Search results for: iterative hard thresholding

Authors: Silvia Benvenuti, Alessandra Cardinali

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In recent years, for instance, in relation to the Covid 19 pandemic and the evidence of climate change, it is becoming quite clear that the development of a young kid into an adult citizen requires a solid scientific background. Citizens are required to exert logical thinking and know the methods of science in order to adapt, understand, and develop as persons. Mathematics sits at the core of these required skills: learning the axiomatic method is fundamental to understand how hard sciences work and helps in consolidating logical thinking, which will be useful for the entire life of a student. At the same time, research shows that the axiomatic study of geometry is a problematic topic for students, even for those with interest in mathematics. With this in mind, the main goals of the research work we will describe are: (1) to show whether non-Euclidean geometries can be a tool to allow students to consolidate the knowledge of Euclidean geometries by developing it in a critical way; (2) to promote the understanding of the modern axiomatic method in geometry; (3) to give students a new perspective on mathematics so that they can see it as a creative activity and a widely discussed topic with a historical background. One of the main issues related to the state-of-the-art in this topic is the shortage of experimental studies with students. For this reason, our aim is to show further experimental evidence of the potential benefits of teaching non-Euclidean geometries at high school, based on data collected from a study started in 2005 in the frame of the Italian National Piano Lauree Scientifiche, continued by a teacher training organized in September 2018, perfected in a pilot study that involved 77 high school students during the school years 2018-2019 and 2019-2020. and finally implemented through an experimental study conducted in 2020-21 with 87 high school students. Our study shows that there is potential for further research to challenge current conceptions of the school mathematics curriculum and of the capabilities of high school mathematics students.

Keywords: Non-Euclidean geometries, beliefs about mathematics, questionnaires, modern axiomatic method

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Authors: Mehran Asadi, Afrand Agah

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In data mining, partitioning is used as a fundamental tool for classification. With the help of partitioning, we study the structure of data, which allows us to envision decision rules, which can be applied to classification trees. In this research, we used online social network dataset and all of its attributes (e.g., Node features, labels, etc.) to determine what constitutes an above average chance of being a divergent node. We used the R statistical computing language to conduct the analyses in this report. The data were found on the UC Irvine Machine Learning Repository. This research introduces the basic concepts of classification in online social networks. In this work, we utilize overfitting and describe different approaches for evaluation and performance comparison of different classification methods. In classification, the main objective is to categorize different items and assign them into different groups based on their properties and similarities. In data mining, recursive partitioning is being utilized to probe the structure of a data set, which allow us to envision decision rules and apply them to classify data into several groups. Estimating densities is hard, especially in high dimensions, with limited data. Of course, we do not know the densities, but we could estimate them using classical techniques. First, we calculated the correlation matrix of the dataset to see if any predictors are highly correlated with one another. By calculating the correlation coefficients for the predictor variables, we see that density is strongly correlated with transitivity. We initialized a data frame to easily compare the quality of the result classification methods and utilized decision trees (with k-fold cross validation to prune the tree). The method performed on this dataset is decision trees. Decision tree is a non-parametric classification method, which uses a set of rules to predict that each observation belongs to the most commonly occurring class label of the training data. Our method aggregates many decision trees to create an optimized model that is not susceptible to overfitting. When using a decision tree, however, it is important to use cross-validation to prune the tree in order to narrow it down to the most important variables.

Keywords: online social networks, data mining, social cloud computing, interaction and collaboration

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Authors: Geminne Manzano, Clairecynth Yu, Lilibeth Salvador-Reyes, Viviene Santiago, Porfirio AliñO

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The distribution and abundance patterns of many marine sessile organisms such as sponges vary among and within reefs. Determining the factors affecting its distribution is essential especially for organisms that produce secondary metabolites with pharmaceutical importance. In this study, the small-scale distribution patterns of the Philippine blue sponge, Xestospongia sp. in relation to some ecological factors were examined. The relationship between the renieramycin-M production and their benthic attributes were also determined. Ecological surveys were conducted on two stations with varying depth and exposure located in Oriental Mindoro, Philippines. Three 30 by 6m belt transect were used to assess the sponge abundance at each station. The substratum of the sponges was also characterized. Fish visual census observations were also taken together with the photo transect methods benthic surveys. Sponge samples were also collected for the extraction of Renieramycin-M and for further chemical analysis. Varying distribution patterns were observed to be attributed to the combination of different ecological and environmental factors. The amount of Renieramycin-production also varied in each station. The common substratum for blue sponges includes hard and soft corals, as well as, dead coral with algal patches. Blue sponges from exposed habitat frequently grow associated with massive and branching corals, Porites sp., while the most frequent substrate found on sheltered habitats is the coral Pavona sp. Exploring the influence of ecological and environmental parameters on the abundance and distribution of sponge assemblages provide ecological insights and their potential applications to pharmaceutical studies. The results of this study provide further impetus in pursuing studies into patterns and processes of the Philippine blue sponge, Xestospongia sp. distribution in relation to the chemical ecology of its secondary metabolites.

Keywords: distribution patterns, Porifera, Renieramycin-M, sponge assemblages, Xestospongia sp.

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Authors: Chris Thurlbourne

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Due to the continual demand for material to build, and a limit of good environmental material credentials of 'normal' building materials, there is a need to look at new and reconditioned material types - both biogenic and non-biogenic - and a field of research that accompanies this. This research development focuses on biogenic and non-biogenic material engineering and the impact of our environment on new and reconditioned material types. In our building industry and all the industries involved in constructing our built environment, building material types can be broadly categorized into two types, biogenic and non-biogenic material properties. Both play significant roles in shaping our built environment. Regardless of their properties, all material types originate from our earth, whereas many are modified through processing to provide resistance to 'forces of nature', be it rain, wind, sun, gravity, or whatever the local environmental conditions throw at us. Modifications are succumbed to offer benefits in endurance, resistance, malleability in handling (building with), and ergonomic values - in all types of building material. We assume control of all building materials through rigorous quality control specifications and regulations to ensure materials perform under specific constraints. Yet materials confront an external environment that is not controlled with live forces undetermined, and of which materials naturally act and react through weathering, patination and discoloring, promoting natural chemical reactions such as rusting. The purpose of the paper is to present recent research that explores the after-life of specific new and reconditioned biogenic and non-biogenic material types and how the understanding of materials' natural processes of transformation when exposed to the external climate, can inform initial design decisions. With qualities to receive in a transient and contingent manner, ecological relationships between material, the colonizing organisms and resulting performances invite opportunities for new design explorations for the benefit of both the needs of human society and the needs of our natural environment. The research follows designing for the benefit of both and engaging in both biogenic and non-biogenic material engineering whilst embracing the continual demand for colonization - human and environment, and the aptitude of a material to be colonized by one or several groups of living organisms without necessarily undergoing any severe deterioration, but embracing weathering, patination and discoloring, and at the same time establishing new habitat. The research follows iterative prototyping processes where knowledge has been accumulated via explorations of specific material performances, from laboratory to construction mock-ups focusing on the architectural qualities embedded in control of production techniques and facilitating longer-term patinas of material surfaces to extend the aesthetic beyond common judgments. Experiments are therefore focused on how the inherent material qualities drive a design brief toward specific investigations to explore aesthetics induced through production, patinas and colonization obtained over time while exposed and interactions with external climate conditions.

Keywords: biogenic and non-biogenic, natural processes of transformation, colonization, patina

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Authors: Lina Psarra, Manogj Sundaresan, Purjeet Sutar

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In response to the global imperative for sustainable solutions, this article proposes the development of a comprehensive circularity index applicable to a wide range of products across various industries. The absence of a consensus on using a universal metric to assess circularity performance presents a significant challenge in prioritizing and effectively managing sustainable initiatives. This circularity index serves as a quantitative measure to evaluate the adherence of products, processes, and systems to the principles of a circular economy. Unlike traditional distinct metrics such as recycling rates or material efficiency, this index considers the entire lifecycle of a product in one single metric, also incorporating additional factors such as reusability, scarcity of materials, reparability, and recyclability. Through a systematic approach and by reviewing existing metrics and past methodologies, this work aims to address this gap by formulating a circularity index that can be applied to diverse product portfolio and assist in comparing the circularity of products on a scale of 0%-100%. Project objectives include developing a formula, designing and implementing a pilot tool based on the developed Product Circularity Index (PCI), evaluating the effectiveness of the formula and tool using real product data, and assessing the feasibility of integration into various sustainability initiatives. The research methodology involves an iterative process of comprehensive research, analysis, and refinement where key steps include defining circularity parameters, collecting relevant product data, applying the developed formula, and testing the tool in a pilot phase to gather insights and make necessary adjustments. Major findings of the study indicate that the PCI provides a robust framework for evaluating product circularity across various dimensions. The Excel-based pilot tool demonstrated high accuracy and reliability in measuring circularity, and the database proved instrumental in supporting comprehensive assessments. The PCI facilitated the identification of key areas for improvement, enabling more informed decision-making towards circularity and benchmarking across different products, essentially assisting towards better resource management. In conclusion, the development of the Product Circularity Index represents a significant advancement in global sustainability efforts. By providing a standardized metric, the PCI empowers companies and stakeholders to systematically assess product circularity, track progress, identify improvement areas, and make informed decisions about resource management. This project contributes to the broader discourse on sustainable development by offering a practical approach to enhance circularity within industrial systems, thus paving the way towards a more resilient and sustainable future.

Keywords: circular economy, circular metrics, circularity assessment, circularity tool, sustainable product design, product circularity index

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Authors: Sara Khamseh, Kambiz Javanruee, Hamid Khorsand

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Plenty of metallic materials are used for biomedical applications like hip joints and screws. Besides, it is reported that metal platforms such as stainless steel show significant deterioration because of wear and friction. The surface of metal substrates has been coated with a variety of multicomponent coatings to prevail these problems. The carbon-based multicomponent coatings such as metal-added amorphous carbon and diamond coatings are crucially important because of their remarkable tribological performance and chemical stability. In the current study, H-D contained Nb: (a-C) multicomponent coatings (H-D: hexagonal diamond, a-C: amorphous carbon) coated on A 304 steel substrates using an unbalanced magnetron (UBM) sputtering system. The effects of Nb and H-D content and ID/IG ratio on microstructure, mechanical and tribological characteristics of (Nb: H-D: a-C) composite coatings were investigated. The results of Raman spectroscopy represented that a-C phase with a Graphite-like structure (GLC with high value of sp2 carbon bonding) is formed, and its domain size increased with increasing Nb content of the coatings. Moreover, the Nb played a catalyst for the formation of the H-D phase. The nanoindentation hardness value of the coatings ranged between ~17 to ~35 GPa and (Nb: H-D: a-C) composite coatings with more H-D content represented higher hardness and plasticity index. It seems that the existence of extra-hard H-D particles straightly increased hardness. The tribological performance of the coatings was evaluated using the pin-on-disc method under the wet environment of SBF (Simulated Body Fluid). The COF value of the (Nb: H-D: a-C) coatings decreased with an increasing ID/IG ratio. The lower coefficient of friction is a result of the lamelliform array of graphitic domains. Also, the wear rate of the coatings decreased with increasing H-D content of the coatings. Based on the literature, a-C coatings with high hardness and H3/E2 ratio represent lower wear rates and better tribological performance. According to the nanoindentation analysis, hardness and H3/E2 ratio of (Nb: H-D: a-C) multicomponent coatings increased with increasing H-D content, which in turn decreased the wear rate of the coatings. The mechanical and tribological potency of (Nb: H-D: a-C) composite coatings on A 304 steel substrates paved the way for the development of innovative advanced coatings to ameliorate the performance of A 304 steel for biomedical applications.

Keywords: COF, mechanical properties, (Nb: H-D: a-C) coatings, wear rate

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Authors: Manchari Paranthahan

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Higher education has often presented barriers to many communities as a result of its colonial roots. While higher education was initially created for white cis-males, student populations have become more diverse in the past few decades. Despite this increase in diversity, barriers like rising costs and hostile education settings continue to make higher education hard to access for certain demographics. These barriers and limitations are compounded for students who are intersectionality marginalized, such as Queer and Trans Black, Indigenous and People of Colour (QTBIPOC) Disabled students. As of 2021-2022, only 57.5% of the Canadian population between the ages of 25 - 64 held a college or university credential, with only 32.9% holding a bachelor’s degree or higher. In that same time frame, only 0.64% of the students who successfully completed a higher education program identified as transgender or nonbinary. QTBIPOC Disabled students experience diverse forms of oppression while navigating education systems, often preventing them from completing their education successfully. This research project will investigate the complex experiences of intersectional marginalization of QTBIPOC Disabled students in Canadian post-secondary education systems. Through this investigation, this research seeks to reimagine more inclusive and accessible education systems in Canada and beyond. The social and academic experiences of QTBIPOC Disabled students in education systems are largely absent from scholarly literature, speaking to their continued marginalization and erasure from academic discourses. The lack of representation for this community in academia reinforces the idea that there is no space for marginalized bodies in further education, a discriminatory belief that this research project aims to investigate and reframe with this project. This research study will be informed by Critical Race theory, Queer Theory and Critical Disability Theories. Through a blend of critical narrative ethnography and ethnodrama for my methodological framing. Using these methodologies will speak to the intersecting factors that impact the experiences that QTBIPOC Disabled students have in education systems while offering space to analyze and create new systems of learning that benefits all students.

Keywords: QTBIPOC, queer, disability, pedagogy

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Authors: Olatunji Sabitu Alimi

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This study investigated the extent to which administrators’ information storage, retrieval and processing capacities influence decisions on staff promotion in the Teaching Service Commissions (TESCOMs) in The South-West, Nigeria. One research question and two research hypotheses were formulated and tested respectively at 0.05 level of significance. The study used the descriptive research of the survey type. One hundred (100) staff on salary grade level 09 constituted the sample. Multi- stage, stratified and simple random sampling techniques were used to select 100 staff from the TESCOMs in The South-West, Nigeria. Two questionnaires titled Administrators’ Information Storage, Retrieval and Processing Capacities (AISRPC), and Staff Promotion Effectiveness (SPE) were used for data collection. The inventory was validated and subjected to test-re-test and reliability coefficient of r = 0.79 was obtained. The data were collected and analyzed using Pearson Product Moment Correlation coefficient and simple percentage. The study found that Administrators at TESCOM stored their information in files, hard copies, soft copies, open registry and departmentally in varying degrees while they also processed information manually and through electronics for decision making. In addition, there is a significant relationship between administrators’ information storage and retrieval capacities in the TESCOMs in South – West, Nigeria, (r cal = 0.598 > r table = 0.195). Furthermore, administrators’ information processing capacity and staff promotion effectiveness were found to be significantly related (r cal = 0.209 > r table = 0.195 at 0.05 level of significance). The study recommended that training, seminars, workshops should be organized for administrators on information management, while educational organizations should provide Information Management Technology (ICT) equipment for the administrators in the TESCOMs. The staff of TESCOM should be promoted having satisfied the promotion criteria such as spending required number of years on a grade level, a clean record of service and vacancy.

Keywords: information processing capacity, staff promotion effectiveness, teaching service commission, Nigeria

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Authors: Niloofar Yousefi, Marie Alaghband, Ivan Garibay

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With the increase of credit card usage, the volume of credit card misuse also has significantly increased, which may cause appreciable financial losses for both credit card holders and financial organizations issuing credit cards. As a result, financial organizations are working hard on developing and deploying credit card fraud detection methods, in order to adapt to ever-evolving, increasingly sophisticated defrauding strategies and identifying illicit transactions as quickly as possible to protect themselves and their customers. Compounding on the complex nature of such adverse strategies, credit card fraudulent activities are rare events compared to the number of legitimate transactions. Hence, the challenge to develop fraud detection that are accurate and efficient is substantially intensified and, as a consequence, credit card fraud detection has lately become a very active area of research. In this work, we provide a survey of current techniques most relevant to the problem of credit card fraud detection. We carry out our survey in two main parts. In the first part, we focus on studies utilizing classical machine learning models, which mostly employ traditional transnational features to make fraud predictions. These models typically rely on some static physical characteristics, such as what the user knows (knowledge-based method), or what he/she has access to (object-based method). In the second part of our survey, we review more advanced techniques of user authentication, which use behavioral biometrics to identify an individual based on his/her unique behavior while he/she is interacting with his/her electronic devices. These approaches rely on how people behave (instead of what they do), which cannot be easily forged. By providing an overview of current approaches and the results reported in the literature, this survey aims to drive the future research agenda for the community in order to develop more accurate, reliable and scalable models of credit card fraud detection.

Keywords: Credit Card Fraud Detection, User Authentication, Behavioral Biometrics, Machine Learning, Literature Survey

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Authors: Mane Darbinyan, Lusine Hayrapetyan, Elen Matevosyan

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Artificial Intelligence in Education (AIED) has been created to help students get ready for the workforce, and over the past 25 years, it has grown significantly, offering a variety of technologies to support academic, institutional, and administrative services. However, this is still challenging, especially considering the labor market's rapid change. While choosing a career, people face various obstacles because they do not take into consideration their own preferences, which might lead to many other problems like shifting jobs, work stress, occupational infirmity, reduced productivity, and manual error. Besides preferences, people should properly evaluate their technical and non-technical skills, as well as their personalities. Professional counseling has become a difficult undertaking for counselors due to the wide range of career choices brought on by changing technological trends. It is necessary to close this gap by utilizing technology that makes sophisticated predictions about a person's career goals based on their personality. Hence, there is a need to create an automated model that would help in decision-making based on user inputs. Improving career guidance can be achieved by embedding machine learning into the career consulting ecosystem. There are various systems of career guidance that work based on the same logic, such as the classification of applicants, matching applications with appropriate departments or jobs, making predictions, and providing suitable recommendations. Methodologies like KNN, Neural Networks, K-means clustering, D-Tree, and many other advanced algorithms are applied in the fields of data and compute some data, which is helpful to predict the right careers. Besides helping users with their career choice, these systems provide numerous opportunities which are very useful while making this hard decision. They help the candidate to recognize where he/she specifically lacks sufficient skills so that the candidate can improve those skills. They are also capable to offer an e-learning platform, taking into account the user's lack of knowledge. Furthermore, users can be provided with details on a particular job, such as the abilities required to excel in that industry.

Keywords: career guidance system, machine learning, career prediction, predictive decision, data mining, technical and non-technical skills

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Authors: Farnaz Jafari

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The surge in mass timber construction represents a pivotal moment in sustainable building practices, yet the lack of comprehensive education in construction management poses a challenge in harnessing this innovation effectively. This research endeavors to bridge this gap by developing a curriculum framework integrating mass timber construction into undergraduate and industry certificate programs. To optimize learning outcomes, the study explores the impact of two prototype formats -Virtual Reality (VR) simulations and physical mock-ups- on students' understanding and skill development. The curriculum framework aims to equip future construction managers with a holistic understanding of mass timber, covering its unique properties, construction methods, building codes, and sustainable advantages. The study adopts a mixed-methods approach, commencing with a systematic literature review and leveraging surveys and interviews with educators and industry professionals to identify existing educational gaps. The iterative development process involves incorporating stakeholder feedback into the curriculum. The evaluation of prototype impact employs pre- and post-tests administered to participants engaged in pilot programs. Through qualitative content analysis and quantitative statistical methods, the study seeks to compare the effectiveness of VR simulations and physical mock-ups in conveying knowledge and skills related to mass timber construction. The anticipated findings will illuminate the strengths and weaknesses of each approach, providing insights for future curriculum development. The curriculum's expected contribution to sustainable construction education lies in its emphasis on practical application, bridging the gap between theoretical knowledge and hands-on skills. The research also seeks to establish a standard for mass timber construction education, contributing to the field through a unique comparative analysis of VR simulations and physical mock-ups. The study's significance extends to the development of best practices and evidence-based recommendations for integrating technology and hands-on experiences in construction education. By addressing current educational gaps and offering a comparative analysis, this research aims to enrich the construction management education experience and pave the way for broader adoption of sustainable practices in the industry. The envisioned curriculum framework is designed for versatile integration, catering to undergraduate programs and industry training modules, thereby enhancing the educational landscape for aspiring construction professionals. Ultimately, this study underscores the importance of proactive educational strategies in preparing industry professionals for the evolving demands of the construction landscape, facilitating a seamless transition towards sustainable building practices.

Keywords: curriculum framework, mass timber construction, physical vs. virtual prototypes, sustainable building practices

Procedia PDF Downloads 73

Authors: Mane Darbinyan, Lusine Hayrapetyan, Elen Matevosyan

Abstract:

Artificial Intelligence in Education (AIED) has been created to help students get ready for the workforce, and over the past 25 years, it has grown significantly, offering a variety of technologies to support academic, institutional, and administrative services. However, this is still challenging, especially considering the labor market's rapid change. While choosing a career, people face various obstacles because they do not take into consideration their own preferences, which might lead to many other problems like shifting jobs, work stress, occupational infirmity, reduced productivity, and manual error. Besides preferences, people should evaluate properly their technical and non-technical skills, as well as their personalities. Professional counseling has become a difficult undertaking for counselors due to the wide range of career choices brought on by changing technological trends. It is necessary to close this gap by utilizing technology that makes sophisticated predictions about a person's career goals based on their personality. Hence, there is a need to create an automated model that would help in decision-making based on user inputs. Improving career guidance can be achieved by embedding machine learning into the career consulting ecosystem. There are various systems of career guidance that work based on the same logic, such as the classification of applicants, matching applications with appropriate departments or jobs, making predictions, and providing suitable recommendations. Methodologies like KNN, neural networks, K-means clustering, D-Tree, and many other advanced algorithms are applied in the fields of data and compute some data, which is helpful to predict the right careers. Besides helping users with their career choice, these systems provide numerous opportunities which are very useful while making this hard decision. They help the candidate to recognize where he/she specifically lacks sufficient skills so that the candidate can improve those skills. They are also capable of offering an e-learning platform, taking into account the user's lack of knowledge. Furthermore, users can be provided with details on a particular job, such as the abilities required to excel in that industry.

Keywords: career guidance system, machine learning, career prediction, predictive decision, data mining, technical and non-technical skills

Procedia PDF Downloads 71

Authors: Elisa Boatti, Ulisse Stefanelli, Alessandro Reali, Ferdinando Auricchio

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Thanks to their unusual properties, shape memory alloys (SMAs) are good candidates for advanced applications in a wide range of engineering fields, such as automotive, robotics, civil, biomedical, aerospace. In the last decades, the ever-growing interest for such materials has boosted several research studies aimed at modeling their complex nonlinear behavior in an effective and robust way. Since the constitutive response of SMAs is strongly thermomechanically coupled, the investigation of the non-isothermal evolution of the material must be taken into consideration. The present study considers an existing three-dimensional phenomenological model for SMAs, able to reproduce the main SMA properties while maintaining a simple user-friendly structure, and proposes a variational reformulation of the full non-isothermal version of the model. While the considered model has been thoroughly assessed in an isothermal setting, the proposed formulation allows to take into account the full nonisothermal problem. In particular, the reformulation is inspired to the GENERIC (General Equations for Non-Equilibrium Reversible-Irreversible Coupling) formalism, and is based on a generalized gradient flow of the total entropy, related to thermal and mechanical variables. Such phrasing of the model is new and allows for a discussion of the model from both a theoretical and a numerical point of view. Moreover, it directly implies the dissipativity of the flow. A semi-implicit time-discrete scheme is also presented for the fully coupled thermomechanical system, and is proven unconditionally stable and convergent. The correspondent algorithm is then implemented, under a space-homogeneous temperature field assumption, and tested under different conditions. The core of the algorithm is composed of a mechanical subproblem and a thermal subproblem. The iterative scheme is solved by a generalized Newton method. Numerous uniaxial and biaxial tests are reported to assess the performance of the model and algorithm, including variable imposed strain, strain rate, heat exchange properties, and external temperature. In particular, the heat exchange with the environment is the only source of rate-dependency in the model. The reported curves clearly display the interdependence between phase transformation strain and material temperature. The full thermomechanical coupling allows to reproduce the exothermic and endothermic effects during respectively forward and backward phase transformation. The numerical tests have thus demonstrated that the model can appropriately reproduce the coupled SMA behavior in different loading conditions and rates. Moreover, the algorithm has proved effective and robust. Further developments are being considered, such as the extension of the formulation to the finite-strain setting and the study of the boundary value problem.

Keywords: generalized gradient flow, GENERIC formalism, shape memory alloys, thermomechanical coupling

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Authors: Stephen Wagman

Abstract:

This paper identifies three common structures in English sentences that are important for understanding academic texts, regardless of the characteristics or background of the readers or whether they are reading English as a second or a foreign language. Adapting a model from the Humanities, the explication of texts used in literary studies, the paper analyses sample sentences to reveal structures that enable the reader not only to decide which words are necessary for understanding the main ideas but to make the decision without knowing the meaning of the words. By their very syntax noun structures point to the key word for understanding them. As a rule, the key noun is followed by easily identifiable prepositions, relative pronouns, or verbs and preceded by single adjectives. With few exceptions, the modifiers are unnecessary for understanding the idea of the sentence. In addition, sentences are often structured by lists in which the items frequently consist of parallel groups of words. The principle of a list is that all the items are similar in meaning and it is not necessary to understand all of the items to understand the point of the list. This principle is especially important when the items are long or there is more than one list in the same sentence. The similarity in meaning of these items enables readers to reduce sentences that are hard to grasp to an understandable core without excessive use of a dictionary. Finally, the idea of subordination and the identification of the subordinate parts of sentences through connecting words makes it possible for readers to focus on main ideas without having to sift through the less important and more numerous secondary structures. Sometimes a main idea requires a subordinate one to complete its meaning, but usually, subordinate ideas are unnecessary for understanding the main point of the sentence and its part in the development of the argument from sentence to sentence. Moreover, the connecting words themselves indicate the functions of the subordinate structures. These most frequently show similarity and difference or reasons and results. Recognition of all of these structures can not only enable students to read more efficiently but to focus their attention on the development of the argument and this rather than a multitude of unknown vocabulary items, the repetition in lists, or the subordination in sentences are the one necessary element for comprehension of academic articles.

Keywords: development of the argument, lists, noun structures, subordination

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Authors: A. F. G. Van Woezik, L. M. A. Braakman-Jansen, O. A. Kulyk, J. E. W. C. Van Gemert-Pijnen

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Background: Zoonoses pose a serious threat to public health and economies worldwide, especially as antimicrobial resistance grows and newly emerging zoonoses can cause unpredictable outbreaks. In order to prevent and control emerging and re-emerging zoonoses, collaboration between veterinary, human health and public health domains is essential. In reality however, there is a lack of cooperation between these three disciplines and uncertainties exist about their tasks and responsibilities. The objective of this ongoing research project (ZonMw funded, 2014-2018) is to develop an online education and communication One Health platform, “eZoon”, for the general public and professionals working in veterinary, human health and public health domains to support the risk communication of non-alimentary zoonoses in the Netherlands. The main focus is on education and communication in times of outbreak as well as in daily non-outbreak situations. Methods: A participatory development approach was used in which stakeholders from veterinary, human health and public health domains participated. Key stakeholders were identified using business modeling techniques previously used for the design and implementation of antibiotic stewardship interventions and consisted of a literature scan, expert recommendations, and snowball sampling. We used a stakeholder salience approach to rank stakeholders according to their power, legitimacy, and urgency. Semi-structured interviews were conducted with stakeholders (N=20) from all three disciplines to identify current problems in risk communication and stakeholder values for the One Health platform. Interviews were transcribed verbatim and coded inductively by two researchers. Results: The following key values were identified (but were not limited to): (a) need for improved awareness of veterinary and human health of each other’s fields, (b) information exchange between veterinary and human health, in particularly at a regional level; (c) legal regulations need to match with daily practice; (d) professionals and general public need to be addressed separately using tailored language and information; (e) information needs to be of value to professionals (relevant, important, accurate, and have financial or other important consequences if ignored) in order to be picked up; and (f) need for accurate information from trustworthy, centrally organised sources to inform the general public. Conclusion: By applying a participatory development approach, we gained insights from multiple perspectives into the main problems of current risk communication strategies in the Netherlands and stakeholder values. Next, we will continue the iterative development of the One Health platform by presenting key values to stakeholders for validation and ranking, which will guide further development. We will develop a communication platform with a serious game in which professionals at the regional level will be trained in shared decision making in time-critical outbreak situations, a smart Question & Answer (Q&A) system for the general public tailored towards different user profiles, and social media to inform the general public adequately during outbreaks.

Keywords: ehealth, one health, risk communication, stakeholder, zoonosis

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Authors: Prama Mukhopadhyay, Rishika Mukhopadhyay

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The twentieth century has seen the world getting divided into three distinct blocks, created by the proponents of the mainstream developmental discourse. India, which has now gained the label of being a ‘developing nation’, stands in between these three groups, as it constantly tries to ‘catch up’ and emulate the developmental standards of the ‘west’. In this endeavour, we find our country trying really hard to blindly replicate the health care infrastructures of the ‘first worlds’, without realizing the needs of evaluating the ground reality. In such a situation, the sudden outbreak of child death in the district of Malda, WB, poses an obvious questions towards the kind of development that our country has been engaging in, ever since its Post Colonial inception. Through this paper we thus try to understand the harsh veracity of the health care facility that exists in rural Bengal, and thereby challenge the conventional notion of ‘health-care’ as is normally discussed in the mainstream developmental discourse. Grounding our research work on detailed ethnography and through the help of questionnaire, interviews and focus group discussions with the local government officials(BDOs), health workers (ICDS, ASHA workers, ANHM and BMOHs) and members of families with experiences of child deaths, we have tried to find out the real and humane factors behind the sudden rise of reported infant deaths in the district, issues which are normally neglected and left out while discussing and evaluating IMR in the mainstream studies on health care and planning in our nation. Therefore the main aim of this paper is to try and look at child death from a ‘wider perspective’, where it is seen from an eye not bounded by the common registers of caste, class and religion. This paper, would thus be an eye opener in some sense, bringing in stories from the rural belt of the country; where the people are regularly torn between the binaries of the developing and shining modernity of ‘India’ which now gets ready to run the last lap and gain the status of becoming a ‘developed nation’ by 2020, and the staggering, dark traditional ‘ Bharat, which lags behind.

Keywords: child mortality, development discourse, health care, tradition and modernity

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Authors: Alexander Musyoki, Collins Odour

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Over the past few years, the bakery industry in Kenya has experienced significant growth largely in part to the increased adoption of technology and automation in their processes; more specifically due to the adoption of bakery management systems to help in running bakeries. While they have been largely responsible for the improved productivity and efficiency in bakeries, most of them are now outdated and pose more challenges than benefits. The proposed online bakery management system mentioned in this paper aims to address this by allowing bakery owners to track inventory, budget, job progress, and data analytics on each job and in doing so, promote the Sustainable Development Goals 3 and 12, which aim to ensure healthy lives and promote sustainable economic growth as the proposed benefits of these features include scalability, easy accessibility, reduced acquisition costs, better reliability, and improved functionality that will allow bakeries to become more competitive, reduce waste and track inventory more efficiently. To better understand the challenges, a comprehensive study has been performed to assess these traditional systems and try to understand if an online bakery management system can prove to be advantageous to bakery owners. The study conducted gathered feedback from bakery owners and employees in Nairobi County, Kenya using an online survey with a response rate of about 86% from the target population. The responses cited complex and hard to use bakery management systems (59.7%), lack of portability from one device to the other (58.1%) and high acquisition costs (51.6%) as the top challenges of traditional bakery management systems. On the other hand, some of the top benefits that most of the respondents would realize from the online bakery management system was better reliability (58.1%) and reduced acquisition costs (58.1%). Overall, the findings suggest that an online bakery management system has a lot of advantages over traditional systems and is likely to be well-received in the market. In conclusion, the proposed online bakery management system has the potential to improve the efficiency and competitiveness of small-sized bakeries in Nairobi County. Further research is recommended to expand the sample size and diversity of respondents and to conduct more in-depth analyses of the data collected.

Keywords: ICT, technology and automation, bakery management systems, food innovation

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Authors: Ilona Buchem, Carolin Gellner

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The call for the support of senior learners in the development of digital literacy has become prevalent in recent years, especially in view of the aging societies paired with advances in digitalization in all spheres of life, including e-health. The goal has been to create opportunities for learning that incorporate the use of context in a reflective and dialogical way. Contextual learning has focused on developing skills through the application of authentic problems. While major research efforts in supporting senior learners in developing digital literacy have been invested so far in e-learning, focusing on knowledge acquisition and cognitive tasks, little research exists in reflective mentoring and coaching with the help of pedagogical agents and addressing the contextual dimensions of learning. This paper describes an approach to creating opportunities for senior learners to improve their digital literacy in the authentic context of the electronic health record (EHR) with the support of an intelligent virtual learning coach. The paper focuses on the design of the virtual coach as part of an e-learning system, which was developed in the EPA-Coach project founded by the German Ministry of Education and Research. The paper starts with the theoretical underpinnings of contextual learning and the related design considerations for a virtual learning coach based on previous studies. Since previous research in the area was mostly designed to cater to the needs of younger audiences, the results had to be adapted to the specific needs of senior learners. Next, the paper outlines the stages in the design of the virtual coach, which included the adaptation of the design requirements, the iterative development of the prototypes, the results of the two evaluation studies and how these results were used to improve the design of the virtual coach. The paper then presents the four prototypes of a senior-friendly virtual learning coach, which were designed to represent different preferences related to the visual appearance, the communication and social interaction styles, and the pedagogical roles. The first evaluation of the virtual coach design was an exploratory, qualitative study, which was carried out in October 2020 with eight seniors aged 64 to 78 and included a range of questions about the preferences of senior learners related to the visual design, gender, age, communication and role. Based on the results of the first evaluation, the design was adapted to the preferences of the senior learners and the new versions of prototypes were created to represent two male and two female options of the virtual coach. The second evaluation followed a quantitative approach with an online questionnaire and was conducted in May 2021 with 41 seniors aged 66 to 93 years. Following three research questions, the survey asked about (1) the intention to use, (2) the perceived characteristics, and (3) the preferred communication/interaction style of the virtual coach, i. e. task-oriented, relationship-oriented, or a mix. This paper follows with the discussion of the results of the design process and ends with conclusions and next steps in the development of the virtual coach including recommendations for further research.

Keywords: virtual learning coach, virtual mentor, pedagogical agent, senior learners, digital literacy, electronic health records

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Authors: Onuoha Ogbonnaya Gideon, Ishaq Hafsah Yusuf

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Introduction: Meat is a perishable food of good nutrition. Meat ranks among the most significant, nutritious, and favored food items available to most locals. It is a good source of protein (17-19%), depending on sources, and contains appreciable amounts of fat and moisture. However, it has a very short shelf life due mainly to its high moisture, fat, and other nutrient contents. Meat spoilage can result from microbial proliferation as well as inherent enzymes in the meat tissues. Bacteria contamination and permeability to both oxygen and water vapor are major concerns associated with spoilage of meat and its storage. Packaging is fundamental in the preservation and presentation of food. Red clay is a very common substance; hydrous aluminum phyllosilicate, sometimes with varying amounts of iron, magnesium, alkali metals, alkaline earth, and cation formed from sedimentary rocks. Furthermore, red clay is an extremely absorbent material and develops plasticity when wet due to the molecular film of water surrounding the clay particles but can become hard, impervious, brittle, and non-brittle and non-plastic when dry. In developing countries, the high cost of refrigeration technologies and most other methods of preserving meat are exorbitant and thus can be substituted with the less expensive and readily available red clay for the preservation of meat. Methodology: 1000g of lean meat was diced into cubes of 10g each. The sample was then divided into four groups labelled raw meat (RMC); raw in 10% brine solution (RMB), boiled meat (BMC), and fried meat (FMC). It was then encapsulated with 2mm thick red clay and then heated in a muffle furnace at a temperature of 600OC for 30min. The samples were kept on a bench top for 30 days, and a storage study was carried out. Results: Our findings showed a decrease in value during storage for the physiochemical properties of all the sample; pH values decreased [RMC (7.05-7.6), RMB (8.46-7.0), BMC (6.0-5.0), FMC (4.08-3.9)]; free fatty acid content decreased with storage time [RMC (32.6%-31%), RMB (30.2%-28.6%), BMC (30.5%-27.4%), FMC (25.6%-23.8%)]; total soluble solid value decreased [RMC16.20-15.07, RMB (17.22-16.04), BMC (17.05-15.54), FMC (15.3-14.9)]. Conclusion: This result shows that encapsulation with red clay reduced all the values analyzed and thus has the potential to extend the shelf life of stored meat.

Keywords: red clay, encapsulating, shelf life, physicochemical properties, lean meat

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Authors: Olivia R. Rendon

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More than half of the world population lives in cities, in the UK, for example, 82% of the population was urban by 2013. Cities concentrate valuable and numerous infrastructure and sectors of the national economies. Cities are particularly vulnerable to climate change which will lead to higher damage costs in the future. There is thus a need to develop and invest in adaptation measures for cities to reduce the impact of flooding and other extreme weather events. Recent flood episodes present a significant and growing challenge to the UK and the estimated cost of urban flood damage is 270 million a year for England and Wales. This study aims to carry out cost-benefit analysis (CBA) of a nature-based approach for flood risk management in cities, focusing on the city of Leeds and the wider Aire catchment as a case study. Leeds was chosen as a case study due to its being one of the most flood vulnerable cities in the UK. In Leeds, over 4,500 properties are currently vulnerable to flooding and approximately £450 million of direct damage is estimated for a potential major flood from the River Aire. Leeds is also the second largest Metropolitan District in England with a projected population of 770,000 for 2014. So far the city council has mainly focused its flood risk management efforts on hard infrastructure solutions for the city centre. However, the wider Leeds district is at significant flood risk which could benefit from greener adaptation measures. This study presents estimates of a nature-based adaptation approach for flood risk management in Leeds. This land use management estimate is based on generating costings utilising primary and secondary data. This research contributes findings on the costs of different adaptation measures to flood risk management in a UK city, including the trade-offs and challenges of utilising nature-based solutions. Results also explore the potential implementation of the adaptation measures in the case study and the challenges of data collection and analysis for adaptation in flood risk management.

Keywords: green infrastructure, ecosystem services, woodland, adaptation, flood risk

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Authors: C. Bejrananda, Y. Lee, T. Khamkaew

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With the rise of the importance of air transportation in the 21st century, the role of economics in airport planning and decision-making has become more important to the urban structure and land value around it. Therefore, this research aims to examine the relationship between an airport and its impacts on the distribution of urban land uses and land values by applying the Alonso’s bid rent model. The New Bangkok International Airport (Suvarnabhumi International Airport) was taken as a case study. The analysis was made over three different time periods of airport development (after the airport site was proposed, during airport construction, and after the opening of the airport). The statistical results confirm that Alonso’s model can be used to explain the impacts of the new airport only for the northeast quadrant of the airport, while proximity to the airport showed the inverse relationship with the land value of all six types of land use activities through three periods of time. It indicates that the land value for commercial land use is the most sensitive to the location of the airport or has the strongest requirement for accessibility to the airport compared to the residential and manufacturing land use. Also, the bid-rent gradients of the six types of land use activities have declined dramatically through the three time periods because of the Asian Financial Crisis in 1997. Therefore, the lesson learned from this research concerns about the reliability of the data used. The major concern involves the use of different areal units for assessing land value for different time periods between zone block (1995) and grid block (2002, 2009). As a result, this affect the investigation of the overall trends of land value assessment, which are not readily apparent. In addition, the next concern is the availability of the historical data. With the lack of collecting historical data for land value assessment by the government, some of data of land values and aerial photos are not available to cover the entire study area. Finally, the different formats of using aerial photos between hard-copy (1995) and digital photo (2002, 2009) made difficult for measuring distances. Therefore, these problems also affect the accuracy of the results of the statistical analyses.

Keywords: airport development area, economic rents, spatial pattern, suvarnabhumi international airport

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Authors: Suraj Mehrotra

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The stock market is a volatile, bustling marketplace that is a cornerstone of economics. It defines whether companies are successful or in spiral. A thorough understanding of it is important - many companies have whole divisions dedicated to analysis of both their stock and of rivaling companies. Linking the world of finance and artificial intelligence (AI), especially the stock market, has been a relatively recent development. Predicting how stocks will do considering all external factors and previous data has always been a human task. With the help of AI, however, machine learning models can help us make more complete predictions in financial trends. Taking a look at the stock market specifically, predicting the open, closing, high, and low prices for the next day is very hard to do. Machine learning makes this task a lot easier. A model that builds upon itself that takes in external factors as weights can predict trends far into the future. When used effectively, new doors can be opened up in the business and finance world, and companies can make better and more complete decisions. This paper explores the various techniques used in the prediction of stock prices, from traditional statistical methods to deep learning and neural networks based approaches, among other methods. It provides a detailed analysis of the techniques and also explores the challenges in predictive analysis. For the accuracy of the testing set, taking a look at four different models - linear regression, neural network, decision tree, and naïve Bayes - on the different stocks, Apple, Google, Tesla, Amazon, United Healthcare, Exxon Mobil, J.P. Morgan & Chase, and Johnson & Johnson, the naïve Bayes model and linear regression models worked best. For the testing set, the naïve Bayes model had the highest accuracy along with the linear regression model, followed by the neural network model and then the decision tree model. The training set had similar results except for the fact that the decision tree model was perfect with complete accuracy in its predictions, which makes sense. This means that the decision tree model likely overfitted the training set when used for the testing set.

Keywords: machine learning, testing set, artificial intelligence, stock analysis

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Authors: Masooma Al-Balushi, Tamer Mohamed Atef

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The Sultanate of Oman is located on the South-eastern tip of the Arabian Peninsula. It is bordered by the Gulf of Oman and the Arabian Sea and has borders with the United Arab Emirates, Saudi Arabia and Yemen. Arabic is the official language. Islam is the official religion. Islam has a great impact on most Omanis, Shari’a law is the law of Oman. The tribal structure plays an essential role in the lives of Omanis. Most people in the Gulf States bear a tribal name rather than a family name. Religion, tribe, and family are highly influential in shaping individuals’ values and behaviors, and have a very noticeable influence on a person’s career choices. Tourism development has been given special attention by the Sultanate of Oman’s government aspiring that the industry would assist in creating direct job opportunities as well as boost the economy through provision of hard currency to improve the balance of payments. This study aims to assess the impact of socio-cultural and religious factors on Omanis employment in the hotel sector. The socio-cultural and religious factors have serious impacts on Omani employment in the hotel sector. Some employees are concerned about the source of income because of the idea that since the hotel business is based on activities such as serving alcohol and pork, gambling, and accommodating unmarried couples, their source of income would be questionable religion wise. For females, the designated job uniform and the interaction with males are major concerns. Ability to fulfil family obligations for married Omanis, and marriage opportunity for singles were other raised concerns. Whilst the future prosperity of the hotel industry depends on the quality of its people, in Oman, the hospitality industry has failed, for a number of reasons, to project an image that could generate interest amongst Omanis. Furthermore, the characteristics and the very nature of the hotel sector are in direct conflict with Islamic doctrines which are embedded in Omani life and society.

Keywords: culture, society, hotel, hospitality, Islam, Oman

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Authors: A. Arshad, M. Lehtonen. M. Humayun

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With the increasing Distributed Generation (DG) penetration, distribution systems are advancing towards the smart grid technology for least latency in tackling voltage control problem in a distributed manner. This paper proposes a Multi-agent based distributed voltage level control. In this method a flat architecture of agents is used and agents involved in the whole controlling procedure are On Load Tap Changer Agent (OLTCA), Static VAR Compensator Agent (SVCA), and the agents associated with DGs and loads at their locations. The objectives of the proposed voltage control model are to minimize network losses and DG curtailments while maintaining voltage value within statutory limits as close as possible to the nominal. The total loss cost is the sum of network losses cost, DG curtailment costs, and voltage damage cost (which is based on penalty function implementation). The total cost is iteratively calculated for various stricter limits by plotting voltage damage cost and losses cost against varying voltage limit band. The method provides the optimal limits closer to nominal value with minimum total loss cost. In order to achieve the objective of voltage control, the whole network is divided into multiple control regions; downstream from the controlling device. The OLTCA behaves as a supervisory agent and performs all the optimizations. At first, a token is generated by OLTCA on each time step and it transfers from node to node until the node with voltage violation is detected. Upon detection of such a node, the token grants permission to Load Agent (LA) for initiation of possible remedial actions. LA will contact the respective controlling devices dependent on the vicinity of the violated node. If the violated node does not lie in the vicinity of the controller or the controlling capabilities of all the downstream control devices are at their limits then OLTC is considered as a last resort. For a realistic study, simulations are performed for a typical Finnish residential medium-voltage distribution system using Matlab ®. These simulations are executed for two cases; simple Distributed Voltage Control (DVC) and DVC with optimized loss cost (DVC + Penalty Function). A sensitivity analysis is performed based on DG penetration. The results indicate that costs of losses and DG curtailments are directly proportional to the DG penetration, while in case 2 there is a significant reduction in total loss. For lower DG penetration, losses are reduced more or less 50%, while for higher DG penetration, loss reduction is not very significant. Another observation is that the newer stricter limits calculated by cost optimization moves towards the statutory limits of ±10% of the nominal with the increasing DG penetration as for 25, 45 and 65% limits calculated are ±5, ±6.25 and 8.75% respectively. Observed results conclude that the novel voltage control algorithm proposed in case 1 is able to deal with the voltage control problem instantly but with higher losses. In contrast, case 2 make sure to reduce the network losses through proposed iterative method of loss cost optimization by OLTCA, slowly with time.

Keywords: distributed voltage control, distribution system, multi-agent systems, smart grids

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Authors: Kathleen Frances Haigh, Mieke Nieder-Heitmann, Somayeh Farzad, Mohsen Ali Mandegari, Johann Ferdinand Gorgens

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Lignocellulose can be converted to a range of biochemicals and biofuels. Where this is derived from agricultural waste, issues of competition with food are virtually eliminated. One such source of lignocellulose is the South African sugar industry. Lignocellulose could be accessed by changes to the current farming practices and investments in more efficient boilers. The South African sugar industry is struggling due to falling sugar prices and increasing costs and it is proposed that annexing a biorefinery to a sugar mill will broaden the product range and improve viability. Process simulations of the selected chemicals were generated using Aspen Plus®. It was envisaged that a biorefinery would be annexed to a typical South African sugar mill. Bagasse would be diverted from the existing boilers to the biorefinery and mixed with harvest residues. This biomass would provide the feedstock for the biorefinery and the process energy for the biorefinery and sugar mill. Thus, in all scenarios a portion of the biomass was diverted to a new efficient combined heat and power plant (CHP). The Aspen Plus® simulations provided the mass and energy balance data to carry out an economic assessment of each scenarios. The net present value (NPV), internal rate of return (IRR) and minimum selling price (MSP) was calculated for each scenario. As a starting point scenarios were generated to investigate the production of ethanol, ethanol and lactic acid, ethanol and furfural, butanol, methanol, and Fischer-Tropsch syncrude. The bypass to the CHP plant is a useful indicator of the energy demands of the chemical processes. An iterative approach was used to identify a suitable bypass because increasing this value had the combined effect of increasing the amount of energy available and reducing the capacity of the chemical plant. Bypass values ranged from 30% for syncrude production to 50% for combined ethanol and furfural production. A hurdle rate of 15.7% was selected for the IRR. The butanol, combined ethanol and furfural, or the Fischer-Tropsch syncrude scenarios are unsuitable for investment with IRRs of 4.8%, 7.5% and 11.5% respectively. This provides valuable insights into research opportunities. For example furfural from sugarcane bagasse is an established process although the integration of furfural production with ethanol is less well understood. The IRR for the ethanol scenario was 14.7%, which is below the investment criteria, but given the technological maturity it may still be considered for investment. The scenarios which met the investment criteria were the combined ethanol and lactic acid, and the methanol scenarios with IRRs of 20.5% and 16.7%, respectively. These assessments show that the production of biochemicals from lignocellulose can be commercially viable. In addition, this assessment have provided valuable insights for research to improve the commercial viability of additional chemicals and scenarios. This has led to further assessments of the production of itaconic acid, succinic acid, citric acid, xylitol, polyhydroxybutyrate, polyethylene, glucaric acid and glutamic acid.

Keywords: biorefineries, sugar mill, methanol, ethanol

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Authors: Sakinah Idris, Gabrine Jagersma, Bjorn Jaime Van Pelt, Kirstin Greaves-Lord

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Background: The PEERS (Program for the Education and Enrichment of Relational Skills) intervention can be considered a well-established, evidence-based intervention in the USA. However, testing the efficacy of cultural adaptations of PEERS is still ongoing. More and more, the involvement of all stakeholders in the development and evaluation of interventions is acknowledged as crucial for the longer term implementation of interventions across settings. Therefore, in the current project, teens with ASD (Autism Spectrum Disorder), their neurotypical peers, parents, teachers, as well as clinicians were involved in the development and evaluation of the Dutch version of PEERS. Objectives: The current presentation covers (1) the formative phase and (2) the preliminary adaptation test phase of the cultural adaptation of evidence-based interventions. In the formative phase, we aim to describe the process of adaptation of the PEERS program to the Dutch culture and care system. In the preliminary adaptation phase, we will present results from the preliminary adaptation test among 32 adolescents with ASD. Methods: In phase 1, a group discussion on common vocabulary was conducted among 70 teenagers (and their teachers) from special and regular education aged 12-18 years old. This inventory concerned 14 key constructs from PEERS, e.g., areas of interests, locations for making friends, common peer groups and crowds inside and outside of school, activities with friends, commonly used ways for electronic communication, ways for handling disagreements, and common teasing comebacks. Also, 15 clinicians were involved in the translation and cultural adaptation process. The translation and cultural adaptation process were guided by the research team, and who included input and feedback from all stakeholders through an iterative feedback incorporation procedure. In phase 2, The parent-reported Social Responsiveness Scale (SRS), the Test of Adolescent Social Skills Knowledge (TASSK), and the Quality of Socialization Questionnaire (QSQ) were assessed pre- and post-intervention to evaluate potential treatment outcome. Results: The most striking cultural adaptation - reflecting the standpoints of all stakeholders - concerned the strategies for handling rumors and gossip, which were suggested to be taught using a similar approach as the teasing comebacks, more in line with ‘down-to-earth’ Dutch standards. The preliminary testing of this adapted version indicated that the adolescents with ASD significantly improved their social knowledge (TASSK; t₃₁ = -10.9, p < .01), social experience (QSQ-Parent; t₃₁ = -4.2, p < .01 and QSQ-Adolescent; t₃₂ = -3.8, p < .01), and in parent-reported social responsiveness (SRS; t₃₃ = 3.9, p < .01). In addition, subjective evaluations of teens with ASD, their parents and clinicians were positive. Conclusions: In order to further scrutinize the effectiveness of the Dutch version of the PEERS intervention, we recommended performing a larger scale randomized control trial (RCT) design, for which we provide several methodological considerations.

Keywords: cultural adaptation, PEERS, preliminary testing, translation

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Authors: Sara Rejeb, Catherine Duveau, Tabea Rebafka

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To monitor the production process of turbofan aircraft engines, multiple measurements of various geometrical parameters are systematically recorded on manufactured parts. Engine parts are subject to extremely high standards as they can impact the performance of the engine. Therefore, it is essential to analyze these databases to better understand the influence of the different parameters on the engine's performance. Self-organizing maps are unsupervised neural networks which achieve two tasks simultaneously: they visualize high-dimensional data by projection onto a 2-dimensional map and provide clustering of the data. This technique has become very popular for data exploration since it provides easily interpretable results and a meaningful global view of the data. As such, self-organizing maps are usually applied to aircraft engine condition monitoring. As databases in this field are huge and complex, they naturally contain multiple missing entries for various reasons. The classical Kohonen algorithm to compute self-organizing maps is conceived for complete data only. A naive approach to deal with partially observed data consists in deleting items or variables with missing entries. However, this requires a sufficient number of complete individuals to be fairly representative of the population; otherwise, deletion leads to a considerable loss of information. Moreover, deletion can also induce bias in the analysis results. Alternatively, one can first apply a common imputation method to create a complete dataset and then apply the Kohonen algorithm. However, the choice of the imputation method may have a strong impact on the resulting self-organizing map. Our approach is to address simultaneously the two problems of computing a self-organizing map and imputing missing values, as these tasks are not independent. In this work, we propose an extension of self-organizing maps for partially observed data, referred to as missSOM. First, we introduce a criterion to be optimized, that aims at defining simultaneously the best self-organizing map and the best imputations for the missing entries. As such, missSOM is also an imputation method for missing values. To minimize the criterion, we propose an iterative algorithm that alternates the learning of a self-organizing map and the imputation of missing values. Moreover, we develop an accelerated version of the algorithm by entwining the iterations of the Kohonen algorithm with the updates of the imputed values. This method is efficiently implemented in R and will soon be released on CRAN. Compared to the standard Kohonen algorithm, it does not come with any additional cost in terms of computing time. Numerical experiments illustrate that missSOM performs well in terms of both clustering and imputation compared to the state of the art. In particular, it turns out that missSOM is robust to the missingness mechanism, which is in contrast to many imputation methods that are appropriate for only a single mechanism. This is an important property of missSOM as, in practice, the missingness mechanism is often unknown. An application to measurements on one type of part is also provided and shows the practical interest of missSOM.

Keywords: imputation method of missing data, partially observed data, robustness to missingness mechanism, self-organizing maps

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Authors: Thevaranchany Sivaskaran

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Women entrepreneurs are the key players in the society and their contributions is highly highlighted to enhance economic stability in the country. In Sri Lanka, especially in North and East provinces people badly affected by war. Most of them are widows and women headed families. Due to this changing environment, Educational opportunities, and the support of NGO’s Most of the women have started their business and become entrepreneurs. Even though existing family setup and social setup entrepreneurial women are overburdened and difficult to balance their business and family roles. The research has been conducted on the experiences of women entrepreneurs with the family role support and work-life balance within the small and micro- enterprise sector in Jaffna, Srilanka. This study aims to identify that what extent the role of family support will be the tool to balancing work and life effectively and, secondly, the main challenges they face in achieving work-life balance. This is done by drawing on literatures including those on work-life balance, small-and micro enterprises, and entrepreneurship theories. To find out this objective, the data were collected from 50 entrepreneurs among the members of Jaffna women chamber in each GS division basis (cluster random sampling). A qualitative methodological technique and semi-structured interviews were used to collect the data for the case study on these entrepreneurs. The results indicate that the majority of entrepreneurs do not enjoy a sense of work-life balance because most of them are women headed family and they need to work hard to generate financial profit for the benefit of family. The motivation for them to work in this way is to provide basic needs. Results confirmed for others that support of husbands is very important. Mostly, emotional support (belief and empowerment) is exposed; however, getting financial contribution seems to be highly appreciated. More responsibilities which spouses were ready to take over regarding the home responsibilities (that is, childcare) should also not be neglected in the system of support to their entrepreneurial wives. Although, more important for all, women with children appreciated other members and spouses help and assistance to a higher extent. Results showed that majority of women who started their own business feel that in the first year of ope-ration the emotional support of family members was more important.

Keywords: family support, work life balance, women entrepreneurs, Jaffna District, Sri Lanka

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Authors: Monica Gonzalez Machorro

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Dementia is hard to diagnose because of the lack of early physical symptoms. Early dementia recognition is key to improving the living condition of patients. Speech technology is considered a valuable biomarker for this challenge. Recent works have utilized conventional acoustic features and machine learning methods to detect dementia in speech. BERT-like classifiers have reported the most promising performance. One constraint, nonetheless, is that these studies are either based on human transcripts or on transcripts produced by automatic speech recognition (ASR) systems. This research contribution is to explore a method that does not require transcriptions to detect early Alzheimer’s disease (AD) and mild cognitive impairment (MCI). This is achieved by fine-tuning a pre-trained ASR model for the downstream early AD and MCI tasks. To do so, a subset of the thoroughly studied Pitt Corpus is customized. The subset is balanced for class, age, and gender. Data processing also involves cropping the samples into 10-second segments. For comparison purposes, a baseline model is defined by training and testing a Random Forest with 20 extracted acoustic features using the librosa library implemented in Python. These are: zero-crossing rate, MFCCs, spectral bandwidth, spectral centroid, root mean square, and short-time Fourier transform. The baseline model achieved a 58% accuracy. To fine-tune HuBERT as a classifier, an average pooling strategy is employed to merge the 3D representations from audio into 2D representations, and a linear layer is added. The pre-trained model used is ‘hubert-large-ls960-ft’. Empirically, the number of epochs selected is 5, and the batch size defined is 1. Experiments show that our proposed method reaches a 69% balanced accuracy. This suggests that the linguistic and speech information encoded in the self-supervised ASR-based model is able to learn acoustic cues of AD and MCI.

Keywords: automatic speech recognition, early Alzheimer’s recognition, mild cognitive impairment, speech impairment

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Authors: Mohammad Anwarul Kabir, Fayezul Islam

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Language invariably is learned / taught to be used primarily as means of communications. Teaching a language for its native audience differs from teaching it to non-native audience. Moreover, teaching a language for communication only is different from teaching it for specific purposes. Arabic language is primarily regarded as the language of the Quran and the Sunnah (Prophetic tradition). Arabic is, therefore, learnt and spread all over the globe. However, Arabic is also a cultural heritage shared by all Islamic nations which has used Arabic for a long period to record the contributions of Muslim thinkers made in the field of wide spectrum of knowledge and scholarship. That is why the phenomenon of teaching Arabic by different educational institutes became quite rife, and the idea of teaching Arabic for specific purposes is heavily discussed in the academic sphere. Although the number of learners of Arabic is increasing consistently, yet their purposes vary. These include religious purpose, international trade, diplomatic purpose, better livelihood in the Arab world extra. By virtue of this high demand for learning Arabic, numerous institutes have been established all over the world including Bangladesh. This paper aims at focusing on the current status of the language institutes which has been established for learning Arabic for specific purposes in Bangladesh including teaching methodology, curriculum, and teachers’ quality. Such curricula and using its materials resulted in a lot of problems. The least, it confused teachers and students as well. Islamic educationalists have been working hard to professionally meet the need. They are following a systematic approach of stating clear and achievable goals, building suitable content, and applying new technology to present these learning experiences and evaluate them. It also suggests a model for designing instructional systems that responds to the need of non-Arabic speaking Islamic communities and provide the knowledge needed in both linguistic and cultural aspects. It also puts forward a number of suggestions for the improvement of the teaching / learning Arabic for specific purposes in Bangladesh after a detailed investigation in the following areas: curriculum, teachers’ skills, method of teaching and assessment policy.

Keywords: communication, Quran, sunnah, educational institutes, specific purposes, curriculum, method of teaching

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