Search results for: international standard industrial classification

Authors: P. Brinks, O. Kornadt, R. Oly

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This research focuses on the optimization of glazed surfaces and the assessment of possible solar gains in industrial buildings. Existing window rating methods for single windows were evaluated and a new method for a simple analysis of energy gains and losses by single windows was introduced. Furthermore extensive transient building simulations were carried out to appraise the performance of low cost polycarbonate multi-cell sheets in interaction with typical buildings for industrial applications. Mainly, energy-saving potential was determined by optimizing the orientation and area of such glazing systems in dependency on their thermal qualities. Moreover the impact on critical aspects such as summer overheating and daylight illumination was considered to ensure the user comfort and avoid additional energy demand for lighting or cooling. Hereby the simulated heating demand could be reduced by up to 1/3 compared to traditional architecture of industrial halls using mainly skylights.

Keywords: solar architecture, Passive Solar Building Design, glazing, Low-Energy Buildings, industrial buildings

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Authors: Kasra Khorsand-Kazemi, Bianca Vizcaino, Mandeep Chhajer Jain, Maryam Moradpour

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This work presents an approach to characterize a non- contact microwave sensor using waveguides for different standard liquids such as ethanol, methanol and 2-propanol (Isopropyl Alcohol). Wideband waveguides operating between 12.4GHz to 18 GHz form the core of the sensing structure. Waveguides are sensitive to changes in conductivity of the sample under test (SUT), making them an ideal tool to characterize different polar liquids. As conductivity of the sample under test increase, the loss tangent of the material increase, thereby decreasing the S21 (dB) response of the waveguide. Among all the standard liquids measured, methanol exhibits the highest conductivity and 2-Propanol exhibits the lowest. The cutoff frequency measured for ethanol, 2-propanol, and methanol are 10.28 GHz, 10.32 GHz, and 10.38 GHz respectively. The measured results can be correlated with the loss tangent results of the standard liquid measured using the dielectric probe. This conclusively enables us to characterize different liquids using waveguides expanding the potential future applications in domains ranging from water quality management to bio-medical, chemistry and agriculture.

Keywords: Waveguides, , Microwave sensors, , Standard liquids characterization, Non-contact sensing

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Authors: Taoues Aimeur

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The present study is the first comparative study of discourses surrounding women on International Women’s Day in French-language newspapers and Arabic-language newspapers in Algeria. It aims at critically examining the way women are positioned on International Women’s Day in four Algerian newspapers by focusing on the post-civil war era in Algeria (2003 till the present time). This is by applying Feminist Critical Discourse Analysis to question representations of women in the selected newspapers by revealing the gender ideologies embedded in their linguistic and visual discourses. The Francophone newspapers chosen for the present research are El Watan and Liberté. As for the Arabophone ones, El Khabar and Echorouk have been selected. The results of the study would help build an understanding of the meanings of gender that are embedded in the discourses of the selected news outlets which differ both linguistically and ideologically.

Keywords: Arabic-language newspapers, Critical Discourse Analysis, discourses, French-language newspapers, gender, International Women’s Day

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Authors: O. Onoriode Emoyan, E. Eyitemi Akporhonor, Charles Otobrise

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Polycyclic Aromatic Hydrocarbons (PAHs) are formed mainly as a result of incomplete combustion of organic materials during industrial, domestic activities or natural occurrence. Their toxicity and contamination of terrestrial and aquatic ecosystem have been established. Though with limited validity index, previous research has focused on PAHs isomer pair ratios of variable physicochemical properties in source identification. The objective of this investigation was to determine the empirical validity of Pearson correlation coefficient (PCC) and cluster analysis (CA) in PAHs source identification along soil samples of different land uses. Therefore, 16 PAHs grouped as endocrine disruption substances (EDSs) were determined in 10 sample stations in top and sub soils seasonally. PAHs was determined the use of Varian 300 gas chromatograph interfaced with flame ionization detector. Instruments and reagents used are of standard and chromatographic grades respectively. PCC and CA results showed that the classification of PAHs along kinetically and thermodyanamically-favoured and those derived directly from plants product through biologically mediated processes used in source signature is about the predominance PAHs are likely to be. Therefore the observed PAHs in the studied stations have trace quantities of the vast majority of the sixteen un-substituted PAHs which may ultimately inhabit the actual source signature authentication. Type and extent of bacterial metabolism, transformation products/substrates, and environmental factors such as: salinity, pH, oxygen concentration, nutrients, light intensity, temperature, co-substrates and environmental medium are hereby recommended as factors to be considered when evaluating possible sources of PAHs.

Keywords: comparative correlation, kinetically and thermodynamically-favored PAHs, pearson correlation coefficient, cluster analysis, sources evaluation

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Authors: Natalia Carolina Encalada Castillo

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As part of an intended radical policy change compared to former administrations in Ecuador, the transformation of the institutionality of international cooperation during the period of President Rafael Correa was considered as a key element for the construction of the state of 'Good Living'. This intention led to several regulatory changes in the reception of cooperation for development, and even the departure of some foreign cooperation agencies. Moreover, Ecuador launched the initiative to become a donor of cooperation towards other developing countries through the ‘South-South Cooperation’ approach. All these changes were institutionalized through the Ecuadorian System of International Cooperation as a new framework to establish rules and policies that guarantee a sovereign management of foreign aid. Therefore, this research project has been guided by two questions: What were the factors that motivated the transformation of the institutionality of international cooperation in Ecuador from 2007 to 2017? and, what were the implications of this transformation in terms of the international role of the country? This paper seeks to answer these questions through Role Theory within a Constructivist meta-theoretical perspective, considering that in this case, changes at the institutional level in the field of cooperation, responded not only to material motivations but also to interests built on the basis of a specific state identity. The latter was only possible to affirm through specific roles such as ‘sovereign recipient of cooperation’ as well as ‘donor of international cooperation’. However, the performance of these roles was problematic as they were not easily accepted by the other actors in the international arena or in the domestic level. In terms of methodology, these dynamics are analyzed in a qualitative way mainly through interpretive analysis of the discourse of high-level decision-makers from Ecuador and other cooperation actors. Complementary to this, document-based research of relevant information as well as interviews have been conducted. Finally, it is concluded that even if material factors such as infrastructure needs, trade and investment interests, as well as reinforcement of state control and monitoring of cooperation flows, motivated the institutional transformation of international cooperation in Ecuador; the essential basis of these changes was the search for a new identity for the country to be projected in the international arena. This identity started to be built but continues to be unstable. Therefore, it is important to potentiate the achievements of the new international cooperation policies, and review their weaknesses, so that non-reimbursable cooperation funds received as well as ‘South-South cooperation’ actions, contribute effectively to national objectives.

Keywords: Ecuador, international cooperation, Role Theory, state identity

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Authors: Mpho Mokoatle, Darlington Mapiye, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

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Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on $k$-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0%, 80.5%, 80.5%, 63.6%, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms.

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

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Authors: Darlington Mapiye, Mpho Mokoatle, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

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Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on k-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0 %, 80.5 %, 80.5 %, 63.6 %, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

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Authors: Alina Gilmanova

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China’s dependency on coal for energy is causing pollution in China and abroad. To supply the increasing energy demand and being under the pressure from international society to reduce the emissions, China was pushed to develop renewable energy. The increasing subsidies in Renewable energy sources (RES) led not only to the price-cutting but also affecting the international trade in green technology sector. In order to evaluate the role of RES in foreign policy of China, I am going to give an (i) overview of RES development in China and examine the cooperation between China and (ii) developed, (ii) developing and emerging countries. The conclusive remarks are intended to address the question of how the present Chinese renewable energy development is impacting its foreign policy and international society.

Keywords: renewable energy, China, foreign affairs, brics, cooperation

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Authors: Mahmud Hafsat Hussaini, Eldah Ephraim Eldah, Bata Zoakah Amina

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This research work was aimed at examining the challenges faced by passengers using Arik air for domestic and international travels. Passengers do complain of delay flights, theft and rude behavior by Arik staff while on transit or in the process of travelling using the aircraft. Being the national carrier in Nigeria these behaviors have tarnished the image of the airline and makes travel experience to be challenging. Hundred survey questionnaires were administered to travellers who have used the airline for domestic and international flights. Findings show that the staff of the airline do lack customer care skills and are sometimes rude to customers. The airline does have different agents that book for international flights who delays confirming bookings even after payment. The website of the airline is mostly down and makes bookings difficult. Other findings related to the study are a delay of domestic flights within Nigeria. Passengers are sometimes kept for 8 hours in the airport due to delay of flights. The study, therefore, recommends that flight schedule should be adhered to and staff should be trained to meet of with passengers demand. The security of guest luggage at the airport should be put in place to avoid theft. An effective booking platform should be accessible to passengers for easy booking.

Keywords: examining, challenges, domestic, international, travels

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Authors: Uche A. Nnawulezi

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Over the past decades, the acquisition and utilization of nuclear energy have remained a standout amongst the most intractable issues which past world leaders have unsuccessfully endeavored to grapple with. This study analyzes the present advancement and enactment on the acquisition and utilization of nuclear energy in contemporary international law. It seeks to address international co-operations in the field of nuclear energy by looking at what nuclear energy is all about and how it came into being. It also seeks to address concerns expressed by a few researchers on the position of nuclear law in the most extensive domain of the law by looking at the authoritative procedure for nuclear law, system of arrangements and traditions. This study also agrees in favour of treaty on non-proliferation of nuclear weapons based on human right and humanitarian principles that are not duly moral, but also legal ones. Specifically, the past development activities on nuclear weapon and the practical system of the nuclear energy institute will be inspected. The study noted among others, former president Obama's remark on nuclear energy and Pakistan nuclear policies and its attendant outcomes. Essentially, we depended on documentary evidence and henceforth scooped a great part of the data from secondary sources. The study emphatically advocates for the adoption of absolute liability principles and setting up of a viability trust fund, all of which will help in sustaining global peace where global best practices in acquisition and use of nuclear energy will be widely accepted in the contemporary international law. Essentially, the fundamental proposals made in this paper if completely adopted, might go far in fortifying the present advancement and enactment on the application and utilization of nuclear energy and accordingly, addressing a portion of the intractable issues under international law.

Keywords: nuclear energy, international law, acquisition, development

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Authors: Zoran Šverko, Saša Vlahinić, Nino Stojković, Ivan Markovinović

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In this article, the classification of target letters is performed using data from the EEG P300 Speller paradigm. Neural networks trained with the results of dynamic connectivity analysis between different brain regions are used for classification. Dynamic connectivity analysis is based on the adaptive window size and the imaginary part of the complex Pearson correlation coefficient. Brain dynamics are analysed using the relative intersection of confidence intervals for the imaginary component of the complex Pearson correlation coefficient method (RICI-imCPCC). The RICI-imCPCC method overcomes the shortcomings of currently used dynamical connectivity analysis methods, such as the low reliability and low temporal precision for short connectivity intervals encountered in constant sliding window analysis with wide window size and the high susceptibility to noise encountered in constant sliding window analysis with narrow window size. This method overcomes these shortcomings by dynamically adjusting the window size using the RICI rule. This method extracts information about brain connections for each time sample. Seventy percent of the extracted brain connectivity information is used for training and thirty percent for validation. Classification of the target word is also done and based on the same analysis method. As far as we know, through this research, we have shown for the first time that dynamic connectivity can be used as a parameter for classifying EEG signals.

Keywords: dynamic connectivity analysis, EEG, neural networks, Pearson correlation coefficients

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Authors: Jae Ni Jang, Young Uk Kim

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Background: Chat Generative Pre-training Transformer-3 (ChatGPT; San Francisco, California, Open Artificial Intelligence) is an artificial intelligence chatbot based on a large language model designed to generate human-like text. As the usage of ChatGPT is increasing among less knowledgeable patients, medical students, and anesthesia and pain medicine residents or trainees, we aimed to evaluate the accuracy of ChatGPT-3 responses to questions about the American Society of Anesthesiologists (ASA) classification based on patients’ underlying diseases and assess the quality of the generated responses. Methods: A total of 47 questions were submitted to ChatGPT using textual prompts. The questions were designed for ChatGPT-3 to provide answers regarding ASA classification in response to common underlying diseases frequently observed in adult patients. In addition, we created 18 questions regarding the ASA classification for pediatric patients and pregnant women. The accuracy of ChatGPT’s responses was evaluated by cross-referencing with Miller’s Anesthesia, Morgan & Mikhail’s Clinical Anesthesiology, and the American Society of Anesthesiologists’ ASA Physical Status Classification System (2020). Results: Out of the 47 questions pertaining to adults, ChatGPT -3 provided correct answers for only 23, resulting in an accuracy rate of 48.9%. Furthermore, the responses provided by ChatGPT-3 regarding children and pregnant women were mostly inaccurate, as indicated by a 28% accuracy rate (5 out of 18). Conclusions: ChatGPT provided correct responses to questions relevant to the daily clinical routine of anesthesiologists in approximately half of the cases, while the remaining responses contained errors. Therefore, caution is advised when using ChatGPT to retrieve anesthesia-related information. Although ChatGPT may not yet be suitable for clinical settings, we anticipate significant improvements in ChatGPT and other large language models in the near future. Regular assessments of ChatGPT's ASA classification accuracy are essential due to the evolving nature of ChatGPT as an artificial intelligence entity. This is especially important because ChatGPT has a clinically unacceptable rate of error and hallucination, particularly in pediatric patients and pregnant women. The methodology established in this study may be used to continue evaluating ChatGPT.

Keywords: American Society of Anesthesiologists, artificial intelligence, Chat Generative Pre-training Transformer-3, ChatGPT

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Authors: John Cheferson R. De Belen, John Paul G. Elizares, Ronald John G. Raz, Janina Elyse A. Reyes, Charie G. Salengua, Aristotle L. Soriano

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Plastic is a type of synthetic or man-made polymer that can readily be molded into a variety of products. Its usage over the past century has enabled society to make huge technological advances. The workers of United Asia International Plastics Corporation (UAIPC), a plastic manufacturing company performs manual packaging which causes fatigue and stress on their arm, neck, and legs due to extended periods of standing and repetitive motions. With the use of the Fishbone Diagram, Five-Why Analysis, Rapid Entire Body Assessment (REBA), and Anthropometry, the stressful tasks and activities were identified and analyzed. Given the anthropometric measurements obtained from the workers, improved dimensions for the tables and chairs should be used and provide a new packaging machine. The validation of this proposal shall follow after its implementation. By eliminating fatigue during working hours in the production, the workers will be at ease at performing their work properly; productivity will increase that will lead to more profit. Further areas for study include measurement and comparison of the worker’s anthropometric measurement with the industry standard.

Keywords: anthropometry, fishbone diagram, five-why analysis, rapid entire body assessment

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Authors: Joseph Lillington, Tom Gout, Mike Harrison, Ian Farnan

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The vitrification of high-level nuclear waste within borosilicate glass and its incorporation within a multi-barrier repository deep underground is widely accepted as the preferred disposal method. However, for this to happen, any safety case will require validation that the initially localized radionuclides will not be considerably released into the near/far-field. Therefore, accurate mechanistic models are necessary to predict glass dissolution, and these should be robust to a variety of incorporated waste species and leaching test conditions, particularly given substantial variations across international waste-streams. Here, machine learning is used to predict glass material properties (viscosity, density) and glass leaching model parameters from large-scale industrial data. A variety of different machine learning algorithms have been compared to assess performance. Density was predicted solely from composition, whereas viscosity additionally considered temperature. To predict suitable glass leaching model parameters, a large simulated dataset was created by coupling MATLAB and the chemical reactive-transport code HYTEC, considering the state-of-the-art GRAAL model (glass reactivity in allowance of the alteration layer). The trained models were then subsequently applied to the large-scale industrial, experimental data to identify potentially appropriate model parameters. Results indicate that ensemble methods can accurately predict viscosity as a function of temperature and composition across all three industrial datasets. Glass density prediction shows reliable learning performance with predictions primarily being within the experimental uncertainty of the test data. Furthermore, machine learning can predict glass dissolution model parameters behavior, demonstrating potential value in GRAAL model development and in assessing suitable model parameters for large-scale industrial glass dissolution data.

Keywords: machine learning, predictive modelling, pattern recognition, radioactive waste glass

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Authors: Eva Tsouparopoulou, Maria Symeonaki

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The internationally documented declining survey response rates of the last two decades are mainly attributed to refusals. In fieldwork, a refusal may be obtained not only from the respondent himself/herself, but from other sources on the respondent’s behalf, such as other household members, apartment building residents or administrator(s), and neighborhood residents. In this paper, we investigate how the composition of the demographic profile of survey refusals changes when different classifications are implemented and the classification issues arising from that. The analysis is based on the 2002-2018 European Social Survey (ESS) datasets for Belgium, Germany, and United Kingdom. For these three countries, the size of selected sample units coded as a type of refusal for all nine under investigation rounds was large enough to meet the purposes of the analysis. The results indicate the existence of four different possible classifications that can be implemented and the significance of choosing the one that strengthens the contrasts of the different types of respondents' demographic profiles. Since the foundation of social quantitative research lies in the triptych of definition, classification, and measurement, this study aims to identify the multiplicity of the definition of survey refusals as a methodological tool for the continually growing research on non-response.

Keywords: non-response, refusals, European social survey, classification

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Authors: Alan C. Lin, Ricky N. Joevan

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This paper focuses on developing a system to transfer mold base plates and standard parts faster during the stage of injection mold design. This system not only provides a way to compare the file version, but also it utilizes Siemens NX 10 to isolate the updated information into a single executable file (.dll), and then, the file can be transferred without the need of transferring the whole file. By this way, the system can help the user to download only necessary mold base plates and standard parts, and those parts downloaded are only the updated portions.

Keywords: CAD, injection molding, mold base, data retrieval

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Authors: Arjun G. Koppad

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The study was conducted in Joida taluk of Uttara Kannada district, Karnataka, India, to assess the land use land cover (LULC) and forest aboveground biomass using L band SAR data. The study area covered has dense, moderately dense, and sparse forests. The sampled area was 0.01 percent of the forest area with 30 sampling plots which were selected randomly. The point center quadrate (PCQ) method was used to select the tree and collected the tree growth parameters viz., tree height, diameter at breast height (DBH), and diameter at the tree base. The tree crown density was measured with a densitometer. Each sample plot biomass was estimated using the standard formula. In this study, the LULC classification was done using Freeman-Durden, Yamaghuchi and Pauli polarimetric decompositions. It was observed that the Freeman-Durden decomposition showed better LULC classification with an accuracy of 88 percent. An attempt was made to estimate the aboveground biomass using SAR backscatter. The ALOS-2 PALSAR-2 L-band data (HH, HV, VV &VH) fully polarimetric quad-pol SAR data was used. SAR backscatter-based regression model was implemented to retrieve forest aboveground biomass of the study area. Cross-polarization (HV) has shown a good correlation with forest above-ground biomass. The Multi Linear Regression analysis was done to estimate aboveground biomass of the natural forest areas of the Joida taluk. The different polarizations (HH &HV, VV &HH, HV & VH, VV&VH) combination of HH and HV polarization shows a good correlation with field and predicted biomass. The RMSE and value for HH & HV and HH & VV were 78 t/ha and 0.861, 81 t/ha and 0.853, respectively. Hence the model can be recommended for estimating AGB for the dense, moderately dense, and sparse forest.

Keywords: forest, biomass, LULC, back scatter, SAR, regression

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Authors: Felipe A. Guth, Shane Ward, Kevin McDonnell

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The assessment of disease levels in crop fields is an important and time-consuming task that generally relies on expert knowledge of trained individuals. Image classification in agriculture problems historically has been based on classical machine learning strategies that make use of hand-engineered features in the top of a classification algorithm. This approach tends to not produce results with high accuracy and generalization to the classes classified by the system when the nature of the elements has a significant variability. The advent of deep convolutional neural networks has revolutionized the field of machine learning, especially in computer vision tasks. These networks have great resourcefulness of learning and have been applied successfully to image classification and object detection tasks in the last years. The objective of this work was to propose a new method based on deep learning convolutional neural networks towards the task of disease level monitoring. Common RGB images of winter wheat were obtained during a growing season. Five categories of disease levels presence were produced, in collaboration with agronomists, for the algorithm classification. Disease level tasks performed by experts provided ground truth data for the disease score of the same winter wheat plots were RGB images were acquired. The system had an overall accuracy of 84% on the discrimination of the disease level classes.

Keywords: crop disease assessment, deep learning, precision agriculture, residual neural networks

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Authors: M. Sanjarani, A. Danehkar, A. Mashincheyan, A. H. Javid, S. M. R. Fatemi

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The oil spill in marine water has direct impact on coastal resources and community. Environmental Sensitivity Index (ESI) map is the first step to assess the potential impact of an oil spill and minimize the damage of coastal resources. In order to create Environmental Sensitivity Maps for the Chabahar bay (Iran), information has been collected in three different layers (Shoreline Classification, Biological and Human- uses resources) by means of field observations and measurements of beach morphology, personal interviews with professionals of different areas and the collection of bibliographic information. In this paper an attempt made to prepare an ESI map for sensitivity to oil spills of Chabahar bay coast. The Chabahar bay is subjected to high threaten to oil spill because of port, dense mangrove forest,only coral spot in Oman Sea and many industrial activities. Mapping the coastal resources, shoreline and coastal structures was carried out using Satellite images and GIS technology. The coastal features classified into three major categories as: Shoreline Classification, Biological and Human uses resources. The important resources classified into mangrove, Exposed tidal flats, sandy beach, etc. The sensitivity of shore was ranked as low to high (1 = low sensitivity,10 = high sensitivity) based on geomorphology of Chabahar bay coast using NOAA standards (sensitivity to oil, ease of clean up, etc). Eight ESI types were found in the area namely; ESI 1A, 1C, 3A, 6B, 7, 8B,9A and 10D. Therefore, in the study area, 50% were defined as High sensitivity, less than 1% as Medium, and 49% as low sensitivity areas. The ESI maps are useful to the oil spill responders, coastal managers and contingency planners. The overall ESI mapping product can provide a valuable management tool not only for oil spill response but for better integrated coastal zone management.

Keywords: ESI, oil spill, GIS, Chabahar Bay, Iran

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Authors: Ruth Estrada Javier - Reyes

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The study assessed the status of HTM program of selected private higher education institutions for internationalization across the eleven regions of the country. The descriptive survey method of research was used in this study. A devised survey questionnaire was utilized to gather information about the status of Philippine Higher Education Institutions’ internationalization of hospitality and tourism management education programs. The respondents were 12 administrators, 17 deans and program heads, 104 faculty members and 860 HTM students. Frequency, percentage, mean, standard deviation, t-test and F-test were used to treat the data. The results of the study are as follows: HEIs’ HTM education had complied with the policies/standards of CHED as per CMO No. 30 S. 2006. The respondents of the HTM education program were qualified for internationalization as assessed both by administrators and faculty. The private HEIs are ready to apply for international certification of their HTM education programs. The curriculum of HTM education programs in private HEIs are enriched by internationalization requirements. The administrators and faculty of HTM education programs are qualified educators but have limited participation in collaborative international research and linkages. The HEIs are qualified to apply for the internationalization of the Hospitality and Tourism Management education program in preparation to the ASEAN 2015.

Keywords: status, Hospitality and Tourism Management Program, internationalization, Private Higher Education Institutions

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Authors: Shilpi Tripathi

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After independence, Bangladesh had to learn to survive on its own without any economic crutches (aid). Foreign direct investment (FDI) became a crucial economic tool for the country to become economically independent. The government started removing restrictions to encourage foreign investment, economic growth, international trade, and the environment. FDI is considered as a way to bridge the saving-investment gap, reduce poverty, balance trade, create jobs for its vast labour force, increase foreign exchange earnings and acquire new modern technology and management skills in the country. At the same time, spillovers of foreign investments in Bangladesh, such as low wages (compared to laborers of developed countries), poor working conditions and unbridled exploitation of the domestic resources, environmental externalities, etc., cannot be ignored. The most important adverse implications of FDI inflows noticed are the environmental problems, which are further impacting the health and society of the country. This paper empirically studies the relationship between FDI, economic growth, international trade (exports and Imports), and the environment since 1996. The first part of the paper focuses on the background and trends of FDI, GDP, trade, and environment (CO₂). The second part focuses on the literature review on the relationship between all the variables. The last part of the paper examines the results of empirical analysis like co-integration and Granger causality. The findings of the paper reveal that a uni-directional relationship exists between FDI, CO₂, and international trade (exports and imports). The direction of the causality reveals that FDI inflow is one of the major contributors to high-volume international trade. At the same time, FDI and international trade both are contributing to carbon emissions in Bangladesh. The paper concludes with the policy recommendations that will ensure environmentally friendly trade, investment, and growth in Bangladesh for the future.

Keywords: foreign direct investment, GDP, international trade, CO₂, Granger causality, environment

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Authors: F. Fatoye, C. E. Mbada, T. Gebrye, A. O. Ogunsola, C. Fatoye, O. Oyewole

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Musculoskeletal disorders (MSDs) such as low back pain (LBP), cervical spondylosis (CSPD), sprain, osteoarthritis (OA), and post immobilization stiffness (PIS) have a major impact on individuals, health systems and society in terms of morbidity, long-term disability, and economics. This study estimated the direct and indirect costs of common MSDs in Osun State, Nigeria. A review of medical charts for adult patients attending Physiotherapy Outpatient Clinic at the Obafemi Awolowo University Teaching Hospitals Complex, Osun State, Nigeria between 2009 and 2018 was carried out. The occupational class of the patients was determined using the International Labour Classification (ILO). The direct and indirect costs were estimated using a cost-of-illness approach. Physiotherapy related health resource use, and costs of the common MSDs, including consultation fee, total fee charge per session, costs of consumables were estimated. Data were summarised using descriptive statistics mean and standard deviation (SD). Overall, 1582 (Male = 47.5%, Female = 52.5%) patients with MSDs population with a mean age of 47.8 ± 25.7 years participated in this study. The mean (SD) direct costs estimate for LBP, CSPD, PIS, sprain, OA, and other conditions were $18.35 ($17.33), $34.76 ($17.33), $32.13 ($28.37), $35.14 ($44.16), $37.19 ($41.68), and $15.74 ($13.96), respectively. The mean (SD) indirect costs estimate of LBP, CSPD, PIS, sprain, OA, and other MSD conditions were $73.42 ($43.54), $140.57 ($69.31), $128.52 ($113.46), sprain $140.57 ($69.31), $148.77 ($166.71), and $62.98 ($55.84), respectively. Musculoskeletal disorders contribute a substantial economic burden to individuals with the condition and society. The unacceptable economic loss of MSDs should be reduced using appropriate strategies. Further research is required to determine the clinical and cost effectiveness of strategies to improve health outcomes of patients with MSDs. The findings of the present study may assist health policy and decision makers to understand the economic burden of MSDs and facilitate efficient allocation of healthcare resources to alleviate the burden associated with these conditions in Nigeria.

Keywords: economic burden, low back pain, musculoskeletal disorders, real-world

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Authors: Mohamad Farhad Bakhtiyariyan

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One of the manner to earning profit and having a high income, is investing in an acceptable market. Every the thinker brain knows, investing in the business world today, maybe, have a manifold profit or lead to failure. So, before entering in the investment market, we must have a comprehensive and sufficient awareness, know markets, acquainted with the main industrial activities, know the rules and regulation and consider the conditions of society. Qatar, as a one of the richest countries in the world, can be a good destination for investment. The inflation rate, taxes, easiness of the importing, company registration, ease of exporting process, profitable and appropriate markets, simple and applicable rules, all of this has made Qatar, one of the best and gainful investment countries. Above all, Qatar 2022 world cup event, has led of investment in this country efficiently and profitable method. In this paper, first, we have introduced the Qatar and its location, also looked at the countries international markets during the world cup and we have described the impact of the world cup on business, and then the laws and regulations of the Qatar in the field of investment, company registration, ownership by foreigners, obtaining residency by investors, export and import process in second part its examined, and in third part, major investment markets, principal industrial activities in Qatar, markets affected by the world cup and the main needs of this country in various fields during the world cup, have been investigated.

Keywords: investment, Qatar, markets, world cup

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Authors: Fernanda M. Bastos, Teógenes A. da Silva

Abstract:

Extrapolation chambers were designed to be used as primary standard dosimeter for measuring absorbed dose in a medium in beta radiation and low energy x-rays. The International Organization for Standardization established series of reference x-radiation for calibrating and determining the energy dependence of dosimeters that are to be reproduced in metrology laboratories. Standardization of the low energy x-ray beams with tube potential lower than 30 kV may be affected by the instrument used for dosimetry. In this work, parameters of a 23392 model PTW extrapolation chamber were determined aiming its use in low energy x-ray beams as a reference instrument.

Keywords: extrapolation chamber, low energy x-rays, x-ray dosimetry, X-ray metrology

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Authors: Fang Bin Guo, Emma Roberts, Haibin Du, Yonggang Wang, Yu Chen, Xiuli Ge

Abstract:

This paper explores the findings so far from a major externally-funded project which operates internationally in China, Germany and the UK. The research team is working in the context of the redevelopment of post-industrial sites in China and how these might be platforms for creative enterprises and thereby, the economy and welfare to flourish. Results from the project are anticipated to inform urban design policies in China and possibly farther afield. The research has utilised ethnographic studies and participatory design methods to investigate alternative strategies for sustainable urban renewal of China’s post-industrial areas. Additionally, it has undertaken comparative studies of successful examples of European and Chinese urban regeneration cases. The international cross-disciplinary team has been seeking different opportunities for developing relevant creative industries whilst retaining cultural and industrial heritage. This paper will explore the research conducted so far by the team and offer initial findings. Findings point out the development challenges of cities respecting the protection of local culture/heritages, history of the industries and transformation of the local economies. The preliminary results and pilot analysis of the current research have demonstrated that local government policyholders, business investors/developers and creative industry practitioners are the three major stakeholders that will impact city revitalisations. These groups are expected to work together with asynchronous vision in order for redevelopments to be successful. Meanwhile, local geography, history, culture, politics, economy and ethnography have been identified as important factors that impact on project design and development during urban transformations. Data is being processed from the team’s research conducted across the focal Western and Chinese cities. This has provided theoretical guidance and practical support to the development of significant experimental projects. Many were re-examined with a more international perspective, and adjustments have been based on the conclusions of the research. The observations and research are already generating design solutions in terms of ascertaining essential site components, layouts, visual design and practical facilities for regenerated sites. Two significant projects undertaken by this project team have been nominated by the central Chinese government as the most successful exemplars. They have been listed as outstanding national industry heritage projects; in particular, one of them was nominated by ArchDaily as Building of the Year 2019, and so this project outcome has made a substantial contribution to research and innovation. In summary, this paper will outline the funded project, discuss the work conducted so far, and pinpoint the initial discoveries. It will detail the future steps and indicate how these will impact on national and local governments in China, designers, local citizens and building users.

Keywords: cultural & industrial heritages, ethnographic research, participatory design, regeneration of post-industrial sites, sustainable

Procedia PDF Downloads 135

Authors: Ana Avila Bohorquez

Abstract:

Elite (Netflix, 2018-) is the second original series produced by Netflix in Spain. Premiered in 2018, it became an international success, both critically and among audiences. Reviewers praised its use of teen drama tropes with a more progressive twist. Netflix announced that the first season had been streamed by over 20 million accounts within its first month of release. This paper aims to determine what characteristics led to Elite’s international success, finding the elements of its narrative and visual design that resonate with global audiences. After reviewing the bibliography about transnational fiction, questionnaires sent to international audience members through social media shed light on what these characteristics are. Additionally, interviews with the creative team were performed in order to compare their point of view with the audiences’ perception. Even though Elite can be considered a Spanish show from its inception, it's setting in the “fantasy” world of the rich and its lack of social realism so common among Spanish productions managed to attract global audiences, to whom it has appealed on a more emotional level.

Keywords: elite, global television, Netflix, teen drama, transnational fiction

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Authors: Mehmet Savsar

Abstract:

This paper presents a practical case application of simulation modeling and analysis in a specific industrial setting. Various maintenance related parameters of the equipment in the system under consideration are determined and a simulation model is developed to study system behavior. System performance is determined based on established parameters and operational policies, which included system operation with and without preventive maintenance implementation. The results show that preventive maintenance practice has significant effects on improving system productivity. The simulation procedures outlined in this paper can be used by operation managers to perform production line analysis under different maintenance policies in various industrial settings.

Keywords: simulation, production line, machine failures, maintenance, industrial bakery

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Authors: Yusuf Jundi Sado

Abstract:

Changes in land use are mostly credited to human actions that result in negative impacts on biodiversity and ecosystem functions. This study aims to analyze the dynamics of land use and land cover changes for sustainable natural resources planning and management. Chilalo-Galama Mountain Range, Ethiopia. This study used Thematic Mapper 05 (TM) for 1986, 2001 and Landsat 8 (OLI) data 2017. Additionally, data from the Central Statistics Agency on human population growth were analyzed. Semi-Automatic classification plugin (SCP) in QGIS 3.2.3 software was used for image classification. Global positioning system, field observations and focus group discussions were used for ground verification. Land Use Land Cover (LU/LC) change analysis was using maximum likelihood supervised classification and changes were calculated for the 1986–2001 and the 2001–2017 and 1986-2017 periods. The results show that agricultural land increased from 27.85% (1986) to 44.43% and 51.32% in 2001 and 2017, respectively with the overall accuracies of 92% (1986), 90.36% (2001), and 88% (2017). On the other hand, forests decreased from 8.51% (1986) to 7.64 (2001) and 4.46% (2017), and grassland decreased from 37.47% (1986) to 15.22%, and 15.01% in 2001 and 2017, respectively. It indicates for the years 1986–2017 the largest area cover gain of agricultural land was obtained from grassland. The matrix also shows that shrubland gained land from agricultural land, afro-alpine, and forest land. Population dynamics is found to be one of the major driving forces for the LU/LU changes in the study area.

Keywords: Landsat, LU/LC change, Semi-Automatic classification plugin, population dynamics, Ethiopia

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Authors: Ravinder Bahl, Jamini Sharma

Abstract:

The paper demonstrates analysis of the cervical cancer based on a probabilistic model. It involves technique for classification and prediction by recognizing typical and diagnostically most important test features relating to cervical cancer. The main contributions of the research include predicting the probability of recurrences in no recurrence (first time detection) cases. The combination of the conventional statistical and machine learning tools is applied for the analysis. Experimental study with real data demonstrates the feasibility and potential of the proposed approach for the said cause.

Keywords: cervical cancer, recurrence, no recurrence, probabilistic, classification, prediction, machine learning

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Authors: Bovornluck Kuosuwan, Kevin Wongleedee

Abstract:

The purposes of this research was to study the level of satisfaction of international tourists in five important areas: satisfaction on visiting tourist destinations, satisfaction on tourist images, satisfaction on value for money, satisfaction on service quality, and satisfaction when compared with their expectation. A probability random sampling of 200 inbound tourists was utilized. A questionnaire was used to collect the data and small in-depth interviews were also used to get their opinions about their positive and negative evaluations of their experience travelling in Thailand. The findings revealed that the majority of respondents had a medium level of satisfaction. When examined in detail, the level of satisfaction can be ranked from highest to lowest according to the mean average as follows: visiting tourist destinations, expectations, service quality, tourist image, and value for money.

Keywords: inbound tourists, satisfaction, Thailand, international tourists

Procedia PDF Downloads 312