Search results for: college student learning experience

Authors: Madhu Babu Cherukuri, Tamoghna Ghosh

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Factory supply chain management spends billions of dollars every year to procure and manage equipment spare parts. Due to technology -and processes changes some of these spares become obsolete/dead inventory. Factories have huge dead inventory worth millions of dollars accumulating over time. This is due to lack of a scientific methodology to identify them and send the inventory back to the suppliers on a timely basis. The standard approach followed across industries to deal with this is: if a part is not used for a set pre-defined period of time it is declared dead. This leads to accumulation of dead parts over time and these parts cannot be sold back to the suppliers as it is too late as per contract agreement. Our main idea is the time period for identifying a part as dead cannot be a fixed pre-defined duration across all parts. Rather, it should depend on various properties of the part like historical consumption pattern, type of part, how many machines it is being used in, whether it- is a preventive maintenance part etc. We have designed a predictive algorithm which predicts part obsolescence well in advance with reasonable accuracy and which can help save millions.

Keywords: obsolete inventory, machine learning, big data, supply chain analytics, dead inventory

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Authors: Mohd Aderi Che Noh, Tuan Rahayu Tuan Lasan

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Higher order thinking skills (HOTS) is an important skill in the Malaysian education system to produce a knowledgeable generation, able to think critically and creatively in order to face the challenges in the future. Educational challenges of the 21st century require that all students to have the HOTS. Therefore, this study aims to identify the level of knowledge, attitude and readiness of students towards HOTS. The respondents were 127 form four students from schools in the Federal Territory of Putrajaya. This study is quantitative survey using a questionnaire to collect data. Data were analyzed using Statistical Package for the Social Sciences (SPSS) 23.0. The results showed that knowledge, attitudes and readiness of students towards HOTS lam were at a high level. Inferential analysis showed that there was a significant relationship between knowledge with attitude and readiness towards HOTS. This study provides information to the schools and teachers to improve the teaching and learning to increase students HOTS and fulfilling the hope of Ministry of Education to produce human capital who can be globally competitive.

Keywords: high order thinking skills, teaching, education, Malaysia

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Authors: Tomas Kos

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An increasing body of research has explored patterns of interaction and peer support among young learners. Although some studies suggest that young learners can collaborate and support each other, other studies indicate that young learners may lack the ability to work together and support one another when interacting on classroom tasks. Moreover, despite the claims that peer collaboration is conducive to learning, studies have not paid enough attention to the “how” to enhance peer collaboration on classroom tasks. To fill this gap, this “how-to” article proposes that teaching young learners how to work together is a powerful pedagogical tool that can greatly improve collaborative behavior and a sense of mutuality among young learners. This article will pay particular attention to primary schools and the context of English as a foreign language. It will first review literature related to patterns of interaction and peer support conducted in the cognitive and sociocultural framework. It will then address what it actually means to collaborate. At the heart of the article, it will discuss some practical pedagogical ideas for language teachers, which entail teaching collaborative principles and strategies that will help their students to support each other and engage in communication with each other.

Keywords: young learners, peer collaboration, peer interaction, peer support, patterns of interaction

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Authors: Sergey Kholodkevich, Tatiana Kuznetsova

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The objective assessment of ecological state of water ecosystems is impossible without the use of biological methods of the environmental monitoring capable in the integrated look to reveal negative for biota changes of quality of water as habitats. Considerable interest for the development of such methods of environmental quality control represents biomarker approach. Measuring systems, by means of which register cardiac activity characteristics, received the name of bioelectronic. Bioelectronic systems are information and measuring systems in which animals (namely, benthic invertebrates) are directly included in structure of primary converters, being an integral part of electronic system of registration of these or those physiological or behavioural biomarkers. As physiological biomarkers various characteristics of cardiac activity of selected invertebrates have been used in bioelectronic system.lChanges in cardiac activity are considered as integrative measures of the physiological condition of organisms, which reflect the state of the environment of their dwelling. Greatest successes in the development of tools of biological methods and technologies of an assessment of surface water quality in real time. Essential advantage of bioindication of water quality by such tool is a possibility of an integrated assessment of biological effects of pollution on biota and also the expressness of such method and used approaches. In the report the practical experience of authors in biomonitoring and bioindication of an ecological condition of sea, brackish- and freshwater areas is discussed. Authors note that the method of non-invasive cardiac activity monitoring of selected invertebrates can be used not only for the advancement of biomonitoring, but also is useful in decision of general problems of comparative physiology of the invertebrates.

Keywords: benthic invertebrates, physiological state, heart rate monitoring, water quality assessment

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Authors: Lewis Mehl-Madrona, Barbara Mainguy, Patrick McFarlane

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Introduction: There are many risk factors for attempting suicide, including young age, “minority stress,” which would include Transgender and Gender Diverse orientations (TGD). The rate of TGD youths for suicide attempts is 3 times higher than heterosexual cis-gender youth. Half of TGD youth have seriously contemplated taking their own lives; of those, about half attempted suicide; and 18% of the TGD teenagers reported suicidal thoughts linked to their gender identity. Native American TGD have a six times higher suicide attempt rate. Conventional mental health has not generally helped these individuals. Stigma and discrimination contribute to healthcare disparities. Storytelling plays a crucial role in the development of human culture and individual identities. Sharing narrative artwork, creative writing, and personal stories allow people to build trust and to share their vulnerabilities. This helps people become aware of themselves in relation to others and gain a sense of comfort that their stories are similar; they may also be transformed in the process. Art provides a means to reach people who are otherwise difficult to engage in services. Methods: TGD individuals are recruited through a snowballing procedure. Following a life story interview, participants complete a scale of gender dysphoria, identification with conventional masculinity, patient-reported anxiety, and depression measure, and a quality-of-life scale. The interview completes the Columbia Suicide Scale. Following this, an artist and a therapist works with the participant to create a story related to their gender identity using the six-part story method. This story is then rendered to an artists’ book, which combines narrative with art (drawings, collage, computer images, etc.) and can take the form of a graphic novella, a zine, or a comic book. The pages can range from plain to ornate, as can the covers. Participants describe their process of making the books as the work unfolds and then participate in an exit interview at the completion of their book, remarking on what has changed for them and how the process affected them. Results: Preliminary results show high levels of suicidal thoughts among this population, as expected. Participants participate enthusiastically in the life story interview process and in the construction of a story related to gender identity. They enthusiastically participate in the studio process of putting their story into the form of a graphic novel, zine, or comic book. Participants reported feeling more comfortable with their TGD identity after the process and more able to resist negative judgments of family members and society. Suicidal thoughts diminish, and participants reported improved emotional wellbeing. Quantitative analysis of questionnaire data is underway Conclusions: A process in which narrative therapy is combined with art therapy shows promise for attracting and helping TGD individuals to reduce their risk for suicide without the stigma of going for mental health treatment. This process can be done outside of conventional mental health settings, on college and University campuses. This can provide an exciting alternative pathway for minority stressed and stigmatized individuals to engage in reflective, psychotherapeutic work without the trappings of psychotherapy or mental health treatment.

Keywords: minority stress, narrative process, artists' books, life story interview

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Authors: Tan Dexian Arthur, James Wei Ming Kwek, Ian Loh, Lee Tee Sin

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Statement of the Problem: Mucoceles most commonly affect the frontal sinus, which results from chronic obstruction of the sinus ostium or cystic dilatation of mucous glands with ductal obstruction. They are known to cause bony erosion of the sinus walls, which can lead to large defects. These defects were typically managed by obliteration or cranialization of the frontal sinus. Although short term outcomes of conservative management of significant posterior table defects from fractures are promising, there have been no studies on the long-term outcomes of large dehiscences in the posterior wall of the frontal sinus. Methodology & Findings : Computed Tomography (CT) Paranasal Sinuses images were analyzed and found complete spontaneous osteogenesis of a large dehiscent frontal sinus posterior wall, secondary to a large mucocele, 9 years from functional endoscopic sinus surgery with the defect managed conservatively. Conclusion & Significance: The dura is well known for its osteogenic properties. Prior studies have showed that dura could induce osteogenesis in cutaneous tissue in the absence of other central nervous system structures. It was also demonstrated that osteogenesis and chondrogenesis were possible in zygomatic fractures by transplanting neonatal dura grafts to the bony defects in rats. Extrapolating from these studies, the authors postulate that the presence of dura beneath the bony deformity of the posterior frontal sinus wall had likely initiated the osteogenesis and restored the bony defect in the patient. In our literature review, we did not find any reports of spontaneous osteogenesis of large frontal sinus defects. While our experience is incidental, it reinforces the osteogenetic potential of an intact dura and further highlights that selected large defects of the posterior wall of the frontal sinus can be conservatively managed.

Keywords: paranasal sinus mucocele, mucocele, osteogenesis, dehiscence

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Authors: Juan Carlos Rubio Romero, Francico Salguero Caparros, Virginia Herrera-Pérez

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No one is in the slightest doubt about the high levels of risk involved in work in the construction industry. They are even higher in structural construction work. The Critical Decision Method (CDM) is a semi-structured interview technique that uses cognitive tests to identify the different disturbances that workers have to deal with in their work activity. At present, the vision of safety focused on daily performance and things that go well for safety and health management is facing the new paradigm known as Resilience Engineering. The aim of this study has been to describe the variability in formwork labour on concrete structures in the construction industry and, from there, to find out the resilient attitude of workers to unexpected events that they have experienced during their working lives. For this purpose, a series of semi-structured interviews were carried out with construction employees with extensive experience in formwork labour in Spain by applying the Critical Decision Method. This work has been the first application of the Critical Decision Method in the field of construction and, more specifically, in the execution of structures. The results obtained show that situations categorised as unthought-of are identified to a greater extent than potentially unexpected situations. The identification during these interviews of both expected and unexpected events provides insight into the critical decisions made and actions taken to improve resilience in daily practice in this construction work. From this study, it is clear that it is essential to gain more knowledge about the nature of the human cognitive process in work situations within complex socio-technical systems such as construction sites. This could lead to a more effective design of workplaces in the search for improved human performance.

Keywords: resilience engineering, construction industry, unthought-of situations, critical decision method

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Authors: Marie-Josée Morneau

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A literacy-based approach, centred on the use of the language of instruction as a cognitive tool, can increase the L2 communication skills of French immersion students. Academic subject areas such as science and mathematics offer an authentic language learning context where students can become more proficient speakers while using specific vocabulary and language structures to learn, interact and communicate their reasoning, when provided the opportunities and guidance to do so. In this Canadian quasi-experimental study, the effects of teaching specific language elements during mathematic classes through literacy-based activities in Early French Immersion programming were compared between two Grade 7/8 groups: the experimental group, which received literacy-based teaching for a 6-week period, and the control group, which received regular teaching instruction. The results showed that the participants from the experimental group made more progress in their mathematical communication skills, which suggests that targeting L2 language as a cognitive tool can be beneficial to immersion learners who learn mathematic concepts and remind us that all L2 teachers are language teachers.

Keywords: mathematics, French immersion, literacy-based, oral communication, L2

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Authors: Eunice Tan

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The purpose of this presentation is to look at an alternative to the approach and methodologies of working with a child with special needs. The strength-based approach to education embodies a paradigm shift. It is a strategy to move away from a deficit-based methodology which inadvertently may lead to an extensive list of things that the child cannot do or is unable to do. Today, many parents of individuals with special needs are focused on the individual’s deficits rather than on his or her strengths. Even when parents recognise and identify their child’s savant strengths to be valuable and wish to develop their abilities, they face the challenge that there are insufficient programs committed to supporting the development and improvement of such abilities. What is a strength-based approach in education? A strength-based approach in education focuses on students' positive qualities and contributions to class instead of the skills and abilities they may not have. Many schools are focused on the child’s special educational needs rather than the whole child. Parents interviewed have said that they have to engage external tutors to help hone in on their child’s interests and strengths. The strength-based approach to writing statements encourages educators to find out: • What a child can do • What a child can do when he or she is given educational support • Learning more about children with special needs and their strengths and talents will broaden our understanding of how we can help them with language acquisition, social skills, as well as self-help and independence skills.

Keywords: special needs, strengths, and talents, alternative educational approach, strength based approach

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Authors: Atuhurra Jesse, N'guessan Yves-Roland Douha, Pabitra Lenka

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The detection of diseases within plants has attracted a lot of attention from computer vision enthusiasts. Despite the progress made to detect diseases in many plants, there remains a research gap to train image classifiers to detect the cacao swollen shoot virus disease or CSSVD for short, pertinent to cacao plants. This gap has mainly been due to the unavailability of high quality labeled training data. Moreover, institutions have been hesitant to share their data related to CSSVD. To fill these gaps, image classifiers to detect CSSVD-infected cacao plants are presented in this study. The classifiers are based on VGG16, ResNet50 and Vision Transformer (ViT). The image classifiers are evaluated on a recently released and publicly accessible KaraAgroAI Cocoa dataset. The best performing image classifier, based on ResNet50, achieves 95.39\% precision, 93.75\% recall, 94.34\% F1-score and 94\% accuracy on only 20 epochs. There is a +9.75\% improvement in recall when compared to previous works. These results indicate that the image classifiers learn to identify cacao plants infected with CSSVD.

Keywords: CSSVD, image classification, ResNet50, vision transformer, KaraAgroAI cocoa dataset

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Authors: Meseret Gebeyehu Yehuala

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Women represent the majority of urban farmers engaged in vegetable and fruit production in Bahir Dar, Ethiopia. We examine urban agriculture in Bahir Dar city in the context of disruptions caused by the civil war and COVID-19. The Sustainable Livelihoods Framework serves as a conceptual frame to explore the vulnerability context, the structural and institutional challenges faced by women, and how this impacts their livelihoods. A total of 25 urban women farmers and 6 key informants were involved in the study through explorative and structured interviews conducted in 2021. Observations and informal conversations during repeated visits provided deeper insights. In addition, key informants employed in civil service institutions and experts were interviewed. Data were analysed by applying qualitative content analysis by using Atlas tia software. Women report that they experience a lack of access to land, insecurity of tenure, irregular technical support and input provision by agricultural extension services, and lack of access to credit and formal marketplaces. The COVID-19 pandemic restrictions aggravated this situation by delaying agricultural extension offices’ provision of necessary inputs and disrupting food handling and storage leading to the loss of perishable products. Bombing in relation to the civil war has destroyed harvests and left women in fear of returning to their fields. Women stated that vegetable and fruit production could contribute to their incomes, household food supplies, and more diversified diets. However, the city municipal office has, so far, not committed to supporting urban agriculture as a livelihood strategy.

Keywords: urban agriculture, institutional challenges, Bahir Dar, sustainable livelihood framework

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Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

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The most aggressive form of brain tumor is called glioma. Glioma is kind of tumor that arises from glial tissue of the brain and occurs quite often. A fully automatic 2D-CNN model for brain tumor segmentation is presented in this paper. We performed pre-processing steps to remove noise and intensity variances using N4ITK and standard intensity correction, respectively. We used Keras open-source library with Theano as backend for fast implementation of CNN model. In addition, we used BRATS 2015 MRI dataset to evaluate our proposed model. Furthermore, we have used SimpleITK open-source library in our proposed model to analyze images. Moreover, we have extracted random 2D patches for proposed 2D-CNN model for efficient brain segmentation. Extracting 2D patched instead of 3D due to less dimensional information present in 2D which helps us in reducing computational time. Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.77 for complete, 0.76 for core, 0.77 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, LGG

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Authors: Duygu Dere, Mert Ergeneci, Kaan Gokcesu

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Google Trends data has gained increasing popularity in the applications of behavioral finance, decision science and risk management. Because of Google’s wide range of use, the Trends statistics provide significant information about the investor sentiment and intention, which can be used as decisive factors for corporate and risk management fields. However, an anomaly, a significant increase or decrease, in a certain query cannot be detected by the state of the art applications of computation due to the random baseline noise of the Trends data, which is modelled as an Additive white Gaussian noise (AWGN). Since through time, the baseline noise power shows a gradual change an adaptive thresholding method is required to track and learn the baseline noise for a correct classification. To this end, we introduce an online method to classify meaningful deviations in Google Trends data. Through extensive experiments, we demonstrate that our method can successfully classify various anomalies for plenty of different data.

Keywords: adaptive data processing, behavioral finance , convex optimization, online learning, soft minimum thresholding

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Authors: Junqi Zou

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As one of the world’s most tech-ready countries, Singapore has initiated the Smart Nation plan to harness the full power and potential of digital technologies to transform the way people live and work, through the more efficient government and business processes, to make the economy more productive. The key evolutions of digital technology transformation in healthcare and the increasing deployment of Internet of Things (IoTs), Big Data, AI/cognitive, Robotic Process Automation (RPA), Electronic Health Record Systems (EHR), Electronic Medical Record Systems (EMR), Warehouse Management System (WMS in the most recent decade have significantly stepped up the move towards an information-driven healthcare ecosystem. The advances in information technology not only bring benefits to patients but also act as a key force in changing management accounting in healthcare sector. The aim of this study is to investigate the impacts of digital technology transformation on Singapore’s healthcare sector from a management accounting perspective. Adopting a Balanced Scorecard (BSC) analysis approach, this paper conducted an exploratory case study of a newly launched Singapore public hospital, which has been recognized as amongst the most digitally advanced healthcare facilities in Asia-Pacific region. Specifically, this study gains insights on how the new technology is changing healthcare organizations’ management accounting from four perspectives under the Balanced Scorecard approach, 1) Financial Perspective, 2) Customer (Patient) Perspective, 3) Internal Processes Perspective, and 4) Learning and Growth Perspective. Based on a thorough review of archival records from the government and public, and the interview reports with the hospital’s CIO, this study finds the improvements from all the four perspectives under the Balanced Scorecard framework as follows: 1) Learning and Growth Perspective: The Government (Ministry of Health) works with the hospital to open up multiple training pathways to health professionals that upgrade and develops new IT skills among the healthcare workforce to support the transformation of healthcare services. 2) Internal Process Perspective: The hospital achieved digital transformation through Project OneCare to integrate clinical, operational, and administrative information systems (e.g., EHR, EMR, WMS, EPIB, RTLS) that enable the seamless flow of data and the implementation of JIT system to help the hospital operate more effectively and efficiently. 3) Customer Perspective: The fully integrated EMR suite enhances the patient’s experiences by achieving the 5 Rights (Right Patient, Right Data, Right Device, Right Entry and Right Time). 4) Financial Perspective: Cost savings are achieved from improved inventory management and effective supply chain management. The use of process automation also results in a reduction of manpower costs and logistics cost. To summarize, these improvements identified under the Balanced Scorecard framework confirm the success of utilizing the integration of advanced ICT to enhance healthcare organization’s customer service, productivity efficiency, and cost savings. Moreover, the Big Data generated from this integrated EMR system can be particularly useful in aiding management control system to optimize decision making and strategic planning. To conclude, the new digital technology transformation has moved the usefulness of management accounting to both financial and non-financial dimensions with new heights in the area of healthcare management.

Keywords: balanced scorecard, digital technology transformation, healthcare ecosystem, integrated information system

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Authors: Hyunbin Choi, Jihyeon Noh, Changwon Lim

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In this paper, we propose SiamMask++, an architecture that performs layer-wise aggregation and depth-wise cross-correlation and introduce multi-RPN module and multi-MASK module to improve EAO (Expected Average Overlap), a representative performance evaluation metric for Visual Object Tracking (VOT) challenge. The proposed architecture, SiamMask++, has two versions, namely, bi_SiamMask++, which satisfies the real time (56fps) on systems equipped with GPUs (Titan XP), and rf_SiamMask++, which combines mask refinement modules for EAO improvements. Tests are performed on VOT2016, VOT2018 and VOT2019, the representative datasets of Visual Object Tracking tasks labeled as rotated bounding boxes. SiamMask++ perform better than SiamMask on all the three datasets tested. SiamMask++ is achieved performance of 62.6% accuracy, 26.2% robustness and 39.8% EAO, especially on the VOT2018 dataset. Compared to SiamMask, this is an improvement of 4.18%, 37.17%, 23.99%, respectively. In addition, we do an experimental in-depth analysis of how much the introduction of features and multi modules extracted from the backbone affects the performance of our model in the VOT task.

Keywords: visual object tracking, video, deep learning, layer wise aggregation, Siamese network

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Authors: Sze Yee Lee

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The death of a sibling in childhood leads to significant impacts on both the personal and family development of the surviving siblings. Yet, the effects of sibling loss in Chinese societies such as Hong Kong have been inadequately documented in the literature. In particular, there is a gap in the literature about the long term impacts on surviving siblings. This paper explores the experience of adult siblings encountering siblings’ death during childhood with the use of in-depth interviews. Through thematic analysis and in-depth interviews, the author explores the impacts on surviving siblings’ emotions, coping styles, struggles and challenges, and personal development. Furthermore, the influences on family dynamics are explored thoroughly, including the changes in a family atmosphere, family roles, family relationships, family communication, and parenting styles. More importantly, the author identifies (i) existing continuing bonds, (ii) crying, (iii) adequate social support, (iv) hiding own emotions as a gesture of protecting parents as the crucial elements pertinent to surviving siblings’ successful adaptation in the face of sibling loss. In addition, 'child-centered' and 'family-centered' interventions for families with siblings' death in a Chinese context are discussed. With the use of age-appropriate language and children’s participation in the preparation of death and after-death arrangements, surviving siblings could be assisted in transforming bereavement into opportunities for growth. In addition, the bereaved family could better cope with grief with open communication platforms, adequate social support, and family education resources. Meanwhile, life-and-death education at both school and community levels could enhance the public’s awareness and understanding of the bereaved individuals to prevent creating further harm to them.

Keywords: children and adolescent bereavement, children-centered, family-centered, sibling’s death

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Authors: Bjorn Kierulf, Arun Chundru

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Over the past decade, collegiate rocketry teams have emerged across the country with various goals: space, liquid-fueled flight, etc. A critical piece of the development of knowledge within a club is the use of so-called "sounding rockets," whose goal is to take in-flight measurements that inform future rocket design. Common measurements include acceleration from inertial measurement units (IMU's), and altitude from barometers. With a properly tuned filter, these measurements can be used to find velocity, but are susceptible to noise, offset, and filter settings. Instead, velocity can be measured more directly and more instantaneously using a pitot tube, which operates by measuring the stagnation pressure. At supersonic speeds, an additional thermodynamic property is necessary to constrain the upstream state. One possibility is the stagnation temperature, measured by a thermocouple in the pitot tube. The routing of the pitot tube from the nosecone tip down to a pressure transducer is complicated by the nosecone's structure. Commercial-off-the-shelf (COTS) nosecones come with a removable metal tip (without a pitot tube). This provides the opportunity to make custom tips with integrated measurement systems without making the nosecone from scratch. The main design constraint is how the nosecone tip is held down onto the nosecone, using the tension in a threaded rod anchored to a bulkhead below. Because the threaded rod connects into a threaded hole in the center of the nosecone tip, the pitot tube follows a winding path, and the pressure fitting is off-center. Two designs will be presented in the paper, one with a curved pitot tube and a coaxial design that eliminates the need for the winding path by routing pressure through a structural tube. Additionally, three manufacturing methods will be presented for these designs: bound powder filament metal 3D printing, stereo-lithography (SLA) 3D printing, and traditional machining. These will employ three different materials, copper, steel, and proprietary resin. These manufacturing methods and materials are relatively low cost, thus accessible to student researchers. These designs and materials cover multiple use cases, based on how fast the sounding rocket is expected to travel and how important heating effects are - to measure and to avoid melting. This paper will include drawings showing key features and an overview of the design changes necessitated by the manufacture. It will also include a look at the successful use of these nosecone tips and the data they have gathered to date.

Keywords: additive manufacturing, machining, pitot tube, sounding rocketry

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Authors: Vitus Onyebuchim Onyemailu, Olive Obianuju Okalibe

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The study tried to examine relationship between exchange rate variations on the balance of payments in Nigeria from 1970 to 2012. Using time series on econometric measures such as Granger causality and ordinary least square (OLS), the study found that exchange rate movements especially the depreciation of naira has not contributed significantly on the balance of payments under the year of the study. The granger result conform the Marshall-Lerner short and long run prepositions that exchange rate devaluation enhances balance of payments. On disaggregation exchange rate granger causes current and capital account balances give the Nigeria data from 1970 to 2012. Overall in the long run OLS regression analysis, exchange rate on semi log functional form, exchange rate variation did not record significant effect on balance of payment equation. This height was also maintained in the current or trade balance which does not match the Marshall-Lerner. The capital account balance in reverse reported a significant impact of exchange rate variability on the capital account balance. Finally, on exchange rate determination equation, where many fundamentals were considered including lagged of exchange rate. Thus, the lagged of exchange rate recorded a positive and significant influence on the present exchange rate. This means that players in the financial markets usually out plays authority’s policy’s stances through their speculative tendencies. The work therefore, recommend that effort should be made by the authorities to providing enabling environment for production of goods and services to triumph in order to take advantages of steady devaluation of its currency. This is done by providing infrastructure, provision of science and technology. Thus, when this is done Nigeria would be able to have competitive power against the rest of the world.

Keywords: exchange rate variation, balance of payments, current account, capital account, Marshall-Lerner hypothesis

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Authors: Lule Basha, Eralda Gjika

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The exchange rate is one of the most important economic variables, especially for a small, open economy such as Albania. Its effect is noticeable in one country's competitiveness, trade and current account, inflation, wages, domestic economic activity, and bank stability. This study investigates the fluctuation of Albania’s exchange rates using monthly average foreign currency, Euro (Eur) to Albanian Lek (ALL) exchange rate with a time span from January 2008 to June 2021, and the macroeconomic factors that have a significant effect on the exchange rate. Initially, the Random Forest Regression algorithm is constructed to understand the impact of economic variables on the behavior of monthly average foreign currencies exchange rates. Then the forecast of macro-economic indicators for 12 months was performed using time series models. The predicted values received are placed in the random forest model in order to obtain the average monthly forecast of the Euro to Albanian Lek (ALL) exchange rate for the period July 2021 to June 2022.

Keywords: exchange rate, random forest, time series, machine learning, prediction

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Authors: Kristine Kalnica-Dorosenko, Aiga Svede

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Amblyopia or 'lazy eye' is impaired or dim vision without obvious defect or change in the eye. It is often associated with abnormal visual experience, most commonly strabismus, anisometropia or both, and form deprivation. The main task of amblyopia treatment is to ameliorate etiological factors to create a clear retinal image and, to ensure the participation of the amblyopic eye in the visual process. The treatment of amblyopia and eccentric fixation is usually associated with problems in the therapy. Eccentric fixation is present in around 44% of all patients with amblyopia and in 30% of patients with strabismic amblyopia. In Latvia, amblyopia is carefully treated in various clinics, but eccentricity diagnosis is relatively rare. Conflict which has developed relating to the relationship between the visual disorder and the degree of eccentric fixation in amblyopia should to be rethoughted, because it has an important bearing on the cause and treatment of amblyopia, and the role of the eccentric fixation in this case. Visuoscopy is the most frequently used method for determination of eccentric fixation. With traditional visuoscopy, a fixation target is projected onto the patient retina, and the examiner asks to look straight directly at the center of the target. An optometrist then observes the point on the macula used for fixation. This objective test provides clinicians with direct observation of the fixation point of the eye. It requires patients to voluntarily fixate the target and assumes the foveal reflex accurately demarcates the center of the foveal pit. In the end, by having a very simple method to evaluate fixation, it is possible to indirectly evaluate treatment improvement, as eccentric fixation is always associated with reduced visual acuity. So, one may expect that if eccentric fixation in amlyopic eye is found with visuoscopy, then visual acuity should be less than 1.0 (in decimal units). With occlusion or another amblyopia therapy, one would expect both visual acuity and fixation to improve simultaneously, that is fixation would become more central. Consequently, improvement in fixation pattern by treatment is an indirect measurement of improvement of visual acuity. Evaluation of eccentric fixation in the child may be helpful in identifying amblyopia in children prior to measurement of visual acuity. This is very important because the earlier amblyopia is diagnosed – the better the chance of improving visual acuity.

Keywords: amblyopia, eccentric fixation, visual acuity, visuoscopy

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Authors: Stephanie Ho

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This project utilizes principles derived from the Surrealist movement to prioritize creative and critical thinking in secondary English Language Arts (ELA). The implementation of Surrealist-style pedagogies within an ELA classroom will be rooted in critical, radical pedagogy, which addresses the injustices caused by economic-oriented educational systems. The use of critical pedagogy will enable the subversive artistic and political aims of Surrealism to be transmitted to a classroom context. Through aesthetic reading strategies, appreciative questioning and dialogue, students will actively critique the power dynamics which structure (and often restrict) their lives. Within the ELA domain, cost-effective approaches often replace the actual “arts” of ELA. This research will therefore explore how Surrealist-oriented pedagogies could restore imaginative freedom and deconstruct conceptual barriers (normative standards, curricular constraints, and status quo power relations) in secondary ELA. This research will also examine how Surrealism can be used as a political and pedagogical model to treat societal problems mirrored in ELA classrooms. The stakeholders are teachers, as they experience constant pressure within their practices. Similarly, students encounter rigorous, results-based pressures. These dynamics contribute to feelings of powerlessness, thus reinforcing a formulaic model of ELA. The ELA curriculum has potential to create laboratories for critical discussion and active movement towards social change. This proposed research strategy of Surrealist-oriented pedagogies could enable students to experiment with social issues and develop senses of agency and voice that reflect awareness of contemporary society while simultaneously building their ELA skills.

Keywords: arts-informed pedagogies, language arts, literature, surrealism

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Authors: Botirjon Kosimov

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This work sheds light on the reforms towards the independence of the judiciary in Uzbekistan, as well as issues of further ensuring judicial independence in the country based on international values, particularly the legal practice of the United States. In every democratic state infringed human rights are reinstated and violated laws are protected by the help of justice based on the strict principle of judicial independence. The realization of this principle in Uzbekistan has been paid much attention since the proclamation of its independence. In the country, a series of reforms have been implemented in the field of the judiciary in order to actualize the principle of judicial independence. Uzbekistan has been reforming the judiciary considering both international and national values and practice of foreign countries. While forming a democratic state based on civil society, Uzbekistan shares practice with the most developed countries in the world. The United States of America can be a clear example which is worth learning how to establish and ensure an independent judiciary. It seems that although Uzbekistan has reformed the judiciary efficiently, it should further reform considering the legal practice of the United States.

Keywords: dependent judges, independent judges, judicial independence, judicial reforms, judicial life tenure, obstacles to judicial independence

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Authors: Sevim Ugur, Cemile Kutmec Yilmaz, Omer Us, Sevdenur Koksaldi

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Aim: This study aims to investigate the effect of digital game playing and Internet addiction on perceived stress levels in university students. Method: The descriptive study was conducted through face-to-face interview method with a total of 364 university students studying at Aksaray University between November 15 and December 30, 2017. The research data were collected using personal information form, a questionnaire to determine the characteristics of playing digital game, the Internet addiction scale and the perceived stress scale. In the evaluation of the data, Mann-Whitney U test was used for two-group comparison of the sample with non-normal distribution, Kruskal-Wallis H-test was used in the comparison of more than two groups, and the Spearman correlation test was used to determine the relationship between Internet addiction and the perceived stress level. Results: It was determined that the mean age of the students participated in the study was 20.13 ± 1.7 years, 67.6% was female, 35.7% was sophomore, and 62.1% had an income 500 TL or less. It was found that 83.5% of the students use the Internet every day and 70.6% uses the Internet for 5 hours or less per day. Of the students, 12.4% prefers digital games instead of spending time outdoors, 8% plays a game as the first activity in leisure time, 12.4% plays all day, 15.7% feels anger when he/she is prevented from playing, 14.8% prefers playing games to get away from his/her problems, 23.4% had his/her school achievement affected negatively because of game playing, and 8% argues with family members due to the time spent for gaming. Students who play games on the computer for a long time were found to feel back pain (30.8%), headache (28.6%), insomnia (26.9%), dryness and pain in the eyes (26.6%), pain in the wrist (21.2%), feeling excessive tension and anger (16.2%), humpback (12.9), vision loss (9.6%) and pain in the wrist and fingers (7.4%). In our study, students' Internet addiction scale mean score was found to be 45.47 ± 16.1 and mean perceived stress scale score was 28.56 ± 2.7. A significant and negative correlation (p=0.037) was found between the total score of the Internet addiction scale and the total score of the perceived stress scale (r=-0.110). Conclusion: It was found in the study that Internet addiction and perceived stress of the students were at a moderate level and that there was a negative correlation between Internet addiction and perceived stress levels. Internet addiction was found to increase with the increasing perceived stress levels of students, and students were found to have health problems such as back pain, dryness in the eyes, pain, insomnia, headache, and humpback. Therefore, it is recommended to inform students about different coping methods other than spending time on the Internet to cope with the stress they perceive.

Keywords: digital game, internet addiction, student, stress level

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Authors: Theresa Zagers, Rita Guerra

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Most research investigating how receiving communities perceive, and experience migration has overlooked the potential role of subjective social class and social class identity in positive intergroup relations and social cohesion of migrants and host societies. The present study aimed to provide insights to understand this relationship and focused on three important features: prosocial behaviour, attitudes and emotions towards Muslim immigrants in Flanders, Belgium. Building on relative deprivation-gratification theory we examined the indirect relationships of subjective social class on prosocial behaviour/intentions, attitudes and emotions via relative deprivation (RD), as well as the moderator role of the importance of social class identity. 431 Belgian participants participated in an online survey study. Overall, our results supported the predicted indirect effect of subjective social class: the lower the subjective social class, the higher the perceptions of relative deprivation, which in turn is related to less prosocial behaviour intentions, and more negative attitudes and emotions towards immigrants. This indirect effect was, however, not moderated by the importance of social class identity. Interestingly, the direct effects of subjective social class showed a different pattern: when bypassing deprivation our results showed higher subjective social class was detrimental for intergroup relations (more negative attitudes and emotions), and that lower subjective social class was positively related to prosocial intentions for those identifying highly with their class identity. Overall, we gained valuable insights in the relationship of subjective social class and the three features of intergroup relations.

Keywords: social class, relative deprivation-gratification, prosocial behavior, attitudes, emotions, Muslim immigrants

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Authors: Nadia Masood Khan, Muhammad Salman Khan, Gul Muhammad Khan

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Cardiologists perform cardiac auscultation to detect abnormalities in heart sounds. Since accurate auscultation is a crucial first step in screening patients with heart diseases, there is a need to develop computer-aided detection/diagnosis (CAD) systems to assist cardiologists in interpreting heart sounds and provide second opinions. In this paper different algorithms are implemented for automated heart sound classification using unsegmented phonocardiogram (PCG) signals. Support vector machine (SVM), artificial neural network (ANN) and cartesian genetic programming evolved artificial neural network (CGPANN) without the application of any segmentation algorithm has been explored in this study. The signals are first pre-processed to remove any unwanted frequencies. Both time and frequency domain features are then extracted for training the different models. The different algorithms are tested in multiple scenarios and their strengths and weaknesses are discussed. Results indicate that SVM outperforms the rest with an accuracy of 73.64%.

Keywords: pattern recognition, machine learning, computer aided diagnosis, heart sound classification, and feature extraction

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Authors: Jaspreet Singh, Gurvinder Singh, Prabhsimran Singh, Rajinder Singh, Prithvipal Singh, Karanjeet Singh Kahlon, Ravinder Singh Sawhney

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Morphological evaluation of Indian languages is one of the burgeoning fields in the area of Natural Language Processing (NLP). The evaluation of a language is an eminent task in the era of information retrieval and text mining. The extraction and classification of knowledge from text can be exploited for sentiment analysis and morphological evaluation. This study coalesce morphological evaluation and sentiment analysis for the task of classification of farmer suicide cases reported in Punjab state of India. The pre-processing of Punjabi text involves morphological evaluation and normalization of Punjabi word tokens followed by the training of proposed model using deep learning classification on Punjabi language text extracted from online Punjabi news reports. The class-wise accuracies of sentiment prediction for four negatively oriented classes of farmer suicide cases are 93.85%, 88.53%, 83.3%, and 95.45% respectively. The overall accuracy of sentiment classification obtained using proposed framework on 275 Punjabi text documents is found to be 90.29%.

Keywords: deep neural network, farmer suicides, morphological processing, punjabi text, sentiment analysis

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Authors: Turuganti Venkateswarlu, Jagadeesh Anmala

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Excessive runoffs from various non-point source land uses, and other point sources are rapidly contaminating the water quality of streams in the Upper Green River watershed, Kentucky, USA. It is essential to maintain the stream water quality as the river basin is one of the major freshwater sources in this province. It is also important to understand the water quality parameters (WQPs) quantitatively and qualitatively along with their important features as stream water is sensitive to climatic events and land-use practices. In this paper, a model was developed for predicting one of the significant WQPs, Fecal Coliform (FC) from precipitation, temperature, urban land use factor (ULUF), agricultural land use factor (ALUF), and forest land-use factor (FLUF) using Random Forest (RF) algorithm. The RF model, a novel ensemble learning algorithm, can even find out advanced feature importance characteristics from the given model inputs for different combinations. This model’s outcomes showed a good correlation between FC and climate events and land use factors (R2 = 0.94) and precipitation and temperature are the primary influencing factors for FC.

Keywords: water quality, land use factors, random forest, fecal coliform

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Authors: Eftah Bte. Moh Hj Abdullah, Izazol Binti Idris, Abd Aziz Bin Abd Shukor

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This study aims to identify the understanding expectations of school administrators concerning school assessment. The researcher utilized a qualitative descriptive study on 19 administrators from three secondary schools in the North Kinta district. The respondents had been interviewed on their understanding expectations of school assessment using the focus group discussion method. Overall findings showed that the administrators’ understanding expectations of school assessment was weak; especially in terms of content focus, articulation across age and grade, transparency and fairness, as well as the pedagogical implications. Findings from interviews indicated that administrators explained their understanding expectations of school assessment from the aspect of school management, and not from the aspect of instructional leadership or specifically as assessment leaders. The study implications from the administrators’ understanding expectations may hint at the difficulty of the administrators to function as assessment leaders, in order to reduce their focus as manager, and move towards their primary role in the process of teaching and learning. The administrator, as assessment leaders, would be able to reach assessment goals via collaboration in identifying and listing teacher assessment competencies, how to construct assessment capacity, how to interpret assessment correctly, the use of assessment and how to use assessment information to communicate confidently and effectively to the public.

Keywords: assessment leaders, assessment goals, instructional leadership, understanding expectation of assessment

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Authors: V. Saccà, A. Sarica, F. Novellino, S. Barone, T. Tallarico, E. Filippelli, A. Granata, P. Valentino, A. Quattrone

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The work aim was to evaluate how well Random Forest (RF) and Support Vector Machine (SVM) algorithms could support the early diagnosis of Multiple Sclerosis (MS) from resting-state functional connectivity data. In particular, we wanted to explore the ability in distinguishing between controls and patients of mean signals extracted from ICA components corresponding to 15 well-known networks. Eighteen patients with early-MS (mean-age 37.42±8.11, 9 females) were recruited according to McDonald and Polman, and matched for demographic variables with 19 healthy controls (mean-age 37.55±14.76, 10 females). MRI was acquired by a 3T scanner with 8-channel head coil: (a)whole-brain T1-weighted; (b)conventional T2-weighted; (c)resting-state functional MRI (rsFMRI), 200 volumes. Estimated total lesion load (ml) and number of lesions were calculated using LST-toolbox from the corrected T1 and FLAIR. All rsFMRIs were pre-processed using tools from the FMRIB's Software Library as follows: (1) discarding of the first 5 volumes to remove T1 equilibrium effects, (2) skull-stripping of images, (3) motion and slice-time correction, (4) denoising with high-pass temporal filter (128s), (5) spatial smoothing with a Gaussian kernel of FWHM 8mm. No statistical significant differences (t-test, p < 0.05) were found between the two groups in the mean Euclidian distance and the mean Euler angle. WM and CSF signal together with 6 motion parameters were regressed out from the time series. We applied an independent component analysis (ICA) with the GIFT-toolbox using the Infomax approach with number of components=21. Fifteen mean components were visually identified by two experts. The resulting z-score maps were thresholded and binarized to extract the mean signal of the 15 networks for each subject. Statistical and machine learning analysis were then conducted on this dataset composed of 37 rows (subjects) and 15 features (mean signal in the network) with R language. The dataset was randomly splitted into training (75%) and test sets and two different classifiers were trained: RF and RBF-SVM. We used the intrinsic feature selection of RF, based on the Gini index, and recursive feature elimination (rfe) for the SVM, to obtain a rank of the most predictive variables. Thus, we built two new classifiers only on the most important features and we evaluated the accuracies (with and without feature selection) on test-set. The classifiers, trained on all the features, showed very poor accuracies on training (RF:58.62%, SVM:65.52%) and test sets (RF:62.5%, SVM:50%). Interestingly, when feature selection by RF and rfe-SVM were performed, the most important variable was the sensori-motor network I in both cases. Indeed, with only this network, RF and SVM classifiers reached an accuracy of 87.5% on test-set. More interestingly, the only misclassified patient resulted to have the lowest value of lesion volume. We showed that, with two different classification algorithms and feature selection approaches, the best discriminant network between controls and early MS, was the sensori-motor I. Similar importance values were obtained for the sensori-motor II, cerebellum and working memory networks. These findings, in according to the early manifestation of motor/sensorial deficits in MS, could represent an encouraging step toward the translation to the clinical diagnosis and prognosis.

Keywords: feature selection, machine learning, multiple sclerosis, random forest, support vector machine

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Authors: S. Gordon

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Dual language immersion is growing fast in language teaching today. This study provides an overview and evaluation of the different models of Dual language immersion programs in US K-12 schools. First, the paper provides a brief current literature review on the theory of Dual Language Immersion (DLI) in Second Language Acquisition (SLA) studies. Second, examples of several types of DLI language teaching models in US K-12 public schools are presented (including 50/50 models, 90/10 models, etc.). Third, we focus on the unique example of DLI education in the state of Utah, a successful, growing program in K-12 schools that includes: French, Chinese, Spanish, and Portuguese. The project investigates the theory and practice particularly of the case of public elementary and secondary school children that study half their school day in the L1 and the other half in the chosen L2, from kindergarten (age 5-6) through high school (age 17-18). Finally, the project takes the observations of Utah French DLI elementary through secondary programs as a case study. To conclude, we look at the principal challenges, pedagogical objectives and outcomes, and important implications for other US states and other countries (such as France currently) that are in the process of developing similar language learning programs.

Keywords: dual language immersion, second language acquisition, language teaching, pedagogy, teaching, French

Procedia PDF Downloads 153