Search results for: learning text

Authors: Su-Lien Liao

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Most of college students in Taiwan do not have sufficient English proficiency to express themselves in written English. Teachers spent a lot of time correcting students’ English writing, but the results are not satisfactory. This study aims to use blogs as a teaching and learning tool in written English. Before applying peer assessment, students should be trained to be good reviewers. The teacher starts the course by posting the error analysis of students’ first English composition on blogs as the comment models for students. Then the students will go through the process of drafting, composing, peer response and last revision on blogs. Evaluation Questionnaires and interviews will be conducted at the end of the course to see the impact and students’ perception for the course.

Keywords: blog, peer assessment, English writing, error analysis

Procedia PDF Downloads 389

Authors: Mohammad K. Abedin, Mohammad Shahjahan, Zeenat Sultana, Tawfique Jahan, Jesmin Akter

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To strengthen social and behavior change communication (SBCC) capacity of Ministry of Health and Family Welfare (MoHFW) of the Government of Bangladesh, BCCP/BKMI developed two eLearning courses providing opportunities for professional development of SBCC Program Managers who have no access to training or refreshers training. The two eLearning courses – Message and Material Development (MMD) and Monitoring and Evaluation (MandE) of SBCC programs – went online in September 2015, where all users could register their participation so results could be monitored. Methodology: To assess the uses of these courses a randomly selected sample was collected to run a pre and post-test analyses and a phone survey were conducted. Systematic random sampling was used to select a sample of 75 MandE and 25 MMD course participants from a sampling frame of 179 and 51 respectively. Results: As of September 2016, more than 179 learners have completed the MandE course, and 49 learners have completed the MMD course. The users of these courses are program managers, university faculty members, and students. Encouraging results were revealed from the analysis of pre and post-test scores and a phone survey three months after course completion. Test scores suggested a substantial increase in knowledge. The pre-test scores findings suggested that about 19% learners scored high on the MandE. The post-test scores finding indicated a high score (92%) of the sample across 4 modules of MandE. For MMD course in pre-test scoring, 30% of the learners scored high, and 100% scored high at the post-test. It was found that all the learners in the phone survey have discussed the courses. Most of the sharing occurred with colleagues and friends, usually through face to face (70%) interaction. The learners reported that they did recommend the two courses to concerned people. About 67% MandE and 76% MMD learners stated that the concepts that they had to learn during the course were put into practice in their work settings. The respondents for both MandE and MMD courses have provided a valuable set of suggestions that would further strengthen the courses. Conclusions: The study showed that the initiative offered ample opportunities to build capacity in various ways in which the eLearning courses were used. It also highlighted the importance of scaling up these efforts to further strengthen the outcomes.

Keywords: e-learning course, message & material development, monitoring & evaluation, social and behavior change communication

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Authors: Kefaya Qaddoum

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The aim of this study is to predict breast cancer and to construct a supportive model that will stimulate a more reliable prediction as a factor that is fundamental for public health. In this study, we utilize general regression neural networks (GRNN) to replace the normal predictions with prediction periods to achieve a reasonable percentage of confidence. The mechanism employed here utilises a machine learning system called conformal prediction (CP), in order to assign consistent confidence measures to predictions, which are combined with GRNN. We apply the resulting algorithm to the problem of breast cancer diagnosis. The results show that the prediction constructed by this method is reasonable and could be useful in practice.

Keywords: neural network, conformal prediction, cancer classification, regression

Procedia PDF Downloads 258

Authors: Ana Maria G. Sperandio, Murilo U. Malek-Zadeh, João Luiz de S. Areas, Jussara C. Guarnieri

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Intersectoral governance is a requirement for developing healthy cities. However, this achievement is difficult to be succeeded, especially in regions at low resources condition. Therefore, it was developed a cheap investigative procedure to diagnose sectoral wishes related to urban planning and health promotion. This procedure is composed of two phases, which can be applied to different groups in order to compare the results. The first phase is a conversation guided by a list of questions. Some of those questions aim to gather information about how individuals understand concepts such as healthy city or a health promotion and what they believe that constitutes the relation between urban planning and urban health. Other questions investigate local issues, and how citizens would like to promote dialogue between sectors. At second phase individuals stand around the investigated city (or city region) map and are asked to represent their wishes on it. They can represent it by writing text notations or inserting icons on it, with the latter representing a city element, for example, some trees, a square, a playground, a hospital, a cycle track. After groups had represented their wishes, the map can be photographed, and then the results from distinct groups can be compared. This procedure was conducted at a small city in Brazil (Holambra), in 2017 which is the first out of four years of the mayor’s term. The prefecture asked for this tool in order to make Holambra become a city of Potential Healthy Municipalities Network in Brazil. Two sectors were investigated: the government and the urban population. By the end of our investigation, the intersection from the group (i.e., population and government) maps was accounted for creating a map of common wishes. Therefore, the material produced can be used as a guide for promoting dialogue between sectors and as a tool of monitoring politics progress. The report of this procedure was directed to public managers, so they could see the common wishes between themselves and local populations, and use this tool as a guide for creating urban politics which intends to enhance health promotion and to develop a healthy city, even at low resources condition.

Keywords: governance, health promotion, intersectorality, urban planning

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Authors: Pedro Barros, Ana Breda, Eugenio Rocha, M. Isabel Santos

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As visual and spatial awareness develops, children apprehension of the concept of direction, (relative) distance and (relative) location materializes. Here we present the educational inclusive digital game ORIESPA, under development by the Thematic Line Geometrix, for children aged between 6 and 10 years old, aiming the improvement of their visual and spatial awareness. Visual-spatial abilities are of crucial importance to succeed in many everyday life tasks. Unavoidable in the technological age we are living in, they are essential in many fields of study as, for instance, mathematics.The game, set on a 2D/3D environment, focusses in tasks/challenges on the following categories (1) static orientation of the subject and object, requiring an understanding of the notions of up–down, left–right, front–back, higher-lower or nearer-farther; (2) interpretation of perspectives of three-dimensional objects, requiring the understanding of 2D and 3D representations of three-dimensional objects; and (3) orientation of the subject in real space, requiring the reading and interpreting of itineraries. In ORIESPA, simpler tasks are based on a quadrangular grid, where the front-back and left-right directions and the rotations of 90º, 180º and 270º play the main requirements. The more complex ones are produced on a cubic grid adding the up and down movements. In the first levels, the game's mechanics regarding the reading and interpreting maps (from point A to point B) is based on map routes, following a given set of instructions. In higher levels, the player must produce a list of instructions taking the game character to the desired destination, avoiding obstacles. Being an inclusive game the user has the possibility to interact through the mouse (point and click with a single button), the keyboard (small set of well recognized keys) or a Kinect device (using simple gesture moves). The character control requires the action on buttons corresponding to movements in 2D and 3D environments. Buttons and instructions are also complemented with text, sound and sign language.

Keywords: digital game, inclusion, itinerary, spatial ability

Procedia PDF Downloads 155

Authors: Jessica Gu, Yu Chen

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Knowledge Management (KM) is undoubtable crucial to organizational value creation, learning, and adaptation. Although the rapidly growing KM domain has been fueled with full-fledged methodologies and technologies, studies on KM evolution that bridge the organizational performance and adaptation to the organizational environment are still rarely attempted. In particular, creation (or generation) and diffusion (or share/exchange) of knowledge are of the organizational primary concerns on the problem-solving perspective, however, the optimized distribution of knowledge creation and diffusion endeavors are still unknown to knowledge workers. This research proposed an agent-based model of knowledge creation and diffusion in an organization, aiming at elucidating how the intertwining knowledge flows at microscopic level lead to optimized organizational performance at macroscopic level through evolution, and exploring what exogenous interventions by the policy maker and endogenous adjustments of the knowledge workers can better cope with different environmental conditions. With the developed model, a series of simulation experiments are conducted. Both long-term steady-state and time-dependent developmental results on organizational performance, network and structure, social interaction and learning among individuals, knowledge audit and stocktaking, and the likelihood of choosing knowledge creation and diffusion by the knowledge workers are obtained. One of the interesting findings reveals a non-monotonic phenomenon on organizational performance under turbulent environment while a monotonic phenomenon on organizational performance under a stable environment. Hence, whether the environmental condition is turbulence or stable, the most suitable exogenous KM policy and endogenous knowledge creation and diffusion choice adjustments can be identified for achieving the optimized organizational performance. Additional influential variables are further discussed and future work directions are finally elaborated. The proposed agent-based model generates evidence on how knowledge worker strategically allocates efforts on knowledge creation and diffusion, how the bottom-up interactions among individuals lead to emerged structure and optimized performance, and how environmental conditions bring in challenges to the organization system. Meanwhile, it serves as a roadmap and offers great macro and long-term insights to policy makers without interrupting the real organizational operation, sacrificing huge overhead cost, or introducing undesired panic to employees.

Keywords: knowledge creation, knowledge diffusion, agent-based modeling, organizational performance, decision making evolution

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Authors: Amir Reza Asnafi, Masoumeh Kazemizadeh, Najmeh Salemi

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Due to the diversity of information resources in the web0.2 environment, which is increasing in number from time to time, the social tagging system should be used to discuss Internet resources. Studying the relevance of social tags to thematic headings can help enrich resources and make them more accessible to resources. The present research is of applied-theoretical type and research method of content analysis. In this study, using the listing method and content analysis, the level of accurate, approximate, relative, and non-conformity of social labels of books available in the field of information science and bibliography of Kitabrah website with Persian subject headings was determined. The exact matching of subject headings with social tags averaged 22 items, the approximate matching of subject headings with social tags averaged 36 items, the relative matching of thematic headings with social tags averaged 36 social items, and the average matching titles did not match the title. The average is 116. According to the findings, the exact matching of subject headings with social labels is the lowest and the most inconsistent. This study showed that the average non-compliance of subject headings with social labels is even higher than the sum of the three types of exact, relative, and approximate matching. As a result, the relevance of thematic titles to social labels is low. Due to the fact that the subject headings are in the form of static text and users are not allowed to interact and insert new selected words and topics, and on the other hand, in websites based on Web 2 and based on the social classification system, this possibility is available for users. An important point of the present study and the studies that have matched the syntactic and semantic matching of social labels with thematic headings is that the degree of conformity of thematic headings with social labels is low. Therefore, these two methods can complement each other and create a hybrid cataloging that includes subject headings and social tags. The low level of conformity of thematic headings with social tags confirms the results of backgrounds and writings that have compared the social tags of books with the thematic headings of the Library of Congress. It is not enough to match social labels with thematic headings. It can be said that these two methods can be complementary.

Keywords: Web 2/0, social tags, subject headings, hybrid cataloging

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Authors: Mansoureh Ghiasabadi Farahani, Samira Kalantary, Sara Taghi-Pour, Mahboubeh Shamsi

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Nowadays, the development of computers technology and its recent applications provide access to new types of data, which have not been considered by the traditional data analysts. Two particularly interesting characteristics of such data sets include their huge size and streaming nature .Incremental learning techniques have been used extensively to address the data stream classification problem. This paper presents a concise survey on the obstacles and the requirements issues classifying data streams with using decision tree. The most important issue is to maintain a balance between accuracy and efficiency, the algorithm should provide good classification performance with a reasonable time response.

Keywords: big data, data streams, classification, decision tree

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Authors: Makinde David Olajide

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Proverb is an important aspect of most indigenous culture in Africa including that of the Yoruba people of southwestern Nigeria. As revealed by recent studies, Yoruba proverbs as an important cultural heritage are threatened and near extinct. This fear of proverb extinct in Yoruba cultural growth has been observed and expressed at different fora by many researchers and professionals including Art historians, culture patrons, social critics’ and teachers among others. Investigation revealed that the intangible nature of proverb is largely responsible for its continuous disappearance in the language structure and creative speeches which give the unique identity to the Yoruba people. Some of the factors that are responsible for culture extinct include: absence of moonlight stories by the elderly, the nuclear family system, and total assimilation of western culture, the concept of modernity and urban nature of Yoruba towns among others. Therefore, to preserve this creative heritage (proverb), there is need for a conscious shift of the traditional role of proverbs in speech development to its use as tool for artistic creations and expressions in visual form. The study was carried out between June, 2013 and February, 2015 in three Yoruba towns; Ilorin, Ede and Ogbomoso selected from Kwara, Osun and Oyo states respectively. The data used in this study were collected through oral and structured interviews. Fifteen interviewers were purposively selected in each of the study areas. It also employs the use of electronic and printed media to generate relevant literature on the subject matter. The study revealed that many Yoruba proverbs are preserved or hidden in text books, monograph, home videos, films and pastoral messages. However, this has not stopped the problem of lack of understanding of its usage, meaning and reasons for its extinction that may hinder its preservation for the incoming generations. This study concludes that indigenous culture can be revived and preserved for future generations when there is a conscious attempt to integrate or convert their traditional roles for present day realities and relevance in our social and educational needs.

Keywords: culture, assimilation, extinct, heritage, preservation

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Authors: Saimir Heta, Kers Kapaj, Rialda Xhizdari, Ilma Robo

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Despite the existence of different dental specialties, the dentist-patient relationship is unique, in the very fact that the treatment is performed by one doctor and the patient identifies the malpractice presented as part of that doctor's practice; this is in complete contrast to cases of medical treatments where the patient can be presented to a team of doctors, to treat a specific pathology. The rules of dental ethics are almost the same as the rules of medical ethics. The appearance of dental malpractice affects exactly this two-party relationship, created on the basis of professionalism, without deviations in this direction, between the dentist and the patient, but with very narrow individual boundaries, compared to cases of medical malpractice. Main text: Malpractice can have different reasons for its appearance, starting from professional negligence, but also from the lack of professional knowledge of the dentist who undertakes the dental treatment. It should always be seen in perspective that we are not talking about the individual - the dentist who goes to work with the intention of harming their patients. Malpractice can also be a consequence of the impossibility, for anatomical or physiological reasons of the tooth under dental treatment, to realize the predetermined dental treatment plan. On the other hand, the dentist himself is an individual who can be affected by health conditions, or have vices that affect the systemic health of the dentist as an individual, which in these conditions can cause malpractice. So, depending on the reason that led to the appearance of malpractice, the method of treatment from a legal point of view also varies, for the dentist who committed the malpractice, evaluating the latter if the malpractice came under the conditions of applying the rules of dental ethics. Conclusions: The deviation from the predetermined dental plan is the minimum sign of malpractice and the latter should not be definitively related only to cases of difficult dental treatments. The identification of the reason for the appearance of malpractice is the initial element, which makes the difference in the way of its treatment, from a legal point of view, and the involvement of the dentist in the assessment of the malpractice committed, must be based on the legislation in force, which must be said to have their specific changes in different states. Malpractice should be referred to, or included in the lectures or in the continuing education of professionals, because it serves as a method of obtaining professional experience in order not to repeat the same thing several times, by different professionals.

Keywords: dental ethics, malpractice, negligence, legal basis, continuing education, dental treatments

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Authors: Gohar Marikyan

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This article is about investigating how to effectively use visuals in teaching introductory mathematics. The analysis showed the use of visuals in teaching introductory mathematics can be an effective tool for enhancing students’ learning and engagement in mathematics. The use of visuals was particularly effective for teaching concepts of numbers, operations with whole numbers, and properties of operations. The analysis also provides strong evidence that the effectiveness of visuals varied depending on the way the visuals are used. Furthermore, the analysis revealed that the use of visuals in mathematics instruction had a positive impact on student’s attitudes toward mathematics, with students showing higher levels of motivation and enjoyment in mathematics classes.

Keywords: analytical thinking skills, instructional strategies with visuals, introductory mathematics, student engagement and motivation

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Authors: Khadija Refouh

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Culture bound-expressions have been a bottleneck for Natural Language Processing (NLP) and comprehension, especially in the case of machine translation (MT). In the last decade, the field of machine translation has greatly advanced. Neural machine translation NMT has recently achieved considerable development in the quality of translation that outperformed previous traditional translation systems in many language pairs. Neural machine translation NMT is an Artificial Intelligence AI and deep neural networks applied to language processing. Despite this development, there remain some serious challenges that face neural machine translation NMT when translating culture bounded-expressions, especially for low resources language pairs such as Arabic-English and Arabic-French, which is not the case with well-established language pairs such as English-French. Machine translation of opaque idioms from English into French are likely to be more accurate than translating them from English into Arabic. For example, Google Translate Application translated the sentence “What a bad weather! It runs cats and dogs.” to “يا له من طقس سيء! تمطر القطط والكلاب” into the target language Arabic which is an inaccurate literal translation. The translation of the same sentence into the target language French was “Quel mauvais temps! Il pleut des cordes.” where Google Translate Application used the accurate French corresponding idioms. This paper aims to perform NMT experiments towards better translation of opaque idioms using high quality clean multilingual corpus. This Corpus will be collected analytically from human generated idiom translation. AutoML translation, a Google Neural Machine Translation Platform, is used as a custom translation model to improve the translation of opaque idioms. The automatic evaluation of the custom model will be compared to the Google NMT using Bilingual Evaluation Understudy Score BLEU. BLEU is an algorithm for evaluating the quality of text which has been machine-translated from one natural language to another. Human evaluation is integrated to test the reliability of the Blue Score. The researcher will examine syntactical, lexical, and semantic features using Halliday's functional theory.

Keywords: multilingual corpora, natural language processing (NLP), neural machine translation (NMT), opaque idioms

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Authors: Lamia Emam

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The attractiveness of entrepreneurship education stems from its perceived value as a venue through which students can develop an entrepreneurial mindset, skill set, and practice, which may not necessarily lead to them starting a new business, but could, more importantly, be manifested as a life skill that could be applied to all types of organizations and career endeavors. This, in turn, raises important questions about what happens in our classrooms; our role as educators, the role of students, center of learning, and the instructional approach; all of which eventually contribute to achieving the desired EE outcomes. With application to an undergraduate entrepreneurship course -Entrepreneurship as Practice- the current paper aims to explore the effect of entrepreneurship education on the development of students’ general entrepreneurial tendencies. Towards that purpose, the researcher herein uses a pre-test and post-test quasi-experimental research design where the Durham University General Enterprising Tendency Test (GET2) is administered to the same group of students before and after course delivery. As designed and delivered, the Entrepreneurship as Practice module is a highly applied and experiential course where students are required to develop an idea for a start-up while practicing the entrepreneurship-related knowledge, mindset, and skills that are taught in class, both individually and in groups. The course is delivered using a combination of short lectures, readings, group discussions, case analysis, guest speakers, and, more importantly, actively engaging in a series of activities that are inspired by diverse methods for developing successful and innovative business ideas, including design thinking, lean-start up and business feasibility analysis. The instructional approach of the course particularly aims at developing the students' critical thinking, reflective, analytical, and creativity-based problem-solving skills that are needed to launch one’s own start-up. The analysis and interpretation of the experiment’s outcomes shall simultaneously incorporate the views of both the educator and students. As presented, the study responds to the rising call for the application of experimental designs in entrepreneurship in general and EE in particular. While doing so, the paper presents an educator’s perspective of EE to complement the dominant stream of research which is constrained to the students’ point of view. Finally, the study sheds light on EE in the MENA region, where the study is applied.

Keywords: entrepreneurship education, andragogy and heutagogy, scholarship of teaching and learning, experiment

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Authors: Utkarsh A. Mishra, Ankit Bansal

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At high temperature, radiative heat transfer is the dominant mode of heat transfer. It is governed by various phenomena such as photon emission, absorption, and scattering. The solution of the governing integrodifferential equation of radiative transfer is a complex process, more when the effect of participating medium and wavelength properties are taken into consideration. Although a generic formulation of such radiative transport problem can be modeled for a wide variety of problems with non-gray, non-diffusive surfaces, there is always a trade-off between simplicity and accuracy of the problem. Recently, solutions of complicated mathematical problems with statistical methods based on randomization of naturally occurring phenomena have gained significant importance. Photon bundles with discrete energy can be replicated with random numbers describing the emission, absorption, and scattering processes. Photon Monte Carlo (PMC) is a simple, yet powerful technique, to solve radiative transfer problems in complicated geometries with arbitrary participating medium. The method, on the one hand, increases the accuracy of estimation, and on the other hand, increases the computational cost. The participating media -generally a gas, such as CO₂, CO, and H₂O- present complex emission and absorption spectra. To model the emission/absorption accurately with random numbers requires a weighted sampling as different sections of the spectrum carries different importance. Importance sampling (IS) was implemented to sample random photon of arbitrary wavelength, and the sampled data provided unbiased training of MC estimators for better results. A better replacement to uniform random numbers is using deterministic, quasi-random sequences. Halton, Sobol, and Faure Low-Discrepancy Sequences are used in this study. They possess better space-filling performance than the uniform random number generator and gives rise to a low variance, stable Quasi-Monte Carlo (QMC) estimators with faster convergence. An optimal supervised learning scheme was further considered to reduce the computation costs of the PMC simulation. A one-dimensional plane-parallel slab problem with participating media was formulated. The history of some randomly sampled photon bundles is recorded to train an Artificial Neural Network (ANN), back-propagation model. The flux was calculated using the standard quasi PMC and was considered to be the training target. Results obtained with the proposed model for the one-dimensional problem are compared with the exact analytical and PMC model with the Line by Line (LBL) spectral model. The approximate variance obtained was around 3.14%. Results were analyzed with respect to time and the total flux in both cases. A significant reduction in variance as well a faster rate of convergence was observed in the case of the QMC method over the standard PMC method. However, the results obtained with the ANN method resulted in greater variance (around 25-28%) as compared to the other cases. There is a great scope of machine learning models to help in further reduction of computation cost once trained successfully. Multiple ways of selecting the input data as well as various architectures will be tried such that the concerned environment can be fully addressed to the ANN model. Better results can be achieved in this unexplored domain.

Keywords: radiative heat transfer, Monte Carlo Method, pseudo-random numbers, low discrepancy sequences, artificial neural networks

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Authors: Katherine van Kampen, Reva Qiu, Patricia Farrugia

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Orthopedic surgery has fallen behind when it comes to gender diversity despite medical school classes reaching gender parity. Studies have shown that orthopedic surgery would require 117 years to reach gender parity with the trainee population, the longest time than any other specialty, including neurosurgery, urology, and otolaryngology. The barriers that face women in orthopedic surgery have been well researched, with contributing factors being on-going stereotypes of the field, lack of women mentors, and gender roles outside of the hospital. Furthermore, women in orthopedic surgery face barriers to achieve promotion, publications, and leadership roles leading to a “leaky pipeline,” resulting in less and less women in key academic roles in the field. It is a complex topic with barriers and challenges faced in medical school, residency, and throughout employment. Our scoping review seeks to understand these challenges across a temporal timeline and to further characterize such barriers and the driving factors behind them. To this date, authors did not find a scoping review that seeks to look broadly at factors impacting the decreased amount of women entering orthopedics and the factors that cause women to hit a “glass ceiling”, the idea that women will not achieve the same success as men despite the same qualifications, upon entering the field. This scoping review is the first of its kind to attempt to summarize the large body of research focusing on women in orthopedic surgery from the preconceptions in medical school impacting their desire to pursue orthopedics all the way to employment, including challenges to academic success and financial success. Literature databases will be searched with the following key terms: women, gender inequity, workforce, orthopedics, and citations will be hand searched and collected. Articles included will discuss gender inequality within orthopedics with non-english, patient related articles excluded. Full-text review will seek to characterize the specific barriers faced by women across medical school, residency, and employment. Themes that are expected to be highlighted are workforce data, women in orthopedic leadership, medical student perspectives on the specialty, and gender bias and discrimination in the field.

Keywords: orthopedics, gender equity, workforce, women in surgery

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Authors: Florentina Hahaianu, Mihaela Negrescu

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The analysis of the positive and negative effects of technology use and abuse in Generation Z comes as a necessity in order to understand their ever-changing emotional development needs. The article quantitatively analyzes the findings of a sociological questionnaire on a group of students in social sciences. It aimed to identify the changes generated by the use of digital resources in the emotional intelligence development. Among the outcomes of our study we include a predilection for IT related activities – be they social, learning, entertainment, etc. which undermines the manifestation of emotional intelligence, especially the reluctance to face-to-face interaction. In this context, the issue of emotional intelligence development comes into focus as a solution to compensate for the undesirable effects that contact with technology has on this generation.

Keywords: digital resources, emotional intelligence, generation Z, students

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Authors: Ahmet Faruk Akyuz, Hasan Sakir Bilge

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Depth estimation using stereo images is a challenging problem in computer vision. Many different studies have been carried out to solve this problem. With advancing machine learning, tackling this problem is often done with neural network-based solutions. The images used in these studies are mostly in the visible spectrum. However, the need to use the Infrared (IR) spectrum for depth estimation has emerged because it gives better results than visible spectra in some conditions. At this point, we recommend using thermal-thermal (IR) image pairs for depth estimation. In this study, we used two well-known networks (PSMNet, FADNet) with minor modifications to demonstrate the viability of this idea.

Keywords: thermal stereo matching, deep neural networks, CNN, Depth estimation

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Authors: Nadwah Onwi, Puspa Maniam, Azmawanie A. Aziz, Fairus Mukhtar, Nor Azrita Mohamed Zin, Nurul Haslina Mohd Zin, Nurul Fatehah Ismail, Mohamad Safwan Yusoff, Susilidianamanalu Abd Rahman, Siti Munirah Harris, Maryam Aizuddin

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Objective: Malaysia has a growing number of individuals with complex communication needs (CCN). The initiation of augmentative and alternative communication (AAC) intervention may facilitate individuals with CCN to understand and express themselves optimally and actively participate in activities in their daily life. AAC is defined as multimodal use of communication ability to allow individuals to use every mode possible to communicate with others using a set of symbols or systems that may include the symbols, aids, techniques, and strategies. It is consequently critical to evaluate the deficits to inform treatment for AAC intervention. However, no known measurement tools are available to evaluate the user with CCN available locally. Design: A systematic review (SR) is designed to analyze the psychometric properties of AAC assessment for adolescents with CCN published in peer-reviewed journals. Tools are rated by the methodological quality of studies and the psychometric measurement qualities of each tool. Method: A literature search identifying AAC assessment tools with psychometrically robust properties and conceptual framework was considered. Two independent reviewers screened the abstracts and full-text articles and review bibliographies for further references. Data were extracted using standardized forms and study risk of bias was assessed. Result: The review highlights the psychometric properties of AAC assessment tools that can be used by speech-language therapists applicable to be used in the Malaysian context. The work outlines how systematic review methods may be applied to the consideration of published material that provides valuable data to initiate the development of Malay Language AAC assessment tools. Conclusion: The synthesis of evidence has provided a framework for Malaysia Speech-Language therapists in making an informed decision for AAC intervention in our standard operating procedure in the Ministry of Health, Malaysia.

Keywords: augmentative and alternative communication, assessment, adolescents, complex communication needs

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Authors: Wendy de Gomez

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Standardization is a critical element in the ability of a society to reduce uncertainty, subjectivity, misrepresentation, and interpretation while simultaneously contributing to innovation. Technological standardization is critical to codify specific operationalization through legal instruments that provide rules of development, expectation, and use. In the current emerging technology landscape Artificial Intelligence (AI) hardware as a general use technology has seen incredible growth as evidenced from AI technology patents between 2012 and 2018 in the United States Patent Trademark Office (USPTO) AI dataset. However, as outlined in the 2023 United States Government National Standards Strategy for Critical and Emerging Technology the codification through standardization of emerging technologies such as AI has not kept pace with its actual technological proliferation. This gap has the potential to cause significant divergent possibilities for the downstream outcomes of AI in both the short and long term. This original empirical research provides an overview of the standardization efforts around AI in different geographies and provides a background to standardization law. It quantifies the longitudinal trend of Artificial Intelligence hardware patents through the USPTO AI dataset. It seeks evidence of existing Standard Essential Patents from these AI hardware patents through a text analysis of the Statement of patent history and the Field of the invention of these patents in Patent Vector and examines their determination as a Standard Essential Patent and their inclusion in existing AI technology standards across the four main AI standards bodies- European Telecommunications Standards Institute (ETSI); International Telecommunication Union (ITU)/ Telecommunication Standardization Sector (-T); Institute of Electrical and Electronics Engineers (IEEE); and the International Organization for Standardization (ISO). Once the analysis is complete the paper will discuss both the theoretical and operational implications of F/Rand Licensing Agreements for the owners of these Standard Essential Patents in the United States Court and Administrative system. It will conclude with an evaluation of how Standard Setting Organizations (SSOs) can work with SEP owners more effectively through various forms of Intellectual Property mechanisms such as patent pools.

Keywords: patents, artifical intelligence, standards, F/Rand agreements

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Authors: Gwendolyn Royal-Smith

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Cocaine ranks as one of the world’s most addictive and commonly abused stimulant drugs. Recent evidence indicates that the abuse of cocaine has risen so quickly among females that this group now accounts for about 40 percent of all users in the United States. Neuropsychological studies have demonstrated that specific neural activation patterns carry higher risks for neurocognitive and executive function in cocaine addicted females thereby increasing their vulnerability for poorer treatment outcomes and more frequent post-treatment relapse when compared to males. This study examined secondary data with a convenience sample of 164 cocaine addicted male and females to assess neurocognitive and executive function. The principal objective of this study was to assess whether individual performance on the Stroop Word Color Task is predictive of treatment success by gender. A second objective of the study evaluated whether individual performance employing neurocognitive measures including the Stroop Word-Color task, the Rey Auditory Verbal Learning Test (RALVT), the Iowa Gambling Task, the Wisconsin Card Sorting Task (WISCT), the total score from the Barratte Impulsiveness Scale (Version 11) (BIS-11) and the total score from the Frontal Systems Behavioral Scale (FrSBE) test demonstrated differences in neurocognitive and executive function performance by gender. Logistic regression models were employed utilizing a covariate adjusted model application. Initial analyses of the Stroop Word color tasks indicated significant differences in the performance of males and females, with females experiencing more challenges in derived interference reaction time and associate recall ability. In early testing including the Rey Auditory Verbal Learning Test (RALVT), the number of advantageous vs disadvantageous cards from the Iowa Gambling Task, the number of perseverance errors from the Wisconsin Card Sorting Task (WISCT), the total score from the Barratte Impulsiveness Scale (Version 11) (BIS-11) and the total score from the Frontal Systems Behavioral Scale, results were mixed with women scoring lower in multiple indicators in both neurocognitive and executive function.

Keywords: cocaine addiction, gender, neuropsychology, neurocognitive, executive function

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Authors: Yiqiao Yin

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Many scholars and educators have dedicated their lives in K12 education system and there has been an exploding amount of attention to implement technical foundations for Artificial Intelligence Education for high school and precollege level students. This paper focuses on the development and use of resources to support K-12 education in Artificial Intelligence (AI). The author and his team have more than three years of experience coaching students from pre-college level age from 15 to 18. This paper is a culmination of the experience and proposed online tools, software demos, and structured activities for high school students. The paper also addresses a portfolio of AI concepts as well as the expected learning outcomes. All resources are provided with online videos and Github repositories for immediate use.

Keywords: K12 education, AI4ALL, pre-college education, pre-college AI

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Authors: Alemu Moges Belay, Torgeir Welo, Jan Ola Strandhagen

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Lean has long been linked with manufacturing, but its application claimed also by other functions such as product development and services. However, there is a challenge on understanding and defining lean in each function context. This paper aims to investigate the literature that focus mainly on PD process improvement, obtain better understanding and redefine LPD in systematic way. In addition to that, the paper attempts to summarize various proposed transformation strategies, definitions, identifying features of manufacturing and product development that would help to redefining lean in product development context. Finally we redefine LPD in organized way that encompasses different steps such as stage gate, communication and information, events, learning, innovation, knowledge and value creation.

Keywords: lean, lean manufacturing, lean product development, transformation, strategies

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Authors: Oluwasina Folajinmi, Kate Ssamulla, Penninah Lutung, Daniel Reijer

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Background: Despite of well-verified benefits of anti-retroviral therapy (ART) in prolonging life expectancy being lost to follow-up (LTFU) presents a challenge to the success of ART programs in resource limited countries like Nigeria. In several studies of ART programs in developing countries, researchers have reported that there has been a high rate of LTFU among patients receiving care and treatment at ART treatment centers. This study seeks to determine the cause of LTFU among HIV clients. Method: A descriptive cross sectional study focused on a population of 9,280 persons living with HIV/AIDS who were enrolled in nine treatment centers in Nigeria (both pre-ART and ART patients were included). Out of the total population, 1752 (18.9%) were found to be LTFU. Of this group we randomly selected 1200 clients (68.5%) their d patients’ information was generated through a database. Data on demographics and CD4 counts, causes of LTFU were analyzed and summarized. Results: Out of 1200 LTFU clients selected, 462 (38.5%) were on ART; 341 clients (73.8%) had CD4 level < 500cell/µL and 738 (61.5%) on pre-ART had CD4 level >500/µL. In our records we found telephone number for 675 (56.1%) of these clients. 675 (56.1%) were owners of a phone. The majority of the client’s 731 (60.9%) were living at not more than 25km away from the ART center. A majority were females (926 or 77.2%) while 274 (22.8%) were male. 675 (56.1%) clients were reported traced via telephone and home address. 326 (27.2%) of clients phone numbers were not reachable; 173 (14.4%) of telephone numbers were incomplete. 71 (5.9%) had relocated due to communal crises and expert client trackers reported that some patient could not afford transportation to ART centers. Conclusion: This study shows that, low health education levels, poverty, relocations and lack of reliable phone contact were major predictors of LTFU. Periodic updates of home addresses, telephone contacts including at least two next of kin, phone text messages and home visits may improve follow up. Early and consistent tracking of missed appointments is crucial. Creation of more ART decentralized centres are needed to avoid long distances.

Keywords: anti-retroviral therapy, HIV/AIDS, predictors, lost to follow up

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Authors: Lubisi L. V., Madumo M. B., Mudau N. P., Makhuvele L., Sibuyi M. M.

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Background and Aims: Learners with disabilities can be integrated into mainstream schools, whereas there are those learners that are accommodated in special schools based on the support needs they require. These needs, among others, pertain to access to high-intensity therapeutic support by physiotherapists, occupational therapists, and speech therapists. However, access to physiotherapists in low- and middle-income countries is limited, and this creates a knowledge gap in identifying, to the best of our knowledge, best practice patterns aligned with physiotherapy at special schools. This gap compromises the quality of support to be rendered towards strengthening rehabilitation and optimising the participation of learners with disabilities in special schools. The aim of the scoping review was to map the evidence on practice patterns employed by physiotherapists at special schools for learners with disabilities. Methods: The Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines were followed. Key terms regarding physiotherapy practice patterns for learners with disabilities at special schools were used to search the literature on the databases. Literature was sourced from Google Scholar, EBSCO, PEDro, PubMed, and Research Gate from 2013 to 2023. A total of 28 articles were initially retrieved and after a process of screening and exclusion, nine articles were included. All the researchers reviewed the articles for eligibility. Articles were initially screened based on the titles, followed by full text. Articles written in English or translated into English mentioned physical / physiotherapy interventions in special schools, both published and unpublished, were included. A qualitative data extraction template was developed and an inductive approach to thematic data analysis was used for included articles to see which themes emerged. Results: Three themes emerged after inductive thematic data analysis. 1. Collaboration with educators, parents, and therapists 2. Family Centred Approach 3. Telehealth. Conclusion: Collaboration is key in delivering therapeutic support to learners with disabilities at special schools. Physiotherapists need to be collaborators at the level of interprofessional and transprofessional. In addition, they need to explore technology to work remotely, especially when learners become absent physically from school.

Keywords: learners with disabilities, special school, physiotherapists, therapeutic support

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Authors: Jae Ni Jang, Young Uk Kim

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Background: Chat Generative Pre-training Transformer-3 (ChatGPT; San Francisco, California, Open Artificial Intelligence) is an artificial intelligence chatbot based on a large language model designed to generate human-like text. As the usage of ChatGPT is increasing among less knowledgeable patients, medical students, and anesthesia and pain medicine residents or trainees, we aimed to evaluate the accuracy of ChatGPT-3 responses to questions about the American Society of Anesthesiologists (ASA) classification based on patients’ underlying diseases and assess the quality of the generated responses. Methods: A total of 47 questions were submitted to ChatGPT using textual prompts. The questions were designed for ChatGPT-3 to provide answers regarding ASA classification in response to common underlying diseases frequently observed in adult patients. In addition, we created 18 questions regarding the ASA classification for pediatric patients and pregnant women. The accuracy of ChatGPT’s responses was evaluated by cross-referencing with Miller’s Anesthesia, Morgan & Mikhail’s Clinical Anesthesiology, and the American Society of Anesthesiologists’ ASA Physical Status Classification System (2020). Results: Out of the 47 questions pertaining to adults, ChatGPT -3 provided correct answers for only 23, resulting in an accuracy rate of 48.9%. Furthermore, the responses provided by ChatGPT-3 regarding children and pregnant women were mostly inaccurate, as indicated by a 28% accuracy rate (5 out of 18). Conclusions: ChatGPT provided correct responses to questions relevant to the daily clinical routine of anesthesiologists in approximately half of the cases, while the remaining responses contained errors. Therefore, caution is advised when using ChatGPT to retrieve anesthesia-related information. Although ChatGPT may not yet be suitable for clinical settings, we anticipate significant improvements in ChatGPT and other large language models in the near future. Regular assessments of ChatGPT's ASA classification accuracy are essential due to the evolving nature of ChatGPT as an artificial intelligence entity. This is especially important because ChatGPT has a clinically unacceptable rate of error and hallucination, particularly in pediatric patients and pregnant women. The methodology established in this study may be used to continue evaluating ChatGPT.

Keywords: American Society of Anesthesiologists, artificial intelligence, Chat Generative Pre-training Transformer-3, ChatGPT

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Authors: Edward Shizha, Edward Makwarimba

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This literature review explores current research on the educational strengths and barriers of newcomer and refugee youth in Canada. Canada’s shift in immigration policy in the past three decades, from Europe to Asian and African countries as source continents of recent immigrants to Canada, has tremendously increased the ethnic, linguistic, cultural and religious diversity of the population, including that of students in its education system. Over 18% of the country’s population was born in another country, of which 70% are visible minorities. There has been an increase in admitted immigrants and refugees, with a total of 226,203 between July 2020 and June 2021. Newcomer parents and their children in all major destination countries, including Canada, face tremendous challenges, including racism and discrimination, lack of English language skills, poverty, income inequality, unemployment, and underemployment. They face additional challenges, including discrimination against those who cannot speak the official languages, English or French. The severity of the challenges depends on several intersectional factors, including immigrant status (asylum seeker, refugee, or immigrant), age, gender, level of education and others. Through the lens of intersectionality as an explanatory perspective, this literature review examines the educational attainment and outcomes of newcomer and refugee youth in Canada in order to understand their educational needs, educational barriers and strengths. Newcomer youths’ experiences are shaped by numerous intersectional and interconnected sociocultural, sociopolitical, and socioeconomic factors—including gender, migration status, racialized status, ethnicity, socioeconomic class, sexual minority status, age, race—that produce and perpetuate their disadvantage. According to research, immigrants and refugees from visible minority ethnic backgrounds experience exclusions more than newcomers from other backgrounds and groups from the mainstream population. For many immigrant parents, migration provides financial and educational opportunities for their children. Yet, when attending school, newcomer and refugee youth face unique challenges related to racism and discrimination, negative attitudes and stereotypes from teachers and other school authorities, language learning and proficiency, differing levels of acculturation, and different cultural views of the role of parents in relation to teachers and school, and unfamiliarity with the social or school context in Canada. Recognizing discrepancies in educational attainment of newcomer and refugee youth based on their race and immigrant status, the paper develops insights into existing research and data gaps related to educational strengths and challenges for visible minority newcomer youth in Canada. The paper concludes that the educational successes or failures of the newcomer and refugee youth and their settlement and integration into the school system in Canada may depend on where their families settle, the attitudes of the host community and the school officials (teachers, guidance counsellors and school administrators) after-school support programs and their own set of coping mechanisms. Conceivably a unique approach to after-school programming should provide learning supports and opportunities that consider newcomer and refugee youth’s needs, experiences, backgrounds and circumstances. This support is likely to translate into significant academic and psychological well-being of newcomer students.

Keywords: deficit discourse, discrimination, educational outcomes, newcomer and refugee youth, racism, strength-based approach, whiteness

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Authors: Leijun Zhang

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Reading literacy has become a powerful tool for academic success and an essential goal of education. The ability to read is not only fundamental for pupils’ academic success but also a prerequisite for successful participation in today’s vastly expanding multi-literate textual environment. It is also important to recognize that, in many educational settings, students are expected to learn a foreign/second language for successful participation in the increasingly globalized world. Therefore, it is crucial to help learners become skilled foreign-language readers. Research indicates that students’ reading comprehension can be significantly improved through explicit instruction of multiple reading strategies. Despite the wealth of research on how to enhance learners’ reading comprehension achievement by identifying an enormous range of reading strategies and techniques for assisting students in comprehending specific texts, relatively scattered studies have centered on whether these reading comprehension strategies and techniques are used in classrooms, especially in Chinese academic settings. Given the central role of ‘the teacher’ in reading instruction, the study investigates the degree of importance that EFL teachers attach to reading comprehension strategies and their classroom employment of those strategies in secondary schools in China. It also explores the efficiency of reading strategy instruction on pupils’ reading comprehension performance. As a mix-method study, the analysis drew on data from a quantitative survey and interviews with seven teachers. The study revealed that the EFL teachers had positive attitudes toward the use of cognitive strategies despite their insufficient knowledge about and limited attention to the metacognitive strategies and supporting strategies. Regarding the selection of reading strategies for instruction, the mandated curriculum and high-stakes examinations, text features and demands, teaching preparation programs and their own EFL reading experiences were the major criteria in their responses, while few teachers took into account the learner needs in their choice of reading strategies. Although many teachers agreed upon the efficiency of reading strategy instruction in developing students’ reading comprehension competence, three challenges were identified in their implementation of the strategy instruction. The study provides some insights into reading strategy instruction in EFL contexts and proposes implications for curriculum innovation, teacher professional development, and reading instruction research.

Keywords: reading comprehension strategies, EFL reading instruction, language teacher cognition, teacher education

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Authors: Stefan Ninković

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The main purpose of this paper is to examine the different theoretical approaches and relevant empirical evidence and thus, recognize some of the most pressing challenges faced by school leaders. This paper starts from the fact that the new mission of the school is characterized by the need for stronger coordination among students' academic, social and emotional learning. In this sense, school leaders need to focus their commitment, vision and leadership on the issues of students' attitudes, language, cultural and social background, and sexual orientation. More specifically, they should know what a good teaching is for student’s at-risk, students whose first language is not dominant in school, those who’s learning styles are not in accordance with usual teaching styles, or who are stigmatized. There is a rather wide consensus around the fact that the traditionally popular concept of instructional leadership of the school principal is no longer sufficient. However, in a number of "pro-leadership" circles, including certain groups of academic researchers, consultants and practitioners, there is an established tendency of attributing school principal an extraordinary influence towards school achievements. On the other hand, the situation in which all employees in the school are leaders is a utopia par excellence. Although leadership obviously can be efficiently distributed across the school, there are few findings that speak about sources of this distribution and factors making it sustainable. Another idea that is not particularly new, but has only recently gained in importance is related to the fact that the collective capacity of the school is an important resource that often remains under-cultivated. To understand the nature and power of collaborative school cultures, it is necessary to know that these operate in a way that they make their all collective members' tacit knowledge explicit. In this sense, the question is how leaders in schools can shape collaborative culture and create social capital in the school. Pressure exerted on schools to systematically collect and use the data has been accompanied by the need for school leaders to develop new competencies. The role of school leaders is critical in the process of assessing what data are needed and for what purpose. Different types of data are important: test results, data on student’s absenteeism, satisfaction with school, teacher motivation, etc. One of the most important tasks of school leaders are data-driven decision making as well as ensuring transparency of the decision-making process. Finally, the question arises whether the existing models of school leadership are compatible with the current social and economic trends. It is necessary to examine whether and under what conditions schools are in need for forms of leadership that are different from those that currently prevail. Closely related to this issue is also to analyze the adequacy of different approaches to leadership development in the school.

Keywords: educational changes, leaders, leadership, school

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Authors: Carmel Sofer, Dan Vilenchik, Ron Dotsch, Galia Avidan

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Studies investigating emotional facial expressions typically reveal consensus among observes regarding the meaning of basic expressions, whose number ranges between 6 to 15 emotional states. Given this limited number of discrete expressions, how is it that the human vocabulary of emotional states is so rich? The present study argues that perceivers use sequences of these discrete expressions as the basis for a much richer vocabulary of emotional states. Such mechanisms, in which a relatively small number of basic components is expanded to a much larger number of possible combinations of meanings, exist in other human communications modalities, such as spoken language and music. In these modalities, letters and notes, which serve as basic components of spoken language and music respectively, are temporally linked, resulting in the richness of expressions. In the current study, in each trial participants were presented with sequences of two images containing facial expression in different combinations sampled out of the eight static basic expressions (total 64; 8X8). In each trial, using single word participants were required to judge the 'state of mind' portrayed by the person whose face was presented. Utilizing word embedding methods (Global Vectors for Word Representation), employed in the field of Natural Language Processing, and relying on machine learning computational methods, it was found that the perceived meanings of the sequences of facial expressions were a weighted average of the single expressions comprising them, resulting in 22 new emotional states, in addition to the eight, classic basic expressions. An interaction between the first and the second expression in each sequence indicated that every single facial expression modulated the effect of the other facial expression thus leading to a different interpretation ascribed to the sequence as a whole. These findings suggest that the vocabulary of emotional states conveyed by facial expressions is not restricted to the (small) number of discrete facial expressions. Rather, the vocabulary is rich, as it results from combinations of these expressions. In addition, present research suggests that using word embedding in social perception studies, can be a powerful, accurate and efficient tool, to capture explicit and implicit perceptions and intentions. Acknowledgment: The study was supported by a grant from the Ministry of Defense in Israel to GA and CS. CS is also supported by the ABC initiative in Ben-Gurion University of the Negev.

Keywords: Glove, face perception, facial expression perception. , facial expression production, machine learning, word embedding, word2vec

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Authors: Alexander Street, Nina Wollersberger, Paul Fernie, Leonardo Muller, Ming Hung HSU, Helen Odell-Miller, Jorg Fachner, Patrizia Di Campli San Vito, Stephen Brewster, Hari Shaji, Satvik Venkatesh, Paolo Itaborai, Nicolas Farina, Alexis Kirke, Sube Banerjee, Eduardo Reck Miranda

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Escalating neuropsychiatric symptoms (NPS) in people with dementia may lead to earlier care home admission. Music listening has been reported to stimulate cognitive function, potentially reducing agitation in this population. We present a scoping review, reporting on current developments and discussing the potential for music listening with related technology in managing agitation in dementia care. Of two searches for music listening studies, one focused on older people or people living with dementia where music listening interventions, including technology, were delivered in participants’ homes or in institutions to address neuropsychiatric symptoms, quality of life and independence. The second included any population focusing on the use of music technology for health and wellbeing. In search one 70/251 full texts were included. The majority reported either statistical significance (6, 8.5%), significance (17, 24.2%) or improvements (26, 37.1%). Agitation was specifically reported in 36 (51.4%). The second search included 51/99 full texts, reporting improvement (28, 54.9%), significance (11, 21.5%), statistical significance (1, 1.9%) and no difference compared to the control (6, 11.7%). The majority in the first focused on mood and agitation, and the second on mood and psychophysiological responses. Five studies used AI or machine learning systems to select music, all involving healthy controls and reporting benefits. Most studies in both reviews were not conducted in a home environment (review 1 = 12; 17.1%; review 2 = 11; 21.5%). Preferred music listening may help manage NPS in the care home settings. Based on these and other data extracted in the review, a reasonable progression would be to co-design and test music listening systems and protocols for NPS in all settings, including people’s homes. Machine learning and automated technology for music selection and arousal adjustment, driven by live biodata, have not been explored in dementia care. Such approaches may help deliver the right music at the appropriate time in the required dosage, reducing the use of medication and improving quality of life.

Keywords: music listening, dementia, agitation, scoping review, technology

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