Search results for: workforce diversity learning

Authors: Yannick Verbelen, Sam De Winne, Niek Blondeel, Ann Peeters, An Braeken, Abdellah Touhafi

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The growing popularity of solid state thermoelectric devices in cooling applications has sparked an increasing diversity of thermoelectric coolers (TECs) on the market, commonly known as “Peltier modules”. They can also be used as generators, converting a temperature difference into electric power, and opportunities are plentiful to make use of these devices as thermoelectric generators (TEGs) to supply energy to low power, autonomous embedded electronic applications. Their adoption as energy harvesters in this new domain of usage is obstructed by the complex thermoelectric models commonly associated with TEGs. Low cost TECs for the consumer market lack the required parameters to use the models because they are not intended for this mode of operation, thereby urging an alternative method to obtain electric power estimations in specific operating conditions. The design of the test setup implemented in this paper is specifically targeted at benchmarking commercial, off-the-shelf TECs for use as energy harvesters in domestic environments: applications with limited temperature differences and space available. The usefulness is demonstrated by testing and comparing single and multi stage TECs with different sizes. The effect of a boost converter stage on the thermoelectric end-to-end efficiency is also discussed.

Keywords: thermoelectric cooler, TEC, complementary balanced energy harvesting, step-up converter, DC/DC converter, energy harvesting, thermal harvesting

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Authors: Odi Fawwaz Alrebei, Rim Ismail

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Sustainable aviation fuel (SAF) has emerged as a critical solution for reducing the aviation sector's carbon footprint. Biological feedstocks, such as lignocellulosic biomass, microalgae, used cooking oil, and municipal solid waste, offer significant potential to replace fossil-based jet fuels with renewable alternatives. This review paper aims to critically examine the current landscape of biological feedstocks for SAF production, focusing on feedstock availability, conversion technologies, and environmental impacts. The paper evaluates the biochemical pathways employed in transforming these feedstocks into SAF, such as hydrothermal liquefaction, Fischer-Tropsch synthesis, and microbial fermentation, highlighting the advancements and challenges in each method. Additionally, the sustainability of biological feedstocks is analyzed with respect to lifecycle emissions, land use, and water consumption, emphasizing the need for region-specific strategies to maximize benefits. Special attention is given to the role of microbial consortia in optimizing feedstock degradation and conversion processes. The review concludes by discussing the scalability and economic viability of biological feedstock-based SAF, with a focus on policy frameworks and technological innovations that can facilitate widespread adoption. This comprehensive review underscores the pivotal role of biological feedstocks in achieving a decarbonized aviation sector and identifies future research directions for improving SAF production efficiency and sustainability.

Keywords: fuel diversity, biological feedstocks, SAF, aviation

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Authors: Ganetsou Evanthia, Koutsikos Emmanouil, Austin Anna Maria

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Information technology has long served the needs of individuals for learning and entertainment, but much less for children in sickness. The aim of the proposed online video game is to provide immersive learning opportunities as well as essential social and emotional scenarios for hospital-bound children with long-term illness. Online self-paced courses on chosen school subjects, including specialised software and multisensory assessments, aim at enhancing children’s academic achievement and sense of inclusion, while doctor minigames familiarise and educate young patients on their medical conditions. Online ethical dilemmas will offer children opportunities to contemplate on the importance of medical procedures and following assigned medication, often challenging for young patients; they will therefore reflect on their condition, reevaluate their perceptions about hospitalisation, and assume greater personal responsibility for their progress. Children’s emotional and psychosocial needs are addressed by engaging in social conventions, such as interactive, daily, collaborative mini games with other hospitalised peers, like virtual competitive sports games, weekly group psychodrama sessions, and online birthday parties or sleepovers. Social bonding is also fostered by having a virtual pet to interact with and take care of, as well as a virtual nurse to discuss and reflect on the mood of the day, engage in constructive dialogue and perspective taking, and offer reminders. Access to the platform will be available throughout the day depending on the patient’s health status. The program is designed to minimise escapism and feelings of exclusion, and can flexibly be adapted to offer post-treatment and a support online system at home.

Keywords: long-term illness, children, hospital, interactive games, cognitive, socioemotional development

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Authors: E. Calil, L. A. Pereira

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The acquisition of orthography is a complex process, involving both lexical and grammatical questions. This learning occurs simultaneously with the domain of multiple textual aspects (e.g.: graphs, punctuation, etc.). However, most of the research on orthographic acquisition focus on this acquisition from an autonomous point of view, separated from the process of textual production. This means that their object of analysis is the production of words selected by the researcher or the requested sentences in an experimental and controlled setting. In addition, the analysis of the Spelling Problems (SP) are identified by the researcher on the sheet of paper. Considering the perspective of Textual Genetics, from an enunciative approach, this study will discuss the SPs recognized by dyads of newly literate students, while they are writing a text collaboratively. Six proposals of textual production were registered, requested by a 2nd year teacher of a Portuguese Primary School between January and March 2015. In our case study we discuss the SPs recognized by the dyad B and L (7 years old). We adopted as a methodological tool the Ramos System audiovisual record. This system allows real-time capture of the text in process and of the face-to-face dialogue between both students and their teacher, and also captures the body movements and facial expressions of the participants during textual production proposals in the classroom. In these ecological conditions of multimodal registration of collaborative writing, we could identify the emergence of SP in two dimensions: i. In the product (finished text): SP identification without recursive graphic marks (without erasures) and the identification of SPs with erasures, indicating the recognition of SP by the student; ii. In the process (text in progress): identification of comments made by students about recognized SPs. Given this, we’ve analyzed the comments on identified SPs during the text in progress. These comments characterize a type of reformulation referred to as Commented Oral Erasure (COE). The COE has two enunciative forms: Simple Comment (SC) such as ' 'X' is written with 'Y' '; or Unfolded Comment (UC), such as ' 'X' is written with 'Y' because...'. The spelling COE may also occur before or during the SP (Early Spelling Recognition - ESR) or after the SP has been entered (Later Spelling Recognition - LSR). There were 631 words entered in the 6 stories written by the B-L dyad, 145 of them containing some type of SP. During the text in progress, the students recognized orally 174 SP, 46 of which were identified in advance (ESRs) and 128 were identified later (LSPs). If we consider that the 88 erasure SPs in the product indicate some form of SP recognition, we can observe that there were twice as many SPs recognized orally. The ESR was characterized by SC when students asked their colleague or teacher how to spell a given word. The LSR presented predominantly UC, verbalizing meta-orthographic arguments, mostly made by L. These results indicate that writing in dyad is an important didactic strategy for the promotion of metalinguistic reflection, favoring the learning of spelling.

Keywords: collaborative writing, erasure, learning, metalinguistic awareness, spelling, text production

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Authors: Raja Al-Khalili

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Traveling abroad for British citizens in the eighteenth century was usually performed for two reasons. The first major form was for administering the expanding realm of the British Empire and its need for officials in governing the natives and facilitating the work of business companies. The other form of travel was for pleasure and involved a manifestation of wealth. This form of travel was a prelude for the modern industry of tourism and usually involved a tour of Europe and the Mediterranean. In both forms of travel the British encountered a myriad of cultures. Travel had fostered a sense of pride and confirmed an ethnocentric view of British superiority, but it also brought a critical self-examination of belonging to a colonial empire that thrives on the weaknesses of other nations. Women writers in particular have sought in the travels a kind of self-exploration of the nature of social patriarchy in a diversity of cultures. Both Lady Elizabeth Craven in A Journey through the Crimea to Constantinople (1789) and Lady Mary Wortley Montagu in Embassy Letters (1716-1718) have observed the culture of the Ottomans and then pursued to reflect on the social role of women in England.

Keywords: travel writing, Elizabeth Craven, Lady Mary Wortley, patriarchy

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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: Martin L. Zurita García, Erick O. Martínez Luque, Jessica Morales Perdomo, Yivy Martínez Duarte, Jorge Ari Noriega

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Colombia’s click beetles (Family Elateridae) are poorly documented in their diversity and taxonomy. There are listed 43 genera for Colombia but without a specific number of their species. No species of the genus Agriotes Eschscholtz (Elaterinae: Agriotini) have been recorded in Colombia. Currently, the subtribe Agriotina in the New World includes three genera: Agriotes, Bohartina Arias and Dalopius Eschscholtz. Historically, the genera Agriotes and Dalopius have had significant taxonomic problems due to their morphological resemblance. These similarities motivated several specialists to generate taxonomic movements such as synonyms and segregations of species in these genera on several occasions. To trying to solve these taxonomic problems, an author proposes some morphological characters present in the larvae, but mainly some genital characters of the females, such as the sclerotized plates of the bursa copulatrix. After examining material newly collected in Colombia, we found a click beetle having a unique combination of diagnostic characters that clearly separate it from any other genera of Agriotina. Hence, we describe and illustrate this click beetle under the name Raphaellus deusminutosi Zurita-García, Morales-Perdomo & Martínez-Luque n. gen. & n. sp., and we also compare this genus with the other New World genera of the subtribes Agriotina.

Keywords: click beetles, new genus, new species, elaterinae, raphaellus deusminutosi

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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: Saeko Toyoshima

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This research will discuss if performance tasks with technology would enhance students' willingness to communicate. The present study investigated how Japanese learners of English would change their attitude to communication in their target language by experiencing a performance task, called 'digital portfolio', in the classroom, applying the concepts of action research. The study adapted questionnaires including four-Likert and open-end questions as mixed-methods research. There were 28 students in the class. Many of Japanese university students with low proficiency (A1 in Common European Framework of References in Language Learning and Teaching) have difficulty in communicating in English due to the low proficiency and the lack of practice in and outside of the classroom at secondary education. They should need to mediate between themselves in the world of L1 and L2 with completing a performance task for communication. This paper will introduce the practice of CALL class where A1 level students have made their 'digital portfolio' related to the topics of TED® (Technology, Entertainment, Design) Talk materials. The students had 'Portfolio Session' twice in one term, once in the middle, and once at the end of the course, where they introduced their portfolio to their classmates and international students in English. The present study asked the students to answer a questionnaire about willingness to communicate twice, once at the end of the first term and once at the end of the second term. The four-Likert questions were statistically analyzed with a t-test, and the answers to open-end questions were analyzed to clarify the difference between them. They showed that the students had a more positive attitude to communication in English and enhanced their willingness to communicate through the experiences of the task. It will be the implication of this paper that making and presenting portfolio as a performance task would lead them to construct themselves in English and enable them to communicate with the others enjoyably and autonomously.

Keywords: action research, digital portfoliio, computer-assisted language learning, ELT with CALL system, mixed methods research, Japanese English learners, willingness to communicate

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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: Mahitab A. A. Mahmoud

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Despite the international community’s galvanized efforts to achieve gender equality, the Arab world still lags behind for their sustained suppression of diversity and freedoms. In Egypt, homosexuals are defamed and hunted not only by authorities but also by politicized religious institutions and media platforms. The resultant state-sponsored homophobia is reflected in media. This paper offers a critical discourse analysis of the representation of LGBTQs in Egypt’s local news articles and movies in an attempt to investigate the underlying ideology. The results reveal a clichéd portrayal of homosexuals as a social parasite that requires cleansing by the government. LGBTQs are depicted as an outcome of debauchery, unhappy marriage, sexual deviancy, deficiency of masculinity/femininity, absence of the mother and/or father figure(s), abject poverty, excessive wealth, psychiatric disorder, debased instincts, childhood sexual molestation, immorality, deviation from religion, chaos, treason, conspiracy against the regime, to name only a few. This image, which is imposed and sustained by the state, exposes homosexuals to a violation of their human rights by both the police and the society, endangers their lives, breeds intolerance, social inequality and violence, prevents healthy coexistence; and deprives them of living a normal life.

Keywords: critical discourse analysis, gender studies, homophobia, homosexuality, ideology, media studies

Procedia PDF Downloads 154

Authors: Atish Bagchi, Siva Chandrasekaran

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Background: According to World Bank national accounts data, the estimated global manufacturing value-added output in 2020 was 13.74 trillion USD. These manufacturing processes are monitored, modelled, and controlled by advanced, real-time, computer-based systems, e.g., Industrial IoT, PLC, SCADA, etc. These systems measure and manipulate a set of physical variables, e.g., temperature, pressure, etc. Despite the use of IoT, SCADA etc., in manufacturing, studies suggest that unplanned downtime leads to economic losses of approximately 864 billion USD each year. Therefore, real-time, accurate detection, classification and prediction of machine behaviour are needed to minimise financial losses. Although vast literature exists on time-series data processing using machine learning, the challenges faced by the industries that lead to unplanned downtimes are: The current algorithms do not efficiently handle the high-volume streaming data from industrial IoTsensors and were tested on static and simulated datasets. While the existing algorithms can detect significant 'point' outliers, most do not handle contextual outliers (e.g., values within normal range but happening at an unexpected time of day) or subtle changes in machine behaviour. Machines are revamped periodically as part of planned maintenance programmes, which change the assumptions on which original AI models were created and trained. Aim: This research study aims to deliver a Graph Neural Network(GNN)based hybrid forecasting model that interfaces with the real-time machine control systemand can detect, predict machine behaviour and behavioural changes (anomalies) in real-time. This research will help manufacturing industries and utilities, e.g., water, electricity etc., reduce unplanned downtimes and consequential financial losses. Method: The data stored within a process control system, e.g., Industrial-IoT, Data Historian, is generally sampled during data acquisition from the sensor (source) and whenpersistingin the Data Historian to optimise storage and query performance. The sampling may inadvertently discard values that might contain subtle aspects of behavioural changes in machines. This research proposed a hybrid forecasting and classification model which combines the expressive and extrapolation capability of GNN enhanced with the estimates of entropy and spectral changes in the sampled data and additional temporal contexts to reconstruct the likely temporal trajectory of machine behavioural changes. The proposed real-time model belongs to the Deep Learning category of machine learning and interfaces with the sensors directly or through 'Process Data Historian', SCADA etc., to perform forecasting and classification tasks. Results: The model was interfaced with a Data Historianholding time-series data from 4flow sensors within a water treatment plantfor45 days. The recorded sampling interval for a sensor varied from 10 sec to 30 min. Approximately 65% of the available data was used for training the model, 20% for validation, and the rest for testing. The model identified the anomalies within the water treatment plant and predicted the plant's performance. These results were compared with the data reported by the plant SCADA-Historian system and the official data reported by the plant authorities. The model's accuracy was much higher (20%) than that reported by the SCADA-Historian system and matched the validated results declared by the plant auditors. Conclusions: The research demonstrates that a hybrid GNN based approach enhanced with entropy calculation and spectral information can effectively detect and predict a machine's behavioural changes. The model can interface with a plant's 'process control system' in real-time to perform forecasting and classification tasks to aid the asset management engineers to operate their machines more efficiently and reduce unplanned downtimes. A series of trialsare planned for this model in the future in other manufacturing industries.

Keywords: GNN, Entropy, anomaly detection, industrial time-series, AI, IoT, Industry 4.0, Machine Learning

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Authors: Peiyuan Guan, Tao Wan, Dewei Chu

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With the flash memory approaching its physical limit, the emerging resistive random-access memory (RRAM) has been considered as one of the most promising candidates for the next-generation non-volatile memory. One selector-one resistor configuration has shown the most promising way to resolve the crosstalk issue without affecting the scalability and high-density integration of the RRAM array. By comparison with other candidates of selectors (such as diodes and nonlinear devices), threshold switching selectors dominated by formation/spontaneous rupture of fragile conductive filaments have been proved to possess low voltages, high selectivity, and ultra-low current leakage. However, the flexibility and transparency of selectors are barely mentioned. Therefore, it is a matter of urgency to develop a selector with highly flexible and transparent properties to assist the application of RRAM for a diversity of memory devices. In this work, threshold switching selectors were designed using a facilely solution-processed fabrication on AgNWs@PDMS composite films, which show high flexibility, transparency and scratch resistance. As-fabricated threshold switching selectors also have revealed relatively high selectivity (~107), low operating voltages (Vth < 1 V) and good switching performance.

Keywords: flexible and transparent, resistive random-access memory, silver nanowires, threshold switching selector

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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: P. K. Singhal, R. Naresh, V. Sharma

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This paper presents the three optimization models, namely New Binary Artificial Bee Colony (NBABC) algorithm, NBABC with Local Search (NBABC-LS), and NBABC with Genetic Crossover (NBABC-GC) for solving the Wind-Thermal Unit Commitment (WTUC) problem. The uncertain nature of the wind power is incorporated using the Weibull probability density function, which is used to calculate the overestimation and underestimation costs associated with the wind power fluctuation. The NBABC algorithm utilizes a mechanism based on the dissimilarity measure between binary strings for generating the binary solutions in WTUC problem. In NBABC algorithm, an intelligent scout bee phase is proposed that replaces the abandoned solution with the global best solution. The local search operator exploits the neighboring region of the current solutions, whereas the integration of genetic crossover with the NBABC algorithm increases the diversity in the search space and thus avoids the problem of local trappings encountered with the NBABC algorithm. These models are then used to decide the units on/off status, whereas the lambda iteration method is used to dispatch the hourly load demand among the committed units. The effectiveness of the proposed models is validated on an IEEE 10-unit thermal system combined with a wind farm over the planning period of 24 hours.

Keywords: artificial bee colony algorithm, economic dispatch, unit commitment, wind power

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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: Alaina Caulkett, Audra Selkowitz, Lauren Harter, Aimee DeFoe

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Educational robotics is an effective tool for teaching and learning STEM curricula. Yet, most traditional professional development programs do not cover engineering, coding, or robotics. This paper will give an overview of how and why the VEX Professional Development Plus Introductory Training courses were developed to provide guided, simple professional development in the area of robotics and computer science instruction. These training courses guide educators through learning the basics of VEX robotics platforms, including VEX 123, GO, IQ, and EXP. Because many educators do not have experience teaching robotics or computer science, this course is meant to simulate one on one training or tutoring through video-based instruction. These videos, led by education professionals, can be watched at any time, which allows educators to watch at their own pace and create their own personalized professional development timeline. This personalization expands beyond the course itself into an online community where educators at different points in the self-paced course can converse with one another or with instructors from the videos and learn from a growing community of practice. By the end of each course, educators are armed with the skills to introduce robotics or computer science in their classroom or educational setting. The design of the course was guided by a variation of the Understanding by Design (UbD) framework and included hands-on activities and challenges to keep educators engaged and excited about robotics. Some of the concepts covered include, but are not limited to, following build instructions, building a robot, updating firmware, coding the robot to drive and turn autonomously, coding a robot using multiple methods, and considerations for teaching robotics and computer science in the classroom, and more. A secondary goal of this research is to discuss how this professional development approach can serve as an example in the larger educational community and explore ways that it could be further researched or used in the future.

Keywords: computer science education, online professional development, professional development, robotics education, video-based instruction

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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: Rabab M. Ramadan, Elaraby A. Elgallad

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With extensive application, the performance of unimodal biometrics systems has to face a diversity of problems such as signal and background noise, distortion, and environment differences. Therefore, multimodal biometric systems are proposed to solve the above stated problems. This paper introduces a bimodal biometric recognition system based on the extracted features of the human palm print and iris. Palm print biometric is fairly a new evolving technology that is used to identify people by their palm features. The iris is a strong competitor together with face and fingerprints for presence in multimodal recognition systems. In this research, we introduced an algorithm to the combination of the palm and iris-extracted features using a texture-based descriptor, the Scale Invariant Feature Transform (SIFT). Since the feature sets are non-homogeneous as features of different biometric modalities are used, these features will be concatenated to form a single feature vector. Particle swarm optimization (PSO) is used as a feature selection technique to reduce the dimensionality of the feature. The proposed algorithm will be applied to the Institute of Technology of Delhi (IITD) database and its performance will be compared with various iris recognition algorithms found in the literature.

Keywords: iris recognition, particle swarm optimization, feature extraction, feature selection, palm print, the Scale Invariant Feature Transform (SIFT)

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Authors: Freitas Vania Moreira, Rodrigues B. B., Araujo M.B., Silva D. R., Sousa A. C., Araujo K. P., Pimentel R. R., Cares J. E., Junqueira N. T. V.

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The Pitahayas are cactus native from America and abundant in arid regions. The cultivation is based mainly on the following species: Hylocereus undatus, H. polyrhizus, H. setaceus and H. megalanthus, being H. undatus the most cultivated in Brazil. The pitahaya cultivation is recent in Brazil and is concentrated in São Paulo. Meloidogyne enterolobii is of unknown origin being distributed in several countries. This nematode has recently been detected in Brazil causing damage in several crops. Similarly, M. incognita is a widely distributed pathogen in Brazil. The objective of this study is to evaluate the following accesses of pitahaya to M. enterolobii: CPAC- Py H. hundatus 01, 02, 03, 04, 05, 06, 07 and 08; CPAC - Py H. costaricense 8A; CPAC - Py Selenicereus setaceus 17 and CPAC - Py S. megalantus 22. And the following accesses to M. incognita: CPAC- Py H. hundatus 05; CPAC - Py H. costaricense 8A; CPAC - Py S. setaceus 17 and CPAC - Py S. megalantus 22. According to the results, CPAC – Py H. hundatus 01, 02, 03, 04 and 07 were considered resistant. While CPAC - Py 05 and 08 was susceptible. CPAC-Py 06 also was considered susceptible, because there was the reaction of susceptibility in one of the trials. Given this wide diversity in H. hundatus and being this species the most cultivated in Brazil it is suggested to work more with this material in Embrapa Cerrados. CPAC - Py H. costaricense 8A behaved as susceptible in one of the trials. CPAC - Py S. setaceus 17 and CPAC – Py S. megalantus 22 were considered highly susceptible. The susceptibility of S. megalantus is widely described in the literature. In relation to M. incognita, there were differences between the results in both experiments, but all behaved as susceptible in at least one of the tests.

Keywords: pitaya, meloidogyne, fruit, resistance

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Authors: Imen Boudali, Marwa Ragmoun

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The Vehicle Routing Problem with Hard Time Windows (VRPHTW) is a basic distribution management problem that models many real-world problems. The objective of the problem is to deliver a set of customers with known demands on minimum-cost vehicle routes while satisfying vehicle capacity and hard time windows for customers. In this paper, we propose to deal with our optimization problem by using a new hybrid stochastic algorithm based on two metaheuristics: Chemical Reaction Optimization (CRO) and Greedy Randomized Adaptive Search Procedure (GRASP). The first method is inspired by the natural process of chemical reactions enabling the transformation of unstable substances with excessive energy to stable ones. During this process, the molecules interact with each other through a series of elementary reactions to reach minimum energy for their existence. This property is embedded in CRO to solve the VRPHTW. In order to enhance the population diversity throughout the search process, we integrated the GRASP in our method. Simulation results on the base of Solomon’s benchmark instances show the very satisfactory performances of the proposed approach.

Keywords: Benchmark Problems, Combinatorial Optimization, Vehicle Routing Problem with Hard Time Windows, Meta-heuristics, Hybridization, GRASP, CRO

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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

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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

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Authors: John G. Vongas, Raghid Al Hajj

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In recent years, there has been a surge in research on empathy across disciplines ranging from management and psychology to philosophy and neuroscience. In organizational behavior, in particular, scholars have become interested in leader empathy given the rise of workplace diversity and the growing perception of leaders as managers of group emotions. It would appear that the current zeitgeist in behavioral and philosophical science is that empathy is a cornerstone of morality and that our world would be better off if only more people – and by extension, more leaders – were empathic. In spite of these claims, however, researchers have used different terminologies to explore empathy, confusing it at times with other related constructs such as emotional intelligence and compassion. Second, extant research that specifies what empathic leaders do and how their behavior affects organizational stakeholders, including themselves, does not devolve from a unifying theoretical framework. These problems plague knowledge development in this important research domain. Therefore, to the authors' best knowledge, this paper provides the first comprehensive review and synthesis of the literature on leader empathy by drawing on disparate yet complementary fields of inquiry. It clarifies empathy from other constructs and presents a theoretical model that elucidates the mechanisms by which a leader’s empathy translates into behaviors that could be either beneficial or harmful to the leaders themselves, as well as to their followers and groups. And third, it specifies the boundary conditions under which a leader’s empathy will become manifest. Finally, it suggests ways in which training could be implemented to improve empathy in practice while also remaining skeptical of its conceptualization as a moral or even effective guide in human affairs.

Keywords: compassion, empathy, leadership, group outcomes

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Authors: Nadiah Mohamad, Wan Samiati Andriana Wan Mohd Daud, M. Suhaimi Tohid, Mohd Fazli Othman, Mohamad Rizal Salleh

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This is a collaborative project of the mural art between The Department of Fine Art from Universiti Teknologi MARA (UiTM) and Petronas Dagangan Berhad (PDB), the most leading retailer and marketer of downstream oil and gas products in Malaysia. Five different states in the Peninsular of Malaysia that has been identified in showcasing the National Identity of Malaysia at each Petronas gas station, this also includes the Air Keroh in Melaka, Pasir Pekan in Kelantan, Pontian in Johor, Simpang Pulai in Perak, and also Wakaf Bharu in Terengganu. This project is to analyze the element of national identity that has been demonstrated at the Petronas's Mural. The ultimate aim of the mural is to let the community and local people to be aware about what Malaysians are consists and proud of and how everyone is able to connect with the idea through visual art. The method that is being explained in this research is by using visual data through research and also self-experience in collecting the visual data in identifying what images is considered as the national identity and idea development and visual analysis is being transferred based upon the visual data collection. In this stage, elements and principles of design will be the key in highlighting what is necessary for a work of art. In conclusion, visual image of the National Identity of Malaysia is able to connect to the audience from local and also to the people from outside the country to learn and understand the beauty and diversity of Malaysia as a unique country with art through the wall of five Petronas gas station.

Keywords: community, fine art, mural art, national identity

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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: 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

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Authors: A. Martins, I. Martins, O. Pereira

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The purpose of this research is to focus on the importance of distributed leadership in universities and Higher Education Institutions (HEIs). The research question is whether there a significant finding in self-reported ratings of leadership styles of those respondents that are studying management. The study aims to further discover whether students are encouraged to become responsible and proactive citizens, to develop their skills set, specifically shared leadership and higher-level skills to inspire creation knowledge, sharing and distribution thereof. Contemporary organizations need active and responsible individuals who are capable to make decisions swiftly and responsibly. Leadership influences innovative results and education play a dynamic role in preparing graduates. Critical reflection of extant literature indicates a need for a culture of leadership and innovation to promote organizational sustainability in the globalised world. This study debates the need for HEIs to prepare the graduate for both organizations and society as a whole. This active collaboration should be the very essence of both universities and the industry in order for these to achieve responsible sustainability. Learning and innovation further depend on leadership efficacy. This study follows the pragmatic paradigm methodology. Primary data collection is currently being gathered via the web-based questionnaire link which was made available on the UKZN notice system. The questionnaire has 35 items with a Likert scale of five response options. The purposeful sample method was used, and the population entails the undergraduate and postgraduate students in the College of Law and Business, University of KwaZulu-Natal, South Africa. Limitations include the design of the study and the reliance on the quantitative data as the only method of primary data collection. This study is of added value for scholars and organizations in the innovation economy.

Keywords: knowledge creation, learning, performance, sustainability

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Authors: Taha SamadSoltani, Peyman Rezaei Hachesu, Marjan GhaziSaeedi, Maryam Zolnoori

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Introduction: Data mining defined as a process to find patterns and relationships along data in the database to build predictive models. Application of data mining extended in vast sectors such as the healthcare services. Medical data mining aims to solve real-world problems in the diagnosis and treatment of diseases. This method applies various techniques and algorithms which have different accuracy and precision. The purpose of this study was to apply knowledge discovery and data mining techniques for the diagnosis of asthma based on patient symptoms and history. Method: Data mining includes several steps and decisions should be made by the user which starts by creation of an understanding of the scope and application of previous knowledge in this area and identifying KD process from the point of view of the stakeholders and finished by acting on discovered knowledge using knowledge conducting, integrating knowledge with other systems and knowledge documenting and reporting.in this study a stepwise methodology followed to achieve a logical outcome. Results: Sensitivity, Specifity and Accuracy of KNN, SVM, Naïve bayes, NN, Classification tree and CN2 algorithms and related similar studies was evaluated and ROC curves were plotted to show the performance of the system. Conclusion: The results show that we can accurately diagnose asthma, approximately ninety percent, based on the demographical and clinical data. The study also showed that the methods based on pattern discovery and data mining have a higher sensitivity compared to expert and knowledge-based systems. On the other hand, medical guidelines and evidence-based medicine should be base of diagnostics methods, therefore recommended to machine learning algorithms used in combination with knowledge-based algorithms.

Keywords: asthma, datamining, classification, machine learning

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Authors: H. Fraga, J. A. Santos

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Vitiviniculture in Portugal is a key socio-economic sector, with a strong connection to local traditions and culture. Despite being a relatively small country, with prevailing Mediterranean environments, Portugal comprises an exceptionally large diversity of growth conditions (Terroirs). The vineyard area in Portugal is over 190 thousand hectares, being the eleventh wine producer and ninth wine exporter worldwide. Owing to the strong impact of weather and climate conditions on grapevine physiological development, grape berry quantity and quality show important inter-annual variability. Grapevines are also susceptible to climate change, as their responses will be unavoidably different under future climates. These impacts may change wine typicity of a given region or even its viticultural suitability. The current study reveals that the projected warming and drying trends for Portugal under the Representative Concentration Pathway (RCP) 4.5 and 8.5, are projected to 1) significantly shift current grapevine growing thermal conditions (e.g., heat and chill accumulation), 2) enhance water stress, 3) anticipate phenological timings and 4) modify yields. Moreover, the present study provides some hints regarding the effectiveness of mulching and irrigation as climate change adaptation measures. Our results show that the effectiveness of these adaptation measures will strongly rest on the strength of the climate change signal at a local scale, thus emphasizing the need for local-to-regional climate change assessments.

Keywords: viticulture, climate change, adaptation measures, Portugal

Procedia PDF Downloads 146