Search results for: online learning tools

Authors: Kibreab Alene Fenite

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The purpose of this study is to investigate the implementation and challenges of different assessment methods for physical education class in some selected preparatory schools of kirkos sub city. The participants in this study are teachers, students, department heads and school principals from 4 selected schools. Of the total 8 schools offering in kirkos sub city 4 schools (Dandi Boru, Abiyot Kirse, Assay, and Adey Ababa) are selected by using simple random sampling techniques and from these schools all (100%) of teachers, 100% of department heads and school principals are taken as a sample as their number is manageable. From the total 2520 students, 252 (10%) of students are selected using simple random sampling. Accordingly, 13 teachers, 252 students, 4 department heads and 4 school principals are taken as a sample from the 4 selected schools purposefully. As a method of data gathering tools; questionnaire and interview are employed. To analyze the collected data, both quantitative and qualitative methods are used. The result of the study revealed that assessment in physical education does not implement properly: lack of sufficient materials, inadequate time allotment, large class size, and lack of collaboration and working together of teachers towards assessing the performance of students, absence of guidelines to assess the physical education subject, no different assessment method that is implementing on students with disabilities in line with their special need are found as major challenges in implementing the current assessment method of physical education. To overcome these problems the following recommendations have been forwarded. These are: the necessary facilities and equipment should be available; In order to make reliable, accurate, objective and relevant assessment, teachers of physical education should be familiarized with different assessment techniques; Physical education assessment guidelines should be prepared, and guidelines should include different types of assessment methods; qualified teachers should be employed, and different teaching room must be build.

Keywords: assessment, challenges, equipment, guidelines, implementation, performance

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Authors: Giulia Cardoni, Francesca Fabbrii

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Living archives perform a function of social memory sharing, which contributes to building social bonds, communities, and identities. This potential lies in the ability to live archives to put together an archival function, which allows the conservation and transmission of memory with an artistic, performative and creative function linked to the present. As part of the DARE-UIA (Digital environment for collaborative alliances to regenerate urban ecosystems in middle-sized cities) project the creation of a living digital archive made it possible to create a narrative that would consolidate the cultural memory of the Darsena district of the city of Ravenna. The aim of the project is to stimulate the urban regeneration of a suburban area of a city, enhancing its cultural memory and identity heritage through digital heritage tools. The methodology used involves various digital storytelling actions necessary for the overall narrative using georeferencing systems (GIS), storymaps and 3D reconstructions for a transversal narration of historical content such as personal and institutional historical photos and to enhance the industrial archeology heritage of the neighborhood. The aim is the creation of an interactive and replicable narrative in similar contexts to the Darsena district in Ravenna. The living archive, in which all the digital contents are inserted, finds its manifestation towards the outside in the form of a museum spread throughout the neighborhood, making the contents usable on smartphones via QR codes and totems inserted on-site, creating thematic itineraries spread around the neighborhood. The construction of an interactive and engaging digital narrative has made it possible to enhance the material and immaterial heritage of the neighborhood by recreating the community that has historically always distinguished it.

Keywords: digital living archive, digital storytelling, GIS, 3D, open-air museum, urban regeneration, cultural memory

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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: Tamas Garamhegyi, Jozsef Kovacs, Rita Pongracz, Peter Tanos, Balazs Trasy, Norbert Magyar, Istvan G. Hatvani

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Like most environmental processes, shallow groundwater fluctuation under natural circumstances also behaves periodically. With the statistical tools at hand, it can easily be determined if a period exists in the data or not. Thus, the question may be raised: Does the estimated average period time characterize the whole time period, or not? This is especially important in the case of such complex phenomena as shallow groundwater fluctuation, driven by numerous factors. Because of the continuous changes in the oscillating components of shallow groundwater time series, the most appropriate method should be used to investigate its periodicity, this is wavelet spectrum analysis. The aims of the research were to investigate the periodic behavior of the shallow groundwater time series of an agriculturally important and drought sensitive region in Central-Eastern Europe and its relationship to the European pressure action centers. During the research ~216 shallow groundwater observation wells located in the eastern part of the Great Hungarian Plain with a temporal coverage of 50 years were scanned for periodicity. By taking the full-time interval as 100%, the presence of any period could be determined in percentages. With the complex hydrogeological/meteorological model developed in this study, non-periodic time intervals were found in the shallow groundwater levels. On the local scale, this phenomenon linked to drought conditions, and on a regional scale linked to the maxima of the regional air pressures in the Gulf of Genoa. The study documented an important link between shallow groundwater levels and climate variables/indices facilitating the necessary adaptation strategies on national and/or regional scales, which have to take into account the predictions of drought-related climatic conditions.

Keywords: climate change, drought, groundwater periodicity, wavelet spectrum and coherence analyses

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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: Fathi Kallel, Abdulelah Alabd Uljabbar, Abdulrahman Aldukhail, Abdulaziz Alomran

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The brain is an important organ in our body since it is responsible about the majority actions such as vision, memory, etc. However, different diseases such as Alzheimer and tumors could affect the brain and conduct to a partial or full disorder. Regular diagnosis are necessary as a preventive measure and could help doctors to early detect a possible trouble and therefore taking the appropriate treatment, especially in the case of brain tumors. Different imaging modalities are proposed for diagnosis of brain tumor. The powerful and most used modality is the Magnetic Resonance Imaging (MRI). MRI images are analyzed by doctor in order to locate eventual tumor in the brain and describe the appropriate and needed treatment. Diverse image processing methods are also proposed for helping doctors in identifying and analyzing the tumor. In fact, a large Computer Aided Diagnostic (CAD) tools including developed image processing algorithms are proposed and exploited by doctors as a second opinion to analyze and identify the brain tumors. In this paper, we proposed a new advanced CAD for brain tumor identification, classification and feature extraction. Our proposed CAD includes three main parts. Firstly, we load the brain MRI. Secondly, a robust technique for brain tumor extraction is proposed. This technique is based on both Discrete Wavelet Transform (DWT) and Principal Component Analysis (PCA). DWT is characterized by its multiresolution analytic property, that’s why it was applied on MRI images with different decomposition levels for feature extraction. Nevertheless, this technique suffers from a main drawback since it necessitates a huge storage and is computationally expensive. To decrease the dimensions of the feature vector and the computing time, PCA technique is considered. In the last stage, according to different extracted features, the brain tumor is classified into either benign or malignant tumor using Support Vector Machine (SVM) algorithm. A CAD tool for brain tumor detection and classification, including all above-mentioned stages, is designed and developed using MATLAB guide user interface.

Keywords: MRI, brain tumor, CAD, feature extraction, DWT, PCA, classification, SVM

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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: Efthimios Kokkotos, Kostakis Marios, Beis Alexandros, Angelos Patakas, Antonios Avgeris, Vassilios Triantafyllidis

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H, C, and O stable isotope ratios were measured in different olive oils and table olives originating from different regions of Greece. In particular, the stable isotope ratios of different olive oils produced in the Lakonia region (Peloponesse – South Greece) from different varieties, i.e., cvs ‘Athinolia’ and ‘koroneiki’, were determined. Additionally, stable isotope ratios were also measured in different table olives (cvs ‘koroneiki’ and ‘kalamon’) produced in the same region (Messinia). The aim of this study was to provide sufficient isotope ratio data regarding each variety and region of origin that could be used in discriminative studies of oil olives and table olives produced by different varieties in other regions. In total, 97 samples of olive oil (cv ‘Athinolia’ and ‘koroneiki’) and 67 samples of table olives (cvs ‘kalmon’ and ‘koroneiki’) collected during two consecutive sampling periods (2021-2022 and 2022-2023) were measured. The C, H, and O isotope ratios were measured using Isotope Ratio Mass Spectrometry (IRMS), and the results obtained were analyzed using chemometric techniques. The measurements of the isotope ratio analyses were expressed in permille (‰) using the delta δ notation (δ=Rsample/Rstandard-1, where Rsample and Rstandardis represent the isotope ratio of sample and standard). Results indicate that stable isotope ratios of C, H, and O ranged between -28,5+0,45‰, -142,83+2,82‰, 25,86+0,56‰ and -29,78+0,71‰, -143,62+1,4‰, 26,32+0,55‰ in olive oils produced in Lakonia region from ‘Athinolia’ and ‘koroneiki ‘varieties, respectively. The C, H, and O values from table olives originated from Messinia region were -28,58+0,63‰, -138,09+3,27‰, 25,45+0,62‰ and -29,41+0,59‰,-137,67+1,15‰, 24,37+0,6‰ for ‘Kalamon’ and ‘koroneiki’ olives respectively. Acknowledgments: This research has been co-financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH—CREATE—INNOVATE (Project code: T2EDK-02637; MIS 5075094, Title: ‘Innovative Methodological Tools for Traceability, Certification and Authenticity Assessment of Olive Oil and Olives’).

Keywords: olive oil, table olives, Isotope ratio, IRMS, geographical origin

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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: Khachen Kongpakwattana, Charungthai Dejthevaporn, Orapitchaya Krairit, Piyameth Dilokthornsakul, Devi Mohan, Nathorn Chaiyakunapruk

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Background: Although an increase in the burden of Alzheimer’s disease (AD) is evident worldwide, knowledge of costs and health-related quality of life (HR-QoL) associated with AD in Low- and Middle-Income Countries (LMICs) is still lacking. We, therefore, aimed to collect real-world cost and HR-QoL data, and investigate their associations with multiple disease-severity indicators among AD patients in Thailand. Methods: We recruited AD patients aged ≥ 60 years accompanied by their caregivers at a university-affiliated tertiary hospital. A one-time structured interview was conducted to collect disease-severity indicators, HR-QoL and caregiving information using standardized tools. The hospital’s database was used to retrieve healthcare resource utilization occurred over 6 months preceding the interview date. Costs were annualized and stratified based on cognitive status. Generalized linear models were employed to evaluate determinants of costs and HR-QoL. Results: Among 148 community-dwelling patients, average annual total societal costs of AD care were 8,014 US$ [95% Confidence Interval (95% CI): 7,295 US$ - 8,844 US$] per patient. Total costs of patients with severe stage (9,860 US$; 95% CI: 8,785 US$ - 11,328 US$) were almost twice as high as those of mild stage (5,524 US$; 95% CI: 4,649 US$ - 6,593 US$). The major cost driver was direct medical costs, particularly those incurred by AD prescriptions. Functional status was the strongest determinant for both total costs and patient’s HR-QoL (p-value < 0.001). Conclusions: Our real-world findings suggest the distinct major cost driver which results from expensive AD treatment, emphasizing the demand for country-specific cost evidence. Increases in cognitive and functional status are significantly associated with decreases in total costs of AD care and improvement on patient’s HR-QoL.

Keywords: Alzheimer's disease, associations, costs, disease-severity indicators, health-related quality of life

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Authors: Janet Wing-Chong Wai, Alex Chiu-Wing Lee, Hailey Hoi-Ching Tsang, Jeffrey Chiu, Kwok-Wing Tang

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Background: Mammography has limited sensitivity and specificity though it is the primary imaging technique for detection of early breast cancer. Ultrasound imaging and contrast-enhanced MRI are useful adjunct tools to mammography. The advantage of breast MRI is high sensitivity for invasive breast cancer. Therefore, indications for and use of breast magnetic resonance imaging have increased over the past decade. Objectives: 1. Cases demonstration on different indications for breast MR imaging. 2. To review of the common artifacts and pitfalls in breast MR imaging. Materials and Methods: This is a retrospective study including all patients underwent dynamic contrast-enhanced breast MRI examination in our centre, performed from Jan 2011 to Dec 2017. The clinical data and radiological images were retrieved from the EPR (electronic patient record), RIS (Radiology Information System) and PACS (Picture Archiving and Communication System). Results and Discussion: Cases including (1) Screening of the contralateral breast in patient with a new breast malignancy (2) Breast augmentation with free injection of unknown foreign materials (3) Finding of axillary adenopathy with an unknown site of primary malignancy (4) Neo-adjuvant chemotherapy: before, during, and after chemotherapy to evaluate treatment response and extent of residual disease prior to operation. Relevant images will be included and illustrated in the presentation. As with other types of MR imaging, there are different artifacts and pitfalls that can potentially limit interpretation of the images. Because of the coils and software specific to breast MR imaging, there are some other technical considerations that are unique to MR imaging of breast regions. Case demonstration images will be available in presentation. Conclusion: Breast MR imaging is a highly sensitive and reasonably specific method for the detection of breast cancer. Adherent to appropriate clinical indications and technical optimization are crucial for achieving satisfactory images for interpretation.

Keywords: MRI, breast, clinical, cancer

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Authors: Botirjon Kosimov

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

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

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Authors: 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: M. Polic, N. Cesarec Salopek

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When it comes to crisis, no company, notwithstanding its financial success, power or reputation is immune to the new environment and circumstances emerging from it. The main challenge company faces with during a crisis is to protect its most valuable intangible asset reputation. Crisis has the serious potential to disrupt company’s everyday operations and damage its reputation extremely fast, especially if the company did not anticipate threats that may cause a crisis. Therefore, when a crisis happens, company must directly respond to it, whilst an effective crisis communication can limit consequences arising from the crisis, protect and repair the reputational damage caused to the company. Since every crisis is unique, each one of it requires different crisis response strategy. In July 2018, airline labor unions threatened Croatia Airlines, the state owned flag carrier of Croatia, to hold a strike that would be called into question regular flights and affect more than 7.600 passengers per day. This study explores the differences between crisis response strategies that Croatia Airlines, the state owned flag carrier of Croatia and airline labor unions used during the crisis period within the Situational Crisis Communication Theory (SCCT) by analyzing the content of formal communication tools used by Croatia Airlines and airline labor unions. Moreover, this study shows how Croatia Airlines successfully managed to communicate to the general public the threat that airline labor unions imposed on it and how was it received by the Croatian media. By using the qualitative and quantitative content analysis, the study will reveal the frames that dominated in the media articles during the crisis period. The greatest significance of this study is that it will provide the deeper insight into how transparent and consistent communication, the one that Croatia Airlines used before and during the crisis period, contributed to the decision of the competent court (Zagreb County Court) which prohibited labor unions strike in August 2018.

Keywords: crisis communication, crisis response strategy, Croatia Airlines, labor union, reputation management, situational crisis communication theory, strike

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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: Getachew Belay Kassahun

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Background: Locally established clinical laboratory reference intervals (RIs) are required to interpret laboratory test results for screening, diagnosis, and prognosis. The objective of this study was to establish a reference interval of clinical chemistry parameters among apparently healthy adolescents aged between 12 and 17 years in Mekelle, Tigrai, in the northern part of Ethiopia. Methods: Community-based cross-sectional study was employed from December 2018 to March 2019 in Mekelle City among 172 males and 172 females based on a Multi-stage sampling technique. Blood samples were tested for Fasting blood sugar (FBS), alanine amino transferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), Creatinine, urea, total protein, albumin (ALB), direct and indirect bilirubin (BIL.D and BIL.T) using 25 Bio system clinical chemistry analyzer. Results were analyzed using SPSS version 23 software and based on the Clinical Laboratory Standard Institute (CLSI)/ International Federation of Clinical Chemistry (IFCC) C 28-A3 Guideline which defines the reference interval as the 95% central range of 2.5th and 97.5th percentiles. Mann Whitney U test, descriptive statistics and box and whisker were statistical tools used for analysis. Results: This study observed statistically significant differences between males and females in ALP, ALT, AST, Urea and Creatinine Reference intervals. The established reference intervals for males and females, respectively, were: ALP (U/L) 79.48-492.12 versus 63.56-253.34, ALT (U/L) 4.54-23.69 versus 5.1-20.03, AST 15.7- 39.1 versus 13.3- 28.5, Urea (mg/dL) 9.33-24.99 versus 7.43-23.11, and Creatinine (mg/dL) 0.393-0.957 versus 0.301-0.846. The combined RIs for Total Protein (g/dL) were 6.08-7.85, ALB (g/dL) 4.42-5.46, FBS(mg/dL) 65-110, BIL.D (mg/dL) 0.033-0.532, and BIL.T (mg/dL) 0.106-0.812. Conclusions: The result showed a marked difference between sex and company-derived values for selected clinical chemistry parameters. Thus, the use of age and sex-specific locally established reference intervals for clinical chemistry parameters is recommended.

Keywords: reference interval, adolescent, clinical chemistry, Ethiopia

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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: Lina S. Calucag

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Integration of research and teaching in higher education can provide valuable ways of enhancing the student learning experience, but establishing such integrative links can be complex and problematic, given different practices and levels of understanding. This study contributes to the pedagogical literature in drawing on findings from students’ survey exploring perceptions of research-informed teaching to examine how links between research and teaching can be suitably strengthened. The study employed a descriptive research design limited to the undergraduate students taking thesis/capstone courses in the tertiary levels private or public colleges and universities across the globe as respondents of the study. The findings noted that the students’ responses from different disciplines: engineering, science, education, business-related, and computer on the nexus between research and teaching is remarkable in fostering student expectations of research-informed teaching approaches. Students’ expectations on research-led, research-oriented, research-based, and research-tutored are enablers in linking research and teaching. It is recommended that experimental studies should be conducted using the four different research-informed teaching approaches in the classroom, namely: research-led, research-oriented, research-based, and research-tutored.

Keywords: research-led, research-informed teaching, research-oriented teaching, research-tutored, research-based

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Authors: S. Gordon

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

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

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Authors: Surendar Vaddepalli

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Management education plays a crucial role to enable industry to cope with emerging challenges. It has spread in the last fifteen-twenty years in India and gained popularity as it was aimed at imbibing versatility and multi-tasking abilities in student community. Several management institutions started looking at upgrading their competencies in terms of faculty, research and industry interaction. The competitive business environment has been one of the drivers that paved the way for growing demand for management graduates in the employment market. Industry expects their executives to be engaged in a constant learning process. The ever-increasing demand for managers has led to establish more management institutions; however, the growth was not in line with the expectations from the industry. While top Business Schools are continuously changing the contents and delivery methodologies, academic standards of most of the other Business Schools are not up to the mark and quality of service provided by these institutes has opened various issues for discussion. On this back ground it is important to address the concerns of Indian management education experiencing with time and we have to rethink about the management education and efforts should be made to create a dynamic environment. This paper ties to study the current trends and tries to find out need for value based management education in India to rejuvenate it.

Keywords: management education, management, value based management education, business school, India

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Authors: Monika Paleczna, Barbara Szmigielska

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The period of adolescence is a time when young people are becoming more and more active and conscious users of the digital world. One of the most frequently undertaken activities by them is computer games. Young players can choose from a wide range of games, including action, adventure, strategy, and logic games. The main aim of this study is to answer the question about the motivation of teenage players. The basic question is what motivates young players to play computer games and what motivates them to play a particular game. Fifty adolescents aged 15-17 participated in the study. They completed a questionnaire in which they determined what motivates them to play, how often they play computer games, and what type of computer games they play most often. It was found that entertainment and learning English are among the most important motives. The most important specific features related to a given game are the knowledge of its previous parts and the ability to play for free. The motives chosen by the players will be described in relation to the concepts of internal and external as well as approach and avoidance motivation. An additional purpose of this study is to present data concerning preferences regarding the type of games and the amount of time they spend playing.

Keywords: computer games, motivation, game preferences, adolescence

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Authors: Srinaath Anbu Durai, Wang Zhaoxia

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Twitter sentiment has been used as a predictor to predict price values or trends in both the stock market and housing market. The pioneering works in this stream of research drew upon works in behavioural economics to show that sentiment or emotions impact economic decisions. Latest works in this stream focus on the algorithm used as opposed to the data used. A literature review of works in this stream through the lens of data used shows that there is a paucity of work that considers the impact of sentiments caused due to an external factor on either the stock or the housing market. This is despite an abundance of works in behavioural economics that show that sentiment or emotions caused due to an external factor impact economic decisions. To address this gap, this research studies the impact of Twitter sentiment pertaining to the Covid-19 pandemic on resale Housing Development Board (HDB) apartment prices in Singapore. It leverages SNSCRAPE to collect tweets pertaining to Covid-19 for sentiment analysis, lexicon based tools VADER and TextBlob are used for sentiment analysis, Granger Causality is used to examine the relationship between Covid-19 cases and the sentiment score, and neural networks are leveraged as prediction models. Twitter sentiment pertaining to Covid-19 as a predictor of HDB price in Singapore is studied in comparison with the traditional predictors of housing prices i.e., the structural and neighbourhood characteristics. The results indicate that using Twitter sentiment pertaining to Covid19 leads to better prediction than using only the traditional predictors and performs better as a predictor compared to two of the traditional predictors. Hence, Twitter sentiment pertaining to an external factor should be considered as important as traditional predictors. This paper demonstrates the real world economic applications of sentiment analysis of Twitter data.

Keywords: sentiment analysis, Covid-19, housing price prediction, tweets, social media, Singapore HDB, behavioral economics, neural networks

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Authors: Widyani Fatwa Dewi, Subroto Athor

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In a telecommunication service provider, quantity and interval of customer demand often difficult to predict due to high dependency on customer expansion strategy and technological development. Demand arrives when a customer needs to add capacity to an existing site or build a network in a new site. Because demand is uncertain for each period, and sometimes there is a null demand for several equipments, it is categorized as intermittent. This research aims to improve demand forecast quality in Indonesia's telecommunication service providers by using Artificial Neural Network. In Artificial Neural Network, the pattern or relationship within data will be analyzed using the training process, followed by the learning process as validation stage. Historical demand data for 36 periods is used to support this research. It is found that demand forecast by using Artificial Neural Network outperforms the existing method if it is reviewed on two criteria: the forecast accuracy, using Mean Absolute Deviation (MAD), Mean of the sum of the Squares of the Forecasting Error (MSE), Mean Error (ME) and service level which is shown through inventory cost. This research is expected to increase the reference for a telecommunication demand forecast, which is currently still limited.

Keywords: artificial neural network, demand forecast, forecast accuracy, intermittent, service level, telecommunication

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Authors: Guerriche Amina

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The recent trends in foreign language teaching -influenced widely by the process of globalization, interculturalism, and global flows and migration- are leaning towards adopting an intercultural perspective to help in developing students who are global citizens able to effectively function across diverse boundaries (cultural, social, geographical). Researchers call for intercultural learning and teaching perspective that would foster and increase intercultural awareness and understanding (e.g., Guilherme, 2002; Byram et al., 2002). The present research aims at unfolding whether including the cultural dimension in foreign language instruction can help in developing students’ intercultural understanding and awareness. In doing so, a cultural pedagogical experiment was designed and conducted for the period of one year at the level of the university. Data were collected qualitatively and analyzed thematically. Results help in drawing important implications for educational institutions, foreign language teachers, and syllabus designers about the importance and effectiveness of perceiving foreign language instruction as a social activity that can nurture interculturally competent individuals who adequately respond to the demands of today’s intercultural and globalized societies.

Keywords: foreign language teaching, intercultural awareness, language and culture, intercultural understanding

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Authors: Daniel James Pitchforth, Timothy James Rogers, Ulf Tyge Tygesen, Elizabeth Jane Cross

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Wave loading is a primary cause of fatigue within offshore structures and its quantification presents a challenging and important subtask within the SHM framework. The accurate representation of physics in such environments is difficult, however, driving the development of data-driven techniques in recent years. Within many industrial applications, empirical laws remain the preferred method of wave loading prediction due to their low computational cost and ease of implementation. This paper aims to develop an approach that combines data-driven Gaussian process models with physical empirical solutions for wave loading, including Morison’s Equation. The aim here is to incorporate physics directly into the covariance function (kernel) of the Gaussian process, enforcing derived behaviors whilst still allowing enough flexibility to account for phenomena such as vortex shedding, which may not be represented within the empirical laws. The combined approach has a number of advantages, including improved performance over either component used independently and interpretable hyperparameters.

Keywords: offshore structures, Gaussian processes, Physics informed machine learning, Kernel design

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Authors: Haofei Li

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To support academic growth and foster love of learning, MathMates has been introduced for grade 6-8 students at Andrew Hamilton public school in 2022. The program is targeted at students from diverse backgrounds, particularly those underperforming in Pennsylvania System of School Assessment (PSSA) exams. Then, this study aims to evaluate the efficacy of MathMates by comparing student performance on the PSSA test, before and after the intervention. Through a randomized control trial, the study will collect associated costs using the ingredients method and measure the effectiveness for cost-effectiveness analysis. Text messages will be sent to parents/guardians as a reminder of the program and to encourage student participation. The findings of this study will provide valuable insights for funding organizations seeking to understand the impact and costs of math tutoring interventions on student academic achievement, which also emphasizes the importance of the collaborative efforts between higher education and local public schools.

Keywords: mathematics education, mathematics tutoring, college-community initiative, middle schools, Philadelphia public schools, after-school program, PSSA

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Authors: Aidin Foroutan, David S. Wishart, Leluo L. Guan, Carolyn Fitzsimmons

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Maximizing efficiency and growth potential of beef cattle requires not only genetic selection (i.e. residual feed intake (RFI)) but also adequate nutrition throughout all stages of growth and development. Nutrient restriction during gestation has been shown to negatively affect post-natal growth and development as well as fertility of the offspring. This, when combined with RFI may affect progeny traits. This study aims to investigate the impact of selection for divergent genetic potential for RFI and maternal nutrition during early- to mid-gestation, on bull calf traits such as fertility and muscle development using multiple ‘omics’ approaches. Comparisons were made between High-diet vs. Low-diet and between High-RFI vs. Low-RFI animals. An epigenetics experiment on semen samples identified 891 biomarkers associated with growth and development. A gene expression study on Longissimus thoracis muscle, semimembranosus muscle, liver, and testis identified 4 genes associated with muscle development and immunity of which Myocyte enhancer factor 2A [MEF2A; induces myogenesis and control muscle differentiation] was the only differentially expressed gene identified in all four tissues. An initial metabolomics experiment on serum samples using nuclear magnetic resonance (NMR) identified 4 metabolite biomarkers related to energy and protein metabolism. Once all the biomarkers are identified, bioinformatics approaches will be used to create a database covering all the ‘omics’ data collected from this project. This database will be broadened by adding other information obtained from relevant literature reviews. Association analyses with these data sets will be performed to reveal key biological pathways affected by RFI and maternal nutrition. Through these association studies between the genome and metabolome, it is expected that candidate biomarker genes and metabolites for feed efficiency, fertility, and/or muscle development are identified. If these gene/metabolite biomarkers are validated in a larger animal population, they could potentially be used in breeding programs to select superior animals. It is also expected that this work will lead to the development of an online tool that could be used to predict future traits of interest in an animal given its measurable ‘omics’ traits.

Keywords: biomarker, maternal nutrition, omics, residual feed intake

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Authors: Yao Chen

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Empathy is crucial for teachers working with teenagers in secondary school. Despite that, little attention was paid to English language teachers’ experiences of empathy in class. Empathy contains cognitive, emotional, and behavioral components that are manifested in the teaching practice. The qualitative study focused on how Chinese ELT teachers expressed empathy in interaction with students in public high schools and private institutions and what factors might lead them to show empathy in different ways. Four participants were invited to attend the individual interviews to share their stories about their empathic experiences. Classroom observation was conducted to investigate teachers’ language use in teaching and non-verbal communication with students to witness their behavior of expressing empathy. Through thematic analysis, three main themes relevant to different types of empathy in teachers’ interaction with students were generated: 1) perspective taking, 2) emotional connections, 3) action taking. Based on the participants’ statements of their personal experiences, the discussion concluded the reasons for their differences in expressing empathy. The result underlined the significance of the role of empathy in building a rapport with students and motivating their language learning. Further implications for the role of empathy in ELT teachers’ professional development are also discussed.

Keywords: teacher empathy, experiences, interaction with students, ELT class

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Authors: Gururaj Bhajantri

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Financial sector is the backbone of any economy and it plays a crucial role in the mobilisation and allocation of resources. One of the main objectives of financial sector is inclusive growth. The constituents of the financial sector are banks, and financial Institutions, which mobilise the resources from the surplus sector and channelize the same to the different needful sectors in the economy. Micro Small and the Medium Enterprises sector in India cover a wide range of economic activities. These enterprises are divided on the basis of investment on equipment. The micro enterprises are divided into manufacturing and services sector. Micro Service enterprises have investment limit up to ten lakhs on equipment. Hairdresser is one who not only cuts and shaves but also provides different types of hair cut, hairstyles, trimming, hair-dye, massage, manicure, pedicure, nail services, colouring, facial, makeup application, waxing, tanning and other beauty treatments etc., hairdressing salons provide these services with the help of equipment. They need investment on equipment not more than ten lakhs. Hence, they can be considered as Micro service enterprises. Hairdressing salons require more than Rs 2.50,000 to start a moderate salon. Moreover, hairdressers are unable to access the organised finance. Still these individuals access finance from money lenders with high rate of interest to lead life. The socio economic conditions of hairdressers are not known properly. Hence, the present study brings a light on the role of financial institutions in promoting hairdressing salons. The study also focuses the socio-economic background of individuals in hairdressings salons, problems faced by them. The present study is based on primary and secondary data. Primary data collected among hairdressing salons in Davangere city. Samples selected with the help of simple random sampling techniques. Collected data analysed and interpreted with the help of simple statistical tools.

Keywords: micro service enterprises, financial institutions, hairdressing salons, financial sector

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Authors: Ouassila Bekkal Brikci Benhabib, Zahia Boucherit Otmani, Kebir Boucherit, A. Seghir

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The establishment of intravenous catheters in hospitalized patient is an act common in many clinical situations. These therapeutic tools, from their insertion in the body, represent gateways including fungal germs prone. The latter can generate the growth of biofilms, which can be the cause of fungal infection. Faced with this problem, we conducted a study at the University Hospital of Tlemcen in the neurosurgery unit and aims to isolate and identify Candida yeasts from intravenous catheters. Then test their ability to form biofilms. Materials and methods: 256 patient hospitalized in surgery of the hospital in west Algeria were submitted to this study. All samples were taken from peripheral venous catheters implanted for 72 hours or more days. A total of 31 isolates of Candida species were isolated. MIC and SMIC are determined at 80% inhibition by the test XTT tetrazolium measured at 490 nm. The final concentrations of antifungal agent being between 0.03 and 16 mg / ml for amphotericin B and from 0.015 to 8 mg / mL caspofungin. Results: 31 Candida species isolates from catheters including 14 Candida albicans and 17 Candida non albicans . 21 strains of all the isolates were able to form biofilms. In their form of Planktonic cells, all isolates are 100% susceptible to antifungal agents tested. However, in their state of biofilms, more isolates have become tolerant to the tested antifungals. Conclusion: Candida yeasts isolated from intravascular catheters are considered an important virulence factor in the pathogenesis of infections. Their involvement in catheter-related infections can be disastrous for their potential to generate biofilms. They survive high concentrations of antifungal where treatment failure. Pending the development of a therapeutic approach antibiofilm related to catheters, their mastery is going through: -The risk of infection prevention based on the training and awareness of medical staff, -Strict hygiene and maximum asepsis, and -The choice of material limiting microbial colonization.

Keywords: candida, biofilm, hospital, infection, amphotericin B, caspofungin

Procedia PDF Downloads 323