Search results for: dataset quality

Authors: Diane Ghanem, Whitney Kagabo, Rebecca Engels, Uma Srikumaran, Babar Shafiq

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Hospitalist co-management of orthopaedic surgery patients is a growing trend across the country. It was created as a collaborative effort to provide overarching care to patients with the goal of improving their postoperative care and decreasing in-hospital medical complications. The aim of this project is to provide a guide for implementing and optimizing a hospitalist co-management service in orthopaedic surgery. Key leaders from the hospitalist team, orthopaedic team and quality, safety and service team were identified. Multiple meetings were convened to discuss the comanagement service and determine the necessary building blocks behind an efficient and well-designed co-management framework. After meticulous deliberation, a consensus was reached on the final service agreement and a written guide was drafted. Fundamental features of the service include the identification of service stakeholders and leaders, frequent consensus meetings, a well-defined framework, with goals, program metrics and unified commands, and a regular satisfaction assessment to update and improve the program. Identified pearls for co-managing orthopaedic surgery patients are standardization, timing, adequate patient selection, and two-way feedback between hospitalists and orthopaedic surgeons to optimize the protocols. Developing a service agreement is a constant work in progress, with meetings, discussions, revisions, and multiple piloting attempts before implementation. It is a partnership created to provide hospitals with a streamlined admission process where at-risk patients are identified early, and patient care is optimized regardless of the number or nature of medical comorbidities. A wellestablished hospitalist co-management service can increase patient care quality and safety, as well as health care value.

Keywords: co-management, hospitalist co-management, implementation, orthopaedic surgery, quality improvement

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Authors: H. Yousefnia, A. Aghanejad, A. Mirzaei, R. Enayati, A. R. Jalilian, S. Zolghadri

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Bone metastases occur in many cases at an early stage of the tumour disease; however, their symptoms are recognized rather late. The aim of this study was the preparation and quality control of 111In-BPAMD for diagnostic purposes. 111In was produced at the Agricultural, Medical, and Industrial Research School (AMIRS) by means of 30 MeV cyclotron via natCd(p,x)111In reaction. Complexion of In‐111 with BPAMD was carried out by using acidic solution of 111InCl3 and BPAMD in absolute water. The effect of various parameters such as temperature, ligand concentration, pH, and time on the radiolabeled yield was studied. 111In-BPAMD was prepared successfully with the radiochemical purity of 95% at the optimized condition (100 µg of BPAMD, pH=5, and at 90°C for 1 h) which was measured by ITLC method. The final solution was injected to wild-type mice and biodistribution was determined up to 72 h. SPECT images were acquired after 2 and 24 h post injection. Both the biodistribution studies and SPECT imaging indicated high bone uptake while accumulation in other organs was approximately negligible. The results show that 111In-BPAMD can be used as an excellent tracer for diagnosis of bone metastases by SPECT imaging.

Keywords: biodistribution, BPAMD, 111In, SPECT

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Authors: Kashika P. H.

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The development of computer vision systems has been greatly aided by the efficient and precise detection of images and videos. Although the ability to recognize and comprehend images is a strength of the human brain, employing technology to tackle this issue is exceedingly challenging. In the past few years, the use of Deep Learning algorithms to treat object detection has dramatically expanded. One of the key issues in the realm of image recognition is the recognition and detection of certain notable people from randomly acquired photographs. Face recognition uses a way to identify, assess, and compare faces for a variety of purposes, including user identification, user counting, and classification. With the aid of an accessible deep learning-based API, this article intends to recognize various faces of people and their facial descriptors more accurately. The purpose of this study is to locate suitable individuals and deliver accurate information about them by using the Amazon Rekognition system to identify a specific human from a vast image dataset. We have chosen the Amazon Rekognition system, which allows for more accurate face analysis, face comparison, and face search, to tackle this difficulty.

Keywords: Amazon rekognition, API, deep learning, computer vision, face detection, text detection

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Authors: Osama A. Omer, Amal Hamed

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Successful blind image Super-Resolution algorithms require the exact estimation of the Point Spread Function (PSF). In the absence of any prior information about the imagery system and the true image; this estimation is normally done by trial and error experimentation until an acceptable restored image quality is obtained. Multi-frame blind Super-Resolution algorithms often have disadvantages of slow convergence and sensitiveness to complex noises. This paper presents a Super-Resolution image reconstruction algorithm based on estimation of the PSF that yields the optimum restored image quality. The estimation of PSF is performed by the knife-edge method and it is implemented by measuring spreading of the edges in the reproduced HR image itself during the reconstruction process. The proposed image reconstruction approach is using L1 norm minimization and robust regularization based on a bilateral prior to deal with different data and noise models. A series of experiment results show that the proposed method can outperform other previous work robustly and efficiently.

Keywords: blind, PSF, super-resolution, knife-edge, blurring, bilateral, L1 norm

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Authors: Usiobaifo Agharese Rosemary, Osaseri Roseline Oghogho

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Diabetes is a complex group of disease with a variety of causes; it is a disorder of the body metabolism in the digestion of carbohydrates food. The application of machine learning in the field of medical diagnosis has been the focus of many researchers and the use of recognition and classification model as a decision support tools has help the medical expert in diagnosis of diseases. Considering the large volume of medical data which require special techniques, experience, and high diagnostic skill in the diagnosis of diseases, the application of an artificial intelligent system to assist medical personnel in order to enhance their efficiency and accuracy in diagnosis will be an invaluable tool. In this study will propose a diabetes diagnosis model using rough set and K-nearest Neighbor classifier algorithm. The system consists of two modules: the feature extraction module and predictor module, rough data set is used to preprocess the attributes while K-nearest neighbor classifier is used to classify the given data. The dataset used for this model was taken for University of Benin Teaching Hospital (UBTH) database. Half of the data was used in the training while the other half was used in testing the system. The proposed model was able to achieve over 80% accuracy.

Keywords: classifier algorithm, diabetes, diagnostic model, machine learning

Procedia PDF Downloads 331

Authors: Amhimmid Mohammed Saffour, Mustafa Mohamed Abdullah

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The use of computers for handling image data in the healthcare is growing. However, the amount of data produced by modern image generating techniques is vast. This data might be a problem from a storage point of view or when the data is sent over a network. This paper using wavelet transform technique for medical images compression. MATLAB program, are designed to evaluate medical images storage and transmission time problem at Sebha Medical Center Libya. In this paper, three different Computed Tomography images which are abdomen, brain and chest have been selected and compressed using wavelet transform. Objective evaluation has been performed to measure the quality of the compressed images. For this evaluation, the results show that the Peak Signal to Noise Ratio (PSNR) which indicates the quality of the compressed image is ranging from (25.89db to 34.35db for abdomen images, 23.26db to 33.3db for brain images and 25.5db to 36.11db for chest images. These values shows that the compression ratio is nearly to 30:1 is acceptable.

Keywords: medical image, Matlab, image compression, wavelet's, objective evaluation

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Authors: Zhe Li, Aihua Cai

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Aiming at the problem of high-density clutter and interference affecting radar detection target track initiation in ECM and complex radar mission, the traditional radar target track initiation method has been difficult to adapt. To this end, we propose a multi-algorithm fusion learning track initiation algorithm, which transforms the track initiation problem into a true-false track discrimination problem, and designs an algorithm based on 1DCNN(One-Dimensional CNN)combined with Bi-LSTM (Bi-Directional Long Short-Term Memory )for fusion classification. The experimental dataset consists of real trajectories obtained from a certain type of three-coordinate radar measurements, and the experiments are compared with traditional trajectory initiation methods such as rule-based method, logical-based method and Hough-transform-based method. The simulation results show that the overall performance of the multi-algorithm fusion learning track initiation algorithm is significantly better than that of the traditional method, and the real track initiation rate can be effectively improved under high clutter density with the average initiation time similar to the logical method.

Keywords: track initiation, multi-algorithm fusion, 1DCNN, Bi-LSTM

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Authors: Piyapat Chitpirom, Teerakiat Jareonsettasin, Chintida Vichitsophaphan

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The Foundation of Virtuous Youth was established and supported by the Crown Property Bureau, with the intention to instill goodness in Thai youth. The Centre for Educational Psychology is one of the three units under the foundation. We aim to develop programmes that can be used to improve the quality of education in schools. Translation of the King’s message in keeping with the modern research from various sources, our team create 6 programmes: (1) Teacher-Student Relationship (2) Growth Mindset (3) Socratic Teaching (4) Peer Tutoring (5) Parental Involvement (6) Inclusion. After nine months of implementing the programmes in the schools, we found that there were more cooperation between student-student, teacher-student, teacher-parent, and student-parent and the school regained trust from the community. Our ideas were accepted well by the government as our director was promoted to be the Vice Minister of Education in order to implement our programmes into national education system. We consider that the key of our success is that we do practical things. We are still continuing, improving, and learning from our work with hope that the quality of Thai education will improve in near future.

Keywords: education reform, educational psychology, effective teaching, teacher-student relationship

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Authors: Wiseman Emmanuel Nkhomah, Chiyembekezo Kachimanga, Moses Banda Aron, Julia Higgins, Manuel Mulwafu, Kondwani Mpinga, Mwayi Chunga, Grace Momba, Enock Ndarama, Dickson Sumphi, Atupere Phiri, Fabien Munyaneza

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Background: Data is key to supporting health service delivery as stakeholders, including NGOs rely on it for effective service delivery, decision-making, and system strengthening. Several studies generated debate on data quality from national health management information systems (HMIS) in sub-Saharan Africa. This limits the utilization of data in resource-limited settings, which already struggle to meet standards set by the World Health Organization (WHO). We aimed to evaluate data quality improvement of Neno district HMIS over a 4-year period (2018 – 2021) following quarterly data reviews introduced in January 2020 by the district health management team and Partners In Health. Methods: Exploratory Mixed Research was used to examine report rates, followed by in-depth interviews using Key Informant Interviews (KIIs) and Focus Group Discussions (FGDs). We used the WHO module desk review to assess the quality of HMIS data in the Neno district captured from 2018 to 2021. The metrics assessed included the completeness and timeliness of 34 reports. Completeness was measured as a percentage of non-missing reports. Timeliness was measured as the span between data inputs and expected outputs meeting needs. We computed T-Test and recorded P-values, summaries, and percentage changes using R and Excel 2016. We analyzed demographics for key informant interviews in Power BI. We developed themes from 7 FGDs and 11 KIIs using Dedoose software, from which we picked perceptions of healthcare workers, interventions implemented, and improvement suggestions. The study was reviewed and approved by Malawi National Health Science Research Committee (IRB: 22/02/2866). Results: Overall, the average reporting completeness rate was 83.4% (before) and 98.1% (after), while timeliness was 68.1% and 76.4 respectively. Completeness of reports increased over time: 2018, 78.8%; 2019, 88%; 2020, 96.3% and 2021, 99.9% (p< 0.004). The trend for timeliness has been declining except in 2021, where it improved: 2018, 68.4%; 2019, 68.3%; 2020, 67.1% and 2021, 81% (p< 0.279). Comparing 2021 reporting rates to the mean of three preceding years, both completeness increased from 88% to 99% (in 2021), while timeliness increased from 68% to 81%. Sixty-five percent of reports have maintained meeting a national standard of 90%+ in completeness while only 24% in timeliness. Thirty-two percent of reports met the national standard. Only 9% improved on both completeness and timeliness, and these are; cervical cancer, nutrition care support and treatment, and youth-friendly health services reports. 50% of reports did not improve to standard in timeliness, and only one did not in completeness. On the other hand, factors associated with improvement included improved communications and reminders using internal communication, data quality assessments, checks, and reviews. Decentralizing data entry at the facility level was suggested to improve timeliness. Conclusion: Findings suggest that data quality in HMIS for the district has improved following collaborative efforts. We recommend maintaining such initiatives to identify remaining quality gaps and that results be shared publicly to support increased use of data. These results can inform Ministry of Health and its partners on some interventions and advise initiatives for improving its quality.

Keywords: data quality, data utilization, HMIS, collaboration, completeness, timeliness, decision-making

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Authors: Nesrine Bougarech, Habib Affes

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This research lays the emphasis on the business process reengineering (BPR) which consists in radically altering the organizational processes through the optimal use of information technology (IT) to attain major enhancements in terms of quality, performance and productivity. A survey of the business process reengineering (BPR) was carried out in three French groups and their subsidiaries in Tunisia. The data collected were qualitatively analyzed in an attempt to test the main indicators of the success of a business process reengineering project (BPR) and to compare the importance of these indicators in the context of France versus Tunisia. The study corroborates that the respect of the inherent principles of the business process reengineering (BPR) and the diversity of the human resources involved in the project can lead to better productivity, higher quality of the goods or services and lower cost. Additionally, our results mirror the extent to which the respect of the principles and the diversity of resources are more important in the French companies than in their Tunisian subsidiaries.

Keywords: business process reengineering (BPR), human resources management (HRM), information technology (IT), management

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Authors: Sudirman

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Competence is a term describing capability that correlates with a person’s occupation. The competence of a teacher consists of four, i.e., pedagogical, professional, personality and social competence. These four components are implemented during interacting with students to motivate the students and improve their achievement. The objective of this qualitative study is to explore the roles and contributions of certified teachers in alleviating the issue of poverty to promote a sustainable development. The data comprise primary and secondary data which were generated from observation, interview, documentation and library research. Furthermore, this study offers in-depth information regarding the performance of the teachers in coping with poverty and sustaining development. The result shows that the teacher’s competence positively contributes to the improvement of students’ achievement. This helps the students to prepare for the real work experience by which it results in a better income and, therefore, alleviate poverty. All in all, the quality of today’s teachers can be measured by their contribution in enhancing the students’ competence prior to entering real work, resulting in a wealthy society. This is to deal with poverty and conceptualizing a sustainable development.

Keywords: competence, development, poverty, teachers

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Authors: Alexander Goncharenko, Andrey Denisov, Sergey Alyamkin, Evgeny Terentev

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The neural network quantization is highly desired procedure to perform before running neural networks on mobile devices. Quantization without fine-tuning leads to accuracy drop of the model, whereas commonly used training with quantization is done on the full set of the labeled data and therefore is both time- and resource-consuming. Real life applications require simplification and acceleration of quantization procedure that will maintain accuracy of full-precision neural network, especially for modern mobile neural network architectures like Mobilenet-v1, MobileNet-v2 and MNAS. Here we present a method to significantly optimize training with quantization procedure by introducing the trained scale factors for discretization thresholds that are separate for each filter. Using the proposed technique, we quantize the modern mobile architectures of neural networks with the set of train data of only ∼ 10% of the total ImageNet 2012 sample. Such reduction of train dataset size and small number of trainable parameters allow to fine-tune the network for several hours while maintaining the high accuracy of quantized model (accuracy drop was less than 0.5%). Ready-for-use models and code are available in the GitHub repository.

Keywords: distillation, machine learning, neural networks, quantization

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Authors: Wisnu Adi Yulianto, Agus Slamet, Sri Luwihana, Septian Albar Dwi Suprayogi

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Parboiled rice was developed to produce rice, which has a low glycemic index for diabetics. However, diabetics also have a chromium (Cr) deficiency. Thus, it is important to fortify rice with Cr to increase the Cr content. Moreover, parboiled rice becomes rancid easily and has a musty odor, rendering the rice unfavorable. Natural herbs such as pandan leaves (Pandanus amaryllifolius Roxb.), bay leaves (Syzygium polyanthum [Wigh] Walp) and cinnamon bark powder (Cinnamomon cassia) are commonly added to food as aroma enhancers. Previous research has shown that these herbs could improve insulin sensitivity. The purpose of this study was to evaluate the effect of herbal extract coatings on the cooking quality and the preference level of chromium fortified - parboiled rice (CFPR). The rice grain variety used for this experiment was Ciherang and the fortificant was CrCl3. The three herbal extracts used for coating the CFPR were cinnamon, pandan and bay leaf, with concentration variations of 3%, 6%, and 9% (w/w) for each of the extracts. The samples were analyzed for their alkali spreading value, cooking time, elongation, water uptake ratio, solid loss, colour and lightness; and their sensory properties were determined by means of an organoleptic test. The research showed that coating the CFPR with pandan and cinnamon extracts at a concentration of 3% each produced a preferred CFPR. When coated with those herbal extracts the CFPR had the following cooking quality properties: alkali spreading value 5 (intermediate gelatinization temperature), cooking time, 26-27 min, color value, 14.95-15.00, lightness, 42.30 – 44.06, elongation, 1.53 – 1.54, water uptake ratio , 4.05-4.06, and solid loss, 0.09/100 g – 0.13 g/100 g.

Keywords: bay leaves, chromium, cinnamon, pandan leaves, parboiled rice

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Authors: Yin Yuanling

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A Deep Feedback Recurrent Neural Network (DFRNN) and Bidirectional Long Short-Term Memory (BiLSTM) are designed to address the problem of low accuracy of traditional relationship extraction models. This method combines a deep feedback-based recurrent neural network (DFRNN) with a bi-directional long short-term memory (BiLSTM) approach. The method combines DFRNN, which extracts local features of text based on deep feedback recurrent mechanism, BiLSTM, which better extracts global features of text, and Self-Attention, which extracts semantic information. Experiments show that the method achieves an F1 value of 76.69% on the CEC dataset, which is 0.0652 better than the BiLSTM+Self-ATT model, thus optimizing the performance of the deep learning method in the event relationship extraction task.

Keywords: event relations, deep learning, DFRNN models, bi-directional long and short-term memory networks

Procedia PDF Downloads 137

Authors: I. O. Oladipo, Olusegun Adewale Ajayi, Omoniyi Oladipupo Adigun

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Information Communication Technology (ICT) have the potential to contribute to different facets of educational development and effective learning; expanding access, promoting efficiency, improve the quality of learning, enhancing the quality of teaching and provide important mechanism for the economic crisis. Considering the prevalence of unemployment among the higher institution graduates in this nation, in which much seems not to have been achieved in this direction. In view of this, the purpose of this study is to create an awareness and enlightenment of ICT for empowerment opportunities after school. A self-developed modified 4-likert scale questionnaire was used for data collection among Colleges of Education, Physical and Health Education students in Oyo State. Inferential statistical analysis of chi-square set at 0.05 alpha levels was used to analyze the stated hypotheses. The study concludes that awareness and enlightenment of ICT significantly influence empowerment opportunities and recommended that college of education students should be encouraged on the application of ICT for job opportunity after school.

Keywords: employment, empowerment, information communication technology, physical education

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Authors: C. G. Jinimole, A. Harsha

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One of the key problems facing in the analysis of Computed Tomography (CT) images is the poor contrast of the images. Image enhancement can be used to improve the visual clarity and quality of the images or to provide a better transformation representation for further processing. Contrast enhancement of images is one of the acceptable methods used for image enhancement in various applications in the medical field. This will be helpful to visualize and extract details of brain infarctions, tumors, and cancers from the CT image. This paper presents a comparison study of five contrast enhancement techniques suitable for the contrast enhancement of CT images. The types of techniques include Power Law Transformation, Logarithmic Transformation, Histogram Equalization, Contrast Stretching, and Laplacian Transformation. All these techniques are compared with each other to find out which enhancement provides better contrast of CT image. For the comparison of the techniques, the parameters Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) are used. Logarithmic Transformation provided the clearer and best quality image compared to all other techniques studied and has got the highest value of PSNR. Comparison concludes with better approach for its future research especially for mapping abnormalities from CT images resulting from Brain Injuries.

Keywords: computed tomography, enhancement techniques, increasing contrast, PSNR and MSE

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Authors: Milena M. Melo, Jane M. Santos, Severine Frere, Valderio A. Reisen, Neyval C. Reis Jr., Mariade Fátima S. Leite

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Although there had been a many studies that shows the impact of air pollution on physical health, comparatively less was known of human behavioral responses and annoyance impacts. Annoyance caused by air pollution is a public health problem because it can be an ambient stressor causing stress and disease and can affect quality of life. The objective of this work is to evaluate the annoyance caused by air pollution in two different industrialized urban areas, Dunkirk (France) and Vitoria (Brazil). The populations of these cities often report feeling annoyed by dust. Surveys were conducted, and the collected data were analyzed using statistical analyses. The results show that sociodemographic variables, importance of air quality, perceived industrial risk, perceived air pollution and occurrence of health problems play important roles in the perceived annoyance. These results show the existence of a common problem in geographically distant areas and allow stakeholders to develop prevention strategies.

Keywords: air pollution, annoyance, industrial risks, public health, perception of pollution, settled dust

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Authors: Heshalini Rajagopal, Li Sze Chow, Raveendran Paramesran

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Magnetic Resonance Imaging (MRI) is one of the most important medical imaging modality. Subjective assessment of the image quality is regarded as the gold standard to evaluate MR images. In this study, a database of 210 MR images which contains ten reference images and 200 distorted images is presented. The reference images were distorted with four types of distortions: Rician Noise, Gaussian White Noise, Gaussian Blur and DCT compression. The 210 images were assessed by ten subjects. The subjective scores were presented in Difference Mean Opinion Score (DMOS). The DMOS values were compared with four FR-IQA metrics. We have used Pearson Linear Coefficient (PLCC) and Spearman Rank Order Correlation Coefficient (SROCC) to validate the DMOS values. The high correlation values of PLCC and SROCC shows that the DMOS values are close to the objective FR-IQA metrics.

Keywords: medical resonance (MR) images, difference mean opinion score (DMOS), full reference image quality assessment (FR-IQA)

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Authors: Yasir Ramadhan

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This study aims to investigate tax avoidance practices when a financial crisis occurs due to the effects of the COVID-19 pandemic. This study also finds out how the influence of independent commissioners and external auditors on tax avoidance practices during the COVID-19 pandemic. Tax avoidance practices are measured by the current ETR. The role of the independent board of commissioners is measured by the proportion of independent commissioners in the composition of the board of commissioners, while the external auditor is measured by audit quality. In this study, there were 342 observations of companies listed on the Indonesia Stock Exchange from 2019 to 2020. This study used the difference-in-differences (DiD) method in data analysis. The results of this study indicate that companies do tax avoidance during the COVID-19 pandemic. Meanwhile, independent commissioners and qualified audits are not proven to be able to negate tax avoidance practices during the COVID-19 Pandemic. These results also show that a higher proportion of independent commissioners and audit quality are not sufficient for countries with low levels of auditor litigation and investor protection and weak regulatory frameworks.

Keywords: audit, commissioner, tax avoidance, COVID-19 pandemic

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Authors: Smitha Haridasan, Zelalem Demissie, Atri Dutta, Ajita Rattani

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Aided by the wind, all it takes is one ember and a few minutes to create a wildfire. Wildfires are growing in frequency and size due to climate change. Wildfires and its consequences are one of the major environmental concerns. Every year, millions of hectares of forests are destroyed over the world, causing mass destruction and human casualties. Thus early detection of wildfire becomes a critical component to mitigate this threat. Many computer vision-based techniques have been proposed for the early detection of forest fire using video surveillance. Several computer vision-based methods have been proposed to predict and detect forest fires at various spectrums, namely, RGB, HSV, and YCbCr. The aim of this paper is to propose a multi-spectral deep learning model that combines information from different spectrums at intermediate layers for accurate fire detection. A heterogeneous dataset assembled from publicly available datasets is used for model training and evaluation in this study. The experimental results show that multi-spectral deep learning models could obtain an improvement of about 4.68 % over those based on a single spectrum for fire detection.

Keywords: deep learning, forest fire detection, multi-spectral learning, natural hazard detection

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Authors: Juan Sebastián Hernández

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The Nevado del Ruíz volcano, located between the limits of the Departments of Caldas and Tolima in Colombia, presented an unstable behaviour in the course of the year 2020, this volcanic activity led to secondary effects on the crust, which is why the prediction of deformations becomes the task of geoscientists. In the course of this article, the use of tropospheric variables such as evapotranspiration, UV aerosol index, carbon monoxide, nitrogen dioxide, methane, surface temperature, among others, is used to train a set of neural networks that can predict the behaviour of the resulting phase of an unrolled interferogram with the DInSAR technique, whose main objective is to identify and characterise the behaviour of the crust based on the environmental conditions. For this purpose, variables were collected, a generalised linear model was created, and a set of neural networks was created. After the training of the network, validation was carried out with the test data, giving an MSE of 0.17598 and an associated r-squared of approximately 0.88454. The resulting model provided a dataset with good thematic accuracy, reflecting the behaviour of the volcano in 2020, given a set of environmental characteristics.

Keywords: crustal deformation, Tropomi, neural networks (ANN), volcanic activity, DInSAR

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Authors: Chutikarn Sriviboon

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The objectives of this research were to study the operation of the Labor Fund and to investigate the needs for money and assistance from Thai laborers both from within the system and out of the system and to compare between the assistance from domestic and international funds. The population of this study included three labor groups: group one was laborer in the system who were the members of saving cooperative, group two was laborer in the system who were not the members of saving cooperative, and group three was laborer who were not in the system. This was a mixed research of quantitative and qualitative methods. The findings can be categorized into four parts. First, the labor fund was beneficial to Thai laborers by giving access to government funds but the weakness was found to be poor public relations. Second, the labor funds should extend their assistance to laborer in the system who was not the members of saving cooperative. Third, the comparison between domestic labor funds and international labor funds revealed that there were no international funds which provided assistance the same way as Thai labor funds. Finally, there was a need to improve the management of labor funds and to provide long term assistance to Thai labors.

Keywords: effectiveness, quality, labor funds, service

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Authors: Surabhi Gautam, Uma Kumar, Rima Dada

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A sustained acute-phase response in Rheumatoid Arthritis (RA) is associated with increased joint damage and inflammation leading to progressive disability. It is induced continuously by consecutive stimuli of proinflammatory cytokines, following a wide range of pathophysiological reactions, leading to increased synthesis of acute phase proteins like C - reactive protein (CRP) and dysregulation in levels of immunomodulatory soluble Human Leukocyte Antigen-G (HLA-G) molecule. This study was designed to explore the effect of yoga and meditation based lifestyle intervention (YMLI) on inflammatory markers in RA patients. Blood samples of 50 patients were collected at baseline (day 0) and after 30 days of YMLI. Patients underwent a pretested YMLI under the supervision of a certified yoga instructor for 30 days including different Asanas (physical postures), Pranayama (breathing exercises), and Dhayna (meditation). Levels of CRP, IL-6, IL-17A, soluble HLA-G and erythrocyte sedimentation rate (ESR) were measured at day 0 and 30 interval. Parameters of disease activity, disability quotient, pain acuity and quality of life were also assessed by disease activity score (DAS28), health assessment questionnaire (HAQ), visual analogue scale (VAS), and World Health Organization Quality of Life (WHOQOL-BREF) respectively. There was reduction in mean levels of CRP (p < 0.05), IL-6 (interleukin-6) (p < 0.05), IL-17A (interleukin-17A) (p < 0.05) and ESR (p < 0.05) and elevation in soluble HLA-G (p < 0.05) at 30 days compared to baseline level (day 0). There was reduction seen in DAS28-ESR (p < 0.05), VAS (p < 0.05) and HAQ (p < 0.05) after 30 days with respect to the base line levels (day 0) and significant increase in WHOQOL-BREF scale (p < 0.05) in all 4 domains of physical health, psychological health, social relationships, and environmental health. The present study has demonstrated that yoga practices are associated with regression of inflammatory processes by reducing inflammatory parameters and regulating the levels of soluble HLA-G significantly in active RA patients. Short term YMLI has significantly improved pain perception, disability quotient, disease activity and quality of life. Thus this simple life style intervention can reduce disease severity and dose of drugs used in the treatment of RA.

Keywords: inflammation, quality of life, rheumatoid arthritis, yoga and meditation

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Authors: Imen Elleuch, Wael Ouarda, Gargouri Bilel

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We proposes in this paper a Deep Learning based approach to classify text in order to enrich an Arabic ontology based on the objects classes of Gaston Gross. Those object classes are defined by taking into account the syntactic and semantic features of the treated language. Thus, our proposed approach is a hybrid one. In fact, it is based on the one hand on the object classes that represents a knowledge based-approach on classification of text and in the other hand it uses the deep learning approach that use the word embedding-based-approach to classify text. We have applied our proposed approach on a corpus constructed from an Arabic dictionary. The obtained semantic classification of text will enrich the Arabic objects classes ontology. In fact, new classes can be added to the ontology or an expansion of the features that characterizes each object class can be updated. The obtained results are compared to a similar work that treats the same object with a classical linguistic approach for the semantic classification of text. This comparison highlight our hybrid proposed approach that can be ameliorated by broaden the dataset used in the deep learning process.

Keywords: deep-learning approach, object-classes, semantic classification, Arabic

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Authors: Nunu Nakashidze, Shota Lominadze, Darejan Jashi

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Citrus culture used to be one of the leading fields of sub-tropical agriculture in Georgia and especially in Adjara region, but the citrus production has been significantly decreased in recent years due to deterioration of quality index of fruit and reduction of sale markets. The fact severely affected both the economy of Republic and population. Intensive technologies of citrus fruit production are widely implemented in the world practices, which include the following: variety of species, consumption of fertilizers and chemicals, proper use of fruit production and etc. However working on technologies which ensure getting of high quality and plentiful product is very much important if taking into consideration modern, global ecological problems. Using of bio-preparations for plant nourishment is considered as one of the activities. The present work discusses liquid organic fertilizer 'Biorag' produced in Georgia and influence of its growth stimulation (Gakhokidze N1, N2, N3) on agrochemical index of soils and mineral composition of fruit of Citrus Unshiu orchards cultivated in the sub-tropical zone of Black Sea in Adjara region. It was ascertained that liquid organic fertilizers used in the orchard of citrus 'Unshiu' and influence of growth stimulators on the quality index of fruit are not clearly shown in comparison with control one. A small priority is noticed in case of growth stimulators. In conditions of red soils, liquid organic fertilizers and growth stimulators added in the nutrition of the citrus more or less influence the dry material of fruit and the composition of ash and nutrition elements. Agro-chemical index of the soil, except exchange acidity, is somehow enlarged which is one of the positive results in this case.

Keywords: growth stimulator, liquid fertilizer, plant, fruit, soil

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Authors: John Akpesiri Olotewo

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One of the controversies in existing marketing literatures is on how to retain existing and new customers to have repurchase intention in the long-run; however, empirical answer to this question is scanty in existing studies. Thus, this study investigates the moderating effect of consumer loyalty on long-run repurchase intentions in telecommunication industry using Lagos State environs. The study adopted field survey research design using questionnaire to elicit responses from 250 respondents who were selected using random and stratified random sampling techniques from the telecommunication industry in Lagos State, Nigeria. The internal consistency of the research instrument was verified using the Cronbach’s alpha, the result of 0.89 implies the acceptability of the internal consistency of the survey instrument. The test of the research hypotheses were analyzed using Pearson Product Method of Correlation (PPMC), simple regression analysis and inferential statistics with the aid of Statistical Package for Social Science version 20.0 (SPSS). The study confirmed that customer satisfaction has a significant relationship with customer loyalty in the telecommunication industry; also Service quality has a significant relationship with customer loyalty to a brand; loyalty programs have a significant relationship with customer loyalty to a network operator in Nigeria and Customer loyalty has a significant effect on the long run repurchase intentions of the customer. The study concluded that one of the determinants of long term profitability of a business entity is the long run repurchase intentions of its customers which hinges on the level of brand loyalty of the customer. Thus, it was recommended that service providers in Nigeria should improve on factors like customer satisfaction, service quality, and loyalty programs in order to increase the loyalty of their customer to their brands thereby increasing their repurchase intentions.

Keywords: customer loyalty, long run repurchase intentions, brands, service quality and customer satisfaction

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Authors: Clarissa Delariarte

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With the aim of helping the poorest of the poor achieve quality education, Psychology students supported and served as teacher assistants to its Early Childhood Education Center in two barangays since the program began in 1999. Making use of qualitative approach, the impact of the program to 29 alumni who served as teacher assistants between 2000-2014 was assessed. Results show that the impact to the alumni is in cognitive as well as social-emotional in terms of feelings of deep satisfaction and sense of volunteerism which is being carried out in their respective workspaces. They also expressed positive feelings of inspiration, gratefulness and happiness. A wider perspective in life, being confident, creative and resourceful was also articulated as concrete impacts. It is concluded that the program had an impact on helping the helper and is a concrete manifestation of the academe being successful in its commitment of forming individuals into becoming integrated and compassionate in the service of the Church and Society. It implies that more opportunities of helping others be provided to students since, in the final analysis, is actually an opportunity of helping the helper be of better service to others.

Keywords: applied psychology, life skill, qualitative research, quality education

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Authors: Graciela Soares Marcelli, Elison Eduardo Jardim Bierhals, Luciane Teresa Salvi, Claudineia Brazil, Rafael Haag

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The sun is a source of renewable energy, and its use as both a source of heat and light is one of the most promising energy alternatives for the future. To measure the thermal or photovoltaic systems a solar irradiation database is necessary. Brazil still has a reduced number of meteorological stations that provide frequency tests, as an alternative to the radio data platform, with reanalysis systems, quite significant. ERA-Interim is a global fire reanalysis by the European Center for Medium-Range Weather Forecasts (ECMWF). The data assimilation system used for the production of ERA-Interim is based on a 2006 version of the IFS (Cy31r2). The system includes a 4-dimensional variable analysis (4D-Var) with a 12-hour analysis window. The spatial resolution of the dataset is approximately 80 km at 60 vertical levels from the surface to 0.1 hPa. This work aims to make a comparative analysis between the ERA-Interim data and the data observed in the Solarimmetric Atlas of the State of Rio Grande do Sul, to verify its applicability in the absence of an observed data network. The analysis of the results obtained for a study region as an alternative to the energy potential of a given region.

Keywords: energy potential, reanalyses, renewable energy, solar radiation

Procedia PDF Downloads 159

Authors: A. Tarantino, F. Lops, G. Lopriore, G. Disciglio

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Biostimulants are known as the organic fertilizers that can be applied in agriculture in order to increase nutrient uptake, growth and development of plants and improve quality, productivity and the environmental positive impacts. The aim of this study was to test the effects of some commercial biostimulants products (Bion® 50 WG, Hendophyt ® PS, Ergostim® XL and Radicon®) on vegeto-productive behavior and qualitative characteristics of fruits of two emerging apricot cultivars (Orange Rubis® and Farbaly®). The study was conducted during the spring-summer season 2015, in a commercial orchard located in the agricultural area of Cerignola (Foggia district, Apulian region, Southern Italy). Eight years old apricot trees, cv ‘Orange Rubis’ and ‘Farbaly®’, were used. The experimental data recorded during the experimental trial were: shoot length, total number of flower buds, flower buds drop and time of flowering and fruit set. Total yield of fruits per tree and quality parameters were determined. Experimental data showed some specific differences among the biostimulant treatments. Concerning the yield of ‘Orange Rubis’, except for the Bion treatment, the other three biostimulant treatments showed a tendentially lower values than the control. The yield of ‘Farbaly’ was lower for the Bion and Hendophyt treatments, higher for the Ergostim treatment, when compared with the yield of the control untreated. Concerning the soluble solids content, the juice of ‘Farbaly’ fruits had always higher content than that of ‘Orange Rubis’. Particularly, the Bion and the Hendophyt treatments showed in both harvest values tendentially higher than the control. Differently, the four biostimulant treatments did not affect significantly this parameter in ‘Orange Rubis’. With regard to the fruit firmness, some differences were observed between the two harvest dates and among the four biostimulant treatments. At the first harvest date, ‘Orange Rubis’ treated with Bion and Hendophyt biostimulants showed texture values tendentially lower than the control. Instead, ‘Farbaly’ for all the biostimulant treatments showed fruit firmness values significantly lower than the control. At the second harvest, almost all the biostimulants treatments in both ‘Orange Rubis’ and ‘Farbaly’ cultivar showed values lower than the control. Only ‘Farbaly’ treated with Radicon showed higher value in comparison to the control.

Keywords: apricot, fruit quality, growth, organic natural fertilizer

Procedia PDF Downloads 323

Authors: Zahra Soltani Shal

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Introduction: The COVID-19 pandemic marks an extraordinary global public health crisis unseen in the last century, with its rapid spread worldwide and associated mortality burden. Healthcare resilience during a pandemic is crucial not only for continuous and safe patients care but also for control of any outbreak. Aim: The present study was conducted to discover the organizational variables effective in increasing resilience and continuing the work of nurses in critical and stressful pandemic conditions. Method: The study population is nurses working in hospitals for patients with coronavirus. Sampling was done purposefully and information was collected from 15 nurses through In-depth semi-structured interviews. The interview was conducted to analyze the data using the framework analysis method consisting of five steps and is classified in the table. Results: According to the findings through semi-structural interviews, among organizational variables, organizational commitment (Affective commitment, continuous commitment, normative commitment) has played a prominent role in nurses' resilience. Discussion: despite the non-withdrawal of nurses and their resilience, due to the negative quality of their working life, the mentioned variable has affected their level of performance and ability and leads to fatigue and physical and mental exhaustion. Implications for practice: By equipping hospitals and improving the facilities of nurses, their organizational commitment can be increased and lead to their resilience in critical situations. Supervisors and senior officials at the hospitals should be responsible for nurses' health and safety. A clear and codified program in critical situations and comprehensive management is effective in improving the quality of the work-life of nurses. Creating an empathetic and interactive environment can help promote nurses' mental health.

Keywords: organizational commitment, quality of work life, nurses resilience, pandemic, coronavirus

Procedia PDF Downloads 154