Search results for: mineral processing.

Authors: Andriana Mkrtchyan, Vahe Khlghatyan

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The choice of a profession is one of the most important decisions people make throughout their life. With the development of modern science, technologies, and all the spheres existing in the modern world, more and more professions are being arisen that complicate even more the process of choosing. Hence, there is a need for a guiding platform to help people to choose a profession and the right career path based on their interests, skills, and personality. This review aims at analyzing existing methods of comparing PDF format documents and suggests that a 3-stage approach is implemented for the comparison, that is – 1. text extraction from PDF format documents, 2. comparison of the extracted text via NLP algorithms, 3. comparison representation using special shape and color psychology methodology.

Keywords: color psychology, data acquisition/extraction, data augmentation, disambiguation, natural language processing, outlier detection, semantic similarity, text-mining, user evaluation, visual search

Procedia PDF Downloads 76

Authors: A. Nachour, L. Ouzizi, Y. Aoura

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Recent developments on multi-agent system have brought a new research field on image processing. Several algorithms are used simultaneously and improved in deferent applications while new methods are investigated. This paper presents a new automatic method for edge detection using several agents and many different actions. The proposed multi-agent system is based on parallel agents that locally perceive their environment, that is to say, pixels and additional environmental information. This environment is built using Vector Field Convolution that attract free agent to the edges. Problems of partial, hidden or edges linking are solved with the cooperation between agents. The presented method was implemented and evaluated using several examples on different synthetic and medical images. The obtained experimental results suggest that this approach confirm the efficiency and accuracy of detected edge.

Keywords: edge detection, medical MRImages, multi-agent systems, vector field convolution

Procedia PDF Downloads 392

Authors: Retno Supriyanti, Ahmad Chuzaeri, Yogi Ramadhani, A. Haris Budi Widodo

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The use of ultrasonography in the medical world has been very popular including the diagnosis of pregnancy. In determining pregnancy, ultrasonography has many roles, such as to check the position of the fetus, abnormal pregnancy, fetal age and others. Unfortunately, all these things still need to analyze the role of the obstetrician in the sense of image raised by ultrasonography. One of the most striking is the determination of gestational age. Usually, it is done by measuring the length of the fetus manually by obstetricians. In this study, we developed a computer-aided diagnosis for the determination of gestational age by measuring the length of the fetus automatically using edge detection method and image morphology. Results showed that the system is sufficiently accurate in determining the gestational age based image processing.

Keywords: computer aided diagnosis, gestational age, and diameter of uterus, length of fetus, edge detection method, morphology image

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Authors: Faraj M. Elkhatri, Hana Ali Allafi

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The spatial and temporal distribution of diagenetic alterations related impact on the reservoir quality of the Sarir Formation. (present day burial depth of about 9000 feet) Depositional facies and diagenetic alterations are the main controls on reservoir quality of Sarir Formation Sirt Ba-sin Libya; these based on lithology and grain size as well as authigenic clay mineral types and their distributions. However, petrology investigation obtained on study area with five sandstone wells concentrated on main rock components and the parameters that may have impacts on reservoirs. the main authigenic clay minerals are kaolinite and dickite, these investigations have confirmed by X.R.D analysis and clay fraction. mainly Kaolinite and Dickite were extensively presented on all of wells with high amounts. As well as trace of detrital smectite and less amounts of illitized mud-matrix are possibly find by SEM image. Thin layers of clay presented as clay-grain coatings in local depth interpreted as remains of dissolved clay matrix is partly transformed into kaolinite adjacent and towards pore throat. This also may have impacts on most of the pore throats of this sandstone which are open and relatively clean with some of fine martial have been formed on occluded pores. This material is identified by EDS analysis to be collections of not only kaolinite booklets, but also small, disaggregated kaolinite platelets derived from the dis-aggregation of larger kaolinite booklets. These patches of kaolinite not only fill this pore, but also coat some of the sur-rounding framework grains. Quartz grains often enlarged by authigenic quartz overgrowths partially occlude and re-duce porosity. Scanning Electron Microscopy with Energy Dispersive Spectroscopy (SEM) was conducted on the post-test samples to examine any mud filtrate particles that may be in the pore throats. Semi-qualitative elemental data on select-ed minerals observed during the SEM study were obtained using an Energy Dispersive Spectroscopy (EDS) unit. The samples showed mostly clean open pore throats, with limited occlusion by kaolinite.

Keywords: por throat, formation damage, porosity lose, solids plugging

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Authors: Colin Schmidt, Adrien Lecossier, Pascal Crubleau, Philippe Blanchard, Simon Richir

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Introduction:The widespread availability of artificial intelligence, exemplified by Generative Pre-trained Transformers (GPT) relying on large language models (LLM), has caused a seismic shift in the realm of knowledge. Everyone now has the capacity to swiftly learn how these models can either serve them well or not. Today, conversational AI like ChatGPT is grounded in neural transformer models, a significant advance in natural language processing facilitated by the emergence of renowned LLMs constructed using neural transformer architecture. Inventiveness of an LLM : OpenAI's GPT-3 stands as a premier LLM, capable of handling a broad spectrum of natural language processing tasks without requiring fine-tuning, reliably producing text that reads as if authored by humans. However, even with an understanding of how LLMs respond to questions asked, there may be lurking behind OpenAI’s seemingly endless responses an inventive model yet to be uncovered. There may be some unforeseen reasoning emerging from the interconnection of neural networks here. Just as a Soviet researcher in the 1940s questioned the existence of Common factors in inventions, enabling an Under standing of how and according to what principles humans create them, it is equally legitimate today to explore whether solutions provided by LLMs to complex problems also share common denominators. Theory of Inventive Problem Solving (TRIZ) : We will revisit some fundamentals of TRIZ and how Genrich ALTSHULLER was inspired by the idea that inventions and innovations are essential means to solve societal problems. It's crucial to note that traditional problem-solving methods often fall short in discovering innovative solutions. The design team is frequently hampered by psychological barriers stemming from confinement within a highly specialized knowledge domain that is difficult to question. We presume ChatGPT Utilizes TRIZ 40. Hence, the objective of this research is to decipher the inventive model of LLMs, particularly that of ChatGPT, through a comparative study. This will enhance the efficiency of sustainable innovation processes and shed light on how the construction of a solution to a complex problem was devised. Description of the Experimental Protocol : To confirm or reject our main hypothesis that is to determine whether ChatGPT uses TRIZ, we will follow a stringent protocol that we will detail, drawing on insights from a panel of two TRIZ experts. Conclusion and Future Directions : In this endeavor, we sought to comprehend how an LLM like GPT addresses complex challenges. Our goal was to analyze the inventive model of responses provided by an LLM, specifically ChatGPT, by comparing it to an existing standard model: TRIZ 40. Of course, problem solving is our main focus in our endeavours.

Keywords: artificial intelligence, Triz, ChatGPT, inventiveness, problem-solving

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Authors: S. Oudjemia, F. Alim, S. Seddiki

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This paper shows the application of multifractal analysis for additional help in cancer diagnosis. The medical image processing is a very important discipline in which many existing methods are in search of solutions to real problems of medicine. In this work, we present results of multifractal analysis of brain MRI images. The purpose of this analysis was to separate between healthy and cancerous tissue of the brain. A nonlinear method based on multifractal detrending moving average (MFDMA) which is a generalization of the detrending fluctuations analysis (DFA) is used for the detection of abnormalities in these images. The proposed method could make separation of the two types of brain tissue with success. It is very important to note that the choice of this non-linear method is due to the complexity and irregularity of tumor tissue that linear and classical nonlinear methods seem difficult to characterize completely. In order to show the performance of this method, we compared its results with those of the conventional method box-counting.

Keywords: irregularity, nonlinearity, MRI brain images, multifractal analysis, brain tumor

Procedia PDF Downloads 443

Authors: Onkar Nath Verma, Nitish Kumar Singh, Raghvendra, Pravin Kumar, Prabhakar Singh

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The perovskite type electrolyte material LaAlO3 was prepared by solution based auto-combustion method using Al (NO3)3.6H2O, La2O3 with dilute nitrate acid (HNO3) as precursors and citric acid (C6H8O7.H2O) as a fuel. The synthesis protocol gave an easy processing of the LaAlO3 nano-particles. The XRD measurement revealed that the material has single phase with space group R-3c (rhombohedral). Thermal behavior was measured by simultaneous differential thermal analysis and thermo gravimetric analysis (DTA-TGA). The compact pellet density was determined. Also, the surface morphology was studied using scanning electron microscopy (SEM). The conductivity of LaAlO3 was measured employing LCR meter and found to increase with increasing temperature. This increase in conductivity may be attributed to increased mobility of oxide ion.

Keywords: perovskite, LaAlO3, XRD, SEM, DTA-TGA, SOFC

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Authors: Shreeyam, Ranjan Kumar Sah, Shivangi

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Recognizing and solving handwritten mathematical expressions can be a challenging task, particularly when certain characters are segmented and classified. This project proposes a solution that uses Convolutional Neural Network (CNN) and image processing techniques to accurately solve various types of equations, including arithmetic, quadratic, and trigonometric equations, as well as logical operations like logical AND, OR, NOT, NAND, XOR, and NOR. The proposed solution also provides a graphical solution, allowing users to visualize equations and their solutions. In addition to equation solving, the platform, called CNNCalc, offers a comprehensive learning experience for students. It provides educational content, a quiz platform, and a coding platform for practicing programming skills in different languages like C, Python, and Java. This all-in-one solution makes the learning process engaging and enjoyable for students. The proposed methodology includes horizontal compact projection analysis and survey for segmentation and binarization, as well as connected component analysis and integrated connected component analysis for character classification. The compact projection algorithm compresses the horizontal projections to remove noise and obtain a clearer image, contributing to the accuracy of character segmentation. Experimental results demonstrate the effectiveness of the proposed solution in solving a wide range of mathematical equations. CNNCalc provides a powerful and user-friendly platform for solving equations, learning, and practicing programming skills. With its comprehensive features and accurate results, CNNCalc is poised to revolutionize the way students learn and solve mathematical equations. The platform utilizes a custom-designed Convolutional Neural Network (CNN) with image processing techniques to accurately recognize and classify symbols within handwritten equations. The compact projection algorithm effectively removes noise from horizontal projections, leading to clearer images and improved character segmentation. Experimental results demonstrate the accuracy and effectiveness of the proposed solution in solving a wide range of equations, including arithmetic, quadratic, trigonometric, and logical operations. CNNCalc features a user-friendly interface with a graphical representation of equations being solved, making it an interactive and engaging learning experience for users. The platform also includes tutorials, testing capabilities, and programming features in languages such as C, Python, and Java. Users can track their progress and work towards improving their skills. CNNCalc is poised to revolutionize the way students learn and solve mathematical equations with its comprehensive features and accurate results.

Keywords: AL, ML, hand written equation solver, maths, computer, CNNCalc, convolutional neural networks

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Authors: Abdullah Khuwaileh

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The central aim of this paper is to investigate writing skills in the two languages involved, English and Arabic, and to see whether there is an association between poor writing across languages. That is to say, and it is thought that learners might be excellent in their L1 (Language 1: Arabic) but not in L2 (language 2: English). However, our experimental research findings resulted in an interesting association between L1 and L2. Data were collected from 150 students (chosen randomly) who wrote about the same topic in English and Arabic. Topics needed no preparation as they were common and well-known. Scripts were assessed respectively by ELT (English Language Teaching) and Arabic specialists. The study confirms that poor writing in English correlates with similar deficiencies in the mother tongue (Arabic). Thus, the common assumption in ELT that all learners are fully competent in their first language skills is unfounded. Therefore, the criticism of ELT programs for speakers of Arabic, based on poor writing skills in English and good writing in Arabic is not justified. The findings of this paper can be extended to other learners of English who speak Arabic as a first language and English as a foreign and/or second language. The study is concluded with several research and practical recommendations

Keywords: language, writing, culture, l1

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Authors: Govinda Pathak

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In modern agriculture, the sustainable enhancement of crop productivity while minimizing environmental impacts remains a paramount challenge. Plant Growth Promoting Rhizobacteria (PGPR) have emerged as a promising solution to address this challenge. The rhizosphere, the dynamic interface between plant roots and soil, hosts intricate microbial interactions crucial for plant health and nutrient acquisition. PGPR, a subset of rhizospheric microorganisms, exhibit multifaceted beneficial effects on plants. Their abilities to stimulate growth, confer stress tolerance, enhance nutrient availability, and suppress pathogens make them invaluable contributors to sustainable agriculture. This work examines the pivotal role of free living nitrogen fixer in optimizing agricultural practices. We delve into the intricate mechanisms underlying PGPR-mediated plant-microbe interactions, encompassing quorum sensing, root exudate modulation, and signaling molecule exchange. Furthermore, we explore the diverse strategies employed by PGPR to enhance plant resilience against abiotic stresses such as drought, salinity, and metal toxicity. Additionally, we highlight the role of PGPR in augmenting nutrient acquisition and soil fertility through mechanisms such as nitrogen fixation, phosphorus solubilization, and mineral mobilization. Furthermore, we discuss the potential of PGPR in minimizing the reliance on chemical fertilizers and pesticides, thereby contributing to environmentally friendly agriculture. However, harnessing the full potential of PGPR requires a comprehensive understanding of their interactions with host plants and the surrounding microbial community. We also address challenges associated with PGPR application, including formulation, compatibility, and field efficacy. As the quest for sustainable agriculture intensifies, harnessing the remarkable attributes of PGPR offers a holistic approach to propel agricultural productivity while maintaining ecological balance. This work underscores the promising prospect of free living nitrogen fixer as a panacea for addressing critical agricultural challenges regarding chemical urea in an era of sustainable and resilient food production.

Keywords: PGPR, nitrogen fixer, quorum sensing, Rhizobacteria, pesticides

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Authors: Xiao-Hua Zhu, Xin Yuan, Yi-Ran Zhao

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High-cadmium pollution in rice is a serious problem in many parts of China. Many kinds of remediation technologies have been tested and applied in many farmlands. Because of the productive function of the farmland, most technologies are inappropriate due to their destruction to the tillage soil layer. And the large labours and expensive fees of many technologies are also the restrictive factors for their applications. The conception of 'Root Micro-Geochemical Barrier' was proposed to reduce cadmium (Cd) bioavailability and the concentration of the cadmium in rice. Remediation and mitigation techniques were demonstrated on contaminated farmland in the downstream of some mine. According to the rule of rice growth, Cd would be absorbed by the crops in every growth stage, and the plant-absorb efficiency in the first stage of the tillering stage is almost the highest. We should create a method to protect the crops from heavy metal pollution, which could begin to work from the early growth stage. Many materials with repair property get our attention. The materials will create a barrier preventing Cd from being absorbed by the crops during all the growing process because the material has the ability to adsorb soil-Cd and making it losing its migration activity. And we should choose a good chance to put the materials into the crop-growing system cheaply as soon as early. Per plant, rice has a little root system scope, which makes the roots reach about 15cm deep and 15cm wide. So small root radiation area makes it possible for all the Cd approaching the roots to be adsorbed with a small amount of adsorbent. Mixing the remediation materials with the seed-raising soli and adding them to the tillage soil in the process of transplanting seedlings, we can control the soil-Cd activity in the range of roots to reduce the Cd-amount absorbed by the crops. Of course, the mineral materials must have enough adsorptive capacity and no additional pollution. More than 3000 square meters farmlands have been remediated. And on the application of root micro-geochemical barrier, the Cd-concentration in rice and the remediation-cost have been decreased by 90% and 80%, respectively, with little extra labour brought to the farmers. The Cd-concentrations in rice from remediated farmland have been controlled below 0.1 ppm. The remediation of one acre of contaminated cropland costs less than $100. The concept has its advantage in the remediation of paddy field contaminated by Cd, especially for the field with outside pollution sources.

Keywords: cadmium pollution, growth stage, cost, root micro-geochemistry barrier

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Authors: Shoji Matsumoto

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Friction Stir Welding (FSW) has been widely used in the automotive, aerospace, and high-tech industries due to its superior mechanical properties after welding. However, when it becomes a matter to perform a high-quality joint using FSW, it is necessary to secure an advanced tilt angle (usually 1 to 5 degrees) using a dedicated FSW machine and to use a joint structure and a restraining jig that can withstand the tool pressure applied during the jointing process using a highly rigid processing machine. One issue that has become a challenge in this process is ‘productivity and versatility’. To solve this problem, we have conducted research and development of multi-functioning machines and robotics with FSW tools, which combine cutting/milling and FSW functions as one in recent years. However, the narrow process window makes it prone to welding defects and lacks repeatability, which makes a limitation for FSW its use in the fields where precisions required. Another reason why FSW machines are not widely used in the world is because of the matter of very high cost of ownership.

Keywords: synchronized, stir, welding, friction, traveling speed, synchronized stir welding, friction stir welding

Procedia PDF Downloads 54

Authors: Mark Harmon, Abdolghani Ebrahimi, Patrick Lucey, Diego Klabjan

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In this paper, we predict the likelihood of a player making a shot in basketball from multiagent trajectories. Previous approaches to similar problems center on hand-crafting features to capture domain-specific knowledge. Although intuitive, recent work in deep learning has shown, this approach is prone to missing important predictive features. To circumvent this issue, we present a convolutional neural network (CNN) approach where we initially represent the multiagent behavior as an image. To encode the adversarial nature of basketball, we use a multichannel image which we then feed into a CNN. Additionally, to capture the temporal aspect of the trajectories, we use “fading.” We find that this approach is superior to a traditional FFN model. By using gradient ascent, we were able to discover what the CNN filters look for during training. Last, we find that a combined FFN+CNN is the best performing network with an error rate of 39%.

Keywords: basketball, computer vision, image processing, convolutional neural network

Procedia PDF Downloads 153

Authors: Sidharth Talan, Devendra Kumar Yadav, Yuvraj Singh Rajput, Subhajit Bhattacharjee

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Mining industry is known for its appetite to spend sizeable capital on mine equipment. However, in the current scenario, the mining industry is challenged by daunting factors of non-uniform geological conditions, uneven ore grade, uncontrollable and volatile mineral commodity prices and the ever increasing quest to optimize the capital and operational costs. Thus, the role of equipment reliability and maintenance planning inherits a significant role in augmenting the equipment availability for the operation and in turn boosting the mine productivity. This paper presents the Risk Based Maintenance (RBM) planning conducted on mine loading equipment namely Load Haul Dumpers (LHDs) at Vedanta Resources Ltd subsidiary Hindustan Zinc Limited operated Sindesar Khurd Mines, an underground zinc and lead mine situated in Dariba, Rajasthan, India. The mining equipment at the location is maintained by the Original Equipment Manufacturers (OEMs) namely Sandvik and Atlas Copco, who carry out the maintenance and inspection operations for the equipment. Based on the downtime data extracted for the equipment fleet over the period of 6 months spanning from 1^st January 2017 until 30^th June 2017, it was revealed that significant contribution of three downtime issues related to namely Engine, Hydraulics, and Transmission to be common among all the loading equipment fleet and substantiated by Pareto Analysis. Further scrutiny through Bubble Matrix Analysis of the given factors revealed the major influence of selective factors namely Overheating, No Load Taken (NTL) issues, Gear Changing issues and Hose Puncture and leakage issues. Utilizing the equipment wise analysis of all the downtime factors obtained, spares consumed, and the alarm logs extracted from the machines, technical design changes in the equipment and pre shift critical alarms checklist were proposed for the equipment maintenance. The given analysis is beneficial to allow OEMs or mine management to focus on the critical issues hampering the reliability of mine equipment and design necessary maintenance strategies to mitigate them.

Keywords: bubble matrix analysis, LHDs, OEMs, Pareto chart analysis, spares consumption matrix, critical alarms checklist

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Authors: Balunkeswar Nayak, Hanjun Cao, Xinruo Zhang

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Elderberry could protect human health from oxidative stress, and reduce aging and certain cardiovascular diseases due to the presence of bioactive phytochemicals with high antioxidant capacity. However, these bioactive phytochemicals, such as anthocyanins and other phenolic acids, are susceptible to degradation during processing of elderberries to juice, jam, and powder due to intensity and duration of thermal exposure. The effects of microwave heating rate during come-up-times, using a domestic 2450 MHz microwave, on the color, total anthocyanin content and total phenolics on elderberry juice was studied. With a variation of come-up-time from 30 sec to 15 min at different power levels (10–50 % of total wattage), the temperature of elderberry juice vary from 40.6 °C to 91.5 °C. However, the color parameters (L, A, and B), total anthocyanin content (using pH differential method) and total phenolics did not vary significantly when compared to the control samples.

Keywords: elderberry, microwave, color, thermal exposure

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Authors: Khald Anisse, Amina Radgui, Mohammed Rziza

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Tracking objects on video sequences is a very challenging task in many works in computer vision applications. However, there is no article that treats this topic in catadioptric vision. This paper is an attempt that tries to describe a new approach of omnidirectional images processing based on inverse stereographic projection in the half-sphere. We used the spherical model proposed by Gayer and al. For object tracking, our work is based on snake method, with optimization using the Greedy algorithm, by adapting its different operators. The algorithm will respect the deformed geometries of omnidirectional images such as spherical neighborhood, spherical gradient and reformulation of optimization algorithm on the spherical domain. This tracking method that we call "spherical snake" permitted to know the change of the shape and the size of object in different replacements in the spherical image.

Keywords: computer vision, spherical snake, omnidirectional image, object tracking, inverse stereographic projection

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Authors: Rajesh Mehra, Bharti Thakur

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In this paper, an IIR filter has been designed and simulated on an FPGA. The implementation is based on MAC algorithm which uses multiply-and-accumulate operations IIR filter design implementation. Parallel Pipelined structure is used to implement the proposed IIR Filter taking optimal advantage of the look up table of the FPGA device. The designed filter has been synthesized on DSP slice based FPGA to perform multiplier function of MAC unit. The DSP slices are useful to enhance the speed performance. The developed IIR filter is designed and simulated with Matlab and synthesized with Xilinx Synthesis Tool (XST), and implemented on Virtex 5 and Spartan 3 ADSP FPGA devices. The IIR filter implemented on Virtex 5 FPGA can operate at an estimated frequency of 81.5 MHz as compared to 40.5 MHz in case of Spartan 3 ADSP FPGA. The Virtex 5 based implementation also consumes less slices and slice flip flops of target FPGA in comparison to Spartan 3 ADSP based implementation to provide cost effective solution for signal processing applications.

Keywords: Butterworth filter, DSP, IIR, MAC, FPGA

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Authors: Qitao Xie, Qingquan Zhang, Xiaofei Zhang, Di Tian, Ruixuan Wen, Ting Zhu, Ping Yi, Xin Li

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Inspired by the recent movement of digital currency, we are building a question answering system concerning the subject of cryptocurrency using Bidirectional Encoder Representations from Transformers (BERT). The motivation behind this work is to properly assist digital currency investors by directing them to the corresponding knowledge bases that can offer them help and increase the querying speed. BERT, one of newest language models in natural language processing, was investigated to improve the quality of generated responses. We studied different combinations of hyperparameters of the BERT model to obtain the best fit responses. Further, we created an intelligent chatbot for cryptocurrency using BERT. A chatbot using BERT shows great potential for the further advancement of a cryptocurrency market tool. We show that the BERT neural networks generalize well to other tasks by applying it successfully to cryptocurrency.

Keywords: bidirectional encoder representations from transformers, BERT, chatbot, cryptocurrency, deep learning

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Authors: Aymen Sekhri, Emmanuel Kwabena Frimpong, Bolaji Mubarak Ayeyemi, Aleksi Hirvonen, Matias Hirvonen, Tedros Tesfay Andemichael

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Fixation identification, which involves isolating and identifying fixations and saccades in eye-tracking protocols, is an important aspect of eye-movement data processing that can have a big impact on higher-level analyses. However, fixation identification techniques are frequently discussed informally and rarely compared in any meaningful way. With two state-of-the-art algorithms, we will implement fixation detection and analysis in this work. The velocity threshold fixation algorithm is the first algorithm, and it identifies fixation based on a threshold value. For eye movement detection, the second approach is U'n' Eye, a deep neural network algorithm. The goal of this project is to analyze and visualize eye-tracking data from an eye gaze dataset that has been provided. The data was collected in a scenario in which individuals were shown photos and asked whether or not they recognized them. The results of the two-fixation detection approach are contrasted and visualized in this paper.

Keywords: human-computer interaction, eye-tracking, CNN, fixations, saccades

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Authors: Alexandra Sargent, Sarah Ferris, Ioannis Theofanous

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The Abbott RealTime High Risk HPV test (RealTime HPV) is one of five assays clinically validated and approved by the English NHS Cervical Screening Programme (CSP) for HPV triage of low grade dyskaryosis and test-of-cure of treated Cervical Intraepithelial Neoplasia. The assay is a highly automated multiplex real-time PCR test for detecting 14 high risk (hr) HPV types, with simultaneous differentiation of HPV 16 and HPV 18 versus non-HPV 16/18 hrHPV. An endogenous internal control ensures sample cellularity, controls extraction efficiency and PCR inhibition. The original cervical specimen collected in SurePath (SP) liquid-based cytology (LBC) medium (BD Diagnostics) and the SP post-gradient cell pellets (SPG) after cytological processing are both CE marked for testing with the RealTime HPV test. During the 2011 NHSCSP validation of new tests only the original aliquot of SP LBC medium was investigated. Residual sample volume left after cytology slide preparation is low and may not always have sufficient volume for repeat HPV testing or for testing of other biomarkers that may be implemented in testing algorithms in the future. The SPG samples, however, have sufficient volumes to carry out additional testing and necessary laboratory validation procedures. This study investigates the correlation of RealTime HPV results of cervical specimens collected in SP LBC medium from women with low grade cytological abnormalities observed with matched pairs of original SP LBC medium and SP post-gradient cell pellets (SPG) after cytology processing. Matched pairs of SP and SPG samples from 750 women with borderline (N = 392) and mild (N = 351) cytology were available for this study. Both specimen types were processed and parallel tested for the presence of hrHPV with RealTime HPV according to the manufacturer´s instructions. HrHPV detection rates and concordance between test results from matched SP and SPGCP pairs were calculated. A total of 743 matched pairs with valid test results on both sample types were available for analysis. An overall-agreement of hrHPV test results of 97.5% (k: 0.95) was found with matched SP/SPG pairs and slightly lower concordance (96.9%; k: 0.94) was observed on 392 pairs from women with borderline cytology compared to 351 pairs from women with mild cytology (98.0%; k: 0.95). Partial typing results were highly concordant in matched SP/SPG pairs for HPV 16 (99.1%), HPV 18 (99.7%) and non-HPV16/18 hrHPV (97.0%), respectively. 19 matched pairs were found with discrepant results: 9 from women with borderline cytology and 4 from women with mild cytology were negative on SPG and positive on SP; 3 from women with borderline cytology and 3 from women with mild cytology were negative on SP and positive on SPG. Excellent correlation of hrHPV DNA test results was found between matched pairs of SP original fluid and post-gradient cell pellets from women with low grade cytological abnormalities tested with the Abbott RealTime High-Risk HPV assay, demonstrating robust performance of the test with both specimen types and reassuring the utility of the assay for cytology triage with both specimen types.

Keywords: Abbott realtime test, HPV, SurePath liquid based cytology, surepath post-gradient cell pellet

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Authors: Chaima Babi, Said Gadri

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The rapid increase in fake news continues to grow at a very fast rate; this requires implementing efficient techniques that allow testing the re-liability of online content. For that, the current research strives to illuminate the fake news problem using deep learning DL and machine learning ML ap-proaches. We have developed the traditional LSTM (Long short-term memory), and the bidirectional BiLSTM model. A such process is to perform a training task on almost of samples of the dataset, validate the model on a subset called the test set to provide an unbiased evaluation of the final model fit on the training dataset, then compute the accuracy of detecting classifica-tion and comparing the results. For the programming stage, we used Tensor-Flow and Keras libraries on Python to support Graphical Processing Units (GPUs) that are being used for developing deep learning applications.

Keywords: machine learning, deep learning, natural language, fake news, Bi-LSTM, LSTM, multiclass classification

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Authors: Wided Bakari, Patrce Bellot, Mahmoud Neji

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With the development of electronic media and the heterogeneity of Arabic data on the Web, the idea of building a clean corpus for certain applications of natural language processing, including machine translation, information retrieval, question answer, become more and more pressing. In this manuscript, we seek to create and develop our own corpus of pair’s questions-texts. This constitution then will provide a better base for our experimentation step. Thus, we try to model this constitution by a method for Arabic insofar as it recovers texts from the web that could prove to be answers to our factual questions. To do this, we had to develop a java script that can extract from a given query a list of html pages. Then clean these pages to the extent of having a database of texts and a corpus of pair’s question-texts. In addition, we give preliminary results of our proposal method. Some investigations for the construction of Arabic corpus are also presented in this document.

Keywords: Arabic, web, corpus, search engine, URL, question, corpus building, script, Google, html, txt

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Authors: Adferotimi Banso

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A laboratory investigation was conducted to determine the effect of Justica flava and Aframonium melegueta on the growth of Aspergillus niger, Rhizopus stolonifer and Fusarium species in sweet orange and mango juices. Aqueous extract (3%v/v) of Justica flava and Aframonium melegueta reduced the growth of the fungi, a combination of 2% (v/v) each of Justica flava and Aframonium melegueta extracts reduced the growth better. Partial purification of aqueous extracts of Justica flava and Aframonium melegueta showed that ethyl acetate fraction of the extracts exhibited the highest level of inhibition of growth of the test fungi compared with diethyl ether and n-hexane fractions. The results suggest that extracts of Justica flava and Aframonium melegueta may be important substitutes for conventional chemical preservatives in the processing of fruit juices.

Keywords: aqueous, fraction, mango, orange, purification, sweet

Procedia PDF Downloads 351

Authors: Omid Shahmirzadi, Adam Lugowski, Kenneth Younge

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Automatic measurement of semantic text similarity is an important task in natural language processing. In this paper, we evaluate the performance of different vector space models to perform this task. We address the real-world problem of modeling patent-to-patent similarity and compare TFIDF (and related extensions), topic models (e.g., latent semantic indexing), and neural models (e.g., paragraph vectors). Contrary to expectations, the added computational cost of text embedding methods is justified only when: 1) the target text is condensed; and 2) the similarity comparison is trivial. Otherwise, TFIDF performs surprisingly well in other cases: in particular for longer and more technical texts or for making finer-grained distinctions between nearest neighbors. Unexpectedly, extensions to the TFIDF method, such as adding noun phrases or calculating term weights incrementally, were not helpful in our context.

Keywords: big data, patent, text embedding, text similarity, vector space model

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Authors: Yasmeen Bassas, Sandra Kuebler, Allen Riddell

Abstract:

Native language identification is one of the growing subfields in natural language processing (NLP). The task of native language identification (NLI) is mainly concerned with predicting the native language of an author’s writing in a second language. In this paper, we investigate the performance of two types of features; content-based features vs. content independent features, when they are evaluated on a different corpus (using social media data “Reddit”). In this NLI task, the predefined models are trained on one corpus (TOEFL), and then the trained models are evaluated on different data using an external corpus (Reddit). Three classifiers are used in this task; the baseline, linear SVM, and logistic regression. Results show that content-based features are more accurate and robust than content independent ones when tested within the corpus and across corpus.

Keywords: NLI, NLP, content-based features, content independent features, social media corpus, ML

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Authors: Riccardo Angiuli, Michele Giannuzzi, Rodolfo Franchi, Gabriele Papadia

Abstract:

Temperature knowledge in machining is fundamental to improve the numerical and FEM models used for the study of some critical process aspects, such as the behavior of the worked material and tool. The extreme conditions in which they operate make it impossible to use traditional measuring instruments; infrared thermography can be used as a valid measuring instrument for temperature measurement during metal cutting. In the study, a large experimental program on superduplex steel (ASTM A995 gr. 5A) cutting was carried out, the relevant cutting temperatures were measured by infrared thermography when certain cutting parameters changed, from traditional values to extreme ones. The values identified were used to calibrate a FEM model for the prediction of residual life of the tools. During the study, the problems related to the detection of cutting temperatures by infrared thermography were analyzed, and a dedicated procedure was developed that could be used during similar processing.

Keywords: machining, infrared thermography, FEM, temperature measurement

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Authors: Luis González-Cavieres, Mario Perez-Won, Anais Palma-Acevedo, Gipsy Tabilo-Munizaga, Erick Jara-Quijada, Roberto Lemus-Mondaca

Abstract:

In this study, pulsed electric field (PEF: 2.0 kV/cm) was used as pretreatment in drying methods, vacuum microwave (VMD); freeze-drying (FD); and hot air (HAD), in Chilean abalone mollusk. Drying parameters, quality, energy consumption, and Sustainability parameters were evaluated. PEF+VMD showed better values than the other drying systems, with drying times 67% and 83% lower than PEF+FD and FD. In the quality parameters, PEF+FD showed a significantly lower value for hardness (250 N), and a lower change of color value (ΔE = 12). In the case of HAD, the PEF application did not significantly influence its processing. In energy parameters, VMD and PEF+VMD reduced energy consumption and CO2 emissions.

Keywords: PEF technology, vacuum microwave drying, energy consumption, CO2 emissions

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Authors: Deokyeong Choe, Jae Eun Nam, Young Hoon Roh, Chul Soo Shin

Abstract:

The development of hydrogels with a high mechanical strength is important for numerous applications of hydrogels. As a material for tough hydrogels, cellulose has attracted much interest. However, cellulose cannot be melted and is very difficult to be dissolved in most solvents. Therefore, its dissolution in tetrabutylammonium fluoride/dimethyl sulfoxide (TBAF/DMSO) solvents has attracted researchers for chemical processing of cellulose. For this reason, studies about rheological properties of cellulose/TBAF/DMSO solution will provide useful information. In this study, viscosities of cellulose solutions prepared using different amounts of cellulose and TBAF in DMSO were measured. As expected, the viscosity of cellulose solution decreased with respect to the increasing volume of DMSO. The most viscose cellulose solution was achieved at a 1:1 mass ratio of cellulose to TBAF regardless of their contents in DMSO. At a 1:1 mass ratio of cellulose to TBAF, the formation of cellulose nanoparticles (467 nm) resulted in a dramatic increase in the viscosity, which led to the fabrication of 3D cellulose hydrogels.

Keywords: cellulose, TBAF/DMSO, viscosity, hydrogel

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Authors: Goban Kumar Panneer Selvam

Abstract:

In past years, there is lots of death caused due to harmful gases. So its very important to monitor harmful gases for human safety, and semiconductor material play important role in producing effective gas sensors.A novel solvothermal synthesis method based on sol-gel processing was prepared to deposit tin oxide thin films on glass substrate at high temperature for gas sensing application. The structure and morphology of tin oxide were analyzed by X-ray diffraction (XRD), Fourier transforms infrared spectroscopy (FTIR) and scanning electron microscopy (SEM). The SEM analysis of how spheres shape in tin oxide nanoparticles. The structure characterization of tin oxide studied by X-ray diffraction shows 8.95 nm (calculated by sheers equation). The UV visible spectroscopy indicated a maximum absorption band shown at 390 nm. Further dope tin oxide with selected metals to attain maximum sensitivity using dip coating technique with different immersion and sensing characterization are measured.

Keywords: tin oxide, gas sensor, chlorine free, sensitivity, crystalline size

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Authors: Sudhina H. K, Ravi M. Yadahalli, N. M. Shetti

Abstract:

Reconfigurable antennas represent a recent innovation in antenna design that changes from classical fixed-form, Fixed function antennas to modifiable structures that can be adapted to fit the requirements of a time varying system. The ability to control the operating band of an antenna system can have many useful applications. Systems that operate in an acquire-and-track configuration would see a benefit from active bandwidth control. In such systems a wide band search mode is first employed to find a desired signal, Then a narrow band track mode is used to follow only that signal. Utilizing active antenna bandwidth control, A single antenna would function for both the wide band and narrow band configurations providing the rejection of unwanted signals with the antenna hardware. This ability to move a portion of the RF filtering out of the receiver and onto the antenna itself will also aid in reducing the complexity of the often expensive RF processing subsystems.

Keywords: designing methods, mems, stack, reconfigurable elements

Procedia PDF Downloads 272