of mean per-joint position error (MPJPE). Our results show that the transformer-based approach outperforms traditional methods and achieves competitive results on the CMU Panoptic dataset. We also perform an ablation study to understand the impact of different design choices on the overall performance of the model. In summary, our work demonstrates the effectiveness of using a transformer-based approach with RGB-D images for multi-human 3D pose estimation and has potential applications in real-world scenarios such as human-computer interaction, robotics, and augmented reality.

Keywords: multi-human 3D pose estimation, RGB-D images, transformer, 3D joint locations

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Authors: Mornay Roberts-Lombard

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Consumers’ perceptions of value are crucial to ensuring their future commitment and behavioral intentions. As a result, service providers, such as Islamic banks, must provide their customers with products and services that are regarded as valuable, stimulating, collaborative, and competent. Therefore, the value provided to customers must meet or surpass their expectations, which can drive customers’ commitment (affective and calculative) and eventually favorably impact their future behavioral intentions. Consequently, Islamic banks in South Africa, as a growing African market, need to obtain a better understanding of the variables that impact Islamic banking customers’ value perceptions and how these impact their future behavioral intentions. Furthermore, it is necessary to investigate how customers’ perceived value perceptions impact their affective and calculative commitment and how the latter impact their future behavioral intentions. The purpose of this study is to bridge these gaps in knowledge, as the competitiveness of the Islamic banking industry in South Africa requires a deeper understanding of the aforementioned relationships. The study was exploratory and quantitative in nature, and data was collected from 250 Islamic banking customers using self-administered questionnaires. These banking customers resided in the Gauteng province of South Africa. Exploratory factor analysis, Pearson’s coefficient analysis, and multiple regression analysis were applied to measure the proposed hypotheses developed for the study. This research will aid Islamic banks in the country in potentially strengthening customers’ future commitment (affective and calculative) and positively impact their future behavioral intentions. The findings of the study established that service quality has a significant and positive impact on perceived value. Moreover, it was determined that perceived value has a favorable and considerable impact on affective and calculative commitment, while calculative commitment has a beneficial impact on behavioral intention. The research informs Islamic banks of the importance of service engagement in driving customer perceived value, which stimulates the future affective and calculative commitment of Islamic bank customers in an emerging market context. Finally, the study proposes guidelines for Islamic banks to develop an enhanced understanding of the factors that impact the perceived value-commitment-behavioral intention link in a competitive Islamic banking market in South Africa.

Keywords: perceived value, affective commitment, calculative commitment, behavioural intention

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Authors: André Augusto Ceballos Melo

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Design to facilitate the recognition of congruent prosthetic movements, context-to-motion translations guided by image, verbal prompt, users nonverbal communication such as facial expressions, gestures, paralinguistics, scene context, and object recognition contributes to this process though it can also be applied to other tasks, such as walking, Prosthetic limbs as assistive technology through gestures, sound codes, signs, facial, body expressions, and scene context The context-to-motion model is a machine learning approach that is designed to improve the control and dexterity of prosthetic limbs. It works by using sensory input from the prosthetic limb to learn about the dynamics of the environment and then using this information to generate smooth, stable movements. This can help to improve the performance of the prosthetic limb and make it easier for the user to perform a wide range of tasks. There are several key benefits to using the context-to-motion model for prosthetic limb control. First, it can help to improve the naturalness and smoothness of prosthetic limb movements, which can make them more comfortable and easier to use for the user. Second, it can help to improve the accuracy and precision of prosthetic limb movements, which can be particularly useful for tasks that require fine motor control. Finally, the context-to-motion model can be trained using a variety of different sensory inputs, which makes it adaptable to a wide range of prosthetic limb designs and environments. Stable diffusion is a machine learning method that can be used to improve the control and stability of movements in robotic and prosthetic systems. It works by using sensory feedback to learn about the dynamics of the environment and then using this information to generate smooth, stable movements. One key aspect of stable diffusion is that it is designed to be robust to noise and uncertainty in the sensory feedback. This means that it can continue to produce stable, smooth movements even when the sensory data is noisy or unreliable. To implement stable diffusion in a robotic or prosthetic system, it is typically necessary to first collect a dataset of examples of the desired movements. This dataset can then be used to train a machine learning model to predict the appropriate control inputs for a given set of sensory observations. Once the model has been trained, it can be used to control the robotic or prosthetic system in real-time. The model receives sensory input from the system and uses it to generate control signals that drive the motors or actuators responsible for moving the system. Overall, the use of the context-to-motion model has the potential to significantly improve the dexterity and performance of prosthetic limbs, making them more useful and effective for a wide range of users Hand Gesture Body Language Influence Communication to social interaction, offering a possibility for users to maximize their quality of life, social interaction, and gesture communication.

Keywords: stable diffusion, neural interface, smart prosthetic, augmenting

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Authors: Hemad Zareiforoush, Saeed Minaei, Ahmad Banakar, Mohammad Reza Alizadeh

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The quality inspection of rice (Oryza sativa L.) during its various processing stages is very important. In this research, an artificial intelligence-based model coupled with computer vision techniques was developed as a decision support system for qualitative grading of rice grains. For conducting the experiments, first, 25 samples of rice grains with different levels of percentage of broken kernels (PBK) and degree of milling (DOM) were prepared and their qualitative grade was assessed by experienced experts. Then, the quality parameters of the same samples examined by experts were determined using a machine vision system. A grading model was developed based on fuzzy logic theory in MATLAB software for making a relationship between the qualitative characteristics of the product and its quality. Totally, 25 rules were used for qualitative grading based on AND operator and Mamdani inference system. The fuzzy inference system was consisted of two input linguistic variables namely, DOM and PBK, which were obtained by the machine vision system, and one output variable (quality of the product). The model output was finally defuzzified using Center of Maximum (COM) method. In order to evaluate the developed model, the output of the fuzzy system was compared with experts’ assessments. It was revealed that the developed model can estimate the qualitative grade of the product with an accuracy of 95.74%.

Keywords: machine vision, fuzzy logic, rice, quality

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Authors: Jie Chen, Chris Cheng, Kai Zhang

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Polycrystalline diamond compact (PDC) cutters with a polycrystalline diamond (PCD) table supported by a cemented tungsten carbide substrate have been widely used for earth-drilling tools in the oil and gas industry. Both wear and impact resistances are key figure of merits of PDC cutters, and they are closely related to the microstructure of the PCD table. As oil and gas exploration enters deeper, harder, and more complex formations, plus increasing requirement of accelerated downhole drilling speed and drilling cost reduction, current PDC cutters face unprecedented challenges for maintaining a longer drilling life than ever. Excessive wear on uneven hard formations, spalling, chipping, and premature fracture due to impact loads are common failure modes of PDC cutters in the field. Tailoring microstructure of the PCD table is one of the effective approaches to improve the wear and impact resistances of PDC cutters, along with other factors such as cutter geometry and bit design. In this research, cross-sectional microstructure, fracture surface, wear surface, and elemental composition of PDC cutters were analyzed using scanning electron microscopy (SEM) with both backscattered electron and secondary electron detectors, and energy dispersive X-ray spectroscopy (EDS). The microstructure and elemental composition were further correlated with the wear and impact resistances of corresponding PDC cutters. Wear modes and impact toughening mechanisms of state-of-the-art PDCs were identified. Directions to further improve the wear and impact resistances of PDC cutters were proposed.

Keywords: fracture surface, microstructure, polycrystalline diamond, PDC, wear surface

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Authors: Apostolos Kalatzis, Ashish Teotia, Vishnunarayan Girishan Prabhu, Laura Stanley

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Emotions are functional behaviors influenced by thoughts, stimuli, and other factors that induce neurophysiological changes in the human body. Understanding and classifying emotions are challenging as individuals have varying perceptions of their environments. Therefore, it is crucial that there are publicly available databases and virtual reality (VR) based environments that have been scientifically validated for assessing emotional classification. This study utilized two commercially available VR applications (Guided Meditation VR™ and Richie’s Plank Experience™) to induce acute stress and calm state among participants. Subjective and objective measures were collected to create a validated multimodal dataset and classification scheme for affective state classification. Participants’ subjective measures included the use of the Self-Assessment Manikin, emotional cards and 9 point Visual Analogue Scale for perceived stress, collected using a Virtual Reality Assessment Tool developed by our team. Participants’ objective measures included Electrocardiogram and Respiration data that were collected from 25 participants (15 M, 10 F, Mean = 22.28  4.92). The features extracted from these data included heart rate variability components and respiration rate, both of which were used to train two machine learning models. Subjective responses validated the efficacy of the VR applications in eliciting the two desired affective states; for classifying the affective states, a logistic regression (LR) and a support vector machine (SVM) with a linear kernel algorithm were developed. The LR outperformed the SVM and achieved 93.8%, 96.2%, 93.8% leave one subject out cross-validation accuracy, precision and recall, respectively. The VR assessment tool and data collected in this study are publicly available for other researchers.

Keywords: affective computing, biosignals, machine learning, stress database

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Authors: Lee Artz

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Based on content analyses of major US media, immediately following the George Floyd killing in May 2020, some mayors and local, state, and national officials offered favorable representations of protests against police violence. As the protest movement grew to historic proportions with 26 million joining actions in large cities and small towns, dominant representations of racism by elected officials and leading media shifted—replacing both the voices and demands of protestors with representations by elected officials. Major media quoted Black mayors and Congressional representatives who emphasized concerns about looting and the disruption of public safety. Media coverage privileged elected officials who criticized movement demands for defunding police and deplored isolated instances of property damaged by protestors. Subsequently, public opinion polls saw an increase in concern for law and order tropes and a decrease in support for protests against police violence. Black Lives Matter and local organizations had no coordinated response and no effective means of communication to counter dominant representations voiced by politicians and globally disseminated by major media. Politician and media-instigated public opinion shifts indicate that social movements need their own means of communication and collective decision-making--both of which were largely missing from Black Lives Matter leaders, leading to disaffection and a political split by more than 20 local affiliates. By itself, social media by myriad individuals and groups had limited purchase as a means for social movement communication and organization. Lacking a collaborative, coordinated strategy, organization, and independent media, the loose network of Black Lives Matter groups was unable to offer more accurate, democratic, and favorable representations of protests and their demands for more justice and equality. The fight for equality was diverted by the fight for representation.

Keywords: black lives matter, public opinion, racism, representations, social movements

Procedia PDF Downloads 185

Authors: Silvia C. Ambag, Racidon P. Bernarte, Jacquelyn B. Buccahi, Jessica R. Lacaron, Charlyn L. Mangulabnan

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This study aimed to answer the query, “What is the impact of Students Online Evaluation on PUP Faculty’s Performance?” The problem of the study was resolve through the objective of knowing the perceived impact of students’ online evaluation on PUP faculty’s performance. The objectives were carried through the application of quantitative research design and by conducting survey research method. The researchers utilized primary and secondary data. Primary data was gathered from the self-administered survey and secondary data was collected from the books, articles on both print-out and online materials and also other theses related study. Findings revealed that PUP faculty in general stated that students’ online evaluation made a highly positive impact on their performance based on their ‘Knowledge of Subject’ and ‘Teaching for Independent Learning’, giving a highest mean of 3.62 and 3.60 respectively., followed by the faculty’s performance which gained an overall means of 3.55 and 3.53 are based on their ‘Commitment’ and ‘Management of Learning’. From the findings, the researchers concluded that Students’ online evaluation made a ‘Highly Positive’ impact on PUP faculty’s performance based on all Four (4) areas. Furthermore, the study’s findings reveal that PUP faculty encountered many problems regarding the students’ online evaluation; the impact of the Students’ Online Evaluation is significant when it comes to the employment status of the faculty; and most of the PUP faculty recommends reviewing the PUP Online Survey for Faculty Evaluation for improvement. Hence, the researchers recommend the PUP Administration to revisit and revise the PUP Online Survey for Faculty Evaluation, specifically review the questions and make a set of questions that will be appropriate to the discipline or field of the faculty. Also, the administration should fully orient the students about the importance, purpose and impact of online faculty evaluation. And lastly, the researchers suggest the PUP Faculty to continue their positive performance and continue on being cooperative with the administrations’ purpose of addressing the students’ concerns and for the students, the researchers urged them to take the online faculty evaluation honestly and objectively.

Keywords: on-line Evaluation, faculty, performance, Polytechnic University of the Philippines (PUP)

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Authors: Jenny Paola Forero Pachón, Sonia Cristina Gamboa Sarmiento, Luis Carlos Gómez Flórez

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The Colombian government has defined an e-government strategy to take advantage of Information Technologies (IT) in order to contribute to the building of a more efficient, transparent and participative State that provides better services to citizens and businesses. In this regard, the Justice sector is one of the government sectors where IT has generated more expectation considering that the country has a judicial processes backlog. This situation has led to the search for alternative forms of access to justice that speed up the process while providing a low cost for citizens. To this end, the Colombian government has authorized the use of Alternative Dispute Resolution methods (ADR), a remedy where disputes can be resolved more quickly compared to judicial processes while facilitating greater communication between the parties, without recourse to judicial authority. One of these methods is conciliation, which includes a special modality that takes advantage of IT for the development of itself known as virtual conciliation. With this option the conciliation is supported by information systems, applications or platforms and communications are provided through it. This paper evaluates the level of maturity in how the service of virtual conciliation is under the framework of this strategy. This evaluation is carried out considering Shahkooh's 5-phase model for e-government. As a result, it is evident that in the context of conciliation, maturity does not reach the necessary level in the model so that it can be considered as virtual conciliation; therefore, it is necessary to define strategies to maximize the potential of IT in this context.

Keywords: alternative dispute resolution, e-government, evaluation of maturity, Shahkooh model, virtual conciliation

Procedia PDF Downloads 257

Authors: Prashanth Pillai, Purnaprajna Mangsuli

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Oil exploration and production companies invest considerable time and efforts to extract essential well attributes (like well status, surface, and target coordinates, wellbore depths, event timelines, etc.) from unstructured data sources like technical reports, which are often non-standardized, multimodal, and highly domain-specific by nature. It is also important to consider the context when extracting attribute values from reports that contain information on multiple wells/wellbores. Moreover, semantically similar information may often be depicted in different data syntax representations across multiple pages and document sources. We propose a hierarchical multi-source fact extraction workflow based on a deep learning framework to extract essential well attributes at scale. An information retrieval module based on the transformer architecture was used to rank relevant pages in a document source utilizing the page image embeddings and semantic text embeddings. A question answering framework utilizingLayoutLM transformer was used to extract attribute-value pairs incorporating the text semantics and layout information from top relevant pages in a document. To better handle context while dealing with multi-well reports, we incorporate a dynamic query generation module to resolve ambiguities. The extracted attribute information from various pages and documents are standardized to a common representation using a parser module to facilitate information comparison and aggregation. Finally, we use a probabilistic approach to fuse information extracted from multiple sources into a coherent well record. The applicability of the proposed approach and related performance was studied on several real-life well technical reports.

Keywords: natural language processing, deep learning, transformers, information retrieval

Procedia PDF Downloads 198

Authors: Rajesh Ranjan, Marimuthu Palaniswami, A. A. Hashmi

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With the changing lifestyle and environment around us, the prevalence of the critical and incurable disease has proliferated. One such condition is the neurological disorder which is rampant among the old age population and is increasing at an unstoppable rate. Most of the neurological disorder patients suffer from some movement disorder affecting the movement of their body parts. Tremor is the most common movement disorder which is prevalent in such patients that infect the upper or lower limbs or both extremities. The tremor symptoms are commonly visible in Parkinson’s disease patient, and it can also be a pure tremor (essential tremor). The patients suffering from tremor face enormous trouble in performing the daily activity, and they always need a caretaker for assistance. In the clinics, the assessment of tremor is done through a manual clinical rating task such as Unified Parkinson’s disease rating scale which is time taking and cumbersome. Neurologists have also affirmed a challenge in differentiating a Parkinsonian tremor with the pure tremor which is essential in providing an accurate diagnosis. Therefore, there is a need to develop a monitoring and assistive tool for the tremor patient that keep on checking their health condition by coordinating them with the clinicians and caretakers for early diagnosis and assistance in performing the daily activity. In our research, we focus on developing a system for automatic classification of tremor which can accurately differentiate the pure tremor from the Parkinsonian tremor using a wearable accelerometer-based device, so that adequate diagnosis can be provided to the correct patient. In this research, a study was conducted in the neuro-clinic to assess the upper wrist movement of the patient suffering from Pure (Essential) tremor and Parkinsonian tremor using a wearable accelerometer-based device. Four tasks were designed in accordance with Unified Parkinson’s disease motor rating scale which is used to assess the rest, postural, intentional and action tremor in such patient. Various features such as time-frequency domain, wavelet-based and fast-Fourier transform based cross-correlation were extracted from the tri-axial signal which was used as input feature vector space for the different supervised and unsupervised learning tools for quantification of severity of tremor. A minimum covariance maximum correlation energy comparison index was also developed which was used as the input feature for various classification tools for distinguishing the PT and ET tremor types. An automatic system for efficient classification of tremor was developed using feature extraction methods, and superior performance was achieved using K-nearest neighbors and Support Vector Machine classifiers respectively.

Keywords: machine learning approach for neurological disorder assessment, automatic classification of tremor types, feature extraction method for tremor classification, neurological movement disorder, parkinsonian tremor, essential tremor

Procedia PDF Downloads 161

Authors: Qiong Li

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This study investigated in which condition computer-mediated communication (CMC) could promote pragmatic development. The focal feature included four Chinese sentence final particles (SFPs), a, ya, ba, and ne. They occur frequently in Chinese, and function as mitigators to soften the tone of speech. However, L2 acquisition of SFPs is difficult, suggesting the necessity of additional exposure to or explicit instruction on Chinese SFPs. This study follows this line and aims to explore two research questions: (1) Is CMC combined with data-driven instruction more effective than CMC alone in promoting L2 Chinese learners’ SFP use? (2) How does L2 Chinese learners’ SFP use change over time, as compared to the production of native Chinese speakers? The study involved 19 intermediate-level learners of Chinese enrolled at a private American university. They were randomly assigned to two groups: (1) the control group (N = 10), which was exposed to SFPs through CMC alone, (2) the treatment group (N = 9), which was exposed to SFPs via CMC and data-driven instruction. Learners interacted with native speakers on given topics through text-based CMC over Skype. Both groups went through six 30-minute CMC sessions on a weekly basis, with a one-week interval after the first two CMC sessions and a two-week interval after the second two CMC sessions (nine weeks in total). The treatment group additionally received a data-driven instruction after the first two sessions. Data analysis focused on three indices: token frequency, type frequency, and acceptability of SFP use. Token frequency was operationalized as the raw occurrence of SFPs per clause. Type frequency was the range of SFPs. Acceptability was rated by two native speakers using a rating rubric. The results showed that the treatment group made noticeable progress over time on the three indices. The production of SFPs approximated the native-like level. In contrast, the control group only slightly improved on token frequency. Only certain SFPs (a and ya) reached the native-like use. Potential explanations for the group differences were discussed in two aspects: the property of Chinese SFPs and the role of CMC and data-driven instruction. Though CMC provided the learners with opportunities to notice and observe SFP use, as a feature with low saliency, SFPs were not easily noticed in input. Data-driven instruction in the treatment group directed the learners’ attention to these particles, which facilitated the development.

Keywords: computer-mediated communication, data-driven instruction, pragmatic development, second language Chinese, sentence final particles

Procedia PDF Downloads 421

Authors: Giselle Martinez Negrette

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Language and culture mutually shape and reflect the human experience. In the learning process, this connection creates and sustains the shared world of learners and educators. Dual Language (DL) programs exemplify this relationship by placing language and culture at the center of their educational approach. These programs, originally conceived to advance social justice in education, aim to foster bilingualism, biliteracy, academic development and sociocultural competence, emphasizing the inseparability of linguistic and cultural growth. Furthermore, because DL programs serve children from diverse cultural, ethnic, and socioeconomic backgrounds, they operate as spaces where linguistic skills and sociocultural understandings are actively cultivated, negotiated, and celebrated. Against this background, this paper examines how two DL teachers see language and culture shaping and reflecting the educational experience, and how their understandings of the relationship influence their mediation of sociocultural competence in their classrooms. This qualitative study employs critical discourse analysis to study in detail participants’ narratives seeking to uncover their perspectives on the “politics” surrounding language use and cultural understandings in their school contexts. Our findings show that these educators are not only keenly aware of the pivotal role that language and culture play in multilingual students’ learning journeys, but they have identified the sociolinguistic “games” taking place in their classrooms. We contend these understandings are pivotal for the critical development of sociocultural competence in DL programs. This study provides DL educators with important conceptual and pedagogical insights regarding the intersection between language and culture in their classrooms and seeks to encourage them to analyze their roles as supporters or opponents of transformative rupture opportunities to contest inequities in education

Keywords: sociocultural competence, critical discourse analysis, dual language programs, language, culture

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Authors: Kun Liang Ang, Eng Toon Saw, Wei He, Xuecheng Dong, Seeram Ramakrishna

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Ester solvents are widely used in pharmaceutical, printing and flavor industry due to their good miscibility, low toxicity, and high volatility. Through pervaporation, these ester solvents can be recovered from industrial wastewater. While metal-doped silicalite 1 zeolite membranes are commonly used in organic solvent recovery in the pervaporation process, these ceramic membranes suffer from low membrane permeation flux, mainly due to the high thickness of the metal-doped zeolite membrane. Herein, a simple method of fabricating an ultrathin tin-silicalite 1 membrane supported on alumina tube is reported. This ultrathin membrane is able to achieve high permeation flux and separation factor for an ester in a diluted aqueous solution. Nanosized tin-Silicalite 1 seeds which are smaller than 500nm has been formed through hydrothermal synthesis. The sn-Silicalite 1 seeds were then seeded onto alumina tube through dip coating, and the tin-Silicalite 1 membrane was then formed by hydrothermal synthesis in an autoclave through secondary growth method. Multiple membrane synthesis factors such as seed size, ceramic substrate surface pore size selection, and secondary growth conditions were studied for their effects on zeolite membrane growth. The microstructure, morphology and the membrane thickness of tin-Silicalite 1 zeolite membrane were examined. The membrane separation performance and stability will also be reported.

Keywords: ceramic membrane, pervaporation, solvent recovery, Sn-MFI zeolite

Procedia PDF Downloads 193

Authors: David A. Harness

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Natural evolution of ATP cognitive systems is to meet AI peer review standards. ATP process of axiom selection from Mizar to prove a conjecture would be further refined, as in all human and machine learning, by solving the real world problem of the proposed AI peer review challenge: Determine which conjecture forms the higher confidence level constructive proof between Standard Model of Physics SU(n) lattice gauge group operation vs. present non-standard 4D GEM EOS SU(n) lattice gauge group spatially extended operation in which the photon and electron are the first two trace angular momentum invariants of a gravitoelectromagnetic (GEM) energy momentum density tensor wavetrain integration spin-stress pressure-volume equation of state (EOS), initiated via 32 lines of Mathematica code. Resulting gravitoelectromagnetic spectrum ranges from compressive through rarefactive of the central cosmological constant vacuum energy density in units of pascals. Said self-adjoint group operation exclusively operates on the stress energy momentum tensor of the Einstein field equations, introducing quantization directly on the 4D spacetime level, essentially reformulating the Yang-Mills virtual superpositioned particle compounded lattice gauge groups quantization of the vacuum—into a single hyper-complex multi-valued GEM U(1) × SU(1,3) lattice gauge group Planck spacetime mesh quantization of the vacuum. Thus the Mizar corpus already contains all of the axioms required for relevant DeepMath premise selection and unambiguous formal natural language parsing in context deep learning.

Keywords: automated theorem proving, constructive quantum field theory, information theory, neural networks

Procedia PDF Downloads 185