Search results for: adaptive educational digital learning environments

Authors: Neda Jalaliyoon, Nooh Abu Bakar, Hamed Taherdoost

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The present research recommended balanced scorecard (BSC) framework to appraise the performance of the universities. As the original model of balanced scorecard has four perspectives in order to implement BSC in present research the same model with “financial perspective”, “customer”,” internal process” and “learning and growth” is used as well. With applying fuzzy Delphi method (FDM) and questionnaire sixteen measures of performance were identified. Moreover, with using the analytic network process (ANP) the weights of the selected indicators were determined. Results indicated that the most important BSC’s aspect were Internal Process (0.3149), Customer (0.2769), Learning and Growth (0.2049), and Financial (0.2033) respectively. The proposed BSC framework can help universities to enhance their efficiency in competitive environment.

Keywords: balanced scorecard, higher education, fuzzy delphi method, analytic network process (ANP)

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Authors: Puteri Zarina M. K., Haddi J. K., Zolkepli N., Shu M. H. B., Hosshan H., Saad M. A.

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This paper provides an overview of the current state of ESL instruction for children with autism in Malaysia. Equal rights, independence, and active participation are guaranteed by the 2006 Convention on the Rights of Persons with Disabilities. Every child is entitled to receive education in an inclusive atmosphere that embraces diversity and ensures equal opportunity for all. The primary objective of the research was to investigate if English as a Second Language (ESL) teachers employ distinct instructional methods and strategies while teaching children diagnosed with autism. Moreover, the objective was to assess the similarities in the challenges faced by teachers when teaching ESL to children with autism in Malaysia. The study aimed to increase understanding of the challenges faced by ESL teachers in teaching autistic students. The study was structured as a qualitative research endeavour. A total of twelve (12) ESL teachers from selected primary schools in Malaysia were involved in this study. The research findings accurately depict the actual state of teaching ESL to autistic children. They confirm the imperative need for additional support in order to facilitate the successful integration of these children into the educational system.

Keywords: autism spectrum disorder, ESL, inclusion, Malaysia, special educational needs

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Authors: Brianne Nichols, John A. Parkinson

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Positive Psychology has provided a rich understanding of the beneficial effects of positive emotions in relation to optimal functioning, and research has been devoted to promote states of positive feeling and thinking. While this is a worthwhile pursuit, positive emotions are not useful in all contexts - some situations may require the individual to make use of their negative emotions to reach a desired end state. To account for the potential value of a wider range of emotional experiences that are common to the human condition, Positive Psychology needs to expand its horizons and investigate how individuals achieve positive outcomes using varied means. The current research seeks to understand the positive psychology of fear of failure (FF), which is a commonly experienced negative emotion relevant to most life domains. On the one hand, this emotion has been linked with avoidance motivation and self-handicap behaviours, on the other; FF has been shown to act as a drive to move the individual forward. To fully capture the depth of this highly subjective emotional experience and understand the circumstances under which FF may be adaptive, this study adopted a mixed methods design using SenseMaker; a web-based tool that combines the richness of narratives with the objectivity of numerical data. Two hundred participants consisting mostly of undergraduate university students shared a story of a time in the recent past when they feared failure of achieving a valued goal. To avoid researcher bias in the interpretation of narratives, participants self-signified their stories in a tagging system that was based on researchers’ aim to explore the role of past failures, the cognitive, emotional and behavioural profile of individuals high and low in FF, and the relationship between these factors. In addition, the role of perceived personal control and self-esteem were investigated in relation to FF using self-report questionnaires. Results from quantitative analyses indicated that individuals with high levels of FF, compared to low, were strongly influenced by past failures and preoccupied with their thoughts and emotions relating to the fear. This group also reported an unwillingness to accept their internal experiences, which in turn was associated with withdrawal from goal pursuit. Furthermore, self-esteem was found to mediate the relationship between perceived control and FF, suggesting that self-esteem, with or without control beliefs, may have the potential to buffer against high FF. It is hoped that the insights provided by the current study will inspire future research to explore the ways in which ‘acceptance’ may help individuals keep moving towards a goal despite the presence of FF, and whether cultivating a non-contingent self-esteem is the key to resilience in the face of failures.

Keywords: fear of failure, goal-pursuit, negative emotions, optimal functioning, resilience

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Authors: Gelareh Changizi, Mahsa Khajavi, Ladan Shahhosseini

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Corporate-level strategy, or simply ‘parent strategy’, is a topic that has received much attention since the very early days of the strategic planning field. Since the multi level enterprises have different sub enterprises which deal with different business environments, we cannot define the same strategic perspective for all of them. Therefore, the determination of a perspective to manage and deal with affiliates of such enterprises is the main challenge. The parent strategy in mother enterprises' level has been analyzed in this research. A case study has been carried to comprehensively describe the proposed model.

Keywords: parent strategy, multi-business companies, performance evaluation, lifecycle

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Authors: Geir Sigurðsson

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This paper compares ancient Daoist and Confucian approaches to the human body as a locus for learning, edification or personal cultivation. While pointing out some major differences between ancient Chinese and mainstream Western visions of the body, it seeks at the same time inspiration in some seminal Western phenomenological and post-structuralist writings, in particular from Maurice Merleau-Ponty and Pierre Bourdieu. By clarifying the somewhat dissimilar scopes of foci found in Daoist and Confucian philosophies with regard to the role of and attitude to the body, the conclusion is nevertheless that their approaches are comparable, and that both traditions take the physical body to play a vital role in the cultivation of excellence. Lastly, it will be argued that cosmological underpinnings prevent the Confucian li from being rigid and invariable and that it rather emerges as a flexible learning device to train through active embodiment a refined sensibility for one’s cultural environment.

Keywords: body, Confucianism, Daoism, li (ritual), phenomenology

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Authors: Gaye Senbag

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In English language teaching, feedback is considered as one of the main components of writing instruction. Teachers put a lot of time and effort in order to provide learners with written feedback for effective language learning. At Anadolu University School of Foreign Languages (AUSFL) students are given written feedback for their each piece of writing through online platforms such as Edmodo and Turnitin, and traditional methods. However, little is known regarding how learners value and respond to teacher-provided feedback. As the perceptions of the students remarkably affect their learning, this study examines how they perceive the effectiveness of feedback provided by the teacher. Aiming to analyse it, 30 intermediate level (B1+ CEFR level) students were given a questionnaire, which includes Likert scale questions. The results will be discussed in detail.

Keywords: feedback, perceptions, writing, English Language Teaching (ELT)

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Authors: Jiangping Wang

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This presentation describes the design and implementation of PaaS (platform as a service) cloud-based labs that are used in database-related courses to teach students practical skills. Traditionally, all labs are implemented in a desktop-based environment where students have to install heavy client software to access database servers. In order to release students from that burden, we have successfully deployed the cloud-based solution to support database-related courses, from which students and teachers can practice and learn database topics in various database courses via cloud access. With its development environment, execution runtime, web server, database server, and collaboration capability, it offers a shared pool of configurable computing resources and comprehensive environment that supports students’ needs without the complexity of maintaining the infrastructure.

Keywords: PaaS, database environment, e-learning, web server

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Authors: Vareesha Masood, Ammara Gul, Nabeeha Areej, Muhammad Asif Masood, Hamna Imran

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The universal use of PDF files has prompted hackers to use them for malicious intent by hiding malicious codes in their victim’s PDF machines. Machine learning has proven to be the most efficient in identifying benign files and detecting files with PDF malware. This paper has proposed an approach using a decision tree classifier with parameters. A modern, inclusive dataset CIC-Evasive-PDFMal2022, produced by Lockheed Martin’s Cyber Security wing is used. It is one of the most reliable datasets to use in this field. We designed a PDF malware detection system that achieved 99.2%. Comparing the suggested model to other cutting-edge models in the same study field, it has a great performance in detecting PDF malware. Accordingly, we provide the fastest, most reliable, and most efficient PDF Malware detection approach in this paper.

Keywords: PDF, PDF malware, decision tree classifier, random forest classifier

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Authors: Mohd Iskandar Illyas Tan, Zuhra Junaida Mohamad Husny, Farawahida Mohd Yusof

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The potentials of Muslim-friendly hospitality services bring huge opportunities to operators (hoteliers, tourist guides, and travel agents), especially among the Muslim countries. In order to provide guidelines that facilitate the operations among these operators, standards and manuals have been developing by the authorities. Among the challenges is the applicability and complexity of the standard to be adopted in the real world. Mobile digital technology can be implemented to overcome those challenges. A prototype has been developed to help operators and authorities to assess their readiness in complying with MS2610:2015. This study analyzes the of mobile digital technology characteristics that are suitable for the user in conducting sharia’ compliant hospitality audit. A focus group study was conducted in the state of Penang, Malaysia that involves operators (hoteliers, tourist guide, and travel agents) as well as agencies (Islamic Tourism Center, Penang Islamic Affairs Department, Malaysian Standard) that involved directly in the implementation of the certification. Both groups were given the 3 weeks to test and provide feedback on the usability of the mobile applications in order to conduct an audit on their readiness towards the Muslim-friendly hospitality services standard developed by the Malaysian Standard. The feedbacks were analyzed and the overall results show that three criteria (ease of use, completeness and fast to complete) show the highest responses among both groups for the mobile application. This study provides the evidence that the mobile application development has huge potentials to be implemented by the Muslim-friendly hospitality services operator and agencies.

Keywords: hospitality, innovation, audit, compliance, mobile application

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Authors: Bencharif Meriem, Sersar Ibrahim, Djaafri Zineb

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Introduction and purpose of the study: Education plays a fundamental role in the lives of young people, but what about their physical well-being as they spend long hours sitting at school? School inactivity is a problem that deserves particular attention because it can have significant repercussions on the health and development of students. The aim of this study was to describe and evaluate the physical activity of students in different practices in class, at recess and in the canteen. Material and methods: A physical activity diary and an anthropometric measurement sheet (weight, height) were provided to 123 school-aged adolescents. The measurements were carried out according to international recommendations. The statistical tests were carried out with the R software. 3.2.4. The significance threshold retained was 0.05. Results and Statistical Analysis: One hundred and twenty-three students agreed to participate in the study. Their average age was 16.5±1.60 years. Overweight was present in 8.13% and obesity in 4.06%. For the practice of physical activity, during physical education and sports classes, all students played sports with an average of 1.94±1.00 hours/week, of which 74.00% sweated or were out of breath during these hours of physical activity. It was also noted that boys practiced sports more than girls (p<0.0001). Each day, on average, students spent 39.78±37.85 min walking or running during recess. On the other hand, they spent, on average 4.25±2.65 hours sitting per day in class, at recess, in the canteen, etc., without counting the time spent in front of a screen. The increasing use of screens has become a major concern for parents and educators. On average, students spent approximately 42.90±38.41 min per day using screens in class, at recess, in the canteen and at home. (computer, tablet, telephone, video games, etc.) and therefore to a prolonged sedentary lifestyle. On average, students sat for more than 1.5 hours without moving for at least 2 minutes in a row approximately 1.72±0.71 times per day. Conclusion: These students spent many hours sitting at school. This prolonged inactivity can have negative consequences on their health, including problems with posture and cardiovascular health. It is crucial that schools, educators and parents collaborate to promote more active learning environments where students can move more and thus contribute to their overall well-being. It's time to rethink how we approach education and student health to give them a healthier, more active future.

Keywords: physical acivity, sedentarity, adolescents, school

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Authors: Omar Elharrouss, Youssef Hmamouche, Assia Kamal Idrissi, Btissam El Khamlichi, Amal El Fallah-Seghrouchni

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Edge detection is represented as one of the most challenging tasks in computer vision, due to the complexity of detecting the edges or boundaries in real-world images that contains objects of different types and scales like trees, building as well as various backgrounds. Edge detection is represented also as a key task for many computer vision applications. Using a set of backbones as well as attention modules, deep-learning-based methods improved the detection of edges compared with the traditional methods like Sobel and Canny. However, images of complex scenes still represent a challenge for these methods. Also, the detected edges using the existing approaches suffer from non-refined results while the image output contains many erroneous edges. To overcome this, n this paper, by using the mechanism of residual learning, a refined edge detection network is proposed (RED-Net). By maintaining the high resolution of edges during the training process, and conserving the resolution of the edge image during the network stage, we make the pooling outputs at each stage connected with the output of the previous layer. Also, after each layer, we use an affined batch normalization layer as an erosion operation for the homogeneous region in the image. The proposed methods are evaluated using the most challenging datasets including BSDS500, NYUD, and Multicue. The obtained results outperform the designed edge detection networks in terms of performance metrics and quality of output images.

Keywords: edge detection, convolutional neural networks, deep learning, scale-representation, backbone

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Authors: Armine Vahanyan

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Humanity has been still coping with the new COVID-19 pandemic. Healthcare providers, economists, psychologists, and other specialists speak about the impact of the virus on different spheres of our life. In the list of similar discussions, the impact of pandemics on global education is of utmost importance. Ideally, providing quality education services should be crucial, and the ways education programs are being adapted will determine the success or failure of the service providers. The paper aims to summarize the research touching upon the current situation of higher education in Armenia. The research includes data from official reports, surveys among education leads, faculty, and students, as well as personal observations and consideration. Through descriptive analysis, the findings of the research are being presented from various aspects. Interim results of the research unveiled two major issues in the sector of higher education in Armenia. On the one hand, the entire compulsory digitization of instruction, assessment, and grading has evoked serious gaps related to the lack of technical competencies. There is an urgent need for professional development programs that will address most of the concerns due to the shift to the online instruction mode. On the other hand, online teaching and learning require revision and adaptation of the existing curricula. Given that the content of certain programs may not be compromised, the teaching methods, the assignments, and evaluation require profound transformation, which will still be in line with course learning outcomes and student learning outcomes. The given paper focuses on the ways the mentioned issues are being addressed in Armenia. The extent of commitment for changes and adaptability to the new situation varies from the government-funded and private universities. In particular, the paper compares and contrasts activities and measures taken at the Armenian State Pedagogical University and the American University of Armenia. Thus, the Pedagogical University focused on the use of Google Classroom as the only means for teaching and learning as well as adopted the compulsory synchronous instruction mode. The American University, on the contrary, kept practicing the academic freedom, enabling both synchronous and asynchronous instruction modes, ensuring alignment of the course learning outcomes and student learning outcomes. The State University utilized the assignments and assessment, which would work for the on-campus instruction mode, while the American university employed a variety of assignments applicable for online teaching mode. The latter has suggested the utilization of multiple apps, internet sources, and online library access for a better online instant. Discussions with faculty through online forums and/or professional development workshops also facilitate restructuring and adaptation of the courses. Finally, the paper will synthesize the results of the undertaken research and will outline the e-learning perspectives and opportunities boosted by the known devastating healthcare issue.

Keywords: assessment, compulsory digitization of education services, online teaching, instruction mode, program restructuring

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Authors: Mariangela Viviani, Daniele Germano, Simone Colace, Agostino Forestiero, Giuseppe Papuzzo, Sara Laurita

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Nowadays, people spend most of their time in closed environments, in offices, or at home. Therefore, secure and highly livable environmental conditions are needed to reduce the probability of aerial viruses spreading. Also, to lower the human impact on the planet, it is important to reduce energy consumption. Heating, Ventilation, and Air Conditioning (HVAC) systems account for the major part of energy consumption in buildings [1]. Devising systems to control and regulate the airflow is, therefore, essential for energy efficiency. Moreover, an optimal setting for thermal comfort and air quality is essential for people’s well-being, at home or in offices, and increases productivity. Thanks to the features of Artificial Intelligence (AI) tools and techniques, it is possible to design innovative systems with: (i) Improved monitoring and prediction accuracy; (ii) Enhanced decision-making and mitigation strategies; (iii) Real-time air quality information; (iv) Increased efficiency in data analysis and processing; (v) Advanced early warning systems for air pollution events; (vi) Automated and cost-effective m onitoring network; and (vii) A better understanding of air quality patterns and trends. We propose AIR SAFE, an IoT-based infrastructure designed to optimize air quality and thermal comfort in indoor environments leveraging AI tools. AIR SAFE employs a network of smart sensors collecting indoor and outdoor data to be analyzed in order to take any corrective measures to ensure the occupants’ wellness. The data are analyzed through AI algorithms able to predict the future levels of temperature, relative humidity, and CO₂ concentration [2]. Based on these predictions, AIR SAFE takes actions, such as opening/closing the window or the air conditioner, to guarantee a high level of thermal comfort and air quality in the environment. In this contribution, we present the results from the AI algorithm we have implemented on the first s et o f d ata c ollected i n a real environment. The results were compared with other models from the literature to validate our approach.

Keywords: air quality, internet of things, artificial intelligence, smart home

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Authors: Kevin William Taylor

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This work draws upon research in the fields of games development and mental health treatments to assess the influence that interactive entertainment has on the populous, and the potential of technology to affect areas of psychiatric assessment and treatment. It will use studies to establish the evolving direction of interactive media in the development of ‘digital self-identity,’ and how this can be incorporated into treatment to the benefit of psychiatry. It will determine that this approach will require collaborative production between developers and psychiatrists in order to ensure precise goals are met, improving the success of serious gaming for psychiatric assessment and treatment. Analysis documents the reach of video games across a growing global community of gamers, highlighting cases of the positives and negatives of video game usage. The games industry is largely oblivious to the psychological negatives, with psychiatrists encountering new conditions such as gaming addiction, which is now recognized by the World Health Organization. With an increasing amount of gamers worldwide, and an additional time per day invested in online gaming and character development, the concept of virtual identity as a means of expressing the id needs further study to ensure successful treatment. In conclusion, the assessment and treatment of game-related conditions are currently reactionary, and while some mental health professionals have begun utilizing interactive technologies to assist with the assessment and treatment of conditions, this study will determine how the success of these products can be enhanced. This will include collaboration between software developers and psychiatrists, allowing new avenues of skill-sharing in interactive design and development. Outlining how to innovate approaches to engagement will reap greater rewards in future interactive products developed for psychiatric assessment and treatment.

Keywords: virtual reality, virtual identity, interactivity, psychiatry

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Authors: Shofiayuningtyas Luftiani

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Some private schools in Indonesia started integrating the online program Gizmos in the teaching-learning process. Gizmos was developed to supplement the existing curriculum by integrating it into the instructional programs. The program has some features using an inquiry-based simulation, in which students conduct exploration by using a worksheet while teachers use the teacher guidelines to direct and assess students’ performance In this study, the discussion about Gizmos highlights its features as the assessment media of mathematics learning for secondary school students. The discussion is based on the case study and literature review from the Indonesian context. The purpose of applying Gizmos as an assessment media refers to the diagnostic assessment. As a part of the diagnostic assessment, the teachers review the student exploration sheet, analyze particularly in the students’ difficulties and consider findings in planning future learning process. This assessment becomes important since the teacher needs the data about students’ persistent weaknesses. Additionally, this program also helps to build student’ understanding by its interactive simulation. Currently, the assessment over-emphasizes the students’ answers in the worksheet based on the provided answer keys while students perform their skill in translating the question, doing the simulation and answering the question. Whereas, the assessment should involve the multiple perspectives and sources of students’ performance since teacher should adjust the instructional programs with the complexity of students’ learning needs and styles. Consequently, the approach to improving the assessment components is selected to challenge the current assessment. The purpose of this challenge is to involve not only the cognitive diagnosis but also the analysis of skills and error. Concerning the selected setting for this diagnostic assessment that develops the combination of cognitive diagnosis, skills analysis and error analysis, the teachers should create an assessment rubric. The rubric plays the important role as the guide to provide a set of criteria for the assessment. Without the precise rubric, the teacher potentially ineffectively documents and follows up the data about students at risk of failure. Furthermore, the teachers who employ the program of Gizmos as the diagnostic assessment might encounter some obstacles. Based on the condition of assessment in the selected setting, the obstacles involve the time constrain, the reluctance of higher teaching burden and the students’ behavior. Consequently, the teacher who chooses the Gizmos with those approaches has to plan, implement and evaluate the assessment. The main point of this assessment is not in the result of students’ worksheet. However, the diagnostic assessment has the two-stage process; the process to prompt and effectively follow-up both individual weaknesses and those of the learning process. Ultimately, the discussion of Gizmos as the media of the diagnostic assessment refers to the effort to improve the mathematical learning process.

Keywords: diagnostic assessment, error analysis, Gizmos online program, skills analysis

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Authors: Javiera Espinosa, Patricia López, Noelia Santos, Nadia Loro, Esther Moraleda

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In recent years, there has been a notable increase in the number of investigations that establish that Down Syndrome and Autism Spectrum Disorder are diagnoses that can coexist together. However, there are also many studies that consider that both diagnoses present neuropsychological, linguistic and adaptive characteristics with a totally different profile. The objective of this research is to question whether there really can be a profile that encompasses both disorders or if they can be incompatible with each other. To this end, a review of the scientific literature of recent years has been carried out. The results indicate that the two lines collect opposite approaches. On the one hand, there is research that supports the increase in comorbidity between Down Syndrome and Autism Spectrum Disorder, and on the other hand, many investigations show a totally different general development profile between the two. The discussion focuses on discussing both lines of work and on proposing future lines of research in this regard.

Keywords: disability, language, speech, down syndrome

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Authors: Sadaf H. Khan, Jyoti Kumar

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Sick Building Syndrome (SBS) is a situation in which inhabitants of a building develop illness symptoms or get infected with a chronic disease as a result of the building in which they reside or work. Certain symptoms tend to get more severe as an individual spends more time in the building; however, they generally improve with time or even disappear when they leave that space. Though ‘Design of Built-Spaces’ is a crucial factor in regulating these symptoms but it still needs to be identified further as to what specific design features of a ‘Built-Space’ trigger sick building syndrome (SBS). Much of the research work present to date is focused on the physiological or physical sickness caused due to inappropriate built-space design. In this paper, the psychological aspects of sick building syndrome (SBS) will be investigated across the adult population, more specifically graduate students in India trying to settle in back to their previous physical work environments, i.e., campus, classrooms, hostels, after a very long hold which lasted more than a year due to lockdowns during Covid-19 crisis all over the world. The study will follow an analytical approach and the data will be collected through self-reported online surveys. The purpose of this study is to enquire causal agents, diagnosable symptoms and remedial design of built spaces which can enhance the productive level of built environments and better facilitate the inhabitants by improving their psychological wellbeing, which is the most uprising concern. The fact that SBS symptoms can be studied only within the initial few weeks as an occupant starts interacting with a built-environment and leaves as the occupant leaves that space or zone, the post-lockdown incoming of students back to their respective campuses provides an opportunity to clearly draw multiple conclusions of the relationship that exist between the Design of Built-Spaces and Psychological Sickness Syndrome associated with it. The study will be one of a kind approach for understanding and formulating methods to improve psychological wellbeing within a built-setting by better identifying factors associated with these psychological symptoms, including anxiety, mental fatigue, reduced attention span and reduced memory span as refined symptoms of SBS discussed in 1987 by Molhave within his study.

Keywords: built-environment psychology, built-space design, healthcare architecture, psychological wellbeing

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Authors: Hannah M. Russell

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‘The Attach Project’ (TAP), is an educational intervention aimed at improving educational and socio-emotional outcomes for children who are looked after. TAP is underpinned by Attachment Theory and is adapted from Dyadic Developmental Psychotherapy (DDP), which is a treatment for children and young people impacted by complex trauma and disorders of attachment. TAP has been implemented in primary schools in Northern Ireland throughout the 2018/19 academic year. During this time, a design and implementation study has been conducted to assess the promise of effectiveness for the future dissemination and ‘scaling-up’ of the programme for a larger, randomised control trial. TAP has been designed specifically for implementation in a school setting and is comprised of a whole school element and a more individualised Key Adult-Key Child pairing. This design and implementation study utilises a mixed-methods research design consisting of quantitative, qualitative, and observational measures with stakeholder input and involvement being considered an integral component. The use of quantitative measures, such as self-report questionnaires prior to and eight months following the implementation of TAP, enabled the analysis of the strengths and direction of relations between the various components of the programme, as well as the influence of implementation factors. The use of qualitative measures, incorporating semi-structured interviews and focus groups, enabled the assessment of implementation factors, identification of implementation barriers, and potential methods of addressing these issues. Observational measures facilitated the continual development and improvement of ‘TAP training’ for school staff. Preliminary findings have provided evidence of promise for the effectiveness of TAP and indicate the potential benefits of introducing this type of attachment-based intervention across other educational settings. This type of intervention could benefit not only children who are looked after but all children who may be impacted by complex trauma or disorders of attachment. Furthermore, findings from this study demonstrate that it is possible for children to form a secondary attachment relationship with a significant adult in school. However, various implementation factors which should be addressed were identified throughout the study, such as the necessity of protected time being introduced to facilitate the development of a positive Key Adult- Key Child relationship. Furthermore, additional ‘re-cap’ training is required in future dissemination of the programme, to maximise ‘attachment friendly practice’ in the whole staff team. Qualitative findings have also indicated that there is a general opinion across school staff that this type of Key Adult- Key Child pairing could be more effective if it was introduced as soon as children begin primary school. This research has provided ample evidence for the need to introduce relationally based interventions in schools, to help to ensure that children who are looked after, or who are impacted by complex trauma or disorders of attachment, can thrive in the school environment. In addition, this research has facilitated the identification of important implementation factors and barriers to implementation, which can be addressed prior to the ‘scaling-up’ of TAP for a robust, randomised controlled trial.

Keywords: attachment, complex trauma, educational interventions, implementation

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Authors: Monireh Ahmadi Bani, Adel Khorramrouz, Lalenoor Morvarid, Bagheri Mahtab

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Background:- Foot disorders are common in musculoskeletal problems. Plantar pressure distribution measurement is one the most important part of foot disorders diagnosis for quantitative analysis. However, the association of plantar pressure and foot disorders is not clear. With the growth of dataset and machine learning methods, the relationship between foot disorders and plantar pressures can be detected. Significance of the study:- The purpose of this study was to predict the probability of common foot disorders based on peak plantar pressure distribution and center of pressure during walking. Methodologies:- 2323 participants were assessed in a foot therapy clinic between 2015 and 2021. Foot disorders were diagnosed by an experienced physician and then they were asked to walk on a force plate scanner. After the data preprocessing, due to the difference in walking time and foot size, we normalized the samples based on time and foot size. Some of force plate variables were selected as input to a deep neural network (DNN), and the probability of any each foot disorder was measured. In next step, we used support vector machine (SVM) and run dataset for each foot disorder (classification of yes or no). We compared DNN and SVM for foot disorders prediction based on plantar pressure distributions and center of pressure. Findings:- The results demonstrated that the accuracy of deep learning architecture is sufficient for most clinical and research applications in the study population. In addition, the SVM approach has more accuracy for predictions, enabling applications for foot disorders diagnosis. The detection accuracy was 71% by the deep learning algorithm and 78% by the SVM algorithm. Moreover, when we worked with peak plantar pressure distribution, it was more accurate than center of pressure dataset. Conclusion:- Both algorithms- deep learning and SVM will help therapist and patients to improve the data pool and enhance foot disorders prediction with less expense and error after removing some restrictions properly.

Keywords: deep neural network, foot disorder, plantar pressure, support vector machine

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Authors: Abdelrahman A. Ramzy, Bassel S. Abdallah, Mohamed E. Bahgat, Sarah M. Abdelkader, Sherif H. ElGohary

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Attention-Deficit/Hyperactivity Disorder (ADHD), epilepsy, and autism affect millions of children worldwide, many of which are undiagnosed despite the fact that all of these disorders are detectable in early childhood. Late diagnosis can cause severe problems due to the late treatment and to the misconceptions and lack of awareness as a whole towards these disorders. Moreover, electroencephalography (EEG) has played a vital role in the assessment of neural function in children. Therefore, quantitative EEG measurement will be utilized as a tool for use in the evaluation of patients who may have ADHD, epilepsy, and autism. We propose a screening tool that uses EEG signals and machine learning algorithms to detect these disorders at an early age in an automated manner. The proposed classifiers used with epilepsy as a step taken for the work done so far, provided an accuracy of approximately 97% using SVM, Naïve Bayes and Decision tree, while 98% using KNN, which gives hope for the work yet to be conducted.

Keywords: ADHD, autism, epilepsy, EEG, SVM

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Authors: Delphine Vendryes, Dushyanth Sekhar, Baojia Tong, Matthew Theisen, Chester Curme

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Much of the data that inform the decisions of governments, corporations and individuals are harvested from unstructured documents. Data extraction is defined here as a process that turns non-machine-readable information into a machine-readable format that can be stored, for instance, in a database. In financial services, introducing more automation in data extraction pipelines is a major challenge. Information sought by financial data consumers is often buried within vast bodies of unstructured documents, which have historically required thorough manual extraction. Automated solutions provide faster access to non-machine-readable datasets, in a context where untimely information quickly becomes irrelevant. Data quality standards cannot be compromised, so automation requires high data integrity. This multifaceted task is broken down into smaller steps: ingestion, table parsing (detection and structure recognition), text analysis (entity detection and disambiguation), schema-based record extraction, user feedback incorporation. Selected intermediary steps are phrased as machine learning problems. Solutions leveraging cutting-edge approaches from the fields of computer vision (e.g. table detection) and natural language processing (e.g. entity detection and disambiguation) are proposed.

Keywords: computer vision, entity recognition, finance, information retrieval, machine learning, natural language processing

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Authors: Cristina Costa-Lobo, Sandra Fernandes, Miguel Magalhães, José Dinis-Carvalho, Alfredo Regueiro, Ana Carvalho

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This paper is a report on the findings of the construction and the validation of a questionnaire monetized in a portuguese higher education context with undergraduate students. The Questionnaire for the Evaluation of Entrepreneurship Project Psychopedagogical Practices consists of six scales: Critical appraisal of the project, Developed Learning and Skills, Teamwork, Teacher and Tutor Roles, Evaluation of Student Performance, and Project Effectiveness as a Teaching-Learning Methodology. The proceedings of its construction are analyzed, and the validity and internal consistency analysis are described. Findings indicate good indicators of validity, good fidelity and an interpretable factorial structure.

Keywords: entrepreneurship project, higher education, psychopedagogical practices, teacher and tutor roles

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Authors: Lana Burmistrova

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Introduction: The influence of visual impairments on several cognitive processes used in the music learning process is an increasingly important area in special education and cognitive musicology. Many children have several visual impairments due to the refractive errors and irreversible inhibitors. However, based on the compensatory neuroplasticity and functional reorganization, congenitally blind (CB) and early blind (EB) individuals use several areas of the occipital lobe to perceive and process auditory and tactile information. CB individuals have greater memory capacity, memory reliability, and less false memory mechanisms are used while executing several tasks, they have better working memory (WM) and short-term memory (STM). Blind individuals use several strategies while executing tactile and working memory n-back tasks: verbalization strategy (mental recall), tactile strategy (tactile recall) and combined strategies. Methods and design: The aim of the pilot study was to substantiate similar tendencies while executing attention, memory and combined auditory tasks in blind and sighted individuals constructed for this study, and to investigate attention, memory and combined mechanisms used in the music learning process. For this study eight (n=8) blind and eight (n=8) sighted individuals aged 13-20 were chosen. All respondents had more than five years music performance and music learning experience. In the attention task, all respondents had to identify pitch changes in tonal and randomized melodic pairs. The memory task was based on the mismatch negativity (MMN) proportion theory: 80 percent standard (not changed) and 20 percent deviant (changed) stimuli (sequences). Every sequence was named (na-na, ra-ra, za-za) and several items (pencil, spoon, tealight) were assigned for each sequence. Respondents had to recall the sequences, to associate them with the item and to detect possible changes. While executing the combined task, all respondents had to focus attention on the pitch changes and had to detect and describe these during the recall. Results and conclusion: The results support specific features in CB and EB, and similarities between late blind (LB) and sighted individuals. While executing attention and memory tasks, it was possible to observe the tendency in CB and EB by using more precise execution tactics and usage of more advanced periodic memory, while focusing on auditory and tactile stimuli. While executing memory and combined tasks, CB and EB individuals used passive working memory to recall standard sequences, active working memory to recall deviant sequences and combined strategies. Based on the observation results, assessment of blind respondents and recording specifics, following attention and memory correlations were identified: reflective attention and STM, reflective attention and periodic memory, auditory attention and WM, tactile attention and WM, auditory tactile attention and STM. The results and the summary of findings highlight the attention and memory features used in the music learning process in the context of blindness, and the tendency of the several attention and memory types correlated based on the task, strategy and individual features.

Keywords: attention, blindness, memory, music learning, strategy

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Authors: Aaditya U. Jhamb

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Due to the current energy crisis that many countries are battling, energy-efficient buildings are the subject of extensive research in the modern technological era because of growing worries about energy consumption and its effects on the environment. The paper explores 8 factors that help determine energy efficiency for a building: (relative compactness, surface area, wall area, roof area, overall height, orientation, glazing area, and glazing area distribution), with Tsanas and Xifara providing a dataset. The data set employed 768 different residential building models to anticipate heating and cooling loads with a low mean squared error. By optimizing these characteristics, machine learning algorithms may assess and properly forecast a building's heating and cooling loads, lowering energy usage while increasing the quality of people's lives. As a result, the paper studied the magnitude of the correlation between these input factors and the two output variables using various statistical methods of analysis after determining which input variable was most closely associated with the output loads. The most conclusive model was the Decision Tree Regressor, which had a mean squared error of 0.258, whilst the least definitive model was the Isotonic Regressor, which had a mean squared error of 21.68. This paper also investigated the KNN Regressor and the Linear Regression, which had to mean squared errors of 3.349 and 18.141, respectively. In conclusion, the model, given the 8 input variables, was able to predict the heating and cooling loads of a residential building accurately and precisely.

Keywords: energy efficient buildings, heating load, cooling load, machine learning models

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Authors: Maria E. Laconi, Kyla D. Scherr, Mary A. Jamieson

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Human populations in urban environments have rapidly grown in recent decades. Consequently, the intensity of land-use and development has also increased in many urban and peri-urban environments. Some cities, such as Detroit, Michigan, USA, have embraced urban agriculture and local food production. Little is known, however, about how the local and landscape scale environmental factors influence crop productivity on urban farms. Our study aims to evaluate factors influencing the productivity of strawberries on community farms and gardens in the Detroit metropolitan area. Strawberries are one of few fruits that can provide an abundant harvest just after the first season of being planted, which is ideal for urban gardeners in developed areas. In the spring of 2016, we planted six different strawberry cultivars (three everbearing and three June bearing varieties) at five farm sites in Wayne and Oakland County (six replicate plants per cultivar per site). We surveyed flower and fruit phenology and production for everbearing varieties weekly (flowers for June bearing varieties were removed to enhance productivity in the coming growing season). Additionally, we conducted one initial 36hr pollinator survey in mid-September during peak fruit production and characterized local and landscape scale land-cover data. Preliminary results and observations from this first year of our study revealed that strawberry production varied significantly by site. Specifically, productivity at our most northern site appeared to suffer from delayed phenology and early frost damage to ripening strawberries. Bee abundance and diversity also differed among farms, though further surveys are needed to adequately inventory the pollinator community. Finally, strawberry cultivars demonstrated significant differences in the number and size of fruits produced. We plan to continue this study in the coming years, increasing the number of sites surveyed and number of pollinator sampling events. Our study aims to inform strategies for enhancing crop productivity on urban and peri-urban farms.

Keywords: insect pollination, strawberry productivity, sustainable agriculture, urban gardening

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Authors: Sherin Ahmed El-Badry Sadek

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In this research, it is scientifically examined what contribution the professionalization of teachers can make to the development of a future-oriented vocational education and training system in Egypt. For this purpose, a needs assessment of the Egyptian vocational training system with the central actors and prevailing structures forms the foundation of the study, which theoretically underpinned with the attempt to resolve to some extent the tension between Luhmann's systems theory approach and the actor-centered theory of professional teacher competence. The vocational education system, in particular, must be adaptable and flexible due to the rapidly changing qualification requirements. In view of the pace of technological progress and the associated market changes, vocational training is no longer to be understood only as an educational tool aimed at those who achieve poorer academic performance or are not motivated to take up a degree. Rather, it is to be understood as a cornerstone for the development of society, and international experience shows that it is the core of lifelong learning. But to what extent have the education systems been able to react to these changes in their political, social, and technological systems? And how effective and sustainable are these changes actually? The vocational training system, in particular, has a particular impact on other social systems, which is why the appropriate parameters with the greatest leverage must be identified and adapted. Even if systems and structures are highly relevant, teachers must not hide behind them and must instead strive to develop further and to constantly learn. Despite numerous initiatives and programs to reform vocational training in Egypt, including the EU-funded Technical and Vocational Education and Training (TVET) reform phase I and phase II, the fit of the skilled workers to the needs of the labor market is still insufficient. Surveys show that the majority of employers are very dissatisfied with the graduates that the vocational training system produces. The data was collected through guideline-based interviews with experts from the education system and relevant neighboring systems, which allowed me to reconstruct central in-depth structures, as well as patterns of action and interpretation, in order to subsequently feed these into a matrix of recommendations for action. These recommendations are addressed to different decision-makers and stakeholders and are intended to serve as an impetus for the sustainable improvement of the Egyptian vocational training system. The research findings have shown that education, and in particular vocational training, is a political field that is characterized by a high degree of complexity and which is embedded in a barely manageable, highly branched landscape of structures and actors. At the same time, the vocational training system is not only determined by endogenous factors but also increasingly shaped by the dynamics of the environment and the neighboring social subsystems, with a mutual dependency relationship becoming apparent. These interactions must be taken into account in all decisions, even if prioritization of measures and thus a clear sequence and process orientation are of great urgency.

Keywords: competence orientation, educational policies, education systems, expert interviews, globalization, organizational development, professionalization, systems theory, teacher training, TVET system, vocational training

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Authors: Muhammad Yasir Wadood, Fatemeh Babaeian

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By developing ultra-wideband (UWB) systems, there is a high demand for UWB filters with low insertion loss, wide bandwidth, and having a planar structure which is compatible with other components of the UWB system. A microstrip interdigital filter is a great option for designing UWB filters. However, the presence of via holes in this structure creates difficulties in the fabrication procedure of the filter. Especially in the higher frequency band, any misalignment of the drilled via hole with the Microstrip stubs causes large errors in the measurement results compared to the desired results. Moreover, in this case (high-frequency designs), the line width of the stubs are very narrow, so highly precise small via holes are required to be implemented, which increases the cost of fabrication significantly. Also, in this case, there is a risk of having fabrication errors. To combat this issue, in this paper, a via-less UWB microstrip filter is proposed which is designed based on a modification of a conventional inter-digital bandpass filter. The novel approaches in this filter design are 1) replacement of each via hole with a quarter-wavelength open circuit stub to avoid the complexity of manufacturing, 2) using a bend structure to reduce the unwanted coupling effects and 3) minimising the size. Using the proposed structure, a UWB filter operating in the frequency band of 3.9-6.6 GHz (1-dB bandwidth) is designed and fabricated. The promising results of the simulation and measurement are presented in this paper. The selected substrate for these designs was Rogers RO4003 with a thickness of 20 mils. This is a common substrate in most of the industrial projects. The compact size of the proposed filter is highly beneficial for applications which require a very miniature size of hardware.

Keywords: band-pass filters, inter-digital filter, microstrip, via-less

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Authors: W. Zekri

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This paper explores Zohra Drif’s memoir, Inside the Battle of Algiers, which narrates her desires as a student to become a revolutionary activist. She exemplified, in her narrative, the different roles, she and her fellows performed as combatants in the Casbah during the Algerian Revolution 1954-1962. This book review aims to evaluate the concept of women’s agency through education and language learning, and its impact on empowering women’s desires. Close-reading method and thematic analysis are used to explore the text. The analysis identified themes that refine the meaning of agency which are social and cultural supports, education, and language proficiency. These themes aim to contribute to the representation in Inside the Battle of Algiers of a woman guerrilla who engaged herself to perform national acts of resistance.

Keywords: agency, education, learning, women

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Authors: Ahmed I. Alutabi, Naghmeh Dezhabad, Sudhakar Ganti

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Data centers have been growing in size and dema nd continuously in the last two decades. Planning for the deployment of resources has been shallow and always resorted to over-provisioning. Data center operators try to maximize the availability of their services by allocating multiple of the needed resources. One resource that has been wasted, with little thought, has been energy. In recent years, programmable resource allocation has paved the way to allow for more efficient and robust data centers. In this work, we examine the predictability of resource usage in a data center environment. We use a number of models that cover a wide spectrum of machine learning categories. Then we establish a framework to guarantee the client service level agreement (SLA). Our results show that using prediction can cut energy loss by up to 55%.

Keywords: machine learning, artificial intelligence, prediction, data center, resource allocation, green computing

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Authors: Todd Zhou, Mikhail Yurochkin

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Out-of-distribution (OOD) detection is receiving increasing amounts of attention in the machine learning research community, boosted by recent technologies, such as autonomous driving and image processing. This newly-burgeoning field has called for the need for more effective and efficient methods for out-of-distribution generalization methods. Without accessing the label information, deploying machine learning models to out-of-distribution domains becomes extremely challenging since it is impossible to evaluate model performance on unseen domains. To tackle this out-of-distribution detection difficulty, we designed a model selection pipeline algorithm and developed a model selection framework with different impurity and randomness measurements to evaluate and choose the best-performing models for out-of-distribution data. By exploring different randomness scores based on predicted probabilities, we adopted the out-of-distribution entropy and developed a custom-designed score, ”CombinedScore,” as the evaluation criterion. This proposed score was created by adding labeled source information into the judging space of the uncertainty entropy score using harmonic mean. Furthermore, the prediction bias was explored through the equality of opportunity violation measurement. We also improved machine learning model performance through model calibration. The effectiveness of the framework with the proposed evaluation criteria was validated on the Folktables American Community Survey (ACS) datasets.

Keywords: model selection, domain generalization, model fairness, randomness measurements, bias index

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