Search results for: traditional learning approach

Authors: Prakash Singh

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The focus of this study is on the use of the SWEAT analysis approach to determine how effectively a school, as an organization, has implemented its curriculum. To gauge the feelings of the teaching staff, unstructured interviews were employed in this study, asking the participants for their ideas and opinions on each of the three identified aspects of the school: instructional materials, media and technology; teachers’ professional competencies; and the curriculum. This investigation was based on the five key components of the SWEAT model: strengths, weaknesses, expectations, abilities, and tensions. The findings of this exploratory study evoke the significance of the SWEAT achievement model as a tool for strategic analysis to be undertaken in any organization. The findings further affirm the usefulness of this analytical tool for human resource development. Employees have expectations, but competency gaps in their professional abilities may hinder them from fulfilling their tasks in terms of their job description. Also, tensions in the working environment can contribute to their experiences of tobephobia (fear of failure). The SWEAT analysis approach detects such shortcomings in any organization and can therefore culminate in the development of programmes to address such concerns. The strategic SWEAT analysis process can provide a clear distinction between success and failure, and between mediocrity and excellence in organizations. However, more research needs to be done on the effectiveness of the SWEAT analysis approach as a strategic analytical tool.

Keywords: SWEAT analysis, strategic analysis, tobephobia, competency gaps

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Authors: Azad Khalid, Sifa Dogan

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Because of its persistence in conventional treatment plants and broad prevalence in water bodies, the pharmaceutical chemical carbamazepine (CBZ) has been suggested as an anthropogenic marker to evaluate water quality. This study provides a thorough examination of the origins and occurrences of CBZ in water bodies, as well as the drug's toxicological effects and laws. Given CBZ's well-documented negative consequences on the human body when used medicinally, cautious monitoring in water is advised. CBZ residues in drinking water may enter embryos and newborns via intrauterine exposure or breast-feeding, causing congenital abnormalities and/or neurodevelopmental issues over time. The insufficiency of solo solutions was shown after an in-depth technical study of traditional and sophisticated treatment technologies. Nanofiltration and reverse osmosis membranes are more successful at removing CBZ than traditional activated sludge and membrane bioreactor techniques. Recent research has shown that severe chemical cleaning, which is essential to prevent membrane fouling, may lower long-term removal efficiency. Furthermore, despite the efficacy of activated carbon adsorption and advanced oxidation processes, a few issues such as chemical cost and activated carbon renewal must be carefully examined. Individual technology constraints lead to the benefits of combined and hybrid systems, namely the heterogeneous advanced oxidation process.

Keywords: carbamazepine, occurrence, toxicity, conventical treatment, advanced oxidation process (AOPs)

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Authors: Binder Hans

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Cancer is no longer seen as solely a genetic disease where genetic defects such as mutations and copy number variations affect gene regulation and eventually lead to aberrant cell functioning which can be monitored by transcriptome analysis. It has become obvious that epigenetic alterations represent a further important layer of (de-)regulation of gene activity. For example, aberrant DNA methylation is a hallmark of many cancer types, and methylation patterns were successfully used to subtype cancer heterogeneity. Hence, unraveling the interplay between different omics levels such as genome, transcriptome and epigenome is inevitable for a mechanistic understanding of molecular deregulation causing complex diseases such as cancer. This objective requires powerful downstream integrative bioinformatics methods as an essential prerequisite to discover the whole genome mutational, transcriptome and epigenome landscapes of cancer specimen and to discover cancer genesis, progression and heterogeneity. Basic challenges and tasks arise ‘beyond sequencing’ because of the big size of the data, their complexity, the need to search for hidden structures in the data, for knowledge mining to discover biological function and also systems biology conceptual models to deduce developmental interrelations between different cancer states. These tasks are tightly related to cancer biology as an (epi-)genetic disease giving rise to aberrant genomic regulation under micro-environmental control and clonal evolution which leads to heterogeneous cellular states. Machine learning algorithms such as self organizing maps (SOM) represent one interesting option to tackle these bioinformatics tasks. The SOMmethod enables recognizing complex patterns in large-scale data generated by highthroughput omics technologies. It portrays molecular phenotypes by generating individualized, easy to interpret images of the data landscape in combination with comprehensive analysis options. Our image-based, reductionist machine learning methods provide one interesting perspective how to deal with massive data in the discovery of complex diseases, gliomas, melanomas and colon cancer on molecular level. As an important new challenge, we address the combined portrayal of different omics data such as genome-wide genomic, transcriptomic and methylomic ones. The integrative-omics portrayal approach is based on the joint training of the data and it provides separate personalized data portraits for each patient and data type which can be analyzed by visual inspection as one option. The new method enables an integrative genome-wide view on the omics data types and the underlying regulatory modes. It is applied to high and low-grade gliomas and to melanomas where it disentangles transversal and longitudinal molecular heterogeneity in terms of distinct molecular subtypes and progression paths with prognostic impact.

Keywords: integrative bioinformatics, machine learning, molecular mechanisms of cancer, gliomas and melanomas

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Authors: Ayala Kobo-Greenhut, Amos Notea, Izhar Ben-Shlomo

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In R&D projects, there is no doubt about the need to change a current concept to an alternative one over time (i.e., concept leaping). Concept leaping is required since with most R&D projects uncertainty is present as they take place in dynamic environments. Despite the importance of concept leaping when needed, R&D teams may fail to do so (i.e., frozen concept). This research suggests a possible reason why frozen concept happens in the framework of quality engineering and control engineering. We suggest that frozen concept occurs since concept determines the derived plan and its implementation may be considered as equivalent to a closed-loop process, and is subject to the problem of not recognizing gaps as failures. We suggest that although implementing quality practices into an R&D project’s routine has many advantages, it intensifies the frozen concept problem since working according to quality practices relates to exploitation of learning behavior, while leaping to a new concept relates to exploring learning behavior.

Keywords: closed loop, control engineering, design, leaping, frozen concept, quality engineering, quality practices

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Authors: Farhad Asadi, Mohammad Javad Mollakazemi

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In this paper, Bayesian online inference in models of data series are constructed by change-points algorithm, which separated the observed time series into independent series and study the change and variation of the regime of the data with related statistical characteristics. variation of statistical characteristics of time series data often represent separated phenomena in the some dynamical system, like a change in state of brain dynamical reflected in EEG signal data measurement or a change in important regime of data in many dynamical system. In this paper, prediction algorithm for studying change point location in some time series data is simulated. It is verified that pattern of proposed distribution of data has important factor on simpler and smother fluctuation of hazard rate parameter and also for better identification of change point locations. Finally, the conditions of how the time series distribution effect on factors in this approach are explained and validated with different time series databases for some dynamical system.

Keywords: time series, fluctuation in statistical characteristics, optimal learning, change-point algorithm

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Authors: Sheila Shahidi

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UV protection by fabrics has recently become a focus of great interest, particularly in connection with environmental degradation or ozone layer depletion. Fabrics provide simple and convenient protection against UV radiation (UVR), but not all fabrics offer sufficient UV protection. To describe the degree of UVR protection offered by clothing materials, the ultraviolet protection factor (UPF) is commonly used. UV-protective fabric can be generated by application of a chemical finish using normal wet-processing methodologies. However, traditional wet-processing techniques are known to consume large quantities of water and energy and may lead to adverse alterations of the bulk properties of the substrate. Recently, usage of plasmas to generate physicochemical surface modifications of textile substrates has become an intriguing approach to replace or enhance conventional wet-processing techniques. In this research work the effect of plasma treatment on UV protection properties of fabrics was investigated. DC magnetron sputtering was used and the parameters of plasma such as gas type, electrodes, time of exposure, power and, etc. were studied. The morphological and chemical properties of samples were analyzed using Scanning Electron Microscope (SEM) and Furrier Transform Infrared Spectroscopy (FTIR), respectively. The transmittance and UPF values of the original and plasma-treated samples were measured using a Shimadzu UV3101 PC (UV–Vis–NIR scanning spectrophotometer, 190–2, 100 nm range). It was concluded that, plasma which is an echo-friendly, cost effective and dry technique is being used in different branches of the industries, and will conquer textile industry in the near future. Also it is promising method for preparation of UV protection textile.

Keywords: fabric, plasma, textile, UV protection

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Authors: Lizhu Y. Davis, Gretchen Higginbottom, Vang Vang

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This presentation explores the adoption of library resources to engage students in a Visual Merchandising course during the 2016 spring semester. This study was a cross-disciplinary collaboration between the Fashion Merchandising Program and the Madden Library at California State University, Fresno. The goal of the project was to explore and assess the students’ use of library resources as a part of the Affordable Learning Solutions Initiative, a California State University (CSU) Office of the Chancellor Program that enables faculty to choose and provide high-quality, free or low-cost educational materials for their students. Students were interviewed afterwards and the results were generally favorable and provided insight into how students perceive and use library resources to support their research needs. This study reveals an important step in examining how open educational resources impact student learning.

Keywords: collaboration, library resources, open educational resources, visual merchandising

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Authors: Maryam Kiani

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In order to enhance the efficiency and stability of an electrocatalyst for formic acid electro-oxidation reaction (FAOR), we developed a method to create Pt/Ni nanoparticles with carbon black. These nanoparticles were prepared using a simple impregnation reduction technique. During the observation, it was found that the nanoparticles had a spherical shape. Additionally, the average particle size remained consistent, falling within the range of about 4 nm. This approach aimed to obtain a loaded Pt-based electrocatalyst that would exhibit improved performance and stability when used in FAOR applications. By utilizing the impregnation reduction method and incorporating Ni nanoparticles along with Pt, we sought to enhance the catalytic properties of the material. By incorporating Ni atoms into the Pt structure, the electronic properties of Pt are modified, resulting in a delay in the chemisorption of harmful CO intermediate species. This modification also promotes the dehydrogenation pathway of the formic acid oxidation reaction (FAOR). Through electrochemical analysis, it has been observed that the Pt3Ni-C catalyst exhibits enhanced performance in FAOR compared to traditional Pt catalysts. This means that the addition of Ni atoms improves the efficiency and effectiveness of the Pt3Ni-C catalyst in facilitating the FAOR process. Overall, the utilization of these alloy nanoparticles as electrocatalysts represents a significant advancement in fuel cell technology.

Keywords: electrocatalyst, impregnation reduction method, formic acid electro-oxidation reaction, fuel cells

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Authors: Jorge A. Ruiz-Vanoye, Ocotlán Díaz-Parra, Alejandro Fuentes-Penna, Daniel Vélez-Díaz, Edith Olaco García

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In this paper, we present the use of the discriminant analysis to select evolutionary algorithms that better solve instances of the vehicle routing problem with time windows. We use indicators as independent variables to obtain the classification criteria, and the best algorithm from the generic genetic algorithm (GA), random search (RS), steady-state genetic algorithm (SSGA), and sexual genetic algorithm (SXGA) as the dependent variable for the classification. The discriminant classification was trained with classic instances of the vehicle routing problem with time windows obtained from the Solomon benchmark. We obtained a classification of the discriminant analysis of 66.7%.

Keywords: Intelligent Transportation Systems, data-mining techniques, evolutionary algorithms, discriminant analysis, machine learning

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Authors: Liubov Magerramova, Eugene Kratt, Pavel Presniakov

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A detailed analysis has been performed for several schemes of Gas Turbine Wheels production based on additive and powder technologies including metal, ceramic, and stereolithography 3-D printing. During the process of development and debugging of gas turbine engine components, different versions of these components must be manufactured and tested. Cooled blades of the turbine are among of these components. They are usually produced by traditional casting methods. This method requires long and costly design and manufacture of casting molds. Moreover, traditional manufacturing methods limit the design possibilities of complex critical parts of engine, so capabilities of Powder Metallurgy Techniques (PMT) were analyzed to manufacture the turbine wheel with air-cooled blades. PMT dramatically reduce time needed for such production and allow creating new complex design solutions aimed at improving the technical characteristics of the engine: improving fuel efficiency and environmental performance, increasing reliability, and reducing weight. To accelerate and simplify the blades manufacturing process, several options based on additive technologies were used. The options were implemented in the form of various casting equipment for the manufacturing of blades. Methods of powder metallurgy were applied for connecting the blades with the disc. The optimal production scheme and a set of technologies for the manufacturing of blades and turbine wheel and other parts of the engine can be selected on the basis of the options considered.

Keywords: additive technologies, gas turbine engine, powder technology, turbine wheel

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Authors: Ola Hall, Ibrahim Wahab, Thorsteinn Rognvaldsson, Mattias Ohlsson

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The subfield of poverty and welfare estimation that applies machine learning tools and methods on satellite imagery is a nascent but rapidly growing one. This is in part driven by the sustainable development goal, whose overarching principle is that no region is left behind. Among other things, this requires that welfare levels can be accurately and rapidly estimated at different spatial scales and resolutions. Conventional tools of household surveys and interviews do not suffice in this regard. While they are useful for gaining a longitudinal understanding of the welfare levels of populations, they do not offer adequate spatial coverage for the accuracy that is needed, nor are their implementation sufficiently swift to gain an accurate insight into people and places. It is this void that satellite imagery fills. Previously, this was near-impossible to implement due to the sheer volume of data that needed processing. Recent advances in machine learning, especially the deep learning subtype, such as deep neural networks, have made this a rapidly growing area of scholarship. Despite their unprecedented levels of performance, such models lack transparency and explainability and thus have seen limited downstream applications as humans generally are apprehensive of techniques that are not inherently interpretable and trustworthy. While several studies have demonstrated the superhuman performance of AI models, none has directly compared the performance of such models and human readers in the domain of poverty studies. In the present study, we directly compare the performance of human readers and a DL model using different resolutions of satellite imagery to estimate the welfare levels of demographic and health survey clusters in Tanzania, using the wealth quintile ratings from the same survey as the ground truth data. The cluster-level imagery covers all 608 cluster locations, of which 428 were classified as rural. The imagery for the human readers was sourced from the Google Maps Platform at an ultra-high resolution of 0.6m per pixel at zoom level 18, while that of the machine learning model was sourced from the comparatively lower resolution Sentinel-2 10m per pixel data for the same cluster locations. Rank correlation coefficients of between 0.31 and 0.32 achieved by the human readers were much lower when compared to those attained by the machine learning model – 0.69-0.79. This superhuman performance by the model is even more significant given that it was trained on the relatively lower 10-meter resolution satellite data while the human readers estimated welfare levels from the higher 0.6m spatial resolution data from which key markers of poverty and slums – roofing and road quality – are discernible. It is important to note, however, that the human readers did not receive any training before ratings, and had this been done, their performance might have improved. The stellar performance of the model also comes with the inevitable shortfall relating to limited transparency and explainability. The findings have significant implications for attaining the objective of the current frontier of deep learning models in this domain of scholarship – eXplainable Artificial Intelligence through a collaborative rather than a comparative framework.

Keywords: poverty prediction, satellite imagery, human readers, machine learning, Tanzania

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Authors: Briante Barretto, Haley Carreon, Anesha-Maelene Ignacio

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This research paper explores the dynamic process of cultural resilience within the context of the modern tourism of two traditional island communities (Bali, Indonesia and Guam, Micronesia). It asks the question: How do indigenous people hold on to their foundational values that define their culture while moving forward in the modern world? Both Bali and Guam serve as famous destinations for tourists from all over the world, with millions of visitors on an annual basis. Both are continually being shaped in profound ways by the forces of modernity through globalization. And both are demonstrating cultural resilience while striving to find creative ways to sustain, preserve and strengthen their values and traditions within the context of a thriving modern tourist economy. This research paper, drawing on ethnographic methodologies, and in particular participant observation and in-depth interviews, explores the many challenges both communities face and the strategies and approaches they are learning to employ that help promote sustainable tourism while contributing to cultural preservation. Drawing on the insights gained from field work in both island communities, as well as the growing literature in this field study, the paper posits important lessons that can guide and inform indigenous communities that are being drawn into the global tourism market. One powerful idea emerges in the research and one that seems to guide and shape tourism policy both indigenous communities - that this current generation should be thought of as the ancestors of future generations, and thus they have a weighty responsibility to continue to learn and strive to sustain and preserve their cultures and traditions, their natural environments, and spiritual foundations for the future.

Keywords: bali, culture, environment, guam, tourism, values

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Authors: Yao-Hong Tsai

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This paper presents a weighted approach to unconstrained iris recognition. Nowadays, commercial systems are usually characterized by strong acquisition constraints based on the subject’s cooperation. However, it is not always achievable for real scenarios in our daily life. Researchers have been focused on reducing these constraints and maintaining the performance of the system by new techniques at the same time. With large variation in the environment, there are two main improvements to develop the proposed iris recognition system. For solving extremely uneven lighting condition, statistic based illumination normalization is first used on eye region to increase the accuracy of iris feature. The detection of the iris image is based on Adaboost algorithm. Secondly, the weighted approach is designed by Gaussian functions according to the distance to the center of the iris. Furthermore, local binary pattern (LBP) histogram is then applied to texture classification with the weight. Experiment showed that the proposed system provided users a more flexible and feasible way to interact with the verification system through iris recognition.

Keywords: authentication, iris recognition, adaboost, local binary pattern

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Authors: Nkeiruka Queendarline Nwaizugbu

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The use of social media and mobile devices has become acceptable in virtually all areas of today’s world. Hence, this study is a survey that was carried out to find out if students and lecturers in public universities in Rivers State use social networking for educational purposes. The sample of the study comprised of 240 students and 99 lecturers from the University of Port Harcourt and the Rivers State University of science and Technology. The study had five research questions, two hypotheses and the instrument for data collection was a 4-point Likert-type rating scale questionnaire. The data was analysed using mean, standard deviation and z-test. The findings gotten from the analysed data shows that students participate in social networking using different types of web applications but they hardly use them for educational purposes. Some recommendations were also made.

Keywords: internet access, mobile learning, participation, social media, social networking, technology

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Authors: Yuri Katz, Kun Liu, Arunram Atmacharan

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Due to illiquidity, mispricing on Credit Markets is inevitable. This creates huge challenges to banks and investors as they seek to find new ways of risk valuation and portfolio management in a post-credit crisis world. Here, we analyze the difference in behavior of the spread-to-maturity in investment and high-yield categories of US corporate bonds between 2014 and 2023. Deviation from the theoretical dependency of this measure in the universe under study allows to identify multiple cases of mispriced credit risk. Remarkably, we observe mispriced bonds in both categories of credit ratings. This identification is supported by the application of the state-of-the-art machine learning model in more than 90% of cases. Noticeably, the ML-driven model-based forecasting of a category of bond’s credit ratings demonstrate an excellent out-of-sample accuracy (AUC = 98%). We believe that these results can augment conventional valuations of credit portfolios.

Keywords: credit risk, credit ratings, bond pricing, spread-to-maturity, machine learning

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Authors: Dawn Tsang

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This paper aims at synthesizing the difficulties in cognitive processes faced by translation majors in mainland China. The purpose is to develop possible solutions and innovation in terms of translation pedagogy, curriculum reform, and syllabus design. This research will base its analysis on students’ instant feedback and interview after training in translation and interpreting courses, and translation faculty’s teaching experiences. This research will take our translation majors as the starting point, who will be one of the focus groups. At present, our Applied Translation Studies Programme is offering translation courses in the following areas: practical translation and interpreting, translation theories, culture and translation, and internship. It is a four-year translation programme, and our students would start their introductory courses since Semester 1 of Year 1. The medium of instruction of our College is solely in English. In general, our students’ competency in English is strong. Yet in translation and especially interpreting classes, no matter it is students’ first attempt or students who have taken university English courses, students find class practices very challenging, if not mission impossible. Their biggest learning problem seems to be weakening cognitive processes in terms of lack of intercultural competence, incomprehension of English language and foreign cultures, inadequate aptitude and slow reaction, and inapt to utilize one’s vocabulary bank etc. This being so, the research questions include: (1) What specific and common cognitive difficulties are students facing while learning translation and interpreting? (2) How to deal with such difficulties, and what implications can be drawn on curriculum reform and syllabus design in translation? (3) How significant should cognitive study be placed on translation curriculum, i.e., the proportion of cognitive study in translation/interpreting courses and in translation major curriculum? and (4) What can we as translation educators do to maximize teaching and learning effectiveness by incorporating the latest development of cognitive study?. We have collected translation students’ instant feedback and conduct interviews with both students and teaching staff, in order to draw parallels as well as distinguishing from our own current teaching practices at United International College (UIC). We have collected 500 questionnaires for now. The main learning difficulties include: poor vocabulary bank, lack of listening and reading comprehension skills in terms of not fully understanding the subtext, aptitude in translation and interpreting etc. This being so, we propose to reform and revitalize translation curriculum and syllabi to address to these difficulties. The aim is to maximize teaching effectiveness in translation by addressing the above-mentioned questions with a special focus on cognitive difficulties faced by translation majors.

Keywords: cognitive difficulties, teaching and learning effectiveness, translation curriculum reform, translation pedagogy

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Authors: Shieh Shiow-fang

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Superstitious thoughts or actions often occur during athletic competitions. Often "superstitious rituals" have a positive impact on the performance of competitive athletes. Athletes affirm the many psychological benefits of religious beliefs mostly in a positive way. Method: By snowball sampling, we recruited 10 experienced competitive athletes as participants. We used in-person and online one-to-one in-depth interview to collect their experiences about sport superstition. The total interview time was 795 minutes. We analyzed the raw data with the grounded theory processes suggested by Strauss and Corbin (1990). Results: The factors affecting athlete performance are ritual beliefs, taboo awareness, learning norms, and spontaneous attribution behaviors. Conclusion: We concluded that sports superstition reflects several psychological implications. The analysis results of this paper can provide another research perspective for the future study of sports superstition behavior.

Keywords: superstition, taboo awareness, learning norms, competitive athlete

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Authors: Kan Yu, Khui Hung Lee, Eben Afrifa-Yamoah, Jing Guo, Katrina Harrison, Jack Goldblatt, Nicholas Pachter, Jitian Xiao, Guicheng Brad Zhang

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Background and Significance of the Study: Congenital Heart Defects (CHDs) are the most common malformation at birth and one of the leading causes of infant death. Although the exact etiology remains a significant challenge, epigenetic modifications, such as DNA methylation, are thought to contribute to the pathogenesis of congenital heart defects. At present, no existing DNA methylation biomarkers are used for early detection of CHDs. The existing CHD diagnostic techniques are time-consuming and costly and can only be used to diagnose CHDs after an infant was born. The present study employed a machine learning technique to analyse genome-wide methylation data in children with and without CHDs with the aim to find methylation biomarkers for CHDs. Methods: The Illumina Human Methylation EPIC BeadChip was used to screen the genome‐wide DNA methylation profiles of 24 infants diagnosed with congenital heart defects and 24 healthy infants without congenital heart defects. Primary pre-processing was conducted by using RnBeads and limma packages. The methylation levels of top 600 genes with the lowest p-value were selected and further investigated by using a random forest approach. ROC curves were used to analyse the sensitivity and specificity of each biomarker in both training and test sample sets. The functionalities of selected genes with high sensitivity and specificity were then assessed in molecular processes. Major Findings of the Study: Three genes (MIR663, FGF3, and FAM64A) were identified from both training and validating data by random forests with an average sensitivity and specificity of 85% and 95%. GO analyses for the top 600 genes showed that these putative differentially methylated genes were primarily associated with regulation of lipid metabolic process, protein-containing complex localization, and Notch signalling pathway. The present findings highlight that aberrant DNA methylation may play a significant role in the pathogenesis of congenital heart defects.

Keywords: biomarker, congenital heart defects, DNA methylation, random forest

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Authors: Feng Shih-Jen, Chiang Yi-Hua, Yang Min-Chih

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After going through mass production and contract manufacturing phases, under the global consumption trend, Taiwan’s traditional industry has turned to creative design, research and development to gain recognition in the consumer market, build competitiveness in the global market and further promote the products from Taiwan’s traditional industry. Taichung City is rich in cultural creative resources, outperforming other counties/cities in originality, creative talents, cultural taste, art/culture participation and global marketing. As the result this has created a diversified and vibrant cultural market in Taichung, giving Taichung the highest potential as a cultural creative city. This research, through the project by Taichung Cultural Creative Industry Promotion Office, has built an exchange platform for the cultural creative industry in central Taiwan. The platform will promote exchanges of creative ideas in the cultural creative industry in Taiwan as well as industrial transformation and brings more value for the industry. This study also proposes the idea of “Taichung Cultural Creative Exhibition” Therefore, this study was conducted in Taiwan, Taichung 10 Creative Zone Exhibition, which is divided into four stages counseling. Respectively, of the first order: the cultural creative Zone specialty shops offer; The second stage is the industrial settlement discussions and counseling workshops in the ground; The third stage of consultation for the recruitment of the cultural creative businesses separate estate; The fourth stage is the story of the build cultural and creative industry. Hope through periodic counseling, handling Taichung 10 Creative Zone Exhibition.

Keywords: cultural creative industry, counseling, Taichung, Taiwan's creative zones

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Authors: Farhad Alizadeh, Alireza Faregh Gharamaleki, Mojtaba Jalilzadeh, Houshang Gholami, Ali Akhoundzadeh

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This study presented hybrid pre-processing approach along with a conceptual model to enhance the accuracy of river discharge prediction. In order to achieve this goal, Ensemble Empirical Mode Decomposition algorithm (EEMD), Discrete Wavelet Transform (DWT) and Mutual Information (MI) were employed as a hybrid pre-processing approach conjugated to Least Square Support Vector Machine (LSSVM). A conceptual strategy namely multi-station model was developed to forecast the Souris River discharge more accurately. The strategy used herein was capable of covering uncertainties and complexities of river discharge modeling. DWT and EEMD was coupled, and the feature selection was performed for decomposed sub-series using MI to be employed in multi-station model. In the proposed feature selection method, some useless sub-series were omitted to achieve better performance. Results approved efficiency of the proposed DWT-EEMD-MI approach to improve accuracy of multi-station modeling strategies.

Keywords: river stage-discharge process, LSSVM, discrete wavelet transform, Ensemble Empirical Decomposition Mode, multi-station modeling

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Authors: Joann Douziech

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Individuals with intellectual and developmental disabilities (IDD) possess characteristics that present both challenges and gifts. Individuals with IDD require and are worthy of intentional, strategic, and specialized support throughout their lifespan to ensure optimum quality-of-life outcomes. The current global advocacy movement advancing the rights of individuals with IDD emphasizes a high degree of choice over life decisions. For some individuals, this degree of choice results in a variety of negative health and well-being outcomes. Improving the quality of life outcomes requires the combination of a commitment to the rights of the individual with a responsibility to provide support and choice commensurate with individual capacity. A belief that individuals with IDD are capable of learning and they are worthy of being taught provides the foundation for a holistic model of support throughout their lifespan. This model is based on three pillars of engineering the environment, promoting skill development and maintenance, and staff support. In an ever-changing world, supporting quality of life requires attention to moments, phases, and changes in stages throughout the lifespan. Balancing these complexities with strategic, responsive, and dynamic interventions enhances the quality of life of individuals with ID throughout their lifespan.

Keywords: achieving optimum quality of life, comprehensive support, lifespan approach, philosophy and pedagogy

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Authors: Auwal Ibrahim Amba

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Bilingualism is the use/existence of two languages in the repertoire of an individual or a community. This linguistic phenomenon may encourage the use of Bilingual Education/Instruction for the teaching of English as a Second Language. Bilingual Education is the teaching of academic content in two languages in most cases simultaneously in multilingual/bilingual communities. This study is an attempt at investigating the impact of Bilingual Education for the teaching of English as a Second Language. The study examines the performance of students in English language examinations in two selected secondary schools that employ Monolingual and Bilingual Education respectively. The schools: Demonstration Secondary School and Higher Islamic Studies Secondary School are public schools that exist side by side at A.D.Rufa’i College of Education, Legal and General Studies Misau, Bauchi State, Nigeria. The choice of the two schools is deliberate because of their existence in the same learning environment, the same public status and bein managed by the same administration. The only difference lies in the use of Bilingual Education for classroom instruction by the former and Monolingual Education by the latter. While Demonstration Secondary School uses English Language as the only Language of instruction, Higher Islamic Studies Secondary School employs English and Arabic for classroom instruction. The study employs qualitative research methods for the collection, presentation and analysis of data. Purposive sampling is employed in selecting students of Senior Secondary School 3 (SS3) from each school as the only participants in the research and a questionnaire was administered on fifty students each in addition to analyzing and comparing the students’ performance based on the Final Certificate Examinations Results. The findings of this study reveal that Bilingual Education slows the rate of learning English as a Second Language and affects learning proficiency. The study recommends the intensive use of the Target Language (English) for the teaching of English as a Second Language. It suggests the adequate use of Language Laboratory, constant listening of international English media organizations like British Broadcasting Corporation (BBC), practical communicative engagement of learners in the Target Language in classroom and outside among other strategies for effective learning.

Keywords: bilingualism, bilingual education, target language, second language

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Authors: Joy Johnbest Egbo

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The study was designed to investigate the relative effectiveness of inquiry role approach and expository instructional methods in fostering students’ retention in chemistry. Two research questions were answered and three null hypotheses were formulated and tested at 0.05 level of significance. A quasi-experimental (the non-equivalent pretest, posttest control group) design was adopted for the study. The population for the study comprised all senior secondary school class two (SS II) students who were offering Chemistry in single sex schools in Enugu Education Zone. The instrument for data collection was a self-developed Chemistry Retention Test (CRT). Relevant data were collected from a sample of one hundred and forty–one (141) students drawn from two secondary schools (1 male and 1 female schools) using simple random sampling technique. A reliability co-efficient of 0.82 was obtained for the instrument using Kuder Richardson formular20 (K-R20). Mean and Standard deviation scores were used to answer the research questions while two–way analysis of covariance (ANCOVA) was used to test the hypotheses. The findings showed that the students taught with Inquiry role approach retained the chemistry concept significantly higher than their counterparts taught with expository method. Female students retained slightly higher than their male counterparts. There is significant interaction between instructional packages and gender on Chemistry students’ retention. It was recommended, among others, that teachers should be encouraged to employ the use of Inquiry-role approach more in the teaching of chemistry and other subjects in general. By so doing, students’ retention of the subject could be increased.

Keywords: inquiry role approach, retention, exposition method, chemistry

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Authors: Edgar Mauricio Ruiz Osuna, Claudia Yaneth Herrera Bolivar, Sandra Liliana Gomez Vasquez

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The increasing needs of professionals with skills in software development in industry are incremental, therefore, the relevance of an educational process in line with the strengthening of these competencies, are part of the responsibilities of universities with careers related to the area of Informatics and Systems. In this sense, it is important to consider that in the National Science, Technology and Innovation Plan for the development of the Electronics, Information Technologies and Communications (2013) sectors, it is established as a weakness in the SWOT Analysis of the Software sector and Services, Deficiencies in training and professional training. Accordingly, UNIMINUTO's Computer Technology Program has addressed the analysis of students' performance in software development, identifying various problems such as dropout in programming subjects, academic averages, as well as deficiencies in strategies and competencies developed in the area of programming. As a result of this analysis, it was determined to design a collaborative learning platform in basic programming using heat maps as a tool to support didactic feedback. The pilot phase allows to evaluate in a programming course the ALGORINFO platform as a didactic resource, through an interactive and collaborative environment where students can develop basic programming practices and in turn, are fed back through the analysis of time patterns and difficulties frequent in certain segments or program cycles, by means of heat maps. The result allows the teacher to have tools to reinforce and advise critical points generated on the map, so that students and graduates improve their skills as software developers.

Keywords: collaborative platform, learning, feedback, programming, heat maps

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Authors: Alam Ali, Ashok Kumar Pathak

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Path analysis is a statistical technique used to evaluate the strength of the direct and indirect effects of variables. One or more structural regression equations are used to estimate a series of parameters in order to find the better fit of data. Sometimes, exogenous variables do not show a significant strength of their direct and indirect effect when the assumption of classical regression (ordinary least squares (OLS)) are violated by the nature of the data. The main motive of this article is to investigate the efficacy of the copula-based regression approach over the classical regression approach and calculate the direct and indirect effects of variables when data violates the OLS assumption and variables are linked through an elliptical copula. We perform this study using a well-organized numerical scheme. Finally, a real data application is also presented to demonstrate the performance of the superiority of the copula approach.

Keywords: path analysis, copula-based regression models, direct and indirect effects, k-fold cross validation technique

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Authors: Serkan Tezgel

Abstract:

Effectively managing threats and power that transcend national boundaries requires a reformulation from the traditional post-modern navy to an adaptive and institutional transnational navy. By analyzing existing soft power concept, post-modern navy, and sea power, this study proposes the transnational navy, founded on the triangle of main attributes of transnational companies, 'Global Competitiveness, Local Responsiveness, Worldwide Learning and Innovation Sharing', a new model which will lead to a positive peace with an institutional network. This transnational model necessitates 'Transnational Navies' to help establish peace with collective and transnational understanding during a transition period 'Reactive Postmodern Navy' has been experiencing. In this regard, it is fairly claimed that a new paradigm shift will revolve around sea power to establish good order at sea with collective and collaborative initiatives and bound to breed new theories and ideas in the forthcoming years. However, there are obstacles to overcome. Postmodern navies, currently shaped by 'Collective Maritime Security' and 'Collective Defense' concepts, can not abandon reactive applications and acts. States deploying postmodern navies to realize their policies on international platforms and seapower structures shaped by the axis of countries’ absolute interests resulted in multipolar alliances and coalitions, but the establishment of the peace. These obstacles can be categorized into three tiers in establishing a unique transnational model navy: Strategic, Organizational and Management challenges. To overcome these obstacles and challenges, postmodern navies should transform into cooperative, collective and independent soft transnational navies with the transnational mentality, global commons, and institutional network. Such an adaptive institution can help the world navigate to a positive peace.

Keywords: postmodern navy, transnational navy, transnational mentality, institutional network

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Authors: Vera Lúcia Raposo

Abstract:

The right to health care – usually known as the right to health – is recognized in many national laws and Constitutions, as well as in international human rights documents. The kind of health care that citizens are entitled to receive, especially in the framework of the National Health Service, is usually identified with conventional medicine. However, since ancient times that a different form of medicine – alternative, traditional or nonconventional medicine – exists. In recent times it is attracting increasing interest, as it is demonstrated by the use of its specific knowledge either by pharmaceutical companies either by modern health technologies. Alternative medicine refers to a holistic approach to body and mind using herbal products, animal parts and minerals instead of technology and pharmaceutical drugs. These notes contributed to a sense of distrust towards it, accusing alternative medicine of being based on superstition and ignorance. However, and without denying that some particular practices lack indeed any kind of evidence or scientific grounds, the fact is that a substantial part of alternative medicine can actually produce satisfactory results. The paper will not advocate the substitution of conventional medicine by alternative medicine, but the complementation between the two and their specific knowledge. In terms of the right to health, as a fundamental right and a human right, this thesis leads to the implementation of a wider range of therapeutic choices for patients, who should be entitled to receive different forms of health care that complement one another, both in public and private health facilities. This scenario would demand a proper regulation for alternative medicine, which nowadays does not exist in most countries, but it is essential to protect patients and public health in general and to reinforce confidence in alternative medicine.

Keywords: alternative medicine, conventional medicine, patient’s rights, right to health

Procedia PDF Downloads 391

Authors: Indarti, Li-Hsun Peng

Abstract:

Batik is one of the most prominent expressions of cultural identity in Indonesia. On October 2009, UNESCO designated Indonesian batik as “a masterpiece of oral and intangible heritage of humanity”. The center of batik Indonesia is in middle of Java where there is center of Javanese royalty in the 17th century (known as classic batik). The development of batik spread to wide range of area in Indonesia, including in Sidoarjo city, East Java - Indonesia. Sidoarjo batik actually has long been around long time and is known as batik using bright colors, very different from classic batik. The aims of this study is to determine the kinds of ornament of Sidoarjo batik currently as one of the locally-based creative industry and to figure out how the attempt to sustainability of Sidoarjo batik from owner and government. The research is conducted in Jetis Village in Sidoarjo city known as village of batik. There is some batik business and batik maker in there. The research method used in-depth interview to search information about ornament of Sidoarjo batik and to analyze the attempt of business owner and government to sustainability of Sidoarjo Batik. In-depth interviews to batik business owners are used to determine the kinds of ornament of Sidoarjo Batik currently and how their attempt to maintain the existence of Sidoarjo Batik. In-depth interviews are also conducted to government to figure out how the support the sustainability of Sidoarjo batik. The result or research will introduce local products of Sidoarjo community to global market and increase knowledge about traditional textile design in one part of the world.

Keywords: Sidoarjo Batik, Traditional Textile, Ornament, Creative Design.

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Authors: Sumaira Ashraf, Elisabete G.S. Félix, Zélia Serrasqueiro

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Traditional financial distress prediction models performed well to predict bankrupt and insolvent firms of the developed markets. Previous studies particularly focused on the predictability of financial distress, financial failure, and bankruptcy of firms. This paper contributes to the literature by extending the definition of financial distress with the inclusion of early warning signs related to quotation of face value, dividend/bonus declaration, annual general meeting, and listing fee. The study used five well-known distress prediction models to see if they have the ability to predict early warning signs of financial distress. Results showed that the predictive ability of the models varies over time and decreases specifically for the sample with early warning signs of financial distress. Furthermore, the study checked the differences in the predictive ability of the models with respect to the financial crisis. The results conclude that the predictive ability of the traditional financial distress prediction models decreases for the firms with early warning signs of financial distress and during the time of financial crisis. The study developed a new model comprising significant variables from the five models and one new variable earning response. This new model outperforms the old distress prediction models before, during and after the financial crisis. Thus, it can be used by researchers, organizations and all other concerned parties to indicate early warning signs for the emerging markets.

Keywords: financial distress, emerging market, prediction models, Z-Score, logit analysis, probit model

Procedia PDF Downloads 247

Authors: Mohamed M. Diab, Fahmy E. Mohamed, Alaa Balbaa

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Background: Myofascial pain syndrome a common type of non-articular musculoskeletal pain, is a condition associated with regional pain and muscle tenderness characterized by the presence of hypersensitive nodules. Objectives: the purpose of this study is to compare between the effects of manual progressive ischemic pressure versus the effect of post isometric facilitation in the treatment of Rhomboid latent myofascial trigger points. Methods: six patients had participated in this study. Patients divided into two groups. Group A treated by manual progressive ischemic pressure and traditional physical therapy program. Group B treated by post isometric facilitation and traditional physical therapy program. Treatment program was for 6 sessions over two week’s period. Result: Statistical analysis revealed that there is no significant difference in post treatment from pretreatment in pain severity (VAS) in myofascial trigger points with Rhomboid muscles) and Pain pressure threshold (PPT) for tenderness at both groups (A,B). Conclusion: ischemic pressure technique appear to be no more effective than post isometric facilitation in treatment of rhomboids latent myofacial trigger point.

Keywords: Rhmoiboid trigger point, myofacila trigger point, ischemic pressure, post isometric facilitation

Procedia PDF Downloads 317