Search results for: scientific data mining

Authors: Ju-Young Kim, Tae-Heon Moon, Jung-Hun Cho

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Urban regeneration projects have been actively promoted in Korea. In particular, Jeonju Hanok Village is evaluated as one of representative cases in terms of utilizing local cultural heritage sits in the urban regeneration project. However, recently, there has been a growing concern in this area, due to the ‘gentrification’, caused by the excessive commercialization and surging tourists. This trend was changing land and building use and resulted in the loss of identity of the region. In this regard, this study analyzed the land use transformation between 2010 and 2016 to identify the commercialization trend in Jeonju Hanok Village. In addition, it conducted SNS big data analysis on Jeonju Hanok Village from February 14th, 2016 to March 31st, 2016 to identify visitors’ awareness of the village. The study results demonstrate that rapid commercialization was underway, unlikely the initial intention, so that planners and officials in city government should reconsider the project direction and rebuild deliberate management strategies. This study is meaningful in that it analyzed the land use transformation and SNS big data to identify the current situation in urban regeneration area. Furthermore, it is expected that the study results will contribute to the vitalization of regeneration area.

Keywords: land use, SNS, text mining, urban regeneration

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Authors: Niousha Bagheri Khulenjani, Mohammad Saniee Abadeh

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Learning from very big datasets is a significant problem for most present data mining and machine learning algorithms. MicroRNA (miRNA) is one of the important big genomic and non-coding datasets presenting the genome sequences. In this paper, a hybrid method for the classification of the miRNA data is proposed. Due to the variety of cancers and high number of genes, analyzing the miRNA dataset has been a challenging problem for researchers. The number of features corresponding to the number of samples is high and the data suffer from being imbalanced. The feature selection method has been used to select features having more ability to distinguish classes and eliminating obscures features. Afterward, a Convolutional Neural Network (CNN) classifier for classification of cancer types is utilized, which employs a Genetic Algorithm to highlight optimized hyper-parameters of CNN. In order to make the process of classification by CNN faster, Graphics Processing Unit (GPU) is recommended for calculating the mathematic equation in a parallel way. The proposed method is tested on a real-world dataset with 8,129 patients, 29 different types of tumors, and 1,046 miRNA biomarkers, taken from The Cancer Genome Atlas (TCGA) database.

Keywords: cancer classification, feature selection, deep learning, genetic algorithm

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Authors: Diana Cunha, Catarina Coelho, Ana Paula Relvas, Elisabeth Kastenholz

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Context: Tourist experiences have a recognized impact on the well-being of individuals. However, studies on the specific benefits of tourist experiences for families are scattered across different disciplines. This study aims to systematically review the literature to synthesize the evidence on the benefits of tourist experiences for families. Research Aim: The main objective is to systematize the evidence in the literature regarding the benefits of tourist experiences for families. Methodology: A systematic literature review was conducted using Nvivo, analyzing 33 scientific studies obtained from various databases. The search terms used were "family"/ "couple" and "tourist experience". The studies included quantitative, qualitative, mixed methods, and literature reviews. All works prior to the year 2000 were excluded, and the search was restricted to full text. A language filter was also used, considering articles in Portuguese, English, and Spanish. For NVivo analysis, information was coded based on both deductive and inductive perspectives. To minimize the subjectivity of the selection and coding process, two of the authors discussed the process and agreed on criteria that would make the coding more objective. Once the coding process in NVivo was completed, the data relating to the identification/characterization of the works were exported to the Statistical Package for the Social Sciences (SPPS), to characterize the sample. Findings: The results highlight that tourist experiences have several benefits for family systems, including the strengthening of family and marital bonds, the creation of family memories, and overall well-being and life satisfaction. These benefits contribute to both immediate relationship quality improvement and long-term family identity construction and transgenerational transmission. Theoretical Importance: This study emphasizes the systemic nature of the effects and relationships within family systems. It also shows that no harm was reported within these experiences, with only some challenges related to positive outcomes. Data Collection and Analysis Procedures: The study collected data from 33 scientific studies published predominantly after 2013. The data were analyzed using Nvivo, employing a systematic review approach. Question Addressed: The study addresses the question of the benefits of tourist experiences for families and how these experiences contribute to family functioning and individual well-being. Conclusion: Tourist experiences provide opportunities for families to enhance their interpersonal relationships and create lasting memories. The findings suggest that formal interventions based on evidence could further enhance the potential benefits of these experiences and be a valuable preventive tool in therapeutic interventions.

Keywords: family systems, individual and family well-being, marital satisfaction, tourist experiences

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Authors: Rizkia Shafarini

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The film A Beautiful Mind explores hallucination in this study. A Beautiful Mind depicts the tale of John Nash, a university student who dislikes studying in class or prefers to study alone. Throughout his life, John Nash has hallucinated, or what is known as schizophrenia, as depicted in the film A Beautiful Mind. The goal of this study was to figure out what hallucinations were, what caused them, and how John Nash managed his hallucinations. In general, this study examines the link between language and mind, or the linguistic relationship portrayed in John Nash's character's speech, as evidenced by his conduct. This study takes a psycholinguistic approach to data analysis by employing qualitative methodologies. Data sources include talks and scenes from the film A Beautiful Mind. Hearing, seeing, and feeling are the scientific results of John Nash's hallucinations in the film A Beautiful Mind. Second, dreams, aspirations, and sickness are the sources of John Nash's hallucinations. Third, John Nash's method of managing hallucinations is to see a doctor without medical or distracting assistance.

Keywords: A Beautiful Mind, hallucination, psycholinguistic, John Nash

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Authors: Dominika Collett

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AI applications, such as machine learning, require access to a vast amount of data in the training phase, which can often be the subject of copyright protection. During later usage, the various content with which the application works can be recorded or made available on the basis of which it produces the resulting output. The EU has recently adopted new legislation to secure machine access to protected works under the DSM Directive; but, the issue of machine use of copyright works is not clearly addressed. However, such clarity is needed regarding the increasing importance of AI and its development. Therefore, this paper provides a basic background of the technology used in the development of applications in the field of computer creativity. The second part of the paper then will focus on a legal analysis of machine use of the authors' works from the perspective of existing European and Czech legislation. The main results of the paper discuss the potential collision of existing legislation in regards to machine use of works with special focus on exceptions and limitations. The legal regulation of machine use of copyright work will impact the development of AI technology.

Keywords: copyright, artificial intelligence, legal use, infringement, Czech law, EU law, text and data mining

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Authors: Natalia Limones, Javier Marzo, Marcus Wijnen, Aleix Serrat-Capdevila

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In this research we developed a structured approach for the detection of areas under the highest levels of drought risk that is suitable for data-scarce environments. The methodology is based on recent scientific outcomes and methods and can be easily adapted to different contexts in successive exercises. The research reviews the history of drought in the south of Angola and characterizes the experienced hazard in the episode from 2012, focusing on the meteorological and the hydrological drought types. Only global open data information coming from modeling or remote sensing was used for the description of the hydroclimatological variables since there is almost no ground data in this part of the country. Also, the study intends to portray the socioeconomic vulnerabilities and the exposure to the phenomenon in the region to fully understand the risk. As a result, a map of the areas under the highest risk in the south of the country is produced, which is one of the main outputs of this work. It was also possible to confirm that the set of indicators used revealed different drought vulnerability profiles in the South of Angola and, as a result, several varieties of priority areas prone to distinctive impacts were recognized. The results demonstrated that most of the region experienced a severe multi-year meteorological drought that triggered an unprecedent exhaustion of the surface water resources, and that the majority of their socioeconomic impacts started soon after the identified onset of these processes.

Keywords: drought risk, exposure, hazard, vulnerability

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Authors: Haluk Eren, Mucahit Karaduman

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This paper presents 15-year trends for scientific studies in a scientific database considering 3D and vehicle words. Two words are selected to find their associated publications in IEEE scholar database. Both of keywords are entered individually for the years 2002, 2012, and 2016 on the database to identify the preferred subjects of researchers in same years. We have classified closer research fields after searching and listing. Three years (2002, 2012, and 2016) have been investigated to figure out progress in specified time intervals. The first one is assumed as the initial progress in between 2002-2012, and the second one is in 2012-2016 that is fast development duration. We have found very interesting and beneficial results to understand the scholars’ research field preferences for a decade. This information will be highly desirable in smart city-based research purposes consisting of 3D and vehicle-related issues.

Keywords: Vehicle, three-dimensional, smart city, scholarly search, semantic

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Authors: Javed Mohammed

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Right now, bio-medical infrastructure lags well behind the curve. Our healthcare system is dispersed and disjointed; medical records are a bit of a mess; and we do not yet have the capacity to store and process the crazy amounts of data coming our way from widespread whole-genome sequencing. And then there are privacy issues. Despite these infrastructure challenges, some researchers are plunging into bio medical Big Data now, in hopes of extracting new and actionable knowledge. They are doing delving into molecular-level data to discover bio markers that help classify patients based on their response to existing treatments; and pushing their results out to physicians in novel and creative ways. Computer scientists and bio medical researchers are able to transform data into models and simulations that will enable scientists for the first time to gain a profound under-standing of the deepest biological functions. Solving biological problems may require High-Performance Computing HPC due either to the massive parallel computation required to solve a particular problem or to algorithmic complexity that may range from difficult to intractable. Many problems involve seemingly well-behaved polynomial time algorithms (such as all-to-all comparisons) but have massive computational requirements due to the large data sets that must be analyzed. High-throughput techniques for DNA sequencing and analysis of gene expression have led to exponential growth in the amount of publicly available genomic data. With the increased availability of genomic data traditional database approaches are no longer sufficient for rapidly performing life science queries involving the fusion of data types. Computing systems are now so powerful it is possible for researchers to consider modeling the folding of a protein or even the simulation of an entire human body. This research paper emphasizes the computational biology's growing need for high-performance computing and Big Data. It illustrates this article’s indispensability in meeting the scientific and engineering challenges of the twenty-first century, and how Protein Folding (the structure and function of proteins) and Phylogeny Reconstruction (evolutionary history of a group of genes) can use HPC that provides sufficient capability for evaluating or solving more limited but meaningful instances. This article also indicates solutions to optimization problems, and benefits Big Data and Computational Biology. The article illustrates the Current State-of-the-Art and Future-Generation Biology of HPC Computing with Big Data.

Keywords: high performance, big data, parallel computation, molecular data, computational biology

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Authors: Farrukh Shahzad

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The rich Islamic resources related to religious text, Islamic sciences, and history are widely available in print and in electronic format online. However, most of these works are only available in Arabic language. In this research, an attempt is made to utilize these resources to create interactive web applications in Arabic, English and other languages. The system utilizes the Pattern Recognition, Knowledge Management, Data Mining, Information Retrieval and Management, Indexing, storage and data-analysis techniques to parse, store, convert and manage the information from authentic Arabic resources. These interactive web Apps provide smart multi-lingual search, tree based search, on-demand information matching and linking. In this paper, we provide details of application architecture, design, implementation and technologies employed. We also presented the summary of web applications already developed. We have also included some screen shots from the corresponding web sites. These web applications provide an Innovative On-line Learning Systems (eLearning and computer based education).

Keywords: Islamic resources, Muslim scholars, hadith, narrators, history, fiqh

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Authors: Styliani Soulioti, Helen Fiddler

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The aim of this study was to investigate the approaches used by physiotherapists in the education of patients with chronic low back pain (cLBP) and the rationale that underpins their choice of approach. Therapeutic patient education (TPE) is considered to be an important aspect of modern physiotherapy practice, as it helps patients achieve better self-management and a better understanding of their problem. Previous studies have explored this subject, but the reasoning behind the choices physiotherapists make as educators has not been widely explored, thus making it difficult to understand areas that could be addressed in order to improve the application of TPE.A qualitative study design, guided by a constructivist epistemology was used in this research project. Semi-structured interviews were used to collect data from 7 physiotherapists. Inductive coding and thematic analysis were used, which allowed key themes to emerge. Data analysis revealed two overarching themes: 1) patient-centred versus therapist-centred educational approaches, and 2) behaviourist versus constructivist educational approaches. Physiotherapists appear to use a patient-centred-approach when they explore patients’ beliefs about cLBP and treatment expectations. However, treatment planning and goal-setting were guided by a therapist-centred approach, as physiotherapists appear to take on the role of the instructor/expert, whereas patients were viewed as students. Using a constructivist approach, physiotherapists aimed to provide guidance to patients by combining their professional knowledge with the patients’ individual knowledge, to help the patient better understand their problem, reflect upon it and find a possible solution. However, educating patients about scientific facts concerning cLBP followed a behaviourist approach, as an instructor/student relationship was observed and the learning content was predetermined and transmitted in a one-way manner. The results of this study suggest that a lack of consistency appears to exist in the educational approaches used by physiotherapists. Although patient-centeredness and constructivism appear to be the aims set by physiotherapists in order to optimise the education they provide, a student-teacher relationship appears to dominate when it comes to goal-setting and delivering scientific information.

Keywords: chronic low back pain, educational approaches, health education, patient education

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Authors: David J. Foran, Nhan Do, Samuel Ajjarapu, Wenjin Chen, Tahsin Kurc, Joel H. Saltz

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The large-scale data and computational requirements of investigators throughout the clinical and research communities demand an informatics infrastructure that supports both existing and new investigative and translational projects in a robust, secure environment. In some subspecialties of medicine and research, the capacity to generate data has outpaced the methods and technology used to aggregate, organize, access, and reliably retrieve this information. Leading health care centers now recognize the utility of establishing an enterprise-wide, clinical data warehouse. The primary benefits that can be realized through such efforts include cost savings, efficient tracking of outcomes, advanced clinical decision support, improved prognostic accuracy, and more reliable clinical trials matching. The overarching objective of the work presented here is the development and implementation of a flexible Intelligent Retrieval and Interrogation System (IRIS) that exploits the combined use of computational imaging, genomics, and data-mining capabilities to facilitate clinical assessments and translational research in oncology. The proposed System includes a multi-modal, Clinical & Research Data Warehouse (CRDW) that is tightly integrated with a suite of computational and machine-learning tools to provide insight into the underlying tumor characteristics that are not be apparent by human inspection alone. A key distinguishing feature of the System is a configurable Extract, Transform and Load (ETL) interface that enables it to adapt to different clinical and research data environments. This project is motivated by the growing emphasis on establishing Learning Health Systems in which cyclical hypothesis generation and evidence evaluation become integral to improving the quality of patient care. To facilitate iterative prototyping and optimization of the algorithms and workflows for the System, the team has already implemented a fully functional Warehouse that can reliably aggregate information originating from multiple data sources including EHR’s, Clinical Trial Management Systems, Tumor Registries, Biospecimen Repositories, Radiology PAC systems, Digital Pathology archives, Unstructured Clinical Documents, and Next Generation Sequencing services. The System enables physicians to systematically mine and review the molecular, genomic, image-based, and correlated clinical information about patient tumors individually or as part of large cohorts to identify patterns that may influence treatment decisions and outcomes. The CRDW core system has facilitated peer-reviewed publications and funded projects, including an NIH-sponsored collaboration to enhance the cancer registries in Georgia, Kentucky, New Jersey, and New York, with machine-learning based classifications and quantitative pathomics, feature sets. The CRDW has also resulted in a collaboration with the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) at the U.S. Department of Veterans Affairs to develop algorithms and workflows to automate the analysis of lung adenocarcinoma. Those studies showed that combining computational nuclear signatures with traditional WHO criteria through the use of deep convolutional neural networks (CNNs) led to improved discrimination among tumor growth patterns. The team has also leveraged the Warehouse to support studies to investigate the potential of utilizing a combination of genomic and computational imaging signatures to characterize prostate cancer. The results of those studies show that integrating image biomarkers with genomic pathway scores is more strongly correlated with disease recurrence than using standard clinical markers.

Keywords: clinical data warehouse, decision support, data-mining, intelligent databases, machine-learning.

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Authors: Mina Samizadeh

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In the past few decades, there has been an explosion in the amount of available data produced from various sources with different topics. The availability of this enormous data necessitates us to adopt effective computational tools to explore the data. This leads to an intense growing interest in the research community to develop computational methods focused on processing this text data. A line of study focused on condensing the text so that we are able to get a higher level of understanding in a shorter time. The two important tasks to do this are keyword extraction and text summarization. In keyword extraction, we are interested in finding the key important words from a text. This makes us familiar with the general topic of a text. In text summarization, we are interested in producing a short-length text which includes important information about the document. The TextRank algorithm, an unsupervised learning method that is an extension of the PageRank (algorithm which is the base algorithm of Google search engine for searching pages and ranking them), has shown its efficacy in large-scale text mining, especially for text summarization and keyword extraction. This algorithm can automatically extract the important parts of a text (keywords or sentences) and declare them as a result. However, this algorithm neglects the semantic similarity between the different parts. In this work, we improved the results of the TextRank algorithm by incorporating the semantic similarity between parts of the text. Aside from keyword extraction and text summarization, we develop a topic clustering algorithm based on our framework, which can be used individually or as a part of generating the summary to overcome coverage problems.

Keywords: keyword extraction, n-gram extraction, text summarization, topic clustering, semantic analysis

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Authors: Martina Perinkova, Lenka Kolarcikova, Marketa Twrda

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Brownfields are one of the most important problems that must be solved by today's cities. The topic of this article is description of developing a comprehensive transformation of post-industrial area of the former iron factory national cultural heritage Lower Vítkovice. City of Ostrava used to be industrial superpower of the Czechoslovak Republic, especially in the area of coal mining and iron production, after declining industrial production and mining in the 80s left many unused areas of former factories generally brownfields and backfields. Since the late 90s we are observing how the city officials or private entities seeking to remedy this situation. Regeneration of brownfields is a very expensive and long-term process. The area is now rebuilt for tourists and residents of the city in the entertainment, cultural, and social center. It was necessary do the reconstruction of the industrial monuments. Equally important was the construction of new buildings, which helped reusing of the entire complex. This is a unique example of transformation of technical monuments and completion of necessary new objects, so that the area could start working again and reintegrate back into the urban system.

Keywords: brown fields, conversion, historical and industrial buildings, reconstruction

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Authors: Paola Cattabriga

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According to Gödel’s first incompleteness argument it is possible to construct a formally undecidable proposition in Principia mathematica, a statement that, although true, turns out to be neither provable nor refutable for the system, making therefore incomplete any formal system suitable for the arithmetic of integers. Its features and limitation effects are today widespread basics throughout whole scientific thought. This article brings Gödel’s achievement into question by the definition of the refutability predicate as a number-theoretical statement. We develop proof of invalidity of Theorem VI in Gödel’s 1931, the so-called Gödel’s first incompleteness theorem, in two steps: defining refutability within the same recursive status as provability and showing that as a consequence propositions (15) and (16), derived from definition 8.1 in Gödel’s 1931, are false and unacceptable for the system. The achievement of their falsity blocks the derivation of Theorem VI, which turns out to be therefore invalid, together with all the depending theorems. This article opens up thus new perspectives for mathematical research and for the overall scientific reasoning.

Keywords: Gödel numbering, incompleteness, provability predicate, refutability predicate

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Authors: Dominique Arrouays, Songchao Chen, Anne C. Richer-De-Forges

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Soils are at the crossing of many issues such as food and water security, sustainable energy, climate change mitigation and adaptation, biodiversity protection, human health and well-being. They deliver many ecosystem services that are essential to life on Earth. Therefore, there is a growing demand for soil information on a national and global scale. Unfortunately, many countries do not have detailed soil maps, and, when existing, these maps are generally based on more or less complex and often non-harmonized soil classifications. An estimate of their uncertainty is also often missing. Thus, there are not easy to understand and often not properly used by end-users. Therefore, there is an urgent need to provide end-users with spatially exhaustive grids of essential soil properties, together with an estimate of their uncertainty. One way to achieve this is digital soil mapping (DSM). The concept of DSM relies on the hypothesis that soils and their properties are not randomly distributed, but that they depend on the main soil-forming factors that are climate, organisms, relief, parent material, time (age), and position in space. All these forming factors can be approximated using several exhaustive spatial products such as climatic grids, remote sensing products or vegetation maps, digital elevation models, geological or lithological maps, spatial coordinates of soil information, etc. Thus, DSM generally relies on models calibrated with existing observed soil data (point observations or maps) and so-called “ancillary co-variates” that come from other available spatial products. Then the model is generalized on grids where soil parameters are unknown in order to predict them, and the prediction performances are validated using various methods. With the growing demand for soil information at a national and global scale and the increase of available spatial co-variates national and continental DSM initiatives are continuously increasing. This short review illustrates the main national and continental advances in Europe, the diversity of the approaches and the databases that are used, the validation techniques and the main scientific and other issues. Examples from several countries illustrate the variety of products that were delivered during the last ten years. The scientific production on this topic is continuously increasing and new models and approaches are developed at an incredible speed. Most of the digital soil mapping (DSM) products rely mainly on machine learning (ML) prediction models and/or the use or pedotransfer functions (PTF) in which calibration data come from soil analyses performed in labs or for existing conventional maps. However, some scientific issues remain to be solved and also political and legal ones related, for instance, to data sharing and to different laws in different countries. Other issues related to communication to end-users and education, especially on the use of uncertainty. Overall, the progress is very important and the willingness of institutes and countries to join their efforts is increasing. Harmonization issues are still remaining, mainly due to differences in classifications or in laboratory standards between countries. However numerous initiatives are ongoing at the EU level and also at the global level. All these progress are scientifically stimulating and also promissing to provide tools to improve and monitor soil quality in countries, EU and at the global level.

Keywords: digital soil mapping, global soil mapping, national and European initiatives, global soil mapping products, mini-review

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Authors: Marek Dosbaba

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Within the mining sector, SEM-based Automated Mineralogy (AM) has been the standard application for quickly and efficiently handling mineral processing tasks. Over the last decade, the trend has been to analyze larger numbers of samples, often with a higher level of detail. This has necessitated a shift from interactive sample analysis performed by an operator using a SEM, to an increased reliance on offline processing to analyze and report the data. In response to this trend, TESCAN TIMA Mineral Analyzer is designed to quickly create a virtual copy of the studied samples, thereby preserving all the necessary information. Depending on the selected data acquisition mode, TESCAN TIMA can perform hyperspectral mapping and save an X-ray spectrum for each pixel or segment, respectively. This approach allows the user to browse through elemental distribution maps of all elements detectable by means of energy dispersive spectroscopy. Re-evaluation of the existing data for the presence of previously unconsidered elements is possible without the need to repeat the analysis. Additional tiers of data such as a secondary electron or cathodoluminescence images can also be recorded. To take full advantage of these information-rich datasets, TIMA utilizes a new archiving tool introduced by TESCAN. The dataset size can be reduced for long-term storage and all information can be recovered on-demand in case of renewed interest. TESCAN TIMA is optimized for network storage of its datasets because of the larger data storage capacity of servers compared to local drives, which also allows multiple users to access the data remotely. This goes hand in hand with the support of remote control for the entire data acquisition process. TESCAN also brings a newly extended open-source data format that allows other applications to extract, process and report AM data. This offers the ability to link TIMA data to large databases feeding plant performance dashboards or geometallurgical models. The traditional tabular particle-by-particle or grain-by-grain export process is preserved and can be customized with scripts to include user-defined particle/grain properties.

Keywords: Tescan, electron microscopy, mineralogy, SEM, automated mineralogy, database, TESCAN TIMA, open format, archiving, big data

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Authors: Feng Yang

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Machine learning (ML), especially deep learning (DL), has been extensively applied to many applications in recently years and gained great success in solving different problems, including scientific problems. However, conventional ML/DL methodologies are purely data-driven which have the limitations, such as need of ample amount of labelled training data, lack of consistency to physical principles, and lack of generalizability to new problems/domains. Recently, there is a growing consensus that ML models need to further take advantage of prior knowledge to deal with these limitations. Physics-informed machine learning, aiming at integration of physics/domain knowledge into ML, has been recognized as an emerging area of research, especially in the recent 2 to 3 years. In this work, physics-informed ML, specifically physics-informed neural network (NN), is employed and implemented to estimate the displacements at x, y, z directions in a solid mechanics problem that is controlled by equilibrium equations with boundary conditions. By incorporating the physics (i.e. the equilibrium equations) into the learning process of NN, it is showed that the NN can be trained very efficiently with a small set of labelled training data. Experiments with different settings of the NN model and the amount of labelled training data were conducted, and the results show that very high accuracy can be achieved in fulfilling the equilibrium equations as well as in predicting the displacements, e.g. in setting the overall displacement of 0.1, a root mean square error (RMSE) of 2.09 × 10−4 was achieved.

Keywords: deep learning, neural network, physics-informed machine learning, solid mechanics

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Authors: José Luis Lorenzo Bayona, Ljiljana Medic-Pejic, Isabel Amez Arenillas, Blanca Castells Somoza

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The communication presents the study results carried out by the Official Laboratory J. M. Madariaga (LOM) of the Polytechnic University of Madrid to analyze the reliability of methane detection systems used in underground mining. Poor firedamp control in work can cause from production stoppages to fatal accidents and since there is currently a great variety of equipment with different functional characteristics, a study is needed to indicate which measurement principles have the highest degree of confidence. For the development of the project, a series of fixed, transportable and portable methane detectors with different measurement principles have been selected to subject them to laboratory tests following the methods described in the applicable regulations. The test equipment has been the one usually used in the certification and calibration of these devices, subject to the LOM quality system, and the tests have been carried out on detectors accessible in the market. The conclusions establish the main advantages and disadvantages of the equipment according to the measurement principle used; catalytic combustion, interferometry and infrared absorption.

Keywords: ATEX standards, gas detector, methane meter, mining safety

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Authors: Zheng Yi

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Among the attempts made worldwide to foster urban and transport sustainability, transit-oriented development certainly is one of the most successful. Residents' travel behavior is a concern in the researches about the impacts of transit-oriented development. The study takes 620 English journal papers in the core collection database of Web of Science as the study objects; the paper tries to map out the scientific knowledge mapping in the field and draw the basic conditions by co-citation analysis, co-word analysis, a total of citation network analysis and visualization techniques. This study teases out the research hotspots and evolution of the relationship between urban rail transit and resident's travel behavior from 1999 to 2019. According to the results of the analysis of the time-zone view and burst-detection, the paper discusses the trend of the next stage of international study. The results show that in the past 20 years, the research focuses on these keywords: land use, behavior, model, built environment, impact, travel behavior, walking, physical activity, smart card, big data, simulation, perception. According to different research contents, the key literature is further divided into these topics: the attributes of the built environment, land use, transportation network, transportation policies. The results of this paper can help to understand the related researches and achievements systematically. These results can also provide a reference for identifying the main challenges that relevant researches need to address in the future.

Keywords: urban rail transit, travel behavior, knowledge map, evolution of researches

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Authors: Haitham Magdy Hamad, Mohamed Ahmed Madkour

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The essential role of the digital library in developing museum display methods, recording ancient Egyptian antiquities, facilitating scientific research, and storing antiquities in the Grand Egyptian Museum, which helped and saved a lot of time and money spent to equip the Grand Egyptian Museum. The technology of digital libraries, linking it to ancient Egyptian antiquities and the latest results, which scientific research has reached in the field of libraries and its impact on many areas of tourism and antiquities. The research also aims to show the main role of the digital library and the Arab countries emulating European countries in digitizing libraries and recent developments in Egyptian libraries and their role in many areas of life and linking them to Egyptology. The research will also explain how the museum display methods will be developed in the Grand Egyptian Museum, and the recording of ancient Egyptian antiquities in order to facilitate the process of scientific research and methods of storing antiquities will also work to save time and effort for researchers. The research will also deal with lighting and its prominent role in the display in the interior design and coordination of the Grand Egyptian Museum, through which the unique artifacts and artifacts displayed can be displayed, and they can be used in a strong or simple form. Depending on the condition of the piece to be displayed. The research will also go to show the role of the digital library in how the Grand Egyptian Museum contains gathering areas and how to distribute spaces, guidance, information, reception, libraries, lecture halls, restaurants, cafeterias, shops, permanent and temporary galleries, and bathrooms.

Keywords: knowledge, library, culture, archaeology, grand Egyptian museum, numbering

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Authors: Lin Qing

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[Objective/Significance] The cultivation of high-value patents is the focus and difficulty of patent work, which is of great significance to the construction of a powerful country with intellectual property rights. This work should not only pay attention to the existing patent applications, but also start from the pre-application to explore the high-value technical solutions as the core of high-value patents. [Methods/processes] Comply with the principle of scientific and technological knowledge diffusion, this study studies the top academic conference papers and their cited patent applications, taking the power semiconductor field as an example, using facts date show the feasibility and rationality of mining technology solutions from high quality research results to foster high value patents, stating the actual benefits of these achievements to the industry, giving patent protection suggestions for Chinese applicants comparative with field situation. [Results/Conclusion] The research shows that the quality of citation applications of ISPSD papers is significantly higher than the field average level, and the ability of Chinese applicants to use patent protection related achievements needs to be improved. This study provides a practical and highly targeted reference idea for patent administrators and researchers, and also makes a positive exploration for the practice of the spirit of breaking the five rules.

Keywords: high-value patents cultivation, technical solutions, knowledge diffusion, top academic conference papers, intellectual property information analysis

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Authors: Luiza Toschi

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This work presents part of an empirical and theoretical master's degree meta-research that is interested in the relationship between the disciplinary area of Social Communication, to be investigated with the characteristics of the Bourdieusian scientific field, and the emergence of public interest in Nonviolent Communication (NVC) in Brazil and the world. To this end, the state of the art of this conceptual and practical relationship is investigated based on scientific productions available in spaces of academic credibility, such as conferences and scientific journals renowned in the field. From there, agents and the sociological aspects that make them contribute or not to scientific production in Brazil and the world are mapped. In this work, a brief dive into the international context is presented to understand if and how nonviolent communication permeates scientific production in communication in a systematic way. Using three accessible articles published between 2013 and 2022 in the 117 magazines classified as Quartiles Q1 in the Journal Ranking of Communication, the international production on the subject is compared with the Brazilian one from its context. The social conditions of the international circulation of ideas are thus discussed. Science is a product of its social environment, arising from relations of interest and power that compete in the political dimension at the same time as in the epistemological dimension. In this way, scientific choices are linked to the resources mobilized from or through the prestige and recognition of peers. In this sense, an object of interest stands out to a scientist for its academic value, but also and inseparably that which has a social interest within the collective, their social stratification, and the context of legitimacy created in their surroundings, influenced by cultural universalism. In Brazil, three published articles were found in congresses and journals that mention NVC in their abstract or keywords. All were written by Public Relations undergraduate students. Between the most experienced researchers who guided or validated the publications, it is possible to find two professionals who are interested in the Culture of Peace and Dialogy. Likewise, internationally, only three of the articles found mention the term in their abstract or title. Two analyze journalistic coverage based on the principles of NVC and Journalism for Peace. The third is from one of the Brazilian researchers identified as interested in dialogic practices, who analyses audiovisual material and promotes epistemological reflections. If, on the one hand, some characteristics inside and outside Brazil are similar: small samples, relationship with peace studies, and female researchers, two of whom are Brazilian, on the other hand, differences are obvious. If within the country, the subject is mostly Organizational Communication, outside this intersection, it is not presented explicitly. Furthermore, internationally, there is an interest in analyzing from the perspective of NVC, which has not been found so far in publications in Brazil. Up to the present moment, it is possible to presume that, universally, the legitimacy of the topic is sought by its association with conflict conciliation research and communication for peace.

Keywords: academic field sociology, international circulation of ideas, meta research in communication, nonviolent communication

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Authors: Jiang Hua Zhou

Abstract:

According to the article "New Theoretical System of Physics in the 21st Century" published by the author, it is proposed to use the "scientific principle" of the "balanced distance" between "gravity" and "repulsion" between "planets" to "research" - "space flying saucer", and The formula for the law of universal repulsion between substances is proposed. Under the guidance of the new theoretical system, according to the principle of "planet" gravitational and repulsive force, the research and development idea of developing discharge-type "space flying saucer" is put forward. This paper expounds the reasons why flying saucers have the following characteristics: Flying Saucers can fly at high speed, change direction immediately, hover at any height on the earth, and there is no sound when flying. With the birth of the theoretical system of physics in the 21st century advocated by the author, a era of interstellar "space flying saucer" research will be created.

Keywords: planet, attraction, repulsive force, balance spacing, scientific principles, research, space, flying saucer

Procedia PDF Downloads 109

Authors: Iftikhar A. Tayubi, Aabdulrahman Alsubhi, Abdullah Althrwi

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The deoxyribonucleic acid text provides a single source of high-quality Cryptography about Deoxyribonucleic acid sequence for structural biologists. We will provide an intuitive, well-organized and user-friendly web interface that allows users to encrypt and decrypt Deoxy Ribonucleic Acid sequence text. It includes complex, securing by using Algorithm to encrypt and decrypt Deoxy Ribonucleic Acid sequence. The utility of this Deoxy Ribonucleic Acid Sequence Text is that, it can provide a user-friendly interface for users to Encrypt and Decrypt store the information about Deoxy Ribonucleic Acid sequence. These interfaces created in this project will satisfy the demands of the scientific community by providing fully encrypt of Deoxy Ribonucleic Acid sequence during this website. We have adopted a methodology by using C# and Active Server Page.NET for programming which is smart and secure. Deoxy Ribonucleic Acid sequence text is a wonderful piece of equipment for encrypting large quantities of data, efficiently. The users can thus navigate from one encoding and store orange text, depending on the field for user’s interest. Algorithm classification allows a user to Protect the deoxy ribonucleic acid sequence from change, whether an alteration or error occurred during the Deoxy Ribonucleic Acid sequence data transfer. It will check the integrity of the Deoxy Ribonucleic Acid sequence data during the access.

Keywords: algorithm, ASP.NET, DNA, encrypt, decrypt

Procedia PDF Downloads 214

Authors: Said Baadel, Fadi Thabtah, Joan Lu

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Clustering involves the partitioning of n objects into k clusters. Many clustering algorithms use hard-partitioning techniques where each object is assigned to one cluster. In this paper, we propose an overlapping algorithm MCOKE which allows objects to belong to one or more clusters. The algorithm is different from fuzzy clustering techniques because objects that overlap are assigned a membership value of 1 (one) as opposed to a fuzzy membership degree. The algorithm is also different from other overlapping algorithms that require a similarity threshold to be defined as a priority which can be difficult to determine by novice users.

Keywords: data mining, k-means, MCOKE, overlapping

Procedia PDF Downloads 548

Authors: Kayondoamunmose Kamafrika

Abstract:

Experimental based Engineering education approach plays a vital role in the development of student’s deep understanding of both social and physical sciences. Experimental based education approach through laboratory class activities prepare students to meet national demand for high-tech skilled individuals in the government and private sector. However, students across the country are faced with difficulties in classes that involve laboratory activities: poor experimental based exposure in their early development of student’s education-life-cycle, lack of student engagement in scientific method practical thinking approach, lack of communication between students and the instructor during class, a large number of students in one classroom, lack of instruments and improper equipment calibration. The purpose of this paper is to help students develop their own scientific knowledge and understanding, develop their methodologies in the design of experiments, collect and analyze data, write laboratory reports, present and explain their findings. Experimental based laboratory activities allow students to learn with high-level understanding as well as engage in the design processes of constructing knowledge through practical means of doing science. Experimental based education systems approach will act as a catalyst in the development of practical-based-educational methodologies in social and physical science and engineering domain of learning; thereby, converting laboratory classes into pilot industries and students into professional experts in finding a solution for complex problems, research, and development of super high- tech systems.

Keywords: experimental, engineering, innovation, practicability

Procedia PDF Downloads 164

Authors: Ankit Sinha, Soham Banerjee, Pratik Chattopadhyay

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Automated product recognition in retail stores is an important real-world application in the domain of Computer Vision and Pattern Recognition. In this paper, we consider the problem of automatically identifying the classes of the products placed on racks in retail stores from an image of the rack and information about the query/product images. We improve upon the existing approaches in terms of effectiveness and memory requirement by developing a two-stage object detection and recognition pipeline comprising of a Faster-RCNN-based object localizer that detects the object regions in the rack image and a ResNet-18-based image encoder that classifies the detected regions into the appropriate classes. Each of the models is fine-tuned using appropriate data sets for better prediction and data augmentation is performed on each query image to prepare an extensive gallery set for fine-tuning the ResNet-18-based product recognition model. This encoder is trained using a triplet loss function following the strategy of online-hard-negative-mining for improved prediction. The proposed models are lightweight and can be connected in an end-to-end manner during deployment to automatically identify each product object placed in a rack image. Extensive experiments using Grozi-32k and GP-180 data sets verify the effectiveness of the proposed model.

Keywords: retail stores, faster-RCNN, object localization, ResNet-18, triplet loss, data augmentation, product recognition

Procedia PDF Downloads 131

Authors: Verónica Diaz Quezada

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This research examines the teaching models used by secondary math teachers when teaching logarithmic, quadratic and exponential functions. For this, descriptive case studies have been carried out on 5 secondary teachers. These teachers have been chosen from 3 scientific-humanistic and technical schools, in Chile. Data have been obtained through non-participant class observation and the application of a questionnaire and a rubric to teachers. According to the results, the didactic model that prevails is the one that starts with an interactive strategy, moves to a more content-based structure, and ends with a reinforcement stage. Nonetheless, there is always influence from teachers, their methods, and the group of students.

Keywords: teaching models, math teachers, functions, secondary education

Procedia PDF Downloads 175

Authors: M. Marín-Ferrer, M. A. Hernández, T. Tollefsen, S. Vanzo, E. Nweke, P. V. Tognoli, M. De Cort

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Under the terms of Article 36 of the Euratom Treaty, European Union Member States (MSs) shall periodically communicate to the European Commission (EC) information on environmental radioactivity levels. Compilations of the information received have been published by the EC as a series of reports beginning in the early 1960s. The environmental radioactivity results received from the MSs have been introduced into the Radioactivity Environmental Monitoring database (REMdb) of the Institute for Transuranium Elements of the EC Joint Research Centre (JRC) sited in Ispra (Italy) as part of its Directorate General for Energy (DG ENER) support programme. The REMdb brings to the scientific community dealing with environmental radioactivity topics endless of research opportunities to exploit the near 200 millions of records received from MSs containing information of radioactivity levels in milk, water, air and mixed diet. The REM action was created shortly after Chernobyl crisis to support the EC in its responsibilities in providing qualified information to the European Parliament and the MSs on the levels of radioactive contamination of the various compartments of the environment (air, water, soil). Hence, the main line of REM’s activities concerns the improvement of procedures for the collection of environmental radioactivity concentrations for routine and emergency conditions, as well as making this information available to the general public. In this way, REM ensures the availability of tools for the inter-communication and access of users from the Member States and the other European countries to this information. Specific attention is given to further integrate the new MSs with the existing information exchange systems and to assist Candidate Countries in fulfilling these obligations in view of their membership of the EU. Article 36 of the EURATOM treaty requires the competent authorities of each MS to provide regularly the environmental radioactivity monitoring data resulting from their Article 35 obligations to the EC in order to keep EC informed on the levels of radioactivity in the environment (air, water, milk and mixed diet) which could affect population. The REMdb has mainly two objectives: to keep a historical record of the radiological accidents for further scientific study, and to collect the environmental radioactivity data gathered through the national environmental monitoring programs of the MSs to prepare the comprehensive annual monitoring reports (MR). The JRC continues his activity of collecting, assembling, analyzing and providing this information to public and MSs even during emergency situations. In addition, there is a growing concern with the general public about the radioactivity levels in the terrestrial and marine environment, as well about the potential risk of future nuclear accidents. To this context, a clear and transparent communication with the public is needed. EURDEP (European Radiological Data Exchange Platform) is both a standard format for radiological data and a network for the exchange of automatic monitoring data. The latest release of the format is version 2.0, which is in use since the beginning of 2002.

Keywords: environmental radioactivity, Euratom, monitoring report, REMdb

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Authors: Shinen B., Bavor J., Dorjkhand B., Suvd B., Maitsetseg B.

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A number of remediation techniques are available for the treatment of soils and sediments contaminated by heavy metals. However, some of these techniques are expensive and environmentally disruptive. Nanomaterials are used in the environment as environmental catalysts to convert toxic substances from water, soil, and sediment into environmentally benign compounds. This study was carried out to scrutinize the feasibility of vivianite nanoparticles for remediation of soils contaminated with heavy metals. Column experiments were performed in the laboratory to examine nanoparticle sequestration of metal in soil amended with vivianite nanoparticle suspension. The effect of environmental parameters such as temperature, pH and redox potential on metal leachability and bioavailability of soil amended with nanoparticle suspension was examined and compared with non-amended soils. The vivianite was effective in reducing the leachability of metals in soils. It is suggested that vivianite nanoparticles could be applied for the remediation of contaminated sites polluted by heavy metals due to mining activities, particularly in Mongolia, where mining industries have been developing rapidly in the last decade.

Keywords: bioavailability, heavy metals, nanoparticles, remediation

Procedia PDF Downloads 170