Search results for: international classification of functioning

Authors: C. V. Aravinda, H. N. Prakash

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In this paper, we tried to convey fusion and state of art pertaining to SIL character recognition systems. In the first step, the text is preprocessed and normalized to perform the text identification correctly. The second step involves extracting relevant and informative features. The third step implements the classification decision. The three stages which involved are Data acquisition and preprocessing, Feature extraction, and Classification. Here we concentrated on two techniques to obtain features, Feature Extraction & Feature Selection. Edge-hinge distribution is a feature that characterizes the changes in direction of a script stroke in handwritten text. The edge-hinge distribution is extracted by means of a windowpane that is slid over an edge-detected binary handwriting image. Whenever the mid pixel of the window is on, the two edge fragments (i.e. connected sequences of pixels) emerging from this mid pixel are measured. Their directions are measured and stored as pairs. A joint probability distribution is obtained from a large sample of such pairs. Despite continuous effort, handwriting identification remains a challenging issue, due to different approaches use different varieties of features, having different. Therefore, our study will focus on handwriting recognition based on feature selection to simplify features extracting task, optimize classification system complexity, reduce running time and improve the classification accuracy.

Keywords: word segmentation and recognition, character recognition, optical character recognition, hand written character recognition, South Indian languages

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Authors: Dagnew Dessie Mengie

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The purpose of this study was to investigate German tourists' demand for Ethiopian tourism destinations. The author has made every effort to identify the differences in the preferences of German visitors’ demand in Ethiopia comparing with Egypt, Kenya, Tanzania, and South African tourism sectors if they are invited to visit at the same time. However, the demand for international tourism for Ethiopia currently lags behind these African countries. Therefore, to offer demand-driven tourism products, the Ethiopian government and tour and travel operators need to understand the important factors that affect international tourists’ decision to visit Ethiopian tourist destinations. The aim of this study was to analyze German Tourists’ Demand for Ethiopian destinations. The researcher aimed to identify the demand for German tourists’ preference for Ethiopian tourist destinations compared to the above-mentioned African countries. For collecting and analysing data for this study, both quantitative and qualitative methods of research are being used in this study. The most significant data are collected by using the primary data collection method i.e. survey and interviews which are the most and large number of potential responses and feedback from nine German active tourists,12 Ethiopian tourism officials, four African embassies, and four well functioning private tour companies and secondary data collected from books, journals, previous research and electronic websites. Based on the data analysis of the information gathered from interviews and questionnaires, the study disclosed that the majority of German tourists do have not that high demand for Ethiopian Tourist destinations due to the following reasons: (1) Many Germans are fascinated by adventures and safari and simply want to lie on the beach and relax. These interests have leaded them to look for other African countries which have these accesses. (2) Uncomfortable infrastructure and transport problems are attributed to the decreasing number of German tourists in the country. (3) Inadequate marketing operation of the Ethiopian Tourism Authority and its delegates in advertising and clarifying the above irregularities which are raised by the tourists.

Keywords: environmental benefits of tourism, social benefits of tourism, economic benefits of tourism, political factors on tourism

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Authors: Prajwal Raj Gyawali, Aastha Dahal

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The tension between human rights and loans provided by international development banks with hidden conditions in the pretext of development is a complex issue with significant implications for the rights of citizens in borrowing countries. It is important for all parties involved, including international banks, borrowing countries, and affected communities, to consider and respect human rights in the negotiation and implementation of development projects. Yet, it is rare for human rights actors or communities to have a seat at the negotiation table when loans are finalized. In our research, we conducted negotiation simulations in law schools to examine how international loan negotiations would play out if human rights actors and communities had seats at the table. We ran the negotiation simulations in Bangladesh, Nepal and India. We found that the presence of community groups and human rights actors makes a difference in loan outcomes. While the international development loan was accepted as opposed to rejected by negotiators in three countries, the cultural values of the respective countries played a significant part in terms of the final agreement. We present the findings and their implications for the design of human rights courses in law schools as well as larger policy implications for expanding the participation of actors in international development loan negotiations.

Keywords: law, development, debt, human rights

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Authors: Soyon Kim, Edward Kim

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In order to retrieve information from the massive stream of songs in the music industry, music search by title, lyrics, artist, mood, and genre has become more important. Despite the subjectivity and controversy over the definition of music genres across different nations and cultures, automatic genre classification systems that facilitate the process of music categorization have been developed. Manual genre selection by music producers is being provided as statistical data for designing automatic genre classification systems. In this paper, an automatic music genre classification system utilizing non-negative matrix factorization (NMF) is proposed. Short-term characteristics of the music signal can be captured based on the timbre features such as mel-frequency cepstral coefficient (MFCC), decorrelated filter bank (DFB), octave-based spectral contrast (OSC), and octave band sum (OBS). Long-term time-varying characteristics of the music signal can be summarized with (1) the statistical features such as mean, variance, minimum, and maximum of the timbre features and (2) the modulation spectrum features such as spectral flatness measure, spectral crest measure, spectral peak, spectral valley, and spectral contrast of the timbre features. Not only these conventional basic long-term feature vectors, but also NMF based feature vectors are proposed to be used together for genre classification. In the training stage, NMF basis vectors were extracted for each genre class. The NMF features were calculated in the log spectral magnitude domain (NMF-LSM) as well as in the basic feature vector domain (NMF-BFV). For NMF-LSM, an entire full band spectrum was used. However, for NMF-BFV, only low band spectrum was used since high frequency modulation spectrum of the basic feature vectors did not contain important information for genre classification. In the test stage, using the set of pre-trained NMF basis vectors, the genre classification system extracted the NMF weighting values of each genre as the NMF feature vectors. A support vector machine (SVM) was used as a classifier. The GTZAN multi-genre music database was used for training and testing. It is composed of 10 genres and 100 songs for each genre. To increase the reliability of the experiments, 10-fold cross validation was used. For a given input song, an extracted NMF-LSM feature vector was composed of 10 weighting values that corresponded to the classification probabilities for 10 genres. An NMF-BFV feature vector also had a dimensionality of 10. Combined with the basic long-term features such as statistical features and modulation spectrum features, the NMF features provided the increased accuracy with a slight increase in feature dimensionality. The conventional basic features by themselves yielded 84.0% accuracy, but the basic features with NMF-LSM and NMF-BFV provided 85.1% and 84.2% accuracy, respectively. The basic features required dimensionality of 460, but NMF-LSM and NMF-BFV required dimensionalities of 10 and 10, respectively. Combining the basic features, NMF-LSM and NMF-BFV together with the SVM with a radial basis function (RBF) kernel produced the significantly higher classification accuracy of 88.3% with a feature dimensionality of 480.

Keywords: mel-frequency cepstral coefficient (MFCC), music genre classification, non-negative matrix factorization (NMF), support vector machine (SVM)

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Authors: P. Bharathiraja

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Computer Aided decision making system is used to enhance diagnosis and prognosis of diseases and also to assist clinicians and junior doctors in clinical decision making. Medical Data used for decision making should be definite and consistent. Data Mining and soft computing techniques are used for cleaning the data and for incorporating human reasoning in decision making systems. Fuzzy rule based inference technique can be used for classification in order to incorporate human reasoning in the decision making process. In this work, missing values are imputed using the mean or mode of the attribute. The data are normalized using min-ma normalization to improve the design and efficiency of the fuzzy inference system. The fuzzy inference system is used to handle the uncertainties that exist in the medical data. Equal-width-partitioning is used to partition the attribute values into appropriate fuzzy intervals. Fuzzy rules are generated using Class Based Associative rule mining algorithm. The system is trained and tested using heart disease data set from the University of California at Irvine (UCI) Machine Learning Repository. The data was split using a hold out approach into training and testing data. From the experimental results it can be inferred that classification using fuzzy inference system performs better than trivial IF-THEN rule based classification approaches. Furthermore it is observed that the use of fuzzy logic and fuzzy inference mechanism handles uncertainty and also resembles human decision making. The system can be used in the absence of a clinical expert to assist junior doctors and clinicians in clinical decision making.

Keywords: decision making, data mining, normalization, fuzzy rule, classification

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Authors: Haonan Hu, Shuge Lei, Dasheng Sun, Huabin Zhang, Kehong Yuan, Jian Dai, Jijun Tang

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This paper focuses on the classification task of breast ultrasound images and conducts research on the reliability measurement of classification results. A dual-channel evaluation framework was developed based on the proposed inference reliability and predictive reliability scores. For the inference reliability evaluation, human-aligned and doctor-agreed inference rationals based on the improved feature attribution algorithm SP-RISA are gracefully applied. Uncertainty quantification is used to evaluate the predictive reliability via the test time enhancement. The effectiveness of this reliability evaluation framework has been verified on the breast ultrasound clinical dataset YBUS, and its robustness is verified on the public dataset BUSI. The expected calibration errors on both datasets are significantly lower than traditional evaluation methods, which proves the effectiveness of the proposed reliability measurement.

Keywords: medical imaging, ultrasound imaging, XAI, uncertainty measurement, trustworthy AI

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Authors: C. M. Priesnitz, G. Zanandrea, J. P. Fabris, S. L. Russo, M. E. Camargo

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This study aimed to the prospection the physiotherapy area technological production registered with the National Intellectual Property Institute (INPI) in Brazil, for understand the evolution of the technological production in the country over time and visualize the distribution this production request in Brazil. There was an evolution in the technology landscape, where the average annual deposits had an increase of 102%, from 3.14 before the year 2004 to 6,33 after this date. It was found differences in the distribution of the number the deposits requested to each Brazilian region, being that of the 132 request, 68,9% were from the southeast region. The international patent classification evaluated the request deposits, and the more found numbers were A61H and A63B. So even with an improved panorama of technology production, this should still have incentives since it is an important tool for the development of the country.

Keywords: distribution, evolution, patent, physiotherapy, technological prospecting

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Authors: Jaiden Xuan Schraut, Leon Liu, Yiqiao Yin

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Computer vision in medical diagnosis has achieved a high level of success in diagnosing diseases with high accuracy. However, conventional classifiers that produce an image to-label result provides insufficient information for medical professionals to judge and raise concerns over the trust and reliability of a model with results that cannot be explained. In order to gain local insight into cancerous regions, separate tasks such as imaging segmentation need to be implemented to aid the doctors in treating patients, which doubles the training time and costs which renders the diagnosis system inefficient and difficult to be accepted by the public. To tackle this issue and drive AI-first medical solutions further, this paper proposes a multi-output network that follows a U-Net architecture for image segmentation output and features an additional convolutional neural networks (CNN) module for auxiliary classification output. Class activation maps are a method of providing insight into a convolutional neural network’s feature maps that leads to its classification but in the case of lung diseases, the region of interest is enhanced by U-net-assisted Class Activation Map (CAM) visualization. Therefore, our proposed model combines image segmentation models and classifiers to crop out only the lung region of a chest X-ray’s class activation map to provide a visualization that improves the explainability and is able to generate classification results simultaneously which builds trust for AI-led diagnosis systems. The proposed U-Net model achieves 97.61% accuracy and a dice coefficient of 0.97 on testing data from the COVID-QU-Ex Dataset which includes both diseased and healthy lungs.

Keywords: multi-output network model, U-net, class activation map, image classification, medical imaging analysis

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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: 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

Abstract:

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: M. Boukhrouk, R. Ed-Dali

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Outbound tourism in Morocco, as in the majority of developing countries, reveals some of the aspects of inequality between the north and the south. Considered by some researchers as one of the facets of the development crisis, access to tourism and especially international tourism is a chance for a small minority with financial means, while the vast portions of the population dream rather of immigrating to a developed country for the sake of improving their standard of living. The right to travel is also limited by visa requirements, procedures in host countries, security and technical measures and creates discrimination in the practice of tourism. These conditions do not seem to be favorable to the democratization of the practice of international tourism for the populations of the southern countries. This paper is a contribution to the reading of the trends of outbound tourism in developing countries through the example of Morocco. It highlights the different aspects of Moroccan outbound tourism, destinations and the behavior of tourists through an analysis of the offer of a sample of 50 travel agencies. In the same vein, it offers a reading grid of the possibilities offered for the development of outbound tourism and the various existing obstacles to the democratization of international outbound tourism in the southern countries. This reading reveals the transformation in the behavior of Moroccan international tourists as well as the profound changes in Moroccan society, through a model of statistical analysis.

Keywords: demand, Hajj, Morocco, outbound tourism, tendency, Umrah

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Authors: Aravind Bagade Shankaranarayana, Parampalli Geetha, Pallavi Gupta

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Objective: This study intends to evaluate sexual dysfunction qualitatively and quantitatively in males suffering from primary obesity through a single centered, observational study. Design and Methods: Sexual function of 33 obese males from the outpatient department of the hospital was assessed using IIEF questionnaire and semen analysis and the results were assessed for statistical significance. Results: A varying degree of sexual dysfunction was observed in four out of five areas of sexual functioning viz. erectile function (p<0.02), orgasmic function (p<0.02), sexual desire (p<0.08) and overall satisfaction (p<0.000) in obese individuals. Statistically significant dysfunction was not observed in intercourse satisfaction. Semen analysis was normal in 19 individuals (63.3%) and abnormal in 11 individuals (36.7%), with statistically insignificant p value 0.144, suggesting mild to moderate variation in semen parameters. Conclusions: Varying degree of sexual dysfunction is present in obese males, suggesting that obesity has a possible role in reducing the quality of sexual functioning in males as indicated in the classical Ayurvedic literature.

Keywords: erectile dysfunction, krucchra vyavaya, obesity, sthoulya

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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: Dagnew Dessie Mengie

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The purpose of this study was to investigate German tourists' demand for Ethiopian tourism destinations. The author has made every effort to identify the differences in the preferences of German visitors’ demand in Ethiopia comparing with Egypt, Kenya, Tanzania, and South African tourism sectors if they are invited to visit at the same time. However, the demand of international tourism for Ethiopia currently lags behind these African countries. Therefore, to offer demand-driven tourism products, the Ethiopian government, Tour & Travel operators need to understand the important factors that affect international tourists’ decision to visit Ethiopian tourist destinations. The aim of this study was intended to analyze German Tourists’ Demand towards Ethiopian destination. The researcher aimed to identify the demand for German tourists’ preference to Ethiopian tourist destinations comparing to the above-mentioned African countries. For collecting and analysing data for this study, both quantitative and qualitative methods of research are being used in this study. The most significant data are collected by using the primary data collection method i.e. survey and interviews which are the most and large number of potential responses and feedback from nine German active tourists,12 Ethiopian tourism officials, four African embassies, and four well functioning private tour companies and secondary data collected from books, journals, previous research and electronic websites. based on the data analysis of the information gathered from interviews and questionnaires, the study disclosed that majority of German tourists have not that much high demand on Ethiopian Tourist destinations due to the following reasons; Many Germans are fascinated by adventures, safari and simply want to lie on the beach and relax. These interests have leaded them to look for other African countries which have these accesses. Uncomfortable infrastructure and transport problems attributed for the decreasing the number of German tourists in the country. Inadequate marketing operation of Ethiopian Tourism Authority and its delegates in advertising and clarifying the above irregularities which are raised by the tourists.

Keywords: environmental benefits of tourism, social benefits of tourism, economical benefits of tourism, political factors in tourism

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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: Merrylord Harb-Azar

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Traditionally, PTSD treatment has involved trauma-focused cognitive behaviour therapy (TF CBT) to consolidate traumatic memories. A piloted integrated treatment of TF CBT and eye movement desensitisation reprocessing therapy (EMDR) of eight phases will fasten the rate memory is being consolidated and enhance cognitive functioning in patients with PTSD. Patients spend a considerable amount of time in treatment managing their traumas experienced firsthand, or from aversive details ranging from war, assaults, accidents, abuse, hostage related, riots, or natural disasters. The time spent in treatment or as inpatient affects overall quality of life, relationships, cognitive functioning, and overall sense of identity. EMDR is being offered twice a week in conjunction with the standard prolonged exposure as an inpatient in a private hospital. Prolonged exposure for up to 5 hours per day elicits the affect response required for EMDR sessions in the afternoon to unlock unprocessed memories and facilitate consolidation in the amygdala and hippocampus. Results are indicating faster consolidation of memories, reduction in symptoms in a shorter period of time, reduction in admission time, which is enhancing the quality of life and relationships, and improved cognition. The impact of events scale (IES) results demonstrate a significant reduction in symptoms, trauma symptoms inventory (TSI), and posttraumatic stressor disorder check list (PCL) that demonstrates large effect sizes to date. An integrated treatment approach for PTSD achieves a faster resolution of memories, improves cognition, and reduces the amount of time spent in therapy.

Keywords: EMDR enhances cognitive functioning, faster consolidation of trauma memory, integrated treatment of TF CBT and EMDR, reduction in inpatient admission time

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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: Julius Steinkopf, Eric Rost, Aike Hessel, Sonia Lippke

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Objective: This study examined possible determinants of return to work (RTW) in individuals who participated in a medical rehabilitation program longitudinally over a time period of six months. Design/methodology/approach: N=1,044 rehabilitants were included in the baseline measurement in terms of completing a questionnaire during their medical rehabilitation. About 30% (n=350) have remained in the study in terms of participating in computer-assisted telephone interviewing (CATI) six months later. Frequency analyses and Regression analyses were run. Findings: About 70% of the rehabilitants returned to work six months after rehabilitation. Regression analyses revealed that the RTW rates were significantly predicted by gender (OR=0.12, men were more likely to return), perceived social support (OR=3.01) and current physical functioning (OR=1.25). Furthermore RTW motives, like expected monetary rewards (OR=25.2) and feelings of being needed (OR=0.18) same as motives for not returning to work (nRTW), like the wish to stop working in order to spend time with the spouse (OR=0.13) or a lack of enjoyment of work (OR=3.81), significantly predicted return to work rates. Life satisfaction, self-efficacy beliefs, mental health, current income, educational background or age did not significantly increase explained variance (all ps > .05). Practical implications: Taking theses predictors into account provides options to increase the effectiveness of interventions aiming at increasing RTW: Medical rehabilitations should not only aim at improving the physical functioning but also to enhance beneficial motives and social support as well as support women specifically in order to improve the effectiveness of medical rehabilitation and public health interventions. Originality/value: Illness-caused work absences are related to high financial costs and individual burden. Despite of the public health and societal implications, this is one of the very few studies investigating systematically fitness and health for the return to work.

Keywords: gender, fitness, health, physical functioning

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Authors: Ana Avila Bohorquez

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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: 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: Bovornluck Kuosuwan, Kevin Wongleedee

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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 318

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: G. Stamatopoulou, M. Symeonaki, C. Michalopoulou

Abstract:

In this work, we study the intergenerational social mobility in Greece, in order to provide up-to-date evidence on the changes in the mobility patterns throughout the years. An analysis for both men and women aged between 25-64 years old is carried out. Three main research objectives are addressed. First, we aim to examine the relationship between the socio-economic status of parents and their children. Secondly, we investigate the evolution of the mobility patterns between different birth cohorts. Finally, the role of education is explored in shaping the mobility patterns. For the analysis, we draw data on both parental and individuals' social outcomes from different national databases. The social class of origins and destination is measured according to the European Socio-Economic Classification (ESeC), while the respondents' educational attainment is coded into categories based on the International Standard Classification of Education (ISCED). Applying the Markov transition probability theory, and a range of measures and models, this work focuses on the magnitude and the direction of the movements that take place in the Greek labour market, as well as the level of social fluidity. Three-way mobility tables are presented, where the transition probabilities between the classes of destination and origins are calculated for different cohorts. Additionally, a range of absolute and relative mobility rates, as well as distance measures, are presented. The study covers a large time span beginning in 1940 until 1995, shedding light on the effects of the national institutional processes on the social movements of individuals. Given the evidence on the mobility patterns of the most recent birth cohorts, we also investigate the possible effects of the 2008 economic crisis.

Keywords: cohort analysis, education, Greece, intergenerational mobility, social class

Procedia PDF Downloads 117