Search results for: topic extraction

Authors: Isidro Perez, Maryam Nazari

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Numerous earthquakes, which have taken place across the world, led to catastrophic damage and collapse of structures (e.g., 1971 San Fernando; 1995 Kobe-Japan; and 2010 Chile earthquakes). Engineers are constantly studying methods to moderate the effect this phenomenon has on structures to further reduce damage, costs, and ultimately to provide life safety to occupants. However, there are regions where structures, cities, or water reservoirs are built near fault lines. When an earthquake occurs near the fault lines, they can be categorized as near-field earthquakes. In contrary, a far-field earthquake occurs when the region is further away from the seismic source. A near-field earthquake generally has a higher initial peak resulting in a larger seismic response, when compared to a far-field earthquake ground motion. These larger responses may result in serious consequences in terms of structural damage which can result in a high risk for the public’s safety. Unfortunately, the response of structures subjected to near-field records are not properly reflected in the current building design specifications. For example, in ASCE 7-10, the design response spectrum is mostly based on the far-field design-level earthquakes. This may result in the catastrophic damage of structures that are not properly designed for near-field earthquakes. This research investigates the knowledge that the effect of near-field earthquakes has on the response of structures. To fully examine this topic, a structure was designed following the current seismic building design specifications, e.g. ASCE 7-10 and ACI 318-14, being analytically modeled, utilizing the SAP2000 software. Next, utilizing the FEMA P695 report, several near-field and far-field earthquakes were selected, and the near-field earthquake records were scaled to represent the design-level ground motions. Upon doing this, the prototype structural model, created using SAP2000, was subjected to the scaled ground motions. A Linear Time History Analysis and Pushover analysis were conducted on SAP2000 for evaluation of the structural seismic responses. On average, the structure experienced an 8% and 1% increase in story drift and absolute acceleration, respectively, when subjected to the near-field earthquake ground motions. The pushover analysis was ran to find and aid in properly defining the hinge formation in the structure when conducting the nonlinear time history analysis. A near-field ground motion is characterized by a high-energy pulse, making it unique to other earthquake ground motions. Therefore, pulse extraction methods were used in this research to estimate the maximum response of structures subjected to near-field motions. The results will be utilized in the generation of a design spectrum for the estimation of design forces for buildings subjected to NF ground motions.

Keywords: near-field, pulse, pushover, time-history

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Authors: Amit Kumar Bhandary, Prithviraj Gupta, Siddhartha Mukherjee, Mahua Ghosh Chaudhuri, Rajib Dey

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Chromite ores are primarily used for extraction of chromium, which is an expensive metal. For low grade chromite ores (containing less than 40% Cr₂O₃), the chromium extraction is not usually economically viable. India possesses huge quantities of low grade chromite reserves. This deposit can be utilized after proper physical beneficiation. Magnetic separation techniques may be useful after reduction for the beneficiation of low grade chromite ore. The sample collected from the sukinda mines is characterized by XRD which shows predominant phases like maghemite, chromite, silica, magnesia and alumina. The raw ore is crushed and ground to below 75 micrometer size. The microstructure of the ore shows that the chromite grains surrounded by a silicate matrix and porosity observed the exposed side of the chromite ore. However, this ore may be utilized in refractory applications. Chromite ores contain Cr₂O₃, FeO, Al₂O₃ and other oxides like Fe-Cr, Mg-Cr have a high tendency to form spinel compounds, which usually show high refractoriness. Initially, the low grade chromite ore (containing 34.8% Cr₂O₃) was reduced at 1200 ⁰C for 80 minutes with 30% coke fines by weight, before being subjected to magnetic separation. The reduction by coke leads to conversion of higher state of iron oxides converted to lower state of iron oxides. The pre-reduced samples are then characterized by XRD. The magnetically inert mass was then reacted with 20% MgO by weight at 1450 ⁰C for 2 hours. The resultant product was then tested for various refractoriness parameters like apparent porosity, slag resistance etc. The results were satisfactory, indicating that the resultant spinel compounds are suitable for refractory applications for elevated temperature processes.

Keywords: apparent porosity, beneficiation, low-grade chromite, refractory, spinel compounds, slag resistance

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Authors: Thanida Sujarittham, Narumon Emarat, Jintawat Tanamatayarat, Kwan Arayathanitkul, Suchai Nopparatjamjomras

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Electric field is an important fundamental concept in electrostatics. In high-school, generally Thai students have already learned about definition of electric field, electric field due to a point charge, and superposition of electric fields due to multiple-point charges. Those are the prerequisite basic knowledge students holding before entrancing universities. In the first-year university level, students will be quickly revised those basic knowledge and will be then introduced to a more complicated topic—electric field due to continuous charged distributions. We initially found that our freshman students, who were from the Faculty of Science and enrolled in the introductory physic course (SCPY 158), often seriously struggled with the basic physics concepts—superposition of electric fields and inverse square law and mathematics being relevant to this topic. These also then resulted on students’ understanding of advanced topics within the course such as Gauss's law, electric potential difference, and capacitance. Therefore, it is very important to determine students' understanding of electric field due to continuous charged distributions. The open-ended question about sketching net electric field vectors from a uniformly charged insulating rod was administered to 260 freshman science students as pre- and post-tests. All of their responses were analyzed and classified into five levels of understandings. To get deep understanding of each level, 30 students were interviewed toward their individual responses. The pre-test result found was that about 90% of students had incorrect understanding. Even after completing the lectures, there were only 26.5% of them could provide correct responses. Up to 50% had confusions and irrelevant ideas. The result implies that teaching methods in Thai high schools may be problematic. In addition for our benefit, these students’ alternative conceptions identified could be used as a guideline for developing the instructional method currently used in the course especially for teaching electrostatics.

Keywords: alternative conceptions, electric field of continuous charged distributions, inverse square law, levels of student understandings, superposition principle

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Authors: M. Feliciano, F. Maia, A. Gonçalves

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Olive oil production sector plays an important role in Portuguese economy. It had a major growth over the last decade, increasing its weight in the overall national exports. International market penetration for Mediterranean traditional products is increasingly more demanding, especially in the Northern European markets, where consumers are looking for more sustainable products. Trying to support this growing demand this study addresses olive oil production under the environmental and eco-efficiency perspectives. The analysis considers two consecutive product life cycle stages: olive trees farming; and olive oil extraction in mills. Addressing olive farming, data collection covered two different organizations: a middle-size farm (~12ha) (F1) and a large-size farm (~100ha) (F2). Results from both farms show that olive collection activities are responsible for the largest amounts of Green House Gases (GHG) emissions. In this activities, estimate for the Carbon Footprint per olive was higher in F2 (188g CO2e/kgolive) than in F1 (148g CO2e/kgolive). Considering olive oil extraction, two different mills were considered: one using a two-phase system (2P) and other with a three-phase system (3P). Results from the study of two mills show that there is a much higher use of water in 3P. Energy intensity (EI) is similar in both mills. When evaluating the GHG generated, two conditions are evaluated: a biomass neutral condition resulting on a carbon footprint higher in 3P (184g CO2e/Lolive oil) than in 2P (92g CO2e/Lolive oil); and a non-neutral biomass condition in which 2P increase its carbon footprint to 273g CO2e/Lolive oil. When addressing the carbon footprint of possible combinations among studied subsystems, results suggest that olive harvesting is the major source for GHG.

Keywords: carbon footprint, environmental indicators, farming subsystem, industrial subsystem, olive oil

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Authors: Jesus Argueta

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This study aims to explore the Business Demography Phenomena along the Central American context, through the examination of its theoretical background, and the revision of Central American corporations success stories, that will eventually guide this research towards the business Demography Key Performance Indicators, across the Central American Business Ambiance. Considering that this analysis will support the development of a Small and Medium Business Observatory over the Honduran commercial landscapes, as platform for the reinforcement of this global topic.

Keywords: business demography, economic dynamism, small, medium and large enterprises, corporate demography

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Authors: Sang-Keun Moon, Hong-Rok Lim, Jin-O Kim

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This paper presents a Power Quality (PQ) modeling and filtering processes for the distribution system disturbances using recognition learning methods. Typical PQ waveforms with mathematical applications and gathered field data are applied to the proposed models. The objective of this paper is analyzing PQ data with respect to monitoring, discriminating, and evaluating the waveform of power disturbances to ensure the system preventative system failure protections and complex system problem estimations. Examined signal filtering techniques are used for the field waveform noises and feature extractions. Using extraction and learning classification techniques, the efficiency was verified for the recognition of the PQ disturbances with focusing on interactive modeling methods in this paper. The waveform of selected 8 disturbances is modeled with randomized parameters of IEEE 1159 PQ ranges. The range, parameters, and weights are updated regarding field waveform obtained. Along with voltages, currents have same process to obtain the waveform features as the voltage apart from some of ratings and filters. Changing loads are causing the distortion in the voltage waveform due to the drawing of the different patterns of current variation. In the conclusion, PQ disturbances in the voltage and current waveforms indicate different types of patterns of variations and disturbance, and a modified technique based on the symmetrical components in time domain was proposed in this paper for the PQ disturbances detection and then classification. Our method is based on the fact that obtained waveforms from suggested trigger conditions contain potential information for abnormality detections. The extracted features are sequentially applied to estimation and recognition learning modules for further studies.

Keywords: power quality recognition, PQ modeling, waveform feature extraction, disturbance trigger condition, PQ signal filtering

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Authors: Chahrazed Zouaoui

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In recent years, the volume of geospatial information is increasing due to the evolution of communication technologies and information, this information is presented often by geographic information systems (GIS) and stored on of spatial databases (BDS). The classical data mining revealed a weakness in knowledge extraction at these enormous amounts of data due to the particularity of these spatial entities, which are characterized by the interdependence between them (1st law of geography). This gave rise to spatial data mining. Spatial data mining is a process of analyzing geographic data, which allows the extraction of knowledge and spatial relationships from geospatial data, including methods of this process we distinguish the monothematic and thematic, geo- Clustering is one of the main tasks of spatial data mining, which is registered in the part of the monothematic method. It includes geo-spatial entities similar in the same class and it affects more dissimilar to the different classes. In other words, maximize intra-class similarity and minimize inter similarity classes. Taking account of the particularity of geo-spatial data. Two approaches to geo-clustering exist, the dynamic processing of data involves applying algorithms designed for the direct treatment of spatial data, and the approach based on the spatial data pre-processing, which consists of applying clustering algorithms classic pre-processed data (by integration of spatial relationships). This approach (based on pre-treatment) is quite complex in different cases, so the search for approximate solutions involves the use of approximation algorithms, including the algorithms we are interested in dedicated approaches (clustering methods for partitioning and methods for density) and approaching bees (biomimetic approach), our study is proposed to design very significant to this problem, using different algorithms for automatically detecting geo-spatial neighborhood in order to implement the method of geo- clustering by pre-treatment, and the application of the bees algorithm to this problem for the first time in the field of geo-spatial.

Keywords: mining, GIS, geo-clustering, neighborhood

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Authors: Marinos Xagoraris, Elisavet Lazarou, Eleftherios Alissandrakis, Christos S. Pappas, Petros A. Tarantilis

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Strawberry tree (Arbutus unedo L.) and autumn heather (Erica manipuliflora Salisb.) are important beekeeping plants of Greece. Six monofloral honeys (four strawberry tree, two autumn heather) were analyzed by means of Solid Phase Micro-Extraction (SPME, 60 min, 60 oC) followed by Gas Chromatography coupled to Mass Spectrometry (GC-MS) for the purpose of assessing the botanical origin. A Divinylbenzene/Carboxen/Polydimethylsiloxane (DVB/CAR/PDMS) fiber was employed, and benzophenone was used as internal standard. The volatile compounds with higher concentration (μg/ g of honey expressed as benzophenone) from strawberry tree honey samples, were α-isophorone (2.50-8.12); 3,4,5-trimethyl-phenol (0.20-4.62); 2-hydroxy-isophorone (0.06-0.53); 4-oxoisophorone (0.38-0.46); and β-isophorone (0.02-0.43). Regarding heather honey samples, the most abundant compounds were 1-methoxy-4-propyl-benzene (1.22-1.40); p-anisaldehyde (0.97-1.28); p-anisic acid (0.35-0.58); 2-furaldehyde (0.52-0.57); and benzaldehyde (0.41-0.56). Norisoprenoids are potent floral markers for strawberry-tree honey. β-isophorone is found exclusively in the volatile fraction of this type of honey, while also α-isophorone, 4-oxoisophorone and 2-hydroxy-isophorone could be considered as additional marker compounds. The analysis of autumn heather honey revealed that phenolic compounds are the most abundant and p-anisaldehyde; 1-methoxy-4-propyl-benzene; and p-anisic acid could serve as potent marker compounds. In conclusion, marker compounds for the determination of the botanical origin for these honeys could be identified as several norisoprenoids and phenolic components were found exclusively or in higher concentrations compared to common Greek honey varieties.

Keywords: SPME/GC-MS, volatile compounds, heather honey, strawberry tree honey

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Authors: Abdirahim Mohamed, Sarita Rana Chhetri, Michael Sleath, Nadia Saleem

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Rationale: Internet usage has been very much integrated into our daily lives. Internet usage within a neurodevelopmental disorder population is also on the increase. Nevertheless, there is very little empirical research on how this population virtually protect themselves; along with how their parents can keep them safe online. This topic was an ever-growing concern to the parents within our services and in many cases would add to the stresses and mental health of parents. This ignited an idea within our team to conduct research to explore the perceived online risks within this population and how they keep themselves safe. In conjunction, we also explored how parents and caregivers monitor and safeguard their young people to the potential threats online. Our hypothesis was that the perceived risks will heavily outnumber the safeguarding measures implemented by this population. Method: Within the Coventry and Warwickshire NHS Partnership Trust Child and Adolescent Mental Health Service (CAMHS), we distributed qualitative questionnaires to all the clinical bases (N=80). Questions explored topics such as daily internet usage, safeguarding measures, and perceived threats. The researchers requested for all CAMHS clinicians to identify participants. Participants in this study were accessing CAMHS for neurodevelopmental specific interventions. Results: The data were analysed using both Excel and SPSS. Within SPSS, a MANOVA was conducted and found a significant difference between safeguarding measures and perceived online risks within responses (p ≤ 0.5). This supports our hypothesis that participants in this population are well versed in the safeguarding issues of the internet; however, struggle to implement appropriate preventative measures. Data were also screened using Excel and found that all parents and carers stated they 'monitored their child’s internet use'. Conclusion: Data suggest that parents/carers may require more specific intervention to equip them with preventative measures due to the clear discrepancy between perceived risks and safeguarding measures. More research may also need to be conducted around this area to determine appropriate methodology to explore this topic further.

Keywords: Internet, health , how safe are we , internet health check

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Authors: Tsitsi Nyukurayi Muparari, Walter Timo De Vries, Jaap Zevenbergen

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The nature of Land administration accommodates diversity in terms of both spatial data handling activities and the expertise involved, which supposedly aims to satisfy the unpredictable demands of land data and the diverse demands of the customers arising from the land. However, it is known that strategic decisions of restructuring are in most cases repelled in favour of complex structures that strive to accommodate professional diversity and diverse roles in the field of Land administration. Yet despite of this widely accepted knowledge, there is scanty theoretical knowledge concerning the psychological methodologies that can extract the deeper perceptions from the diverse spatial expertise in order to explain the invisible control arm of the polarised reception of the ideas of change. This paper evaluates Q methodology in the context of a cadastre and land registry merger (under one agency) using the Swedish cadastral system as a case study. Precisely, the aim of this paper is to evaluate the effectiveness of Q methodology towards modelling the diverse psychological perceptions of spatial professionals who are in a widely contested decision of merging the cadastre and land registry components of Land administration using the Swedish cadastral system as a case study. An empirical approach that is prescribed by Q methodology starts with the concourse development, followed by the design of statements and q sort instrument, selection of the participants, the q-sorting exercise, factor extraction by PQMethod and finally narrative development by logic of abduction. The paper uses 36 statements developed from a dominant competing value theory that stands out on its reliability and validity, purposively selects 19 participants to do the Qsorting exercise, proceeds with factor extraction from the diversity using varimax rotation and judgemental rotation provided by PQMethod and effect the narrative construction using the logic abduction. The findings from the diverse perceptions from cadastral professionals in the merger decision of land registry and cadastre components in Sweden’s mapping agency (Lantmäteriet) shows that focus is rather inclined on the perfection of the relationship between the legal expertise and technical spatial expertise. There is much emphasis on tradition, loyalty and communication attributes which concern the organisation’s internal environment rather than innovation and market attributes that reveals customer behavior and needs arising from the changing humankind-land needs. It can be concluded that Q methodology offers effective tools that pursues a psychological approach for the evaluation and gradations of the decisions of strategic change through extracting the local perceptions of spatial expertise.

Keywords: cadastre, factor extraction, land administration merger, land registry, q-methodology, rotation

Procedia PDF Downloads 175

Authors: N. Szczepanska, B. Kudlak, G. Yotova, S. Tsakovski, J. Namiesnik

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In the scientific literature related to the widely understood issue of packaging materials designed to have contact with food (food contact materials), there is much information on raw materials used for their production, as well as their physiochemical properties, types, and parameters. However, not much attention is given to the issues concerning migration of toxic substances from packaging and its actual influence on the health of the final consumer, even though health protection and food safety are the priority tasks. The goal of this study was to estimate the impact of particular foodstuff packaging type, food production, and storage conditions on the degree of leaching of potentially toxic compounds and endocrine disruptors to foodstuffs using the acute toxicity test Microtox and XenoScreen YES YAS assay. The selected foodstuff packaging materials were metal cans used for fish storage and tetrapak. Five stimulants respectful to specific kinds of food were chosen in order to assess global migration: distilled water for aqueous foods with a pH above 4.5; acetic acid at 3% in distilled water for acidic aqueous food with pH below 4.5; ethanol at 5% for any food that may contain alcohol; dimethyl sulfoxide (DMSO) and artificial saliva were used in regard to the possibility of using it as an simulation medium. For each packaging three independent variables (temperature and contact time) factorial design simulant was performed. Xenobiotics migration from epoxy resins was studied at three different temperatures (25°C, 65°C, and 121°C) and extraction time of 12h, 48h and 2 weeks. Such experimental design leads to 9 experiments for each food simulant as conditions for each experiment are obtained by combination of temperature and contact time levels. Each experiment was run in triplicate for acute toxicity and in duplicate for estrogen disruption potential determination. Multi-factor analysis of variation (MANOVA) was used to evaluate the effects of the three main factors solvent, temperature (temperature regime for cup), contact time and their interactions on the respected dependent variable (acute toxicity or estrogen disruption potential). From all stimulants studied the most toxic were can and tetrapak lining acetic acid extracts that are indication for significant migration of toxic compounds. This migration increased with increase of contact time and temperature and justified the hypothesis that food products with low pH values cause significant damage internal resin filling. Can lining extracts of all simulation medias excluding distilled water and artificial saliva proved to contain androgen agonists even at 25°C and extraction time of 12h. For tetrapak extracts significant endocrine potential for acetic acid, DMSO and saliva were detected.

Keywords: food packaging, extraction, migration, toxicity, biotest

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Authors: Volkmar Nolting

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Fatigue crack growth prediction has become an important topic in both engineering and non-destructive evaluation. Crack propagation is influenced by the mechanical properties of the material and is conveniently modelled by the Paris-Erdogan equation. The critical crack size and the total number of load cycles are calculated. From a Larson-Miller plot the maximum operational temperature can for a given stress level be determined so that failure does not occur within a given time interval t. The study is used to determine a reasonable inspection cycle and thus enhances operational safety and reduces costs.

Keywords: fracturemechanics, crack growth prediction, lifetime of a component, structural health monitoring

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Authors: V. Veeraprathap, G. S. Harish, G. Narendra Kumar

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Uncontrolled growth of abnormal cells in the lung in the form of tumor can be either benign (non-cancerous) or malignant (cancerous). Patients with Lung Cancer (LC) have an average of five years life span expectancy provided diagnosis, detection and prediction, which reduces many treatment options to risk of invasive surgery increasing survival rate. Computed Tomography (CT), Positron Emission Tomography (PET), and Magnetic Resonance Imaging (MRI) for earlier detection of cancer are common. Gaussian filter along with median filter used for smoothing and noise removal, Histogram Equalization (HE) for image enhancement gives the best results without inviting further opinions. Lung cavities are extracted and the background portion other than two lung cavities is completely removed with right and left lungs segmented separately. Region properties measurements area, perimeter, diameter, centroid and eccentricity measured for the tumor segmented image, while texture is characterized by Gray-Level Co-occurrence Matrix (GLCM) functions, feature extraction provides Region of Interest (ROI) given as input to classifier. Two levels of classifications, K-Nearest Neighbor (KNN) is used for determining patient condition as normal or abnormal, while Artificial Neural Networks (ANN) is used for identifying the cancer stage is employed. Discrete Wavelet Transform (DWT) algorithm is used for the main feature extraction leading to best efficiency. The developed technology finds encouraging results for real time information and on line detection for future research.

Keywords: artificial neural networks, ANN, discrete wavelet transform, DWT, gray-level co-occurrence matrix, GLCM, k-nearest neighbor, KNN, region of interest, ROI

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Authors: Sangita Pokhrel, Nalinda Somasiri, Rebecca Jeyavadhanam, Swathi Ganesan

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Tourism is a booming industry with huge future potential for global wealth and employment. There are countless data generated over social media sites every day, creating numerous opportunities to bring more insights to decision-makers. The integration of Big Data Technology into the tourism industry will allow companies to conclude where their customers have been and what they like. This information can then be used by businesses, such as those in charge of managing visitor centers or hotels, etc., and the tourist can get a clear idea of places before visiting. The technical perspective of natural language is processed by analysing the sentiment features of online reviews from tourists, and we then supply an enhanced long short-term memory (LSTM) framework for sentiment feature extraction of travel reviews. We have constructed a web review database using a crawler and web scraping technique for experimental validation to evaluate the effectiveness of our methodology. The text form of sentences was first classified through Vader and Roberta model to get the polarity of the reviews. In this paper, we have conducted study methods for feature extraction, such as Count Vectorization and TFIDF Vectorization, and implemented Convolutional Neural Network (CNN) classifier algorithm for the sentiment analysis to decide the tourist’s attitude towards the destinations is positive, negative, or simply neutral based on the review text that they posted online. The results demonstrated that from the CNN algorithm, after pre-processing and cleaning the dataset, we received an accuracy of 96.12% for the positive and negative sentiment analysis.

Keywords: counter vectorization, convolutional neural network, crawler, data technology, long short-term memory, web scraping, sentiment analysis

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Authors: S. McLean, J. A. Scott

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The research topic is focusing on improving sustainable operation through recovery and reuse of waste heat in process water streams, an area in the mining industry that is often overlooked. There are significant advantages to the application of this topic, including economic and environmental benefits. The smelting process in the mining industry presents an opportunity to recover waste heat and apply it to alternative uses, thereby enhancing the overall process. This applied research has been conducted at the Sudbury Integrated Nickel Operations smelter site, in particular on the water cooling towers. The aim was to determine and optimize methods for appropriate recovery and subsequent upgrading of thermally low-grade heat lost from the water cooling towers in a manner that makes it useful for repurposing in applications, such as within an acid plant. This would be valuable to mining companies as it would be an opportunity to reduce the cost of the process, as well as decrease environmental impact and primary fuel usage. The waste heat from the cooling towers needs to be upgraded before it can be beneficially applied, as lower temperatures result in a decrease of the number of potential applications. Temperature and flow rate data were collected from the water cooling towers at an acid plant over two years. The research includes process control strategies and the development of a model capable of determining if the proposed heat recovery technique is economically viable, as well as assessing any environmental impact with the reduction in net energy consumption by the process. Therefore, comprehensive cost and impact analyses are carried out to determine the best area of application for the recovered waste heat. This method will allow engineers to easily identify the value of thermal resources available to them and determine if a full feasibility study should be carried out. The rapid scoping model developed will be applicable to any site that generates large amounts of waste heat. Results show that heat pumps are an economically viable solution for this application, allowing for reduced cost and CO₂ emissions.

Keywords: environment, heat recovery, mining engineering, sustainability

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Authors: Prashanth Pillai, Purnaprajna Mangsuli

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Oil exploration and production companies invest considerable time and efforts to extract essential well attributes (like well status, surface, and target coordinates, wellbore depths, event timelines, etc.) from unstructured data sources like technical reports, which are often non-standardized, multimodal, and highly domain-specific by nature. It is also important to consider the context when extracting attribute values from reports that contain information on multiple wells/wellbores. Moreover, semantically similar information may often be depicted in different data syntax representations across multiple pages and document sources. We propose a hierarchical multi-source fact extraction workflow based on a deep learning framework to extract essential well attributes at scale. An information retrieval module based on the transformer architecture was used to rank relevant pages in a document source utilizing the page image embeddings and semantic text embeddings. A question answering framework utilizingLayoutLM transformer was used to extract attribute-value pairs incorporating the text semantics and layout information from top relevant pages in a document. To better handle context while dealing with multi-well reports, we incorporate a dynamic query generation module to resolve ambiguities. The extracted attribute information from various pages and documents are standardized to a common representation using a parser module to facilitate information comparison and aggregation. Finally, we use a probabilistic approach to fuse information extracted from multiple sources into a coherent well record. The applicability of the proposed approach and related performance was studied on several real-life well technical reports.

Keywords: natural language processing, deep learning, transformers, information retrieval

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Authors: P. Karthick, K. Mahesh

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Video has become an increasingly significant component of our digital everyday contact. With the advancement of greater contents and shows of the resolution, its significant volume poses serious obstacles to the objective of receiving, distributing, compressing, and revealing video content of high quality. In this paper, we propose the primary beginning to complete a deep video compression model that jointly upgrades all video compression components. The video compression method involves splitting the video into frames, comparing the images using convolutional neural networks (CNN) to remove duplicates, repeating the single image instead of the duplicate images by recognizing and detecting minute changes using generative adversarial network (GAN) and recorded with long short-term memory (LSTM). Instead of the complete image, the small changes generated using GAN are substituted, which helps in frame level compression. Pixel wise comparison is performed using K-nearest neighbours (KNN) over the frame, clustered with K-means, and singular value decomposition (SVD) is applied for each and every frame in the video for all three color channels [Red, Green, Blue] to decrease the dimension of the utility matrix [R, G, B] by extracting its latent factors. Video frames are packed with parameters with the aid of a codec and converted to video format, and the results are compared with the original video. Repeated experiments on several videos with different sizes, duration, frames per second (FPS), and quality results demonstrate a significant resampling rate. On average, the result produced had approximately a 10% deviation in quality and more than 50% in size when compared with the original video.

Keywords: video compression, K-means clustering, convolutional neural network, generative adversarial network, singular value decomposition, pixel visualization, stochastic gradient descent, frame per second extraction, RGB channel extraction, self-detection and deciding system

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Authors: Hozaifa Zaki, Ghada Soliman

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In this paper, we introduced an approach for Automated Dotted Arabic Expiration Date Extraction using Optimized Convolutional Autoencoder (ARABEX) with bidirectional LSTM. This approach is used for translating the Arabic dot-matrix expiration dates into their corresponding filled-in dates. A custom lightweight Convolutional Recurrent Neural Network (CRNN) model is then employed to extract the expiration dates. Due to the lack of available dataset images for the Arabic dot-matrix expiration date, we generated synthetic images by creating an Arabic dot-matrix True Type Font (TTF) matrix to address this limitation. Our model was trained on a realistic synthetic dataset of 3287 images, covering the period from 2019 to 2027, represented in the format of yyyy/mm/dd. We then trained our custom CRNN model using the generated synthetic images to assess the performance of our model (ARABEX) by extracting expiration dates from the translated images. Our proposed approach achieved an accuracy of 99.4% on the test dataset of 658 images, while also achieving a Structural Similarity Index (SSIM) of 0.46 for image translation on our dataset. The ARABEX approach demonstrates its ability to be applied to various downstream learning tasks, including image translation and reconstruction. Moreover, this pipeline (ARABEX+CRNN) can be seamlessly integrated into automated sorting systems to extract expiry dates and sort products accordingly during the manufacturing stage. By eliminating the need for manual entry of expiration dates, which can be time-consuming and inefficient for merchants, our approach offers significant results in terms of efficiency and accuracy for Arabic dot-matrix expiration date recognition.

Keywords: computer vision, deep learning, image processing, character recognition

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Authors: O. Fatemi

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Considering growing building construction industry in developing countries and sustainable development concept, as well as the importance of taking care of the future generations, codifying buildings scoring system based on environmental criteria, has always been a subject for discussion. The existing systems cannot be used for all the regions due to several reasons, including but not limited to variety in regional variables. In this article, the most important common LEED (Leadership in Energy and Environmental Design) and BREEAM (Building Research Establishment Environmental Assessment Method) common and Global environmental scoring systems, used in UK, USA, and Japan, respectively, have been discussed and compared with a special focus on CASBEE (Comprehensive Assessment System for Built Environment Efficiency), to credit assigning field (weighing and scores systems) as well as sustainable development criteria in each system. Then, converging and distinct fields of the foregoing systems are examined considering National Iranian Building Code. Furthermore, the common credits in the said systems not mentioned in National Iranian Building Code have been identified. These credits, which are generally included in well-known fundamental principles in sustainable development, may be considered as offered options for the Iranian building environmental scoring system. It is suggested that one of the globally and commonly accepted systems is chosen considering national priorities in order to offer an effective method for buildings environmental scoring, and then, a part of credits is added and/or removed, or a certain credit score is changed, and eventually, a new scoring system with a new title is developed for the country. Evidently, building construction industry highly affects the environment, economy, efficiency, and health of the relevant occupants. Considering the growing trend of cities and construction, achieving building scoring systems based on environmental criteria has always been a matter of discussion. The existing systems cannot be used for all the regions due to several reasons, including but not limited to variety in regional variables.

Keywords: scoring system, sustainability assessment, water efficiency, national Iranian building code

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Authors: Getaneh Berie Tarekegn

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A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. It also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Santos Andressa M. N.

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The research brings reflections on the importance of Instagram for the clothing trade, aiming to analyze the use of this social network as a sales tool by small companies in the fashion/clothing sector in Boqueirão-PI. Thus, field research was carried out, with the application of questionnaires, to raise and analyze data related to the topic. Thus, it is believed that Instagram positively influences the dissemination, visibility, reach and profitability of companies in Boqueirão do Piauí. The survey had a low number of companies due to the lack of availability of the owners during the COVID-19 pandemic.

Keywords: Instagram, sales, fashion, marketing

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Authors: A. Knezović

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21st century has transformed the labor market landscape in a way of posing new and different demands on university graduates as well as university lecturers, which means that the knowledge and academic skills students acquire in the course of their studies should be applicable and transferable from the higher education context to their future professional careers. Given the context of the Languages for Specific Purposes (LSP) classroom, the teachers’ objective is not only to teach the language itself, but also to prepare students to use that language as a medium to develop generic skills and competences. These include media and information literacy, critical and creative thinking, problem-solving and analytical skills, effective written and oral communication, as well as collaborative work and social skills, all of which are necessary to make university graduates more competitive in everyday professional environments. On the other hand, due to limitations of time and large numbers of students in classes, the frequently topic-centered syllabus of LSP courses places considerable focus on acquiring the subject matter and specialist vocabulary instead of sufficient development of skills and competences required by students’ prospective employers. This paper intends to explore some of those issues as viewed both by LSP lecturers and by business professionals in their respective surveys. The surveys were conducted among more than 50 LSP lecturers at higher education institutions in Croatia, more than 40 HR professionals and more than 60 university graduates with degrees in economics and/or business working in management positions in mainly large and medium-sized companies in Croatia. Various elements of LSP course content have been taken into consideration in this research, including reading and listening comprehension of specialist texts, acquisition of specialist vocabulary and grammatical structures, as well as presentation and negotiation skills. The ability to hold meetings, conduct business correspondence, write reports, academic texts, case studies and take part in debates were also taken into consideration, as well as informal business communication, business etiquette and core courses delivered in a foreign language. The results of the surveys conducted among LSP lecturers will be analyzed with reference to what extent those elements are included in their courses and how consistently and thoroughly they are evaluated according to their course requirements. Their opinions will be compared to the results of the surveys conducted among professionals from a range of industries in Croatia so as to examine how useful and important they perceive the same elements of the LSP course content in their working environments. Such comparative analysis will thus show to what extent the syllabi of LSP courses meet the demands of the employment market when it comes to the students’ language skills and competences, as well as transferable skills. Finally, the findings will also be compared to the observations based on practical teaching experience and the relevant sources that have been used in this research. In conclusion, the ideas and observations in this paper are merely open-ended questions that do not have conclusive answers, but might prompt LSP lecturers to re-evaluate the content and objectives of their course syllabi.

Keywords: languages for specific purposes (LSP), language skills, topic-centred syllabus, transferable skills

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Authors: Hien Thi Dieu Truong, Mahmoud Al-Sarayreh, Pullanagari Reddy, Marlon M. Reis, Richard Archer

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New Zealand mānuka honey is a honeybee product derived mainly from Leptospermum scoparium nectar. The potent antibacterial activity of mānuka honey derives principally from methylglyoxal (MGO), in addition to the hydrogen peroxide and other lesser activities present in all honey. MGO is formed from dihydroxyacetone (DHA) unique to L. scoparium nectar. Mānuka honey also has an idiosyncratic phenolic profile that is useful as a chemical maker. Authentic mānuka honey is highly valuable, but almost all honey is formed from natural mixtures of nectars harvested by a hive over a time period. Once diluted by other nectars, mānuka honey irrevocably loses value. We aimed to apply hyperspectral imaging to honey frames before bulk extraction to minimise the dilution of genuine mānuka by other honey and ensure authenticity at the source. This technology is non-destructive and suitable for an industrial setting. Chemometrics using linear Partial Least Squares (PLS) and Support Vector Machine (SVM) showed limited efficacy in interpreting chemical footprints due to large non-linear relationships between predictor and predictand in a large sample set, likely due to honey quality variability across geographic regions. Therefore, an advanced modelling approach, one-dimensional convolutional neural networks (1D-CNN), was investigated for analysing hyperspectral data for extraction of biochemical information from honey. The 1D-CNN model showed superior prediction of honey quality (R² = 0.73, RMSE = 2.346, RPD= 2.56) to PLS (R² = 0.66, RMSE = 2.607, RPD= 1.91) and SVM (R² = 0.67, RMSE = 2.559, RPD=1.98). Classification of mono-floral manuka honey from multi-floral and non-manuka honey exceeded 90% accuracy for all models tried. Overall, this study reveals the potential of HSI and deep learning modelling for automating the evaluation of honey quality in frames.

Keywords: mānuka honey, quality, purity, potency, deep learning, 1D-CNN, chemometrics

Procedia PDF Downloads 117

Authors: Marta Merkl

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The ongoing project what the paper will present is about how the author introduces chefs to the history of art through a selected piece of art. The author is originally an art historian, but since 2019 she has been working on her PhD research topic related to designing dining experiences in the restaurant context, including the role of sensory experiences and storytelling. Due to a scholarship, she can participate in the re-design of a fine dining restaurant called Onyx in Budapest, which was awarded two Michelin stars before the pandemic caused by COVID-19. The management of the restaurant wants to broaden the chefs' horizons and develop their creativity by introducing them to each chapter of the visual arts. There is a kind of polyphony in the mass of information about what should a chef, a food designer, or anybody who make food in everyday basis use as a source of inspiration for inventing and preparing new dishes: nostalgia, raw material, cookbooks, etc. In today's world of fine dining, nature is the main inspiration for outstanding achievements, as exemplified by the Slovenian restaurant Hiša Franko** and its chef Ana Roš. The starting point for the project and the research was the idea of using art history as an inspiration for gastronomy. The research relies on data collection via interviews, ethnography, and autoethnography. In this case, the reflective introspection of the researcher is also relevant because the researcher is an important part of the process (GOULD, 1995). The paper overviews the findings of the autoethnography literature relevant to our topic. In the literature review, it will be also pointed out that sustainability, eating as an experience, and the world of art can be linked. As ERDMANN and co-authors (1999) argues that the health dimension of sustainability has a component called 'joy of eating,' which implies strong ties to the experiential nature of eating. Therefore, it is worth to compare with PINE and GILMORE's (1998) theory of experience economy and with CSÍKSZENTMIHÁLYI's (1999) concept of flow, which give examples of gastronomy and art. The aim of the research is to map experiences of the pilot project, the discourse between the art world and the gastronomy actors. Another noteworthy aspect is whether the chefs are willing to use art history as an inspiration.

Keywords: art history, autoethnography, chef, education, experience, food preparation, inspiration, sustainability

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Authors: Concetta Papapicco

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The spreading of new Coronavirus (COVID-19) in addition to becoming a global phenomenon, following the declaration of a pandemic state, has generated excessive access to information, sometimes not thoroughly screened, which makes it difficult to navigate a given topic because of the difficulty of finding reliable sources. As a result, there is a high level of contagion, understood as the spread of the virus, but also as the spread of information in a viral and harmful way, which prompted the World Health Organization to coin the term Infodemia to give 'a name' the phenomenon of excessive information. With neologism 'Infodemia', the World Health Organization (OMS) wanted, in these days when fear of the coronavirus is raging, point out that perhaps the greatest danger of global society in the age of social media. This phenomenon is the distortion of reality in the rumble of echoes and comments of the global community on real or often invented facts. The general purpose of the exploratory study is to investigate how the coronavirus situation is described from journalistic communication. Starting from La Repubblica online, as a reference journalistic magazine, as a specific objective, the research aims to understand the way in which journalistic communication describes the phenomenon of the COVID-19 virus spread, the spread of contagion and restrictive measures of social distancing in the Italian context. The study starts from the hypothesis that if the circulation of information helps to create a social representation of the phenomenon, the excessive accessibility to sources of information (Infodemia) can be modulated by the 'how' the phenomenon is described by the journalists. The methodology proposed, in fact, in the exploratory study is a quanti-qualitative (mixed) method. A Content Analysis with the SketchEngine software is carried out first. In support of the Content Analysis, a Diatextual Analysis was carried out. The Diatextual Analysis is a qualitative analysis useful to detect in the analyzed texts, that is the online articles of La Repubblica on the topic of coronavirus, Subjectivity, Argomentativity, and Mode. The research focuses mainly on 'Mode' or 'How' are the events related to coronavirus in the online articles of La Repubblica about COVID-19 phenomenon. The results show the presence of the contrast vision about COVID-19 situation in Italy.

Keywords: coronavirus, Italian infodemia, La Republica online, mix method

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Authors: O. E. Akay, E. Güzel, M. T. Özcan

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The pepper has quite a rich variety. The development of a single harvesting machine for all kinds of peppers is a difficult research topic. By development of harvesting mechanisms, we could be able to facilitate the pepper harvesting problems. In this study, an experimental harvesting machine was designed for chili pepper. Four-bar mechanism was used for the design of the prototype harvesting machine. At the result of harvest trials, 80% of peppers were harvested and 8% foreign materials were collected. These results have provided some tips on how to apply to large-scale pepper Four-bar mechanism of the harvest machine.

Keywords: kinematic simulation, four bar linkage, harvest mechanization, pepper harvest

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Authors: Kenichi Hirota, Jifeng Wang, Sadao Araki, Koji Endo, Hideki Yamamoto

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Zirconium (Zr) has been used as a fuel cladding tube for nuclear reactors, because of the excellent corrosion resistance and the low adsorptive material for neutron. Generally speaking, the natural resource of Zr is often containing Hf that has similar properties. The content of Hf in the Zr resources is about 2~4 wt%. In the industrial use, the content of Hf in Zr resources should be lower than the 100 ppm. However, the separation of Zr and Hf is not so easy, because of similar chemical and physical properties such as melting point, boiling point and things. Solvent extraction method has been applied for the separation of Zr and Hf from Zr natural resources. This method can separate Hf with high efficiency (Hf < 100ppm), however, it needs much amount of organic solvents for solvent extraction and the cost of its disposal treatment is high. Therefore, we attached attention for the fractional crystallization. This separation method depends on the solubility difference of Zr and Hf in the solvent. In this work, hexafluorozirconate (hafnate) (K2Zr(Hf)F6) was used as model compound. Solubility of K2ZrF6 in water showed lower than that of K2HfF6. By repeating of this treatment, it is possible to purify Zr, practically. In this case, 16-18 times of recrystallization stages were needed for its high purification. The improvement of the crystallization process was carried out in this work. Water, hydrofluoric acid (HF) and hydrofluoric acid (HF) +hydrochloric acid (HCl) mixture were chosen as solvent for dissolution of Zr and Hf. In the experiment, 10g of K2ZrF6 was added to each solvent of 100mL. Each solution was heated for 1 hour at 353K. After 1h of this operation, they were cooled down till 293K, and were held for 5 hours at 273K. Concentration of Zr or Hf was measured using ICP analysis. It was found that Hf was separated from Zr-Hf mixed compound with high efficiency, when HF-HCl solution was used for solvent of crystallization. From the comparison of the particle size of each crystal by SEM, it was confirmed that the particle diameter of the crystal showed smaller size with decreasing of Hf content. This paper concerned with purification of Zr from Zr-Hf mixture using crystallization method.

Keywords: crystallization, zirconium, hafnium, separation

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Authors: Wahid Terro, Miray Terro, Omar Zain

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Context: The immediate placement of dental implants into fresh, non-infected sockets is an accepted successful technique, while the placement of these implants into pathological Dento-alveolar sockets is still a controversial issue. Aims: This clinical case-serious study aimed to report, retrospectively, the survival rate of immediate dental implants placed immediately after extraction of teeth with infected Dento-alveolar sockets in the maxilla and mandible during the osseointegration period (3 months). Material and Methods: A retrospective analysis was made of the clinical and radiographic findings corresponding to 15 consecutive patients (7 women and 8 men, between the ages of 21 and 59 years) with a mean age of 44.14 years (SD= 9.28). A total of 36 locking-taper Bicon dental implants (hydroxyapatite, HA-coated) were immediately placed into infected fresh extraction sockets, including radicular cysts, chronic periapical lesions, and sub-acute periodontal and endodontic infections using a flap or flapless surgery. Retrospective data on implant position, implant size, pathological condition, and baseline radiographs were obtained from patient records. Clinical and radiographic analyses were performed to evaluate the treatment outcome. Data were considered using descriptive statistics. Results: All the implants (N=36) except two achieved osseointegration in 3 months follow-up. This reflects a 94.44% success rate within this small study group and a 5.55% failure rate. Complications were related to the reasons for tooth loss. Conclusions: This retrospective clinical case-series study showed the possibility that immediate dental implant placement is successful in infected extraction sockets.

Keywords: implant, socket, infected, osteointegration

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Authors: Aikaterini Amanatidou

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We describe the case of a 20-year-old female patient diagnosed with Ehlers-Danlos Syndrome (EDS) who was scheduled to undergo a wisdom teeth extraction in outpatient surgery. EDS is a hereditary connective tissue disorder characterized by joint hypermobility, skin hyper-extensibility, and vascular and soft tissue fragility. There are six subtypes of Ehlers-Danlos, and in our case, the patient had EDS hyper-mobility (HT) type disorder. One important clinical feature of this syndrome is chronic pain, which is often poorly understood and treated. Our patient had a long history of articular and lumbar pain when she was diagnosed. She was prescribed analgesic treatment for acute and neuropathic pain and had multiple sessions of psychotherapy and physiotherapy to ease the pain. Unfortunately, her extensive medical history was underrated by our anesthetic team, and no further measures were taken for the operation. Despite an uneventful intra-operative phase, the patient experienced several episodes of hyperalgesia during the immediate post-operative care. Management of pain was challenging for the anesthetic team: initial opioid treatment had only a temporary effect and a paradoxical reaction after a while. Final pain relief was eventually obtained with psycho-physiologic treatment, high doses of ketamine, and patient-controlled analgesia infusion of morphine-ketamine-dehydrobenzperidol. We suspected an episode of Opioid-Induced hyperalgesia. This case report supports the hypothesis that anti-hyperalgesics such as ketamine as well as lidocaine, and dexmedetomidine should be considered intra-operatively to avoid opioid-induced hyperalgesia and may be an alternative solution to manage complex chronic pain like others in neuropathic pain syndromes.

Keywords: Ehlers-Danlos, post-operative management, hyperalgesia, opioid-induced hyperalgesia, rare disease

Procedia PDF Downloads 74

Authors: Hezha Hewa, Taher Sur

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Nowadays, child affairs is a matter of both national and international interests. This issue is regarded a vital topic for various scientific fields across ages, and for all the communities without exception. However, the nature of child caring may vary due to the verities in science perspectives. So, considering child's affairs from different perspectives is helpful to have a complementary image about this matter. The purpose behind selecting this topic is to keep a balance between the victim on the one hand, and the guardian and the offender on the other hand, (i.e.) to avoid any kind of excessiveness either in the protection of the child and its rights not in the punishment of the offender. This is achieved through considering various legal materials in the Iraqi legislation and in the comparative legislations that are concerned with the child's issue and the extent to which the child makes use of these rights. The scope of this study involves the crimes that are considered as aggressions against the child's right to life, and the crimes that are dangerous to their physical and psychological safety. So, this study comprehensively considers the intentional murder of child, child murder to avoid disgrace, child kidnapping, child abandonment, physical abuse for the sake of punishment or not, child circumcision, verbal violence, and abstaining from leaving a child with a person who has the right of custody. This study ends with the most significant concluding points that have been derived throughout this study, which are: Unlike the Iraqi legislation, the Egyptian legislation defines the child in the Article 2 of the Child Law No. 12 of 1996 amended by the Law No. 126 of 2008 that the child is a person who does not exceed 18 years of age. Some legislation does not provide special criminal protection for child intentional murder, as in the Iraqi and the Egyptian legislation. However, some others have provided special criminal protection for a child, as in French and Syrian legislations. Child kidnapping is regarded as one of the most dangerous crimes that affects the child and the family as well, as it may expose the child's life to danger or to death. The most significant recommendations from the researcher are: The Iraqi legislation is recommended to take the necessary measures to establish a particular legislation for the child by including all the legal provisions that are associated with this weak creature, and make use of the Egyptian legislator’s experience as a pioneer in this respect. Both the Iraqi legislation and the Egyptian legislation are recommended to enact special laws to protect a child from the crimes of intentional murder, as the crime of child murder is currently subjected to the same provisions consider for adult murder.

Keywords: child, criminal, penal, law, safety

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