Search results for: practice learning

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: Kamran Yazdanbakhsh, Somayeh Mahmoudi

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Three reasons make good use of the decision theory in medicine: 1. Increased medical knowledge and their complexity makes it difficult treatment information effectively without resorting to sophisticated analytical methods, especially when it comes to detecting errors and identify opportunities for treatment from databases of large size. 2. There is a wide geographic variability of medical practice. In a context where medical costs are, at least in part, by the patient, these changes raise doubts about the relevance of the choices made by physicians. These differences are generally attributed to differences in estimates of probabilities of success of treatment involved, and differing assessments of the results on success or failure. Without explicit criteria for decision, it is difficult to identify precisely the sources of these variations in treatment. 3. Beyond the principle of informed consent, patients need to be involved in decision-making. For this, the decision process should be explained and broken down. A decision problem is to select the best option among a set of choices. The problem is what is meant by "best option ", or know what criteria guide the choice. The purpose of decision theory is to answer this question. The systematic use of decision models allows us to better understand the differences in medical practices, and facilitates the search for consensus. About this, there are three types of situations: situations certain, risky situations, and uncertain situations: 1. In certain situations, the consequence of each decision are certain. 2. In risky situations, every decision can have several consequences, the probability of each of these consequences is known. 3. In uncertain situations, each decision can have several consequences, the probability is not known. Our aim in this article is to show how decision theory can usefully be mobilized to meet the needs of physicians. The decision theory can make decisions more transparent: first, by clarifying the data systematically considered the problem and secondly by asking a few basic principles should guide the choice. Once the problem and clarified the decision theory provides operational tools to represent the available information and determine patient preferences, and thus assist the patient and doctor in their choices.

Keywords: decision making, medicine, treatment strategies, patient

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Authors: Shahryar Eslamitabar

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Currently, the internet plays an important role in the various scientific, commercial and service practices. Thanks to information and communication technology, the healthcare industry via the internet, generally known as cyber-medicine, can offer professional medical service in a wider geographical area. Having some appealing benefits such as convenience in offering healthcare services, improved accessibility to the services, enhanced information exchange, cost-effectiveness, time-saving, etc. Tele-health has increasingly developed innovative models of healthcare delivery. However, it presents many potential hazards to cyber-patients, inherent in the use of the system. First, there are legal issues associated with the communication and transfer of information on the internet. These include licensure, malpractice, liabilities and jurisdictions as well as privacy, confidentiality and security of personal data as the most important challenge brought about by this system. Additional items of concern are technological and ethical. Although, there are some rules to deal with pitfalls associated with cyber-medicine practices in the USA and some European countries, yet for all developments, it is being practiced in a legal vacuum in many countries. In addition to the domestic legislations to deal with potential problems arisen from the system, it is also imperative that some international or regional agreement should be developed to achieve the harmonization of laws among countries and states. This article discusses some implications posed by the practice of cyber-medicine in the healthcare system according to the experience of some developed countries using a comparative study of laws. It will also review the status of tele-health laws in Iran. Finally, it is intended to pave the way to outline a plan for countries like Iran, with newly-established judicial system for health laws, to develop appropriate regulations through providing some recommendations.

Keywords: tele-health, cyber-medicine, telemedicine, criminal laws, legislations, time-saving

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Authors: Enze Zhang

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One of the most challenging steps in implementing virtual water content (VWC) analysis of crops is to get properly the total volume of consumptive water use (CWU) and, therefore, the choice of a reliable crop CWU estimation method. In practice, lots of previous researches obtaining CWU of crops follow a classical procedure for calculating crop evapotranspiration which is determined by multiplying reference evapotranspiration by appropriate coefficient, such as crop coefficient and water stress coefficients. However, this manner of calculation requires lots of field experimental data at point scale and more seriously, when current growing conditions differ from the standard conditions, may easily produce deviation between the calculated CWU and the actual CWU. Since evapotranspiration caused by crop planting always plays a vital role in surface water-energy balance in an agricultural region, this study decided to alternatively estimates crop evapotranspiration by Budyko framework. After brief introduce the development process of Budyko framework. We choose a modified Budyko framework under unsteady-state to better evaluated the actual CWU and apply it in an agricultural irrigation area in North China Plain which rely on underground water for irrigation. With the agricultural statistic data, this calculated CWU was further converted into VWC and its subdivision of crops at the annual scale. Results show that all the average values of VWC, VWC_blue and VWC_green show a downward trend with increased agricultural production and improved acreage. By comparison with the previous research, VWC calculated by Budyko framework agree well with part of the previous research and for some other research the value is greater. Our research also suggests that this methodology and findings may be reliable and convenient for investigation of virtual water throughout various agriculture regions of the world.

Keywords: virtual water content, Budyko framework, consumptive water use, crop evapotranspiration

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Authors: Slwa Al-Hammad

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Adaptation studies have been closely aligned to translation studies as both deal with the process of rendering the meaning from one culture to another. These two disciplines are related to each other, but the theories are still being developed. This research aims to fill this gap and provide a contribution to the growing discipline of adaptation studies through a theoretical perspective while investigating how different cultural interpretations of adaptation influence the final literary product. This research focuses on the theoretical concepts of Barthes’s death of the author and Benjamin’s afterlife of the text in translation, which is believed to lead to the birth of the adapter in a literary work. That is, in adaptation, the ‘death’ of the author allows for the ‘birth’ of the adapter, offering them all the creative possibilities of authorship. It also explores the differences between the meanings of adaptation in the West and the Arab world through the analysis of adapted texts in Arabic initially deriving from the European and American literature of the 19th and 20th centuries. The methodology of this thesis is based upon qualitative literary analysis, in which original and adapted works are compared and contrasted, with the additional insights of literary and adaptation theories and prior scholarship. The main works discussed are the Arabic adaptations of William Faulkner’s novels. The analysis is guided by theories of adaptation studies to help in explaining the concepts of relocating, recreating, and rewriting in the process of adaptation. It draws on scholarship on adaptations to inquire into the status of the adapted texts in relation to the original texts. Also, these theories prove that adaptation is the process that is used to transfer text from source to adapted text, not some other analytical practice. Through the textual analysis, concepts of the death of the author and the birth of the adapter will be illustrated, as will the roles of the adapter and the task of rendering works for a different culture, and the understanding of adaptation and Arabization in Arabic literature.

Keywords: adaptation, Arabization, authorship, recreating, relocating

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Authors: Haris Karnezi, Kevin Tierney

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Cognitive Behaviour Drama is a research-based intervention model that brought together the science of psychology with the art form of drama to create an unobtrusive and exciting approach that would provide children on the higher end of the autism spectrum the motivation to explore the rules of social interaction and develop competencies associated with communicative success. The method involves engaging the participants in exciting fictional scenarios and encouraging them to seek various solutions on a number of problems that will lead them to an understanding of causal relationships and how a different course of action may lead to a different outcome. The sessions are structured to offer opportunities to the participants to practice target behaviours and understand the functions they serve. The study involved six separate interventions and employed both single case and group designs. Overall 8 children aged between 6 to 13 years, diagnosed with ASD participated in the study. Outcomes were measured using theory of mind tests, executive functioning tests, behavioural observations, pre and post intervention standardised social competence questionnaires for parents and teachers. Collectively, the results indicated positive changes in the self esteem and behaviour of all eight participants. In particular, improvements in the ability to solve theory of mind tasks were noted in the younger group; and qualitative improvements in social communication, in terms of verbal (content) and non verbal expression (body posture, vocal expression, fluency, eye contact, reduction of ritualistic mannerisms) were noted in the older group. The need for reliable impact measures to assess the effectiveness of the model in generating global changes in the participants’ behaviour outside the therapeutic context was identified.

Keywords: autism, drama, intervention, social skills

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Authors: Mark Herman Sumagang Potoy

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State of the City Address (SOCA) is a speech, modelled after the State of the Nation Address, given not as mandated by law but usually a matter of practice or tradition delivered before the chief executive’s constituents. Through this, the general public is made to know the performance of the local government unit and its agenda for the coming year. Therefore, it is imperative for SOCAs to clearly convey its message and carry out the myriad function of enlightening its readers which could be achieved through the proper use of reference. Anaphora and cataphora are the two major types of reference; the former refer back to something that has already been mentioned while the latter points forward to something which is yet to be said. This paper seeks to identify the types of reference employed on the SOCAs from 2014 to 2016 of Hon. Rosalina Garcia Jalosjos, Mayor of Dapitan City and look into how the references contribute to the clarity of the message of the text. The qualitative method of research is used in this study through an in-depth analysis of the corpus. As soon as the copies of the SOCAs are secured from the Office of the City Mayor, they are then analyzed using documentary technique categorizing the types of reference as to anaphora and cataphora, counting each of these types and describing the implications of the dominant types used in the addresses. After a thorough analysis, it is found out that the two reference types namely, anaphora and cataphora are both employed on the three SOCAs, the former being used more frequently than the latter accounting to 80% and 20% of actual usage, respectively. Moreover, the use of anaphors and cataphora on the three addresses helps in conveying the message clearly because they primarily become aids to avoid the repetition of the same element in the text especially when there wasn’t a need to emphasize a point. Finally, it is recommended that writers of State of the City Addresses should have a vast knowledge on how reference should be used and the functions they take in the text since this is a vital tool to clearly transmit a message. Moreover, English teachers should explicitly teach the proper usage of anaphora and cataphora, as instruments to develop cohesion in written discourse, to enable students to write not only with sense but also with fluidity in tying utterances together.

Keywords: anaphora, cataphora, reference, State of the City Address

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Authors: Meral Melek Unver

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This paper aims to explore ways to help English as a Foreign Language (EFL) learners notice and revise voice in English and raise their awareness of when and how to use active and passive voice to convey meaning in their written and spoken work. Because passive voice is commonly preferred in certain genres such as academic essays and news reports, despite the current trends promoting active voice, it is essential for learners to be fully aware of the meaning, use and form of passive voice to better communicate. The participants in the study are 22 EFL learners taking a one-year intensive English course at a university, who will receive English medium education (EMI) in their departmental studies in the following academic year. Data from students’ written and oral work was collected over a four-week period and the misuse or inaccurate use of passive voice was identified. The analysis of the data proved that they failed to make sensible decisions about when and how to use passive voice partly because the differences between their mother tongue and English and because they were not aware of the fact that active and passive voice would not alternate all the time. To overcome this, a Test-Teach-Test shape lesson, as opposed to a Present-Practice-Produce shape lesson, was designed and implemented to raise their awareness of the decisions they needed to make in choosing the voice and help them notice the meaning and use of passive voice through concept checking questions. The results first suggested that awareness raising activities on the meaning and use of voice in English would be beneficial in having accurate and meaningful outcomes from students. Also, helping students notice and renotice passive voice through carefully designed activities would help them internalize the use and form of it. As a result of the study, a number of activities are suggested to revise and notice passive voice as well as a short questionnaire to help EFL teachers to self-reflect on their teaching.

Keywords: voice in English, test-teach-test, passive voice, English language teaching

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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: Suvorov Vasyl, Filipchuk Viktor

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Developmental Dysplasia of the Hip (DDH) is a frequent pathology in pediatric orthopedist’s practice. Neglected or residual cases of DDH in walking patients are usually treated using pelvic osteotomies. Plastic changes take place in hinge points due to acetabulum reorientation during surgery. Classically described hinge points and a traditional division of pelvic osteotomies on reshaping and reorientation are currently debated. The purpose of this article was to evaluate biomechanical changes during the most commonly used pelvic osteotomies (Salter, Dega, Pemberton) for DDH treatment in pediatric patients. Methods: virtual pelvic models of 2- and 6-years old patients were created, material properties were assigned, pelvic osteotomies were simulated and biomechanical changes were evaluated using finite element analysis (FEA). Results: it was revealed that the patient's age has an impact on pelvic bones and cartilages density (in younger patients the pelvic elements are more pliable - p<0.05). Stress distribution after each of the abovementioned pelvic osteotomy was assessed in 2- and 6-years old patients’ pelvic models; hinge points were evaluated. The new term "restriction point" was introduced, which means a place where restriction of acetabular deformity correction occurs. Pelvic ligaments attachment points were mainly these restriction points. Conclusions: it was found out that there are no purely reshaping and reorientation pelvic osteotomies as previously believed; the pelvic ring acts as a unit in carrying out the applied load. Biomechanical overload of triradiate cartilage during Salter osteotomy in 2-years old patient and in 2- and 6-years old patients during Pemberton osteotomy was revealed; overload of the posterior cortical layer in the greater sciatic notch in 2-years old patient during Dega osteotomy was revealed. Level of Evidence – Level IV, prognostic.

Keywords: developmental dysplasia of the hip, pelvic osteotomy, finite element analysis, hinge point, biomechanics

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Authors: Ya-Mei Chen

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Online crowdsourced translation, an innovative translation practice brought by Web 2.0 technologies and the democratization of information, has become increasingly popular in the Internet era. Carried out by grass-root internet users, crowdsourced translation contains fundamentally different features from its off-line traditional counterpart, such as voluntary participation and parallel collaboration. To better understand such a participatory and collaborative nature, this paper will use the online Chinese translation project of Global Voices as a case study to investigate the following issues: (1) the changes in volunteer translators’ and reviewers’ motivations for participation, (2) translators’ and reviewers’ use of translation strategies and (3) the correlations of translators’ and reviewers’ motivations and strategies with the organizational mission, the translation style guide, the translator-reviewer interaction, the mediation of the translation platform and various types of capital within the translation field. With an aim to systematically explore the above three issues, this paper will collect both quantitative and qualitative data and then draw upon Engestrom’s activity theory and Bourdieu’s field theory as a theoretical framework to analyze the data in question. An online anonymous questionnaire will be conducted to obtain the quantitative data. The questionnaire will contain questions related to volunteer translators’ and reviewers’ backgrounds, participation motivations, translation strategies and mutual relations as well as the operation of the translation platform. Concerning the qualitative data, they will come from (1) a comparative study between some English news texts published on Global Voices and their Chinese translations, (2) an analysis of the online discussion forum associated with Global Voices’ Chinese translation project and (3) the information about the project’s translation mission and guidelines. It is hoped that this research, through a detailed sociological analysis of a cause-driven crowdsourced translation project, can enable translation researchers and practitioners to adequately meet the translation challenges appearing in the digital age.

Keywords: crowdsourced translation, global voices, motivation, translation strategies

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Authors: Coulibaly Fatoumata, Gragnon Biego, Aka N. David, Mbari K. Benjamin, Soro Y. René, Ndiaye Jean-louis

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Poultry is nowadays one of the most consumed sources of protein, and its livestock represents one of the few opportunities for savings, investment and protection against risk. It provides income for the most vulnerable sections of society, in particular, women (70%) and children who mainly practice this breeding. A study was conducted in the commune of Korhogo at the level of 52 poultry farms, the objective of which was to know the epidemiological situation of parasitism external and internal poultry in order to contribute to the improvement of the health status of modern poultry farms in the said commune. The method described by OIE (2005), consisting of using the standard formula (n = δ2*p*(1-p) *c /i2), made it possible to calculate the size of the sample. Then, samples of droppings and ectoparasites were taken from the affected farms. After analysis and identification, two (2) species of mallophagous lice, including Menopon gallinae (50%) and Menacanthus stramineus (33%) and a species of bug Cimex lectularius (17%) were highlighted. The laying hens were more infested than broilers. Regarding gastrointestinal parasites, different species (six) have been identified: Trichostrongylus tenuis (17%), Syngamus trachea (19%), Heterakis sp (10%), Ascaridia sp (17%), Raillietina sp (8%) and Eimeria sp (29%). In addition, coccidiosis (Eimeria sp) proved to be the dominant pathology representing 67% of pathologies in broiler farms and 33% in poultry farms. The presence of these parasitoses in these modern farms constitutes a constraint major contribution to productivity and their development In view of all these difficulties, proposals have been made in order to participate in the establishment of a good prophylaxis program (health and medical). In addition, the Ivorian government, with the support of veterinarians, must interfere more in the organization of the health monitoring of traditional chickens and poultry in general through supervision and training in order to preserve public health ( animal, human and environmental health).

Keywords: gastrointestinal parasites, ectoparasites, pathologies, poultry, korhogo.

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Authors: Saha Naseri

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Introduction/Objective: Son preference, a preference for sons over daughters, is a practice deeply-rooted in gender inequality that is widespread in many societies and across different religions and cultures. In this study, we are aiming to study the effects of son preference on fertility outcomes (birth interval and current contraceptive use) in Afghanistan, where have been perceived with high rates of son preference. The objectives of the study are to examine the association between the sex of the previous child and the duration of the subsequent birth interval and to evaluate the effect of son preference on current contraceptive use. Methodology: Afghanistan Demographic and Health Survey (DHS) (2015) was used to study the impact of son preference on fertility outcomes among married women. The data collected from 28,661 on currently-married women, aged between 15 and 49 years who have at least one child, have used to conduct this quantitative study. Outcomes of interest are birth interval and current contraceptive use. Simple and multiple regression analysis have been conducted to assess the effect of son preference on these fertility outcomes. Results: The present study has highlighted that son preference somehow exists among married women in Afghanistan. It is indicated that the sex of the first birth is significantly associated with the succeeding birth interval. Having a female child as the first baby was associated with a shorter average succeeding birth interval by 1.8 months compared to a baby boy (p-value = 0.000). For the second model, the results identified that women who desire for more sons have 7% higher odds to be current contraceptive user compared to those who have no preference (p-value = 0.03). The latter results do not indicate the son preference. However, one limitation for this result was the timeliness of the questions asked since contraceptive use in the current time was asked along with a question on ‘future’ desired sex composition. Moreover, women may have just given birth and want to reach a certain time span of birth interval before planning for another child, even if it was a boy, which might have affected the results. Conclusion: Overall, this study has demonstrated that there is a positive relationship between son preference and one main fertility behaviors, birth interval. The second fertility outcome, current contraceptive use, was not a good indicator to measure son preference. Based on the finding, recommendations will be made for appropriate interventions addressing gender norms and related fertility decisions.

Keywords: Afghanistan, birth interval, contraceptive, son preference

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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: Najla Alhkalaf

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The focus of this study is answering the following question: How do e-government services in Bahrain support the productivity of SMEs? This study examines the current E-government function in enhancing SME productivity in Bahrain through analysing the efficiency of e- government by viewing its facilitators and barriers from the perspective of different stakeholders. The study aims to identify and develop best practice guidelines with the end-goal of creating a standardised channel of communication between e-government and SMEs that fulfil the requirement of SME owners, and thus achieve the prime objective of e-government. E-government services for SMEs have been offered in Bahrain since 2005. However, the current services lack the required mechanism for SMEs to fully take advantage of these services because of lagging communication between service provider and end-user. E-government employees believe that a lack of awareness and trust are the main stumbling block, whereas the SME owners believe that there is a lack of sufficiency in the content and efficiency provided through e- services. A questionnaire has been created based on a pilot study that highlighted the main indicators of e-government efficiency and SMEs productivity as well as previous studies conducted on this subject. This allowed for quantitative data to be extracted. Also interviews were conducted with SME owners and government employees from both case studies, which formed the qualitative data for this study. The findings portray that both the service provider and service receiver largely agree on the existence of most of the technical and administrative barriers. However, the data reflects a level of dissatisfaction from the SME side, which contradicts with the perceived level of satisfaction from the government employees. Therefore, the data supports the argument that assures the existence of a communication gap between stakeholders. To this effect, this research would help build channels of communication between stakeholders, and then induces a plan unlocking the potential of e-government application. The conclusions of this study will help devise an optimised E-government strategy for Bahrain.

Keywords: e-government, SME, e-services, G2B, government employees' perspective, entrepreneurs' perspective, enterprise

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Authors: Sireen Irsheid

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Despite concerted efforts to improve education attainment with progress in recent years, student achievement and attainment remain among the most significant challenges for school districts across the United States. Many scholars have argued that students who do not complete high school do not drop out of school voluntarily but are ‘pushed out’ of schools through multiple mechanisms related to structural and socioeconomic barriers, behavioral health challenges, pedagogical practices, and administrative procedures. Extant literature has shown that living in historically disadvantaged neighborhoods or attending under-resourced schools exacerbates student-level risk factors for grade retention and school pushout. Most efforts to respond to the school pushout phenomenon have focused on individual characteristics of students, with relatively little attention to addressing these multiple system-level characteristics related to perpetuating inequities. This study is built on a growing body of social justice-oriented research concerned with the systemic influences that shape the experiences and mental health challenges of young people. Specifically, this study examined how young people who have been experiencing education inequities make meaning and navigate the structural factors related to neighborhood and school disinvestment and access to resources and supports, and their risk for school pushout. Furthermore, schools as political, cultural, and ideologically reproductive spaces often serve as sites of resistance and can support students who are impacted by educational inequity. Study findings provide education, neighborhood, school psychology, social work practice, and policy considerations.

Keywords: education policy, mental health, school prison nexus, school pushout, structural trauma

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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: M. Pushparani, A. Sagaya

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Embedded systems have emerged as important elements in various domains with extensive applications in automotive, commercial, consumer, healthcare and transportation markets, as there is emphasis on intelligent devices. On the other hand, Business Intelligence (BI) has also been extensively used in a range of applications, especially in the agriculture domain which is the area of this research. The aim of this research is to create a framework for Embedded Weight Comparison Algorithm with Business Intelligence (EWCA-BI). The weight comparison algorithm will be embedded within the plantation management system and the weighbridge system. This algorithm will be used to estimate the weight at the site and will be compared with the actual weight at the plantation. The algorithm will be used to build the necessary alerts when there is a discrepancy in the weight, thus enabling better decision making. In the current practice, data are collected from various locations in various forms. It is a challenge to consolidate data to obtain timely and accurate information for effective decision making. Adding to this, the unstable network connection leads to difficulty in getting timely accurate information. To overcome the challenges embedding is done on a portable device that will have the embedded weight comparison algorithm to also assist in data capture and synchronize data at various locations overcoming the network short comings at collection points. The EWCA-BI will provide real-time information at any given point of time, thus enabling non-latent BI reports that will provide crucial information to enable efficient operational decision making. This research has a high potential in bringing embedded system into the agriculture industry. EWCA-BI will provide BI reports with accurate information with uncompromised data using an embedded system and provide alerts, therefore, enabling effective operation management decision-making at the site.

Keywords: embedded business intelligence, weight comparison algorithm, oil palm plantation, embedded systems

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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: 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: Naser Shagerdi Esmaeli, Mohsen Hamidpour, Parisa Hasankhani Tehrani

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Background And Objective: Haematopoietic stem cell transplant is a potentially curative treatment option in various benign and malignant haematological diseases. Patients undergoing stem cell transplant procedure require blood transfusion on a daily basis. Currently, there is paucity of data from developing countries on transfusion practices. This audit was undertaken to determine the consumption of packed red blood cells (PRBCs) transfusion in the bone marrow transplant unit of the Shahid Ghazi Tabatabaei Hospital, Tabriz, Iran. Subjects And Methods: A retrospective audit was conducted for packed red cell transfusion ordering practice over a period from March 2017 to march 2018. All consecutive patients admitted for stem cell transplant procedure for various underlying diseases were included. Outcome measures used in this study were (i) cross match to transfusion (C: T) ratio and (ii) transfusion trigger. Results: During the study period, n=13 patients underwent a haematopoietic stem cell transplant. There were n=10 males and n=3 females. One patient was less than 15 years of age, while rests were adults. Median age±SD was 26.5±14.5 years (12∼54 years). The underlying diagnosis included Aplastic anemia (n=4), Thalassemia major (n=1), Multiple Myeloma (n=3), Acute leukemia (n=3), Hodgkin's lymphoma (n=1), PRCA (n=1). Grand total consumption of PRBCs during the study period was 204, while 258 products were crossmatch. The C:T ratio was 1.26. The transfusion trigger was Hb level of less than 8 gr/dl. Conclusion: The results of our BMT unit indicate that the C:T ratio and transfusion trigger is comparable to the international criteria and pioneer country in BMT transplantation. Also, we hope that our blood consumption become less than it is now.

Keywords: blood consumption, C: T ratio, PRBCs, stem cell transplant, tabriz, Iran

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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: Nirali Shukla, Neel Shah

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The World Bank Institute (WBI) is undertaking a review of government interventions aimed at facilitating sustainable investment in public private partnerships (PPPs) in various under developed countries. The study presents best practice for applying financial model to make PPPs financially viable. The lessons presented here, if properly implemented, can help countries use limited funds to attract more private investment, get more infrastructure built and, as a result, achieve greater economic growth. The four countries Brazil, Colombia, Mexico, and India in total develop an average of nearly US$50 billion in PPPs per year. There are a range of policies and institutional arrangements governments use to provide subsidies to PPPs. For example, some countries have created dedicated agencies, or ‘funds’, capitalized with money from the national budget to manage and allocate subsidies. Other countries have established well-defined policies for appropriating subsidies on an ad hoc basis through an annual budget process. In this context, subsidies are direct fiscal contributions or grants paid by the government to a project when revenues from user fees are insufficient to cover all capital and operating costs while still providing private investors with a reasonable rate of return. Without subsidies, some infrastructure projects that would provide economic or social gains, but are not financially viable, would go undeveloped. But the Financial model of BOLT (PPP) model described in this study suggests that it is most feasible option rather than going for subsidy schemes for making infrastructure projects financially viable. The major advantage for implementing this model is the government money is saved and can be used for other projects as well as the private investors are getting better rate of return than subsidized schemes.

Keywords: PPP, BOLT, subsidy schemes, financial model

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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

Procedia PDF Downloads 226