Search results for: computer processing of large databases
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 12740

Search results for: computer processing of large databases

12020 Integrated Models of Reading Comprehension: Understanding to Impact Teaching—The Teacher’s Central Role

Authors: Sally A. Brown

Abstract:

Over the last 30 years, researchers have developed models or frameworks to provide a more structured understanding of the reading comprehension process. Cognitive information processing models and social cognitive theories both provide frameworks to inform reading comprehension instruction. The purpose of this paper is to (a) provide an overview of the historical development of reading comprehension theory, (b) review the literature framed by cognitive information processing, social cognitive, and integrated reading comprehension theories, and (c) demonstrate how these frameworks inform instruction. As integrated models of reading can guide the interpretation of various factors related to student learning, an integrated framework designed by the researcher will be presented. Results indicated that features of cognitive processing and social cognitivism theory—represented in the integrated framework—highlight the importance of the role of the teacher. This model can aid teachers in not only improving reading comprehension instruction but in identifying areas of challenge for students.

Keywords: explicit instruction, integrated models of reading comprehension, reading comprehension, teacher’s role

Procedia PDF Downloads 97
12019 Electrospun Membrane doped with Gold Nanorods for Surface-Enhanced Raman Sepctroscopy

Authors: Ziwei Wang, Andrea Lucotti, Luigi Brambilla, Matteo Tommasini, Chiara Bertarelli

Abstract:

Surface-enhanced Raman Spectroscopy (SERS) is a highly sensitive detection that provides abundant information on low concentration analytes from various researching areas. Based on localized surface plasmon resonance, metal nanostructures including gold, silver and copper have been investigated as SERS substrate during recent decades. There has been increasing more attention of exploring good performance, homogenous, repeatable SERS substrates. Here, we show that electrospinning, which is an inexpensive technique to fabricate large-scale, self-standing and repeatable membranes, can be effectively used for producing SERS substrates. Nanoparticles and nanorods are added to the feed electrospinning solution to collect functionalized polymer fibrous mats. We report stable electrospun membranes as SERS substrate using gold nanorods (AuNRs) and poly(vinyl alcohol). Particularly, a post-processing crosslinking step using glutaraldehyde under acetone environment was carried out to the electrospun membrane. It allows for using the membrane in any liquid environment, including water, which is of interest both for sensing of contaminant in wastewater, as well as for biosensing. This crosslinked AuNRs/PVA membrane has demonstrated excellent performance as SERS substrate for low concentration 10-6 M Rhodamine 6G (Rh6G) aqueous solution. This post-processing for fabricating SERS substrate is the first time reported and proved through Raman imaging of excellent stability and outstanding performance. Finally, SERS tests have been applied to several analytes, and the application of AuNRs/PVA membrane is broadened by removing the detected analyte by rinsing. Therefore, this crosslinked AuNRs/PVA membrane is re-usable.

Keywords: SERS spectroscopy, electrospinning, crosslinking, composite materials

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12018 Dental Pathologies and Agriculture: Literature Review

Authors: Ricardo Andrés Márquez Ortiz

Abstract:

Objective: The objective of this literature review is to compile updated information from studies that have addressed the association between dental pathologies and agriculture. Materials and method: The research carried out corresponds to a documentary study of ex post facto retrospective, historiographic, and bibliometric design. An exhaustive bibliographic review search was carried out in databases and the Internet, books and articles on dental anthropology, archeology, and dentistry, on the relationship between dental pathologies and agriculture in prehistoric and current populations from different parts of the world. Subsequently, data collection was carried out through the ATLAS.ti computer program. Conclusions: In an influential article by Turner, which addresses the correlation between caries and the way of subsistence of both prehistoric and modern populations (hunting and gathering, mixed and agricultural economies), an average of 1.3% was found in hunter-gatherer societies, and 10.4% in agricultural societies. Sreebny compared global grain supply data (rice, wheat and corn) with DMF (spoiled, lost and blocked) rates. He concluded that rice has no association with dental caries, corn has a negative correlation, and wheat has a positive correlation. Additionally, intensive monoculture agricultural production systems cause an increase in dental pathologies. Meanwhile, polyculture agriculture, which leads to a more varied diet, generates a better state of dental health.

Keywords: dental pathologies, agricultural production systems, extensive agriculture, dental anthropology

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12017 Teaching Computer Programming to Diverse Students: A Comparative, Mixed-Methods, Classroom Research Study

Authors: Almudena Konrad, Tomás Galguera

Abstract:

Lack of motivation and interest is a serious obstacle to students’ learning computing skills. A need exists for a knowledge base on effective pedagogy and curricula to teach computer programming. This paper presents results from research evaluating a six-year project designed to teach complex concepts in computer programming collaboratively, while supporting students to continue developing their computer thinking and related coding skills individually. Utilizing a quasi-experimental, mixed methods design, the pedagogical approaches and methods were assessed in two contrasting groups of students with different socioeconomic status, gender, and age composition. Analyses of quantitative data from Likert-scale surveys and an evaluation rubric, combined with qualitative data from reflective writing exercises and semi-structured interviews yielded convincing evidence of the project’s success at both teaching and inspiring students.

Keywords: computational thinking, computing education, computer programming curriculum, logic, teaching methods

Procedia PDF Downloads 316
12016 Large Strain Creep Analysis of Composite Thick-Walled Anisotropic Cylinders

Authors: Vinod Kumar Arya

Abstract:

Creep analysis of a thick-walled composite anisotropic cylinder under internal pressure and considering large strains is presented. Using a threshold creep law for composite materials, expressions for stresses, strains, and strain rates are derived for several anisotropic cases. Numerical results, presented through several graphs and tables, depict the effect of anisotropy on the stress, strain, and strain rate distributions. Since for a specific type of material anisotropy described in the paper, these quantities are found to have the lowest values at the inner radius (the potential location of cylinder failure), it is concluded that by employing such an anisotropic material for the design of a thick-walled cylinder a longer service life for the cylinder may be achieved.

Keywords: creep, composites, large strains, thick-walled cylinders, anisotropy

Procedia PDF Downloads 149
12015 Environment Management Practices at Oil and Natural Gas Corporation Hazira Gas Processing Complex

Authors: Ashish Agarwal, Vaibhav Singh

Abstract:

Harmful emissions from oil and gas processing facilities have long remained a matter of concern for governments and environmentalists throughout the world. This paper analyses Oil and Natural Gas Corporation (ONGC) gas processing plant in Hazira, Gujarat, India. It is the largest gas-processing complex in the country designed to process 41MMSCMD sour natural gas & associated sour condensate. The complex, sprawling over an area of approximate 705 hectares is the mother plant for almost all industries at Hazira and enroute Hazira Bijapur Jagdishpur pipeline. Various sources of pollution from each unit starting from Gas Terminal to Dew Point Depression unit and Caustic Wash unit along the processing chain were examined with the help of different emission data obtained from ONGC. Pollution discharged to the environment was classified into Water, Air, Hazardous Waste and Solid (Non-Hazardous) Waste so as to analyze each one of them efficiently. To protect air environment, Sulphur recovery unit along with automatic ambient air quality monitoring stations, automatic stack monitoring stations among numerous practices were adopted. To protect water environment different effluent treatment plants were used with due emphasis on aquaculture of the nearby area. Hazira plant has obtained the authorization for handling and disposal of five types of hazardous waste. Most of the hazardous waste were sold to authorized recyclers and the rest was given to Gujarat Pollution Control Board authorized vendors. Non-Hazardous waste was also handled with an overall objective of zero negative impact on the environment. The effect of methods adopted is evident from emission data of the plant which was found to be well under Gujarat Pollution Control Board limits.

Keywords: sulphur recovery unit, effluent treatment plant, hazardous waste, sour gas

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12014 The Integration of ICT in the Teaching and Learning of French Language in Some Selected Schools in Nigeria: Prospects and Challenges

Authors: Oluyomi A. Abioye

Abstract:

The 21st century has been witnessing a lot of technological advancements and innovations, and Information and Communication Technology (ICT) happens to be one of them. Education is the cornerstone of any nation and the language in which it is delivered is the bedrock of any development. The French language is our choice in this study. French is a language of reference on the national and international scenes; however its teaching is clouded with myriads of problems. The output of students’ academic performance depends on to a large extent on the teaching and learning the process. The methodology employed goes a long way in contributing to the effectiveness of the teaching and learning the process. Therefore, with the integration of ICT, French teaching has to align with and adapt to this new digital era. An attempt is made to define the concept of ICT. Some of the challenges encountered in the teaching of French language are highlighted. Then it discusses the existing methods of French teaching and the integration of ICT in the teaching and learning of the same language. Then some prospects and challenges of ICT in the teaching and learning of French are discussed. Data collected from questionnaires administered among some students of some selected schools are analysed. Our findings revealed that only very few schools in Nigeria have the electronic and computer-mediated facilities to teach the French language. The paper concludes by encouraging 'savoir-faire' of ICT by the French teachers, an openness of students to this digital technology and adequate provision of electronic and computer-mediated gadgets by the Nigerian government to its educational institutions.

Keywords: French language in Nigeria, integration of ICT, prospects and challenges, teaching and learning

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12013 A Survey on Types of Noises and De-Noising Techniques

Authors: Amandeep Kaur

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Digital Image processing is a fundamental tool to perform various operations on the digital images for pattern recognition, noise removal and feature extraction. In this paper noise removal technique has been described for various types of noises. This paper comprises discussion about various noises available in the image due to different environmental, accidental factors. In this paper, various de-noising approaches have been discussed that utilize different wavelets and filters for de-noising. By analyzing various papers on image de-noising we extract that wavelet based de-noise approaches are much effective as compared to others.

Keywords: de-noising techniques, edges, image, image processing

Procedia PDF Downloads 336
12012 Dynamic Risk Identification Using Fuzzy Failure Mode Effect Analysis in Fabric Process Industries: A Research Article as Management Perspective

Authors: A. Sivakumar, S. S. Darun Prakash, P. Navaneethakrishnan

Abstract:

In and around Erode District, it is estimated that more than 1250 chemical and allied textile processing fabric industries are affected, partially closed and shut off for various reasons such as poor management, poor supplier performance, lack of planning for productivity, fluctuation of output, poor investment, waste analysis, labor problems, capital/labor ratio, accumulation of stocks, poor maintenance of resources, deficiencies in the quality of fabric, low capacity utilization, age of plant and equipment, high investment and input but low throughput, poor research and development, lack of energy, workers’ fear of loss of jobs, work force mix and work ethic. The main objective of this work is to analyze the existing conditions in textile fabric sector, validate the break even of Total Productivity (TP), analyze, design and implement fuzzy sets and mathematical programming for improvement of productivity and quality dimensions in the fabric processing industry. It needs to be compatible with the reality of textile and fabric processing industries. The highly risk events from productivity and quality dimension were found by fuzzy systems and results are wrapped up among the textile fabric processing industry.

Keywords: break even point, fuzzy crisp data, fuzzy sets, productivity, productivity cycle, total productive maintenance

Procedia PDF Downloads 338
12011 Physicochemical Stability of Pulse Spreads during Storage after Sous Vide Treatment and High Pressure Processing

Authors: Asnate Kirse, Daina Karklina, Sandra Muizniece-Brasava, Ruta Galoburda

Abstract:

Pulses are high in plant protein and dietary fiber, and contain slowly digestible starches. Innovative products from pulses could increase their consumption and benefit consumer health. This study was conducted to evaluate physicochemical stability of processed cowpea (Vigna unguiculata (L.) Walp. cv. Fradel) and maple pea (Pisum sativum var. arvense L. cv. Bruno) spreads at 5 °C temperature during 62-day storage. Physicochemical stability of pulse spreads was compared after sous vide treatment (80 °C/15 min) and high pressure processing (700 MPa/10 min/20 °C). Pulse spreads were made by homogenizing cooked pulses in a food processor together with salt, citric acid, oil, and bruschetta seasoning. A total of four different pulse spreads were studied: Cowpea spread without and with seasoning, maple pea spread without and with seasoning. Transparent PA/PE and light proof PET/ALU/PA/PP film pouches were used for packaging of pulse spreads under vacuum. The parameters investigated were pH, water activity and mass losses. Pulse spreads were tested on days 0, 15, 29, 42, 50, 57 and 62. The results showed that sous-vide treatment and high pressure processing had an insignificant influence on pH, water activity and mass losses after processing, irrespective of packaging material did not change (p>0.1). pH and water activity of sous-vide treated and high pressure processed pulse spreads in different packaging materials proved to be stable throughout the storage. Mass losses during storage accounted to 0.1% losses. Chosen sous-vide treatment and high pressure processing regimes and packaging materials are suitable to maintain consistent physicochemical quality of the new products during 62-day storage.

Keywords: cowpea, flexible packaging, maple pea, water activity

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12010 Future Education: Changing Paradigms

Authors: Girish Choudhary

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Education is in a state of flux. Not only one need to acquire skills in order to cope with a fast changing global world, an explosive growth in technology, on the other hand is providing a new wave of teaching tools - computer aided video instruction, hypermedia, multimedia, CD-ROMs, Internet connections, and collaborative software environments. The emerging technology incorporates the group qualities of interactive, classroom-based learning while providing individual students the flexibility to participate in an educational programme at their own time and place. The technology facilitating self learning also seems to provide a cost effective solution to the dilemma of delivering education to masses. Online education is a unique learning domain that provides for many to many communications as well. The computer conferencing software defines the boundaries of the virtual classroom. The changing paradigm provides access of instruction to a large proportion of society, promises a qualitative change in the quality of learning and echoes a new way of thinking in educational theory that promotes active learning and open new learning approaches. Putting it to practice is challenging and may fundamentally alter the nature of educational institutions. The subsequent part of paper addresses such questions viz. 'Do we need to radically re-engineer the curriculum and foster an alternate set of skills in students?' in the onward journey.

Keywords: on-line education, self learning, energy and power engineering, future education

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12009 Influence of the Refractory Period on Neural Networks Based on the Recognition of Neural Signatures

Authors: José Luis Carrillo-Medina, Roberto Latorre

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Experimental evidence has revealed that different living neural systems can sign their output signals with some specific neural signature. Although experimental and modeling results suggest that neural signatures can have an important role in the activity of neural networks in order to identify the source of the information or to contextualize a message, the functional meaning of these neural fingerprints is still unclear. The existence of cellular mechanisms to identify the origin of individual neural signals can be a powerful information processing strategy for the nervous system. We have recently built different models to study the ability of a neural network to process information based on the emission and recognition of specific neural fingerprints. In this paper we further analyze the features that can influence on the information processing ability of this kind of networks. In particular, we focus on the role that the duration of a refractory period in each neuron after emitting a signed message can play in the network collective dynamics.

Keywords: neural signature, neural fingerprint, processing based on signal identification, self-organizing neural network

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12008 System Survivability in Networks in the Context of Defense/Attack Strategies: The Large Scale

Authors: Asma Ben Yaghlane, Mohamed Naceur Azaiez, Mehdi Mrad

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We investigate the large scale of networks in the context of network survivability under attack. We use appropriate techniques to evaluate and the attacker-based- and the defender-based-network survivability. The attacker is unaware of the operated links by the defender. Each attacked link has some pre-specified probability to be disconnected. The defender choice is so that to maximize the chance of successfully sending the flow to the destination node. The attacker however will select the cut-set with the highest chance to be disabled in order to partition the network. Moreover, we extend the problem to the case of selecting the best p paths to operate by the defender and the best k cut-sets to target by the attacker, for arbitrary integers p,k > 1. We investigate some variations of the problem and suggest polynomial-time solutions.

Keywords: defense/attack strategies, large scale, networks, partitioning a network

Procedia PDF Downloads 283
12007 Automatic Processing of Trauma-Related Visual Stimuli in Female Patients Suffering From Post-Traumatic Stress Disorder after Interpersonal Traumatization

Authors: Theresa Slump, Paula Neumeister, Katharina Feldker, Carina Y. Heitmann, Thomas Straube

Abstract:

A characteristic feature of post-traumatic stress disorder (PTSD) is the automatic processing of disorder-specific stimuli that expresses itself in intrusive symptoms such as intense physical and psychological reactions to trauma-associated stimuli. That automatic processing plays an essential role in the development and maintenance of symptoms. The aim of our study was, therefore, to investigate the behavioral and neural correlates of automatic processing of trauma-related stimuli in PTSD. Although interpersonal traumatization is a form of traumatization that often occurs, it has not yet been sufficiently studied. That is why, in our study, we focused on patients suffering from interpersonal traumatization. While previous imaging studies on PTSD mainly used faces, words, or generally negative visual stimuli, our study presented complex trauma-related and neutral visual scenes. We examined 19 female subjects suffering from PTSD and examined 19 healthy women as a control group. All subjects did a geometric comparison task while lying in a functional-magnetic-resonance-imaging (fMRI) scanner. Trauma-related scenes and neutral visual scenes that were not relevant to the task were presented while the subjects were doing the task. Regarding the behavioral level, there were not any significant differences between the task performance of the two groups. Regarding the neural level, the PTSD patients showed significant hyperactivation of the hippocampus for task-irrelevant trauma-related stimuli versus neutral stimuli when compared with healthy control subjects. Connectivity analyses revealed altered connectivity between the hippocampus and other anxiety-related areas in PTSD patients, too. Overall, those findings suggest that fear-related areas are involved in PTSD patients' processing of trauma-related stimuli even if the stimuli that were used in the study were task-irrelevant.

Keywords: post-traumatic stress disorder, automatic processing, hippocampus, functional magnetic resonance imaging

Procedia PDF Downloads 199
12006 A Combined Approach Based on Artificial Intelligence and Computer Vision for Qualitative Grading of Rice Grains

Authors: Hemad Zareiforoush, Saeed Minaei, Ahmad Banakar, Mohammad Reza Alizadeh

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The quality inspection of rice (Oryza sativa L.) during its various processing stages is very important. In this research, an artificial intelligence-based model coupled with computer vision techniques was developed as a decision support system for qualitative grading of rice grains. For conducting the experiments, first, 25 samples of rice grains with different levels of percentage of broken kernels (PBK) and degree of milling (DOM) were prepared and their qualitative grade was assessed by experienced experts. Then, the quality parameters of the same samples examined by experts were determined using a machine vision system. A grading model was developed based on fuzzy logic theory in MATLAB software for making a relationship between the qualitative characteristics of the product and its quality. Totally, 25 rules were used for qualitative grading based on AND operator and Mamdani inference system. The fuzzy inference system was consisted of two input linguistic variables namely, DOM and PBK, which were obtained by the machine vision system, and one output variable (quality of the product). The model output was finally defuzzified using Center of Maximum (COM) method. In order to evaluate the developed model, the output of the fuzzy system was compared with experts’ assessments. It was revealed that the developed model can estimate the qualitative grade of the product with an accuracy of 95.74%.

Keywords: machine vision, fuzzy logic, rice, quality

Procedia PDF Downloads 419
12005 The Influence of E-Learning on Teachers and Students Educational Interactions in Tehran City

Authors: Hadi Manjiri, Mahdyeh Bakhshi, Ali Jafari, Maryam Salati

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This study investigates the influence of e-learning on teacher-student instructional interactions through the mediating role of computer literacy among elementary school teachers in Tehran. The research method is a survey that was conducted among elementary school students in Tehran. A sample size of 338 was determined based on Morgan's table. A stratified random sampling method was used to select 228 women and 110 men for the study. Bagherpour et al.'s computer literacy questionnaire, Elahi et al.'s e-learning questionnaire, and Lourdusamy and Khine's questionnaire on teacher-student instructional interactions were used to measure the variables. The data were analyzed using SPSS and LISREL software. It was found that e-learning affects teacher-student instructional interactions, mediated by teachers' computer literacy. In addition, the results suggest that e-learning predicts a 0.66 change in teacher-student instructional interactions, while computer literacy predicts a 0.56 change in instructional interactions between teachers and students.

Keywords: e-learning, instructional interactions, computer literacy, students

Procedia PDF Downloads 118
12004 Classification of Manufacturing Data for Efficient Processing on an Edge-Cloud Network

Authors: Onyedikachi Ulelu, Andrew P. Longstaff, Simon Fletcher, Simon Parkinson

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The widespread interest in 'Industry 4.0' or 'digital manufacturing' has led to significant research requiring the acquisition of data from sensors, instruments, and machine signals. In-depth research then identifies methods of analysis of the massive amounts of data generated before and during manufacture to solve a particular problem. The ultimate goal is for industrial Internet of Things (IIoT) data to be processed automatically to assist with either visualisation or autonomous system decision-making. However, the collection and processing of data in an industrial environment come with a cost. Little research has been undertaken on how to specify optimally what data to capture, transmit, process, and store at various levels of an edge-cloud network. The first step in this specification is to categorise IIoT data for efficient and effective use. This paper proposes the required attributes and classification to take manufacturing digital data from various sources to determine the most suitable location for data processing on the edge-cloud network. The proposed classification framework will minimise overhead in terms of network bandwidth/cost and processing time of machine tool data via efficient decision making on which dataset should be processed at the ‘edge’ and what to send to a remote server (cloud). A fast-and-frugal heuristic method is implemented for this decision-making. The framework is tested using case studies from industrial machine tools for machine productivity and maintenance.

Keywords: data classification, decision making, edge computing, industrial IoT, industry 4.0

Procedia PDF Downloads 182
12003 Microwave Single Photon Source Using Landau-Zener Transitions

Authors: Siddhi Khaire, Samarth Hawaldar, Baladitya Suri

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As efforts towards quantum communication advance, the need for single photon sources becomes imminent. Due to the extremely low energy of a single microwave photon, efforts to build single photon sources and detectors in the microwave range are relatively recent. We plan to use a Cooper Pair Box (CPB) that has a ‘sweet-spot’ where the two energy levels have minimal separation. Moreover, these qubits have fairly large anharmonicity making them close to ideal two-level systems. If the external gate voltage of these qubits is varied rapidly while passing through the sweet-spot, due to Landau-Zener effect, the qubit can be excited almost deterministically. The rapid change of the gate control voltage through the sweet spot induces a non-adiabatic population transfer from the ground to the excited state. The qubit eventually decays into the emission line emitting a single photon. The advantage of this setup is that the qubit can be excited without any coherent microwave excitation, thereby effectively increasing the usable source efficiency due to the absence of control pulse microwave photons. Since the probability of a Landau-Zener transition can be made almost close to unity by the appropriate design of parameters, this source behaves as an on-demand source of single microwave photons. The large anharmonicity of the CPB also ensures that only one excited state is involved in the transition and multiple photon output is highly improbable. Such a system has so far not been implemented and would find many applications in the areas of quantum optics, quantum computation as well as quantum communication.

Keywords: quantum computing, quantum communication, quantum optics, superconducting qubits, flux qubit, charge qubit, microwave single photon source, quantum information processing

Procedia PDF Downloads 98
12002 Programmable Microfluidic Device Based on Stimuli Responsive Hydrogels

Authors: Martin Elstner

Abstract:

Processing of information by means of handling chemicals is a ubiquitous phenomenon in nature. Technical implementations of chemical information processing lack of low integration densities compared to electronic devices. Stimuli responsive hydrogels are promising candidates for materials with information processing capabilities. These hydrogels are sensitive toward chemical stimuli like metal ions or amino acids. The binding of an analyte molecule induces conformational changes inside the polymer network and subsequently the water content and volume of the hydrogel varies. This volume change can control material flows, and concurrently information flows, in microfluidic devices. The combination of this technology with powerful chemical logic gates yields in a platform for highly integrated chemical circuits. The manufacturing process of such devices is very challenging and rapid prototyping is a key technology used in the study. 3D printing allows generating three-dimensional defined structures of high complexity in a single and fast process step. This thermoplastic master is molded into PDMS and the master is removed by dissolution in an organic solvent. A variety of hydrogel materials is prepared by dispenser printing of pre-polymer solutions. By a variation of functional groups or cross-linking units, the functionality of the hole circuit can be programmed. Finally, applications in the field of bio-molecular analytics were demonstrated with an autonomously operating microfluidic chip.

Keywords: bioanalytics, hydrogels, information processing, microvalve

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12001 Studying the Effect of Reducing Thermal Processing over the Bioactive Composition of Non-Centrifugal Cane Sugar: Towards Natural Products with High Therapeutic Value

Authors: Laura Rueda-Gensini, Jader Rodríguez, Juan C. Cruz, Carolina Munoz-Camargo

Abstract:

There is an emerging interest in botanicals and plant extracts for medicinal practices due to their widely reported health benefits. A large variety of phytochemicals found in plants have been correlated with antioxidant, immunomodulatory, and analgesic properties, which makes plant-derived products promising candidates for modulating the progression and treatment of numerous diseases. Non-centrifugal cane sugar (NCS), in particular, has been known for its high antioxidant and nutritional value, but composition-wise variability due to changing environmental and processing conditions have considerably limited its use in the nutraceutical and biomedical fields. This work is therefore aimed at assessing the effect of thermal exposure during NCS production over its bioactive composition and, in turn, its therapeutic value. Accordingly, two modified dehydration methods are proposed that employ: (i) vacuum-aided evaporation, which reduces the necessary temperatures to dehydrate the sample, and (ii) window refractance evaporation, which reduces thermal exposure time. The biochemical composition of NCS produced under these two methods was compared to traditionally-produced NCS by estimating their total polyphenolic and protein content with Folin-Ciocalteu and Bradford assays, as well as identifying the major phenolic compounds in each sample via HPLC-coupled mass spectrometry. Their antioxidant activities were also compared as measured by their scavenging potential of ABTS and DPPH radicals. Results show that the two modified production methods enhance polyphenolic and protein yield in resulting NCS samples when compared to traditional production methods. In particular, reducing employed temperatures with vacuum-aided evaporation demonstrated to be superior at preserving polyphenolic compounds, as evidenced both in the total and individual polyphenol concentrations. However, antioxidant activities were not significantly different between these. Although additional studies should be performed to determine if the observed compositional differences affect other therapeutic activities (e.g., anti-inflammatory, analgesic, and immunoprotective), these results suggest that reducing thermal exposure holds great promise for the production of natural products with enhanced nutritional value.

Keywords: non-centrifugal cane sugar, polyphenolic compounds, thermal processing, antioxidant activity

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12000 Document-level Sentiment Analysis: An Exploratory Case Study of Low-resource Language Urdu

Authors: Ammarah Irum, Muhammad Ali Tahir

Abstract:

Document-level sentiment analysis in Urdu is a challenging Natural Language Processing (NLP) task due to the difficulty of working with lengthy texts in a language with constrained resources. Deep learning models, which are complex neural network architectures, are well-suited to text-based applications in addition to data formats like audio, image, and video. To investigate the potential of deep learning for Urdu sentiment analysis, we implemented five different deep learning models, including Bidirectional Long Short Term Memory (BiLSTM), Convolutional Neural Network (CNN), Convolutional Neural Network with Bidirectional Long Short Term Memory (CNN-BiLSTM), and Bidirectional Encoder Representation from Transformer (BERT). In this study, we developed a hybrid deep learning model called BiLSTM-Single Layer Multi Filter Convolutional Neural Network (BiLSTM-SLMFCNN) by fusing BiLSTM and CNN architecture. The proposed and baseline techniques are applied on Urdu Customer Support data set and IMDB Urdu movie review data set by using pre-trained Urdu word embedding that are suitable for sentiment analysis at the document level. Results of these techniques are evaluated and our proposed model outperforms all other deep learning techniques for Urdu sentiment analysis. BiLSTM-SLMFCNN outperformed the baseline deep learning models and achieved 83%, 79%, 83% and 94% accuracy on small, medium and large sized IMDB Urdu movie review data set and Urdu Customer Support data set respectively.

Keywords: urdu sentiment analysis, deep learning, natural language processing, opinion mining, low-resource language

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11999 Determining Water Quantity from Sprayer Nozzle Using Particle Image Velocimetry (PIV) and Image Processing Techniques

Authors: M. Nadeem, Y. K. Chang, C. Diallo, U. Venkatadri, P. Havard, T. Nguyen-Quang

Abstract:

Uniform distribution of agro-chemicals is highly important because there is a significant loss of agro-chemicals, for example from pesticide, during spraying due to non-uniformity of droplet and off-target drift. Improving the efficiency of spray pattern for different cropping systems would reduce energy, costs and to minimize environmental pollution. In this paper, we examine the water jet patterns in order to study the performance and uniformity of water distribution during the spraying process. We present a method to quantify the water amount from a sprayer jet by using the Particle Image Velocimetry (PIV) system. The results of the study will be used to optimize sprayer or nozzles design for chemical application. For this study, ten sets of images were acquired by using the following PIV system settings: double frame mode, trigger rate is 4 Hz, and time between pulsed signals is 500 µs. Each set of images contained different numbers of double-framed images: 10, 20, 30, 40, 50, 60, 70, 80, 90 and 100 at eight different pressures 25, 50, 75, 100, 125, 150, 175 and 200 kPa. The PIV images obtained were analysed using custom-made image processing software for droplets and volume calculations. The results showed good agreement of both manual and PIV measurements and suggested that the PIV technique coupled with image processing can be used for a precise quantification of flow through nozzles. The results also revealed that the method of measuring fluid flow through PIV is reliable and accurate for sprayer patterns.

Keywords: image processing, PIV, quantifying the water volume from nozzle, spraying pattern

Procedia PDF Downloads 237
11998 Screening Deformed Red Blood Cells Irradiated by Ionizing Radiations Using Windowed Fourier Transform

Authors: Dahi Ghareab Abdelsalam Ibrahim, R. H. Bakr

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Ionizing radiation, such as gamma radiation and X-rays, has many applications in medical diagnoses and cancer treatment. In this paper, we used the windowed Fourier transform to extract the complex image of the deformed red blood cells. The real values of the complex image are used to extract the best fitting of the deformed cell boundary. Male albino rats are irradiated by γ-rays from ⁶⁰Co. The male albino rats are anesthetized with ether, and then blood samples are collected from the eye vein by heparinized capillary tubes for studying the radiation-damaging effect in-vivo by the proposed windowed Fourier transform. The peripheral blood films are prepared according to the Brown method. The peripheral blood film is photographed by using an Automatic Image Contour Analysis system (SAMICA) from ELBEK-Bildanalyse GmbH, Siegen, Germany. The SAMICA system is provided with an electronic camera connected to a computer through a built-in interface card, and the image can be magnified up to 1200 times and displayed by the computer. The images of the peripheral blood films are then analyzed by the windowed Fourier transform method to extract the precise deformation from the best fitting. Based on accurate deformation evaluation of the red blood cells, diseases can be diagnosed in their primary stages.

Keywords: windowed Fourier transform, red blood cells, phase wrapping, Image processing

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11997 DOS and DDOS Attacks

Authors: Amin Hamrahi, Niloofar Moghaddam

Abstract:

Denial of Service is for denial-of-service attack, a type of attack on a network that is designed to bring the network to its knees by flooding it with useless traffic. Denial of Service (DoS) attacks have become a major threat to current computer networks. Many recent DoS attacks were launched via a large number of distributed attacking hosts in the Internet. These attacks are called distributed denial of service (DDoS) attacks. To have a better understanding on DoS attacks, this article provides an overview on existing DoS and DDoS attacks and major defense technologies in the Internet.

Keywords: denial of service, distributed denial of service, traffic, flooding

Procedia PDF Downloads 392
11996 CsPbBr₃@MOF-5-Based Single Drop Microextraction for in-situ Fluorescence Colorimetric Detection of Dechlorination Reaction

Authors: Yanxue Shang, Jingbin Zeng

Abstract:

Chlorobenzene homologues (CBHs) are a category of environmental pollutants that can not be ignored. They can stay in the environment for a long period and are potentially carcinogenic. The traditional degradation method of CBHs is dechlorination followed by sample preparation and analysis. This is not only time-consuming and laborious, but the detection and analysis processes are used in conjunction with large-scale instruments. Therefore, this can not achieve rapid and low-cost detection. Compared with traditional sensing methods, colorimetric sensing is simpler and more convenient. In recent years, chromaticity sensors based on fluorescence have attracted more and more attention. Compared with sensing methods based on changes in fluorescence intensity, changes in color gradients are easier to recognize by the naked eye. Accordingly, this work proposes to use single drop microextraction (SDME) technology to solve the above problems. After the dechlorination reaction was completed, the organic droplet extracts Cl⁻ and realizes fluorescence colorimetric sensing at the same time. This method was integrated sample processing and visual in-situ detection, simplifying the detection process. As a fluorescence colorimetric sensor material, CsPbBr₃ was encapsulated in MOF-5 to construct CsPbBr₃@MOF-5 fluorescence colorimetric composite. Then the fluorescence colorimetric sensor was constructed by dispersing the composite in SDME organic droplets. When the Br⁻ in CsPbBr₃ exchanges with Cl⁻ produced by the dechlorination reactions, it is converted into CsPbCl₃. The fluorescence color of the single droplet of SDME will change from green to blue emission, thereby realizing visual observation. Therein, SDME can enhance the concentration and enrichment of Cl⁻ and instead of sample pretreatment. The fluorescence color change of CsPbBr₃@MOF-5 can replace the detection process of large-scale instruments to achieve real-time rapid detection. Due to the absorption ability of MOF-5, it can not only improve the stability of CsPbBr₃, but induce the adsorption of Cl⁻. Simultaneously, accelerate the exchange of Br- and Cl⁻ in CsPbBr₃ and the detection process of Cl⁻. The absorption process was verified by density functional theory (DFT) calculations. This method exhibits exceptional linearity for Cl⁻ in the range of 10⁻² - 10⁻⁶ M (10000 μM - 1 μM) with a limit of detection of 10⁻⁷ M. Whereafter, the dechlorination reactions of different kinds of CBHs were also carried out with this method, and all had satisfactory detection ability. Also verified the accuracy by gas chromatography (GC), and it was found that the SDME we developed in this work had high credibility. In summary, the in-situ visualization method of dechlorination reaction detection was a combination of sample processing and fluorescence colorimetric sensing. Thus, the strategy researched herein represents a promising method for the visual detection of dechlorination reactions and can be extended for applications in environments, chemical industries, and foods.

Keywords: chlorobenzene homologues, colorimetric sensor, metal halide perovskite, metal-organic frameworks, single drop microextraction

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11995 Isolated and Combined Effects of Multimedia Computer Assisted Coaching and Traditional Coaching on Motor Ability Component and Physiological Variables among Sports School Basketball Players

Authors: Biju Lukose

Abstract:

The objective of the study was to identify the isolated and combined effect of multi-media computer assisted coaching and traditional coaching on selected motor ability component and physiological variables among sports school basketball players. Forty male basketball players aged between 14 to 18 years were selected randomly. They were divided into four groups of three experimental and one control. Isolated multi-media computer assisted coaching, isolated traditional coaching and combined coaching (multimedia computer assisted coaching and traditional coaching) are the three experimental groups. All the three experimental groups were given coaching for 24 weeks and control group were not allowed to participate in any coaching programme. The subjects were tested dependent variables such as speed and cardio vascular endurance; at the beginning (pre-test) in middle 12 week (mid-test) and after the coaching 24 week (post-test). The coaching schedule was for a period of 24 weeks. The data were collected two days before and after the coaching schedule and mid test after the 12 weeks of the coaching schedule. The data were analysed by applying ANCOVA and Scheffe’s Post hoc test. The result showed that there were significant changes in dependent variables such as speed and cardio vascular endurance. The results of the study showed that combined coaching (multimedia computer assisted coaching and traditional coaching) is more superior to traditional coaching and multimedia computer assisted coaching groups and no significant change in speed in the case of isolated multimedia computer assisted coaching group.

Keywords: computer, computer-assisted coaching, multimedia coaching, traditional coaching

Procedia PDF Downloads 458
11994 Iterative Solver for Solving Large-Scale Frictional Contact Problems

Authors: Thierno Diop, Michel Fortin, Jean Deteix

Abstract:

Since the precise formulation of the elastic part is irrelevant for the description of the algorithm, we shall consider a generic case. In practice, however, we will have to deal with a non linear material (for instance a Mooney-Rivlin model). We are interested in solving a finite element approximation of the problem, leading to large-scale non linear discrete problems and, after linearization, to large linear systems and ultimately to calculations needing iterative methods. This also implies that penalty method, and therefore augmented Lagrangian method, are to be banned because of their negative effect on the condition number of the underlying discrete systems and thus on the convergence of iterative methods. This is in rupture to the mainstream of methods for contact in which augmented Lagrangian is the principal tool. We shall first present the problem and its discretization; this will lead us to describe a general solution algorithm relying on a preconditioner for saddle-point problems which we shall describe in some detail as it is not entirely standard. We will propose an iterative approach for solving three-dimensional frictional contact problems between elastic bodies, including contact with a rigid body, contact between two or more bodies and also self-contact.

Keywords: frictional contact, three-dimensional, large-scale, iterative method

Procedia PDF Downloads 210
11993 Vision Aided INS for Soft Landing

Authors: R. Sri Karthi Krishna, A. Saravana Kumar, Kesava Brahmaji, V. S. Vinoj

Abstract:

The lunar surface may contain rough and non-uniform terrain with dips and peaks. Soft-landing is a method of landing the lander on the lunar surface without any damage to the vehicle. This project focuses on finding a safe landing site for the vehicle by developing a method for the lateral velocity determination of the lunar lander. This is done by processing the real time images obtained by means of an on-board vision sensor. The hazard avoidance phase of the soft-landing starts when the vehicle is about 200 m above the lunar surface. Here, the lander has a very low velocity of about 10 cm/s:vertical and 5 m/s:horizontal. On the detection of a hazard the lander is navigated by controlling the vertical and lateral velocity. In order to find an appropriate landing site and to accordingly navigate, the lander image processing is performed continuously. The images are taken continuously until the landing site is determined, and the lander safely lands on the lunar surface. By integrating this vision-based navigation with the INS a better accuracy for the soft-landing of the lunar lander can be obtained.

Keywords: vision aided INS, image processing, lateral velocity estimation, materials engineering

Procedia PDF Downloads 466
11992 Challenges in Video Based Object Detection in Maritime Scenario Using Computer Vision

Authors: Dilip K. Prasad, C. Krishna Prasath, Deepu Rajan, Lily Rachmawati, Eshan Rajabally, Chai Quek

Abstract:

This paper discusses the technical challenges in maritime image processing and machine vision problems for video streams generated by cameras. Even well documented problems of horizon detection and registration of frames in a video are very challenging in maritime scenarios. More advanced problems of background subtraction and object detection in video streams are very challenging. Challenges arising from the dynamic nature of the background, unavailability of static cues, presence of small objects at distant backgrounds, illumination effects, all contribute to the challenges as discussed here.

Keywords: autonomous maritime vehicle, object detection, situation awareness, tracking

Procedia PDF Downloads 458
11991 Machine Learning and Deep Learning Approach for People Recognition and Tracking in Crowd for Safety Monitoring

Authors: A. Degale Desta, Cheng Jian

Abstract:

Deep learning application in computer vision is rapidly advancing, giving it the ability to monitor the public and quickly identify potentially anomalous behaviour from crowd scenes. Therefore, the purpose of the current work is to improve the performance of safety of people in crowd events from panic behaviour through introducing the innovative idea of Aggregation of Ensembles (AOE), which makes use of the pre-trained ConvNets and a pool of classifiers to find anomalies in video data with packed scenes. According to the theory of algorithms that applied K-means, KNN, CNN, SVD, and Faster-CNN, YOLOv5 architectures learn different levels of semantic representation from crowd videos; the proposed approach leverages an ensemble of various fine-tuned convolutional neural networks (CNN), allowing for the extraction of enriched feature sets. In addition to the above algorithms, a long short-term memory neural network to forecast future feature values and a handmade feature that takes into consideration the peculiarities of the crowd to understand human behavior. On well-known datasets of panic situations, experiments are run to assess the effectiveness and precision of the suggested method. Results reveal that, compared to state-of-the-art methodologies, the system produces better and more promising results in terms of accuracy and processing speed.

Keywords: action recognition, computer vision, crowd detecting and tracking, deep learning

Procedia PDF Downloads 161