Search results for: learning style

Authors: David M Gilstrap

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In an online course with a large enrollment, the potential exists for the instructor to become overburdened with having to respond to students’ emails, which consequently decreases the instructor’s efficiency in teaching the course. Repetition of instructions is an effective way of reducing confusion among students, which in turn increases their efficiencies, as well. World of Turf is the largest online course at Michigan State University, which employs Brightspace as its management system (LMS) software. Recently, the LMS upgraded its capabilities to utilize agents, which are auto generated email notifications to students based on certain criteria. Agents are additional tools that can enhance course design. They can be run on-demand or according to a schedule. Agents can be timed to effectively remind students of approaching deadlines. The content of these generated emails can also include reinforced instructions. With a large online course, even a small percentage of students that either do not read or do not comprehend the course syllabus or do not notice instructions on course pages can result in numerous emails to the instructor, often near the deadlines for assignments. Utilizing agents to decrease the number of emails from students has enabled the instructor to efficiently instruct more than one thousand students per semester without any graduate student teaching assistants.

Keywords: agents, Brightspace, large enrollment, learning management system, repetition of instructions

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Authors: Luyao Zhang, Tianyu Wu, Jiayi Li, Carlos-Gustavo Salas-Flores, Saad Lahrichi

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Recent advances in AI have made algorithmic trading a central role in finance. However, current research and applications are disconnected information islands. We propose a generally applicable pipeline for designing, programming, and evaluating algorithmic trading of stock and crypto tokens. Moreover, we provide comparative case studies for four conventional algorithms, including moving average crossover, volume-weighted average price, sentiment analysis, and statistical arbitrage. Our study offers a systematic way to program and compare different trading strategies. Moreover, we implement our algorithms by object-oriented programming in Python3, which serves as open-source software for future academic research and applications.

Keywords: algorithmic trading, AI for finance, fintech, machine learning, moving average crossover, volume weighted average price, sentiment analysis, statistical arbitrage, pair trading, object-oriented programming, python3

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Authors: Shireen Simon

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This study explores the interactions between primary school parents-teachers in Malaysia. Schools in the country are organized to promote participation between parents and teachers. Exchanges of dialogue are most valued between parents and teachers because teachers are in daily contact with pupils’ and the first line of communication with parents. Teachers are considered by parents as the most important connection to improve children learning and well-being. Without a good communication, interaction or involvement between parent-teacher might tarnish a pupils’ performance in school. This study tries to find out multiple emotions among primary school parents-teachers, either estranged or cordial, when they communicate in a multi-cultured society in Malaysia. Important issues related to parent-teacher interactions are discussed further. Parents’ involvement in an effort to boost better education in school is significantly more effective with parents’ involvement. Lastly, this article proposes some suggestions for parents and teachers to build a positive relationship with effective communication and establish more democratic open door policy.

Keywords: multi-cultured society, parental involvement, parent-teacher relationships, parents’ interaction

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Authors: Oladapo Tolulope Ibitoye

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Neural networks have become prominent and widely engaged in algorithmic-based machine learning networks. They are perfect in solving day-to-day issues to a certain extent. Neural networks are computing systems with several interconnected nodes. One of the numerous areas of application of neural networks is object detection. This is a prominent area due to the coronavirus disease pandemic and the post-pandemic phases. Wearing a face mask in public slows the spread of the virus, according to experts’ submission. This calls for the development of a reliable and effective model for detecting face masks on people's faces during compliance checks. The existing neural network models for facemask detection are characterized by their black-box nature and large dataset requirement. The highlighted challenges have compromised the performance of the existing models. The proposed model utilized Faster R-CNN Model on Inception V3 backbone to reduce system complexity and dataset requirement. The model was trained and validated with very few datasets and evaluation results shows an overall accuracy of 96% regardless of skin tone.

Keywords: convolutional neural network, face detection, face mask, masked faces

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Authors: Merav Hayakac, Orit Avidov-Ungarab

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The current study adopted an interpretive-constructivist approach to examine how senior academics from a large sample of Israeli teacher education colleges serving general or religious populations perceived the integration of digital games into their teacher instruction and what their policy and vision were in this regard in the context of the COVID-19 pandemic. Half the participants expressed a desire to integrate digital games into their teaching and learning but acknowledged that this practice was uncommon. Only a small minority believed they had achieved successful integration, with doubt and skepticism expressed by some religious colleges. Most colleges had policies encouraging technology integration supported by ongoing funding. Although a considerable gap between policy and implementation remained, the COVID-19 pandemic was viewed as having accelerated the integration of digital games into pre-service teacher instruction. The findings suggest that discussions around technology-related vision and policy and their translation into practice should relate to the specific cultural needs and academic preparedness of the population(s) served by the college.

Keywords: COVID-19, digital games, pedagogy, teacher education colleges

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Authors: Lai Junzhe, Wang Lihao, Burra Venkata Durga Kumar

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In recent years, due to today's global technological advances, big data and artificial intelligence technologies have been widely used in various industries and fields, playing an important role in reducing costs and increasing efficiency. Among them, artificial intelligence has derived another branch in its own continuous progress and the continuous development of computer personnel, namely distributed artificial intelligence computing systems. Distributed AI is a method for solving complex learning, decision-making, and planning problems, characterized by the ability to take advantage of large-scale computation and the spatial distribution of resources, and accordingly, it can handle problems with large data sets. Nowadays, distributed AI is widely used in military, medical, and human daily life and brings great convenience and efficient operation to life. In this paper, we will discuss three areas of distributed AI computing systems in vision processing, blockchain, and smart home to introduce the performance of distributed systems and the role of AI in distributed systems.

Keywords: distributed system, artificial intelligence, blockchain, IoT, visual information processing, smart home

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Authors: M. Michael Gromiha, A. Mary Thangakani, Sandeep Kumar, D. Velmurugan

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The main cause of several neurodegenerative diseases such as Alzhemier, Parkinson, and spongiform encephalopathies is formation of amyloid fibrils and plaques in proteins. We have analyzed different sets of proteins and peptides to understand the influence of sequence-based features on protein aggregation process. The comparison of 373 pairs of homologous mesophilic and thermophilic proteins showed that aggregation-prone regions (APRs) are present in both. But, the thermophilic protein monomers show greater ability to ‘stow away’ the APRs in their hydrophobic cores and protect them from solvent exposure. The comparison of amyloid forming and amorphous b-aggregating hexapeptides suggested distinct preferences for specific residues at the six positions as well as all possible combinations of nine residue pairs. The compositions of residues at different positions and residue pairs have been converted into energy potentials and utilized for distinguishing between amyloid forming and amorphous b-aggregating peptides. Our method could correctly identify the amyloid forming peptides at an accuracy of 95-100% in different datasets of peptides.

Keywords: aggregation, amyloids, thermophilic proteins, amino acid residues, machine learning techniques

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Authors: Rachid Essamoud, Abdelkrim Afenzar, Ahmed Belqadi

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During the Early Mesozoic, the northwestern part of the African continent was affected by initial fracturing associated with the early stages of the opening of the Central Atlantic (Atlantic Rift). During this rifting phase, the Moroccan Meseta experienced an extensive tectonic regime. This extension favored the formation of a set of rift-type basins, including the Mohammedia-Benslimane-ElGara-Berrechid basin. Thus, it is essential to know the nature of the deposits in this basin and their evolution over time as well as their relationship with the basaltic effusion of the Central Atlantic Magmatic Province (CAMP). These deposits are subdivided into two large series: The Lower clay-salt series attributed to the Triassic and the Upper clay-salt series attributed to the Liassic. The two series are separated by the Upper Triassic-Lower Liassic basaltic complex. The detailed sedimentological analysis made it possible to characterize four mega-sequences, fifteen types of facies and eight architectural elements and facies associations in the Triassic series. A progressive decrease observed in paleo-slope over time led to the evolution of the paleoenvironment from a proximal system of alluvial fans to a braided fluvial style, then to an anastomosed system. These environments eventually evolved into an alluvial plain associated with a coastal plain where playa lakes, mudflats and lagoons had developed. The pure and massive halitic facies at the top of the series probably indicate an evolution of the depositional environment towards a shallow subtidal environment. The presence of these evaporites indicates a climate that favored their precipitation, in this case, a fairly hot and humid climate. The sedimentological analysis of the supra-basaltic part shows that during the Lower Liassic, the paleopente after basaltic effusion remained weak with distal environments. The faciological analysis revealed the presence of four major sandstone, silty, clayey and evaporitic lithofacies organized in two mega-sequences: the sedimentation of the first rock-salt mega-sequence took place in a brine depression system free, followed by saline mudflats under continental influences. The upper clay mega-sequence displays facies documenting sea level fluctuations from the final transgression of the Tethys or the opening Atlantic. Saliferous sedimentation is therefore favored from the Upper Triassic, but experienced a sudden rupture by the emission of basaltic flows which are interstratified in the azoic salt clays of very shallow seas. This basaltic emission which belongs to the CAMP would come from a fissural volcanism probably carried out through transfer faults located in the NW and SE of the basin. Their emplacement is probably subaquatic to subaerial. From a chronological and paleogeographic point of view, this main volcanism, dated between the Upper Triassic and the Lower Liassic (180-200 MA), is linked to the fragmentation of Pangea and managed by a progressive expansion triggered in the West in close relation with the initial phases of Central Atlantic rifting and seems to coincide with the major mass extinction at the Triassic-Jurassic boundary.

Keywords: Basalt, CAMP, Liassic, sedimentology, Triassic, Morocco

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Authors: Josef Wolfartsberger, Michael Heiml, Georg Schwarz, Sabrina Egger

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Growing individualization and higher numbers of variants in industrial assembly products raise the complexity of manufacturing processes. Technical assistance systems considering both procedural and human factors allow for an increase in product quality and a decrease in required learning times by supporting workers with precise working instructions. Due to varying needs of workers, the presentation of working instructions leads to several challenges. This paper presents an approach for a multi-modal visualization application to support assembly work of complex parts. Our approach is integrated within an interconnected assistance system network and supports the presentation of cloud-streamed textual instructions, images, videos, 3D animations and audio files along with multi-modal user interaction, customizable UI, multi-platform support (e.g. tablet-PC, TV screen, smartphone or Augmented Reality devices), automated text translation and speech synthesis. The worker benefits from more accessible and up-to-date instructions presented in an easy-to-read way.

Keywords: assembly, assistive technologies, augmented reality, manufacturing, visualization

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Authors: HU YINYAO

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Learning and using a second language have become more and more common in daily life. Understanding the complexity of second language proficiency can help students develop their interpersonal relationships with their friends and professors, even enhancing intimacy. This paper examines Wenzhou-Kean University students' second language proficiency and interpersonal relationships. The purpose of the research was to explore the relationship between second language proficiency, extent of intimacy, and interpersonal relationships of the 100 Wenzhou-Kean University students. A mixed methodology was utilized in the research study. Student respondents from Wenzhou-Kean University were chosen randomly by using random sampling. The data analysis used descriptive data in terms of figures and thematical data in the table. The researcher found that Wenzhou-Kean University’s students have shown lower intermediate level of second language proficiency and that their intimacy is middle when using a second language. Especially when talking about some sensitive topics, students tend not to use a second language due to low proficiency. This research project has a strong implication on interpersonal relationships and second language proficiency. The outcome of the study would be greatly helpful to enhance the interpersonal relationship and intimacy between students and students, students and professors who use.

Keywords: Interpersonal relationship, second language proficiency, intimacy, education, univeristy students

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Authors: Felicia Kikelomo Oluwalola

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This study examined lecturers’ perception of the roles of Information and Communication Technology (ICT) in Office Technology and Management (OTM) programme in polytechnics, in South-West, Nigeria. Descriptive survey design was adopted in this study. Purposive sampling technique was used to select all OTM lecturers in the nine (9) Polytechnics in the South-West, Nigeria. A 4-rating scale was adopted questionnaire titled ‘Lecturers’ Perception of the Roles of ICT in OTM Programme in Polytechnics’ with a reliability index of 0.93 was used. Two research questions were answered, and one null hypothesis was tested for the study. Data collected was analysed using descriptive statistics, independent t-test and one way Analysis of Variance (ANOVA) at 0.05 level of significance. The study revealed that lecturers have right perception of the roles of ICT in OTM programme in polytechnics. Also, the study revealed no significant difference between the mean perception of male and female lecturers in office technology and management. Based on the findings, the study recommended among others that recruitment of professionals in the field of ICT is necessary for effective teaching learning to be established and OTM curriculum should be constantly reviewed to enhance some ICT package that is acceptable globally.

Keywords: communication, information, perception, technology

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Authors: Annabelle Nelson

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This literature review documents indigenous storytelling as it functions to help humans face adversity and find emotional strength by aligning with nature. Archetypes in stories can transform the inner world from a Jungian perspective. Joseph Campbell’s hero-heroine cycle depicts the structure of stories to include a call to adventure, tests, helpers, and a return as the transformed person can help him or herself and even help their communities. By showcasing certain character traits, such as bravery or perseverance or humility, stories give maps for humans to face adversity. The main characters or archetypes in stories, as Carl Jung posited, provide a vehicle that can open consciousness if a listener identifies with the character. As documented in the review, this has many benefits. First, it can open consciousness to the collective unconscious for insight and intuitive clarity, as well as healing and release emotional trauma. The resultant spacious quality of consciousness allows the spiritual self to present insights to conscious awareness. Research in applied youth development programs demonstrates the utility of storytelling to prompt healthy choices and transform difficult life experience into success.

Keywords: archetypes, learning, storytelling, transformation

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Authors: Mona Baniahmadi, Saied Haghanifar

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Radio Frequency Identification (RFID) is regarded as a promising technology for the optimization of supply chain processes since it improves manufacturing and retail operations from forecasting demand for planning, managing inventory, and distribution. This study precisely aims at learning to know the RFID technology and at explaining how it can concretely be used for supply chain management and how it can help improving it in the case of Hejrat Company which is located in Iran and works on the distribution of medical drugs and cosmetics. This study uses some statistical analysis to calculate the expected benefits of an integrated RFID system on supply chain obtained through competitive advantages increases with decreasing cost factor. The study investigates how the cost of storage process, labor cost, the cost of missing goods, inventory management optimization, on-time delivery, order cost, lost sales and supply process optimization affect the performance of the integrated RFID supply chain regarding cost factors and provides a competitive advantage.

Keywords: cost, competitive advantage, radio frequency identification, supply chain

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Authors: Kholod J. Alotaibi, Andrew M. Gravell

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A study was conducted in which 212 software developers in higher education institutions in Saudi Arabia were surveyed to gather an indication of their understanding of the concept of usability, their acceptance of its importance, and to see how well its principles are applied. Interviews were then held with 20 of these developers, and a demonstration of Usage-Centred Design was attempted, a highly usability focused software development methodology, at one select institution for its redesign of an e-learning exam system interface during the requirements gathering phase. The study confirms the need to raise awareness of usability and its importance, and for Usage-Centred Design to be applied in its entirety, also need to encourage greater consultation with potential end-users of software and collaborative practices. The demonstration of Usage-Centred Design confirmed its ability to capture usability requirements more completely and precisely than would otherwise be the case, and hence its usefulness for developers concerned with improving software usability. The concluding discussion delves on the challenges for promoting usability and Usage-Centred Design in light of the research results and findings and recommendations are made for the same.

Keywords: usability, usage-centred, applying principles of usage-centred, Saudi Arabia

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Authors: S. Nickolas, Shobha K.

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The treatment of incomplete data is an important step in the data pre-processing. Missing values creates a noisy environment in all applications and it is an unavoidable problem in big data management and analysis. Numerous techniques likes discarding rows with missing values, mean imputation, expectation maximization, neural networks with evolutionary algorithms or optimized techniques and hot deck imputation have been introduced by researchers for handling missing data. Among these, imputation techniques plays a positive role in filling missing values when it is necessary to use all records in the data and not to discard records with missing values. In this paper we propose a novel artificial neural network based clustering algorithm, Adaptive Resonance Theory-2(ART2) for imputation of missing values in mixed attribute data sets. The process of ART2 can recognize learned models fast and be adapted to new objects rapidly. It carries out model-based clustering by using competitive learning and self-steady mechanism in dynamic environment without supervision. The proposed approach not only imputes the missing values but also provides information about handling the outliers.

Keywords: ART2, data imputation, clustering, missing data, neural network, pre-processing

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Authors: Farhad Asadi, Mohammad Javad Mollakazemi

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In this paper, Bayesian online inference in models of data series are constructed by change-points algorithm, which separated the observed time series into independent series and study the change and variation of the regime of the data with related statistical characteristics. variation of statistical characteristics of time series data often represent separated phenomena in the some dynamical system, like a change in state of brain dynamical reflected in EEG signal data measurement or a change in important regime of data in many dynamical system. In this paper, prediction algorithm for studying change point location in some time series data is simulated. It is verified that pattern of proposed distribution of data has important factor on simpler and smother fluctuation of hazard rate parameter and also for better identification of change point locations. Finally, the conditions of how the time series distribution effect on factors in this approach are explained and validated with different time series databases for some dynamical system.

Keywords: time series, fluctuation in statistical characteristics, optimal learning, change-point algorithm

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Authors: Veronique Troch, Wouter Van der Borght, Véronique De Bleeker, Bram Marynissen, Nathan Van der Eecken, Gijs Du Laing

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Among the challenges associated with increased urban food production are health risks from food contamination, due to the higher pollution loads in urban areas, compared to rural sites. Therefore, the risks posed by industrial or traffic pollution of locally grown food, was defined as one of five high-priority issues of urban agriculture requiring further investigation. The impact of air pollution on urban horticulture is the subject of this study. More particular, this study focuses on the atmospheric deposition of trace metals on leaf vegetables cultivated in the city of Ghent, Belgium. Ghent is a particularly interesting study site as it actively promotes urban agriculture. Plants accumulate heavy metals by absorption from contaminated soils and through deposition on parts exposed to polluted air. Accumulation of trace metals in vegetation grown near roads has been shown to be significantly higher than those grown in rural areas due to traffic-related contaminants in the air. Studies of vegetables demonstrated, that the uptake and accumulation of trace metals differed among crop type, species, and among plant parts. Studies on vegetables and fruit trees in Berlin, Germany, revealed significant differences in trace metal concentrations depending on local traffic, crop species, planting style and parameters related to barriers between sampling site and neighboring roads. This study aims to supplement this scarce research on heavy metal accumulation in urban horticulture. Samples from leaf vegetables were collected from different sites, including allotment gardens, in Ghent. Trace metal contents on these leaf vegetables were analyzed by ICP-MS (inductively coupled plasma mass spectrometry). In addition, precipitation on each sampling site was collected by NILU-type bulk collectors and similarly analyzed for trace metals. On one sampling site, different parameters which might influence trace metal content in leaf vegetables were analyzed in detail. These parameters are distance of planting site to the nearest road, barriers between planting site and nearest road, and type of leaf vegetable. For comparison, a rural site, located farther from city traffic and industrial pollution, was included in this study. Preliminary results show that there is a high correlation between trace metal content in the atmospheric deposition and trace metal content in leaf vegetables. Moreover, a significant higher Pb, Cu and Fe concentration was found on spinach collected from Ghent, compared to spinach collected from a rural site. The distance of planting site to the nearest road significantly affected the accumulation of Pb, Cu, Mo and Fe on spinach. Concentrations of those elements on spinach increased with decreasing distance between planting site and the nearest road. Preliminary results did not show a significant effect of barriers between planting site and the nearest road on accumulation of trace metals on leaf vegetables. The overall goal of this study is to complete and refine existing guidelines for urban gardening to exclude potential health risks from food contamination. Accordingly, this information can help city governments and civil society in the professionalization and sustainable development of urban agriculture.

Keywords: atmospheric deposition, leaf vegetables, trace metals, traffic pollution, urban agriculture

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Authors: Sonja Giese, Tess N. Peacock

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South African based Innovation Edge is experimenting with technology to drive positive behavior change, enable data-driven decision making, and scale quality early years services. This paper uses five case studies to illustrate how technology can be used in resource-constrained environments to first, encourage parenting practices that build early language development (using a stage-based mobile messaging pilot, ChildConnect), secondly, to improve the quality of ECD programs (using a mobile application, CareUp), thirdly, how to affordably scale services for the early detection of visual and hearing impairments (using a mobile tool, HearX), fourthly, how to build a transparent and accountable system for the registration and funding of ECD (using a blockchain enabled platform, Amply), and finally enable rapid data collection and feedback to facilitate quality enhancement of programs at scale (the Early Learning Outcomes Measure). ChildConnect and CareUp were both developed using a design based iterative research approach. The usage and uptake of ChildConnect and CareUp was evaluated with qualitative and quantitative methods. Actual child outcomes were not measured in the initial pilots. Although parents who used and engaged on either platform felt more supported and informed, parent engagement and usage remains a challenge. This is contrast to ECD practitioners whose usage and knowledge with CareUp showed both sustained engagement and knowledge improvement. HearX is an easy-to-use tool to identify hearing loss and visual impairment. The tool was tested with 10000 children in an informal settlement. The feasibility of cost-effectively decentralising screening services was demonstrated. Practical and financial barriers remain with respect to parental consent and for successful referrals. Amply uses mobile and blockchain technology to increase impact and accountability of public services. In the pilot project, Amply is being used to replace an existing paper-based system to register children for a government-funded pre-school subsidy in South Africa. Early Learning Outcomes Measure defines what it means for a child to be developmentally ‘on track’ at aged 50-69 months. ELOM administration is enabled via a tablet which allows for easy and accurate data collection, transfer, analysis, and feedback. ELOM is being used extensively to drive quality enhancement of ECD programs across multiple modalities. The nature of ECD services in South Africa is that they are in large part provided by disconnected private individuals or Non-Governmental Organizations (in contrast to basic education which is publicly provided by the government). It is a disparate sector which means that scaling successful interventions is that much harder. All five interventions show the potential of technology to support and enhance a range of ECD services, but pathways to scale are still being tested.

Keywords: assessment, behavior change, communication, data, disabilities, mobile, scale, technology, quality

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Authors: Victoria Crynes

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The question of England’s role in Britain is increasingly relevant due to the ongoing rise in citizens identifying as English. Furthermore, the Brexit Referendum was predominantly supported by constituents identifying as English. Few politicians appear to comprehend how Englishness is politically manifested. Politics and the media have depicted English identity as a negative and extremist problem - an inaccurate representation that ignores the breadth of English identifying citizens. This environment prompts the question, 'How are British Politicians Addressing the Modern English Identity Question?' Parliamentary debates, political blogs, and interviews are synthesized to establish a more coherent understanding of the current political attitudes towards English identity, the perceived nature of English identity, and the political manifestation of English representation and governance. Analyzed parliamentary debates addressed the democratic structure of English governance through topics such as English votes for English laws, devolution, and the union. The blogs examined include party-based, multi-author style blogs, and independently authored blogs by politicians, which provide a dynamic and up-to-date representation of party and politician viewpoints. Lastly, fourteen semi-structured interviews of British politicians provide a nuanced perspective on how politicians conceptualize Englishness. Interviewee selection was based on three criteria: (i) Members of Parliament (MP) known for discussing English identity politics, (ii) MPs of strongly English identifying constituencies, (iii) MPs with minimal English identity affiliation. Analysis of parliamentary debates reveals the discussion of English representation has gained little momentum. Many politicians fail to comprehend who the English are, why they desire greater representation and believe that increased recognition of the English would disrupt the unity of the UK. These debates highlight the disconnect of parliament from the disenfranchised English towns. A failure to recognize the legitimacy of English identity politics generates an inability for solution-focused debates to occur. Political blogs demonstrate cross-party recognition of growing English disenfranchisement. The dissatisfaction with British politics derives from multiple factors, including economic decline, shifting community structures, and the delay of Brexit. The left-behind communities have seen little response from Westminster, which is often contrasted to the devolved and louder voices of the other UK nations. Many blogs recognize the need for a political response to the English and lament the lack of party-level initiatives. In comparison, interviews depict an array of local-level initiatives reconnecting MPs to community members. Local efforts include town trips to Westminster, multi-cultural cooking classes, and English language courses. These efforts begin to rebuild positive, local narratives, promote engagement across community sectors, and acknowledge the English voices. These interviewees called for large-scale, political action. Meanwhile, several interviewees denied the saliency of English identity. For them, the term held only extremist narratives. The multi-level analysis reveals continued uncertainty on Englishness within British politics, contrasted with increased recognition of its saliency by politicians. It is paramount that politicians increase discussions on English identity politics to avoid increased alienation of English citizens and to rebuild trust in the abilities of Westminster.

Keywords: British politics, contemporary identity politics and its impacts, English identity, English nationalism, identity politics

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Authors: Yishu Gong, Liangliang Yang, Jianyu Zhang, Zhengyu Chen, Sihong He, Xusheng Zhang, Wei Zhang

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Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects millions of people worldwide and is characterized by cognitive decline and behavioral changes. People living with Alzheimer’s disease often find it hard to complete routine tasks. However, there are limited objective assessments that aim to quantify the difficulty of certain tasks for AD patients compared to non-AD people. In this study, we propose to use speech emotion recognition (SER), especially the frustration level, as a potential biomarker for quantifying the difficulty patients experience when describing a picture. We build an SER model using data from the IEMOCAP dataset and apply the model to the DementiaBank data to detect the AD/non-AD group difference and perform longitudinal analysis to track the AD disease progression. Our results show that the frustration level detected from the SER model can possibly be used as a cost-effective tool for objective tracking of AD progression in addition to the Mini-Mental State Examination (MMSE) score.

Keywords: Alzheimer’s disease, speech emotion recognition, longitudinal biomarker, machine learning

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Authors: K. C. Wong

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This paper demonstrates a number of examples in the hope to shed some light on the possibility of designing future operating systems in a more adaptation-based manner. A modern operating system, we conceive, should possess the capability of 'learning' in such a way that it can dynamically adjust its services and behavior according to the current status of the environment in which it operates. In other words, a modern operating system should play a more proactive role during the session of providing system services to users. As such, a modern operating system is expected to create a computing environment, in which its users are provided with system services more matching their dynamically changing needs. The examples demonstrated in this paper show that user's resource access patterns 'learned' and determined during a session can be utilized to improve system performance and hence to provide users with a better and more effective computing environment. The paper also discusses how to use the frequency, the continuity, and the duration of resource accesses in a session to quantitatively measure and determine user's resource access patterns for the examples shown in the paper.

Keywords: adaptation-based systems, operating systems, resource access patterns, system performance

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Authors: Alexandra Cheira

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Cultural appropriation has been theorised as a form of colonialism in which members of a dominant culture reduce cultural elements that are deeply meaningful to a minority culture to the category of the “exotic other” since they do not experience the oppression and discriminations faced by members of the minority culture. Yet, in the particular case of literature, writers such as Lionel Shriver and Bernardine Evaristo have argued that authors from a cultural majority have a right to write in the voice of someone from a cultural minority, hence attacking the idea that this is a form of cultural appropriation. By definition, Shriver and Evaristo claim, writers are supposed to write beyond their own culture, gender, class, and/ or race. In this light, this paper discusses the limits of cultural appropriation vis-à-vis the ethics of narrative empathy by addressing the mixed critical reception of Kathryn Stockett’s The Help (2009) and Jeanine Cummins’s American Dirt (2020). In fact, both novels were acclaimed as global eye-openers regarding the struggles of respectively South American migrants and African American maids. At the same time, both novelists have been accused of cultural appropriation by telling a story that is not theirs to tell, given the fact that they are white women telling these stories in what critics have argued is really an American voice telling a story to American readers.These claims will be investigated within the framework of Edward Said’s foundational examination of Orientalism in the field of postcolonial studies as a Western style for authoritatively restructuring the Orient. This means that Orientalist stereotypes regarding Eastern cultures have implicitly validated colonial and imperial pursuits, in the specific context of literary representations of African American and Mexican cultures by white writers. At the same time, the conflicted reception of American Dirt and The Help will be examined within the critical framework of narrative empathy as theorised by Suzanne Keen. Hence, there will be a particular focus on the way a reader’s heated perception that the author’s perspective is purely dishonest can result from a friction between an author’s intention and a reader’s experience of narrative empathy, while a shared sense of empathy between authors and readers can be a rousing momentum to move beyond literary response to social action.Finally, in order to assess that “the key question should not be who can write about whom, but how the writer tells the story”, the recent controversy surrounding Dutch author Marieke Lucas Rijneveld’s decision to resign the translation of American poet Amanda Gorman’s work into Dutch will be duly investigated. In fact, Rijneveld stepped out after journalist and activist Janice Deul criticised Dutch publisher Meulenhoff for choosing a translator who was not also Black, despite the fact that 22-year-old Gorman had selected the 29-year-old Rijneveld herself, as a fellow young writer who had likewise come to fame early on in life. In this light, the critical argument that the controversial reception of The Help reveals as much about US race relations in the early twenty-first century as about the complex literary transactions between individual readers and the novel itself will also be discussed in the extended context of American Dirt and white author Marieke Rijneveld’s withdrawal from the projected translation of Black poet Amanda Gorman.

Keywords: cultural appropriation, cultural stereotypes, narrative empathy, race relations

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Authors: Elias Nemer, Greg Vines

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Time-frequency transformation and spectral representations of audio signals are commonly used in various machine learning applications. Training networks on frequency features such as the Mel-Spectrogram or Cochleogram have been proven more effective and convenient than training on-time samples. In practical realizations, these features are created on a different processor and/or pre-computed and stored on disk, requiring additional efforts and making it difficult to experiment with different features. In this paper, we provide a PyTorch framework for creating various spectral features as well as time-frequency transformation and time-domain filter-banks using the built-in trainable conv1d() layer. This allows computing these features on the fly as part of a larger network and enabling easier experimentation with various combinations and parameters. Our work extends the work in the literature developed for that end: First, by adding more of these features and also by allowing the possibility of either starting from initialized kernels or training them from random values. The code is written as a template of classes and scripts that users may integrate into their own PyTorch classes or simply use as is and add more layers for various applications.

Keywords: neural networks Mel-Spectrogram, chromagram, cochleogram, discrete Fourrier transform, PyTorch conv1d()

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Authors: Frederic Jumelle, Kelvin So, Didan Deng

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In this paper, we are introducing a model of artificial general intelligence (AGI), the functional neural network (FNN), for modeling human decision-making processes. The FNN is composed of multiple artificial mirror neurons (AMN) racing in the network. Each AMN has a similar structure programmed independently by the users and composed of an intention wheel, a motor core, and a sensory core racing at a specific velocity. The mathematics of the node’s formulation and the racing mechanism of multiple nodes in the network will be discussed, and the group decision process with fuzzy logic and the transformation of these conceptual methods into practical methods of simulation and in operations will be developed. Eventually, we will describe some possible future research directions in the fields of finance, education, and medicine, including the opportunity to design an intelligent learning agent with application in AGI. We believe that FNN has a promising potential to transform the way we can compute decision-making and lead to a new generation of AI chips for seamless human-machine interactions (HMI).

Keywords: neural computing, human machine interation, artificial general intelligence, decision processing

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Authors: Joann Douziech

Abstract:

Individuals with intellectual and developmental disabilities (IDD) possess characteristics that present both challenges and gifts. Individuals with IDD require and are worthy of intentional, strategic, and specialized support throughout their lifespan to ensure optimum quality-of-life outcomes. The current global advocacy movement advancing the rights of individuals with IDD emphasizes a high degree of choice over life decisions. For some individuals, this degree of choice results in a variety of negative health and well-being outcomes. Improving the quality of life outcomes requires the combination of a commitment to the rights of the individual with a responsibility to provide support and choice commensurate with individual capacity. A belief that individuals with IDD are capable of learning and they are worthy of being taught provides the foundation for a holistic model of support throughout their lifespan. This model is based on three pillars of engineering the environment, promoting skill development and maintenance, and staff support. In an ever-changing world, supporting quality of life requires attention to moments, phases, and changes in stages throughout the lifespan. Balancing these complexities with strategic, responsive, and dynamic interventions enhances the quality of life of individuals with ID throughout their lifespan.

Keywords: achieving optimum quality of life, comprehensive support, lifespan approach, philosophy and pedagogy

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Authors: Nady Farag Faragalla Hanna

Abstract:

In the car dealership industry in Japan, the sales specialist is a key factor in the success of the company. I hypothesize that when a company understands the characteristics of sales professionals in its industry, it is easier to recruit and train salespeople effectively. Lean human resources management ensures the economic success and performance of companies, especially small and medium-sized companies.The purpose of the article is to determine the characteristics of sales specialists for small and medium-sized car dealerships using the chi-square test and the proximate variable model. Accordingly, the results show that career change experience, learning ability and product knowledge are important, while university education, career building through internal transfer, leadership experience and people development are not important for becoming a sales professional. I also show that the characteristics of sales specialists are perseverance, humility, improvisation and passion for business.

Keywords: electronics engineering, marketing, sales, E-commerce digitalization, interactive systems, sales process ARIMA models, sales demand forecasting, time series, R codetraits of sales professionals, variable precision rough sets theory, sales professional, sales professionals

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Authors: Liu Dan

Abstract:

It was considered either unnecessary or impossible for primary school students to implement online teaching until last year. A large number of E-learning or E-teaching researches have been focused on adult-learners, andragogy and technology, however, primary school education, it is facing many problems that need to be solved. Therefore, this research is aimed at exploring barriers and influential factors on online teaching for K-12 students from teachers’ perspectives and discussing the E-pedagogy that is suitable for primary school students and teachers. Eight hundred and ninety-six teachers from 10 primary schools in Shanghai were invited to participate in a questionnaire survey. Data were analysed by hierarchical regression, and the results stress the significant three barriers by teachers with online teaching: the existing system is deficient in emotional interaction, teachers’ attitude towards the technology is negative and the present teacher training is lack of systematic E-pedagogy guidance. The barriers discovered by this study will help the software designers (E-lab) develop tools that allow for flexible and evolving pedagogical approaches whilst providing an easy entry point for cautious newcomers, so that help the teachers free to engage in E-teaching at pedagogical and disciplinary levels, to enhance their repertoire of teaching practices.

Keywords: online teaching barriers (OTB), e-teaching, primary school, teachers, technology

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Authors: Mehrdad Shahrbanozadeh, Gholam Abbas Barani, Saeed Shojaee

Abstract:

In this study, a finite element (Seep3D model) and an artificial neural network (ANN) model were developed to simulate flow through dam foundation. Seep3D model is capable of simulating three-dimensional flow through a heterogeneous and anisotropic, saturated and unsaturated porous media. Flow through the Shahid Abbaspour dam foundation has been used as a case study. The FEM with 24960 triangular elements and 28707 nodes applied to model flow through foundation of this dam. The FEM being made denser in the neighborhood of the curtain screen. The ANN model developed for Shahid Abbaspour dam is a feedforward four layer network employing the sigmoid function as an activator and the back-propagation algorithm for the network learning. The water level elevations of the upstream and downstream of the dam have been used as input variables and the piezometric heads as the target outputs in the ANN model. The two models are calibrated and verified using the Shahid Abbaspour’s dam piezometric data. Results of the models were compared with those measured by the piezometers which are in good agreement. The model results also revealed that the ANN model performed as good as and in some cases better than the FEM.

Keywords: seepage, dam foundation, finite element method, neural network, seep 3D model

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Authors: Ovidiu Domşa, Nicolae Bold

Abstract:

Using Information and Communication Technologies (ICT) notions in education and three basic processes of education (teaching, learning and assessment) can bring benefits to the pupils and the professional development of teachers. In this matter, we refer to these notions as concepts taken from the informatics area and apply them to the domain of education. These notions refer to genetic algorithms and arborescent structures, used in the specific process of assessment or evaluation. This paper uses these kinds of notions to generate subtrees from a main tree of tests related between them by their degree of difficulty. These subtrees must contain the highest number of connections between the nodes and the lowest number of missing edges (which are subtrees of the main tree) and, in the particular case of the non-existence of a subtree with no missing edges, the subtrees which have the lowest (minimal) number of missing edges between the nodes, where a node is a test and an edge is a direct connection between two tests which differs by one degree of difficulty. The subtrees are represented as sequences. The tests are the same (a number coding a test represents that test in every sequence) and they are reused for each sequence of tests.

Keywords: chromosome, genetic algorithm, subtree, test

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Authors: Tiago do Carmo Nogueira, Cássio Dener Noronha Vinhal, Gélson da Cruz Júnior, Matheus Rudolfo Diedrich Ullmann

Abstract:

Generating automatic image descriptions through natural language is a challenging task. Image captioning is a task that consistently describes an image by combining computer vision and natural language processing techniques. To accomplish this task, cutting-edge models use encoder-decoder structures. Thus, Convolutional Neural Networks (CNN) are used to extract the characteristics of the images, and Recurrent Neural Networks (RNN) generate the descriptive sentences of the images. However, cutting-edge approaches still suffer from problems of generating incorrect captions and accumulating errors in the decoders. To solve this problem, we propose a model based on the encoder-decoder structure, introducing a module that generates the weights according to the importance of the word to form the sentence, using the part-of-speech (PoS). Thus, the results demonstrate that our model surpasses state-of-the-art models.

Keywords: gated recurrent units, caption generation, convolutional neural network, part-of-speech

Procedia PDF Downloads 81