Results for 'Dataset,'

186 found
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  1.  54
    Spotify Status Dataset.Mohammad Ayman Mattar & Samy S. Abu-Naser - 2023 - International Journal of Engineering and Information Systems (IJEAIS) 7 (10):14-21.
    Abstract: The Spotify Status Dataset is a valuable resource that provides real-time insights into the operational status and performance of Spotify, a popular music streaming platform. This dataset contains a wide array of information related to server uptime, user activity, service disruptions, and more, serving as a critical tool for both Spotify's internal monitoring and the broader data analysis community. As digital services like Spotify continue to play a central role in music consumption, understanding the platform's status becomes crucial for (...)
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  2. Dataset of Vietnamese students’ intention in respect of study abroad before and during COVID-19 pandemic.Thuy Ta, Anh-Duc Hoang, Hiep Hung Pham, Yen Chi Nguyen, Quang Anh Phan & Viet Hung Dinh - unknown
    The Covid-19 Pandemic had completely disrupted the worldwide educational system. Many schools chose the online delivery mode for students in case learning losses incurred during social distance decree. However, as to these students who are currently in the study abroad planning stages, reached an intention crossroads, whether standing for certain unchanging decisions in study abroad destinations or changing swiftly due to the unexpected policies in quarantine. This case opened to interpretation, which was based on our e-survey since 3 May to (...)
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  3.  61
    SeCoDa: Sense Complexity Dataset.David Strohmaier, Sian Gooding, Shiva Taslimipoor & Ekaterina Kochmar - 2020 - Proceedings of the 12Th Language Resources and Evaluation Conference.
    The Sense Complexity Dataset (SeCoDa) provides a corpus that is annotated jointly for complexity and word senses. It thus provides a valuable resource for both word sense disambiguation and the task of complex word identification. The intention is that this dataset will be used to identify complexity at the level of word senses rather than word tokens. For word sense annotation SeCoDa uses a hierarchical scheme that is based on information available in the Cambridge Advanced Learner’s Dictionary. This way we (...)
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  4. Dataset on Islamic ethical work behavior among Bruneian Malay Muslim teachers with measures concerning religiosity and theory of planned behavior.Nur Amali Aminnuddin - 2020 - Data in Brief 29:105157.
    The data presents an examination of Islamic ethical work behavior of Malay Muslim teachers in Brunei through religiosity and theory of planned behavior. The total number of participants was 370 Bruneian Malay Muslim teachers. The participants were sampled from two different types of school systems being non-religious schools and religious schools, with five schools each. By documenting information of the data, this data article presented the demographic characteristics of participants, and reliability and correlation of measures involved. Analyses of the data (...)
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  5. ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19.Isaric Clinical Characterization Group - 2022 - Scientific Data 9 (1):454.
    The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute (...)
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  6. Comparative Analysis of the Performance of Popular Sorting Algorithms on Datasets of Different Sizes and Characteristics.Ahmed S. Sabah, Samy S. Abu-Naser, Yasmeen Emad Helles, Ruba Fikri Abdallatif, Faten Y. A. Abu Samra, Aya Helmi Abu Taha, Nawal Maher Massa & Ahmed A. Hamouda - 2023 - International Journal of Academic Engineering Research (IJAER) 7 (6):76-84.
    Abstract: The efficiency and performance of sorting algorithms play a crucial role in various applications and industries. In this research paper, we present a comprehensive comparative analysis of popular sorting algorithms on datasets of different sizes and characteristics. The aim is to evaluate the algorithms' performance and identify their strengths and weaknesses under varying scenarios. We consider six commonly used sorting algorithms: QuickSort, TimSort, MergeSort, HeapSort, RadixSort, and ShellSort. These algorithms represent a range of approaches and techniques, including divide-and-conquer, hybrid (...)
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  7. Dataset of Vietnamese teachers’ perspectives and perceived support during the COVID-19 pandemic.Cam-Tu Vu, Anh-Duc Hoang, Van-Quan Than, Manh-Tuan Nguyen, Viet-Hung Dinh, Quynh-Anh Thi Le, Thu-Trang Thi Le, Hiep-Hung Pham & Yen-Chi Nguyen - manuscript
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  8.  21
    Leveraging Artificial Neural Networks for Cancer Prediction: A Synthetic Dataset Approach.Mohammed S. Abu Nasser & Samy S. Abu-Naser - 2023 - International Journal of Academic Engineering Research (IJAER) 7 (11):43-51.
    Abstract: This research explores the application of artificial neural networks (ANNs) in predicting cancer using a synthetically generated dataset designed for research purposes. The dataset comprises 10,000 pseudo-patient records, each characterized by gender, age, smoking history, fatigue, and allergy status, along with a binary indicator for the presence or absence of cancer. The 'Gender,' 'Smoking,' 'Fatigue,' and 'Allergy' attributes are binary, while 'Age' spans a range from 18 to 100 years. The study employs a three-layer ANN architecture to develop a (...)
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  9. Bigger Isn’t Better: The Ethical and Scientific Vices of Extra-Large Datasets in Language Models.Trystan S. Goetze & Darren Abramson - 2021 - WebSci '21: Proceedings of the 13th Annual ACM Web Science Conference (Companion Volume).
    The use of language models in Web applications and other areas of computing and business have grown significantly over the last five years. One reason for this growth is the improvement in performance of language models on a number of benchmarks — but a side effect of these advances has been the adoption of a “bigger is always better” paradigm when it comes to the size of training, testing, and challenge datasets. Drawing on previous criticisms of this paradigm as applied (...)
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  10. Indiscretions of a Contemporary Artist: Reflections on Trevor Paglen's (ab)use of the JAFFE dataset.Michael Lyons - manuscript
    Reflections on Trevor Paglen's (ab)use of the JAFFE dataset.
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  11.  68
    Predictive Modeling of Breast Cancer Diagnosis Using Neural Networks:A Kaggle Dataset Analysis.Anas Bachir Abu Sultan & Samy S. Abu-Naser - 2023 - International Journal of Academic Engineering Research (IJAER) 7 (9):1-9.
    Breast cancer remains a significant health concern worldwide, necessitating the development of effective diagnostic tools. In this study, we employ a neural network-based approach to analyze the Wisconsin Breast Cancer dataset, sourced from Kaggle, comprising 570 samples and 30 features. Our proposed model features six layers (1 input, 1 hidden, 1 output), and through rigorous training and validation, we achieve a remarkable accuracy rate of 99.57% and an average error of 0.000170 as shown in the image below. Furthermore, our investigation (...)
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  12. Gender, age, research experience, leading role and academic productivity of Vietnamese researchers in the social sciences and humanities: exploring a 2008-2017 Scopus dataset.Quan-Hoang Vuong - 2017 - European Science Editing 43 (3):51-55.
    Background: Academic productivity has been studied by scholars all round the world for many years. However, in Vietnam, this topic has scarcely been addressed. This research therefore aims at better understanding the correlations between gender, age, research experience, the leading role of corresponding authors, and the total number of their publications in the specific realm of social sciences and humanities. Methods: The study employed a Scopus dataset with publication profiles of 410 Vietnamese researchers between 2008 and 2017. Results: Men did (...)
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  13. Promoting skills-based education in the 21st century: A dataset of Vietnamese secondary students.Do Duc Lan, Bui Thi Dien, Hoang Phuong Hanh, Ly Quoc Bien, Bui Dieu Quynh, Nguyen Hong Lien & Le Anh Vinh - 2020 - VIETNAM JOURNAL OF EDUCATIONAL SCIENCES 1 (June/2020):38-45.
    As the world has become more digitally interconnected than ever before in the 21stcentury, the next generation is required to possess various sets of new skills to succeed in their works and lives. The purpose of the article is to present a dataset of socio-demographic, in-school, out-of-school factors as well as the eight domains of 21st-century skills of Vietnamese secondary school students. A total of 1183 observations from 30 secondary schools in both rural and urban areas of Vietnam are introduced (...)
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  14. “Excavating AI” Re-excavated: Debunking a Fallacious Account of the JAFFE Dataset.Michael J. Lyons - 2021 - arXiv 2107:1-20.
    Twenty-five years ago, my colleagues Miyuki Kamachi and Jiro Gyoba and I designed and photographed JAFFE, a set of facial expression images intended for use in a study of face perception. In 2019, without seeking permission or informing us, Kate Crawford and Trevor Paglen exhibited JAFFE in two widely publicized art shows. In addition, they published a nonfactual account of the images in the essay “Excavating AI: The Politics of Images in Machine Learning Training Sets.” The present article recounts the (...)
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  15. _Attention what is it like [Dataset].Vitor Manuel Dinis Pereira - manuscript
    R Core Team. (2016). R: A language and environment for statistical computing. R Foundation for Statistical Computing. Supplement to Occipital and left temporal instantaneous amplitude and frequency oscillations correlated with access and phenomenal consciousness. Occipital and left temporal instantaneous amplitude and frequency oscillations correlated with access and phenomenal consciousness move from the features of the ERP characterized in Occipital and Left Temporal EEG Correlates of Phenomenal Consciousness (Pereira, 2015) towards the instantaneous amplitude and frequency of event-related changes correlated with a (...)
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  16. Potato Classification Using Deep Learning.Abeer A. Elsharif, Ibtesam M. Dheir, Alaa Soliman Abu Mettleq & Samy S. Abu-Naser - 2020 - International Journal of Academic Pedagogical Research (IJAPR) 3 (12):1-8.
    Abstract: Potatoes are edible tubers, available worldwide and all year long. They are relatively cheap to grow, rich in nutrients, and they can make a delicious treat. The humble potato has fallen in popularity in recent years, due to the interest in low-carb foods. However, the fiber, vitamins, minerals, and phytochemicals it provides can help ward off disease and benefit human health. They are an important staple food in many countries around the world. There are an estimated 200 varieties of (...)
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  17.  72
    Relationship between climate change belief and water conservation behaviors: Is there a role for political identity?Quan-Hoang Vuong, Dan Li, Viet-Phuong La, Minh-Phuong Thi Duong & Minh-Hoang Nguyen - manuscript
    In the United States, public opinions about climate change have become polarized, with a stark difference in the belief in climate change. Climate change denialism is pervasive among Republicans, especially conservatives, contrasting the high recognition of human-induced climate change issues among Democrats. As the water crisis is closely linked to climate change, the current study aims to examine how the belief in climate change’s impacts on future water supply uncertainty affects water conservation behaviors and whether the effect is conditional on (...)
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  18. Glass Classification Using Artificial Neural Network.Mohmmad Jamal El-Khatib, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2019 - International Journal of Academic Pedagogical Research (IJAPR) 3 (23):25-31.
    As a type of evidence glass can be very useful contact trace material in a wide range of offences including burglaries and robberies, hit-and-run accidents, murders, assaults, ram-raids, criminal damage and thefts of and from motor vehicles. All of that offer the potential for glass fragments to be transferred from anything made of glass which breaks, to whoever or whatever was responsible. Variation in manufacture of glass allows considerable discrimination even with tiny fragments. In this study, we worked glass classification (...)
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  19. Energy Efficiency Prediction using Artificial Neural Network.Ahmed J. Khalil, Alaa M. Barhoom, Bassem S. Abu-Nasser, Musleh M. Musleh & Samy S. Abu-Naser - 2019 - International Journal of Academic Pedagogical Research (IJAPR) 3 (9):1-7.
    Buildings energy consumption is growing gradually and put away around 40% of total energy use. Predicting heating and cooling loads of a building in the initial phase of the design to find out optimal solutions amongst different designs is very important, as ell as in the operating phase after the building has been finished for efficient energy. In this study, an artificial neural network model was designed and developed for predicting heating and cooling loads of a building based on a (...)
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  20. How social classes and health considerations in food consumption affect food price concerns.Ruining Jin, Tam-Tri Le, Resti Tito Villarino, Adrino Mazenda, Minh-Hoang Nguyen & Quan-Hoang Vuong - manuscript
    Food prices are a daily concern in many households’ decision-making, especially when people want to have healthier diets. Employing Bayesian Mindsponge Framework (BMF) analytics on a dataset of 710 Indonesian citizens, we found that people from wealthier households are less likely to have concerns about food prices. However, the degree of health considerations in food consumption was found to moderate against the above association. In other words, people of higher income-based social classes may worry more about food prices if they (...)
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  21.  13
    Rethinking the effects of performance expectancy and effort expectancy on new technology adoption: Evidence from Moroccan nursing students.Ni Putu Wulan Purnama Sari, Minh-Phuong Thi Duong, Dan Li, Minh-Hoang Nguyen & Quan-Hoang Vuong - manuscript
    Clinical practice is a part of the integral learning method in nursing education. The use of information and communication technologies (ICT) in clinical learning is highly encouraged among nursing students to support evidence-based nursing and student-centered learning. Through the information-processing lens of the mindsponge theory, this study views performance expectancy (or perceived usefulness) and effort expectancy (or perceived ease of use) as results of subjective benefit and cost judgments determining the students’ ICT using intention for supporting clinical learning, respectively. Therefore, (...)
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  22. Towards a Contextual Approach to Data Quality.Stefano Canali - 2020 - Data 4 (5):90.
    In this commentary, I propose a framework for thinking about data quality in the context of scientific research. I start by analyzing conceptualizations of quality as a property of information, evidence and data and reviewing research in the philosophy of information, the philosophy of science and the philosophy of biomedicine. I identify a push for purpose dependency as one of the main results of this review. On this basis, I present a contextual approach to data quality in scientific research, whereby (...)
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  23. Fraudulent Financial Transactions Detection Using Machine Learning.Mosa M. M. Megdad, Samy S. Abu-Naser & Bassem S. Abu-Nasser - 2022 - International Journal of Academic Information Systems Research (IJAISR) 6 (3):30-39.
    It is crucial to actively detect the risks of transactions in a financial company to improve customer experience and minimize financial loss. In this study, we compare different machine learning algorithms to effectively and efficiently predict the legitimacy of financial transactions. The algorithms used in this study were: MLP Repressor, Random Forest Classifier, Complement NB, MLP Classifier, Gaussian NB, Bernoulli NB, LGBM Classifier, Ada Boost Classifier, K Neighbors Classifier, Logistic Regression, Bagging Classifier, Decision Tree Classifier and Deep Learning. The dataset (...)
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  24. How Digital Natives Learn and Thrive in the Digital Age: Evidence from an Emerging Economy.Trung Tran, Manh-Toan Ho, Thanh-Hang Pham, Minh-Hoang Nguyen, Khanh-Linh P. Nguyen, Thu-Trang Vuong, Thanh-Huyen T. Nguyen, Thanh-Dung Nguyen, Thi-Linh Nguyen, Quy Khuc, Viet-Phuong La & Quan-Hoang Vuong - 2020 - Sustainability 12 (9):3819.
    As a generation of ‘digital natives,’ secondary students who were born from 2002 to 2010 have various approaches to acquiring digital knowledge. Digital literacy and resilience are crucial for them to navigate the digital world as much as the real world; however, these remain under-researched subjects, especially in developing countries. In Vietnam, the education system has put considerable effort into teaching students these skills to promote quality education as part of the United Nations-defined Sustainable Development Goal 4 (SDG4). This issue (...)
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  25.  85
    ‘The agenda is to have fun’: Exploring experiences of guided running in visually impaired and guide runners.Dona Hall, Jacquelyn Allen-Collinson & Patricia C. Jackman - 2023 - Qualitative Research in Sport, Exercise and Health 15 (1):89–103.
    The partnership between a visually impaired runner (VIR) and sighted guide runner (SGR) constitutes a unique sporting dyad. The quality of these partnerships may profoundly impact the sport and physical activity (PA) experiences of visually impaired (VI) people, yet little is known about the experiences of VIRs and SGRs. This study aimed to explore qualitatively the running experiences of VIRs and SGRs. Five VIRs and five SGRs took part in in-depth, semi-structured interviews (M length = 62 minutes) exploring their running (...)
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  26. Classification of Real and Fake Human Faces Using Deep Learning.Fatima Maher Salman & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (3):1-14.
    Artificial intelligence (AI), deep learning, machine learning and neural networks represent extremely exciting and powerful machine learning-based techniques used to solve many real-world problems. Artificial intelligence is the branch of computer sciences that emphasizes the development of intelligent machines, thinking and working like humans. For example, recognition, problem-solving, learning, visual perception, decision-making and planning. Deep learning is a subset of machine learning in artificial intelligence that has networks capable of learning unsupervised from data that is unstructured or unlabeled. Deep learning (...)
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  27.  38
    Heart attack analysis & Prediction: A Neural Network Approach with Feature Analysis.Majd N. Allouh & Samy S. Abu-Naser - 2023 - International Journal of Academic Information Systems Research (IJAISR) 7 (9):47-54.
    heart attack analysis & prediction dataset is a major cause of death worldwide. Early detection and intervention are essential for improving the chances of a positive outcome. This study presents a novel approach to predicting the likelihood of a person having heart failure using a neural network model. The dataset comprises 304 samples with 11 features, such as age, sex, chest pain type, Trtbps, cholesterol, fasting blood sugar, resting electrocardiogram results, maximum heart rate achieved, exercise-induced angina, oldpeak, ST_Slope, and HeartDisease. (...)
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  28.  58
    The Attraction of the Cosmos: How information inducing happiness and impression affects attitudes toward space tourism.Tam-Tri Le, Ruining Jin, Minh-Hoang Nguyen & Quan-Hoang Vuong - manuscript
    Space tourism is an emerging field where few people have direct experience. However, considering the potential in the near future, it is beneficial to better understand how related information influences people’s attitudes about this new form of tourism. Employing information-processing-based Bayesian Mindsponge Framework (BMF) analytics on a dataset of 361 respondents consuming content related to space tourism on Chinese social media, we found that induced happiness and impression are positively associated with willingness to try space tourism. Information authenticity positively moderates (...)
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  29. Cantaloupe Classifications using Deep Learning.Basel El-Habil & Samy S. Abu-Naser - 2021 - International Journal of Academic Engineering Research (IJAER) 5 (12):7-17.
    Abstract cantaloupe and honeydew melons are part of the muskmelon family, which originated in the Middle East. When picking either cantaloupe or honeydew melons to eat, you should choose a firm fruit that is heavy for its size, with no obvious signs of bruising. They can be stored at room temperature until you cut them, after which they should be kept in the refrigerator in an airtight container for up to five days. You should always wash and scrub the rind (...)
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  30. Classification of Anomalies in Gastrointestinal Tract Using Deep Learning.Ibtesam M. Dheir & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (3):15-28.
    Automatic detection of diseases and anatomical landmarks in medical images by the use of computers is important and considered a challenging process that could help medical diagnosis and reduce the cost and time of investigational procedures and refine health care systems all over the world. Recently, gastrointestinal (GI) tract disease diagnosis through endoscopic image classification is an active research area in the biomedical field. Several GI tract disease classification methods based on image processing and machine learning techniques have been proposed (...)
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  31. Interdisciplinarity and insularity in the diffusion of knowledge: an analysis of disciplinary boundaries between philosophy of science and the sciences.John McLevey, Alexander V. Graham, Reid McIlroy-Young, Pierson Browne & Kathryn Plaisance - 2018 - Scientometrics 1 (117):331-349.
    Two fundamentally different perspectives on knowledge diffusion dominate debates about academic disciplines. On the one hand, critics of disciplinary research and education have argued that disciplines are isolated silos, within which specialists pursue inward-looking and increasingly narrow research agendas. On the other hand, critics of the silo argument have demonstrated that researchers constantly import and export ideas across disciplinary boundaries. These perspectives have different implications for how knowledge diffuses, how intellectuals gain and lose status within their disciplines, and how intellectual (...)
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  32. Gender Prediction from Retinal Fundus Using Deep Learning.Ashraf M. Taha, Qasem M. M. Zarandah, Bassem S. Abu-Nasser, Zakaria K. D. AlKayyali & Samy S. Abu-Naser - 2022 - International Journal of Academic Information Systems Research (IJAISR) 6 (5):57-63.
    Deep learning may transform health care, but model development has largely been dependent on availability of advanced technical expertise. The aim of this study is to develop a deep learning model to predict the gender from retinal fundus images. The proposed model was based on the Xception pre-trained model. The proposed model was trained on 20,000 retinal fundus images from Kaggle depository. The dataset was preprocessed them split into three datasets (training, validation, Testing). After training and cross-validating the proposed model, (...)
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  33. Exploring RoBERTa's theory of mind through textual entailment.Michael Cohen - manuscript
    Within psychology, philosophy, and cognitive science, theory of mind refers to the cognitive ability to reason about the mental states of other people, thus recognizing them as having beliefs, knowledge, intentions and emotions of their own. In this project, we construct a natural language inference (NLD) dataset that tests the ability of a state of the art language model, RoBERTa-large finetuned on the MNLI dataset, to make theory of mind inferences related to knowledge and belief. Experimental results suggest that the (...)
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  34.  30
    Alzheimer: A Neural Network Approach with Feature Analysis.Hussein Khaled Qarmout & Samy S. Abu-Naser - 2023 - International Journal of Academic Information Systems Research (IJAISR) 7 (10):10-18.
    Abstract Alzheimer's disease has spread insanely throughout the world. Early detection and intervention are essential to improve the chances of a positive outcome. This study presents a new method to predict a person's likelihood of developing Alzheimer's using a neural network model. The dataset includes 373 samples with 10 features, such as Group,M/F,Age,EDUC, SES,MMSE,CDR ,eTIV,nWBV,Oldpeak,ASF.. A four-layer neural network model (1 input, 2 hidden, 1 output) was trained on the dataset and achieved an accuracy of 98.10% and an average error (...)
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  35.  29
    Chances of Survival in the Titanic using ANN.Udai Hamed Saeed Al-Hayik & Samy S. Abu-Naser - 2023 - International Journal of Academic Engineering Research (IJAER) 7 (10):17-21.
    Abstract: The sinking of the RMS Titanic in 1912 remains a poignant historical event that continues to captivate our collective imagination. In this research paper, we delve into the realm of data-driven analysis by applying Artificial Neural Networks (ANNs) to predict the chances of survival for passengers aboard the Titanic. Our study leverages a comprehensive dataset encompassing passenger information, demographics, and cabin class, providing a unique opportunity to explore the complex interplay of factors influencing survival outcomes. Our ANN-based predictive model (...)
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  36.  99
    In search of value: The intricate impacts of benefit perception, knowledge, and emotion about climate change on marine protection support.Minh-Hoang Nguyen, Minh-Phuong Thi Duong, Quang-Loc Nguyen, Viet-Phuong La & Quan-Hoang Vuong - manuscript
    Marine and coastal ecosystems are crucial in maintaining human livelihood, facilitating social development, and reducing climate change impacts. Studies have examined how the benefit perception of aquatic ecosystems, knowledge, and emotion about climate change affect peoples’ support for marine protection. However, their interaction effects remain understudied. The current study explores the intricate interaction effect of the benefit perception of aquatic ecosystems, knowledge, and worry about climate change on marine protection support. Bayesian Mindsponge Framework (BMF) analytics was employed on a dataset (...)
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  37. Improving the market for livestock production households to alleviate food insecurity in the Philippines.Minh-Phuong Thi Duong, Ni Putu Wulan Purnama Sari, Adrino Mazenda, Tam-Tri Le, Minh-Hoang Nguyen & Quan-Hoang Vuong - manuscript
    Food security is one of the major concerns in the Philippines. Although livestock and poultry production accounts for a significant proportion of the country’s agricultural output, smallholder households are still vulnerable to food insecurity. The current study aims to examine how livestock production and selling difficulties affect smallholder households’ food-insecure conditions. For this objective, Bayesian Mindsponge Framework (BMF) analytics was employed on a dataset of the Food and Agriculture Organization’s Data in Emergencies Monitoring (DIEM) system. We found that production and (...)
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  38. Policy Response, Social Media and Science Journalism for the Sustainability of the Public Health System Amid the COVID-19 Outbreak: The Vietnam Lessons.La Viet Phuong, Pham Thanh Hang, Manh-Toan Ho, Nguyen Minh Hoang, Nguyen Phuc Khanh Linh, Vuong Thu Trang, Nguyen To Hong Kong, Tran Trung, Khuc Van Quy, Ho Manh Tung & Quan-Hoang Vuong - 2020 - Sustainability 12:2931.
    Vietnam, with a geographical proximity and a high volume of trade with China, was the first country to record an outbreak of the new Coronavirus disease (COVID-19), caused by the Severe Acute Respiratory Syndrome Coronavirus 2 or SARS-CoV-2. While the country was expected to have a high risk of transmission, as of April 4, 2020—in comparison to attempts to contain the disease around the world—responses from Vietnam are being seen as prompt and effective in protecting the interests of its citizens, (...)
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  39. Developing a Knowledge-Based System for Diagnosis and Treatment Recommendation of Neonatal Diseases Using CLIPS.Nida D. Wishah, Abed Elilah Elmahmoum, Husam A. Eleyan, Walid F. Murad & Samy S. Abu-Naser - 2023 - International Journal of Academic Engineering Research (IJAER) 7 (6):38-50.
    A newborn baby is an infant within the first 28 days of birth. Diagnosis and treatment of infant diseases require specialized medical resources and expert knowledge. However, there is a shortage of such professionals globally, particularly in low-income countries. To address this challenge, a knowledge-based system was designed to aid in the diagnosis and treatment of neonatal diseases. The system utilizes both machine learning and health expert knowledge, and a hybrid data mining process model was used to extract knowledge from (...)
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  40.  70
    Contradicting effects of subjective economic and cultural values on ocean protection willingness: preliminary evidence of 42 countries.Quang-Loc Nguyen, Minh-Hoang Nguyen, Tam-Tri Le, Thao-Huong Ma, Ananya Singh, Thi Minh-Phuong Duong & Quan-Hoang Vuong - manuscript
    Coastal protection is crucial to human development since the ocean has many values associated with the economy, ecosystem, and culture. However, most ocean protecting efforts are currently ineffective due to the burdens of finance, lack of appropriate management, and international cooperation regimes. For aiding bottom-up initiatives for ocean protection support, this study employed the Mindsponge Theory to examine how the public’s perceived economic and cultural values influence their willingness to support actions to protect the ocean. Analyzing the European-Union-Horizon-2020-funded dataset of (...)
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  41. Breast Cancer Diagnosis and Survival Prediction Using JNN.Mohammed Ziyad Abu Shawarib, Ahmed Essam Abdel Latif, Bashir Essam El-Din Al-Zatmah & Samy S. Abu-Naser - 2020 - International Journal of Engineering and Information Systems (IJEAIS) 4 (10):23-30.
    Abstract: Breast cancer is reported to be the most common cancer type among women worldwide and it is the second highest women fatality rate amongst all cancer types. Notwithstanding all the progresses made in prevention and early intervention, early prognosis and survival prediction rates are still not sufficient. In this paper, we propose an ANN model which outperforms all the previous supervised learning methods by reaching 99.57 in terms of accuracy in Wisconsin Breast Cancer dataset. Experimental results on Haberman’s Breast (...)
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  42. ANN Car Mileage per Gallon Prediction.Jomana Ahmed, Bayan Harb, Bassem S. Abu, Mohsen Afana & Rafiq Madhoun - 2017 - International Journal of Advanced Science and Technology 124:51-58.
    In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Make, Model, Type, Origin, DriveTrain, MSRP, Invoice, EngineSize, Cylinders, Horsepower, MPG_Highway, Weight, Wheelbase, Length. ANN was used in prediction of the number of miles per gallon when the car is driven in the city(MPG_City). The results showed that ANN model was able to predict MPG_City with 97.50 (...)
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  43. A Proposed Expert System for Diagnosis of Migraine.Malak S. Hammad, Raja E. N. Altarazi, Rawan N. Al Banna, Dina F. Al Borno & Samy S. Abu-Naser - 2023 - International Journal of Academic Engineering Research (IJAER) 7 (6):1-8.
    Migraine is a complex neurological disorder characterized by recurrent moderate to severe headaches, accompanied by additional symptoms such as nausea, sensitivity to light and sound, and visual disturbances. Accurate and timely diagnosis of migraines is crucial for effective management and treatment. However, the diverse range of symptoms and overlapping characteristics with other headache disorders pose challenges in the diagnostic process. In this research, we propose the development of an expert system for migraine diagnosis using artificial intelligence and the CLIPS (C (...)
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  44.  77
    Quantitative dynamics of design thinking and creativity perspectives in company context.Georgi V. Georgiev & Danko D. Georgiev - 2023 - Technology in Society 74:102292.
    This study is intended to provide in-depth insights into how design thinking and creativity issues are understood and possibly evolve in the course of design discussions in a company context. For that purpose, we use the seminar transcripts of the Design Thinking Research Symposium 12 (DTRS12) dataset “Tech-centred Design Thinking: Perspectives from a Rising Asia,” which are primarily concerned with how Korean companies implement design thinking and what role designers currently play. We employed a novel method of information processing based (...)
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  45.  72
    Predicting Kidney Stone Presence from Urine Analysis: A Neural Network Approach using JNN.Amira Jarghon & Samy S. Abu-Naser - 2023 - International Journal of Academic Information Systems Research (IJAISR) 7 (9):32-39.
    Kidney stones pose a significant health concern, and early detection can lead to timely intervention and improved patient outcomes. This research endeavours to predict the presence of kidney stones based on urine analysis, utilizing a neural network model. A dataset of 552 urine specimens, comprising six essential physical characteristics (specific gravity, pH, osmolarity, conductivity, urea concentration, and calcium concentration), was collected and prepared. Our proposed neural network architecture, featuring three layers (input, hidden, output), was trained and validated, achieving an impressive (...)
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  46.  40
    Prediction Heart Attack using Artificial Neural Networks (ANN).Ibrahim Younis, Mohammed S. Abu Nasser, Mohammed A. Hasaballah & Samy S. Abu-Naser - 2023 - International Journal of Engineering and Information Systems (IJEAIS) 7 (10):36-41.
    Abstract Heart Attack is the Cardiovascular Disease (CVD) which causes the most deaths among CVDs. We collected a dataset from Kaggle website. In this paper, we propose an ANN model for the predicting whether a patient has a heart attack or not that. The dataset set consists of 9 features with 1000 samples. We split the dataset into training, validation, and testing. After training and validating the proposed model, we tested it with testing dataset. The proposed model reached an accuracy (...)
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  47. Enhancing user creativity: semantic measures for idea generation.Georgi V. Georgiev & Danko D. Georgiev - 2018 - Knowledge-Based Systems 151:1-15.
    Human creativity generates novel ideas to solve real-world problems. This thereby grants us the power to transform the surrounding world and extend our human attributes beyond what is currently possible. Creative ideas are not just new and unexpected, but are also successful in providing solutions that are useful, efficient and valuable. Thus, creativity optimizes the use of available resources and increases wealth. The origin of human creativity, however, is poorly understood, and semantic measures that could predict the success of generated (...)
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  48. Prediction of Heart Disease Using a Collection of Machine and Deep Learning Algorithms.Ali M. A. Barhoom, Abdelbaset Almasri, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2022 - International Journal of Engineering and Information Systems (IJEAIS) 6 (4):1-13.
    Abstract: Heart diseases are increasing daily at a rapid rate and it is alarming and vital to predict heart diseases early. The diagnosis of heart diseases is a challenging task i.e. it must be done accurately and proficiently. The aim of this study is to determine which patient is more likely to have heart disease based on a number of medical features. We organized a heart disease prediction model to identify whether the person is likely to be diagnosed with a (...)
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  49. How AI’s Self-Prolongation Influences People’s Perceptions of Its Autonomous Mind: The Case of U.S. Residents.Quan-Hoang Vuong, Viet-Phuong La, Minh-Hoang Nguyen, Ruining Jin, Minh-Khanh La & Tam-Tri Le - 2023 - Behavioral Sciences 13 (6):470.
    The expanding integration of artificial intelligence (AI) in various aspects of society makes the infosphere around us increasingly complex. Humanity already faces many obstacles trying to have a better understanding of our own minds, but now we have to continue finding ways to make sense of the minds of AI. The issue of AI’s capability to have independent thinking is of special attention. When dealing with such an unfamiliar concept, people may rely on existing human properties, such as survival desire, (...)
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  50.  75
    The Pandemic Experience Survey II: A Second Corpus of Subjective Reports of Life Under Social Restrictions During COVID-19 in the UK, Japan, and Mexico.Mark M. James, Havi Carel, Matthew Ratcliffe, Tom Froese, Jamila Rodrigues, Ekaterina Sangati, Morgan Montoya, Federico Sangati & Natalia Koshkina - 2022 - Frontiers in Public Health.
    In August 2021, Froese et al. published survey data collected from 2,543 respondents on their subjective experiences living under imposed social distancing measures during COVID-19 (1). The questionnaire was issued to respondents in the UK, Japan, and Mexico. By combining the authors’ expertise in phenomenological philosophy, phenomenological psychopathology, and enactive cognitive science, the questions were carefully phrased to prompt reports that would be useful to phenomenological investigation and theorizing (2–4). These questions reflected the various author’s research interests (e.g., technology, grief, (...)
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