Search results for: deep work

Authors: Vusala Amirbayova

Abstract:

The science of modern musicology, based on the achievements of a number of neighboring science fields, has more deeply penetrated into the sphere of artistic content of the art of music and developed a new scientific methodology, methods and approaches for a comprehensive study of the problem. In this regard, a new theory developed by the famous Russian musician-scientist, professor V. Kholopova – the specific and non – specific content of music – draws the attention with its different philosophical foundation and covering historical periods of the art of composing. The scientist related her theory to the art of European composer’s creativity, and did not include musical professionalism and especially, folklore creativity existing in other continent in her circle of interest. The researcher made an effort to explain triad (the world of ideas, emotions and subjects) which is included in the general content of music in the example of composers’ works belonging to different periods and cultures. In this respect, the artistic content of works has been deeply and comprehensively analyzed new philosophical basis. The theme ‘Leyli and Majnun’ was developed by many poets as one of the ancient legends of the East, and each artist was able to give a unique artistic interpretation of the work. This literary source was successfully developed in cognominal opera of great U. Hajibeyli in Azerbaijani music and its embodiment with symphonic means required great skill and courage from Gara Garayev. Unlike opera, as there is the opportunity to show the plot of ‘Leyli and Majnun’ in the symphonic poem, the composer achieved to reflect the main purpose of its idea convincingly with pure musical means, and created a great work with tragic spirit having a great emotional impact. Though the artistic content and form of ‘Leyli and Majnun’ symphonic poem have been sufficiently analyzed by music theorists until now, in our opinion, it is for the first time that the work is considered from the point of specific music content. Therefore, we will make an effort to penetrate into a specific layer of its artistic content after firstly reviewing the poem with traditional methods in the general plan. The use of both national fret – intonations and the system of major – minor by G. Garayev is based on well-tempered root. The composer, widely using national fret – intonations and model harmonic means on this ground, achieved to express the spirit and content of the poem. It perfectly embodies the grandeur and immortality of divine love, and the struggle of powerful human personality with the forces of despotism. Gara Garayev said about this work: “My most sublime goal and desire is to explain the literary issue that love endures to all obstacles and overcomes even death”. The music of ‘Leyli and Majnun’ symphonic poem is rich with deep desires and sharp contradictions. G.Garayev reflected these wonderful ideas about the power of music in his book ‘Articles, schools and sayings’: “Music is the decoration of life and a powerful source of inspiration”.

Keywords: content, music, symphonic, theory

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Authors: S. Sumanth, Babu Rao Ponangi, K. N. Seetharamu

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As the technology is emerging day by day, there is a need for some better methodology which will enhance the performance of radiator. Nanofluid is the one area which has promised the enhancement of the radiator performance. Currently, nanofluid has got a well effective solution for enhancing the performance of the automobile radiators. Suspending the nano sized particle in the base fluid, which has got better thermal conductivity value when compared to a base fluid, is preferably considered for nanofluid. In the current work, at first mathematical formulation has been carried out, which will govern the performance of the radiator. Current work is justified by plotting the graph for different parameters. Current work justifies the enhancement of radiator performance using nanofluid.

Keywords: nanofluid, radiator performance, graphene, gamma aluminium oxide (γ-Al2O3), titanium dioxide (TiO2)

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Authors: Henriette Jarild-Koblanck, Monica Moro

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The research has been implemented at the Kalmar University now LNU Linnaeus University inside the Design Program (Designprogrammet) for several years. The Work Book tool was created using the framework of the Bologna declaration. The project concerns primarily pedagogy and design methodology, focusing on how we evaluate artistic work processes and projects and on how we can develop the preconditions for cross-disciplinary work. The original idea of the Work Book springs from the steady habit of the Swedish researcher and now retired full professor and dean Henriette Koblanck to put images, things and colours in a notebook, right from her childhood, writing down impressions and reflections. On this preliminary thought of making use of a work book, in a form freely chosen by the user, she began to develop the Design Program (Designprogrammet) that was applied at the Kalmar University now LNU Linnaeus University, where she called a number of professionals to collaborate, among them Monica Moro an Italian designer, researcher, and teacher in the field of colour and shape. The educational intention is that the Work Book should become a tool that is both inspirational for the process of thinking and intuitional creating, and personal support for both rational and technical thinking. The students were to use the Work Book not only to visually and graphically document their results from investigations, experiments and thoughts but also as a tool to present their works to others, -students, tutors and teachers, or to other stakeholders they discussed the proceedings with. To help the students a number of matrixes were developed oriented to evaluate the projects in elaboration, based on the Bologna Declaration. In conclusion, the feedback from the students is excellent; many are still using the Work Book as a professional tool as in their words they consider it a rather accurate representation of their working process, and furthermore of themselves, so much that many of them have used it as a portfolio when applying for jobs.

Keywords: academic program, art, assessment of student’s progress, Bologna Declaration, design, learning, self-assessment

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Authors: Qingsong Xiong, Cheng Yuan, Qingzhao Kong, Haibei Xiong

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Deep-learning-driven approaches based on vibration responses have attracted larger attention in rapid structural condition assessment while obtaining sufficient measured training data with corresponding labels is relevantly costly and even inaccessible in practical engineering. This study proposes an integrated label propagation network for structural condition assessment, which is able to diffuse the labels from continuously-generating measurements by intact structure to those of missing labels of damage scenarios. The integrated network is embedded with damage-sensitive features extraction by deep autoencoder and pseudo-labels propagation by optimized fuzzy clustering, the architecture and mechanism which are elaborated. With a sophisticated network design and specified strategies for improving performance, the present network achieves to extends the superiority of self-supervised representation learning, unsupervised fuzzy clustering and supervised classification algorithms into an integration aiming at assessing damage conditions. Both numerical simulations and full-scale laboratory shaking table tests of a two-story building structure were conducted to validate its capability of detecting post-earthquake damage. The identifying accuracy of a present network was 0.95 in numerical validations and an average 0.86 in laboratory case studies, respectively. It should be noted that the whole training procedure of all involved models in the network stringently doesn’t rely upon any labeled data of damage scenarios but only several samples of intact structure, which indicates a significant superiority in model adaptability and feasible applicability in practice.

Keywords: autoencoder, condition assessment, fuzzy clustering, label propagation

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Authors: Sarai Guerrero, Lijia Liu

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Zinc gallogermanate (ZGGO) is a persistent phosphor that can emit in the near infrared (NIR) range once dopped with Cr³⁺ enabling its use for in-vivo deep-tissue bio-imaging. Such a property also allows for its application in cancer diagnosis and therapy. Given this, work into developing a synthetic procedure that can be done using common laboratory instruments and equipment as well as understanding ZGGO overall, is in demand. However, the ZGGO nanoparticles must have a size compatible for cell intake to occur while still maintaining sufficient photoluminescence. The nanoparticle must also be made biocompatible by functionalizing the surface for hydrophilic solubility and for high particle uniformity in the final product. Additionally, most research is completed on doped ZGGO, leaving a gap in understanding the base form of ZGGO. It also leaves a gap in understanding how doping affects the synthesis of ZGGO. In this work, the first step of optimizing the particle size via the crystalline size of ZGGO was done with undoped ZGGO using the organic acid, oleic acid (OA) for organic ligand-assisted biphasic hydrothermal synthesis. The effects of this synthesis procedure on ZGGO’s crystallinity were evaluated using Powder X-Ray Diffraction (PXRD). OA was selected as the capping ligand as experiments have shown it beneficial in synthesizing sub-10 nm zinc gallate (ZGO) nanoparticles as well as palladium nanocrystals and magnetite (Fe₃O₄) nanoparticles. Later it is possible to substitute OA with a different ligand allowing for hydrophilic solubility. Attenuated Total Reflection Fourier-Transform Infrared (ATR-FTIR) was used to investigate the surface of the nanoparticle to investigate and verify that OA had capped the nanoparticle. PXRD results showed that using this procedure led to improved crystallinity, comparable to the high-purity reagents used on the ZGGO nanoparticles. There was also a change in the crystalline size of the ZGGO nanoparticles. ATR-FTIR showed that once capped ZGGO cannot be annealed as doing so will affect the OA. These results point to this new procedure positively affecting the crystallinity of ZGGO nanoparticles. There are also repeatable implying the procedure is a reliable source of highly crystalline ZGGO nanoparticles. With this completed, the next step will be working on substituting the OA with a hydrophilic ligand. As these ligands effect the solubility of the nanoparticle as well as the pH that the nanoparticles can dissolve in, further research is needed to verify which ligand is best suited for preparing ZGGO for bio-imaging.

Keywords: biphasic hydrothermal synthesis, crystallinity, oleic acid, zinc gallogermanate

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Authors: Budhvin T. Withana, Sulochana Rupasinghe

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The educational system faces a significant concern with regards to Dyslexia and Dysgraphia, which are learning disabilities impacting reading and writing abilities. This is particularly challenging for children who speak the Sinhala language due to its complexity and uniqueness. Commonly used methods to detect the risk of Dyslexia and Dysgraphia rely on subjective assessments, leading to limited coverage and time-consuming processes. Consequently, delays in diagnoses and missed opportunities for early intervention can occur. To address this issue, the project developed a hybrid model that incorporates various deep learning techniques to detect the risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16, and YOLOv8 models were integrated to identify handwriting issues. The outputs of these models were then combined with other input data and fed into an MLP model. Hyperparameters of the MLP model were fine-tuned using Grid Search CV, enabling the identification of optimal values for the model. This approach proved to be highly effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention. The Resnet50 model exhibited a training accuracy of 0.9804 and a validation accuracy of 0.9653. The VGG16 model achieved a training accuracy of 0.9991 and a validation accuracy of 0.9891. The MLP model demonstrated impressive results with a training accuracy of 0.99918, a testing accuracy of 0.99223, and a loss of 0.01371. These outcomes showcase the high accuracy achieved by the proposed hybrid model in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, dyslexia, dysgraphia, deep learning, learning disabilities, data science

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Authors: Majd Owda, Raed Abubadawia

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Seventy-four years have passed, and the Palestinian refugees are still waiting to exercise their right of return, which was approved by the international community through dozens of international resolutions. Despite the wait, Palestinian refugees continue to suffer in many host countries. In these waiting stations, they are still deprived of many basic rights. Perhaps Lebanon is one of the most extreme waiting stations in depriving Palestinian refugees of these rights, especially the right to work. This paper attempts to identify the various Lebanese partisan and sectarian points of view that stand in the way of granting Palestinian refugees their basic rights, foremost of which is the right to work, in addition to the recent administrative attempts of the Lebanese government (2021) to grant them their basic rights. And the legal and political obstacles faced by these attempts and which have eliminated them since their launch. This paper highlights the continued need of Palestinian refugees in Lebanon for various social, political and international moves to grant them their basic rights in order to preserve human dignity, which cannot be resolved without these rights.

Keywords: Palestinian refugees, Lebanon, labor law, right to work.

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Authors: Murat Colak, Berkay Cakir Saridogan

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Since the dawn of modern corporations, almost every single employee has been working in the same loop, which contains three basic steps: going to work, providing the needs for the work, and getting back home. Only a small amount of people were able to break that standard and live outside the box. As the 2019 pandemic hit the Earth and most companies shut down their physical offices, that loop had to change for everyone. This means that the old management styles had to be significantly re-arranged to the "work from home" type of business methods. The methods include online conferences and meetings, time and task tracking using algorithms, globalization of the work, and, most importantly, remote working. After the global epidemic started, even the tech giants were concerned. Now, it can be seen those technology companies have an incredible step-up in their shares compared to the other companies because they know how to manage such situations even better than every other industry. This study aims to take the old traditional management styles in big companies and compare them with the post-covid methods (2019-2022). As a result of this comparison made using the annual reports and shared statistics, this study aims to explain why the winners of this crisis are the technology companies.

Keywords: Covid-19, technology companies, business models, remote work

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Authors: Kalpana Goel

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Australian social work schools are finding it difficult to find appropriate placements for the increasing number of international students enrolled in their Master of Social Work qualifying (MSWQ) programs. Anecdotally, it has been noticed that fewer social work students are ready to work with older people whose numbers are rising globally. An innovative and unique placement for international students enrolled in the MSWQ at one Australian university was organised in partnership with a community-based service working with older clients to meet two objectives: increasing the number of suitable placements for international students and preparing social work students to work with older people. Creative activities and projects were designed to provide meaningful engagement and experience in working with older people in the community. Students participated in a number of projects that were matched with their interest and capability in a 500-hour placement. The students were asked to complete an online survey after all work for the placement had been completed. The areas of assessment were: self-perceived change in perception towards age and older people, valued field placement experiences including reflective practice, knowledge and skill development, and constraints and challenges experienced in the placement. Findings revealed students’ increased level of confidence in applying social work theory to practice, developing effective communication and interpersonal skills, and use of innovation and creativity in preparing well-being plans with older adults. Challenges and constraints related to their limited English language ability and lack of cultural knowledge of the host society. It was recognised that extra support for these students and more planning in the beginning phase of placement are vital to placement success. Caution in matching students with clients of similar cultural background must be exercised to ensure that there is equity in task allocation and opportunities for wider experiences.

Keywords: field placement, international students, older people, social work

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Authors: Budhvin T. Withana, Sulochana Rupasinghe

Abstract:

The problem of Dyslexia and Dysgraphia, two learning disabilities that affect reading and writing abilities, respectively, is a major concern for the educational system. Due to the complexity and uniqueness of the Sinhala language, these conditions are especially difficult for children who speak it. The traditional risk detection methods for Dyslexia and Dysgraphia frequently rely on subjective assessments, making it difficult to cover a wide range of risk detection and time-consuming. As a result, diagnoses may be delayed and opportunities for early intervention may be lost. The project was approached by developing a hybrid model that utilized various deep learning techniques for detecting risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16 and YOLOv8 were integrated to detect the handwriting issues, and their outputs were fed into an MLP model along with several other input data. The hyperparameters of the MLP model were fine-tuned using Grid Search CV, which allowed for the optimal values to be identified for the model. This approach proved to be effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention of these conditions. The Resnet50 model achieved an accuracy of 0.9804 on the training data and 0.9653 on the validation data. The VGG16 model achieved an accuracy of 0.9991 on the training data and 0.9891 on the validation data. The MLP model achieved an impressive training accuracy of 0.99918 and a testing accuracy of 0.99223, with a loss of 0.01371. These results demonstrate that the proposed hybrid model achieved a high level of accuracy in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, Dyslexia, Dysgraphia, deep learning, learning disabilities, data science

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Authors: Alexis Polanco Jr, Tsai Lu Liu

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Research on digital assessment for deaf and hard of hearing (DHH) students is negligible. Part of this stems from the DHH assessment design existing at the intersection of the emergent disciplines of usability, accessibility, and child-computer interaction (CCI). While these disciplines have some prevailing guidelines —e.g. in user experience design (UXD), there is Jacob Nielsen’s 10 Usability Heuristics (Nielsen-10); for accessibility, there are the Web Content Accessibility Guidelines (WCAG) & the Principles of Universal Design (PUD)— this research was unable to uncover a unified set of guidelines. Given that digital assessments have lasting implications for the funding and shaping of U.S. school districts, it is vital that cross-disciplinary guidelines emerge. As a result, this research seeks to provide a framework by which these disciplines can share knowledge. The framework entails a process of asking subject-matter experts (SMEs) and design & development professionals to self-describe their fields of expertise, how their work might serve DHH students, and to expose any incongruence between their ideal process and what is permissible at their workplace. This research used two rounds of mixed methods. The first round consisted of structured interviews with SMEs in usability, accessibility, CCI, and DHH education. These practitioners were not designers by trade but were revealed to use designerly work processes. In addition to asking these SMEs about their field of expertise, work process, etc., these SMEs were asked to comment about whether they believed Nielsen-10 and/or PUD were sufficient for designing products for middle-school DHH students. This first round of interviews revealed that Nielsen-10 and PUD were, at best, a starting point for creating middle-school DHH design guidelines or, at worst insufficient. The second round of interviews followed a semi-structured interview methodology. The SMEs who were interviewed in the first round were asked open-ended follow-up questions about their semantic understanding of guidelines— going from the most general sense down to the level of design guidelines for DHH middle school students. Designers and developers who were never interviewed previously were asked the same questions that the SMEs had been asked across both rounds of interviews. In terms of the research goals: it was confirmed that the design of digital assessments for DHH students is inherently cross-disciplinary. Unexpectedly, 1) guidelines did not emerge from the interviews conducted in this study, and 2) the principles of Nielsen-10 and PUD were deemed to be less relevant than expected. Given the prevalence of Nielsen-10 in UXD curricula across academia and certificate programs, this poses a risk to the efficacy of DHH assessments designed by UX designers. Furthermore, the following findings emerged: A) deep collaboration between the disciplines of usability, accessibility, and CCI is low to non-existent; B) there are no universally agreed-upon guidelines for designing digital assessments for DHH middle school students; C) these disciplines are structured academically and professionally in such a way that practitioners may not know to reach out to other disciplines. For example, accessibility teams at large organizations do not have designers and accessibility specialists on the same team.

Keywords: deaf, hard of hearing, design, guidelines, education, assessment

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Authors: Bastien Batardière, Joon Kwon

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For finite-sum optimization, variance-reduced gradient methods (VR) compute at each iteration the gradient of a single function (or of a mini-batch), and yet achieve faster convergence than SGD thanks to a carefully crafted lower-variance stochastic gradient estimator that reuses past gradients. Another important line of research of the past decade in continuous optimization is the adaptive algorithms such as AdaGrad, that dynamically adjust the (possibly coordinate-wise) learning rate to past gradients and thereby adapt to the geometry of the objective function. Variants such as RMSprop and Adam demonstrate outstanding practical performance that have contributed to the success of deep learning. In this work, we present AdaLVR, which combines the AdaGrad algorithm with loopless variance-reduced gradient estimators such as SAGA or L-SVRG that benefits from a straightforward construction and a streamlined analysis. We assess that AdaLVR inherits both good convergence properties from VR methods and the adaptive nature of AdaGrad: in the case of L-smooth convex functions we establish a gradient complexity of O(n + (L + √ nL)/ε) without prior knowledge of L. Numerical experiments demonstrate the superiority of AdaLVR over state-of-the-art methods. Moreover, we empirically show that the RMSprop and Adam algorithm combined with variance-reduced gradients estimators achieve even faster convergence.

Keywords: convex optimization, variance reduction, adaptive algorithms, loopless

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Authors: Isaac K. E. Ampomah, Seong-Bae Park, Sang-Jo Lee

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Over the past decade, there have been promising developments in Natural Language Processing (NLP) with several investigations of approaches focusing on Recognizing Textual Entailment (RTE). These models include models based on lexical similarities, models based on formal reasoning, and most recently deep neural models. In this paper, we present a sentence encoding model that exploits the sentence-to-sentence relation information for RTE. In terms of sentence modeling, Convolutional neural network (CNN) and recurrent neural networks (RNNs) adopt different approaches. RNNs are known to be well suited for sequence modeling, whilst CNN is suited for the extraction of n-gram features through the filters and can learn ranges of relations via the pooling mechanism. We combine the strength of RNN and CNN as stated above to present a unified model for the RTE task. Our model basically combines relation vectors computed from the phrasal representation of each sentence and final encoded sentence representations. Firstly, we pass each sentence through a convolutional layer to extract a sequence of higher-level phrase representation for each sentence from which the first relation vector is computed. Secondly, the phrasal representation of each sentence from the convolutional layer is fed into a Bidirectional Long Short Term Memory (Bi-LSTM) to obtain the final sentence representations from which a second relation vector is computed. The relations vectors are combined and then used in then used in the same fashion as attention mechanism over the Bi-LSTM outputs to yield the final sentence representations for the classification. Experiment on the Stanford Natural Language Inference (SNLI) corpus suggests that this is a promising technique for RTE.

Keywords: deep neural models, natural language inference, recognizing textual entailment (RTE), sentence-to-sentence relation

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Authors: Rosana Silvina Codaro, Patricia Amelia Tomei

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This study explores the relationship between job satisfaction and alignment between the individual´s current occupation and his talents, needs and values, namely his 'career anchors'. With this purpose in mind, a quantitative survey was performed for a non- graduate probabilistic sample of management business students of a private university in Rio de Janeiro. The results of the survey showed there is no significant association between satisfaction at work and alignment with the individual’s career anchor. The most frequent career anchor found for both genders was lifestyle, showing a trend towards finding a career that allows some balance between professional and personal life. The study also showed that self-employed individuals are more satisfied with their work than the individuals employed by a company are, and men are more satisfied at work than women are, Individuals aligned and not satisfied tend to be the ones who have fewer years of work experience and individuals not aligned and satisfied tend to be older.

Keywords: careers, career anchors, job satisfaction, Schein´s career anchor model

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Authors: Robin C. Ladwig

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Work experiences and satisfaction as well as the feeling of belonging has been narrowly explored from the perspective of trans and gender diverse individuals. Hence, the study investigates the relationship of values, attitudes, and norms of occupational environments and the working identity of trans and gender diverse people of the Australian workforce. Based on 22 semi-structured interviews with trans and gender diverse individuals regarding their work and career experiences, a first insight about their feeling of belonging through commonality in the workplace could be established. Communality between the values, attitudes and norms of a trans and gender diverse individuals working identities and profession, organization and working environment could increase the feeling of belonging. Further reflection and evaluation of trans and gender diverse identities in the workplace need to be considered to create an equitable and inclusive workplace of the future. Consequently, an essential development step for the future of work and its fundamental values of diversity, inclusion, and belonging will consist of the acknowledgement and inclusion of trans and gender diverse people as part of a broader social identity of the workplace.

Keywords: belonging, future of work, working identity, trans and gender diverse identity

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Authors: El Oualid Mokhnache, Noureddine Ramdani

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The choice of gun barrel materials is crucial to ensure the maximum high rate of fire. The high rate of fire causes wear-out damage and shuts off mechanical properties (hardness, strength, wear resistance, etc.) and ballistic properties (bullet speed, dispersion and precision, longevity of barrel, etc). To overcome these kinds of problems, a deep understanding of the effect of the firing cycle on the mechanical and ballistic properties of the barrel is regarded as crucial to improving its characteristics. In the present work, a real experimental test of firing by using a high steel barrel with 7.62x39 ammunition was carried. Microstructural observations by using SEM were investigated. Hardness evolution through the barrel of both barrels labeled as reference barrels and as fired barrels were compared and discussed. Ballistic properties during the firing test, including speed of projectile and precision dispersion, are revealed and discussed as well. The aim of the present communication is about to discuss the relationship between pressure distribution versus mechanical properties through the wall barrel. Ballistic properties, including speed of the projectile, dispersion, and precision results during the shooting process, were investigated. Microstructure observations of the as-rifled barrel in comparison with the as-reference barrel were performed as well.

Keywords: barrel, ballistic, pressure, microstructure evolution, hardness

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Authors: Robyn Moloney, HuiLing Xu

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Many countries wish to produce Asia-literate citizens, through language education. International contexts of Chinese language education are seeking pedagogical innovation to meet local contextual factors frequently holding back learner success. In multicultural Australia, innovative pedagogy is urgently needed to support motivation in sustained study, with greater strategic integration of technology. This research took a qualitative approach to identify need and solutions. The paper analyses strategies that three secondary school teachers are adopting to meet specific challenges in the Australian context. The data include teacher interviews, classroom observations and student interviews. We highlight the use of task-based learning and differentiated teaching for multilevel classes, and the role which digital technologies play in facilitating both areas. The strategy examples are analysed in reference both to a research-based framework for describing quality teaching, and to current understandings of motivation in language learning. The analysis of data identifies learning featuring deep knowledge, higher-order thinking, engagement, social support, utilisation of background knowledge, and connectedness, all of which work towards the learners having a sense of autonomy and an imagination of becoming an adult Chinese language user.

Keywords: Chinese pedagogy, digital technologies, motivation, secondary school

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Authors: Ann Vibert, Heather Hemming

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This paper presentation summarizes the findings and implications of research on the plight and practices of women educational leaders in public school systems and in one university. The authors, both women university administrators, are also scholars and researchers of education. The research project on which this paper presentation is based proposed to examine how women educational leaders imagined, experienced, and carried out their leadership roles in the context of a growing local and global accountability-based performativity discourse which is reshaping educational work especially for women, we argue, in both public school and post-secondary sites. The research employed critical ethnographic interviews with 20 women educational leaders in P-12 school systems and three women university level educational leaders. Data were collected on women educational leaders’ perceptions of the effects of accountability and performativity discourses on the nature of their work. Specifically, leaders were asked to speak to whether they experienced a growth in managerial work as a consequence of increased accountability demands; how they experienced their work changing as a consequence of accountability and performativity demands; how these changes impacted the central values they enacted in their work as women educational leaders changes; and how they responded to/negotiated/accommodated changes in the nature of their work developing as a consequence of accountability and performativity frameworks. Findings from the research data and analyses confirm and extend recent scholarly work on the gendered nature of performativity and accountability discourses and frameworks, and their differential effects across differing genders. The oral presentation we propose here focusses on those findings in terms of similarities for women educational leaders across different educational contexts.

Keywords: women in educational leadership, gender and educational performativity, accountability and women leaders, gender and educational leadership

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Authors: T. C. Bera, A. Bansal, D. Nema

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During performing turning operation, cutting force plays a significant role in metal cutting process affecting tool-work piece deflection, vibration and eventually part quality. The present research work aims to develop a mechanistic cutting force model and to study the mechanistic constants used in the force model in case of turning operation. The proposed model can be used for the reliable and accurate estimation of the cutting forces establishing relationship of various force components (cutting force and feed force) with uncut chip thickness. The accurate estimation of cutting force is required to improve thin-walled part accuracy by controlling the tool-work piece deflection induced surface errors and tool-work piece vibration.

Keywords: turning, cutting forces, cutting constants, uncut chip thickness

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Authors: Pius Marthin, Nihal Ata Tutkun

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Survival analysis has become one of the paramount procedures in the modeling of time-to-event data. When we encounter complex survival problems, the traditional approach remains limited in accounting for the complex correlational structure between the covariates and the outcome due to the strong assumptions that limit the inference and prediction ability of the resulting models. Several studies exist on the deep learning approach to survival modeling; moreover, the application for the case of complex survival problems still needs to be improved. In addition, the existing models need to address the data structure's complexity fully and are subject to noise and redundant information. In this study, we design a deep learning technique (CmpXRnnSurv_AE) that obliterates the limitations imposed by traditional approaches and addresses the above issues to jointly predict the risk-specific probabilities and survival function for recurrent events with competing risks. We introduce the component termed Risks Information Weights (RIW) as an attention mechanism to compute the weighted cumulative incidence function (WCIF) and an external auto-encoder (ExternalAE) as a feature selector to extract complex characteristics among the set of covariates responsible for the cause-specific events. We train our model using synthetic and real data sets and employ the appropriate metrics for complex survival models for evaluation. As benchmarks, we selected both traditional and machine learning models and our model demonstrates better performance across all datasets.

Keywords: cumulative incidence function (CIF), risk information weight (RIW), autoencoders (AE), survival analysis, recurrent events with competing risks, recurrent neural networks (RNN), long short-term memory (LSTM), self-attention, multilayers perceptrons (MLPs)

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Authors: Kamarul Fairuz Hassim, Sharifah Fatimah Syed-Ahmad

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New managerialism has become the current trend in managing public sector which emphasizes on efficiency, effectiveness, and accountability. Public universities are not exempted from experiencing this new system. This study tries to explore the direct impact of new managerialism towards work performance of the employees in a public university in Malaysia and the indirect impact through a mediating factor – Organizational Commitment. Feedback were gathered from 204 respondents comprises of academics and non-academics managers in the University of Malaya using a 39 items, self-administered questionnaire. Respondents’ views were asked in the aspects of managerialism level of the university, their organizational commitment, and self-rated work performance level. The findings exhibit that there is a direct impact of new managerialism towards employees’ work performance in a positive way. This is contradicting to the established Hypotheses of this study. Furthermore, there is no significant finding on the role of all three components of organizational commitment – affective, normative, and continuance as the mediating factors in new managerialism approach that gave impact towards work performance. Consequently these insignificant found failed to corroborate the remaining six hypotheses in this study. On another note, findings gathered from this study show some contradiction to the original research conducted earlier by Smeenk et al. in 2009. Therefore, results obtained from this study do contribute to the existing pool of knowledge as previous studies on this topic are scarce especially in the Malaysia’s context.

Keywords: new managerialism, Malaysia public universities, organizational commitment, work performance

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Authors: Katerine Moraes dos Satons, Gisele Massante Peixoto Tracera, Regina Célia Gollner Zeitoune

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To analyze the psychosocial risks related to the organization of nursing work in outpatient clinics of university hospitals. Cross-sectional epidemiological study developed in 11 outpatient units linked to the three public universities of the city of Rio de Janeiro, Brazil. Participants were 388 nursing professionals who worked in patient care at the time of the research. Data were collected from July to December 2018, using a self-applicable instrument. A questionnaire was used for sociodemographic, occupational and health characterization, and the Work Organization Scale. The bivariate analyses were performed using the odds ratio (OR), with a confidence interval of 95%, significance level of 5%. The organization of nursing work received an assessment of medium psychosocial risk by the professionals participating in the research, demanding interventions in the short and medium term. There was no association between sociodemographic, occupational and health characteristics and the organization of outpatient work. Interventional measures should be performed in the psychosocial risk factors presented in this research, with a view to improving the work environment, so that the importance of maintaining satisfactory material conditions is considered, as well as the adequate quantity of human resources. In addition, it aims to expand the spaces of nursing participation in decision- making, strengthening its autonomy as a profession.

Keywords: occupational risks, nursing, nursing team, worker’s health, psychosocial risks

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Authors: Jiaying Zhang, Xin Mu, Chang Ni, Jeff L. Zhang

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Magnetic resonance elastography (MRE) non-invasively assesses tissue elastic properties, such as shear modulus, by measuring tissue’s displacement in response to mechanical waves. The estimated metrics on tissue elasticity or stiffness have been shown to be valuable for monitoring physiologic or pathophysiologic status of tissue, such as a tumor or fatty liver. To quantify tissue shear modulus from MRE-acquired displacements (essentially an inverse problem), multiple approaches have been proposed, including Local Frequency Estimation (LFE) and Direct Inversion (DI). However, one common problem with these methods is that the estimates are severely noise-sensitive due to either the inverse-problem nature or noise propagation in the pixel-by-pixel process. With the advent of deep learning (DL) and its promise in solving inverse problems, a few groups in the field of MRE have explored the feasibility of using DL methods for quantifying shear modulus from MRE data. Most of the groups chose to use real MRE data for DL model training and to cut training images into smaller patches, which enriches feature characteristics of training data but inevitably increases computation time and results in outcomes with patched patterns. In this study, simulated wave images generated by Finite Differential Time Domain (FDTD) simulation are used for network training, and U-Net is used to extract features from each training image without cutting it into patches. The use of simulated data for model training has the flexibility of customizing training datasets to match specific applications. The proposed method aimed to estimate tissue shear modulus from MRE data with high robustness to noise and high model-training efficiency. Specifically, a set of 3000 maps of shear modulus (with a range of 1 kPa to 15 kPa) containing randomly positioned objects were simulated, and their corresponding wave images were generated. The two types of data were fed into the training of a U-Net model as its output and input, respectively. For an independently simulated set of 1000 images, the performance of the proposed method against DI and LFE was compared by the relative errors (root mean square error or RMSE divided by averaged shear modulus) between the true shear modulus map and the estimated ones. The results showed that the estimated shear modulus by the proposed method achieved a relative error of 4.91%±0.66%, substantially lower than 78.20%±1.11% by LFE. Using simulated data, the proposed method significantly outperformed LFE and DI in resilience to increasing noise levels and in resolving fine changes of shear modulus. The feasibility of the proposed method was also tested on MRE data acquired from phantoms and from human calf muscles, resulting in maps of shear modulus with low noise. In future work, the method’s performance on phantom and its repeatability on human data will be tested in a more quantitative manner. In conclusion, the proposed method showed much promise in quantifying tissue shear modulus from MRE with high robustness and efficiency.

Keywords: deep learning, magnetic resonance elastography, magnetic resonance imaging, shear modulus estimation

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Authors: Hajer Chaker Ben Hadj Kacem, Thouraya Slama, Néjiba El Yetim Zribi

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This paper analyzes the effects of gender, affiliation, prior work experience, social work, and vicarious learning through family role models on entrepreneurial skills development by students when they have learned through the entrepreneurship method in Tunisia. Authors suggest that these variables enhance the development of students’ entrepreneurial skills when combined with teaching through entrepreneurship. The article assesses the impact of these combinations by comparing their effects on the development of thirteen students’ entrepreneurial competencies, namely entrepreneurial mindset, core self-evaluation, entrepreneurial attitude, entrepreneurial knowledge, creativity, financial literacy, managing ambiguity, marshaling of resources, planning, teaching methods, entrepreneurial teachers, innovative employee, and Entrepreneurial intention. Authors use a two-sample independent t-test to make the comparison, and the results indicate that, when combined with teaching through the entrepreneurship method, students with prior work experience developed better six entrepreneurial skills; students with social work developed better three entrepreneurial skills, men developed better four entrepreneurial skills than women. However, all students developed their entrepreneurial skills through this practical method regardless of their affiliation and their vicarious learning through family role models.

Keywords: affiliation, entrepreneurial skills, gender, role models, social work, teaching through entrepreneurship, vicarious learning, work experience

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Authors: Shen Xiaoyun

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The AI-generated works must intersect with the right holder’s work, thus having a certain impact on the rights and interests of the right holder’s work. The law needs to explore and improve the regulation of the fair use of AI creations and build a compensation system to adapt to the development of the times. The development of AI technology has brought about problems such as the unclear relationship between fair use and infringement of copyright, the unclear general terms and conditions of application, and the incomplete criteria for judging at different stages. Through different theoretical methods, the legitimacy of the rational use of the system can be demonstrated. The compensation standard for fair use of copyright in AI creation can refer to the market pricing of the right holder's work, and the compensation can construct a formula for the amount of damages for AI copyright infringement, and construct the compensation standard based on the main factors affecting the market value of the work, so as to provide a reference for the construction of a compensation system for fair use of works generated by AI.

Keywords: artificial intelligence, creative acts, fair use of copyright, copyright compensation system

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Authors: Vyacheslav Furtak, Merja Roivainen, Olga Mirochnichenko, Majid Laassri, Bella Bidzhieva, Tatiana Zagorodnyaya, Vladimir Chizhikov, Konstantin Chumakov

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Molecular epidemiology and environmental surveillance are parts of a rational strategy to control infectious diseases. They have been widely used in the worldwide campaign to eradicate poliomyelitis, which otherwise would be complicated by the inability to rapidly respond to outbreaks and determine sources of the infection. The conventional scheme involves isolation of viruses from patients and the environment, followed by their identification by nucleotide sequences analysis to determine phylogenetic relationships. This is a tedious and time-consuming process that yields definitive results when it may be too late to implement countermeasures. Because of the difficulty of high-throughput full-genome sequencing, most such studies are conducted by sequencing only capsid genes or their parts. Therefore the important information about the contribution of other parts of the genome and inter- and intra-species recombination to viral evolution is not captured. Here we propose a new approach based on the rapid concentration of sewage samples with tangential flow filtration followed by deep sequencing and reconstruction of nucleotide sequences of viruses present in the samples. The entire nucleic acids content of each sample is sequenced, thus preserving in digital format the complete spectrum of viruses. A set of rapid algorithms was developed to separate deep sequence reads into discrete populations corresponding to each virus and assemble them into full-length consensus contigs, as well as to generate a complete profile of sequence heterogeneities in each of them. This provides an effective approach to study molecular epidemiology and evolution of natural viral populations.

Keywords: poliovirus, eradication, environmental surveillance, laboratory diagnosis

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Authors: Hend Al-Ma'seb, Anwar Alkhurinej

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In the field of social work, social workers understand that it is very difficult for individuals to ask for help from therapists. Therefore, it is important to study the variables associated with seeking professional help. A total of 478 undergraduate students from Kuwait University participated voluntarily in the study. The findings for this study showed that the participants of the study have a slightly high degree of public stigma, low self–stigma, and positive attitude toward seeking professional help. In addition, the findings of the study reveal that there are significant relationships between gender, taking social work classes, thinking about receiving counseling and having social problems and participants' attitude towards seeking professional help. Furthermore, the findings of the study showed that there were significant relationships between gender, and thinking about receiving counseling, and self-stigma. The findings of the current study have implications for the field of social work in Kuwait that would help to improve the knowledge in this area.

Keywords: attitude towards help, social work, social workers, stigma

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Authors: Dyah Adi Sriwahyuni

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Institutional work has become a prominent and contemporary institutional theory perspective in organization studies. A wealth of studies in organizations have explored actor activities in creating, maintaining, and disrupting institutions at the field level. However, the exploration of the work of actors in creating new management practices at the organizational level has been somewhat limited. The current institutional work literature mostly describes the work of actors at the field level and ignores organizational actors who work to realize management practices. Organizational actors here are defined as actors in organizations who work to institutionalize a particular management practice within the organizations. The extant literature has also generalized the types of management practices, which meant overlooking the unique characteristics of each management fashion as well as a management practice. To fill these gaps, this study aims to provide empirical evidence so as to contribute theoretically to institutional work through a comparative case study on organizational actors’ creation of knowledge management (KM) practice in two public sector organizations in Indonesia. KM is a contemporary management practice employed to manage individual and organizational knowledge in order to improve organizational performance. This practice presents a suitable practical setting with which to provide a rich understanding of the organizational actors’ institutional work and their connection with technology. Drawing on and extending the work of Perkmann and Spicer (2008), this study explores the forms of institutional work performed by organizational actors, including their motivation, skills, challenges, and opportunities. The primary data collection is semi-structured interviews with knowledgeable actors and document analysis for validity and triangulation. Following Eisenhardt's cross-case patterns, the researcher analyzed the collected data focusing on within-group similarities and intergroup differences. The researcher coded interview data using NVivo and used documents to corroborate the findings. The study’s findings add to the wealth of institutional theory literature in organization studies, particularly institutional work related to management practices. This study builds a theory about the work of organizational actors in creating knowledge management practices. Using the perspective of institutional work, research can show the roles of the various actors involved, their practices, and their relationship to technology (materiality), not only focusing on actors with a power which has been the theorizing of institutional entrepreneurship. The development of knowledge management practices in the Indonesian public sector is also a significant additional contribution, given that the current KM literature is dominated by conceptualizing the KM framework and the impact of KM on organizations. The public sector, which is the research setting, also provides important lessons on how actors in a highly institutionalized context are creating an institution, in this case, a knowledge management practice.

Keywords: institutional work, knowledge management, case study, public sector organizations

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Authors: Marwa Mamdouh Shaban, Nagat Saied Habib, Shireen Ezz El-Din Taha, Eman Mahmoud Seif El-Naser

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Background: Dental nurses and dentists were constantly exposed to a number of specific work related health risk factors which develop and intensify with years. Awareness regarding these work-related health risk factors and implementation of preventive health care measures could provide a safe work environment for all dental nurses and dentists. Aim of the study: to assess the work-related health risk factors among dental nurses and dentists and preventive health care measures applied among dental nurses and dentists. Research design: A descriptive design was utilized. Sample: Convenience sample of 50 dental nurses and 150 dentists were included in the current study. Setting: This study was conducted at the dental clinics at faculty of oral and dental medicine, Al-Kasr Al Ainy Hospital. Tools of data collection: Three tools were developed, tested for clarity, and feasibility: a-Socio-demographic data sheet, b-Work-related health risk factors questionnaire, and c-structured observational checklist. Results: The most common work risk factors prevailing among dental nurses were emotional exhaustion (82%), low back pain (76%) and latex allergy (62%) and the most common work risk factors prevailing among dentists were percutaneous exposure incident (100%), emotional exhaustion (100%) and low back pain (93.3%). Also, statistically significant negative correlation (r=-0.274, at p = 0.045) between the incidence of chemical health risk factors and application of chemical preventive measures among dental nurses. A statistically significant negative correlation (r=-0.177, at p = 0.030) between the incidences of mechanical health risk factors among dentists and application of mechanical preventive measures. Conclusion: The studied dental nurses and dentists exposed to many work related health risk factors as latex allergy, percutaneous exposure incidents, low back pain and emotional exhaustion related to inappropriate application of preventive health care measures. Recommendation: Raise awareness of dental nurses and dentists about work-related health risk factors, design and implement health education program for preventive health care measures.

Keywords: work-related risk factors, preventive measures, nurses, dentists

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Authors: Edo Shonin, William Van Gordon, Mark D. Griffiths

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Due to its potential to concurrently improve Work-Related Wellbeing (WRW) and job performance; occupational stakeholders are becoming increasingly interested in meditation. Despite this, there is a scarcity of methodologically robust research examining the utility of meditation within occupational contexts. This study conducted the first randomized controlled trial to assess the effects of meditation on outcomes relating to both WRW and job performance. Office-based middle-hierarchy managers (n=152) were allocated to either an eight-week meditation intervention (Meditation Awareness Training: MAT) or an active control intervention. MAT participants demonstrated significant improvements (with strong effect-sizes) over control-group participants in levels of work-related stress, job satisfaction, psychological distress, and employer-rated job performance. It is concluded that MAT appears to be effective for improving both WRW and job performance in middle-hierarchy managers. There are a number of novel implications: (i) meditation can effectuate a perceptual shift in how employees experience their work and psychological environment and may thus constitute a cost-effective WRW intervention, (ii) meditation-based (i.e., present-moment-focused) working styles may be more effective than goal-based (i.e., future-orientated) working styles, and (iii) meditation may reduce the separation made by employees between their own interests and those of the organizations they work for.

Keywords: work-related stress, workplace wellbeing, occupational stress, job performance, meditation awareness training, mindfulness

Procedia PDF Downloads 318